Police are investigating the report of a suspicious approach to a child in Dungannon.
The PSNI said there was a report that a child was approached in the Windmill Court area of Dungannon on the evening of Thursday 26 January.
A PSNI spokesperson said: "It is reported that a man spoke with a six year old girl at approximately 9.30pm.
"A relation of the girl interrupted and took the girl to her home.
"The man is described as being over 6ft tall and was wearing a flat cap and glasses.
"He is thought to have been driving a small blue or black car.


This is a special invitation to participate in the Annual M.L.King Observance Day Association, Inc,"EXPRESS – SUCCESS" Saturday, February 16, 2019, 12:00-4:00 p.m., Bethlehem Baptist Church,1008 May Street, in the beautiful L.Scott Stell Fellowship Hall.
A day to showcase a wide variety of Savannah's Youth Talent, Education, and Career exhibits. We are inviting ALL VENDORS,- FREE OF CHARGE!,(one table and 2-chairs will be provided), table and chairs are limited, come and set up your table to allow the city of Savannah to see what you are offering.
The committee is currently seeking youth talent, ages up to 20 yrs. old ,spaces are limited.. To sign up as a vendor or for the Youth Talent Showcase, please call the M.L. King Observance Day Association, Inc. business office at 912-234-5502, Monday – Friday, 9:00 a.m. – 5:00 p.m., or www.mlksavannah.com.


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Introducing the 2020 Red Cross Class of Heroes: Detective Phil Hemmeler, Law Enforcement Hero
by Macaire Douglas May 12, 2020
When Detective Phil Hemmeler of the Palatine Police Department heard the radio call of a car that crashed into a building and caught fire, he jumped in to help, ultimately saving the driver's life. "The smoke was really starting to fill up in the car and I was trying to hold my breath, trying to give him voice commands like, 'hey, I want to get you out, it's on fire' and he wasn't responding," he told the Red Cross.
The fire had surrounded the driver and Detective Hemmeler could see the driver's feet burning. The flames were also spreading to the visor above the victim's head, burning his shoulders and head. He recalls thinking he needed to figure out a different way to get the injured driver out of the car. That is when he and other officers that had just arrived at the scene decided to use a tow strap procured by a manager of a near business.
Detective Hemmeler, with assistance from others at the scene, secured the tow strap to his squad car, a Chevy Tahoe, and to the vehicle on fire. After three attempts, he was able to pull the vehicle out. Now able to open the driver's side door, Detective Hemmeler tried to get the man out of the car but was met with resistance. "I couldn't get around him, I couldn't get in the car far enough to get the leverage to pull him out," he explained. He remembers trying to put the fire out as much as he could from around the man's face and head and using fire extinguishers until the fire department arrived on the scene. Firefighters were then able to pull the man out of the car with the help of special equipment.
In his nearly 14 years with the Palatine Police Department, Detective Hemmeler had never experienced a situation like the one he faced on June 7, 2019. Today, Detective Hemmeler is receiving the 2020 Red Cross Law Enforcement Hero award, sponsored by Motorola Solutions Foundation.
Later that day, back at the police station, Detective Hemmeler got in touch with the man's family. A few days later, while visiting the victim in the hospital, Phil had the opportunity to meet the man's son who shared how grateful he was that his dad had made it alive.
Since COVID-19, Detective Hemmeler's entire routine has changed. With extra health precautions in place, he continues to serve his community. "The public is providing tremendous support…and the Village of Palatine has gone above and beyond—dropping off gloves and masks…to keep everyone as safe as possible," he told the Red Cross.
Detective Hemmeler was to receive his award at the Red Cross of Illinois' annual Heroes Breakfast, which was cancelled because of coronavirus. We hope you are inspired by his story, and consider donating to the Red Cross at www.redcross.org/ChicagoHero. Right now, the impact of your gift will be doubled by a generous match.
Better is honored to be a sponsor of the Heroes Breakfast and to collaborate with the Red Cross to share the inspiring stories of all the 2020 Heroes too.
More from Better:
Honor the 2020 Red Cross "Extraordinary Heroes" and Double Your Impact
You Said It: Members of the Chicago Community Offer Hope During the Pandemic
From COVID-19 to Fashion: The Global Ripple Effect of Our Actions
ChicagoheroesphilanthropyRed Cross Heroes
Coronavirus in Chicago: Resources and Ways to Help Yourself and Others During the COVID-19 Outbreak
A Red Cross Hero's Words: 'I Am My Best Self in Situations Like These'
American Red Cross of Chicago & Northern Illinois Celebrates 15 Years of Community Heroes

redpajama_set_name: RedPajamaCommonCrawl


When Jag and Linda Cheema needed a family in their new hometown, New Mexico State University answered the call. When NMSU students needed a home away from home, the Cheemas dialed in. Now, the Jag and Linda Cheema Endowed Scholarship will create a way for student athletes to be their best, not only on the playing fields and courts but in the classroom as well.
Jag Cheema, a tennis player, picked up the phone and called NMSU to ask for a tennis partner.
The stories of NMSU students affected Jag and Linda in different ways. Jag, originally from India, felt a desire to help foreign students, the way he was helped as a student. Jag's family also had innate expectations of education and giving back. It was an example set by his grandfather, an Indian freedom fighter, who showed that it was their duty to take care of people who cannot take care of themselves.
Linda, a first-generation college student, wanted to pay tribute to a great uncle who helped her through school, even though he only had a third-grade education.
For years, the Cheemas' gifts were in the form of something intangible, but invaluable – being the community that NMSU students needed. Jag remembers the first time they got involved with the women's basketball team, spending time with the players after the game.
"When we couldn't afford to create scholarships, that's what we were doing instead – we were their biggest cheerleaders and doted on them," Linda said about how they welcomed the students into their home.
"And they need it," Jag agreed.
"I tell the parents who don't live in the area, I can get to your kid a lot quicker than you can," said Jag who remembered helping a student who needed knee surgery.
On a recent trip to Croatia, they met up with a former Aggie basketball player – one of the many former students whom they consider a daughter.
"We have two sons and four grandsons, but we have hundreds of daughters," Linda said. Their gift of time and devotion extended not only to their new daughters, but to the students' families as well.
When Jag and Linda sat down to consider giving a financial gift to NMSU, they decided to go with their core values.
The Cheemas took advantage of NMSU's Giving Tuesday initiative focused on raising dollars and participation. Some donations were even matched dollar-for-dollar, thanks to revenue from the NMSU license plate program and an estate gift from a generous donor.


Tritium Disposal with Safety | Self Luminous Exit Signs Co.
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Why tritium disposal need to be safe?
Tritium can cause environmental issues. Tritium disposal is necessary because even when the time span of a tritium self luminous light expires, a significant quantity of tritium remains left in the exit sign. Tritium disposal is the removal of this remaining tritium.
Tritium disposal services are provided by producers of tritium exit signs. You can attain free and safe tritium disposal service if you decide to buy a new tritium exit sign in return of tritium disposal. However, tritium disposal isn't too expensive and even if you are not willing to buy a new replacement, you can attain tritium disposal service at cheap cost.
While hazards related with unsafe tritium disposal are a serious concern, people realize the usefulness of tritium exit signs. You won't need electricity to use tritium exit sign and it will not fuse as easily as a bulb can. Thus tritium disposal and related fears fail to discourage people from buying tritium exit signs and tritium is also used in tritium hand watches. In case of watches too, it is necessary to remain alert about safe disposal of tritium. Precautions can help you to avoid any hazard caused by tritium. The United States Environment Protection Agency works under Clean Air Act to regulate tritium disposal laws to make it sure that tritium disposal is being done safely. The idea of offering free tritium disposal service for users willing to buy new tritium exit sign to replace the old one is also increasing the popularity of tritium self luminous exit signs and it is also successfully spreading awareness about safe tritium disposal in masses. There are alternatives that offer freedom from responsibility of safe tritium disposal such as the photo luminescent exit signs that requires no tritium disposal issue. However, tritium exit signs are relatively cheaper and durable and one will need to worry about tritium disposal only after a period of twelve and half years.
Why should you worry about tritium disposal?
Tritium in solid form is relatively harmless but in gaseous form, it can be lethal. To protect environment from ill effects of gaseous tritium, it is necessary to follow safe tritium disposal measures. Tritium is not a carcinogen and hence managed tritium disposal confirms that there will be no harm of using tritium exit signs. Opting for managed tritium disposal is free as you can take free tritium disposal service from the distributors of tritium exit signs for buying a new tritium exit sign which will again demand safe tritium disposal after twelve and half year.


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Finnair Debuts Via Spa at Helsinki
by airportxadmin | Dec 17, 2009 | News Flash |
Finnair, the national airline of Finland, has opened Via Spa as part of its new Via Lounge at Helsinki (HEL).
"The high quality Via Spa will offer Finnair customers first-class spa and wellness services," says Markku Remes, Finnair's customer experience development manager. "For instance, the spa will offer four different types of sauna. There will be a spruce sauna and a stone sauna from the Alps, a steam sauna and a traditional Finnish sauna, which actually provides a view over a mineral water pool to the airport's runways."
The spa's concept is based on German spa pioneer Paul Haslauer's ideology and research and offers naturopathic treatments; all products are organic. Shorter services are designed for transit passengers, and there is a cold-water paddling pool and a mineral water pool to help with travel fatigue and jetlag.
"A big step in the transformation of the Helsinki Airport terminal extension already took place in September when new shops opened their doors along with the 400-seat My City Helsinki restaurant world," says Michael Maass, Finnair's sales director for North America. "At the same time, we opened new departure gates and a seven-line security check area for arriving transit passengers."
The Via Spa and Via Lounge are at the end of the new Helsinki Airport terminal extension. The lounge has room for about 250 customers and includes six private shower rooms, a buffet, a Via Bar and relaxation areas. There is also free Wi-Fi, work stations outfitted with computers and multi-purpose facilities. Services are provided in cooperation with SSP Finland Oy.
The Via Lounge is open from 6 a.m. to midnight, and the Via Spa is open from 10 a.m. to 10 p.m.
Access to the Via Lounge is free for Finnair Business Class passengers and Finnair Plus Platinum/Gold/Silver card holders plus one guest, and to oneworld Emerald/Sapphire card holders plus one guest. Other customers who wish to use the facility are charged 45 euros per person.
The Via Spa offers free access for Finnair Plus Platinum card holders (no guests), and any customer wishing to use the service at a charge of 45 euros. Personal well-being treatments are available between noon and 8 p.m. for an additional charge.
ARN's Director Of The Year Chief Executive Officer, Dallas/Fort Worth International Jeffrey P. Fegan
ARN's Director Of The Year: Jeffrey P. Fegan, Chief Executive Officer Of Dallas/Fort Worth International


Where it was Made: Beetlejuice!
Welcome to another episode of our web-series, Where It Was Made, in which we revisit the actual filming locations for some of the most popular films ever made and see how they're holding up today, all while examining just how these locations were used in the finished film. Our latest episode heads to East Corinth, Vermont to revisit the locations of Tim Burton's classic tale of the Ghost with the Most, BEETLEJUICE, starring Michael Keaton, Winona Ryder, Alec Baldwin, Geena Davis, Catherine O'Hara and Jeffrey Jones!


