Miracle-dz/UniFAR-FTUs huggingface dataset:
Utilization of Contingency Tables in Stochastic Computing

Stochastic computing (SC) is a re-emerging approach adopted in vision and learning machines. SC, as a hardware-efficient unconventional computation paradigm, utilizes digital logic systems for arithmetic operations. Conventional logic gates are fed binary streams that hold corresponding pulse probabilities. The similarity between binary input pulses is crucial to the correlation. In this brief, the utilization of a contingency table (CT) in an SC simulation is proposed as a main contribution. The CT manipulates input scalars to perform SC-based logic operations, which avoids lengthy bit-by-bit bitstream processing. After positive and negative correlation tuning via CT, three different approaches to emulate uncorrelated bitstreams are studied. Taking advantage of the ease of a memory- and runtime-efficient CT, correlation occurrence and error analyses are thoroughly discussed. The ability to use a CT for all input combinations instead of bitwise processing in any simulation environment is ascertained.
Robust Vibration Control for Active Suspension System of In-Wheel-Motor-Driven Electric Vehicle via μ-Synthesis Methodology

This paper proposes a robust vibration controller design for active suspension system of in-wheel-motor-driven electric vehicles based on unified µ-synthesis framework. First, multiple parameter uncertainties and unmodelled high-order dynamics of the suspension are analyzed and discussed. By applying the mixed uncertainties and linear fraction transformation, model perturbations are separated from the suspension system and their perturbation bounds can be also limited. Then the uncertain quarter-vehicle active suspension model with dynamic damping in-wheel motor driven system is established, in which in-wheel motor is suspended as a dynamic vibration absorber. The resulting robust µ-synthesis feedback controller of generalized closed-loop active suspension system is designed with the concept of structured singular value µ and µ-synthesis theoretics, and solved via comprehensive solution of the D-G-K iteration. The µ analysis results show that the µ controller possesses less conservative stability and performance margins as compared to the H8 method against system uncertainties. Furthermore, simulations of nominal and perturbed suspension systems are implemented and the corresponding frequency and time-domain responses are compared, and then simulations results confirm that the developed µ controller is capable of attenuating the negative vibration of the active suspension system compared with H8 controller and passive suspension.
A CROSS-SECTIONAL STUDY ON THE RELATIONSHIP BETWEEN SMARTPHONE ADDICTION AND DEPRESSION, ANXIETY AND SOCIAL APPEARANCE ANXIETY IN YOUNG ADULTS

Objective: The aim of this study was to determine the prevalence of smartphone addiction in young adults, and to inves- tigate the relationship between smartphone use, depression, anxiety, and social appearance anxiety. Materials and Methods: Sociodemographic data form, Smart- phone Dependence Scale-Short Form, Beck Depression Inventory for Primary Care-Short Form, Beck Anxiety Scale, and Social Appearance Anxiety Scale were applied face to face in this cross-descriptive study. Results: A total of 259 subjects, 128 (49.4%) female and 131 (50.6%) male, were included in the study. 25.9% of the participants were smartphone addicts. There was a high positive correlation between smartphone usage time and smartphone addiction score. The social appearance anxiety average scores of the social media users (30.8±13.9) were higher than those of subjects who do not use social media (28.8±11.3). Smartphone addiction scale had a positive correlation with anxiety and social appearance anxiety scores, while not with depression. Conclusion: Our results revealed that the purpose of smart- phone usage affects people more than smartphone usage or smartphone addiction. The internet, and especially programs related to sharing one’s appearance and lifestyle and applica-tions that create an unrealistic appearance that conforms to virtual norms, can add hard-to-repair prejudices to the mind. This situation should be seen as a threat, especially for the the test is evaluated in direct proportion as the risk of addiction increases. This is a sin-gle-factor scale without subscales. In the Korean sample, the cut-off score was determined as 31 for male and 33 for female. The Cronbach alpha coefficient of the original form’s internal consistency and concurrent validity is 0.91 (13). The Turkish validity and reliability study of the scale was conducted by Noyan et al. and Cronbach’s alpha coefficient of the scale was 0.867 and had a 0.926 reliability coefficient (5). younger generation, and is a new sociological problem worth investigating.
E-Learning Instruction Generation Approach in terms of E-Learning Instruction Generation Approach in terms of Experience Economy Experience Economy

