nils-herrmann/clean_scirepeval huggingface dataset:
Optical Communication in Space: Challenges and Mitigation Techniques

In recent years, free space optical (FSO) communication has gained significant importance owing to its unique features: large bandwidth, license free spectrum, high data rate, easy and quick deployability, less power, and low mass requirements. FSO communication uses optical carrier in the near infrared band to establish either terrestrial links within the Earth’s atmosphere or inter-satellite/deep space links or ground-to-satellite/satellite-to-ground links. It also finds its applications in remote sensing, radio astronomy, military, disaster recovery, last mile access, backhaul for wireless cellular networks, and many more. However, despite of great potential of FSO communication, its performance is limited by the adverse effects (viz., absorption, scattering, and turbulence) of the atmospheric channel. Out of these three effects, the atmospheric turbulence is a major challenge that may lead to serious degradation in the bit error rate performance of the system and make the communication link infeasible. This paper presents a comprehensive survey on various challenges faced by FSO communication system for ground-to-satellite/satellite-to-ground and inter-satellite links. It also provides details of various performance mitigation techniques in order to have high link availability and reliability. The first part of this paper will focus on various types of impairments that pose a serious challenge to the performance of optical communication system for ground-to-satellite/satellite-to-ground and inter-satellite links. The latter part of this paper will provide the reader with an exhaustive review of various techniques both at physical layer as well as at the other layers (link, network, or transport layer) to combat the adverse effects of the atmosphere. It also uniquely presents a recently developed technique using orbital angular momentum for utilizing the high capacity advantage of optical carrier in case of space-based and near-Earth optical communication links. This survey provides the reader with comprehensive details on the use of space-based optical backhaul links in order to provide high capacity and low cost backhaul solutions.
A web accessibility report card for top international university web sites

University web pages play a central role in the activities of current and prospective postsecondary students. University sites that are not accessible may exclude people with disabilities from participation in educational, social and professional activities. In order to assess the current state of university web site accessibility, we performed a multi-method analysis of the home pages of 100 top international universities. Each site was analyzed for compliance with accessibility standards, image accessibility, alternate-language and text-only content, and quality of web accessibility statements. Results showed that many top universities continue to have accessibility problems. University web site accessibility also varies greatly across different countries and geographic regions. Remaining obstacles to universal accessibility for universities include low accessibility in non-English-speaking countries and absent or low-quality accessibility policies.
Weakly Supervised One-Shot Detection with Attention Siamese Networks

We consider the task of weakly supervised one-shot detection. In this task, we attempt to perform a detection task over a set of unseen classes, when training only using weak binary labels that indicate the existence of a class instance in a given example. The model is conditioned on a single exemplar of an unseen class and a target example that may or may not contain an instance of the same class as the exemplar. A similarity map is computed by using a Siamese neural network to map the exemplar and regions of the target example to a latent representation space and then computing cosine similarity scores between representations. An attention mechanism weights different regions in the target example, and enables learning of the one-shot detection task using the weaker labels alone. The model can be applied to detection tasks from different domains, including computer vision object detection. We evaluate our attention Siamese networks on a oneshot detection task from the audio domain, where it detects audio keywords in spoken utterances. Our model considerably outperforms a baseline approach and yields a 42.6% average precision for detection across 10 unseen classes. Moreover, architectural developments from computer vision object detection models such as a region proposal network can be incorporated into the model architecture, and results show that performance is expected to improve by doing so.
Cyber Security using Game theory

Cyber Security is a complex concept that depends on the domain knowledge and requires cognitive abilities to determine possible threats from large amount of network data. Strengthening the security and resilience of cyberspace has become an important homeland security mission. Game theory is famous theory for detecting the threats as well as preventing the threats. In analysis various attack strategies can be considered such as inflation, deflation and Oscillation. Game theory provides the basic training and awareness of key algorithmic principles and lessons learned. In Game theory, the defense strategies are outlier detection and Adaptive Threshold selection. Using game theory the user can easily detect the intruders and provide the solution for the problems in step by step manner, which is easy and understandable language.
Structural Inertia and Organizational Change Revisited III : The Evolution of Organizational Inertia ∗