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WWE Filming "WWE 24" Special On RAW 25, Seth Rollins' Ex-Girlfriend Now Single, Royal Rumble
Sting Cuts Promo For Imperial Wrestling (Video), Top 10 Royal Rumble Intruders, Sasha Banks
Laurel Van Ness On Herself, Bobby Lashley & EC3 Leaving Impact, Possibly Going To WWE
Nia Jax On Ronda Rousey To WWE, Surprise Entrants In Women's Royal Rumble Match
Kevin Owens Recalls Vince McMahon Cussing At Him Before Infamous Headbutt Segment
Dana White Confirms CM Punk Will Fight Again, Believes Brock Lesnar Will As Well
WWE Filming "WWE 24" Special On RAW 25, Seth Rollins' Ex-Girlfriend Now Single, Royal Rumble
Posted by Matt Boone January 20, 2018
- As WWE Royal Rumble 2018 continues to draw closer, WWE continues to offer past Royal Rumble matches for free via their official YouTube channel. Featured below is the WWE Royal Rumble 2012 match. WWE Royal Rumble 2018 goes down next Sunday, January 28th, at the Wells Fargo Center in…
- The latest edition of the WWE YouTube series, WWE Top 10, which you can check out below, takes a look at the top ten infamous Royal Rumble match intruders of all-time. - Sasha Banks is scheduled to make an appearance at the StubHub Store on 1412 Broadway in New…
Former Impact Wrestling Knockouts Champion Laurel Van Ness recently spoke with The Orlando Sentinel after confirming her release from the promotion earlier this week. Featured below are some of the highlights from the interview. On parting ways with Impact Wrestling: "It's stressful, it's crazy, it's exciting, all at once. ……
Nia Jax On Ronda Rousey To WWE, Surprise Entrants In Women's Royal Rumble Match
Nia Jax recently spoke with the folks from The Mirror to promote this month's joint-brand WWE Royal Rumble 2018 pay-per-view. Featured below are some of the highlights from the interview. On Kurt Angle picking her to win the first women's Royal Rumble match, and what she thinks her chances are:…
Former best friends reunited on a recent episode of Chris Jericho's "Talk Is Jericho" podcast. Kevin Owens and Sami Zayn appeared as a guest on Jericho's podcast and during the show, Owens spoke at great length about his memorable in-ring segment with Vince McMahon. Owens was asked about his segment…
As noted, Dana White spoke with TSN during Saturday's UFC Media Day in Boston and seemed to indicate interest in having both CM Punk and Brock Lesnar compete inside the Octagon. When given odds by the interviewer, White claimed that he would bet "Yes" on both competing at some point…
ROH TV Taping Lineup (1/20): Multiple Title Matches, Women Of Honor Opening Round Bouts
Ring Of Honor (ROH) returns to the Municipal Auditorium in Nashville, Tennessee for the latest set of ROH television tapings. Featured below is the scheduled lineup for tonight's set of tapings, which includes multiple ROH World Championship bouts, as well as the first round matches in the tournament to crown…
Natalya Addresses Rumors Of Paige Being Forced Into WWE Retirement
WWE Superstar Natalya recently spoke with Brian Fritz for an interview. During the discussion, the Total Divas cast member spoke about the possibility of Paige being forced into retirement due to injuries. Featured below are some of the highlights. On Paige's physical condition: "I don't know the particulars of exactly…
Stephanie McMahon On Her Favorite RAW Moment, RAW 25, Women's Royal Rumble
Stephanie McMahon recently spoke with the folks from The Mirror to promote this coming Monday night's WWE RAW 25th Anniversary special in New York. Featured below are some of the highlights from the interview. On what it means to be part of the WWE RAW 25th Anniversary special this coming…
Drew Gulak On This Weekend's First-Ever 205 Live House Shows, Enzo Amore & More
Drew Gulak recently spoke with ESPN to promote the first-ever 205 Live house shows this weekend. Featured below are some of the highlights from the interview. On his recent success as part of 205 Live: "It's been really surreal. I'm basically getting the chance to revisit old creative stuff that…
Fightful Select reports that former IMPACT Wrestling and WWE RAW Tag Team Champions The Good Brothers (Luke Gallows and Karl Anderson) of The O.C. have signed a five-year deal with WWE that will see them remain in the company until 2027. The Good Brothers have competed in promotions all around...
— Despite being scheduled for the match, Rey Mysterio never made it to Saturday's Royal Rumble with Dominik appearing with Rey's mask and ripping it up, implying that he (and the rest of Judgment Day) beat him up backstage, preventing him from being able to wrestle. — In actuality, according...
Two-time WWE Hall of Famer Booker T recently took to his "Hall Of Fame" podcast, where he spoke about a variety of topics such as what he thinks about the late Jay Briscoe. Booker T said: "I never met Jay Briscoe, but one thing, you can always tell a person's...
It was previously reported that pro wrestling legend Jay Briscoe passed away last Tuesday, January 17 due to a car accident. A tribute show would then be held for the 13-time ROH World Tag Team Champion, which was aired for free on ROH's Honor Club and the official ROH YouTube...
WWE Hall of Famer Mick Foley recently took to his "Foley Is Pod" podcast, where he spoke about topics such as if he feels like blood has a place in wrestling. Mick Foley said: "I always felt like [blood] had a place. I've been around when it was overused, I've...
All Elite Wrestling previously announced that this Wednesday night's episode of AEW Dynamite will see AEW TNT Champion Darby Allin defend his title against Samoa Joe in a No Holds Barred Match, "Hangman" Adam Page battle Jon Moxley in a Singles Match, Timothy Thatcher take on Bryan Danielson in a...
Seth "Freakin" Rollins, who is one of the biggest stars not only in the WWE, but in all of wrestling, is the latest person who wants nothing to do with former AEW and WWE Champion CM Punk. Seth, who is a former 2-time WWE Champion as well as a former...


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Mapping the Disproportionate Threat of Policing to NYC's Commercial Cyclists
By David Meyer
Policing of delivery cyclists is concentrated in a few Manhattan neighborhoods, while non-commercial infractions are most prevalent in some of NYC's poorest areas. Image: Biking Public Project
Immigrant cyclists in NYC are disproportionately policed in the neighborhoods where they work and live, according to a recently-released analysis of NYPD cycling infraction data by the Biking Public Project.
From 2007 to 2015, 92 percent of commercial cycling tickets were issued in just four Manhattan precincts, covering the Upper East Side, Upper West Side, and parts of Midtown — areas whose populations are 75 percent white. Meanwhile, non-commercial infractions were most heavily concentrated in precincts with high levels of poverty and majority-minority populations.
Image: Biking Public Project
The severely disproportionate policing of commercial cyclists by those four Manhattan precincts — the 17th (Midtown East), 18th (Midtown North), 19th (Upper East Side), and 20th (Upper East Side) holds true when controlling for the large number of restaurants in those areas.
In Midtown East, for example, 291 commercial cycling summonses were issued annually for every 100 restaurants. In comparison, the 88th Precinct in Fort Greene and Clinton Hill issued just .37 tickets per year per 100 restaurants.
The top eight precincts for commercial cycling infractions per 100 restaurants are all in Manhattan. "The commercial cycling infractions are all happening in affluent, white neighborhoods," Biking Public's Do Lee told Streetsblog. "Most [commercial cyclists] tend to be Asian and Latino immigrant workers."
At the same time, all but two of the top 10 police precincts for non-commercial cycling summonses are in majority-minority neighborhoods. You can toggle between the commercial and non-commercial bike enforcement datasets on this map:
"Given that most working cyclists in NYC are food delivery workers who tend to be Latino and Asian immigrants," concludes Lee in a recent summary of the research, "this map means that in NYC, people of color who bike have been policed both where they live and where they work."
Public conversations about cycling in the neighborhoods with heavy commercial bike enforcement tend to single out delivery cyclists. On the Upper East Side, for example, residents often complain about delivery cyclists in public forums about cycling and bike infrastructure. In response, Council Member Ben Kallos and the 19th Precinct have held "bike safety workshops" and promoted ticketing blitzes implicitly targeted at delivery workers.
The Biking Public Project took interest in the NYPD data after Chinese delivery workers indicated in a focus group that interactions with police were one of their primary concerns. Workers often have to choose between breaking the law and their livelihood, which depends on fast service and good tips.
Making matters more difficult, many delivery workers speak limited English, so they often don't know what they're being charged with until they get to court.
Lee notes that the number of criminal court summonses for commercial and non-commercial cycling infractions has dropped in recent years. But the data is incomplete: NYPD has not made data for non-criminal traffic summonses available to the public. The traffic violation data that is available does not differentiate between motorists and cyclists.
Lee warns that the media attention and public complaints about delivery cyclists, coupled with the reflective vests they are required by law to wear, continues to put them in an especially vulnerable position.
"This question of policing immigrant food delivery cyclists takes on particular meaning with Trump's promise to accelerate the deportation of undocumented residents," Lee writes. "While the level of criminal summonses for commercial cycling has dropped, the laws and tools remain in place and can be revived at any given time."
Filed Under: Bicycling, NYPD, Promoted
When Media Outlets Cover Delivery Cyclists, They Rarely Talk to Them
By David Meyer	| Jul 29, 2016
NYC's mostly-immigrant food delivery cyclists don't have it easy, working on car-centric streets through all sorts of weather, all while under pressure to make their deliveries as quickly as possible. But media coverage of delivery cyclists tends to dehumanize them, failing to convey their perspective or consider the difficult working conditions they contend with. That's the conclusion […]
Drivers Are Killing People, and the 19th Precinct Is Sending Cyclists to Court
By Brad Aaron	| Jun 16, 2016
Police activity on 79th & 1st–a blitz of enforcement on cyclists https://t.co/KSOdmtUHvp pic.twitter.com/1HO3zaGUwm — Our Town (@OurTownNYC) June 1, 2016 The 19th Precinct likes to boast about local officers aggressively ticketing people for riding bikes on sidewalks. A data analysis by Transportation Alternatives shows the precinct also issues far more criminal court summonses for sidewalk riding than […]
Shameful Scenes From de Blasio's Crackdown on Delivery Workers Who Use Electric Bikes
As NYPD boasts about confiscating bikes from people trying to support themselves and their families, cyclists continue to face the real mortal threat on NYC streets.
The Upper East Side Can Still Deliver an Old-Fashioned Bike Lane Kvetchfest
True to form, last night's Upper East Side community board meeting about bike lanes was a ridiculous carnival of vituperative whining.
NYPD in Default Victim-Blaming Mode After Yellow Cab Driver Kills Cyclist in Chinatown
NYC motorists killed four people riding bikes over a 15-day period in June and July. In every case, NYPD said the victim ran a red while citing no corroborative evidence.
How NYPD's Opaque Crash Investigations Spoil Its Street Safety Message
By Stephen Miller	| Feb 6, 2014
Last month, the Upper East Side's 19th Precinct devoted two full pages to traffic safety in its inaugural monthly newsletter. In an echo of Police Commissioner Bill Bratton, who claimed at the initial Vision Zero press conference that 73 percent of crashes injuring pedestrians are the victim's fault, it featured an eyebrow-raising statistic that blames […]


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Children and the trauma of immigration
Tags: immigration, Children
Immigrant children have become the collateral damage of the Trump administration's Zero Tolerance policies aimed at their parents, as well as "bargaining chips" in the administration's negotiations with Congress. In addition, our current administration probably hopes that its disdainful treatment of children at the border will be a deterrent to Central American families contemplating life in the U.S.
Unfortunately, the violence and poverty in Guatemala, Honduras and El Salvador is making families sufficiently desperate to underestimate the hardships of travel north by bus, truck or on foot; the trauma of crossing our southern border without papers; and the heartbreak of separation from their children during detention, including the possibility of their disappearance or even death.
Recently, I met a couple in their 20s who had just arrived from Guatemala with two little preschool girls. We were in the office of a social worker, to whom they had come for help in obtaining medical care for the mother and a lawyer to represent them at court hearings in fall. If their story seemed free of the worst disasters, they had certainly had opportunities for trauma.
Knowing virtually no English, the parents described in Spanish their crossing of the Rio Grande on inner tubes, each holding one child. Somehow they had lost track of each other as they entered U.S. territory. Encountering the border patrol, without proper documents, the parents were arrested separately and given different dates to appear in immigration court. Still, unable to find, or even communicate with each other, but knowing the address of a family member in Connecticut, the husband and wife separately made their way north, each traveling with one child, and were miraculously reunited at the home of this family member.
The little girls were pretty but frail in their fresh white blouses. They quietly occupied themselves with crayons and paper the social worker had given them, making no demands on the adults in the room. When would they be able to tell their own stories? Would their words be Spanish or in English, a language they did not yet know? In the meantime, their little bodies would hold their silent fears.
According to the National Child Traumatic Stress Network (www.nctsn.org), children may be traumatized when they fear for their lives, believe they might be injured, witness violence, experience a sudden and drastic separation from a loved one, or simply become refugees.
The parents had said little about why they had left everything to come to the U.S., and their immigration experience, as they told it, seemed comparatively benign: No one had spent significant time in detention, and both children had apparently remained with one parent. Nevertheless, crossing the Rio Grande in an inner tube, losing a parent and a sibling, and encountering the border patrol, had all been potentially traumatizing for the little girls. Moreover, although the family's life was relatively stable for the time being, the little girls might well be re-traumatized this coming fall, when one by one, two months apart, their parents would be called before an immigration judge. Without an attorney with a well-developed argument that the family needs asylum, which the family was unlikely to afford, one or both parents might well leave court with a deportation order; the family would likely be separated, or everyone would suddenly be back in Guatemala.
The six tragic deaths of immigrant children while in detention shocked our nation. But the problem with federal policies that ignore the fragility of children goes far beyond the latest policy of holding children in detention with nothing to do because recreation and schooling are being eliminated to save money. Long after a traumatic experience, childhood survivors may suffer from emotional upset, depression, difficulties with self-regulation, inattention, academic difficulties, and trouble sleeping and eating. Childhood survivors are also more likely to have long-term health problems, to use health and mental health services, and to be involved with the child welfare and juvenile justice systems.
These are heartbreaking costs to the families who gave up their homeland for a better life — and they are costs that our country, which will become home to some of these immigrants, has not begun to consider.


