nils-herrmann/clean_scirepeval huggingface dataset:
Customer acceptance of online business management degree programs in online education markets
Year: 2019

This paper investigates the critical factors that promote the customer acceptance of online business management degree programs in online education markets. The model examines the impact of reputation, price, teaching quality, student service quality, and ethical practices on the customer acceptance of online degree programs and customer loyalty to online degree programs. Five hundred and seventy five samples, which were collected from participants in a web based survey in Korea, were analyzed using multiple regression analysis techniques. The findings of the study suggested that the reputation of online programs, the price of online degree programs, the teaching quality of online instruction, and the student service quality of online institutions are significantly related to the customer acceptance of online degree programs, while the ethical practices of online institutions are not significantly related to the customer acceptance of online degree programs. In addition, the empirical findings show that the reputation of online degree programs plays the most important role in establishing and promoting customer acceptance in the markets. Based on the findings of the study, we discuss possible strategies for marketing success in online education markets.
Near Field Communication Based Digital Transaction Card
Year: 2018

Our paper aim is to design a reprogrammable smart payment card that replaces all other cards in the wallet assembled using an ultra low power e paper display, Bluetooth Communication, capacitive touch sensor and NFC. The controllers used in this project based on ARM Cortex M architecture. The main advantage of this paper is the card will be in constant communication with the smartphone. In case if the connection was lost, after a certain time interval the card interprets it as lost or stolen and will automatically disable itself. The user can re enable the card only by entering the authentication password on the card and from the smartphone app.
The Equivalence of " Forward " and " Backward " Nonclassical Particle Transport Theories
Year: 2017

In this paper, two distinct "nonclassical" particle transport theories in which the distribution function P(s) for the distance s between collisions is not exponential are discussed. The two nonclassical theories were developed to describe different physical problems, and the mathematical transport equations that arise from the two theories are different. Nonetheless, we show in this paper that by means of a physicallymotivated transformation, it is possible to derive one of the theories from the other. Our analysis also includes boundary conditions for finite media; previous publications on nonclassical transport have usually only considered infinite media.
A stage polymorphic IR for compiling MATLAB style dynamic tensor expressions
Venue: GPCE
Year: 2019

We propose a novel approach for compiling MATLAB and similar languages that are characterized by tensors with dynamic shapes and types. We stage an evaluator for a subset of MATLAB using the Lightweight Modular Staging (LMS) framework to produce a compiler that generates C code. But the first Futamura projection alone does not lead to efficient code: we need to refine the rigid stage distinction based on type and shape inference to remove costly runtime checks. To this end, we introduce a stage polymorphic data structure, that we refer to as metacontainer, to represent MATLAB tensors and their type and shape information. We use metacontainers to efficiently "inject" constructs into a high level intermediate representation (IR) to infer shape and type information. Once inferred, metacontainers are also used as the primary abstraction for lowering the computation, performing type, shape, and ISA specialization. Our prototype MATLAB compiler MGen produces static C code that supports all primitive types, heavily overloaded operators, many other dynamic aspects of the language, and explicit vectorization for SIMD architectures.
Oblivious Chase Termination: The Sticky Case
Venue: ICDT
Year: 2019

The chase procedure is one of the most fundamental algorithmic tools in database theory. A key algorithmic task is uniform chase termination, i.e. given a set of tuple generating dependencies (tgds) is it the case that the chase under this set of tgds terminates, for every input database? In view of the fact that this problem is undecidable, no matter which version of the chase we consider, it is natural to ask whether well behaved classes of tgds, introduced in different contexts such as ontological reasoning, make our problem decidable. In this work, we consider a prominent decidability paradigm for tgds, called stickiness. We show that for sticky sets of tgds, uniform chase termination is decidable if we focus on the (semi )oblivious chase, and we pinpoint its exact complexity: PSPACE complete in general, and NLOGSPACE complete for predicates of bounded arity. These complexity results are obtained via graph based syntactic characterizations of chase termination that are of independent interest.
A Neuroevolution Approach to General Atari Game Playing
Venue: IEEE Transactions on Computational Intelligence and AI in Games
Year: 2014

