Miracle-dz/UniFAR-FTUs huggingface dataset:
Validating Temporal Behavior Models of Complex Real-Time Systems

When constructing a model of the behavior of a software system, model validation is necessary in order to assure tha t the model accuratly describes the system at an appropriate level of abstraction. How to validate a model is however not obvious, since a model is an abstraction of the real system. This paper presents an approach for validation of temporal behavior models, targeting complex industrial real-ti me systems. The paper also proposes a method for robustness analysis, how to determine if the model is robust with respect to the typical changes to the system.
Face Detection Based on Fuzzy Cascade Classifier with Scale-invariant Features

Viola et al. have introduced a rapid object detection framework based on a boosted cascade of simple feature classifiers. In this paper we extend their work and achieve two contributions. Firstly, we propose a novel feature definition and introduce a feature shape mask to represent it. The defined features are scale-invariant which means the features can be rescaled easily and reduce the performance degradation introduced by rounding. The feature shape mask can be computed efficiently and expanded conveniently, which can simulate feature shapes used by others and thus enriches the haar-like feature pool. Secondly, we present an improved cascade-structured classifier which is called fuzzy cascade classifier. The cascade-structured classifier owns the disadvantage of neglecting confidence of the prior stage classifiers while only using the binary output of prior stages. Motivated by fuzzy theory, we expand the output of each stage to three states: face, non-face, and potential face and set probability being face to each candidate window to make full use of the information of prior stages. Merged by voting, we improve the hit rate at similar false alarm rate. Keyword: Face detection, AdaBoost, Scale-invariant feature, Fuzzy cascade classifier
Alternating Direction Methods for Sparse Covariance Selection *

The mathematical model of the widely-used sparse covariance selection problem (SCSP) is an NP-hard combinatorial problem, whereas it can be well approximately by a convex relaxation problem whose maximum likelihood estimation is penalized by the L1 norm. This convex relaxation problem, however, is still numerically challenging, especially for large-scale cases. Recently, some efficient first-order methods inspired by Nesterov’s work have been proposed to solve the convex relaxation problem of SCSP. This paper is to apply the well-known alternating direction method (ADM), which is also a first-order method, to solve the convex relaxation of SCSP. Due to the full exploitation to the separable structure of a simple reformulation of the convex relaxation problem, the ADM approach is very efficient for solving large-scale SCSP. Our preliminary numerical results show that the ADM approach substantially outperforms existing first-order methods for SCSP.
Point registration via efficient convex relaxation

Point cloud registration is a fundamental task in computer graphics, and more specifically, in rigid and non-rigid shape matching. The rigid shape matching problem can be formulated as the problem of simultaneously aligning and labelling two point clouds in 3D so that they are as similar as possible. We name this problem the Procrustes matching (PM) problem. The non-rigid shape matching problem can be formulated as a higher dimensional PM problem using the functional maps method. High dimensional PM problems are difficult non-convex problems which currently can only be solved locally using iterative closest point (ICP) algorithms or similar methods. Good initialization is crucial for obtaining a good solution. We introduce a novel and efficient convex SDP (semidefinite programming) relaxation for the PM problem. The algorithm is guaranteed to return a correct global solution of the problem when matching two isometric shapes which are either asymmetric or bilaterally symmetric. We show our algorithm gives state of the art results on popular shape matching datasets. We also show that our algorithm gives state of the art results for anatomical classification of shapes. Finally we demonstrate the power of our method in aligning shape collections.
THE UNEXPLORED COMBINATIVE EFFECT OF SKILLS AND TECHNOLOGY ON FIRMS ’ PERFORMANCE