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Blog | Academic & Government
A journal is as a journal does: Four emergent properties of journals in scholarly communication
Marie McVeigh
Head of Editorial Integrity, Clarivate
For 350 years, the scholarly journal has played a role in the communication of research. More recently, with millions of articles readily searchable and with preprints servers extending across many topics, some aspects of this communications role are being met by other products. Discovery often takes place on or through aggregators, and distribution of research can precede publication in a journal. Nonetheless, the journal occupies a unique level of organization between the articles and platforms of articles, and most of the important properties of journals exist solely at the level of the journal as an organic whole: not just a collection of papers, but a system of content and collaborations.
In 1999, the economist Jeffrey Goldstein described emergence as "the arising of novel and coherent structures, patterns, and properties during the process of self-organization in complex systems."[1] Journals are self-organizing systems in that they arise not as the sole creation of an individual author or individual editor, but as the result of dynamic, independent actions of many stakeholders and groups of stakeholders. Authors, reviewers, editorial boards, editors, publishers, and readers all participate in the development of a journal as a whole. Journals are created and maintained by a set of collaborative processes through which content is submitted, evaluated, improved, selected, produced, distributed, discovered, and consumed. Journals have properties that are not present or predictable within the individual articles and that are not easily replicated in more generalized structures such as platforms or databases.
Particular features that arise solely at the journal level and underlie their contribution to the scholarly communications system are described below, both as features of the journal and in terms of how they arise from the work of participating stakeholders.
"The Red Journal" is a familiar entity to researchers in gastroenterology, though the title on the spine is American Journal of Gastroenterology. The sans serif font of the Cell Press journals was iconic through the journal's early years, making even isolated copies of articles immediately identifiable. Medical professionals and researchers know where to find a Case Record of Massachusetts General Hospital (New England Journal of Medicine) and, if they know that, they are likely to know that is different from a Clinical Challenge (JAMA-Journal of the American Medical Association) and a Clinical Picture (The Lancet).
Scope, type of materials published, the idiosyncratic names of sections, the familiar layout for the table of contents, the design and navigation of the journal's website, the title, and logo are all non-quality features of a journal's being recognizable, of its "character." Increasingly, the business and publication model (OA or subscription, continuous publication or regularized issues), author and editor diversity, and other features of a journal's operations, such as peer review model and time to publication, also contribute to the perceived character of a publication.
Character both defines and is defined by the communications goals of the journal. Society-managed journals may include non-research, non-scholarly materials that support the organization's mission or vision like community engagement, public policy in support of research, continuing education, the broader benefit of society, and development of the professional network of its members. Journals targeted to practitioners (as opposed to academic researchers) may include more descriptive or educational works. Even journals that publish mostly or exclusively research content have character through their reputation, brand, and perspective on the topic of study.
Character arises collaboratively through the interactions between the publisher, editor, and editorial board. They determine the vision for the journal and anticipate its contribution to the topic or fulfillment of a community's needs. They set the guidelines for sections and the goals for the publication and the market. They determine the tone of communications within and around the operation of the journal. An influential, recognizable editor may play an outsized role in defining the journal's character; nevertheless, many journals replace or rotate editorial responsibility regularly and successfully. A robust and well-managed journal benefits from its editorial team and also survives changes in leadership. Some features of how character is created are primarily influenced by the publisher,[2] but this is seldom entirely independent of the academic editorial board.
At the journal level, content is defined by the process of curation and the effects of this curation on the materials published.
Content does not begin and end with the articles published. Rather, the content of a journal begins with the articles submitted, since these are necessarily the raw materials from which the journal selects. While content can be requested or even commissioned, it is a struggle for new journals to establish a pipeline of appropriate submissions. Every journal must work with what independent authors decide to submit for consideration.
Content as a property at the journal level, also includes the steps by which submitted articles are developed through peer and editorial review. Surveys have consistently shown that authors believe their work has been improved in quality through the process of peer review[3]. Further, a recent study showed that the more rounds of review an article has completed, the higher its later citation profile[4]. While these reports cannot be taken as a de facto demonstration of increased article quality, they do indicate that peer review represents an active engagement around content among several parties; author(s), reviewer(s), editor(s), and often the publisher manage and administer the system.
Finally, editorial selection sets an overall direction for the journal. In addition to the evaluation of quality of an individual item, content decisions reflect what the decision maker values in the field – the topics and types of research that are important.
An operational definition of content has two additional features when considered at the journal level: intellectual synergy and reputational effect. Attracting articles on a topic, subjecting them to review and curation, and co-presenting them allows related articles to contribute to each other's discoverability and interest. A slightly different manifestation of that phenomenon is demonstrated in the fact that identical articles published in two different journals will show citation rates that correlate to the citation performance of the journal.[5]. Whether this effect is attributable to reputation (see "Character," above), distribution (see "Community," below), it means that the article operates differently when presented in the context of a different journal. A journal adds a layer of meaning to the content it has brought together.
Content expands the contributors to a journal beyond those who are committed to the success of the journal itself. From publisher-editor-editorial board, content extends the system of a journal to authors who submit to the journal and to other journals and to reviewers who participate in article development, selection, and rejection for the journal and for other journals.
As a property of journals, community can be defined as how a journal creates a nexus for a scholarly dialog, not only among the authors, reviewers, and editors, but also the topic's scholarly community of specialists or general-interest readers.
Like character, community is anchored in the journal's scholarly communication goals. The journal's successful creation of its intended community is not entirely determined by its management, but also by the self-organization of an interested group of participants who read and use the journal. Journals affiliated with scholarly societies may have some advantage in their access to a membership community. Journals affiliated with large publishers may have the advantage of expansive and experienced marketing and distribution networks. However, independent journals in a specialized topic also have a community dynamic based on the network of existing scholarly interactions on and around the subject itself. This, in fact, is the most basic type of community as a property of journals.
A more subtle aspect of the community around and within a journal include the developed sense of trust that readers have in the type, quality, and editorial direction of the materials they expect to find in a journal—the trust of the authors that their article is reaching its intended audience.
A final property of journals that emerges systemically is continuity. Journals are not static entities, but are constantly evolving. Like a "Ship of Theseus,"[6] a journal possesses an ongoing identity despite the continual replacement of its components. A journal is not one article, or one issue, or one volume, therefore it is possible to consider a journal across time in a way that makes less sense for the more stable properties of an individual article. A journal's continuity, across years, allows it to develop properties of character, content, and community as an entity in its own right.
To disarticulate a journal into a tabulation of articles destroys something essential and meaningful about the journal as a complex system comprising the work and the vision of an editor and publisher; the contribution and collaboration of reviewers and authors; the participation of readers who cite the journal; and the interest of readers whose use is reflected in practice, knowledge, or insight. Articles, curated and collected into a journal, absorb some of the properties of the journal. A journal known for outstanding editorial oversight, commitment to developmental review, and an engaged community of authors and readers will benefit from the reputation of the journal. Similarly, the journal is dependent on the continued excellence of both editorial activities and article quality to maintain this reputation.
The system of articles in journals has been a critical part of how knowledge has been advanced and shared in all fields of study. While the value of an article cannot be fully implied by the journal that publishes it; neither can the value of a journal be fully implied by any one article it published. Each exists as a specific level of organization in the complex system of scholarly communication, and has an important role to play.
[1] Jeffrey Goldstein (1999) Emergence as a Construct: History and Issues, Emergence, 1:1, 49-72, DOI: 10.1207/s15327000em0101_4
[2] See items 3, 6, 39, and 40, in a recent Scholarly Kitchen post: https://scholarlykitchen.sspnet.org/2018/02/06/focusing-value-102-things-journal-publishers-2018-update/ )
[3] https://authorservices.taylorandfrancis.com/peer-review-global-view/
[4] Rigby, J., Cox, D. & Julian, K. Scientometrics (2018) 114: 1087. https://doi.org/10.1007/s11192-017-2630-5
[5] Tobias Opthof (1997). Sense and nonsense about the Journal Impact Factor. Cardiovascular Research, 33 (1):1–7, DOI: 10.1016/S0008-6363(96)00215-5
[6] https://en.wikipedia.org/wiki/Ship_of_Theseus
JCR 2018 Journals Scholarly Publishing Scientific and Academic Research Web Of Science
Innovating to improve research integrity
Dr Nandita Quaderi
Editor-in-Chief and Editorial VP of the Web of Science


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City Councilman Scott Griggs confirmed today that the developer buying the site of El Corazon de Tejas restaurant is planning to demolish it and build a CVS store.
The restaurant on West Davis at Beckley is closing Sunday, and we reported two weeks ago that a CVS developer was making plans for the location. A demolition permit already has been issued for the building.
I spoke with Jason Price of Orange Development about El Corazon. Mr. Price indicated that a CVS is planned for the site and his group has completed the design and plans for the CVS.
Mr. Price implied the contract of sale was already signed or imminent and the demolition of the building would be occurring very soon.
I indicated my disappointment that the building wasn't being saved. Mr. Price stated that the building has no historic significance. I also indicated my disappointment that Oak Cliff isn't given the opportunity to to collaborate on the design. Mr. Price had no comment.
Mr. Price also indicated that he has been lurking on my Facebook page and reading my posts.
Please come to Oak Cliff and meet our great people. I believe you and CVS can work with our community to save the building and put a wonderful CVS in the building. Can we at least try?
Another CVS? I suppose it was that or Dollar General.


text:
\section{Introduction}

Support vector machines are amongst the most widely used machine learning techniques today. The classical SVM \citep{L1svm} has evolved into a multitude of diverse formulations with different properties. The most commonly used variants are the maximum margin $L_1$ norm SVM \citep{L1svm}, and the least squares SVM (LSSVM) \citep{suykens1999least}, both of which require the solution of a quadratic programming problem. In the last few years, SVMs have been applied to a number of applications to obtain cutting edge performance; novel uses have also been devised, where their utility has been amply demonstrated \citep{Yang201477, Ding20143, Wu201498, Li201331, Wu2014119, Wenjian2013116, Peng2013134, Jalalian2013270, Peng2013486, Huang2013118, Gomes20123, Ni2014127, Peng2013197, Yin2014224, LópezChau2013198, Kumar2014271, Ruano2014273, Liu201397, Zhao2013225, Ji2014281, Zhao20121, Sun2014111}. SVMs were motivated by the celebrated work of Vapnik and his colleagues on generalization, and the complexity of learning. It is well known the capacity of a learning machine can be measured by its Vapnik-Chervonenkis (VC) dimension. The VC dimension can be used to estimate a probabilistic upper bound on the test set error of a classifier. A small VC dimension leads to good generalization and low error rates on test data.\\

In his widely read tutorial, Burges \citep{burges1998} states that SVMs can have a very large VC dimension, and that \textit{``at present there exists no theory which shows that good generalization performance is guaranteed for SVMs''}. This paper shows how to learn a classifier with large margin, by minimizing an exact (\boldmath{$\Theta$}) bound on the VC dimension. In other words, the proposed objective linearly bounds the VC dimension from both above and below. We show that this leads to a simple linear programming problem. This approach is generic, and it suggests numerous variants that can be derived from it - as has been done for SVMs. Experimental results provided in the sequel show that the proposed Minimal Complexity Machine outperforms conventional SVMs in terms of test set accuracy, while often using far fewer support vectors. That the approach minimizes the machine capacity may be guaged from the fact that on many datasets, the MCM yields better test set accuracy while using less than $\frac{1}{10}$-th the number of support vectors obtained by SVMs.