This paper addresses the challenge of learning to play many different video games with little domain specific knowledge. Specifically, it introduces a neuroevolution approach to general Atari 2600 game playing. Four neuroevolution algorithms were paired with three different state representations and evaluated on a set of 61 Atari games. The neuroevolution agents represent different points along the spectrum of algorithmic sophistication including weight evolution on topologically fixed neural networks (conventional neuroevolution) covariance matrix adaptation evolution strategy (CMA ES) neuroevolution of augmenting topologies (NEAT) and indirect network encoding (HyperNEAT) State representations include an object representation of the game screen, the raw pixels of the game screen, and seeded noise (a comparative baseline) Results indicate that direct encoding methods work best on compact state representations while indirect encoding methods (i.e. HyperNEAT) allow scaling to higher dimensional representations (i.e. the raw game screen) Previous approaches based on temporal difference (TD) learning had trouble dealing with the large state spaces and sparse reward gradients often found in Atari games. Neuroevolution ameliorates these problems and evolved policies achieve state of the art results, even surpassing human high scores on three games. These results suggest that neuroevolution is a promising approach to general video game playing (GVGP)
FedServing: A Federated Prediction Serving Framework Based on Incentive Mechanism
Venue: IEEE INFOCOM 2021 IEEE Conference on Computer Communications
Year: 2021

Data holders, such as mobile apps, hospitals and banks, are capable of training machine learning (ML) models and enjoy many intelligence services. To benefit more individuals lacking data and models, a convenient approach is needed which enables the trained models from various sources for prediction serving, but it has yet to truly take off considering three issues: (i) incentivizing prediction truthfulness; (ii) boosting prediction accuracy; (iii) protecting model privacy.We design FedServing, a federated prediction serving framework, achieving the three issues. First, we customize an incentive mechanism based on Bayesian game theory which ensures that joining providers at a Bayesian Nash Equilibrium will provide truthful (not meaningless) predictions. Second, working jointly with the incentive mechanism, we employ truth discovery algorithms to aggregate truthful but possibly inaccurate predictions for boosting prediction accuracy. Third, providers can locally deploy their models and their predictions are securely aggregated inside TEEs. Attractively, our design supports popular prediction formats, including top 1 label, ranked labels and posterior probability. Besides, blockchain is employed as a complementary component to enforce exchange fairness. By conducting extensive experiments, we validate the expected properties of our design. We also empirically demonstrate that FedServing reduces the risk of certain membership inference attack.
Browser App Approach: Can It Be an Answer to the Challenges in Cross Platform App Development?
Year: 2017

As smartphones proliferate, many different platforms begin to emerge. The challenge to developers as well as IS educators and students is how to learn the skills to design and develop apps to run on cross platforms.  For developers, the purpose of this paper is to describe an alternative to the complex native app development. For IS educators and students, the paper provides a feasible way to learn and develop fully functional mobile apps without technical burdens.  The methods used in the development of browser based apps is prototyping. Our proposed approach is browser based, supports cross platforms, uses opensource standards, and takes advantage of "write once and run anywhere" (WORA) concept.  The paper illustrates the application of the browser based approach to create a series of browser apps without high learning curve.  The results show the potentials for using browser app approach to teach as well as to create new apps. Recommendations for Practitioners Our proposed browser app development approach and example would be useful to mobile app developers/IS educators and non technical students because the source code as well as documentations in this project are available for downloading. Future Research For further work, we discuss the use of hybrid development framework to enhance browser apps.
Numerical modeling and experimental analysis of thrust cutting force and torque in drilling process of titanium alloy Ti6Al4V
Year: 2018

Cutting forces are critically important in cutting operations because they correlate strongly with cutting performance such as surface accuracy, tool wear, tool breakage, cutting temperature, self excited, and forced vibrations. The drilling operation of titanium alloys is considered by manufactures as complex and difficult in view of the mechanical and thermal properties of this material. In fact, titanium has a very small coefficient of conduction which leaves a high temperature at the area of contact between the tool and the workpiece, which decreases the cutting forces and increases the wear of the tool. For this, more research has focused on the prediction of cutting forces during the drilling of titanium in order to improve the machinability of this material as well as the wear of the tool. Many efforts have been made by researchers to better understand the drilling process and to formulate theoretical cutting forces models to predict and to simulate the phenomenon. This paper presents a numerical model for prediction of cutting forces and torque during a drilling operation including the effect of the regenerative chatter and of the cutting process damping. The corresponding algorithm allows understanding the interaction between the tool and the workpiece and identifying numerically the three dimensional evolution of the cutting force components and cutting torque generated by the drilling process of a titanium alloy. Verification tests are conducted on a vertical machine for titanium alloy Ti6Al4V and the effectiveness of the model and the algorithm is verified by the good agreement of simulation result with that of cutting tests under different cutting conditions.
Lesbian refugees in transit: The making of authenticity and legitimacy in Turkey
Venue: Journal of lesbian studies
Year: 2019