Building on a formal theory of the structural aspects of organizational change initiated in Hannan, Pólos, and Carroll (2002a, 2002b), this paper focuses on structural inertia. We define inertia as a persistent organizational resistance to changing architectural features. We examine the evolutionary consequences of architectural inertia. The main theorem holds that selection favors architectural inertia in the sense that the median level of inertia in cohort of organizations presumably increases over time. A second theorem holds that the selection intensity favoring architectural inertia is greater when foresight about the consequences of changes is more limited. According to the prior theory of Hannan, Pólos, and Carroll (2002a, 2002b), foresight is limited by complexity and opacity. Thus it follows that the selection intensity favoring architectural inertia is stronger in populations composed of complex and opaque organizations than in those composed of simple and transparent ones. ∗This research was supported by fellowships from the Netherlands Institute for Advanced Study and by the Stanford Graduate School of Business Trust, ERIM at Erasmus University, and the Centre for Formal Studies in the Social Sciences at Lorand Eötvös University. We benefited from the comments of Jim Baron, Dave Barron, Gábor Péli, Joel Podolny, and the participants in the workshop of the Nagymaros Group on Organizational Ecology and in the Stanford Strategy Conference. †Stanford University ‡Loránd Eötvös University, Budapest and Erasmus University, Rotterdam §Stanford University
Wearable Privacy: Skeletons in The Data Closet

Equipped with sensors that are capable of collecting physiological and environmental data continuously, wearable technologies have the potential to become a valuable component of personalized healthcare and health management. However, in addition to the potential benefits of wearable devices, the widespread and continuous use of wearables also poses many privacy challenges. In some instances, users may not be aware of the risks associated with wearable devices, while in other cases, users may be aware of the privacy-related risks, but may beunable to negotiate complicated privacy settings to meet their needs and preferences. This lack of awareness could have an adverse impact on users in the future, even becoming a "skeleton in the closet." In this work, we conducted 32 semi-structured interviews to understand how users perceive privacy in wearable computing. Results suggest that user concerns toward wearable privacy have different levels of variety ranging from no concern to highly concerned. In addition, while user concerns and benefits are similar among participants in our study, these variablesshould be investigated more extensively for the development of privacy enhanced wearable technologies.
Automated Game Design via Conceptual Expansion

Automated game design has remained a key challenge within the field of Game AI. In this paper, we introduce a method for recombining existing games to create new games through a process called conceptual expansion. Prior automated game design approaches have relied on hand-authored or crowdsourced knowledge, which limits the scope and applications of such systems. Our approach instead relies on machine learning to learn approximate representations of games. Our approach recombines knowledge from these learned representations to create new games via conceptual expansion. We evaluate this approach by demonstrating the ability for the system to recreate existing games. To the best of our knowledge, this represents the first machine learning-based automated game design system.
Improving Adaptive Game Ai with Evolutionary Learning

Game AI is defined as the decision-making process of computercontrolled opponents in computer games. Adaptive game AI can improve the entertainment provided by computer games, by allowing the computer-controlled opponents to fix automatically weaknesses in the game AI, and to respond to changes in humanplayer tactics online, i.e., during gameplay. Successful adaptive game AI is based invariably on domain knowledge of the game it is used in. Dynamic scripting is an algorithm that implements adaptive game AI. The domain knowledge used by dynamic scripting is stored in a rulebase with manually designed rules. In this paper we propose the use of an offline evolutionary algorithm to enhance the performance of adaptive game AI, by evolving new domain knowledge. We empirically validate our proposal, using dynamic scripting as adaptive game AI in a real-time-strategy (RTS) game, in three steps: (1) we implement and test dynamic scripting in an RTS game; (2) we use an offline evolutionary algorithm to evolve new tactics that are able to deal with optimised tactics, which dynamic scripting cannot defeat using its original rulebase; (3) we translate the evolved tactics to rules in the rulebase, and test dynamic scripting with the revised rulebase. The empirical validation shows that the revised rulebase yields a significantly improved performance of dynamic scripting compared to the original rulebase. We therefore conclude that offline evolutionary learning can be used to improve the performance of
Content Differences for Abstract and Concrete Concepts

Concept properties are an integral part of theories of conceptual representation and processing. To date, little is known about conceptual properties of abstract concepts, such as idea. This experiment systematically compared the content of 18 abstract and 18 concrete concepts, using a feature generation task. Thirty-one participants listed characteristics of the concepts (i.e., item properties) or their relevant context (i.e., context properties). Abstract concepts had significantly fewer intrinsic item properties and more properties expressing subjective experiences than concrete concepts. Situation components generated for abstract and concrete concepts differed in kind, but not in number. Abstract concepts were predominantly related to social aspects of situations. Properties were significantly less specific for abstract than for concrete concepts. Thus, abstractness emerged as a function of several, both qualitative and quantitative, factors.
Academic self-efficacy mediates the effects of school psychological climate on academic achievement.

