Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach for Implementation of Bus Arbitration Techniques

In modern days, due to down scaling in technologies have led to highly complex billion transistor integrated circuits (ICs). As a consequence, manufacturers are integrating increasing number of components on a chip. A heterogeneous System on Chip (SoC) might include one or more programmable components such as general purpose processor cores, digital signal processor cores, or application specific intellectual property cores (IPs) as well as an analog front end, On-chip memory, I/O devices and other application specific components. In SoC, multiple IPs need to communicate with each other to access the required functionality. When multiple IPs requests the bus at the same time, contention may occur. This makes on-chip bus based communication a major challenge for the system designer in the current SoC technology. Thus, Bus arbiters are proposed. The masters on a SoC bus may requests simultaneously and hence an arbiter is required to decide which master is granted. To do so different algorithms are developed. In this paper an approach for implementation of bus arbitration techniques like RR, FCFS and Token Pass are discussed.
Interface for Fake Product Review Detection, Analysis and Removal

: The shift towards shopping online is increasing worldwide day by day. People prefer online shopping over traditional in store shopping for the many advantages which comes in ancillary. The main reason for the boost in online shopping is the convenience it provides to the customer. The customer can switch stores and products at the click of the button rather than traveling to a store. But, there is a catch. The customer could face difficulties when it comes to the quality standards of the product. Customer generated ratings and reviews helps the customer to understand the quality of the product before buying the product. This makes reviews and rating very important aspects that affects purchasing decisions. Therefore a negative review over a good product can affect its sales. A fake negative review can lead to have far reaching consequences. To solve this problem we propose Fake Review Analysis and Detection System (FRADS). FRADS is an Intelligent Interface that uses the Uniform Resource Locator(URL) related to products of the online shopping sites which it monitors and analyzes the reviews provided, and provides the customer with the original rating. The uniqueness of the technology is it can analyze ratings and reviews and also ranks the best reviews in a top down fashion. The proposed system achieved the accuracy of 87% in detecting fake reviews.
Mechanical Spectroscopy Investigation of Point Defect-Driven Phenomena in a Cr Martensitic Steel

The paper presents and discusses results of mechanical spectroscopy (MS) tests carried out on a Cr martensitic steel. The study regards the following topics: (i) embrittlement induced by Cr segregation; (ii) interaction of hydrogen with C–Cr associates; (iii) nucleation of Cr carbides. The MS technique permitted characterising of the specific role played by point defects in the investigated phenomena: (i) Cr segregation depends on C–Cr associates distribution in as-quenched material, in particular, a slow cooling rate (~150 K/min) from austenitic field involves an unstable distribution, which leads to Cr concentration fluctuations after tempering at 973 K; (ii) hydrogen interacts with C–Cr associates, and the phenomenon hinders hydrogen attack (HA) because hydrogen atoms bound by C–Cr associates are not able to diffuse towards grain boundaries and dislocation where CH4 bubbles may nucleate, grow, and merge to form the typical HA cracks; (iii) C–Cr associates take part in the nucleation mechanism of Cr7C3 carbides, and specifically these carbides form by the aggregation of C–Cr associates with 1 Cr atom.
DYNAMIC STABILITY AS MEASURED BY TIME TO STABILIZATION DOES NOT RELATE TO CHANGE-OF-DIRECTION SPEED

Numerous physical capacities have been said to contribute to change-of-direction speed (CODS), including technique, strength, power, and dynamic stability. Out of these capacities, the relationship dynamic stability has with CODS has received very little analysis in the literature. Therefore, this study analyzed whether time to stabilization (TTS) as a dynamic stability assessment could differentiate between faster (n = 13) and slower (n = 13) recreational male team sport athletes in the 505 CODS test, and the modified T-test. TTS was measured via a force plate as the duration for the vertical force component to reach and stay within 5% of the participant’s body weight following a unilateral vertical jump landing for each leg. Between-leg TTS differences were also derived. A one-way analysis of variance (p < 0.05) determined significant differences in TTS and the CODS tests; effect sizes (d) were also calculated. Pearson’s correlations (p < 0.05) were calculated from the pooled data (N = 26) in order to ascertain relationships between TTS, and 505 and modified T-test performance. Results indicated the faster group were quicker in all CODS tests (p ≤ 0.001-0.042; d = 0.85-2.84). There were no differences in TTS (p = 0.071-0.961). Additionally, there were no significant correlations between TTS and the CODS tests (p = 0.138-0.963). TTS does not differentiate between athletes with faster or slower CODS, nor does it correlate with 505 and modified T-test performance. Coaches wishing to assess dynamic stability relating to team sport-specific performance should use a different test for their athletes.
EFFECT OF DIRECTIONAL STRESS HISTORY ON ANISOTROPY OF INITIAL STIFFNESS OF COHESIVE SOILS MEASURED BY BENDER ELEMENT TESTS

