Miracle-dz/UniFAR-FTUs huggingface dataset:
Inferring noncompensatory choice heuristics

Human decision making is a topic of great interest to marketers, psychologists, economists, and others. People are often modeled as rational utility maximizers with unlimited mental resources. However, due to the structure of the environment as well as cognitive limitations, people frequently use simplifying heuristics for making quick yet accurate decisions. In this research, we apply discrete optimization to infer from observed data if a person is behaving in way consistent with a choice heuristic (e.g., a noncompensatory lexicographic decision rule). We analyze the computational complexity of several inference related problems, showing that while some are easy due to possessing a greedoid language structure, many are hard and likely do not have polynomial time solutions. For the hard problems we develop an exact dynamic programming algorithm that is robust and scalable in practice, as well as analyze several local search heuristics. We conduct an empirical study of SmartPhone preferences and find that the behavior of many respondents can be explained by lexicographic strategies. Furthermore, we find that lexicographic decision rules predict better on holdout data than some standard compensatory models. Finally, we look at a more general form of noncompensatory decision process in the context of consideration set formation. Specifically, we analyze the computational complexity of rule-based consideration set formation, develop solution techniques for inferring rules given observed consideration data, and apply the techniques to a real dataset. Thesis Supervisor: James B. Orlin Title: Edward Pennell Brooks Professor of Operations Research
Arabic supervised learning method using N-gram

Purpose – Recently, classification of Arabic documents is a real problem for juridical centers. In this case, some of the Lebanese official journal documents are classified, and the center has to classify new documents based on these documents. This paper aims to study and explain the useful application of supervised learning method on Arabic texts using N‐gram as an indexing method (n = 3). Design/methodology/approach – The Lebanese official journal documents are categorized into several classes. Supposing that we know the class(es) of some documents (called learning texts), this can help to determine the candidate words of each class by segmenting the documents.Findings – Results showed that N‐gram text classification using the cosine coefficient measure outperforms classification using Dice's measure and TF*ICF weight. Then it is the best between the three measures but it still insufficient. N‐gram method is good, but still insufficient for the classification of Arabic documents, and then it is necess.
Stochastic Optimality Theory , local search , and Bayesian learning of hierarchical models

The Gradual Learning Algorithm (GLA) (Boersma and Hayes, 2001) can be seen as a stochastic local search method for learning Stochastic OT grammars. This paper tries to achieve the following goals: first, in response to the criticism in (Keller and Asudeh, 2002), we point out that the computational problem of learning stochastic grammars does have a general approximate solution (Lin, 2005). Second, we argue that the Bayesian framework on which the general solution is based connects the perspective of learning a probability distribution over grammars with local search strategies. Third, we also suggest that a general class of hierarchical probabilistic models may be suitable for marrying linguistic formalism with probability distribution.
GIST : A CLINICOPATHOLOGICAL ANALYSIS OF 10 CASES

GISTs account for approximately 80% of gastrointestinal mesenchymal tumours. The literature about GIST remains confusing because tumour classification and terminology are continually refined. Furthermore, the exact definition of GIST varies among authors. Mostly occur in the stomach and small intestine with rare occurrence in the rectum (5%), colon (1%), oesophagus and appendix. The diagnosis of GIST is currently based on morphologic features and immunohistochemical demonstration of KIT (CD 117). Early resection is treatment of choice. STI-571 (Imatinib), a KIT tyrosine kinase inhibitor has recently shown promise in the treatment of metastatic GISTs. The three key prognostic factors have been mitotic rate, tumour size and site. The five year survival rate declines and prognosis becomes poor with increase in the size and mitotic activity. This article deals with the study of GIST at different sites with varied clinical, radiodiagnostic and histopathological findings, and treatment approach. We have analysed 10 different cases of GIST and have drawn possible conclusions.
Teaching Information Security Policy

Information security education includes many topics, some technical and some managerial. One topic that is central to all of these is that of information security policy. Before policy can become the centerpiece of information security education, a coherent model that can encompass the broad range of the topic is needed. In addition to the essential elements of policy, students also need to be exposed to the best practices for managing information security policy. Once a teaching model for policy is selected, faculty can use lectures, project assignments and lab exercises to reinforce student learning.
Performance bounds for distributed memory multithreaded architectures

In distributed memory multithreaded systems, the long memory latencies and unpredictable synchronization delays are tolerated by context switching, i.e., by suspending the current thread and switching the processor to another thread waiting for execution. Simple analytical upper bounds on performance measures are derived using throughput analysis and extreme values of some model parameters. These derived bounds are compared with performance results obtained by simulation of a detailed model of the analyzed architecture.
MODAL CLUSTERING IN UNIVARIATE , CONJUGATE DIRICHLET PROCESS MIXTURE MODELS