The motivation for the MCM originates from some sterling work on generalization \citep{shawe1996framework, shawetaylor98, vapnik98, scholkopf2002learning}. We restrict our attention in this paper to a given binary classification dataset for which a hyperplane classifier needs to be learnt. Consider such a binary classification problem with data points $x^i, i = 1, 2, ..., M$, and where samples of class +1 and -1 are associated with labels $y_i = 1$ and $y_i = -1$, respectively. We assume that the dimension of the input samples is $n$, i.e. $x^i = (x_1^i, x_2^i, ..., x_n^i)^T$. For the set of all gap tolerant hyperplane classifiers with margin $d \geq d_{min}$, Vapnik \citep{vapnik98} showed that the VC dimension $\gamma$ is bounded by
\begin{equation}\label{eqnh}
\gamma \leq 1 + \operatorname{Min}(\frac{R^2}{d^2_{min}}, n)
\end{equation}
where $R$ denotes the radius of the smallest sphere enclosing all the training samples. Burges, in \citep{burges1998}, stated that \textit{``the above arguments strongly suggest that algorithms that minimize $\frac{R^2}{d^2}$ can be expected to give better generalization performance. Further evidence for this is found in the following theorem of (Vapnik, 1998), which we quote without proof''}. We follow this line of argument and show, through a constructive result, that this is indeed the case.\\

The remainder of this paper is organized as follows. Section \ref{linmcm} outlines the proposed optimization problem for a linear hyperplane classfier in the input space. Section \ref{kmcm} discusses the extension of the Minimum Complexity Machine to the kernel case. Section \ref{experimental} is devoted to a discussion of results obtained on selected benchmark datasets. Section \ref{conclusion} contains concluding remarks. In Appendix \ref{appendix1}, we derive an exact bound for the VC dimension of a hyperplane classifier. Appendix \ref{appendix2} deals with the formulation of the hard margin MCM.

\section{The Linear Minimal Complexity Machine} \label{linmcm}
We first consider the case of a linearly separable dataset. By definition, there exists a hyperplane that can classify these points with zero error. Let the separating hyperplane be given by
\begin{equation}
 u^Tx + v = 0.
\end{equation}

Let us denote
\begin{gather}
 h = \frac{\operatorname*{Max}_{i = 1, 2, ..., M} \|u^T x^i + v\|}{\operatorname*{Min}_{i = 1, 2, ..., M} \|u^T x^i + v\|}.
\end{gather}
In Appendix \ref{appendix1}, we show that $h$ may also be written as
\begin{gather}
 h = \frac{\operatorname*{Max}_{i = 1, 2, ..., M} \;y_i(u^T x^i + v)}{\operatorname*{Min}_{i = 1, 2, ..., M} \;y_i(u^T x^i + v)},
\end{gather}
and we show that there exist constants $\alpha, \beta > 0$, $\alpha, \beta \in \Re$ such that
\begin{equation}\label{exactbound}
 \alpha h^2 \leq \gamma \leq \beta h^2,
\end{equation}
or, in other words, $h^2$ constitutes a tight or exact ($\theta$) bound on the VC dimension $\gamma$. An exact bound implies that $h^2$ and $\gamma$ are close to each other.\\

 Therefore, the machine capacity can be minimized by keeping $h^2$ as small as possible. Since the square function $(\cdot)^2$ is monotonically increasing, we can minimize $h$ instead of $h^2$. We now formulate an optimization problem that tries to find the classifier with smallest machine capacity that classifies all training points of the linearly separable dataset correctly; this problem is given by

\begin{equation}\label{minh1}
\operatorname*{Minimize  }_{u, v} \; h ~=~ \frac{\operatorname*{Max}_{i = 1, 2, ..., M} \; y_i(u^T x^i + v)}{\operatorname*{Min}_{i = 1, 2, ..., M} \; y_i(u^T x^i + v)}
\end{equation}

Note that in deriving the exact bound in Appendix \ref{appendix1}, we assumed that the separating hyperplane $u^Tx + v = 0$ correctly separates the linearly separable training points; consequently, no other constraints are present in the optimization problem (\ref{minh1}).\\

In Appendix \ref{appendix2}, we show that the optimization problem (\ref{minh1}) may be reduced to the problem
\begin{gather}
\operatorname*{Min}_{w, b, h} ~~h \label{objm4}\\
h \geq y_i \cdot [{w^T x^i + b}], ~i = 1, 2, ..., M \label{consm41}\\
y_i \cdot [{w^T x^i + b}] \geq 1, ~i = 1, 2, ..., M, \label{consm42}
\end{gather}
where $w \in \Re^n$, and $b, h \in \Re$. We refer to the problem (\ref{objm4}) - (\ref{consm42}) as the hard margin Linear Minimum Complexity Machine (Linear MCM). \\

Note that the variable $h$ in (\ref{objm4}) and that in (\ref{exactbound}) refer to the same functional. By minimizing $h$ in (\ref{objm4}), we are minimizing an exact bound on $\gamma$, the VC dimension of the classifier. Once $w$ and $b$ have been determined by solving (\ref{objm4})-(\ref{consm42}), the class of a test sample $x$ may be determined from the sign of the discriminant function
\begin{equation}\label{testresult}
 f(x) = w^T x + b
\end{equation}

In general, datasets will not be linearly separable. The soft margin equivalent of the MCM is obtained by introducing additional slack variables, and is given by
\begin{gather}
\operatorname*{Min}_{w, b, h} ~~h + C \cdot \sum_{i = 1}^M q_i \label{obj5}\\
h \geq y_i \cdot [{w^T x^i + b}] + q_i, ~i = 1, 2, ..., M \label{cons51}\\
y_i \cdot [{w^T x^i + b}] + q_i \geq 1, ~i = 1, 2, ..., M \label{cons52} \\
q_i \geq 0, ~i = 1, 2, ..., M. \label{cons53}
\end{gather}
Here, the choice of $C$ allows a tradeoff between the complexity (machine capacity) of the classifier and the classification error.\\

Once $w$ and $b$ have been determined, the class of a test sample $x$ may be determined as before by using the sign of $f(x)$ in (\ref{testresult}). In the sequel, we show how to extend the idea to nonlinearly separable datasets.

\section{The Kernel MCM}\label{kmcm}
We consider a map $\phi(x)$ that maps the input samples from $\Re^n$ to $\Re^l$, where $l > n$. The separating hyperplane in the image space is  given by

\begin{equation}
 u^T \phi(x) + v = 0.
\end{equation}

Following (\ref{obj5}) - (\ref{cons52}), the corresponding optimization problem for the kernel MCM may be shown to be

\begin{gather}
\operatorname*{Min}_{w, b, h, q} \; h + C \cdot \sum_{i = 1}^M q_i \label{objk6}\\
h \geq y_i \cdot [{w^T \phi(x^i) + b}] + q_i, ~i = 1, 2, ..., M \\
y_i \cdot [{w^T \phi(x^i) + b}] + q_i \geq 1, ~i = 1, 2, ..., M \label{consk61} \\
q_i \geq 0, ~i = 1, 2, ..., M.
\end{gather}

The image vectors $\phi(x^i), i = 1, 2, ..., M$ form an overcomplete basis in the empirical feature space, in which $w$ also lies. Hence, we can write
\begin{equation}\label{weqsumlambda}
 w = \sum_{j = 1}^M \lambda_j \phi(x^j).
\end{equation}

Therefore,
\begin{gather}\label{simpliphi}
 w^T \phi(x^i) + b = \sum_{j = 1}^M \lambda_j \phi(x^j)^T\phi(x^i) + b = \sum_{j = 1}^M \lambda_j K(x^i, x^j) + b,
\end{gather}

where $K(p, q)$ denotes the Kernel function with input vectors $p$ and $q$, and is defined as
\begin{equation}
 K(p, q) = \phi(p)^T \phi(q).
\end{equation}\label{kernel}

Substituting from (\ref{simpliphi}) into (\ref{objk6}) - (\ref{consk61}), we obtain the following optimization problem.
\begin{gather}
\operatorname*{Min}_{w, b, h, q} \; h + C \cdot \sum_{i = 1}^M q_i \label{objk7}\\
h \geq y_i \cdot [\sum_{j = 1}^M \lambda_j K(x^i, x^j) + b] + q_i, ~i = 1, 2, ..., M\\
y_i \cdot [\sum_{j = 1}^M \lambda_j K(x^i, x^j) + b] + q_i \geq 1, ~i = 1, 2, ..., M \\ \label{consk71}
q_i \geq 0, ~i = 1, 2, ..., M.
\end{gather}

Once the variables $\lambda_j, j = 1, 2, ..., M$ and $b$ are obtained, the class of a test point $x$ can be determined by evaluating the sign of
\begin{equation}
f(x) ~=~ w^T \phi(x) + b ~=~ \sum_{j = 1}^M \lambda_j K(x, x^j) + b.
\end{equation}\label{testval}

Note that in (\ref{weqsumlambda}), the $\phi(x^j)$'s for which the corresponding $\lambda_j$'s are non-zero constitute the support of the vector $w$. Hence, $\phi(x^j)$'s for which the $\lambda_j$'s are non-zero may be termed as support vectors. The maximum number of support vectors is the number of training samples $M$, as in the case of the SVM.

