Miracle-dz/UniFAR-FTUs huggingface dataset:
Natural Interaction of Game-based Learning for Elasticity

Game-based Learning (GBL) is an alternative method for learners to experiencing a volatile environment in a safe place. In this environment, an alternative technique is required to facilitate the learning and to prevent injuries and potential hazards. Subjects involving elasticity are commonly considered as a hazardous issue and can cause injuries such as bouncing a ball. Elasticity is a subject that requires hands-on practicality for learners to experience the effect of elastic objects. In this paper, we have investigated the interaction between learners and elastic objects naturally in a safe environment using GBL. During the interaction, the potentials of natural interaction in the learning process had been observed to investigate the exhibited gestures over the learning procedure. GBL was developed using Kinect technology to teach elasticity to children aged 7-12 years old in primary school. The procedure comprises of detecting the gesture of body and defining the meaning of gestures exhibited during the learning process. The quantitative approach was applied to constantly monitor the interaction between the student and the system. Based on our results, we found that Natural Interaction GBL (Ni-GBL) made students feel that the educational game is useful indirectly because they can learn how to play the game easily.
A Survey on Intelligent Agricultural Information Handling Methodologies

The term intelligent agriculture, or smart farming, typically involves the incorporation of computer science and information technologies into the traditional notion of farming. The latter utilizes plain machinery and equipment used for many decades and the only significant improvement made over the years has been the introduction of automation in the process. Still, at the beginning of the new century, there are ways and room for further vast improvements. More specifically, the low cost of rather advanced sensors and small-scale devices, now even connected to the Internet of Things (IoT), allowed them to be introduced in the process and used within agricultural production systems. New and emerging technologies and methodologies, like the utilization of cheap network storage, are expected to advance this development. In this sense, the main goals of this paper may be summarized as follows: (a) To identify, group, and acknowledge the current state-of-the-art research knowledge about intelligent agriculture approaches, (b) to categorize them according to meaningful data sources categories, and (c) to describe current efficient data processing and utilization aspects from the perspective of the main trends in the field.
Mobile video delivery with minimal bitrate changes

Mobile data traffic keeps increasing year after year, as does the need for devices and technologies that support that growth. Video streaming, in particular, has been the major concern for mobile data traffic due to the complexity in handling the bulky nature of the data. HTTP has become the main medium for video streaming over mobile devices due to its existing popularity. When streaming video to multiple clients on the same network, a bandwidth allocation manager is required to efficiently distribute the available bandwidth among the clients and to ensure a high Quality of Experience (QoE). At the same time, the bandwidth allocation manager should ensure high utilization of the available bandwidth as well as seamlessly adapt to network changes. In this project we developed a bandwidth allocation management mechanism that reduces the number of bitrate changes while maintaining the high bandwidth utilization and therefore improving the Quality of Experience for the user. To show the results of the bandwidth allocation manager, we developed a simulator that represents a video streamed to many mobile clients from different classes of service. Since the QoE can be negatively affected by the number of bitrate changes, we use Exponential Smoothing and Bitrate Changes Optimization techniques to distribute the bandwidth while ensuring the low number of bitrate changes.
Real-Time Attributes in Operating Systems

General-Purpose Operating Systems (GPOSes) are being used more and more extensively to support interactive, real-time and distributed applications, such as found in the multimedia domain. In fact, the wide availability of supported multimedia devices and protocols, together with the wide availability of libraries and tools for handling multimedia contents, make them an almost ideal platform for the development of this kind of complex applications. However, contrarily to Real-Time Operating Systems, General-Purpose ones used to lack some important functionality that are needed for providing proper scheduling guarantees to application processes. Recently, the increasing use of GPOSes for multimedia applications is gradually pushing OS developers towards enriching the kernel of a GPOS so as to provide more and more real-time functionality, thus enhance the performance and responsiveness of hosted time-sensitive applications. In this chapter, an overview is performed over the efforts done in the direction of enriching GPOSes with real-time capabilities, with a particular focus on the Linux OS. Due to its open-source nature and wide diffusion and availability, Linux is one of the most widely used OSes for such experimentations.
Rapid feedback analysis method for underground caverns during construction