The Dirichlet Process mixture (DPM) model is a popular nonparametric Bayesian tool for modeling unknown distributions through mixtures of components. Integrating out the latent location variables in a DPM model leads to a product partition model. This paper describes a modefinding algorithm which quickly finds either the maximizer of the partition posterior or the maximizer of the partition likelihood in a class of product partition models. Sufficient conditions when the algorithm can be used are given and these conditions are shown to be satisfied in several univariate, conjugate DPM models. Clustering observations based on a modal partition is a modelbased clustering procedure which, prior to this work, could only be approximated. The proposed procedure is demonstrated in a microarray dataset of expression levels of more than 10,000 genes.
MobileGrid: capacity-aware topology control in mobile ad hoc networks

Since wireless mobile ad hoc networks are arbitrarily and dynamically deployed, the network performance may be affected by many unpredictable factors such as the total number of nodes, physical area of deployment, and transmission range on each node. Previous research results only focus on maximizing power efficiency through dynamically adjusting the transmission range on each node. Via extensive performance evaluations, we have observed that the network performance is linked with a single parameter, the network contention index, which each node may estimate in a fully distributed fashion. This paper introduces the definition of such a parameter, which is derived from relevant parameters such as the number of nodes and the transmission range on each node. With the presence of node mobility, we present a detailed study of the effects of contention index on the network performance, with respect to network capacity and power efficiency. We have observed that the capacity is a concave function of the contention index. We further show that the impact of node mobility is minimal on the network performance when the contention index is high. Based on these important observations, we present MobileGrid, a fully distributed topology control algorithm that attempts to achieve the best possible network capacity, by maintaining optimal contention index via dynamically adjusting the transmission range on each of the nodes in the network.
Cost allocation : methods, principles, applications

This book provides a theoretical framework for systematically evaluating the "pros" and "cons" of various methods. It also includes a series of case studies in cost allocation to give a sense of the real problems encountered in implementation. Among the examples treated are telecommunications pricing, multipurpose reservoir charges, and airport landing fees. Finally several articles address the broader fairness issues inherent in the pricing of public services. The history of the notion of the "just price" from medieval to modern times is discussed, together with observations on what principles seem to guide decisions in telecommunications rate cases in the United States. The connections between cost allocation, efficiency, and entry in the telecommunications market are also examined in two different contexts: the U.S. and France. The overall aim of the book is to provide theoretical foundations for using specific methods, to examine the distributional and fairness issues involved in cost allocation, and to give a sense of the practical problems encountered in implementation. The book will appeal to practitioners interested in what allocation methods are available, and to theorists concerned with their axiomatic foundations.
Computing Similarity between a Pair of Trajectories

With recent advances in sensing and tracking technology, trajectory data is becoming increasingly pervasive and analysis of trajectory data is becoming exceedingly important. A fundamental problem in analyzing trajectory data is that of identifying common patterns between pairs or among groups of trajectories. In this paper, we consider the problem of identifying similar portions between a pair of trajectories, each observed as a sequence of points sampled from it. We present new measures of trajectory similarity --- both local and global --- between a pair of trajectories to distinguish between similar and dissimilar portions. Our model is robust under noise and outliers, it does not make any assumptions on the sampling rates on either trajectory, and it works even if they are partially observed. Additionally, the model also yields a scalar similarity score which can be used to rank multiple pairs of trajectories according to similarity, e.g. in clustering applications. We also present efficient algorithms for computing the similarity under our measures; the worst-case running time is quadratic in the number of sample points. Finally, we present an extensive experimental study evaluating the effectiveness of our approach on real datasets, comparing with it with earlier approaches, and illustrating many issues that arise in trajectory data. Our experiments show that our approach is highly accurate in distinguishing similar and dissimilar portions as compared to earlier methods even with sparse sampling.
On the Role of Bank Competition for Corporate Finance and Corporate Control in Transition Economies

Banks play a central role in financing and monitoring firms in transition economies. This study examines how bank competition affects the efficiency of credit allocation; monitoring of firms; and the firms' restructuring effort. In our model, banks compete to finance an investment project with uncertain return. By screening the firm a bank learns about its profitability. Surprisingly, it is found that an increase in bank competition need not reduce a bank's screening incentive even though it lowers its expected profits. Furthermore, competition has a positive impact on the firms restructuring efforts. This suggests a positive role for bank competition in transition economies.
IN FAVOR OF CROSS-CULTURAL TRANSFERABILITY OF TRAVEL-DEMAND MODELS. IN: NEW HORIZONS IN TRAVEL-BEHAVIOR RESEARCH