ABSTRACT This paper describes the initial stiffness of reconstituted kaolinite clay in both vertical and horizontal planes under three different stress histories. The initial shear stiffness was obtained from bi-directional bender element tests during isotropic and K0 stress loading and unloading. An empirical correlation was established based on the initial stiffness of normally consolidated soils. Unlike the unique relationship of the initial vertical stiffness of normally consolidated clays, the initial stiffness in the horizontal plane is dependent on the stress ratio and previous stress history; thus, three different relationships of the initial horizontal stiffness were obtained for the three loading programs. The effect of the stress history on the initial horizontal stiffness can be considered properly by defining the degree of overconsolidation in terms of the horizontal effective stress. The change in the initial stiffness has a directional dependency on the stress history in the direction of the particle motion and wave propagation in the bender element tests.
CNN-Based Network Intrusion Detection against Denial-of-Service Attacks

As cyberattacks become more intelligent, it is challenging to detect advanced attacks in a variety of fields including industry, national defense, and healthcare. Traditional intrusion detection systems are no longer enough to detect these advanced attacks with unexpected patterns. Attackers bypass known signatures and pretend to be normal users. Deep learning is an alternative to solving these issues. Deep Learning (DL)-based intrusion detection does not require a lot of attack signatures or the list of normal behaviors to generate detection rules. DL defines intrusion features by itself through training empirical data. We develop a DL-based intrusion model especially focusing on denial of service (DoS) attacks. For the intrusion dataset, we use KDD CUP 1999 dataset (KDD), the most widely used dataset for the evaluation of intrusion detection systems (IDS). KDD consists of four types of attack categories, such as DoS, user to root (U2R), remote to local (R2L), and probing. Numerous KDD studies have been employing machine learning and classifying the dataset into the four categories or into two categories such as attack and benign. Rather than focusing on the broad categories, we focus on various attacks belonging to same category. Unlike other categories of KDD, the DoS category has enough samples for training each attack. In addition to KDD, we use CSE-CIC-IDS2018 which is the most up-to-date IDS dataset. CSE-CIC-IDS2018 consists of more advanced DoS attacks than that of KDD. In this work, we focus on the DoS category of both datasets and develop a DL model for DoS detection. We develop our model based on a Convolutional Neural Network (CNN) and evaluate its performance through comparison with an Recurrent Neural Network (RNN). Furthermore, we suggest the optimal CNN design for the better performance through numerous experiments.
Single Image Super-Resolution through Sparse Representation via Coupled Dictionary learning

Abstract- Single Image Super-Resolution (SISR) through sparse representation has received much attention in the past decade due to significant development in sparse coding algorithms. However, recovering high-frequency textures is a major bottleneck of existing SISR algorithms. Considering this, dictionary learning approaches are to be utilized to extract high-frequency textures which improve SISR performance significantly. In this paper, we have proposed the SISR algorithm through sparse representation which involves learning of Low Resolution (LR) and High Resolution (HR) dictionaries simultaneously from the training set. The idea of training coupled dictionaries preserves correlation between HR and LR patches to enhance the Super-resolved image. To demonstrate the effectiveness of the proposed algorithm, a visual comparison is made with popular SISR algorithms and also quantified through quality metrics. The proposed algorithm outperforms compared to existing SISR algorithms qualitatively and quantitatively as shown in experimental results. Furthermore, the performance of our algorithm is remarkable for a smaller training set which involves lesser computational complexity. Therefore, the proposed approach is proven to be superior based upon visual comparisons and quality metrics and have noticeable results at reduced computational complexity.
Network Anomaly Detection inside Consumer Networks—A Hybrid Approach

With an increasing number of Internet of Things (IoT) devices in the digital world, the attack surface for consumer networks has been increasing exponentially. Most of the compromised devices are used as zombies for attacks such as Distributed Denial of Services (DDoS). Consumer networks, unlike most commercial networks, lack the infrastructure such as managed switches and firewalls to easily monitor and block undesired network traffic. To counter such a problem with limited resources, this article proposes a hybrid anomaly detection approach that detects irregularities in the network traffic implicating compromised devices by using only elementary network information like Packet Size, Source, and Destination Ports, Time between subsequent packets, Transmission Control Protocol (TCP) Flags, etc. Essential features can be extracted from the available data, which can further be used to detect zero-day attacks. The paper also provides the taxonomy of various approaches to classify anomalies and description on capturing network packets inside consumer networks.
Effect of Chitosan Electrospun Fiber Mesh as Template on the Crystallization of Calcium Oxalate