It is impossible to obtain complete field data in underground engineering;for example,information on stresses and properties.can only be partially known.The back-analysis is oriented toward using relatively little site-specific data to give the most help to geotechnical engineering.Key factors affecting back-analysis results were investigated in detail,especially the authenticity of input data,the adaptability of computation model and the reliability of the computation result.The orthogonal experimental method was used to performing a successful devise for numerical experiments.The layered range optimizing method was established to assemble uncertain problem-specific parameters.Considering the geological characteristics of underground engineering,the measurement data and the interval analysis method,the rapid feedback method for huge underground houses was established during construction.The spectrum of back-analysis was also presented.Analyzing the deformation law of underground engineering structures in process of construction,sufficient feedback experiments can produce relevant rock parameters,which help to optimized the subsequent engineering construction process.If enough data of a high quality are available,the feedback can give good predictions.
Exchange Rate and Trade Balance: The Case for J-curve Effect in Nigeria

The Nigerian currency has since the introduction of the Structural Adjustment Programme (SAP) of 1986 has been continually depreciated except for a few years. This study investigated the “J-curve” effect which is the nexus between trade balance (TB) and the real effective exchange rate (REER) in Nigeria. It adopted Johansen Cointegration following the outcome of the preliminary Augmented Dickey-Fuller (ADF) test for stationarity of the data series in the model from 1981 to 2016. The Granger causality and the Impulse Response Function tests were also deployed. The post-estimation diagnostic validation conducted included the normality, heteroskedasticity and autocorrelation tests. Empirical evidence from this study showed that in the short run, the trade balance benefited from the devaluation of the Naira rather than suffer deleterious consequences. There was no long run relationship between the dependent variable, (TB) and the explanatory variables, REER and GDP. In Nigeria, it was the inverted J-curve effect. The evidence from impulse response function corroborated the inconsistent long run relationship beyond the fourth year. There was the absence of Granger-causality directions amongst the variables. In view of the contrarian findings of this study, the Nigerian policy makers are enjoined to allow the financial markets determine exchange rates. Exception can be made for priority areas of the economy with the capacity to benefit the strategic intent of governance. In this investigation of the exchange rate and trade balance nexus, the case for J-curve effect has not been made in Nigeria. Keywords: Trade Balance, Effective real exchange rate, J-Curve Effect, Johansen Cointegration
CONTINUATION: Evaluation of adaptive somatic models in a gold standard whole genome somatic dataset

In http://dx.doi. org/10.1101/079087, we presented adaptive models for calling somatic mutations in high-throughput sequencing data. These models were developed by training deep neural networks with semi-simulated data. In this continuation, I evaluate how such models can predict known somatic mutations in a real dataset. To address this question, I tested the approach using samples from the International Cancer Genome Consortium (ICGC) and the previously published ground-truth mutations (GoldSet). This evaluation revealed that training models with semi-simulation does produce models that exhibit strong performance in real datasets. I found a linear relationship between the performance observed on a semi-simulated validation set and independent ground-truth in the gold set (R2 = 0.952, P < 2−16). I also found that semi-simulation can be used to pre-train models before continuing training with true labels and that this pre-training improves model performance substantially on the real dataset compared to training models only with the real dataset. The best model pre-trained with semi-simulation achieved an AUC of 0.969 [0.957-0.982] (95% confidence interval) compared to 0.911 [0.890-0.932] when training with real labels only. These data demonstrate that semi-simulation can be a very effective approach to training filtering and ranking probabilistic models.
The role of student feedback in evaluating mathematics support centres

Accurate evaluation of mathematics support centres is a complex task, given that such centres should ideally be integrated into the overall learning experience of the student, complementing structures such as lectures and tutorials. As such, a multi-faceted approach should be undertaken in order to best measure the effectiveness of such support, combining quantitative data such as attendance records and analysis of exam results with qualitative data such as anonymous student feedback. Over the five years of its operation to date, the Maths Learning Centre in Dublin City University has maintained detailed records regarding the use of its drop-in support service. These records serve the dual purpose of allowing more efficient planning of resources by providing an overview of student attendance patterns and common problem areas, while also enabling an analysis of subsequent student performance to be conducted. However, such data provides little information as to the quality of the student experience within the Centre. Therefore, at the end of each academic year, an anonymous questionnaire is given to firstyear service mathematics students to ascertain their opinions and experiences of the Centre. Over the past couple of years, more than four hundred students per year have completed this survey, over half of whom had used the Centre. Here, following a brief overview of our quantitative data, we focus on the survey results and discuss what can be learnt from these. We also consider the responses in the context of records kept and anecdotal evidence to determine the usefulness and reliability of such feedback.
The Analysis of Farmers' Financial Literacy and its' Impact on Microcredit Accessibility with Interest Subsidy on Agricultural Sector

