Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey of Visualization of High-Dynamic-Range Images

This paper gives a survey of visualization of High-Dynamic-Range(HDR) images on typical display devices with limited dynamic range.Global tone-mapping methods,local tone-mapping methods and color appearance model based tone-mapping methods are compared,and drawbacks and strengths of all methods are given according to the authors' opinions.This survey can help potential users to choose the right method for displaying HDR images on the typical display devices,and can help researchers to find new methods to improve the displaying results of HDR images.
VOLATILITAS RETURN SAHAM DI INDONESIA : POLA DAN PERBANDINGAN DENGAN MALAYSA DAN SINGAPURA

During the last decade, volatility issues have been common tofics for stock market partisipants in line with increasing financial market liberalization, Why does volatility matter if excesive return volatility happened, it endangers stock market by blurring the usefulness of stock prices as a fair representative of company value (karolyi,2001). This paper will elaborate the pattern of return volatility in indonesia, especially in periode before and during the world financial crisis, malaysa and singapore, were taken into account for a comparison , By using student-t EGARCH the existence of the asymmetric effect on return volatility upon the market shock was well document, where volatility was more influenced by negative shocks rather than positive shocks. Its was also found that during the crisis, the shocks magnitude in indonesia was greater, as compared to that of malaysia and Singapore, nonetheless, in term of persistence, indonesia was in between malaysia and singapore.
Kształtowanie klimatu organizacyjnego niwelującego wypalenia zawodowe a zatrzymanie pracowników w organizacji

Streszczenie: Dynamiczny rozwój technologii i przeobrażenia społeczno-gospodarcze doprowadziły do wzrostu znaczenia wykwalifikowanych pracowników w kształtowaniu przewagi konkurencyjnej przedsiębiorstw. Aby pracownicy mogli działać efektywnie, niezbędne jest zapewnienie odpowiedniego klimatu organizacyjnego, niwelującego poczucie wypalenia zawodowego. W celu wytypowania czynników kształtujących pożądany klimat organizacyjny przeprowadzono badania na grupie pracowników z sześciu grup zawodowych (N = 600). Oceny klimatu dokonano za pomocą Kwestionariusza do badania klimatu organizacyjnego L. Rosenstiela i R. Bögela, natomiast do analizy poziomu wypalenia zawodowego posłużono się kwestionariuszem OLBI (Oldenburg Burnout Inventory) autorstwa E. Demerouti. Statystyczna weryfikacja hipotez wykazała występowanie silnych związków między oceną klimatu organizacyjnego a poziomem wypalenia zawodowego. Analiza modelu regresji pozwoliła wytypować czynniki organizacyjne wyjaśniające zmienność poziomu wypalenia zawodowego w badanej próbie.
Investigating Predictability of Different "Forms of Return" in Tehran Stock Exchange: Some Rolling Regressions-Based Evidence

This paper has provided "out of sample" evidence of stock returns predictability in Tehran Stock Exchange. 68 qualified companies over the period from 2002 to 2015 were selected and for five different "forms of returns", five superior predictive models have been designed by applying "General to specific" approach of modeling technique. Then "out of sample" analysis, based on rolling regressions, has been used to test the validation of the designed models. The result showed that all designed models have sufficient "out of sample" validity and the aggregate returns have a higher predictability level.
Document Clustering for Authorship Analysis

The widespread use of computers and the advent of the internet has made it easier to plagiarize the work of others. Most cases of plagiarism are found in academia where documents are typically essays or reports. Detection of plagiarism can be manual or software assisted. Software assisted detection and analysis allows vast collections of documents to be compared to each other making accurate and successful detection.Document clustering is the application of cluster analysis to textual documents. It has applications in automatic document organization, topic extraction and fast information retrieval.In technical publishing authorship of a work is claimed by those making intellectual contributions to the completion of the research described in the work. Analysis of this work is termed as authorship analysis.The methods include data collection, extracting features, document clustering, cluster evaluation Rand index
Design of Wireless Sensor Networks Nodes Based on CC2420

A low-power chip CC2420,which conforms with Zigbee specification,is developed by Chipcon Enterprise.This paper briefly introduces the architecture of wireless sensor networks nodes at first.And then the functions of chip CC2420 are analyzed.Meanwhile according with running principles and application circuit of CC2420,it proposes a design of wireless sensor networks nodes which uses ATmega128L microcontroller and CC2420 RF transceiver.
From hiscore to high marks: Empirical study of teaching programming through gamification