Biominerals fulfill various physiological functions in living organisms, however, pathological mineralization can also occur generating mineral pathologies such as the formation of calcium oxalate (CaOx) calculi in the urinary tract. Inspired by the ability of living organisms to generate biogenic minerals using biological organic matrices, and the need to understand the mechanisms of crystallization, three-dimensional fibrillary meshes based on chitosan fibers with random and controlled topology by electrospinning were manufactured. Chitosan was selected due to its active role on in vitro crystallization and its physicochemical properties, which allows the exposure of their functional chemical groups that could selectively stabilize hydrated crystalline forms of CaOx. CaOx crystals were generated on conductive tin indium oxide (ITO) glass substrates modified with electrospun chitosan fibers by using electrocrystallization (EC) technique. The chitosan fibers and the resulting CaOx crystals were analyzed by optical microscopy (OM), scanning electron microscopy (SEM), and X-ray diffraction (XRD) techniques, which demonstrated that the chemical nature and topology of the three-dimensional fibers used as organic template are key factors in the control of type, morphology, and crystallographic orientation of CaOx.
Why CEOs invest in Corporate Social Responsibility initiatives: evidence on Shariah compliant firms

ABSTRACT The aim of this article is to investigate the motivation of CEOs to invest in Corporate Social Responsibility (CSR) activities. To carry out this analysis, we assess a sample of US conventional and Shariah Compliant (SC) firms, from Dow Jones Indices. As SC firms undergo business and financial screening, they are expected to follow different managerial styles and capital structures as compared to conventional firms. This comparison is important in view of the growing size of the Islamic Financial Services Industry that has surpassed total asset values of USD 2.00 Trillion. Existing literature argues that, for conventional firms, CEOs spend on CSR either to promote their private benefits (agency view) or to reduce conflicts among shareholders (conflict resolution view). Our results provide evidence that across both types of firms, CEOs do not invest in CSR initiatives to pursue selfish motives but to resolve conflicts among stakeholders to maximize firm value. The findings are also robust across different specifications and methods in order to address endogeneity issues. This article contributes to the growing literature on managerial styles, capital structure and Islamic Finance, carrying out important implications for the investment industry and for the long-term value of the firm.
The study of parametric optimization algorithms on example of vehicle bumper crashworthiness

Different algorithms of parametric optimization (implemented in the program LS-OPT) to solve high-speed and high-nonlinear problems of impact character on the example of vehicle bumper optimization are considered and compared. Different algorithms of response surface optimization such as linear polynomial model, quadratic polynomial model, Feedforward, Radial Basis Function, Kriging and Support Vector Regression were studied and analyzed; algorithms of choosing point selection scheme were considered. The analysis of optimization results allowed us to determine which of these algorithms are most effective in terms of accuracy and computational time. The problem of impact on the vehicle’s bumper is solved in the paper, the optimization is based on the application of metamodel (RBF). The method provided a reduction of its mass by 16% while maintaining the initial parameters of crashworthiness.
Analysis of Enhanced Pool Boiling Heat Transfer on Laser—Textured Surfaces

Enhancement of pool boiling heat transfer can be attained with a number of passive and active techniques. The paper experimentally analyses the impact of laser treatment of the copper surfaces on pool boiling heat transfer of distilled water and ethyl alcohol. The samples were modified with a laser beam to produce longitudinal grooves of highly developed microstructures in the laser textured area. Specimens of different groove depths, groove widths and micro-fin widths were produced. The results indicate a significant influence of laser processing on heat flux dissipated from the surfaces and heat transfer enhancement for all the samples tested. The experimental results have been generalized in the form of a heat flux correlation based on a modified model of enhanced pool boiling heat transfer.
Theory of College, Student Loans, and Education Policy

This paper analyzes the effectiveness of three different types of education policies: tuition subsidies (broad based, merit based, and flat tuition), grant subsidies (broad based and merit based), and loan limit restrictions. We develop a quantitative theory of college within the context of general equilibrium overlapping generations economy. College is modeled as a multi-period risky investment with endogenous enrollment, time-to-degree, and dropout behavior. Tuition costs can be financed using federal grants, student loans, and working while at college. We show that our model accounts for the main statistics regarding education (enrollment rate, dropout rate, and time to degree) while matching the observed aggregate wage premiums. Our model predicts that broad based tuition subsidies and grants increase college enrollment. However, due to the correlation between ability and financial resources most of these new students are from the lower end of the ability distribution and eventually dropout or take longer than average to complete college. Merit based education policies counteract this adverse selection problem but at the cost of a muted enrollment response. The importance of loan availability critically depends on the underlying distribution of abilities.
Chapter 21 Securing Mobile Ad Hoc Networks

