Efficiency of Truthful and Symmetric Mechanisms in One-sided Matching

We study the efficiency (in terms of social welfare) of truthful and symmetric mechanisms in one-sided matching problems with {\em dichotomous preferences} and {\em normalized von Neumann-Morgenstern preferences}. We are particularly interested in the well-known {\em Random Serial Dictatorship} mechanism. For dichotomous preferences, we first show that truthful, symmetric and optimal mechanisms exist if intractable mechanisms are allowed. We then provide a connection to online bipartite matching. Using this connection, it is possible to design truthful, symmetric and tractable mechanisms that extract 0.69 of the maximum social welfare, which works under assumption that agents are not adversarial. Without this assumption, we show that Random Serial Dictatorship always returns an assignment in which the expected social welfare is at least a third of the maximum social welfare. For normalized von Neumann-Morgenstern preferences, we show that Random Serial Dictatorship always returns an assignment in which the expected social welfare is at least \frac{1}{e}\frac{\nu(\opt)^2}{n}, where \nu(\opt) is the maximum social welfare and $n$ is the number of both agents and items. On the hardness side, we show that no truthful mechanism can achieve a social welfare better than \frac{\nu(\opt)^2}{n}.Comment: 13 pages, 1 figur

Social welfare in one-sided matchings: Random priority and beyond

We study the problem of approximate social welfare maximization (without money) in one-sided matching problems when agents have unrestricted cardinal preferences over a finite set of items. Random priority is a very well-known truthful-in-expectation mechanism for the problem. We prove that the approximation ratio of random priority is Theta(n^{-1/2}) while no truthful-in-expectation mechanism can achieve an approximation ratio better than O(n^{-1/2}), where n is the number of agents and items. Furthermore, we prove that the approximation ratio of all ordinal (not necessarily truthful-in-expectation) mechanisms is upper bounded by O(n^{-1/2}), indicating that random priority is asymptotically the best truthful-in-expectation mechanism and the best ordinal mechanism for the problem.Comment: 13 page

School Admissions Reform in Chicago and England: Comparing Mechanisms by Their Vulnerability to Manipulation

In Fall 2009, officials from Chicago Public Schools changed their assignment mechanism for coveted spots at selective college preparatory high schools midstream. After asking about 14,000 applicants to submit their preferences for schools under one mechanism, the district asked them re-submit their preferences under a new mechanism. Officials were concerned that "high-scoring kids were being rejected simply because of the order in which they listed their college prep preferences" under the abandoned mechanism. What is somewhat puzzling is that the new mechanism is also manipulable. This paper introduces a method to compare mechanisms based on their vulnerability to manipulation. Under our notion, the old mechanism is more manipulable than the new Chicago mechanism. Indeed, the old Chicago mechanism is at least as manipulable as any other plausible mechanism. A number of similar transitions between mechanisms took place in England after the widely popular Boston mechanism was ruled illegal in 2007. Our approach provides support for these and other recent policy changes involving matching mechanisms.

The Boston Public School Match

Economic

Value of preoperative spirometry to predict postoperative pulmonary complications

AbstractIn order to determine the incidence of postoperative pulmonary complications (POPC) and the value of preoperative spirometry to predict pulmonary complications after upper abdominal surgery, 24 women and 36 men (total 60 patients) were studied prospectively (mean age 48·3 years). On the day before the operation and for 15 days after the operation, each patients's respiratory status was assessed by clinical examination, chest radiography, spirometry and blood gas analysis, and patients were monitored for pulmonary complications by a chest physician and a surgeon independently. In this study, postoperative pulmonary complications developed in 21 (35%) patients (pneumonia in 10 patients, bronchitis in nine patients, atelectasis in one patient, pulmonary embolism in one patient). Of 31 patients with abnormal preoperative spirometry, 14 (45·2%) patients showed complications, whereas among 29 patients with normal preoperative spirometry, 7 (24·1%) patients showed complications (P<0·05). The incidence of POPC was higher in patients with advanced age, smoking, preoperative abnormal findings obtained from physical examination of the chest, higher ASA class and longer duration of operation. The sensitivity (0·76) and specificity (0·79) of abnormal preoperative findings obtained from physical examination to predict POPC were higher than abnormal preoperative spirometry (0·67 and 0·56 retrospectively). There was no significant difference between patients with and without pulmonary complications in regard to weight, serum albumin, type of incision, incidence of abnormal preoperative blood gases and duration of postoperative hospital stay. We conclude that POPC is still a serious cause of postoperative morbidity. Multiple risk factors include preoperative abnormal spirometry responsible for development of POPC. If used alone, spirometry has limited clinical value as a screening test to predict POPC after upper abdominal surgery

Fair Allocation of Vaccines, Ventilators and Antiviral Treatments: Leaving No Ethical Value Behind in Health Care Rationing