With the trend of service innovation and experience economy, innovative services with mass customization is the right way to shift into the Experience Economy. Nowadays, E-Learning services development is limited and digital learning material inadequate is one of the most important issues in this area. By taking rapid instruction prototyping into consideration and implementing the modular architecture that offer mass customization services and rapid, then the E-Learning in terms of Experience Economy will realize rapidly. This study proposes an innovative service concept with efficiently offering reusable learning assets for accelerating learning material development. The innovative approach of E-Learning instruction generation services is illustrated and the conceptual model of proposed service framework is outlined. The major findings of this study are: E-Learning instruction generation model for effectively utilizing course contents in Web 2.0 website; conceptual model for dynamic componentization of learning assets. Finally, discussion direction for further research is proposed.
Water vapour adsorption and desorption in GCLs

Super-saturated salt solutions are used to control relative humidity (RH) and to infer the hydration (water uptake and loss) behaviour of three needle-punched geosynthetic clay liners (GCLs) with respect to time under conditions of both free swell and 20 kPa applied stress. It is shown that RH and applied stress play a key role in the hydration behaviour with time when GCL specimens were in equilibrium with water vapour. It was also observed that water uptake and loss was affected by the bentonite form (powdered or granular) and mineralogy of the bentonite. However, the effect of GCL structure (i.e. difference in geotextiles and bonding of needle-punched fibres to the carrier geotextile) on their hydration behaviour for GCLs with similar form of bentonite was not significant for RH ≤ 97.7%. The effect of GCL structure became more apparent at 100% RH (for all GCLs). The results presented in this study can be used to better assess the hydration of GCLs in field applications such as waste containment liners .
LMM-MQM time series mapping - An application in a murine advanced intercross line identifies novel growth QTLs

The Berlin Fat Mouse Inbred line 860 (BFMI860) is a mouse model for juvenile obesity. Previously, a recessive major effect locus (jObes1) was identified on chromosome 3 explaining around 26% of the body weight variance in an BFMI860xC57BL/6NCrl advanced intercross line. The aim of this study was to discover additional QTL. Time series body weight data were modeled using linear mixed models (LMM), while a multiple QTL mapping (MQM) approach compensated for the jObes1 locus effect. LMM-MQM identified five additional loci significantly associated with body weight. Variance explained by the jObes1 locus increased to 38.1% when using LMM-MQM mapping, while the additional loci explained between 2.0% and 3.9% of the body weight variance. Several positional candidate genes within the novel QTL regions were found in KEGG pathways for insulin signaling and insulin resistance. Strong distortion with preference for the BFMI allele was observed within a newly identified QTL containing the well-known Foxo1 regulator of adipocyte differentiation. Here, we present a novel method for QTL detection in time series data: LMM-MQM time series mapping. We show that our method is more powerful in detecting QTLs compared to single timepoint mapping approaches. Thus, the time series structure should be considered for optimal detection of small effect QTLs. LMM-MQM time series mapping can be used to find genetic determinants of all kind of “phenotypes over time” be it lactation curves in cattle, plant biomass, drug clearance in human clinical trials, or cognitive decline during disease.
Some Methodological Considerations for the relationship between Environmental Degradation, Economic Growth and Energy Consumption for South Asian Countries

The present study is designed to investigate that how Economic Growth (EG) of the South Asian region has affected the Environmental Degradation (ED) from 1980 to 2018. This study has used Newey and West (1987) robust standard errors approach to overcome the problem of autocorrelation and heteroskedasticity in panel data. The results of the statistical model confirmed the existence of the Inverted U-shaped Environmental Kuznets Curve (EKC). Furthermore, the results also confirmed that the use of energy is also deteriorating the environment significantly. One significant contribution of the study is to check the causality between EG and CO2 by applying a relatively new approach namely Granger non-causality test presented by Dumitrescu and Hurlin (2012). The results confirmed that economic growth is contributing towards more CO2 emissions. The study concluded that South Asian countries should use environment-friendly renewable energy sources to achieve a higher growth rate.
Understanding and Evaluating Assurance Cases

Assurance cases are a method for providing assurance for a system by giving an argument to justify a claim about the system, based on evidence about its design, development, and tested behavior. In comparison with assurance based on guidelines or standards (which essentially specify only the evidence to be produced), the chief novelty in assurance cases is provision of an explicit argument. In principle, this can allow assurance cases to be more finely tuned to the specific circumstances of the system, and more agile than guidelines in adapting to new techniques and applications. The first part of this report (Sections 1-4) provides an introduction to assurance cases. Although this material should be accessible to all those with an interest in these topics, the examples focus on software for airborne systems, traditionally assured using the DO-178C guidelines and its predecessors. A brief survey of some existing assurance cases is provided in Section 5. The second part (Section 6) considers the criteria, methods, and tools that may be used to evaluate whether an assurance case provides sufficient confidence that a particular system or service is fit for its intended use. An assurance case cannot provide unequivocal "proof" for its claim, so much of the discussion focuses on the interpretation of such less-than-definitive arguments, and on methods to counteract confirmation bias and other fallibilities in human reasoning.
Thermal buckling and vibro-acoustic behaviour of functionally graded graphene polymer layered composites subjected to in-plane temperature variance