The government of Indonesia has been rolling out the Food Security and Energy Credit (KKP-E) with interest rate subsidy since 2008 for the people who have no access to banking but have a feasible business. This study aims (1) to analyze the level and influence variables of respondents' financial literacy and (2) to analyze the variables that influence the farmers' accessibility to KKP-E. The methods used are multiple regressions and logistic analysis. The results show that the levels of financial literacy are in the medium categories, which variables affected consist of age, education duration, distance to the capital regency location, annual income, bank account ownership, and financial education experiences. The variables influence of KKP-E accessibility consists of farms' income, the width of the cultivated area, collateral, interest rate, financial literacy index, farmer group legal status, credit accessibility experiences, and loan amount. Financial literacy significantly influences the KKP-E accessibility.
The Effect of Good Governance on the Real Exchange Rate Behavior in Iran and Selected Countries

This study aimed to evaluate the relationship between good governance indicators and real exchange rate behavior. The period under study is that of 1996-2014 to be examined for Iran and the six selected countries of the Organization for Economic Co-operation Development including Germany, Japan, Brazil, India, Sudan and Bangladesh. The Edwards model was used, which is estimated using a simple panel method with constant effects. Estimates indicate that there is a negative and significant relationship between the real exchange rate and variables of the degree of trade openness, the coefficient of internal credit changes, regulatory quality indicators, and the right to comment and accountability. There was also a positive relationship between the real exchange rate and variables such as investment to GDP and indicators such as rule of law, political stability and absence of violence. The convergence of the studied countries was also studied by estimating a gravity model, and this convergence was then confirmed. Therefore, if the targeting of economic policymakers in the studied countries is in the direction of strengthening the national currency, it is necessary to consider variables that have a negative relationship with the real exchange rate, such as indicators of regulatory quality, the right to comment and accountability.
Simple Molecular Systems At Very High Density

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Editorial for the special issue on advances in simulation‐driven modeling and optimization of microwave/RF circuits

Computer simulation tools, especially those involving full‐ wave electromagnetic (EM) analyses, have become ubiquitous in the design of microwave and RF devices and systems. Initially used for design verification, EM simulations are nowadays utilized in the design process itself, for example, for finding optimum values of geometry and/or material parameters of the structures of interest. In a growing number of cases, EM‐driven design closure is mandatory because alternative ways of evaluating the circuit performance (such as through equivalent network modeling) are grossly inaccurate and unable to account for cross‐coupling effects (e.g., in densely arranged layouts of compact circuits) or various environmental components that affect the circuit performance (e.g., connectors or housing for antenna structures). Despite its importance, EM‐driven design poses significant challenges, mostly because of the high‐computational cost of accurate, high‐fidelity simulation. The availability of massive computational resources does not always translate into design speedup because of the need to account for interactions between devices and their surroundings as well as multi‐ physics (e.g., EM‐thermal) effects. Not surprisingly, traditional design optimization procedures that directly utilize EM‐simulated responses typically fail or are impractical. As a consequence, there is growing interest in alternative optimization and modeling methodologies, especially ones that exploit computationally cheap surrogate models. Out of practical necessity, in particular, to address the aforementioned challenges, methodologies for computer‐ aided modeling and design of microwave/RF devices and circuits have undergone tremendous developments over the past decade. The research efforts have been focused on a number of topics, including both local and global optimization methods as well as techniques for constructing fast replacement models (surrogates) to reduce the cost and improve reliability of simulation‐based design processes. There has been a growing interest observed in the development of surrogate‐ assisted modeling and optimization methods such as space mapping and various response correction techniques, knowledge‐based methods and fast tuning methodologies, global optimization algorithms involving population‐based metaheuristics (also in surrogate‐assisted frameworks for single‐ and multi‐objective optimization), but also techniques for solving inverse electromagnetic problems. Commercial
A graph-based system for the dynamic generation of soundscapes