Unlike conventional taught learning, video games are very successful at keeping players constantly motivated and engaged on a set of tasks for many hours without apparent loss of focus. Additionally, when playing, gamers solve complex problems without experiencing the fatigue or frustration, which would normally accompany a comparable learning task. Any methods able to deliver deep learner engagement are naturally of interest to the academic community, thus resulting in an increasing interest in adopting gamification – the integration of gaming elements, mechanics, and frameworks into non-game situations and scenarios – as a means to drive student engagement and improve information retention. However, its application to education has been a challenging task, as attempts have generally been restricted to a one-dimensional approach, such as transposing a trivial reward system onto existing teaching material. The empirical evidence presented in this paper suggests that a gamified, multi-dimensional, problem-based learning approach may yield improved outcomes even when applied to a very complex and traditionally dry task like the teaching of computer programming. This quasi-experimental study employed a real time sequence of scored quizzes, instructor feedback, and live coding to deliver a fully interactive learning experience. By using a combination of the classroom version of the TV game show “Who Wants To Be A Millionaire? ”, the “Kahoot! ” Classroom Response System (CRS), and Codecademy’s online interactive platform on a Python programming course, students were allowed to experience multiple interlocking methods similar to what would be found in a top quality game experience. Empirical data on learning outcomes from the gamified group were compared with a control group that followed a traditional learning path, which had been used during previous cohorts. Whilst this was a relatively small study, the results were quite interesting in a number of key metrics, including attendance, downloading of course material, and final grades.
Extending and Inferring Functional Dependencies in

kind of constraints in multidatabase systems. A major challenge is when component database schemas are schematic discrepant from each other, i.e., data values of one database correspond to schema labels of another. We propose “qualified functional dependencies” (or qualified FDs), an extension to conventional FDs to formalize integrity constraints in multidatabase systems. We first give inference rules to derive qualified FDs in fixed schemas, then study the derivation of qualified FDs during the transformations between schematic discrepant schemas. Propagation rules are given to derive qualified FDs of transformed schemas from qualified FDs of original schemas. Our work can be used in different stages of building and accessing a multidatabase system, e.g., to detect and resolve value inconsistency in schema integration, to verify lossless schema transformations, to normalize integrated schemas, to verify the integrity of data, and to optimize queries at an integration level. In particular, as an application of our theory, we will use FDs to check the validity of SchemaSQL views (SchemaSQL is a powerful multidatabase language).
Increasing Returns, Balanced-Budget Rules, and Aggregate Fluctuations

In a seminal contribution, Guo and Harrison (2004, JET) showed that, under a balanced-budget rule, the neoclassical growth model exhibits saddle-path stability when the adjustment is based on wasteful public spending. The present paper challenges this result in an endogenous growth framework with non-trivial dynamics of the debt-to-GDP ratio. We show that the emergence of aggregate instability dramatically depends on the strength of social labor externalities. If the labor demand is positively sloped and steeper than the labor supply, two reachable balanced-growth paths appear-a no growth trap, and a positive growth solution-that gives birth to both local and global indeterminacy, hence aggregate instability driven by self-fulfilling beliefs (sunspots). In addition, we show that a fiscal rule such that the tax rate strongly responds to public-debt increases can remove the no-growth trap, and secure positive long-run growth. JEL classification: E62; O41
Leveraging Client Processing for Location Privacy in Mobile Local Search

Usage of mobile services is growing rapidly. Most Internet-based services targeted for PC based browsers now have mobile counterparts. These mobile counterparts often are enhanced when they use user’s location as one of the inputs. Even some PC-based services such as point of interest Search, Mapping, Airline tickets, and software download mirrors now use user’s location in order to enhance their services. Location-based services are exactly these, that take the user’s location as an input and enhance the experience based on that. With increased use of these services comes the increased risk to location privacy. The location is considered an attribute that user’s hold as important to their privacy. Compromise of one’s location, in other words, loss of location privacy can have several detrimental e ects on the user ranging from trivial annoyance to unreasonable persecution. More and more companies in the Internet economy rely exclusively on the huge data sets they collect about users. The more detailed and accurate the data a company has about its users, the more valuable the company is considered. No wonder that these companies are often the same companies that o er these services for free. This gives them an opportunity to collect more accurate location information. Research community in the location privacy protection area had to reciprocate by modeling an adversary that could be the service provider itself. To further drive this point, we show that a well-equipped service provider can infer user’s location even if the location information is not directly available by using other information he collects about the user. There is no dearth of proposals of several protocols and algorithms that protect location privacy. A lot of these earlier proposals require a trusted third party to play as an intermediary between the service provider and the user. These protocols use anonymization
Investigating sustainable tourism heterogeneity: competing orders of worth among stakeholders of a Nordic destination