The aim of this paper is to add new findings to the knowledge based view of the firm, where the crosslearning ability of individuals and organizations plays a fundamental role in the determination of firms’ superior performances. Collective, non formal – informal, formal types of learning (learning drivers) contribute to shape the competitiveness of firms, especially in the present knowledge-based economy, where the necessity to respond effectively to frequent external shock (demand, technology, competitive environment driven) emphasizes the importance of being flexible and quickly adaptive. Nevertheless, focusing on learning capacities, and particularly on human skills, often leads to forget the existence of another equal important factor, which increases the explanatory power of the learning drivers: firms’ innovative intensity. This work explores the conjoint effect of learning drivers and innovative intensity on firms’ performance by showing some evidences from statistical data analysis on the Danish IDA (Integrated Database for Labour Market Research). A sample of firms belonging to the manufacturing industry is studied using data related to the year 1999. The paper proceeds as follows: firstly, the role and relevance of human resources in the determination of firm’s performance is presented. Secondly, a missing ring in the knowledge based view of the firm is detected: the R&D investments intensity. Thirdly, the data analysis process and the methodology adopted are illustrated. Finally, the results are presented and discussed. JEL – classification: J24; L2; L6; O3.
Towards 3-D model-based tracking and recognition of human movement: a multi-view approach

In this paper we describe our work on 3-D model-based tracking and recognition of human movement from real images. Our system has two major components. The rst component takes real image sequences acquired from multiple views and recovers the 3-D body pose at each time instant. The pose-recovery problem is formulated as a search problem and entails nding the pose parameters of a graphical human model for which its synthesized appearance is most similar to the actual appearance of the real human in the multi-view images. Currently, we use a best-rst search technique and chamfer matching as a fast similarity measure between synthesized and real edge images. The second component of our system deals with the representation and recognition of human movement patterns. The recognition of human movement patterns is considered as a classiication problem involving the matching of a test sequence with several reference sequences representing prototypical activities. A variation of dynamic time-warping is used to match movement patterns using 3-D joint angles as features. We illustrate our approach on real data acquired simultaneously from three views and data derived from stereo Moving Light Displays with diierent types of hand-gestures.
Performance analysis and tuning of variable-structure PID controllers for level process

A methodology of analysis of stability and performance of variable structure (VS) PID controllers is proposed. It is proposed that stability of the VS system can be approximately assessed via the describing function method. The describing function of the VS PID controller is derived. It is shown that the system with the VS PID controller is quasilinear. Tuning rules for VS PI controller for the level process are given. It is shown that the VS PI controller has higher performance than the conventional PI controller for the process considered.
The Celtic fringe of Britain: insights from small mammal phylogeography

Recent genetic studies have challenged the traditional view that the ancestors of British Celtic people spread from central Europe during the Iron Age and have suggested a much earlier origin for them as part of the human recolonization of Britain at the end of the last glaciation. Here we propose that small mammals provide an analogue to help resolve this controversy. Previous studies have shown that common shrews (Sorex araneus) with particular chromosomal characteristics and water voles (Arvicola terrestris) of a specific mitochondrial (mt) DNA lineage have peripheral western/northern distributions with striking similarities to that of Celtic people. We show that mtDNA lineages of three other small mammal species (bank vole Myodes glareolus, field vole Microtus agrestis and pygmy shrew Sorex minutus) also form a ‘Celtic fringe’. We argue that these small mammals most reasonably colonized Britain in a two-phase process following the last glacial maximum (LGM), with climatically driven partial replacement of the first colonists by the second colonists, leaving a peripheral geographical distribution for the first colonists. We suggest that these natural Celtic fringes provide insight into the same phenomenon in humans and support its origin in processes following the end of the LGM.
The Cumulus Parameterization Problem: Past, Present, and Future