This study investigated the effects of proximal and distal constructs on adolescent's academic achievement through self-efficacy. Participants included 482 ninth- and tenth- grade Norwegian students who completed a questionnaire designed to assess school-goal orientations, organizational citizenship behavior, academic self-efficacy, and academic achievement. The results of a bootstrapping technique used to analyze relationships between the constructs indicated that school-goal orientations and organizational citizenship predicted academic self-efficacy. Furthermore, school-goal orientation, organizational citizenship, and academic self-efficacy explained 46% of the variance in academic achievement. Mediation analyses revealed that academic self-efficacy mediated the effects of perceived task goal structure, perceived ability structure, civic virtue, and sportsmanship on adolescents' academic achievements. The results are discussed in reference to current scholarship, including theories underlying our hypothesis. Practical implications and directions for future research are suggested.
Man ’ s search for meaning : The case of Legos

We investigate how perceived meaning influences labor supply. In a laboratory setting, we manipulate the perceived meaning of simple, repetitive tasks and find a strong influence on subjects’ labor supply. Despite the fact that the wage and the task are identical across the conditions in each experiment, subjects in the less meaningful conditions exhibit reservation wages that are consistently much higher than the subjects in the more meaningful conditions. The result replicates across different types of tasks. Moreover, in the more meaningful conditions, subjects’ productivity influences labor supply more strongly.
Relationship Among Physical Activity Level, Mood and Anxiety States and Quality of Life in Physical Education Students

Physical activity level (PAL) is known to play an important role in reducing risk factors associated with sedentarism, in addition to improving the mental health and health-related quality of life (HRQL).



Investigate the relationship of PAL and their domains with HRQL, mood state (MS) and anxiety.  140 Physical Education students (23.6 ± 3.7 years) were evaluated. The Baecke Habitual Physical Activity and Quality of Life (QOL-36) questionnaires, State-Trait Anxiety Inventories (STAI-S and STAI-T) and Profile of Mood States (POMS) scale were used to investigate PAL, HRQL and mental health indicators. Pearson's correlation coefficient examined the association between PAL and both mental health and HRQL parameters.



There was a correlation between state anxiety and both the domain leisure-time physical activity (LTPA) (p = 0.013) and total PAL score (p = 0.010). In relation to MS, a negative correlation was found between LTPA and total mood disorder (TMD) (p = 0.004). However, there were positive correlations between the vigor subscale and both LTPA (p=0.001) and total PAL (p=0.019). With respect to HRQL, analysis of the relationship between LTPA and total PAL demonstrated positive coefficients with the physical component summary (PCS) (p=0.000; p = 0.005), mental component summary (MCS) (p = 0.000; p = 0.006) and total HRQL (p = 0.000; p = 0.003).



The findings suggest that the rise in LTPA was related to an increase in HRQL and MS. However, PAL was positively related to anxiety.
Universal lossless data compression algorithms

4 Improved compression algorithm based on the Burrows–Wheeler transform 61 4.1 Modifications of the basic version of the compression algorithm. 61 5 Conclusions 141 iii Acknowledgements 145 Bibliography 147 Appendices 161 A Silesia corpus 163 B Implementation details 167 C Detailed options of examined compression programs 173 D Illustration of the properties of the weight functions 177 E Detailed compression results for files of different sizes and similar contents 185 List of Symbols and Abbreviations 191 List of Figures 195 List of Tables 198 Index 200 Chapter 1 Preface I am now going to begin my story (said the old man), so please attend. Contemporary computers process and store huge amounts of data. Some parts of these data are excessive. Data compression is a process that reduces the data size, removing the excessive information. Why is a shorter data sequence often more suitable? The answer is simple: it reduces the costs. A full-length movie of high quality could occupy a vast part of a hard disk. The compressed movie can be stored on a single CD-ROM. Large amounts of data are transmitted by telecommunication satellites. Without compression we would have to launch many more satellites that we do to transmit the same number of television programs. The capacity of Internet links is also limited and several methods reduce the immense amount of transmitted data. Some of them, as mirror or proxy servers, are solutions that minimise a number of transmissions on long distances. The other methods reduce the size of data by compressing them. Multimedia is a field in which data of vast sizes are processed. The sizes of text documents and application files also grow rapidly. Another type of data for which compression is useful are database tables. Nowadays, the amount of information stored in databases grows fast, while their contents often exhibit much redundancy. Data compression methods can be classified in several ways. One of the most important criteria of classification is whether the compression algorithm 1 2 CHAPTER 1. PREFACE removes some parts of data which cannot be recovered during the decompres-sion. The algorithms removing irreversibly some parts of data are called lossy, while others are called lossless. The lossy algorithms are usually used when a perfect consistency with the original data is not necessary after the decom-pression. Such a situation occurs for example in compression of video or picture data. If the recipient of the video …
Internet Addiction and its Psychosocial Risks (Depression, Anxiety, Stress and Loneliness) among Iranian Adolescents and Young Adults: A Structural Equation Model in a Cross-Sectional Study