\section{Experimental results}\label{experimental}
The MCM was coded in MATLAB \citep{matlab}. Figure \ref{matlabmcm} provides a flowchart illustrating the MCM implementation; as may be seen, we use the \textit{linprog} function in MATLAB to solve the optimization problem comprising the MCM.

\begin{figure}[hbtp]
        \centering
                \includegraphics[scale=0.5]{matlabmcm.eps}
                \caption{Illustration of the MATLAB flowchart for the MCM code.}
                \label{matlabmcm}
\end{figure}

In order to compare the MCM with SVMs, we chose a number of benchmark datasets from the UCI machine learning repository \citep{uciml}. Table \ref{tabledatasets} summarizes information about the number of samples and features of each dataset. Some of the benchmark datasets are multi-class ones. These have been learnt by adopting a one-versus-rest approach. Accuracies, CPU times, and the number of support vectors have been averaged across all the classifiers learnt in a one-versus-rest approach.

\begin{table}[htbp]
  \centering
\caption{Characteristics of the Benchmark Datasets used}
     \begin{tabular}{cc}
    \toprule
    dataset & Size (samples $\times$ features $\times$ classes) \\
    \midrule
          &  \\
    blogger & 100 $\times$ 6 $\times$ 2 \\
    fertility diagnosis & 100 $\times$ 9 $\times$ 2 \\
    promoters  & 106 $\times$ 57 $\times$ 2 \\
    echocardiogram  & 132 $\times$ 12 $\times$ 2 \\
    teaching assistant & 151 $\times$ 5 $\times$ 3 \\
    hepatitis  & 155 $\times$ 19 $\times$ 2 \\
    hayes & 160 $\times$ 5 $\times$ 3 \\
    plrx  & 182 $\times$ 12 $\times$ 2 \\
    seed  & 210 $\times$ 7 $\times$ 3 \\
    glass & 214 $\times$ 10 $\times$ 6 \\
    heartstatlog  & 270 $\times$ 13 $\times$ 2 \\
    horsecolic  & 300 $\times$ 27 $\times$ 2 \\
    haberman  & 306 $\times$ 3 $\times$ 2 \\
    ecoli & 336 $\times$ 8 $\times$ 3 \\
    house voters & 435 $\times$ 16 $\times$ 2 \\
    wholesale customer & 440 $\times$ 8 $\times$ 2 \\
    IPLD  & 583 $\times$ 10 $\times$ 2 \\
    balance & 625 $\times$ 4 $\times$ 3 \\
    australian  & 690 $\times$ 14 $\times$ 2 \\
    crx   & 690 $\times$ 15 $\times$ 2 \\
    transfusion  & 748 $\times$ 5 $\times$ 2 \\
    tic tac toe & 958 $\times$ 9 $\times$ 2 \\
    sorlie & 85 $\times$ 456 $\times$ 2 \\
    secom & 1567 $\times$ 591 $\times$ 2 \\
    tian   & 173 $\times$ 12626 $\times$ 2 \\
    \bottomrule
    \end{tabular}%
  \label{tabledatasets}%
\end{table}%

Table \ref{table1} summarizes five fold cross validation results of the linear MCM on the datasets listed in Table \ref{tabledatasets}. Accuracies are indicated as mean $\pm$ standard deviation, computed over the five folds. The table compares the linear MCM with the SVM using a linear kernel. Note that the MCM solves the primal problem and not the dual. The linear SVM is solved using the dual, by using a linear kernel. This is done because the SVM primal is numerically less attractive owing to the ill conditioning of the Hessian. Hence, there is a subtle difference between a linear MCM and a SVM (linear kernel). The values of $C$ were determined for the MCM by performing a grid search. The table also provides a comparison between the CPU times taken by the SVM and the MCM. For the implementation of the SVM, we use a small MATLAB code that solves the quadratic programming dual form of the classical $L_1$ norm SVM by calling the \textit{quadprog} command in MATLAB. This has been done to enable a comparison of the CPU times taken by the MCM and the SVM. Faster implementations based on active set methods are possible for the MCM; such methods exist for the SVM and include Platt's SMO \citep{plattsmo} and the 1SMO algorithm \citep{jdsumt2012}.

\begin{table}[htbp]
  \centering
  \caption{Linear MCM Results}
  \begin{threeparttable}
    \begin{tabular}{ccccc}
    \toprule
    datasets & \multicolumn{2}{c}{linear MCM}     & \multicolumn{2}{c}{linear SVM} \\
    \midrule
          & accuracy & time (s)  & accuracy & time (s) \\
    blogger & 69.00 $\pm$ 17.15 & 0.0012 $\pm$ 6.64e-5 & 58.00 $\pm$ 20.40 & 6.17 $\pm$ 2.51 \\
    fertility diagnosis & 88.00 $\pm$ 9.27 & 0.0013 $\pm$ 5.27e-5 & 86.00 $\pm$ 9.01 & 8.12 $\pm$ 1.47 \\
    promoters  & 74.08 $\pm$ 10.88 & 0.0014 $\pm$ 4.53e-5 & 67.78 $\pm$ 10.97 & 0.85 $\pm$ 0.03 \\
    echocardiogram  &  90.88 $\pm$ 5.75  & 0.0014 $\pm$ 4.62e-5 & 86.38 $\pm$ 4.50 & 0.72 $\pm$ 0.36 \\
    teaching assistant & 66.27 $\pm$ 6.77 & 0.0013 $\pm$ 3.46e-5 & 64.94 $\pm$ 6.56 & 16.07 $\pm$ 4.17 \\
    hepatitis  & 68.38 $\pm$ 6.26 & 0.0014 $\pm$ 3.82e-5 & 60.64 $\pm$ 7.19 & 1.90 $\pm$ 0.56 \\
    hayes & 76.32 $\pm$ 9.25 & 0.0012 $\pm$ 2.73e-5 & 73.56 $\pm$ 7.73 & 7.19 $\pm$ 3.81 \\
    plrx  & 71.83 $\pm$ 7.49 & 0.0015 $\pm$ 3.37e-5 & 71.42 $\pm$ 7.37 & 4.35 $\pm$ 0.78 \\
    seed  & 97.61 $\pm$ 1.51 & 0.0015 $\pm$ 3.97e-5 & 90.95 $\pm$ 4.09 & 12.37 $\pm$ 4.51 \\
    glass & 99.06 $\pm$ 1.16 & 0.0042 $\pm$ 5.56e-3 & 98.12 $\pm$ 1.75 & 11.83 $\pm$ 3.44 \\
    heartstatlog  & 84.81 $\pm$ 3.87 & 0.0018 $\pm$ 1.47e-5 & 82.59 $\pm$ 2.22 & 9.43 $\pm$ 4.25 \\
    horsecolic  & 81.00 $\pm$ 4.03 & 0.0021 $\pm$ 7.17e-5 & 80.26 $\pm$ 4.63 & 41.39 $\pm$ 13.93 \\
    haberman  & 73.89 $\pm$ 3.71 & 0.0019 $\pm$ 4.34e-5 & 72.56 $\pm$ 3.73 & 13.74 $\pm$ 6.63 \\
    ecoli & 96.73 $\pm$ 1.96 & 0.0023 $\pm$ 1.3e-4 & 96.73 $\pm$ 1.96 & 18.41 $\pm$ 2.57 \\
    house voters & 95.63 $\pm$ 1.84 & 0.0031 $\pm$ 1.87e-4 & 94.48 $\pm$ 2.46 & 15.77 $\pm$ 2.19 \\
    wholesale customer & 92.26 $\pm$ 1.97 & 0.0033 $\pm$ 1.07e4 & 91.13 $\pm$ 1.95 & 32.11 $\pm$ 8.29 \\
    IPLD  & 71.35 $\pm$ 2.93 & 0.0065 $\pm$ 4e-5 & 71.35 $\pm$ 2.93 & 12.30 $\pm$ 8.26 \\
    balance & 95.26 $\pm$ 1.02 & 0.0077 $\pm$ 1.3e-3 & 95.20 $\pm$ 1.01 & 8.37 $\pm$ 1.03 \\
    australian  & 85.73 $\pm$ 2.04 & 0.0076 $\pm$ 9.75e-5 & 84.49 $\pm$ 1.18 & 407.97 $\pm$ 167.73 \\
    crx   & 69.56 $\pm$ 2.79 & 0.0095 $\pm$ 1.36e-3 & 67.79 $\pm$ 3.47 & 498.04 $\pm$ 35.22 \\
    transfusion  & 78.19 $\pm$ 3.25 & 0.0082 $\pm$ 8.21e-4 & 77.13 $\pm$ 2.26 & 173.06 $\pm$ 44.12 \\
    tic tac toe & 74.22 $\pm$ 5.50 & 0.038 $\pm$ 4.9e-2 & 73.91 $\pm$ 6.11 & 24.13 $\pm$ 6.81 \\
    sorlie \tnote{1} & 94.084 $\pm$ 1.54 & 0.165 $\pm$ 0.15 & 90.19 $\pm$ 2.47 & 187.50 $\pm$ 1.37 \\
    secom \tnote{1} & 87.87 $\pm$ 1.88 & 957.00 $\pm$ 87.29 & 86.04 $\pm$ 0.82 & 6359.78 $\pm$ 15.93 \\
    tian \tnote{1} & 81.71 $\pm$ 1.43 & 1.39 $\pm$ 0.67 & 80.92 $\pm$ 1.39 & 7832.76 $\pm$ 6.31 \\
    \bottomrule
    \end{tabular}%
  \begin{tablenotes}
  \item[1] {Marked datasets were run on shared computing platforms, and compute times may not be representative.}
  \end{tablenotes}
  \end{threeparttable}
  \label{table1}%
\end{table}%

Table \ref{table2} summarizes five fold cross validation results of the kernel MCM on a number of datasets. A Gaussian or Radial Basis Function (RBF) kernel was chosen for both the MCM and SVM. The width of the MCM Gaussian kernel and the value of $C$ were chosen by using a grid search.

\begin{table}[htbp]
  \centering
\footnotesize\setlength{\tabcolsep}{2.5pt}
  \caption{Kernel MCM Results}
\begin{threeparttable}
\begin{tabular}{c|ccc|ccc}
\hline
	 & & Kernel MCM &  & & Kernel SVM &  \\ \hline
	datasets & accuracy & CPU time (s) & \#SV & accuracy & CPU time (s) & \#SV \\ \hline