The paper provides two different types of cross-cultural transferability conclusions. The first, that a high degree of transferability can be expected at the general model-class level, given the utility maximizing behavioral underpinning. The second conclusion is that cross-cultural transferability of model-coefficient values is likely to be rejected in the majority of cases. However, the circumstances in which travel behavior experience is of value to decision makers usually require quick action and do not allow extensive studies to be conducted, implying a need for some very real tradeoffs between scientific rejection and mature policy recommendations. This leads to the recommendation that key transport study results be standardized and stored for retrieval by as many advisors and decision makers as possible around the world.
Trust differences across national-societal cultures: Much to do, or much ado about nothing?

Does trust and its development, functions and meaning, differ between people from different national–societal cultures? There is considerable anecdotal evidence and some theoretical argumentation to suggest it does, but are these supported by empirical research? This chapter reviews the available empirical evidence on the effects of national–societal culture on interpersonal trust. It focuses largely on quantitative empirical evidence to consider the extent to which, and the ways in which, interpersonal trust differs across national–societal cultures. In every category of our review we found evidence of cross-cultural differences, particularly on generalized trust, and also evidence of trust universals across cultures. In evaluating these findings, we conclude that trust may operate as a variform universal and variform functional universal. We conclude with two proposed routes for future research, and implications for practice. Introduction To an ever-increasing extent, ‘work’ involves close interaction and cooperation with people who come from a national–societal cultural background different from one's own. This emerging reality of work can be attributed to a number of factors. First, with the unrelenting advance of globalization, more and more organizations are taking a global approach to operations, including the operation of overseas international joint ventures and alliances, working with offshore suppliers and customers, and conducting global searches for talent. Second, the advance of communication technologies such as e-mail and videoconferencing has fostered a movement toward global virtual teams involving individuals from a variety of different cultural backgrounds.
Effects of intermittent stimulation patterns on the sensation during electrocutaneous stimulation

For electrotactile displays to become useful for supplementary sensory feedback for transfemoral prosthesis users the interface needs to be optimized. A closer look is taken at the nature of adaptation during electrocutaneous stimulation. In this portion the effect of intermittent stimulation patterns on the sensation is investigated. Seven different intermittent stimulation signals and two continuous signals were applied to the subjects skin in random order. Each of the nine trials lasted for about fifteen minutes and during these trials the stimulation current was adjusted at 80% of the dynamic range, as recommended in a previous study. The Visual Analog Scale was used to record the course of sensation during the period of stimulation. Results suggest two things. One, a minimal stimulation time (Ton) of 0.5 seconds is required to reach a maximal sensation. Two, a minimal rest period of about 0.3 seconds is required in order to postpone the occurrence of full adaptation (Toff).
From Monads to Effects and Back Madoko sample – do not distribute

The combination of monads and effects leads to a clean and easy to reason programming paradigm. Monadic programming is easy to reason, but can be cumbersome, as it requires explicit lifting and binding. In this paper, we combine monads and effects within a single programming paradigm: we use monads to define the semantics of effect types, and then, use the effects to program with those monads. In particular, we implemented an extension to the effect type system of Koka [20] with user defined effects. We use a type-directed translation to automatically lift such effectful programs into monadic programs, by inserting bindand unit operations. As such, these user-defined effects are not just introducing a new effect type, but also enable full monadic abstraction and let us “take control of the semi-colon” in a typed and structured manner. We give examples of various abstractions like ambiguous computations and parsers. All examples have been implemented in the Koka language and we describe various implementation issues and optimization mechanisms.
Efficient object search for mobile robots in dynamic environments: Semantic map as an input for the decision maker

In this work we study the efficient search of objects in domestic environments, using probabilistic logic to represent uncertainty about object location and partially observable Markov decision processes (POMDP) for the decision-making process regarding the movements to be carried out by the robot to improve its belief about the object locations. We propose the use of a semantic map that stores information about the knowledge in the system and updates it, by an inference process, with sensor information received from the object recognition module. However, semantic maps are not capable of actively search for more information in the environment. For that reason a decision-making module, based on a POMDP framework, is integrated in the system. Several experiments were made in a realistic apartment test bed using every day objects and a mobile robot, showing that this hybrid solution makes the search process more efficient.
GENERALIZED QUANTUM RELATIVISTIC KINEMATICS: A STABILITY POINT OF VIEW