COVID-19 has revealed limitations of existing mechanisms for rationing medical resources under emergency scenarios. Many argue that these mechanisms abandon various ethical values such as equity by discriminating against disadvantaged communities. Illustrating that these limitations are aggravated by a restrictive choice of mechanism, we formulate pandemic rationing of medical resources as a new application of market design and propose a reserve system as a resolution. We develop a general theory of reserve design, introduce new concepts such as cutoff equilibria and smart reserves, extend analysis of previously-known ones such as sequential reserve matching, relate these concepts to current debates, and present preliminary policy impact.Comment: Keywords: ethical rationing, reserve system, COVID-19, vaccines, ventilator

Eylem çıkarımı ve varlık tanıma için ontoloji tabanlı bilgi çıkarımı ve belge yapı analizinin tümleştirilmesi

This study covers research activity in the field of automatic processing and event extraction from documents in Turkish. Proposed approach benefits valuable hints provided by document structure analysis for extracting information. Approach checks entities and relations of entities across document and verifies them by using relational database integration rules that are defined for each domain event. It contains a morphological analyzer for Turkish, a document structure analyzer and an extraction ontology. Even though there has been an on-going effort for eliminating free-formatted text documents, certain forms of communication continue to be completely unstructured such as fax and e-mail. Proposed approach benefits extraction ontology, where currently available parsing approaches do not use ontology very effectively, mostly depending on rule-based or statistical parsers. Ontology based IE increases portability and scalability of an IE system. Proposed approach requires only extraction concepts when compared to information extraction systems that rely on large set of linguistic patterns. Proposed architecture is tested on a set of 3000 documents in 3 different domains, including data in tabular, list and itemized form. Proposed architecture has an F-Score 99% for extracting information from financial documents, frequent flyer emails and student written letters. Experimental results indicate that it obtained a high performance for detecting document domain, document model, entities and domain events. Main IE tasks can be listed as extracting entities, extracting pre-specified events, extracting relations between entities and events. Experimental results indicate that document structure analysis and ontology based IE techniques mutually benefit each other. In proposed architecture, input document is treated as a combination of document model and event concept, where entities within document are cross-related to each other. Approach determines document model by locating document blocks, and using document models it determines the document domain. Approach also verifies document model by detecting the domain event in the input document.  Using document structure analysis approach also determines some of the unknown entity types. Experimental results also indicate that approach successfully locates data in tabular, list and itemized form. For detecting data in tabular or list form it depends on a specific set of titles called "Descriptor Titles" which refer to column or row headers in tables or lists. In Turkish, morphological analysis is more complex when compared to languages like English, because it has agglutinative morphology. Due to the fact that Turkish is a free constituent language, proposed approach focuses on locating domain specific concepts in a sentence using the proposed "Concept Zoning" technique. In case approach detects an unknown triggering verb, using concept similarity calculations, it determines the closest matching event in the extraction ontology. This case is especially useful during system development phase. Benefiting this feature a known domain event with an unknown triggering verb or an unknown domain event made up of known domain concepts can be determined. Approach also detects connected actions. It treats each action as seperate events however, in practice certain events require another event to make sense and its triggering verb contains specific morphological features. Main contributions involved in this thesis are listed as the following items: Test the effect of proposed "Concept Zoning" technique and document layout analysis on entity recognition and event extraction. Develop an ontology editor for designing domain concepts and events for extracting domain specific events in different document domains. Validating extracted information by using both relational database integration and document model validation, and benefit this integration for determining unknown entity types. Keywords: Ontology based information extraction, document structure analysis, entity recognition, natural language understanding.Bu &ccedil;alışmada, T&uuml;rk&ccedil;e belgelerin otomatik olarak işlenmesi ve bu belgelerden bilgi &ccedil;ıkarımı i&ccedil;in ontoloji tabanlı bilgi &ccedil;ıkarımı ve belge yapı analizi teknikleri bir arada kullanılmıştır. Geleneksel bilgi &ccedil;ıkarımı sistemleri giriş metnini sıralı kelimeler olarak ele almakta iken, &ouml;nerilen mimari belge yapı şablonlarının ve belge modellerinin sağladığı bilgilerden faydalanmaktadır. Bu &ouml;zelliklere ek olarak, belgenin doğruluğunu sınamak i&ccedil;in, belgede yer alan varlıklar arasındaki ilişkiler sınanmakta ve &ccedil;ıkarımı yapılmış varlıklar ile ger&ccedil;ek veriler karşılaştırılmaktadır. (&Ouml;rnek: M&uuml;şteri veritabanı). &Ouml;nerilen yaklaşım, T&uuml;rk&ccedil;e i&ccedil;in bi&ccedil;imbirimsel analiz mod&uuml;l&uuml;, belge yapı analiz mod&uuml;l&uuml; ve &ccedil;ıkarım ontolojisi i&ccedil;ermektedir. Y&uuml;ksek miktarda dilbilimsel şablona dayalı &ccedil;alışan bilgi &ccedil;ıkarım sistemlerinin aksine, &ccedil;ıkarım ontolojisi kullanılarak bilgi &ccedil;ıkarımı i&ccedil;in sadece alan kavramı tanımları yeterli olmaktadır. T&uuml;rk&ccedil;e&rsquo;de &ouml;ğeler c&uuml;mlenin anlamını bozmadan serbest&ccedil;e yer değiştirebilmektedir. Bu nedenle kullanılan ontoloji tabanlı ayrıştırıcı ile &ccedil;ıkarımı yapılması istenilen varlıkların c&uuml;mle i&ccedil;indeki pozisyonundan bağımsız olarak bulunması hedeflenmiştir. Test belgeleri yazılı bankacılık talimatlarını, sık u&ccedil;anlar e-postlarını ve &ouml;ğrenci dilek&ccedil;elerini i&ccedil;ermektedir. Bu belgeler serbest metin, tablolu, listeli ve maddesel yapıda veriler i&ccedil;ermektedir. Deneysel sonu&ccedil;lar &ouml;nerilen mimarinin kısıtlı belge alanları i&ccedil;in, belge modeli tanıma, varlıkların ve alan eylemlerinin &ccedil;ıkarımı konularında y&uuml;ksek başarı elde ettiğini g&ouml;stermiştir. &nbsp;Anahtar Kelimeler: Ontoloji tabanlı bilgi &ccedil;ıkarımı, belge yapı analizi, varlık tanıma, doğal dil anlama