This paper presents a graph-based system for the dynamic generation of soundscapes and its implementation in an application that allows for an interactive, real-time exploration of the resulting soundscapes. The application can be used alone, as a pure sonic exploration device, but it can also be integrated into a virtual reality engine. In this way, the soundcape can be acoustically integrate in the exploration of an architectonic/urbanistic landscape. The paper is organized as follows: after taking into account the literature relative to soundscape, a formal definition of the concept is given; then, a model is introduced; finally, a software application is described together with a case-study.
Managing corporate sustainability: Risk management process based perspective

Sustainability risk management requires holistic and systematic integration of ecological, socioeconomic, and corporate risk factors in the business management. This paper presents an integrative conceptual framework for sustainability risk management in enterprise-wide. The development of this integrative framework is accomplished by tailoring of the enterprise risk management framework. In this paper, the conceptual model to corporate sustainability is offered as the specific management and organizational system to both manage and integrate the corporate goals in order to create economic and financial value and awareness of environmental and social responsibility. Key words: Corporate sustainability, management, risk, risk management, strategic management, sustainability.
Influencing Message Propagation in a Social Network Using Embedded Boolean Networks: A Demonstration Using Agent‐Based Modeling

A Boolean network is a self‐organizing construct originally developed in the field of theoretical biology to investigate the limited variety of processes within genetic networks. Our research objective is to reformulate this descriptive biological/mathematical model into an engineering approach that can be used to shape the operational state space of a targeted complex system in a desired way. We demonstrate this by coupling the state control of a Boolean network to the rules used by the agents in an agent‐based system, thereby controlling when these rules are expressed. The application presented in this paper uses an agent‐based model of the financial community network on Twitter as the target system. A Boolean network is employed to influence the propagation of information through the community by inhibiting the retweeting rule of agents with high network centrality. The results are compared against those produced by manually removing the high centrality nodes.
Image Matching Using a Bat Algorithm with Mutation

Due to shortcoming of traditional image matching for computing the fitness for every pixel in the searching space, a new bat algorithm with mutation (BAM) is proposed to solve image matching problem, and a modification is applied to mutate between bats during the process of the new solutions updating. This new approach can accelerate the global convergence speed while preserving the strong robustness of the basic BA. The realization procedure for this improved meta-heuristic approach BAM is also presented. To prove the performance of this proposed meta-heuristic method, BAM is compared with BA and other population-based optimization methods, DE and SGA. The experiment shows that the proposed approach is more effective and feasible in image matching than the other model.
Immigration, Visible-Minority Status, Gender, and Depression

This study examines if the association between length of residence and mental health—as measured by depression—of immigrants post-arrival in the host country is altered by visible-minority status and gender among a sample of immigrants to Toronto, Canada, as compared to the native-born. The analytic sample excluded refugees. Of the 1,911 adults included, 23 percent were foreign-born. Adjusted multivariate results indicate a significant and positive association between depression and length of residence in the host country—but only among visible-minority immigrant men as compared to Canadian-born men. The positive association between depression and length of residence among visible-minority immigrant men is found to be due to a parallel rise in perceived discrimination and the experience of anger with tenure in the host country.
Understanding the investment of underrepresented minorities in doctoral engineering programs

Underrepresented minorities (URM) tend to have lower completion rates than their majority colleagues in the pursuit of the Ph.D. in engineering. This phenomenon of doctoral attrition has been related to a poor socialization process into becoming an independent scholar. Using the Graduate Student Socialization Framework, this qualitative study aims to describe the types of investments URM students in engineering experience in the pursuit of the doctoral degree. Through a qualitative analysis of semi-structured interviews, we found four types of investment in the doctoral pursuit: effort investment, time investment, financial investment, and mental investment. We conclude that while most of the types of investments found could be applicable to all doctoral students, the differing investments may present harmful implications for URM students’ degree progress.