    \midrule
          &       &       &       &       &       &  \\
    blogger & 88.00 $\pm$ 4.00 & 0.32 $\pm$ 0.03 & 22.20 $\pm$ 5.91 & 81.00 $\pm$ 10.20 & 2573 $\pm$ 49.2 & 51.20 $\pm$ 3.06 \\
    fertility diagnosis & 89.00 $\pm$ 2.00 & 0.18 $\pm$ 0.09 & 9.80 $\pm$ 19.60 & 88.00 $\pm$ 9.27 & 8.03 $\pm$ 1.95 & 38.20 $\pm$ 1.60 \\
    promoters  & 84.93 $\pm$ 1.56 & 0.45 $\pm$ 0.39 & 82.40 $\pm$ 2.73 & 75.59 $\pm$ 7.63 & 4.40 $\pm$ 1.33 & 83.80 $\pm$ 0.98 \\
    echocardiogram  & 89.34 $\pm$ 4.57 & 0.31 $\pm$ 0.01 & 12.00 $\pm$ 0.00 & 87.14 $\pm$ 7.27 & 8.58 $\pm$ 1.91 & 48.00 $\pm$ 2.10 \\
    teaching assistant & 74.83 $\pm$ 2.60 & 0.39 $\pm$ 0.13 & 26.60 $\pm$ 32.43 & 68.88 $\pm$ 6.48 & 4192 $\pm$ 162 & 86.00  3.22 \\
    hepatitis  & 85.80 $\pm$ 8.31 & 0.44 $\pm$ 0.02 & 20.00 $\pm$ 0.00 & 82.57 $\pm$ 6.32 & 3561 $\pm$ 4392 & 72.20 $\pm$ 4.31 \\
    hayes & 81.82 $\pm$ 7.28 & 0.31 $\pm$ 0.05 & 3.23 $\pm$ 1.11 & 79.57 $\pm$ 6.60 & 1427 $\pm$ 54.7 & 84.20 $\pm$ 2.04 \\
    plrx  & 71.99 $\pm$ 5.81 & 0.41 $\pm$ 0.10 & 4.40 $\pm$ 8.80 & 71.41 $\pm$ 6.04 & 144.21 $\pm$ 5816 & 116.2 $\pm$ 6.14 \\
    seed  & 97.13 $\pm$ 0.95 & 0.79 $\pm$ 0.01 & 11.20 $\pm$ 5.71 & 91.90 $\pm$ 2.86 & 3362 $\pm$ 85.1 & 51.80 $\pm$ 1.72 \\
    glass & 96.23 $\pm$ 2.77 & 1.69 $\pm$ 0.50 & 36.00 $\pm$ 11.49 & 90.64 $\pm$ 5.09 & 20475 $\pm$ 832 & 64.80 $\pm$ 2.40 \\
    heart statlog  & 84.44 $\pm$ 3.21 & 1.32 $\pm$ 0.76 & 10 $\pm$ 2.23 & 83.7 $\pm$ 1.54 & 1547 $\pm$ 324.52 & 124.6 $\pm$ 4.15 \\
    horsecolic  & 82.33 $\pm$ 4.03 & 3.84 $\pm$ 2.31 & 36.60 $\pm$ 17.70 & 81.33 $\pm$ 4.14 & 13267 $\pm$ 2646 & 187.2 $\pm$ 3.27 \\
    haberman  & 73.49 $\pm$ 3.85 & 1.23 $\pm$ 0.32 & 8.50 $\pm$ 7.00 & 72.81 $\pm$ 3.51 & 2087 $\pm$ 750 & 138.2 $\pm$ 3.27 \\
    ecoli & 97.32 $\pm$ 1.73 & 3.47 $\pm$ 0.30 & 24.00 $\pm$ 1.41 & 96.42 $\pm$ 2.92 & 11829 $\pm$ 248 & 57.00 $\pm$ 4.65 \\
    house voters & 95.87 $\pm$ 1.16 & 4.24 $\pm$ 0.83 & 17.80 $\pm$ 8.91 & 95.42 $\pm$ 2.04 & 8827 $\pm$ 349 & 93.60 $\pm$ 3.93 \\
    wholesale customer & 92.72 $\pm$ 1.54 & 7.31 $\pm$ 0.93 & 39.00 $\pm$ 10.64 & 90.90 $\pm$ 1.90 & 9243 $\pm$ 362 & 123.40 $\pm$ 2.15 \\
    IPLD  & 72.03 $\pm$ 3.20 & 4.06 $\pm$ 5.02 & 23.40 $\pm$ 30.50 & 70.15 $\pm$ 2.24 & 9743 $\pm$ 322 & 311.60 $\pm$ 5.31 \\
    balance & 97.64 $\pm$ 1.32 & 8.78 $\pm$ 1.32 & 14.60 $\pm$ 0.49 & 97.60 $\pm$ 0.51 & 15442 $\pm$ 651 & 143.00 $\pm$ 4.23 \\
    australian  & 85.65 $\pm$ 2.77 & 103.45 $\pm$ 18.04 & 108.80 $\pm$ 1.60 & 84.31 $\pm$ 3.01 & 94207 $\pm$ 4476 & 244.8 $\pm$ 4.64 \\
    crx   & 69.56 $\pm$ 2.90 & 5.95 $\pm$ 2.55 & 3.40 $\pm$ 6.80 & 69.27 $\pm$ 2.62 & 19327 $\pm$ 5841 & 404.4 $\pm$ 8.69 \\
    transfusion  & 77.00 $\pm$ 2.84 & 7.08 $\pm$ 0.69 & 6.00 $\pm$ 3.52 & 76.73 $\pm$ 2.88 & 18254 $\pm$ 1531 & 302.20 $\pm$ 7.55 \\
    tic tac toe & 98.32 $\pm$ 0.89 & 12.55 $\pm$ 0.56 & 10.00 $\pm$ 0.00 & 93.94 $\pm$ 2.10 & 18674 $\pm$ 973 & 482.60 $\pm$ 3.93 \\
    sorlie \tnote{1} & 98.82 $\pm$ 2.35 & 0.44 $\pm$ 0.15 & 50 $\pm$ 4.77 & 97.644 $\pm$ 2.88 & 78.63 $\pm$ 9.81 & 68.95 $\pm$ 3.72\\
    secom \tnote{1} & 94.11 $\pm$ 2.23 & 1521 $\pm$ 75.5 & 382.8 $\pm$ 44.23 & 92.29 $\pm$ 0.82 & 38769.25 $\pm$ 8.87 & 593.2 $\pm$ 17.22\\
    tian \tnote{1} & 97.09 $\pm$ 3.83 & 2.05 $\pm$ 0.199 & 70.4 $\pm$ 3.26 & 95.188 $\pm$ 4.26 & 88.97 $\pm$ 3.26 & 75.6 $\pm$ 1.01\\
    \bottomrule
    \end{tabular}%
 \begin{tablenotes}
  \item[1] {Marked datasets were run on shared computing platforms, and compute times may not be representative.}
  \end{tablenotes}
  \end{threeparttable}
    \label{table2}%
\end{table}%

The table shows test set accuracies and the number of support vectors for both the kernel MCM, and the classical SVM with a Gaussian kernel. The results indicate that the kernel MCM yields better generalization than the SVM. In the case of kernel classification, the MCM uses fewer support vectors, generally about one-third the number used by SVMs. In the case of many of the datasets, the MCM uses less than one-tenth the number of support vectors required by a SVM. The code for the MCM classifier would be available from the author's website. The large difference with the SVM results indicates that despite good performance, SVM solutions may still be far from optimal. Vapnik \citep{vapnik95} showed that
\begin{equation}
E(P_{error}) \leq \frac{E(\# \mbox{support vectors})}{\# \mbox{training samples}},
\end{equation}\label{vcbound2}
where $E(P_{error})$ denotes the expected error on test samples taken from the general distribution, $\# \mbox{training samples}$  denotes the number of training samples, and $E(\#$ support vectors $)$ denotes the expected number of support vectors obtained on training sets of the same size. Although the bound was shown for linearly separable datasets, it does indicate that the number of support vectors is also related to the prediction error. An examination of the table indicates that the proposed approach shows a lower test set error, and also uses a smaller number of support vectors. \\

\begin{table}[htbp]
  \centering
  \caption{Values of $h$ for the linear and the kernel MCM}
    \begin{tabular}{ccr}
    \toprule
    datasets & kernel MCM $h$ & linear MCM $h$\\
    \midrule
          &       &  \\
    blogger & 3.73 $\pm$ 1.90 & \multicolumn{1}{c}{2.53 $\pm$ 0.78} \\
    fertility diagnosis & 1.00 $\pm$ 0.00 & \multicolumn{1}{c}{2.72 $\pm$ 1.56} \\
    promoters  & 1.00 $\pm$ 0.00 & \multicolumn{1}{c}{35.77 $\pm$ 18.58} \\
    echocardiogram  & 8.00 $\pm$ 2.94 & \multicolumn{1}{c}{35.76 $\pm$ 18.58} \\
    seed  & 8.32 $\pm$ 4.50 & \multicolumn{1}{c}{9.46 $\pm$ 3.28} \\
    hepatitis  & 3.02 $\pm$ 1.49 & \multicolumn{1}{c}{2.02 $\pm$ 1.32} \\
    teaching assistant & 1.38 $\pm$ 0.47 & \multicolumn{1}{c}{2.12 $\pm$ 0.94} \\\
    plrx  & 1.00 $\pm$ 0.00 & \multicolumn{1}{c}{1.00 $\pm$ 0.00} \\
    hayes & 3.23 $\pm$ 1.11 & \multicolumn{1}{c}{5.00 $\pm$ 0.00} \\
    glass & 8.80 $\pm$ 7.96 & \multicolumn{1}{c}{13.64 $\pm$ 3.32} \\
    heart statlog  & 2.12 $\pm$ 1.87 & \multicolumn{1}{c}{3.79 $\pm$ 1.08} \\
    horsecolic  & 1.20 $\pm$ 0.40 & \multicolumn{1}{c}{1.00 $\pm$ 0.00} \\
    haberman  & 1.18 $\pm$ 0.24 & \multicolumn{1}{c}{1.06 $\pm$ 0.07} \\
    ecoli & 2.41 $\pm$ 1.02 & \multicolumn{1}{c}{4.85 $\pm$ 1.93} \\
    house voters & 4.24 $\pm$ 0.83 & \multicolumn{1}{c}{4.41 $\pm$ 4.21} \\
    wholesale customer & 2.36 $\pm$ 0.97 & \multicolumn{1}{c}{19.79 $\pm$ 6.55} \\
    IPLD  & 6.46 $\pm$ 3.22 & \multicolumn{1}{c}{1.00 $\pm$ 0.00} \\
    balance & 8.73 $\pm$ 7.21 & \multicolumn{1}{c}{16.60 $\pm$ 0.80} \\
    australian  & 1.00 $\pm$ 0.00 & \multicolumn{1}{c}{1.86 $\pm$ 0.43} \\
    crx   & 1.00 $\pm$ 0.00 & \multicolumn{1}{c}{1.00 $\pm$ 0.00} \\
    transfusion  & 2.07 $\pm$ 1.36 & \multicolumn{1}{c}{1.57 $\pm$ 0.71} \\
    tic tac toe & 1.52 $\pm$ 0.06 & \multicolumn{1}{c}{3.07 $\pm$ 1.04} \\
    sorlie & 1.00 $\pm$ 0.00 & \multicolumn{1}{c}{1.12 $\pm$ 0.17} \\
    secom & 8.32 $\pm$ 0.71 & \multicolumn{1}{c}{1.00 $\pm$ 0.00} \\
    tian & 1.25 $\pm$ 0.27 & \multicolumn{1}{c}{5.31 $\pm$ 2.26} \\
     \bottomrule
    \end{tabular}%
  \label{htable}%
\end{table}%

Table \ref{htable} shows the values of $h$ for the linear MCM and the kernel MCM on the benchmark datasets. The values have been indicated as mean $\pm$ standard deviation, computed over the five folds in a five-fold cross validation setting. Note that $h^2$ is an exact bound on the VC dimension $\gamma$, and thus an approximate measure of the capacity of the learning machine. The table indicates that the values of $h$ for the kernel MCM are generally smaller than that for the linear MCM. This also reflects in the better generalization achieved by the kernel MCM.\\

\section{Acknowledgment}
The author would like to thank Prof. Suresh Chandra of the Department of Mathematics, IIT Delhi, for his valuable comments and a critical appraisal of the manuscript. The extensive simulations were the result of the untiring efforts of Siddarth Sabharwal and Sanjit Singh Batra. Early simulations on the linear model were done by Prasoon Goel.

\section{Conclusion} \label{conclusion}
In this paper, we propose a way to build a hyperplane classifier, termed as the Minimal Complexity Machine (MCM), that attempts to minimize a bound on the VC dimension. The classifier can be found by solving a linear programming problem. Experimental results show that the learnt classifier outperforms the classical SVM in terms of generalization accuracies on a number of selected benchmark datasets. At the same time, the number of support vectors is less, often by a substantial factor. It has not escaped our attention that the proposed approach can be extended to least squares classifiers, as well as to tasks such as regression; in fact, a large number of variants of SVMs can be re-examined with the objective of minimizing the VC dimension.

\appendices
\section{An Exact Bound on the VC dimension $\gamma$} \label{appendix1}
We derive an exact or tight ($\Theta$) bound on the VC dimension $\gamma$. Vapnik \citep{vapnik98} showed that the VC dimension $\gamma$ for fat margin hyperplane classifiers with margin $d \geq d_{min}$ satisfies
\begin{equation}
\gamma \leq 1 + \operatorname{Min}(\frac{R^2}{d^2_{min}}, n)
\end{equation}
where $R$ denotes the radius of the smallest sphere enclosing all the training samples. We first consider the case of a linearly separable dataset. By definition, there exists a hyperplane $u^Tx + v = 0$ with positive margin $d$ that can classify these points with zero error. We can always choose $d_{min} = d$; for all further discussion we assume that this is the case. Without loss of generality, we consider hyperplanes passing through the origin. To see that this is possible, we augment the co-ordinates of all samples with an additional dimension or feature whose value is always $1$, i.e. the samples are given by $\hat{x}^i \leftarrow \{x^i; 1\}, i = 1, 2, ..., M$; also, we assume that the weight vector is $(n+1)$-dimensional, i.e. $\hat{u} \leftarrow \{u; v\}$.