A hybrid expert system approach for evaluation systems

Sistemlerin, sentetik ortamların, insanların performansının değerlendirilmesi genellikle karmaşık olup &ccedil;ok zaman gerektirmektedir. Mevcut değerlendirme sistemleri belli bir alana y&ouml;nelik olarak geliştirilmişlerdir ve sistemin değerlendirme sonu&ccedil;larına nasıl ulaştığını a&ccedil;ıklamazlar. Elde edilen yeni değerlendirme bilgilerinin, değerlendirme sisteminde g&uuml;ncellenmesi kolay değildir. Değerlendirme s&uuml;reci, uzmanlık gerektirmektedir. Fakat uzmanlar az sayıda olup, bilgilerinin bilgisayar ortamına aktarılarak daha fazla istifade edilmeleri gerekir. Bu &ccedil;alışmada, değerlendirme s&uuml;recini kolaylaştıran, hızlandıran ve farklı alanlarda kullanılabilen&nbsp; &ldquo;Genel Değerlendirme Modeli&rdquo; ve &ldquo;Zeki Değerlendirme Sistemi&rdquo; (ZeDeS) geliştirildi. Bu kapsamda, farklı alanlardaki uzmanlardan elde edilen sezgisel bilgilerin ve farklı kaynaklardan elde edilen bilgilerin bilgisayarla değerlendirme ama&ccedil;lı kullanılabilmeleri i&ccedil;in bir y&ouml;ntem geliştirildi. Bu y&ouml;ntemde, değerlendirme bilgileri, değerlendirme ama&ccedil;larının, değerlendirme kurallarının, &ouml;l&ccedil;&uuml;mlerinin, metotlarının ve parametrelerinin referans modeli olarak ifade edildi. Melez uzman sistem ve bulanık mantıktan meydana gelen &ldquo;Zeki Değerlendirme Sistemi&rdquo;, &ouml;ğrencileri, eğitmenleri, işe başvuranları, bilgisayar tarafından meydana getirilmiş kuvvetler gibi sentetik kuvvetleri değerlendirdiği gibi ger&ccedil;ek sistemleri de değerlendirebilmekte olup &ldquo;Genel Değerlendirme Modeli&rdquo;ne ve değerlendirme ihtiya&ccedil;larına g&ouml;re geliştirildi. Değerlendirme bazı a&ccedil;ılardan belirsizlik i&ccedil;erdiğinden, değerlendirmede genel &ccedil;ıkarım i&ccedil;in bulanık mantıkla uzman sistemler beraber kullanıldı. ZeDeS, Hava Savunma Sistemi, &ouml;ğretici performansı, pilot performansı değerlendirmesi ve eleman se&ccedil;imi gibi &ccedil;eşitli alanlarda ilk defa olarak kullanıldı. Makalede bir Hava Savunma Sistemi değerlendirmesinin ZeDeS kullanılarak nasıl yapıldığı ayrıntılı şekilde verilmiştir. &nbsp;Anahtar Kelimeler: Zeki Değerlendirme Sistemi, yapay zek&acirc;, melez uzman sistem, bulanık mantık.Evaluation of systems, synthetic environments and human performance are generally complicated and time-consuming tasks. Evaluation is needed nearly for all engineering tasks and the obstacles related with evaluation are increased proportional with complexity. Existing evaluation systems are domain dependent and do not provide explanation on how the system reaches the evaluation results. Expertise is needed for the evaluation process. Elicited new evaluation information cannot be updated to the system easily. Forming an evaluation definition is a complicated and time-consuming task. Finding out and formulating the required knowledge from the domain for which the evaluation is to be performed, is generally difficult due to lack of structured approach. It is not only important to formulate the knowledge, but finding out the right source of knowledge is also essential. Structured knowledge architecture is especially important in order to utilize evaluation knowledge automatically, especially in distributed environments. In this study, Common Evaluation Model (CEM) and INtelligent Evaluation System (INES), which simplify, speed up the evaluation process and decrease the evaluation cost, were developed. The study indicates that it is possible to put knowledge related to evaluation into a structured format. In this scope, a methodology was developed to handle the heuristic knowledge of experts from different domains and information from different sources for evaluation purposes. In this method, evaluation knowledge was represented as a reference model of evaluation objectives, production rules, measures, methods and parameters. Evaluation Objectives indicate what is going to be evaluated. Evaluation rules are criteria used to assess the collected parameters or calculated evaluation measures. Evaluation parameters are variables needed for applying rules or calculating the result of methods. The results of methods are defined as measures