Abstract A review of the cumulus parameterization problem is presented with an emphasis on its conceptual aspects covering the history of the underlying ideas, major problems existing at present, and possible directions and approaches for future climate models. Since its introduction in the early 1960s, there have been decades of controversies in posing the cumulus parameterization problem. In this paper, it is suggested that confusion between budget and advection considerations is primarily responsible for the controversies. It is also pointed out that the performance of parameterization schemes can be better understood if one is not bound by their authors' justifications. The current trend in posing cumulus parameterization is away from deterministic diagnostic closures, including instantaneous adjustments, toward prognostic or nondeterministic closures, including relaxed and/or triggered adjustments. A number of questions need to be answered, however, for the merit of this trend to be fully utilized. M.
Biological and biochemical characterization of a cloned Leu-3- cell surviving infection with the acquired immune deficiency syndrome retrovirus

Leu-3- cells that survive infection with the acquired immune deficiency syndrome (AIDS) retrovirus can be induced with IUdR to express infectious virus. A cellular clone (8E5), isolated by limiting dilution of a mass culture of survivor cells, was found to contain a single, integrated provirus that was constitutively expressed. Although IUdR treatment of 8E5 cells failed to induce infectious virus, cocultivation with Leu-3+ cells generated the characteristic syncytia associated with acute AIDS retrovirus infection. The single integrated copy of proviral DNA directs the synthesis of all major viral structural proteins except p64, as monitored by immunoblotting. The relationship of the 8E5 clone to viral latency and persistence is discussed.
Lipid droplets are central organelles for meiosis II progression during yeast sporulation

During meiosis II, lipids are remodeled and incorporated into a double-membrane structure termed the prospore membrane (PSM), which grows as it sequesters four haploid nuclei to form spores. Cellular organelle lipid droplets are recruited to the PSM, where they play an active role in organizing membrane morphogenesis.
The Relationship between Self-Determined Motivation, Dietary Restraint, and Disinhibition and their Impact on Eating Behaviors, Weight Loss, and Weight Loss Maintenance in a Behavioral Weight Loss Program

Robert A. Carels, Advisor While research indicates that many overweight and obese individuals may have difficulty losing weight and maintaining weight loss, the factors that contribute to poor treatment outcome are unclear. Three individual factors that may impact the ability to lose weight and maintain weight loss are an individual’s 1) level of intrinsic versus extrinsic motivation for healthy eating, 2) dietary restraint, and 3) disinhibition. However, research on these factors is equivocal. This study seeks to understand whether greater self-determined motivation for healthy eating, higher dietary restraint, and lower disinhibition are associated with healthier eating behaviors (i.e., increased fruit and vegetable intake and decreased fat intake) and therefore greater weight loss and weight loss maintenance. The study also seeks to understand the relationship between selfdetermined motivation, dietary restraint, and disinhibition. Participants in the current study were 36 obese, sedentary individuals participating in an 18-week behavioral weight loss program. The current study found that post-treatment restraint and increases in restraint from baseline to follow-up were significantly associated with greater weight loss at 18 weeks and six months post-treatment. These findings suggest that participation in a weight loss program may increase dietary restraint, which in turn aids in weight loss and weight loss maintenance.
Vision Based SLAM for Mobile Robot Navigation Using Distributed Filters