Turkey is a "transit" country, where refugees spend many years waiting before they have a chance to be resettled to a third country. During this liminal period of waiting, refugees have to pursue and legitimize their asylum claims with various state and parastatal asylum infrastructures, such as the Turkish asylum authority, the UNHCR, third countries' embassies, and national, international, and diasporic NGOs and aid providers. This article examines how Iranian lesbian refugees navigate these legal, governmental, and humanitarian bodies that make disparate demands to evaluate the "authenticity" of their identities and the "legitimacy" of their claims. I argue that, during the period of waiting in Turkey, lesbian refugees learn to master specific forms of telling and performance demanded by states, NGOs, and communities in order to carve space for themselves in a system that systematically discredits their sexualities. By continually tailoring their narratives and performances to conform to certain "lesbian types" prioritized by these institutions, organizations, and communities, refugees not only make themselves "authentic," "deserving," and "legitimate" subjects within established tropes, but also transform how they imagine and embody their own and others' sexualities and genders.
Deep Cybersecurity: A Comprehensive Overview from Neural Network and Deep Learning Perspective
Year: 2021

Deep learning, which is originated from an artificial neural network (ANN) is one of the major technologies of today's smart cybersecurity systems or policies to function in an intelligent manner. Popular deep learning techniques, such as multi layer perceptron, convolutional neural network, recurrent neural network or long short term memory, self organizing map, auto encoder, restricted Boltzmann machine, deep belief networks, generative adversarial network, deep transfer learning, as well as deep reinforcement learning, or their ensembles and hybrid approaches can be used to intelligently tackle the diverse cybersecurity issues. In this paper, we aim to present a comprehensive overview from the perspective of these neural networks and deep learning techniques according to today's diverse needs. We also discuss the applicability of these techniques in various cybersecurity tasks such as intrusion detection, identification of malware or botnets, phishing, predicting cyberattacks, e.g. denial of service, fraud detection or cyberanomalies, etc. Finally, we highlight several research issues and future directions within the scope of our study in the field. Overall, the ultimate goal of this paper is to serve as a reference point and guidelines for the academia and professionals in the cyber industries, especially from the deep learning point of view.
Simulations on Saddle Armature With Concave Arc Surface in Small Caliber Railgun
Venue: IEEE Transactions on Plasma Science
Year: 2019

Keeping good electrical contact between armature and rails is an important issue in the electromagnetic launch process. At the start of railgun launching with driving current ramp up, the appearance of aluminum coating tends to be concentrated on the outsides of rails, which indicates current concentration on the edge of armature resulting in the armature edge erosion. The current distribution in the railgun determines its efficiency and contact performance of armature/rail sliding. To improve the electromechanical performance, one type of armature with concave arc surface and saddle structure is designed by removing arch forms from the conventional flat armature and adopts saddle structure. Using a finite element software to establish a 3 D perfect electric contact simulation models on static condition, the current density distribution of armature, inductance gradient of railgun, and erosion area of armature with various central angles <inline formula> <tex math notation="LaTeX"\varphi /tex math>/inline formula> was numerically simulated. The results show that: 1) in the nonaugmented railgun system, the increase in the central angle <inline formula> <tex math notation="LaTeX"\varphi /tex math>/inline formula> is beneficial to reduce the maximum current density value of contact interface and the erosion area of armature, but it is not conducive to the improvement on the electromagnetic launch system's inductance gradient and 2) in the augmented railgun system, the change of the central angle <inline formula> <tex math notation="LaTeX"\varphi /tex math>/inline formula> has little effect on the maximum current density value of contact interface and the electromagnetic emission system's inductance gradient, but the influence on the erosion area is obvious. Based on the above mentioned work, the improved armature structures are proposed.
Estimation and comparision of curve numbers based on dynamic land use land cover change, observed rainfall runoff data and land slope
Year: 2013

The CN represents runoff potential is estimated using three different methods for three watersheds namely Barureva, Sher and Umar watershed located in Narmada basin. Among three watersheds, Sher watershed has gauging site for the runoff measurements. The CN computed from the observed rainfall runoff events is termed as CN (PQ) land use and land cover (LULC) is termed as CN (LU) and the CN based on land slope is termed as SACN 2 The estimated annual CN (PQ) varies from 69 to 87 over the 26 years data period with median 74 and average 75. The range of CN (PQ) from 70 to 79 are most significant values and these truly represent the AMC II condition for the Sher watershed. The annual CN (LU) was computed for all three watersheds using GIS and the years are 1973, 1989 and 2000. Satellite imagery of MSS, TM and ETM+ sensors are available for these years and obtained from the Global Land Cover Facility Data Center of Maryland University USA. The computed CN (LU) values show rising trend with the time and this trend is attributed to expansion of agriculture area in all watersheds. The predicted values of CN (LU) with time (year) can be used to predict runoff potential under the effect of change in LULC. Comparison of CN (LU) and CN (PQ) values shows close agreement and it also validates the classification of LULC. The estimation of slope adjusted SA CN 2 shows the significant difference over conventional CN for the hilly forest lands. For the micro watershed planning, SCS CN method should be modified to incorporate the effect of change in land use and land cover along with effect of land slope.
On the Relationship Between Positive and Negative Affect: Their Correlation and Their Co Occurrence
Venue: Emotion
Year: 2017