The current study reports the thermal buckling, vibration and acoustic characteristics of functionally graded graphene polymer layer composite plates subjected to the in-plane temperature variance. The macroscopic properties of the composites are evaluated using the modified rule of mixtures to compute the layer-wise properties of an functionally graded graphene polymer layer composite plate. The critical buckling temperature is computed and compared for various functional gradings, boundary conditions and in-plane temperature variances. The in-plane temperature variance showed a major impact on the critical thermal buckling temperature and respective mode shapes. The vibro-acoustic behaviour of the functionally graded graphene polymer layer composite plate is investigated and documented keeping critical buckling temperature as a function. With an increase in thermal load and the nature of in-plane temperature variance, the vibro-acoustic results showed significant difference in velocity and acoustic response. For functionally graded graphene polymer layer composite plate with one free edge, the difference was statistically significant as indicated by an octave band plot. We conclude that the portion of the functionally graded graphene polymer layer composite plate that is subjected to the higher temperature in an in-plane temperature variance, as well as the nature of the boundary conditions may exacerbate the effect of in-plane temperature variance and are crucial in predicting vibro-acoustic characteristics.
Practical Unit Testing with JUnit and Mockito

This book explains in detail how to implement unit tests using two very popular open source Java technologies: JUnit and Mockito. It presents a range of techniques necessary to write high quality unit tests - e.g. mocks, parametrized tests and matchers. It also discusses trade-offs related to the choices we have to make when dealing with some real-life code issues. The book stresses the importance of writing readable and maintainable unit tests, and puts a lot of stress on code quality. It shows how to achieve testable code and to eliminate common mistakes by following the Test Driven Development approach. Every topic discussed in the book is illustrated with code examples, and each chapter is accompanied by some exercises. By reading this book you will: Grasp the role and purpose of unit tests Write high-quality, readable and maintainable unit tests Learn how to use JUnit and Mockito (but also other useful tools) Avoid common pitfalls when writing unit tests Recognize bad unit tests, and fix them in no time Develop code following the Test Driven Development (TDD) approach Use mocks, stubs and test-spies intelligently Measure the quality of your tests using code coverage and mutation testing Learn how to improve your tests' code so it is an asset and not a burden Test collections, expected exceptions, time-dependent methods and much more Customize test reports so that they show you what you really need to know Master tools and techniques your team members have never even heard of (priceless! ) :) Nowadays every developer is expected to write unit tests. While simple in theory, in practice writing high-quality unit tests can turn out to be a real challenge. This book will help.
The Expanded Endocannabinoid System Contributes to Metabolic and Body Mass Shifts in First-Episode Schizophrenia: A 5-Year Follow-Up Study

Alterations in the expanded endocannabinoid system (eECS) and cell membrane composition have been implicated in the pathophysiology of schizophrenia spectrum disorders. We enrolled 54 antipsychotic (AP)-naïve first-episode psychosis (FEP) patients and 58 controls and applied a targeted metabolomics approach followed by multivariate data analysis to investigate the profile changes in the serum levels of endocannabinoids: 2-arachidonoylglycerol (2-AG) and anandamide, endocannabinoids-like N-acylethanolamines (NAEs: linoleoylethanolamide, oleoylethanolamide, and palmitoylethanolamide), and their dominating lipid precursor’s phosphatidylcholines. Biomolecule profiles were measured at the onset of first-episode psychosis (FEP) and 0.6 years and 5.1 years after the initiation of AP treatment. The results indicated that FEP might be characterized by elevated concentrations of NAEs and by decreased 2-AG levels. At this stage of the disease, the NAE-mediated upregulation of peroxisome proliferator-activated receptors (PPARs) manifested themselves in energy expenditure. A 5-year disease progression and AP treatment adverse effects led to a robust increase in 2-AG levels, which contributed to strengthened cannabinoid (CB1) receptor-mediated effects, which manifested in obesity. Dynamic 2-AG, NAEs, and their precursors in terms of phosphatidylcholines are relevant to the description of the metabolic shifts resulting from the altered eECS function during and after FEP.
RFID System and its Perspective Analysis with KERGM(1,1) Model