Simultaneous Localization and Mapping (SLAM) has been developed for mobile robot applications to obtain navigation information. SLAM is a strategy for building up maps in unknown environments and figuring out its position without any prior map information. To implement SLAM, various kinds of sensors such as laser range finders, ultrasonic sensors, vision sensors, etc. (Sheng Fu et al., 2007) can be considered. Each configuration often depends upon the required performance and cost condition. In this chapter, we suggest a vision-based SLAM method to improve the navigation performance of mobile robot. It consists of a set of vision sensors and encoders which are equipped on mobile robot’s wheels (Leonard & Durrant-Whyte, 1991). The heading and position of a mobile robot can be independently estimated with only 2 encoders. However the result often yields large inaccuracies due to errors and the noise of sensors (i.e. a vision sensor and encoders). On the other hand, as the vision sensor is incorporated, a feature point tracking algorithm must be used (it’s not mentioned in this chapter, because it’s out of focus). In the integrated system, the relative position between feature points and the mobile robot is continuously estimated using information (i.e. feature points), so the position and heading errors are compensated using the filter estimation results (Hugh Durrant-Whyte & Tim Bailey, 2006). The Extended Kalman Filter (EKF) has been widely used for SLAM (Jing Wu & Hong Zhang, 2007). Additionally, a particle filter is occasionally used with landmark or geometric constraints to enhance performance (Sukhan Lee & Seongsoo Lee, 2006), because the measurement model of the vision sensor is not linear. In comparison with previous works, this chapter takes a distributed particle filter approach without landmark information and geometric constraints. The distributed particle filter is known to have powerful performance under nonlinear, multi-modal models and features points in varying conditions (Ristic et al., 2004). In addition to a vision sensor, range sensors are generally used to compute the 3-D position of feature points, because it is difficult to estimate the position in case of a single vision sensor system. This chapter uses a delayed initialization method instead of range sensors to compute the feature point position using single vision sensor system (Philip J. Schneider & David H. Eberly, 2003). 8
A Researcher's Guide to the National Statistics Socio-Economic Classification

PART ONE: INTRODUCTION TO THE NATIONAL STATISTICS SOCIO-ECONOMIC CLASSIFICATION The NS-SEC Described - David Rose and David J Pevalin The NS-SEC Explained - David Rose and David J Pevalin PART TWO: THE NS-SEC AS A MEASURE OF EMPLOYMENT RELATIONS - David Rose and David J Pevalin Empirical Variation in Employment Relations and Conditions - Abigail McKnight and Peter Elias Employment Relations, Employment Conditions and the NS-SEC - Colin Mills and Geoffrey Evans Criterion Validity and Occupational Classification - Anthony P M Coxon and Kimberly Fisher The Seven Economic Relations Measures and the NS-SEC An Initial Exploration of the Employment Conditions of Full-Time and Part-Time Workers Using the NS-SEC - Kimberly Fisher PART THREE: CONSTRUCT VALIDATION Earnings, Unemployment and the NS-SEC - Peter Elias and Abigail McKnight Examining Mortality Rates by NS-SEC Using Death Registration Data and the 1991 Census - Justine Fitzpatrick Social Class and the Incidence of Low-weight Births - David J Pevalin Gender, Health and Occupational Classifications in Working and Later Life - Helen Cooper and Sara Arber Old and New Social Class Measures - Anthony Heath, Jean Martin and Roeland Beerten A Comparison PART FOUR: FURTHER REFLECTIONS ON THE NS-SEC The Problem of Lower Sales, Services and Clerical Occupations - David Rose and David J Pevalin The NS-SEC - David Rose and David J Pevalin Overview and Conclusions
Is Accounting Conservatism Due to Debt or Equity Markets? An International Test of “Contracting” and “Value Relevance” Theories of Accounting

Acknowledgments We gratefully acknowledge the comments of Sudipta Basu, Christian Leuz and Jerry Zimmerman, the referee, and workshop participants at the Universities of Amsterdam and Chicago. We are grateful for financial support from the University of Chicago, Graduate School of Business. Abstract We provide a simple test of " costly contracting " and " value relevance theories " of accounting, using data on the importance of countries' debt and equity markets. Contracting (debt markets) theory predicts conditional conservatism, in the Basu (1997) sense of asymmetrically timelier loss recognition than gain recognition, a proxy for which is greater sensitivity of earnings to negative returns than to positive returns. Contracting theory also predicts the degree of asymmetry increases in the importance of a country's debt markets, but not in the importance of equity markets. In contrast, value relevance (equity markets) theory implies a symmetric and strong relation between earnings and returns, regardless of the sign of returns. Furthermore, contracting theory predicts that unconditional conservatism, in the sense of unconditionally low earnings and book values, does not increase contracting efficiency, and thus is unrelated to debt market importance. Data from a small cross-sectional sample of 22 countries are consistent with all of the predictions of " costly contracting " theory.
An ellipsoidal calculus based on propagation and fusion