We apply Lie algebra deformation theory to the problem of identifying the stable form of the quantum relativistic kinematical algebra. As a warm up, given Galileo's conception of spacetime as input, some modest computer code we wrote zeroes in on the Poincare-plus-Heisenberg algebra in about a minute. Further ahead, along the same path, lies a three-dimensional deformation space, with an instability double cone through its origin. We give physical as well as geometrical arguments supporting our view that moment, rather than position operators, should enter as generators in the Lie algebra. With this identification, the deformation parameters give rise to invariant length and mass scales. Moreover, standard quantum relativistic kinematics of massive, spinless particles corresponds to non-commuting moment operators, a purely quantum effect that bears no relation to spacetime non-commutativity, in sharp contrast to earlier interpretations.
The Study on Construction of E-government Platform Based on SOA and Efficiency Comparison of Serving Model

Low entry cost and high expected returns in the E-Government boom in the recent decades in China. As E-government becomes a very active research area, a lot of solutions aiming to provide citizens, business partners and administrative staff with information more accessible, effective and accountable are being deployed. Yet, how to build a more effective serving platform of E-government and how to better serve citizens and enterprises still remains an open question. In this case, this paper analyzes the construction of E-government platform based on SOA and serving models of E-government, and makes an efficiency comparison of serving model.
Selecting Optimal Subset of Features for Student Performance Model

Educational data mining (EDM) is a new growing research area and the essence of data mining concepts are used in the educational field for the purpose of extracting useful information on the student behavior in the learning process. Classification methods like decision trees, rule mining, and Bayesian network, can be applied on the educational data for predicting the student behavior like performance in an examination. This prediction may help in student evaluation. As the feature selection influences the predictive accuracy of any performance model, it is essential to study elaborately the effectiveness of student performance model in connection with feature selection techniques. The main objective of this work is to achieve high predictive performance by adopting various feature selection techniques to increase the predictive accuracy with least number of features. The outcomes show a reduction in computational time and constructional cost in both training and classification phases of the student performance model.
Fractional Integration and Cointegration in the Japanese Exchange Rate Market

There is widespread agreement that the logarithmic spot and forward exchange rates are both integrated of order one (I(1)) variables, so that their corresponding returns are I(0) stationary. In this article, we examine this hypothesis for the Japanese market by means of fractional integration techniques. The results show that, although fractional degrees of integration are plausible in some cases, the confidence intervals include the unit root in both series. The possibility of the two variables being fractionally cointegrated is also examined throughout the differenced series. The empirical evidence supports this hypothesis, implying that there is a long run equilibrium relationship between the Japanese spot and forward exchange rates, with deviations from equilibrium being highly persistent.
Image Encryption Based on AES Key Expansion

The relentless growth of Internet and communication technologies has made the extensive use of images unavoidable. The specific characteristics of image like high transmission rate with limited bandwidth, redundancy, bulk capacity and correlation among pixels makes standard algorithms not suitable for image encryption. In order to overcome these limitations for real time applications, design of new algorithms that require less computational power while preserving a sufficient level of security has always been a subject of interest. This paper proposes an algorithm based on AES Key Expansion in which the encryption process is a bit wise exclusive or operation of a set of image pixels along with the a 128 bit key which changes for every set of pixels . The keys to be used are generated independently at the sender and receiver side based on AES Key Expansion process hence the initial key is alone shared rather than sharing the whole set of keys. The algorithm has been experimented with standard bench mark images proposed in USC-SIPI database. Experimental results and security analysis of the proposed algorithm shows that the proposed algorithm offers good resistance against brute force attack, key sensitivity tests and statistical crypt analysis.
Vision-based robust calibration for optical see-through head-mounted displays

We propose Vision-based Robust Calibration (ViRC) method for OSTHMDs equipped with a camera. In the ViRC method, calibration parameters are decomposed into off-line parameters that remain constant relative to the positional relationship between the camera and the virtual screen, and on-line parameters related to the user's eye. Calculating the off-line parameters beforehand reduces the number of unknown parameters in the on-line phase, giving robust protection against the user's misalignments during calibration. In the off-line phase, the approximate position of the user's eye is calculated using the PnP algorithm. In the online phase, the actual position of the user's eye is estimated from the approximate one by non-linear minimization. In our experiments, we show that the ViRC method can decrease reprojection error by as much as 83% compared with the conventional method based on the DLT algorithm.