RFID (Radio Frequency Identification) technology will be indispensable to our future life. This paper gives certain insight analysis of RFID system from the view of application perspective. First, this paper introduces some essential implementation principles of RFID system and shows its hot application areas. Then, we analyze the limiting factors of RFID system in advanced development, and present a generalized modeling process from the view of knowledge-embedded data mining. Further, based on the above though of knowledge-embedded data mining, a new forecasting method, KERGM(1,1), is developed to forecast RFID's potential application prospect. Lastly, several countermeasures and advices for the development of RFID industry are put forward. It is shown that the future RFID industry should be greatly promising, however, some countermeasures should be adopted to support its development, such as reducing the cost of RFID tag with technical innovation, popularizing RFID system in wider fields, and strengthening international cooperation in RFID standard system.
Software-Defined Networking in Cloud Computing

Through network programmability, we may simplify network management and bring innovation, cloud computing introduced some of its network concepts. One of the most prominent cloud models for minimizing maintenance obligations and simplifying network infrastructure administration is the SDN (Software Defined Network) architecture. SDN stands out because it provides separation of the control plane and programmability for developing network applications. As a result, SDN is expected to enable more efficient configuration, higher performance, and increased flexibility to support new network architectures. This article is aimed to demonstrates the importance of the SDN and the major role it plays in the organization and how SDNs can be profitable to many organizations that remain in the archaic or a traditional cloud environment and how SDN can restructure the cloud architecture with more security enhancement and also to investigate SDN related issues and challenges to provide insight into the obstacles that this revolutionary network paradigm will face in the future, from both a protocol and architecture standpoint. In this study, systematic literature was conducted and descriptive was used to analyze data. When it comes to SDN, the following challenges and issues stand out: All of these phrases are used to characterize the properties of a system: scalability, high availability, reliability, elasticity, security, performance, resilience, and dependability.
Non-Invasive Classification of Blood Glucose Level for Early Detection Diabetes Based on Photoplethysmography Signal

Monitoring systems for the early detection of diabetes are essential to avoid potential expensive medical costs. Currently, only invasive monitoring methods are commercially available. These methods have significant disadvantages as patients experience discomfort while obtaining blood samples. A non-invasive method of blood glucose level (BGL) monitoring that is painless and low-cost would address the limitations of invasive techniques. Photoplethysmography (PPG) collects a signal from a finger sensor using a photodiode, and a nearby infrared LED light. The combination of the PPG electronic circuit with artificial intelligence makes it possible to implement the classification of BGL. However, one major constraint of deep learning is the long training phase. We try to overcome this limitation and offer a concept for classifying type 2 diabetes (T2D) using a machine learning algorithm based on PPG. We gathered 400 raw datasets of BGL measured with PPG and divided these points into two classification levels, according to the National Institute for Clinical Excellence, namely, “normal” and “diabetes”. Based on the results for testing between the models, the ensemble bagged trees algorithm achieved the best results with an accuracy of 98%.
Maximizing the Minimum End-to-End Data Rate Considering Traffic Demand in Multi-Hop and Multi-Channel Wireless Mesh Network

Wireless mesh network is built on a mix of fixed and mobile nodes interconnected via wireless links to form a large-scale multi-hop wireless communication network. In near future, wireless mesh network will provides attractive services such as public services, peer-to-peer communication, mobile Internet access and video-on-demand (VOD) in rural areas because of low costs. In wireless mesh network, each node has multiple network interface cards and there are several orthogonal channels based on IEEE 802.11 standards. In this paper, we consider sourcedestination pairs in wireless mesh network that each pair has traffic demand. The problem is formulated as a binary integer programming which maximizes the minimum end-to-end data rate considering traffic demand.
A Survey of Trust Management Schemes for Social Internet of Things

Social Internet of Things (SIoT) involves integrating social networking concepts in the Internet of Things (IoT) to enhance social interactions among IoT objects and users. SIoT is envisaged to provide adequate service selection and discovery. Trust is an essential factor whenever social concepts are discussed in communication networks. Trust usually leads to a mutual relationship between two parties (i.e., the trustor and trustee) where they both enjoy mutual benefits. For secure social relationships, Trust management (TM) is a crucial feature of SIoT. The primary aim of this work is to provide a comprehensive review of trust management proposals/schemes available for SIoT. Four main trust calculation algorithms for trust management were selected for this review, and they were examined in detail. The IEEE Xplore, Scopus, ResearchGate, and Google Scholar databases were searched for articles containing the terms "Trust aggregation approaches in IoT", and "Trust computation in SIoT" with a particular emphasis on works published between 2018 and 2021. The paper also discussed the pros and cons of each TM technique, trust metrics/features, contributions, and limitations of the state-of-the-art SIoT TM proposals in the literature. The paper further provides open issues and possible research directions for entry-level researchers in the domain of SIoT.