Understanding the nature of emotional experience requires understanding the relationship between positive and negative affect. Two particularly important aspects of that relationship are the extent to which positive and negative affect are correlated with one another and the extent to which they co occur. Some researchers have assumed that weak negative correlations imply greater co occurrence (i.e. more mixed emotions) than do strong negative correlations, but others have noted that correlations may imply very little about co occurrence. We investigated the relationship between the correlation between positive and negative affect and co occurrence. Participants in each of 2 samples provided moment to moment happiness and sadness ratings as they watched an evocative film and listened to music. Results indicated (a) that 4 measures of the correlation between positive and negative affect were quite highly related to 1 another; (b) that the strength of the correlation between measures of mixed emotions varied considerably; (c) that correlational measures were generally (but not always) weakly correlated with mixed emotion measures; and (d) that bittersweet stimuli consistently led to elevations in mixed emotion measures but did not consistently weaken the correlation between positive and negative affect. Results highlight that the correlation between positive and negative affect and their co occurrence are distinct aspects of the relationship between positive and negative affect. Such insight helps clarify the implications of existing work on age related and cultural differences in emotional experience and sets the stage for greater understanding of the experience of mixed emotions.
Raising standards for hospitality and tourism education in Malaysia
Year: 2020

The purpose of this paper is to present a briefing on milestones of Malaysia Centre of Tourism and Hospitality Education (MyCenTHE) regarding its role as a nation building exercise in developing human capital talent for future sustainable hospitality and tourism in Malaysia. Under a national initiative by the ministry of education, hospitality and tourism educational institutes in the country have set out to better prepare graduates for industry. MyCenTHE aspires to build a hospitality and tourism cluster (threefold) so that Malaysia is able to increase its annual output of hospitality and tourism personnel from 20,000 in 2009 to 50,000 in 2020 and increase the share of graduates with diploma or degree level awards from 13% to 50% by 2020. These expectations can only be achieved by creating a sustainable pool of workers for this sector. It was in this context for which "MyCenTHE" was conceived.,The current study is based on documentary analysis of secondary sources, qualitative in nature, and presents a case study of MyCenTHE with its key accomplishments in promoting hospitality and tourism education in Malaysia.,The hospitality and tourism industry in Malaysia is set to create 600,000 new job opportunities and in so doing, will need many more skilled, work ready graduates in the coming decade. This paper highlights the collective efforts of the private higher education sector together with some selected public institutions (polytechnics) under the umbrella of the ministry of education through the MyCenTHE platform in promoting hospitality and tourism education nationwide via national awareness campaigns, conferences, skill competitions, seminars, forums and corporate social responsibility projects.,This paper is of value in its own context and in particular support from ministry and related authorities, 26 institutions of higher education working together, approaches to hundreds of local schools and thousands of audiences/participants in awareness campaigns.
Understanding the relationship between work intensification and burnout in secondary teachers
Year: 2019

This cross sectional study sought to investigate teachers' experiences of work intensification and wellbeing. Using the Job Demands Resources model as a framework, this study investigated the relationship between work intensification, satisfaction with workload, perceived organisational support, and burnout. An Australian sample of 215 high school teachers completed a confidential and anonymous online survey battery. Multiple regression analyses indicated that non teaching related workload was a stronger predictor of burnout than teaching related workload. In addition, the results indicated that perceived organisational support moderated the relationship between work intensification and the emotional exhaustion component of burnout. These findings have important implications for teacher wellbeing and highlight the importance of organisational support for staff.
A Review of Nosema cerane and Nosema apis: Caracterization and Impact for Beekeeping
Year: 2019

Two microsporidia have been described infecting honey bees worldwide: Nosema apis and Nosema ceranae. The infecting forms of the parasite are the spores, ingested by the adult host insects. Studies demonstrated that the infection with Nosema spp. range from less than 1 to 100 percent, this disease reduces worker longevity by 22 44% which in turn reduces honey production and causes incomplete crop pollination. However, the used conventional drugs in beekeeping sector has a strong limitation due to the big concern about antibiotics resistance, transmission of antibiotics residues in beehive products and to a lesser extent, unbalancing risk of bee gut microbiota.This review highlights the importance to have healthy bee colonies, which implicitly lead to safety bee products. For this reason, orientation towards alternative treatments without antibiotics and based on natural products with higher antimicrobial effects it is very topical.