Abstract This paper contributes to increased knowledge of sustainable tourism heterogeneity by identifying how different underlying mindsets characterise negotiations among community stakeholders in a popular Nordic destination. Based on convention theory (orders of worth), this paper theorises how sustainable tourism is negotiated in-between tourism regimes that are shaped by order structures of society. While much research argues for stakeholder heterogeneity by presupposing the influence of a dominant tourism-centric logic, our ethnographic inspired study reveals the co-presence of an “activist” regime that brings about social change among “welfare” and “professional market” regimes. Assessing the disputes among stakeholders we reveal six orders of worth that constitute opposing justifications of sustainable tourism and thus the underlying mindsets of heterogeneity. We discover that stakeholders from various local cultures legitimise their positions quite arbitrarily across the various regimes to question previous theoretical accounts of the community-based perspective. We theorise the challenge of “boundary worth”, i.e. when a tourism initiative receives its identity on behalf of different orders of worth that blurs expectation and intentions. Finally, we argue that activist involvement in a destination can result in “composite compromises” that ease heterogeneity by balancing conflicting regimes without converging to either of the respective logics.
What Do We Really Know About the Employment Effects of the Uk's National Minimum Wage?

A substantial body of research on the UK's National Minimum Wage (NMW) has concluded that the the NMW has not had a detrimental effect on employment. This research has directly influenced, through the Low Pay Commission, the conduct of policy, including the subsequent introduction of the National Living Wage (NLW). We revisit this literature and offer a reassessment, motivated by two concerns. First, much of this literature employs difference-in-difference designs, even though there are significant challenges in conducting appropriate inference in such designs, and they can have very low power when inference is conducted appropriately. Second, the literature has focused on the binary outcome of statistical rejection of the null hypothesis, without attention to the range of (positive or negative) impacts on employment that are consistent with the data. In our re-analysis of the data, we conduct inference using recent suggestions for best practice and consider what magnitude of employment effects the data can and cannot rule out. We find that the data are consistent with both large negative and small positive impacts of the UK National Minimum Wage on employment. We conclude that the existing data, combined with difference-in-difference designs, in fact offered very little guidance to policy makers.
Personalized Knowledge Service for Smart Cell-Phone Based on Usage: Conceptual Model and Intention Prediction Algorithm

Smart cell-phones include many advanced applications and services that allow their users to achieve various useful goals. However, many users face difficulties when upgrading their cell-phone devices to more advanced ones, partially because their applications include more complex patterns of use for achieving the users’ goals. We present a conceptual framework that aims to help overcoming usage barrier by providing smart cell-phone users a personalized knowledge service. The framework is based on the utilization of task models and on the tracking and analyzing the usage of the applications included in the smart cell-phone, that enable to construct user stereotypes and suggest personalized help according to their usage patterns. It is assumed that the system monitors the usage patterns of the user, thus enabling dynamic update of his/her belonging to a stereotype. The user can override the suggestions and navigate independently in order to find the required knowledge. This paper describes a method to model smart cell-phone applications, a software tool that enables a modeler to create task models for such applications, and an algorithm for analyzing the usage of mobile phone applications.
Is Technical Efficiency Affected by Farmers’ Preference for Mitigation and Adaptation Actions against Climate Change? A Case Study in Northwest Mexico

Climate change has adverse effects on agriculture, decreasing crop quality and productivity. This makes it necessary to implement adaptation and mitigation strategies that contribute to the maintenance of technical efficiency (TE). This study analyzed the relationship of TE with farmers’ mitigation and adaptation action preferences, their risk and environmental attitudes, and their perception of climate change. Through the stochastic frontier method, TE levels were estimated for 370 farmers in Northwest Mexico. The results showed the average efficiency levels (57%) for three identified groups of farmers: High TE (15% of farmers), average TE (72%), and low TE (13%). Our results showed a relationship between two of the preferred adaptation actions against climate change estimated using the analytical hierarchy process (AHP) method. The most efficient farmers preferred “change crops,” while less efficient farmers preferred “invest in irrigation infrastructure. ” The anthropocentric environmental attitude inferred from the New Ecological Paradigm (NEP) scale was related to the level of TE. Efficient farmers were those with an anthropocentric environmental attitude, compared to less efficient farmers, who exhibited an ecocentric attitude. The climate change issues were more perceived by moderately efficient farmers. These findings set out a roadmap for policy-makers to face climate change at the regional level.
Textual Supportiveness Recognition Based on Combinations of Syntax Features for Automated Argument Generation