Internet addiction has become an increasingly researched area in many Westernized countries. However, there has been little research in developing countries such as Iran, and when research has been conducted, it has typically utilized small samples. This study investigated the relationship of Internet addiction with stress, depression, anxiety, and loneliness in 1052 Iranian adolescents and young adults. The participants were randomly selected to complete a battery of psychometrically validated instruments including the Internet Addiction Test, Depression Anxiety Stress Scale, and the Loneliness Scale. Structural equation modeling and Pearson correlation coefficients were used to determine the relationship between Internet addiction and psychological impairments (depression, anxiety, stress and loneliness). Pearson correlation, path analysis, multivariate analysis of variance (MANOVA), and t-tests were used to analyze the data. Results showed that Internet addiction is a predictor of stress, depression, anxiety, and loneliness. Findings further indicated that addictive Internet use is gender sensitive and that the risk of Internet addiction is higher in males than in females. The results showed that male Internet addicts differed significantly from females in terms of depression, anxiety, stress, and loneliness. The implications of these results are discussed.
ITEM RESPONSE THEORY

Item Response Theory is based on the application of related mathematical models to testing data. Because it is generally regarded as superior to classical test theory, it is the preferred method for developing scales, especially when optimal decisions are demanded, as in so-called high-stakes tests. The term item is generic: covering all kinds of informative item. They might be multiple choice questions that have incorrect and correct responses, but are also commonly statements on questionnaires that allow respondents to indicate level of agreement (a rating or Likert scale), or patient symptoms scored as present/absent, or diagnostic information in complex systems. IRT is based on the idea that the probability of a correct/keyed response to an item is a mathematical function of person and item parameters. The person parameter is construed as (usually) a single latent trait or dimension. Examples include general intelligence or the strength of an attitude.
Assessing Business-IT Alignment Maturity

Business and IT practitioners, researchers, and consultants have been asking for an effective tool to assess IT-business alignment. Until now, none was available. This chapter introduces the strategic alignment maturity assessment. This assessment tool is based on the authors research and consulting experience that identified the major enablers and inhibitors in the achievement of business-IT alignment and the methodology that leverages the most important enablers and inhibitors. Alignment focuses on the activities that management performs to achieve cohesive goals across the IT (information technology) and other functional (e.g., finance, marketing, H/R, manufacturing) organizations. Therefore, alignment addresses both how IT is in harmony with the business, and how the business should/could be in harmony with IT. Alignment evolves to a relationship where IT and business adapt their strategies together. Achieving alignment is evolutionary and dynamic. IT requires strong support from senior management, good working relationships, strong leadership, appropriate prioritization, trust, and effective communication, as well as a thorough understanding of the business and technical environments. Achieving and sustaining alignment demands focusing on maximizing the enablers and minimizing the inhibitors. The purpose of this chapter is to discuss an approach for assessing the maturity of the business-IT alignment. Once the maturity is understood, an organization can identify opportunities for enhancing the harmonious relationship of business and IT.  Decades have passed. Billions of dollars have been invested on information technology (IT). Today, every organization is in the information business. Alignment  applying IT in an appropriate and timely way, in harmony with business strategies, goals and needs  remains a key concern of business executives. This This chapter appears in the book, Strategic Information Technology: Opportunities for Competitive Advantage by Raymond Papp.
AGRA: An Analysis-Generation-Ranking Framework for Automatic Abbreviation from Paper Titles

People sometimes choose word-like abbreviations to refer to items with a long description. These abbreviations usually come from the descriptive text of the item and are easy to remember and pronounce, while preserving the key idea of the item. Coming up with a nice abbreviation is not an easy job, even for human. Previous assistant naming systems compose names by applying hand-written rules, which may not perform well. In this paper, we propose to view the naming task as an artificial intelligence problem and create a data set in the domain of academic naming. To generate more delicate names, we propose a three-step framework, including description analysis, candidate generation and abbreviation ranking, each of which is parameterized and optimizable. We conduct experiments to compare different settings of our framework with several analysis approaches from different perspectives. Compared to online or baseline systems, our framework could achieve the best results.