Presents an ellipsoidal calculus based solely on two basic operations: propagation and fusion. Propagation refers to the problem of obtaining an ellipsoid that must satisfy an affine relation with another ellipsoid, and fusion to that of computing the ellipsoid that tightly bounds the intersection of two given ellipsoids. These two operations supersede the Minkowski sum and difference, affine transformation and intersection tight bounding of ellipsoids on which other ellipsoidal calculi are based. Actually, a Minkowski operation can be seen as a fusion followed by a propagation and an affine transformation as a particular case of propagation. Moreover, the presented formulation is numerically stable in the sense that it is immune to degeneracies of the involved ellipsoids and/or affine relations. Examples arising when manipulating uncertain geometric information in the context of the spatial interpretation of line drawings are extensively used as a testbed for the presented calculus.
Understanding the Role of Thermography in Energy Auditing: Current Practices and the Potential for Automated Solutions

The building sector accounts for 41% of primary energy consumption in the US, contributing an increasing portion of the country's carbon dioxide emissions. With recent sensor improvements and falling costs, auditors are increasingly using thermography-infrared (IR) cameras-to detect thermal defects and analyze building efficiency. Research in automated thermography has grown commensurately, aimed at reducing manual labor and improving thermal models. Though promising, we could find no prior work exploring the professional auditor's perspectives of thermography or reactions to emerging automation. To address this gap, we present results from two studies: a semi-structured interview with 10 professional energy auditors, which includes design probes of five automated thermography scenarios, and an observational case study of a residential audit. We report on common perspectives, concerns, and benefits related to thermography and summarize reactions to our automated scenarios. Our findings have implications for thermography tool designers as well as researchers working on automated solutions in robotics, computer science, and engineering.
Remote Collaboration With Augmented and Virtual Reality Interfaces

Some applications require a person in a remote location (the trainer), to instruct another person (the trainee) on how to put together a number of objects according to a precise set of spatial relationships. In this paper we report the results of using a collaborative Mixed Reality application that allows the trainer to manipulate the virtual objects in a virtual environment. At the same time, the trainee observes the virtual object manipulation as means to move the real objects accordingly. The trainer uses a Virtual Reality interface and the trainee uses an Augmented Reality one. The results show that, even though the time to complete the task using the application is longer, users perceive that collaboration using a similar application in the real world could make collaboration easier.
Subclass Problem-Dependent Design for Error-Correcting Output Codes

A common way to model multiclass classification problems is by means of Error-Correcting Output Codes (ECOCs). Given a multiclass problem, the ECOC technique designs a code word for each class, where each position of the code identifies the membership of the class for a given binary problem. A classification decision is obtained by assigning the label of the class with the closest code. One of the main requirements of the ECOC design is that the base classifier is capable of splitting each subgroup of classes from each binary problem. However, we cannot guarantee that a linear classifier model convex regions. Furthermore, nonlinear classifiers also fail to manage some type of surfaces. In this paper, we present a novel strategy to model multiclass classification problems using subclass information in the ECOC framework. Complex problems are solved by splitting the original set of classes into subclasses and embedding the binary problems in a problem-dependent ECOC design. Experimental results show that the proposed splitting procedure yields a better performance when the class overlap or the distribution of the training objects conceal the decision boundaries for the base classifier. The results are even more significant when one has a sufficiently large training size.
AnswerFinder : Question Answering from your Desktop

For many years Internet search engines have made a valiant attempt at quickly finding documents relevant to a users query. As the size of the Internet continues to grow, however, these search engines are returning more and more documents for a single query, leaving the user to wade through a vast amount of text. What is required are a new range of systems that are not only easy to use but are capable of returning just the answer to the user’s question. The AnswerFinder application outlined in this paper attempts to meet both of these requirements.