in order to simplify the evaluation rules and provide reusability. Evaluation methods are the algorithms for analyzing the collected parameters or / and calculating measures used in the rules. CEM shows the relation between evaluation objectives, rules, measures, methods and parameters. Using Reference Model of Evaluation Knowledge and CEM decreases the number of evaluation rules that are necessary to perform an evaluation to the related application. CEM also simplifies the representation of evaluation knowledge. INES is a hybrid expert-fuzzy system and was developed based on CEM and evaluation needs. Before development of INES, AI techniques including expert systems, fuzzy logic, neural networks, genetic algorithms, intelligent agents and conventional programming were investigated and compared with respect to achieving high level requirements of Evaluation Systems. INES?s Knowledge Base (KB) and KB Editor were developed for forming, editing and updating evaluation knowledge. INES?s Inference Engine was developed for executing the evaluation definition, which includes evaluation objectives, production rules, measures, methods and parameters. Backward chaining technique was used for INES?s inferencing.  Some benefits of INES, which are mostly AI related, are speeding up the evaluation process, decreasing the evaluation cost, explaining the reason of evaluation results, modelling the uncertainty on an overall evaluation, providing reasoning on linguistic variables, providing a flexible structure, allow updating evaluation knowledge base without changing the source code, reducing the complexity associated with the evaluation and providing an objective and a reliable evaluation. INES was successful and was tested in the following conditions: Knowledge of experts from the related domain and knowledge (or information) from the related sources for evaluation purposes are existed. Identifying evaluation criteria from the expert knowledge and information from different sources is possible. INES was implemented for the first time in various areas from different domains such as evaluation of Air Defence System, instructor performance, personnel selection, and pilot performance. Evaluation of an Air Defence System using INES is given in the paper. As the evaluation includes uncertainty in some aspects, Fuzzy Logic was used for reasoning. But it was realized that Fuzzy Logic could be used to perform overall performance or assessment instead of the evaluation itself for complex tasks. In other words, fuzzy logic can be more beneficial and more easily used for overall evaluation of main objective instead of all aspects of evaluation. A lot of parameters for evaluation are required and writing a lot of rules for these parameters in fuzzy logic is not an efficient way. As more rules are needed for complex systems, it becomes increasingly difficult to relate these rules to the system. Therefore, fuzzy system was used at an abstract level of evaluation.   Keywords: Intelligent Evaluation System, artificial intelligence, hybrid expert-fuzzy system

Rationing Safe and Effective COVID-19 Vaccines: Allocating to States Proportionate to Population May Undermine Commitments to Mitigating Health Disparities

A central goal in the National Academies of Science, Engineering and Medicine’s (NASEM) framework for equitable COVID-19 vaccine allocation is to mitigate existing inequities, particularly those affecting economically worse-off racial and ethnic minorities. The Advisory Committee on Immunization Practice (ACIP) likewise notes that equity demands to “reduce, rather than increase, health disparities in each phase of vaccine distribution”. A crucial question in this regard is how vaccines should be distributed to states. The default is to allocate proportionate to population size. However, this approach risks increasing scarcity for worse-off populations in states where they represent above-average shares. To avoid lower odds of receiving a vaccine for worse-off groups, more vaccines could be given to states with larger shares of worse-off populations, and fewer to ones with smaller shares. We show here the consequences of allocating by these two different approaches