Then, the margin, which is the distance of the closest point from the hyperplane, is given by
\begin{equation}
 d = \operatorname*{Min}_{i = 1, 2, ...M} \frac{\|\hat{u}^T \hat{x}^i\|}{\|\hat{u}\|}
\end{equation}\label{geomargin0}

\begin{equation}
\frac{R}{d} = \frac{\operatorname*{Max}_{i = 1, 2, ...M}\|\hat{x}^i\|}{\operatorname*{Min}_{i = 1, 2, ...M} \frac{\|\hat{u}^T \hat{x}^i\|}{\|\hat{u}\|}} = \frac{\operatorname*{Max}_{i = 1, 2, ...M} \|\hat{u}\| \| \hat{x}^i\|}{\operatorname*{Min}_{i = 1, 2, ...M} \|\hat{u}^T \hat{x}^i\|} \label{Rbyd1}
\end{equation}

From the Cauchy-Schwarz inequality, we have
\begin{gather}
\|\hat{u}^T \hat{x}^i\| \leq \|\hat{u}\| \|\hat{x}^i\| \label{csineq1}\\
\implies \operatorname*{Max}_{~i = 1, 2, ..., M} \|\hat{u}^T \hat{x}^i\| \leq \operatorname*{Max}_{~i = 1, 2, ..., M} \|\hat{u}\| \|\hat{x}^i\| \label{csineq2}
\end{gather}

Therefore, from (\ref{Rbyd1}), we have
\begin{gather}
 \frac{\operatorname*{Max}_{i = 1, 2, ..., M} \|\hat{u}^T \hat{x}^i\|}{\operatorname*{Min}_{i = 1, 2, ..., M} \|\hat{u}^T \hat{x}^i\|} ~ \leq \frac{R}{d} \label{csineq3}
\end{gather}
or, in terms of the original variables $u$ and $v$,

\begin{gather}\label{bound1a}
 \frac{\operatorname*{Max}_{i = 1, 2, ..., M} \|u^T x^i + v\|}{\operatorname*{Min}_{i = 1, 2, ..., M} \|u^T x^i + v\|} \leq \frac{R}{d}
\end{gather}\\

Denoting
\begin{gather}
 h = \frac{\operatorname*{Max}_{i = 1, 2, ..., M} \|u^T x^i + v\|}{\operatorname*{Min}_{i = 1, 2, ..., M} \|u^T x^i + v\|},
\end{gather}
we can write
\begin{gather}\label{bound1}
 h \leq \frac{R}{d}, \\
 \implies h^2 \leq (\frac{R}{d})^2 < 1 + (\frac{R}{d})^2.
\end{gather}
Assuming that the dimension $n$ of the data samples is sufficiently large, we have, from (\ref{eqnh}),
\begin{gather}
 \gamma \leq 1 + (\frac{R}{d})^2.
\end{gather}
Hence, $\exists \beta \in \Re$,  $\beta > 0$, such that
\begin{gather}\label{gammaleqh2}
\gamma \leq \beta h^2.
\end{gather}

We also note that
\begin{equation}\label{minh}
 h^2 \geq 1,
\end{equation}
the minimum being achieved when all samples are equidistant from the separating hyperplane.

Also note that the VC dimension $\gamma$ satisfies
\begin{equation}\label{minvc}
 \gamma \geq 1.
\end{equation}

In short, both $h^2$ and $\gamma$ have the same lower and upper bounds, i.e. they are of the same order. Therefore, from (\ref{gammaleqh2}), (\ref{minh}) and (\ref{minvc}), we note that there exist constants $\alpha, \beta > 0$, $\alpha, \beta \in \Re$ such that

\begin{equation}\label{thetavc2}
 \alpha h^2 \leq \gamma \leq \beta h^2,
\end{equation}
or, in other words, $h^2$ constitutes a tight or exact ($\theta$) bound on the VC dimension $\gamma$.\\

Since the dataset has been assumed to be linearly separable, we have
\begin{eqnarray}
 u^Tx^i + v \geq 0, & \mbox{if } y_i = 1 \mbox{   (Class 1 points)} \label{moduvg0}\\
 u^Tx^i + v \leq 0, & \mbox{if } y_i = -1 \mbox{  (Class -1 points)} \label{moduvl0}
\end{eqnarray}

We also have
\begin{equation}\label{moduv}
 \|u^Tx^i + v\| = \begin{cases} u^Tx^i + v, & \mbox{if } u^Tx^i + v \geq 0 \\
                                -(u^Tx^i + v), & \mbox{if } u^Tx^i + v \leq 0 \end{cases}
\end{equation}

Therefore, from (\ref{moduvg0}), (\ref{moduvl0}), and (\ref{moduv}), we can write
\begin{equation}
 \|u^Tx^i + v\| = y_i \cdot [u^T x^i + v], ~i = 1, 2, ..., M.
\end{equation}

Therefore,
\begin{gather}\label{eqhrepeat}
 h = \frac{\operatorname*{Max}_{i = 1, 2, ..., M} \;y_i(u^T x^i + v)}{\operatorname*{Min}_{i = 1, 2, ..., M} \;y_i(u^T x^i + v)}.
\end{gather}

\section{The Hard Margin MCM Formulation} \label{appendix2}
In this appendix, we derive the hard margin MCM formulation in the input space. We begin with the optimization problem in (\ref{minh1}), which was obtained from the exact bound on $\gamma$ derived in Appendix \ref{appendix1}. In deriving the exact bound in Appendix \ref{appendix1}, we assumed that the separating hyperplane $u^Tx + v = 0$ correctly separates the linearly separable training points; hence, no other constraints are present in the optimization problem (\ref{minh1}). For the convenience of the reader, (\ref{minh1}) [also (\ref{eqhrepeat})] is reproduced below.
\begin{equation}
\operatorname*{Minimize  }_{u, v} \; h ~=~ \frac{\operatorname*{Max}_{i = 1, 2, ..., M} \; y_i(u^T x^i + v)}{\operatorname*{Min}_{i = 1, 2, ..., M} \; y_i(u^T x^i + v)} \nonumber
\end{equation}
The problem (\ref{minh1}) may be rewritten as

\begin{gather}
\operatorname*{Min}_{u, v, g, l} ~~\frac{g}{l} \label{obj1}\\
g \geq y_i \cdot [{u^T x^i + v}], ~i = 1, 2, ..., M \label{cons1}\\
l \leq y_i \cdot [{u^T x^i + v}], ~i = 1, 2, ..., M \label{cons2}
\end{gather}

This is a linear fractional programming problem \citep{numoptbook}. We apply the Charnes-Cooper transformation \citep[see][p. 463]{numoptbook}. This consists of introducing a variable $p = \frac{1}{l}$, which we substitute into (\ref{obj1})-(\ref{cons2}) to obtain

\begin{gather}
\operatorname*{Min}_{u, v, g, p, l} ~~h = g \cdot p \label{obj2}\\
g \cdot p \geq y_i \cdot [p \cdot {u^T x^i + p \cdot v}], ~i = 1, 2, ..., M \label{cons21}\\
l \cdot p \leq y_i \cdot [p \cdot {u^T x^i + p \cdot v}], ~i = 1, 2, ..., M \label{cons22}\\
p \cdot l = 1 \label{cons24}
\end{gather}

Denoting $w \equiv p \cdot u$, $b \equiv p \cdot v$, and noting that $p \cdot l = 1$, we obtain the following optmization problem.
\begin{gather}
\operatorname*{Min}_{w, b, h} ~~h \label{obj3}\\
h \geq y_i \cdot [{w^T x^i + b}], ~i = 1, 2, ..., M \label{cons31}\\
1 \leq y_i \cdot [{w^T x^i + b}], ~i = 1, 2, ..., M \label{cons32}
\end{gather}

which may be written as
\begin{gather}
\operatorname*{Min}_{w, b, h} ~~h \label{obj4}\\
h \geq y_i \cdot [{w^T x^i + b}], ~i = 1, 2, ..., M \label{cons41}\\
y_i \cdot [{w^T x^i + b}] \geq 1, ~i = 1, 2, ..., M \label{cons42}
\end{gather}

We refer to the problem (\ref{obj4}) - (\ref{cons42}) as the hard margin Linear Minimum Complexity Machine (Linear MCM). Note that $h^2$ is an exact bound on $\gamma$, the VC dimension of the classifier.

\bibliographystyle{elsarticle-num}

redpajama_set_name: RedPajamaArXiv


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I finished my Hobbyboss AMX…. mostly.
The instructions call for placing the small M61 Vulcan gun barrel part as one of the last steps. Simple enough…. unless you push it in too far, and it drops inside the fuselage. Half an hour of shaking the model around produced no joy in getting it out. Thankfully, a friend has offered a suitable replacement part, so once I get that, I'll add that in.
So I'm calling this "Ivory Soap Finished". Meaning it's 99 44⁄100% of the way there.
This kit has to be in the top 5 of my all time favorite kits. It has no vices at all. The parts just fit, with no fuss. The detailing is very good. The decals could be a little better, but they're not bad. I'd recommend this kit to anyone.
I'm not entirely happy with the finish. I tried a lot of new techniques on this one, and now that I look at the finished product, I wish I'd have experimented a little less. It doesn't look bad, but because of my lack of experience with these new techniques, the overall look is not what I envisioned.
Still- I like it. It's the first time in a very long time I've built a model and just looked at it for a while and smiled.
I normally sell everything I build, but I think I'm going to keep this one for a while. it's been such a rejuvenating process to do something different, just for the fun of it. I want it on my shelf, at least for a while.
You can look back on the build process here.
Next Post:Trumpeter 1/48 JL-9- What In The Wide World Of Sports Is A JL-9?
There is no technique on the model looking out of place imho, then again refinement is in the eye of the beholder i suppose.
now the result might not be inline with the realism you imagined, when that happens to me i usually hide the model out of sight and let it dwell there for a couple of days and then have a look with a fresh set of eyes. when i become involved too much with a particular subject i think i develop some kinda myopia and lose sight of the bigger picture if you get what i mean.
even in gray colors it's refreshing to see an unusual subject always and your model looks lovely. i too love this kind of trainer/lt attack jet aircraft and i will take your word on the HB kit and like to build one when able!
Thanks for your kind words and perspective!
That is an awesome looking little jet Jon – so nice to see you building a jet and actually enjoying it. Great work!
I agree with you that these Trainer/attack aircraft can really interesting.


text:
import Vectorised
import Timing
import Randomish
import System.Environment
import Data.Vector.Unboxed		(Vector)
import Data.Array.Parallel	as P
import Data.Array.Parallel.PArray	as P
import qualified Data.Vector.Unboxed	as V
import Data.Maybe

main :: IO ()
main
 = do	args	<- getArgs
	case args of
	  [len]	-> run (read len)
	  _	-> putStr usage

-- | Command line usage information.
usage :: String
usage	= unlines
	[ "Usage: quicksort <length>" ]

-- | Run the benchmark.
run :: Int -> IO ()
run len
 = do	-- Create the input vector
	let vInts 	= fromUArray
			$ randomishDoubles len 0 1 1234

	vInts `seq` return ()

	-- Compute the convex hull.
	(vSorted, tElapsed)
		<- time
		$  let 	vSorted	= quicksortPA vInts
		   in	vSorted `seq` return vSorted