This paper describes a technique to recognize “supportiveness” of a given text for an argument topic object and a value. Given an argument topic object (o), a value (v), and a text fragment (t), supportiveness refers to whether t supports a hypothesis “o promotes/suppresses v” or not. For example, with “o: casino” and “v: employment”, then a text “The casinos in Mississippi have created 35,000 jobs. ” should support a hypothesis “o promotes v”. This technique enables to automatically collect texts representing reasons and counterexamples for some hypothesis that humans build up (e.g. “casino promotes employment”), combined with text search. Because the difference from relation extraction is polarity of relations, proposed method utilizes multiplifications based on local syntax structures, extending reversing hypothesis in sentiment analysis. We propose feature combinations consisting of “primary features” and “secondary features” for supportiveness recognition. “Primary features” represent local syntax structures around a given target or a given value. “Secondary features” represent global syntax structures generated by combining the primary features. The proposed method calculates weighted sum of secondary features to recognize promoting/suppressing supportiveness. The experiments showed that our method outperforms a Bag-of-Words baseline and a conventional relation extraction method.
Challenges in Delivering Case-Based Teaching in the Online Asynchronous Learning Environment

absTracT Case method teaching is prominent in its efficacy at improving the cognitive learning process in face-to-face classes. However, the efficacy of conducting this teaching method in an online asynchronous environment, where learners and instructor do not have real-time interactions, could be problematic. This study assesses and compares the efficacy of case method teaching in face-to-face and online asynchronous learning (OAL) environments. We proposed four hypotheses on the correlation between these two delivery modes of case method teaching and the learning performance of students. This study reports additional findings on the usage behavior of students in an online asynchronous environment. These findings are a useful aggregated surrogate to measure the effect of case teaching method in the online asynchronous environment. The overall findings of this study indicate that an online asynchronous environment can promote students' participation in certain cases. As most antagonists for the adoption of online asyn-chronous case method surmised, cognitive learning gains via this learning method do not seem to be as high as in the face-to-face environment. The findings provide ample room for a further exploration of creative online asynchronous methods to continuously improve cognitive gains of learners.
Research on Anti-jamming Synchronization Algorithm in the Frequency Hopping Communication System

Frequency Hopping(FH) system is very popular in the military communication because of its high anti-jamming and low detective probability performance.Synchronization is one of the key technologies for FH communication system.Based on the main requirement of abrupt FH system,a synchronization scheme with adaptive anti-jamming ability is presented.The key algorithm and performance are analyzed.Finally,the simulation result shows that the discussed synchronization method not only has the feature of high anti-jamming,high capture probability and low detective probability,but also can adjust the anti-jamming threshold as the changes of the channel with the satisfaction of synchronization catching time.
Effects of the Interaction with Robot Swarms on the Human Psychological State

Human-swarm interaction studies how human beings can interact with a robot swarm—a large number of robots cooperating with each other without any form of centralized control. In today’s human-swarm interaction literature, the large majority of the works investigate how human beings can issue commands to and receive feedback from a robot swarm. However, only a few of these works study the effect of the interaction with a robot swarm on human psychology (e.g., on the human stress or on the human workload). Understanding human psychology in human-swarm interaction is important because the human psychological state can have significant impact on the way humans interact with robot swarms (e.g., a high level of stress can cause a human operator to freeze in the middle of a critical task, such as a searchand-rescue task). Most existing works that study human psychology in human-swarm interaction conduct their experiments using robot swarms simulated on a computer screen. The use of simulation is convenient because experimental conditions can be repeated perfectly in different experimental runs and because experimentation using real robots is expensive both in money and time. However, simulation suffers from the so-called reality gap: the inherent discrepancy between simulation and reality. It is therefore important to study whether this inherent discrepancy can affect human psychology—human operators interacting with a simulated robot swarm can react differently than when interacting with a real robot swarm. A large literature in human-robot interaction has studied the psychological impact of the interaction between human beings and single robots. This literature could in principle be highly relevant to human-swarm interaction. However, an inherent difference between human-robot interaction and human-swarm interaction is that in the latter, human operators interact with a large number of robots. This large number of robots can affect human psychology—human operators interacting with a large number of robots can react differently than when interacting with a single robot or with a small number of robots. It is therefore important to understand whether the large number of robots that composes a robot swarm affects human psychology. In fact, if this is the case, it would not be possible to directly apply the results of human-robot interaction research to human-swarm interaction. We conducted several experiments in order to understand the effect of