The vision of nomadic computing with its ubiquitous access has stimulated much interest in the mobile ad hoc networking (MANET) technology. These infrastructureless, self-organized networks, which either operate autonomously or as an extension to the wired networking infrastructure, are expected to support new MANET-based applications. However, the proliferation of this networking paradigm strongly depends on the availability of security provisions, among other factors. The absence of infrastructure, the nature of the envisioned applications, and the resource-constrained environment pose some new challenges in securing the protocols in ad hoc networking environments. The security requirements can differ significantly from those for infrastructure-based networks and the provision of security enhancements may take completely different directions as well. In this chapter, we study the schemes proposed to secure mobile ad hoc networks. We explain the primary goals of security enhancements, shed light on the commensurate challenges, survey the current literature on this topic, and finally introduce our approach to this multifaceted and intriguing topic.
EXPLORING THE IMPACT OF INTERNET ADDICTION ON ACADEMIC ACHIEVEMENT

This study provides an account of the phenomenon of internet addiction from the perspective of academic achievement. In other words, this study aimed to explore the relation between academic performance of Turkish high school students in such different subject as Maths, English, History, GPA and their use of internet. Different school subjects were selected consciously as the predictor of success in different domains such as social sciences, language, mathematics and the mean of them (GPA). In this respect, employing convenience sampling method, 217 high school students (107 males, 110 females) were included in the study. The level of internet addiction among the participants was determined through administering one dimension of the adopted version of The Social Networking and Social Media Status Scale (Arslan & Kirik, 2013) (α = 0.88). For academic performance, the students were asked to write down the grade points for the specified three subjects and GPA as in their recent school reports. Following the statistics and the procedures run for the reliability and validity of the scale using both SPSS 21 and Liesrel 6 for Windows; adequacy of the sampling; normality and homogeneity of the distribution, parametric tests (Independent Sample T tests & Pearson Product Moment Correlation) were run to analyze the data through SPSS 21 for Windows. The results suggested no gender impact on internet addiction. In terms of the academic performance, statistically positive relation was found between EFL performance and internet use while GPA scores were found to be negatively correlated with it. No correlation between performance in history or math and internet use was found. Article visualizations:
DESIGN OF HEXADECAGON CIRCULAR PATCH ANTENNA WITH DGS AT KU BAND FOR SATELLITE COMMUNICATIONS

The design of a hexadecagon circular patch (HDCP) antenna for dual-band operation is presented in this paper. The proposed antenna operates at two resonating frequencies 13.67 GHz, 15.28 GHz with return loss of −42.18 dB, −38.39 dB, and gain 8.01 dBi, 6.01 dBi, respectively. Impedance bandwidths of 854 MHz (13.179–14.033 GHz) and 1140 MHz (14.584–15.724 GHz) are observed for the dual bands, respectively. To produce circular polarization, the HDCP antenna is incorporated with ring and square slots on the radiating patch. The defected ground structure (DGS) is considered for enhancement of gain. Axial ratio of the proposed antenna is less than 3 dB, and VSWR ≤ 2 for dual bands. The measured and simulated (HFSS, CST) results of the HDCP antenna are in agreement. The HDCP antenna can work at Ku band for satellite communications.
Experimental evaluation of the relationship between dimensional dependencies of MnZn ferrites and filter inductor impedances

This study investigates the relationship between filter inductor impedance and dimensional resonance of MnZn ferrite. Experimental results clarify that multiple factors affect inductor impedance resonances. These can be classified into three factors: the inherent characteristics of a magnetic material, self‐resonance due to winding stray capacitance, and winding that acts as a distributed constant line. Next, based on the measurement results, the dimensional dependencies of complex permeabilities (dimensional resonance) and the influence of dimensional resonance on inductor impedance are discussed in detail. Finally, this study verifies that the influence of dimensional resonance on complex permeability can be mitigated, and filter inductor impedance can be increased in the high frequency range by core lamination. All experiments are performed using off‐the‐shelf magnetic core products.
Knowledge Management: The Way to Organizational Competitive Advantage

The paper explains the crucial knowledge management (KM) processes which are rapidly growing in importance in the present day globalized knowledge based economy. A firm’s intellectual capital is thus increasingly seen today as possessing the potential to become the primary wealth creator in many business organizations. The researchers, therefore, stick to the description of the primary activities of learning, creativity and performance, which are inherent in the holistic frame of modern KM systems, and which sequentially follow each other as typical knowledge processes evolve in a knowledge centric organization.