	-- Print how long it took.
	putStr $ prettyTime tElapsed

	-- Check they're really sorted.
	print	$ isSorted $ P.toUArray vSorted

-- | Check if a vector is sorted (monotonically increasing)
isSorted :: Vector Double -> Bool
isSorted = isJust . V.fold1M (\x y -> if y >= x then Just y else Nothing)

redpajama_set_name: RedPajamaGithub


text:
Devlin v. Devlin.
Decided: September 14, 2016
Margaret E. Devlin, for Appellant. Patrick Hammond Garrard, Athens, William Brent Ney, Atlanta, for Appellee.
Margaret Devlin ("the grandmother"), pro se, appeals from a superior court order denying her request for an established schedule of grandparent visitation under OCGA § 19–7–3 (d). She contends that the trial court erred in: (1) denying her requests to present telephonic testimony under OCGA § 19–9–50 (b); (2) denying her request to participate in a mediation by telephone; (3) failing to determine whether she could "travel to Georgia without financial harm"; (4) allowing the daughter-in-law "to enter testimony without legitimate evidence"; (5) failing to discover "conclusively that the [mother]'s testimony was true"; and (6) concluding "that the grandparent visitation would cause harm to the children." For the reasons explained below, we find no merit in these contentions and affirm.
The record shows that the grandmother first sought visitation through a Pennsylvania court following the death of her son, the minor children's father, in July 2013. In June 2014, a Pennsylvania court awarded sole physical and legal custody of the children to their mother, allowed limited grandparent visitation, and approved the mother's relocation to Georgia with the children. In February 2014, the mother moved to Georgia, obtained a Georgia driver's license, employment, leased a home, and enrolled the children in a Georgia school.
In December 2014, the mother filed an action in Georgia to enforce and modify the custody and visitation order entered by the Pennsylvania court. She alleged that the grandmother failed to cooperate with her efforts to establish a schedule for grandparent visitation time, and asked the court
to provide for an established schedule regarding visitation upon the showing required by OCGA § 19–7–3 (c). Alternatively, the timing, duration and conditions of any visitation should be determined exclusively by Petitioner. Any Court–Ordered visitation should take place in Georgia and at times and dates approved by Petitioner.
Following a hearing in which the Georgia court allowed the grandmother to participate pro se in a limited manner by telephone, it concluded that the mother and children had been continuous residents of the State of Georgia for six months before the Georgia proceeding was filed and that it had "exclusive jurisdiction as to all issues of custody and visitation."
Two months after this order was entered, the trial court scheduled a mediation for the parties to take place in Georgia in mid-July 2015, almost one month later. The grandmother promptly filed another request to participate by telephone, alleging that she did "not have the funds to travel to Georgia solely for the purposes of this mediation." The mother opposed this request, asserting that the history between the parties made "it unlikely that the parties could reach a mediated settlement, and Respondent's request to remotely participate makes the prospect of settlement even less likely." The record before us does not include a written order on the grandmother's request to participate in the mediation by telephone, but a later order references that this request was denied. A subsequently-filed brief by the mother states that she appeared for the court-ordered mediation, while the grandmother did not do so.
Shortly after the date for the scheduled mediation, the grandmother filed a motion for an emergency hearing with regard to her request for unsupervised visitation with the children in Pennsylvania for two weeks out of each year. In the same motion she alleged that the mother had committed "perjury by not being truthful throughout this process." She also asked that she be allowed to testify by telephone in the hearing because she did "not have the funds to travel to Georgia solely for the purpose of this Hearing." The mother opposed her request to testify by telephone, arguing that "live testimony will aid the Court in determining which party is telling the truth and help the Court understand the true motivations for Respondent's continued frivolous litigation tactics. This is particularly true since it was clear that Respondent was receiving coaching from an unknown person during her previous telephonic testimony at the jurisdictional hearing."
On October 15, 2015, the trial court denied the grandmother's request to testify telephonically, stating:
Respondent has filed a Motion for Emergency Hearing. Included in that motion, is Respondent's requests that she be permitted to testify telephonically. A review of the record shows that Respondent failed to attend mediation as ordered by the Court. At that time, the Court denied Respondent's request to mediate telephonically. Additionally the primary purpose of the instant motion appears to be an attempt by Respondent to re-litigate issues that were resolved in a previous hearing and Order by this Court.
IT IS ORDERED that Respondent's Motion for Emergency Hearing is DENIED WITH REGARD TO HER REQUEST TO TESTIFY TELEPHONICALLY.
In the same order, the trial court scheduled a final hearing on the merits of the grandmother's request for custody for December 1, 2015, and expressly required the grandmother "to appear in person at the hearing, if she wishes to be heard on this motion."
On November 10, 2015, the grandmother filed a pro se "motion for an appeal" of the trial court's denial of her request to appear by telephone. She asserted that she was "a retired Pennsylvania Correctional Officer surviving on an earned Pension or 'fixed income' " and that she qualified for free legal services but could not receive them in Georgia as a non-resident. The mother opposed the grandmother's request for an appeal because it was filed 26 days after the trial court's order, well after the 10–day time period for a party to request a certificate for immediate review of an interlocutory matter under OCGA § 5–6–34 (b). The trial court construed the grandmother's request for an appeal as a motion for reconsideration and denied it.
The grandmother did not appear for the final hearing at which the trial court heard evidence on the issue of visitation. A transcript of this hearing is not a part of the record before us. The day after the hearing held on December 2, 2015, the trial court issued an order in which it made the following findings of fact:
(1) Respondent has failed to appear for Court–Ordered mediation after receiving notice and after being ordered by the Court to appear in person; (2) Respondent has failed to appear for the Final Hearing after receiving notice and after being ordered by the Court to appear in person; (3) Respondent carries the burden of proof to show that visitation under OCGA § 19–7–3 (d) is in the best interests of the Minor Children; (4) in light of Respondent not appearing at the hearing, Respondent has failed to present any evidence that such visitation is in the best interests of the Minor Children and has otherwise failed to carry her burden of proof; (5) Petitioner presented evidence at the hearing in the form of testimony and documents showing the circumstances surrounding the death of the Minor Children's father, instances of inappropriate and unsupported accusations by Respondent's family members directed at Petitioner and her Minor Children that could be harmful to the Minor Children if they were exposed to such, and Respondent's failure to intervene to protect the Minor Children from this harmful conduct; (6) Petitioner presented testimony that in her judgment visitation under OCGA § 19–7–3 (d) was not in the best interests of the Minor Children, and, while not conclusive, the Court pursuant to the statute, defers to that based upon its review of the record and the evidence presented. Based upon the lack of evidence presented by Respondent and based upon evidence presented at the Final Hearing by Petitioner and the findings of fact above, the Court finds that visitation between the Minor Children and Respondent is not in the best interests of the Minor Children, and the Court hereby DENIES grandparent visitation under OCGA § 19–7–3. Any grandparent visitation with the Minor Children shall occur only at such times, places, and under such conditions as Petitioner deems advisable in her discretion.
On December 28, 2015, the grandmother filed a pauper's affidavit for the first time in connection with her request for a waiver of the filing fee for an appeal in this court. According to her affidavit, her household received a total of $4,669 per month through pensions and social security. The trial court denied her request based upon the amount of monthly income.
1. As the grandmother's claims of error regarding her requests to appear by telephone and her financial ability to travel to Georgia are related, we will consider them together.
Georgia has adopted the Uniform Child Custody Jurisdiction and Enforcement Act ("UCCJEA"), OCGA § 19–9–40 et seq., which provides: "A court of this state may permit an individual residing in another state to be deposed or to testify by telephone, audiovisual means, or other electronic means before a designated court or at another location in that state." (Emphasis supplied.) OCGA § 19–9–50 (b). Although there are no Georgia decisions interpreting this Code section, other states have concluded that this portion of the UCCJEA permits, but does not require, a trial court to allow telephonic testimony. See In re the Marriage of Neubauer, 815 NW2d 410 (IV) (Iowa App. 2012); In re Marriage of Tamasy, 929 NE2d 820, 830 (II) (B) (Ind. App. 2010); Schwier v. Bernstein, 734 So.2d 531 (Fla. App. 1999). In Georgia, "[a] trial judge has broad discretion in regulating the conduct of counsel, parties and witnesses, and in prescribing the manner in which the business shall be conducted." (Citations and footnote omitted.) Brown v. State, 285 Ga. App. 453, 455 (2) (646 SE2d 289) (2007). See also OCGA § 15–1–3 (4); 24–6–611 (a). We will therefore review the trial court's ruling on the admission of telephonic testimony for an abuse of discretion. See Baars v. Freeman, 288 Ga. 835, 842 (3) (708 SE2d 273) (2011) (reviewing trial court's decision to allow telephonic testimony under identical provision of former OCGA § 19–11–135 (f)1 for abuse of discretion).
Other jurisdictions considering whether a trial court has abused its discretion in a ruling on the use of telephonic testimony find an examination of the function served by a personal appearance in court useful. See, e.g., Cenlar, FSB v. Moore, 2009 N.M. App. Unpub. LEXIS 87, Slip Op. at * 8–9 (B) (Case No.26,768, decided May 8, 2009). In its oft-cited decision in In re Marriage of Bonamarte, 263 Mont. 170 (866 P2d 1132) (1994), the Montana Supreme Court concluded that a witness's personal appearance in court served the following important policies and purposes:
1. assists the trier of fact in evaluating the witness' credibility by allowing his or her demeanor to be observed firsthand;
2. helps establish the identity of the witness;
3. impresses upon the witness, the seriousness of the occasion;
4. assures that the witness is not being coached or influenced during testimony;
5. assures that the witness is not referring to documents improperly; and
6. in cases where required, provides for the right of confrontation of witnesses.
(Citation and punctuation omitted.) Id. at 174.
Here, the trial court allowed the grandmother to appear by telephone in a hearing to determine its jurisdiction. After once allowing the grandmother to appear by telephone, the trial court denied the grandmother's subsequent requests to appear by telephone for a mediation and the final evidentiary hearing on the issue of grandparent visitation. As outlined above, there are numerous reasons that a personal appearance is preferable, and we cannot conclude that the trial court abused its discretion in requiring the grandmother to travel to Georgia. While the grandmother contends that the trial court should have determined that she was able to travel to Georgia without financial harm, our law does not mandate that the trial court make such a finding.2 And even if such a requirement did exist,3 the grandmother failed to provide the trial court with the necessary evidence to make such a determination, and when she ultimately provided it in connection with the costs of her appeal, the trial court determined that she was not indigent. See OCGA § 9–15–2 (a) (2) ("The judgment of the trial court on all issues of fact concerning the ability of a party to pay costs or give bond shall be final."); Penland v. State, 256 Ga. 641, 642 (352 SE2d 385) (1987) (defendant suffers no denial of due process from provision in OCGA § 9–15–2 (a) (2) that trial court's findings concerning party's ability to pay costs or post bond are not subject to review).
For these reasons, we find no abuse of discretion by the trial court in connection with its denial of the grandmother's request to appear by telephone and its failure to determine that she could travel without financial harm.
2. The grandmother's remaining enumerations of error relate to the evidence before the trial court during the final hearing on the issue of grandparent visitation, but the record before us does not include a transcript of the final hearing. "Where the record did not contain a transcript of evidence adduced upon [an evidentiary hearing], questions of whether or not there was any merit in the enumeration of error could not be determined, so the judgment must be affirmed." (Citations omitted.) Wells Fargo Home Mtg., Inc. v. Cook, 267 Ga. App. 368, 369 (1) (599 SE2d 319) (2004). Accordingly, the grandmother's remaining claims of error do not require a reversal.
1. Former OCGA § 9–11–135 (f) provided: "In a proceeding under [The Uniform Interstate Family Support Act, 19–11–100 et seq.], a tribunal of Georgia may permit a party or witness residing in another state to be deposed or to testify by telephone, audiovisual means, or other electronic means at a designated tribunal or other location in that state."
2. To the extent the grandmother relies upon OCGA § 19–7–3 (e), this Code section does not apply as it relates only to a trial court's discretion to require a grandparent seeking visitation to be solely responsible for the expense of mediation, and makes no mention of a grandparent's financial ability to travel.
3. We note that some jurisdictions require a showing of special or exigent circumstances necessitating telephonic testimony, Bonamarte, supra; Aqua Marine Products, Inc. v. Pathe Computer Control Systems Corp., 229 N.J. Super. 264 (551 A.2d 195) (N.J. App.1988), and in some of these states, financial inability to travel is not considered an adequate special or exigent circumstance. See, e.g., In re B.C., 283 Mont. 423, 429 (942 P2d 106) (1997).
Boggs, Judge.
Barnes, P.J., and Rickman, J., concur.


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