bluuebunny/crossref_metadata_2025_split huggingface dataset:
Metro bus transit frequency regulation system for a smart city using an optimization algorithm
Authors: S.Govindaraj S. , Dhalia Sweetlin J. , Vignesh A. , Daphy Louis Lovenia J. , Roshini C. , Horsley Solomon P. 
Published: July 2024

Background:The increase in passengers with inadequate number of buses available results in an overcrowded bus. This is accompanied by a cramped experience for the passengers.Objectives:To facilitate the passengers and to ease their travel, by automating bus and route allocation.Methods:In this work, a Metro Bus Transit Frequency Regulation System Using Nelder-Mead Optimization Algorithm is presented. This system allows the Metropolitan Transport Corporation to allot buses in specified routes according to the demands and eases the ordeal that daily commuters face. Additionally, it aims to reduce the fuel expenses incurred by the Metropolitan Transport Corporation by optimizing the allocation of the number of buses in a particular route. It not only assuages the distresses of the passengers but also looks to reduce the woes of the workers of the Transport Corporation in allocation of buses. The vision of the proposed work is to produce a smart automated bus transit system which paves the way for a technologically improved city.Results:The simulation of the system resulted in 95% of requirements satisfaction by the passengers by using an average resource of 70% during the peak hours in the morning.Conclusions: From the results, it is inferred that developing a transit frequency regulation system will definitely ease the commutation of passengers and also reduces the fuel expenses. Indirectly the system can be used to reduce air pollution by reducing the number of private vehicles on road.Â Â
Corrosion behavior of electro-deposited nickel aluminum composite coating on the stainless steel 316L
Authors: Nawal Mohammed Dawood Dr. , Talib Abdulameer Jasim Eng. , Zaid Falah Sharbah Eng. 
Published: July 2024

The characterization of aluminum particulates charging in a coating cell on the morphology and corrosion behavior of nickel aluminum composite coating by an electro-chemical co-deposition coating were evaluated. The aluminum reinforced nickel matrix composite coatings were co-deposited on Austenitic Stainless Steel (316 L) work pieces by a nickel-ion electrolytic solution firmly postponed with -10 Âµm max. diameter aluminum particulates. The extreme limit of codeposited aluminum can be occurred at a particulate gratified of 50 g/l in cell, a current density of 4.5 A/dm2, a PH of 4.0 â€“ 4.1, and a circulation rate of 400 rpm.Entirely codeposited specimens were heat treated under vacuum atmosphere for five hours at 950 Â°C prior to Potentiostatic testing. Throughout heat treatment, coating morphological development was initiated to occur by the exothermic reaction nickel +aluminum = nickel aluminum.Surface morphology was inspected by scanning electron microscopy(SEM) and X-ray diffraction (XRD) and atomic absorption. Furthermore, The electrochemical enactment of the coatings was considered by Potentiostatic test in 3.5wt.% NaCl. It was originate that, combination of aluminum particulates in nickel matrix sophisticated the nickel grains coatings. Though , polarization curves raised to negative potentials and the rate of corrosion is reduced.Â Â
Building Standard Offline Anti-phishing Dataset for Benchmarking
Authors: Leng Chiew Kang , Hung Chang Ee , Lin Tan Choon , Abdullah Johari , Sheng Kelvin , Yong Chek 
Published: July 2024

Anti-phishing research is one of the active research fields in information security. Due to the lack of a publicly accessible standard test dataset, most of the researchers are using their own dataset for the experiment. This makes the benchmarking across different anti-phishing techniques become challenging and inefficient. In this paper, we propose and construct a large-scale standard offline dataset that is downloadable, universal and comprehensive. In designing the dataset creation approach, major anti-phishing techniques from the literature have been thoroughly considered to identify their unique requirements. The findings of this requirement study have concluded several influencing factors that will enhance the dataset quality, which includes: the type of raw elements, source of the sample, sample size, website category, category distribution, language of the website and the support for feature extraction. These influencing factors are the core to the proposed dataset construction approach, which produced a collection of 30,000 samples of phishing and legitimate webpages with a distribution of 50 percent of each type. Thus, this dataset is useful and compatible for a wide range of anti-phishing researches in conducting the benchmarking as well as beneficial for a research to conduct a rapid proof of concept experiment. With the rapid development of anti-phishing research to counter the fast evolution of phishing attacks, the need of such dataset cannot be overemphasised. The complete dataset is available for download at http://www.fcsit.unimas.my/research/legit-phish-set.Â Â
Comparison of Different Feature Selection Techniques in Attribute Selection of Learning Style Prediction
Authors: Shamsudin Haziqah , Kalsom Yusof Umi , Sabudin Maziani 
Published: July 2024

Learning style of specific users on an online learning system is determined based on their interaction and behavior towards the system. The most common online learning theory used in determining the learning style is the Felder-Silvermanâ€™s Theory. Many researchers have proposed machine learning algorithms to establish learning style by using the log file attributes. Due to many attributes in predicting the learning style, the performance and efficiency of the classification and prediction are still poor; so far it is only between 58%-85%. This research is conducted to determine the most relevant attributes in predicting the learning style. First, three different feature selection methods are used to select the most relevant number of attributes, which are Rank by Importance (RbI), Recursive Feature Elimination (RFE) and Correlation. Next, five different classifiers are used to evaluate those selected feature selection methods. The classifiers are Support Vector Machine (SVM), Random Forest (RF), k-Nearest Neighbour (KNN), Linear Discriminant Analysis (LDA) and Classification and Regression Tree (CART). From the experiments, RbI has proven to be the most effective feature selection method, with the accuracy improvement from 87% to 91%.Â Â
A Study of Web Design for Customer Billing Telephony System Using User Experience (UX) Approach
Authors: Che Pa Noraini , Bidin Raziera , Kamaruddin Azrina 
Published: July 2024

Telecommunications industry has gone through series of development efforts to make services available to consumers and to provide quality services. The hardest challenge in telecommunications industry is to meet the customer satisfaction in billing system such as the accurate billing, easy to understand and resolving billing issue, the billing problem resolution speed, the service cost performance, rate discount degree, and rate communication. Hence, the improvement of these issues can enhance the customer satisfaction. User Experience (UX) is an approach that takes in consideration on userâ€™s preference, emotions, physical and psychological responses, perceptions, behavior that occur before, during and after using the system in designing the user interfaces. Obviously, this creates innumerable design and experience opportunities which represent the holistic view with of the pragmatic aspect and hedonic aspect. Nowadays, UX is becoming an important issue in developing web based system and it has been discussed by many researchers. This research is focus on a study of customer billing telephony system in order to decrease the challenges in telecommunications industry. A survey conducted to collect data from the customers of telecommunication industry. Â The result shows that the improvement of billing system is needed to improve the efficiency and correctness in billing process.Â It is expected that by implementing the UX approach, it will improve the customer billing telephony system. In addition, it gives the positive perceptions and experiences of a service in order to increase the customer satisfaction.Â Â
A Success Model for Semantic Technology based - Knowledge Management Systems: an Empirical Investigation
Authors: Babangida Umar Abdulmajid , Jaâ€™afar Azmi , A. Jabar Marzanah , Azrifah Azmi Murad Masrah 
Published: July 2024

Provision of sufficient knowledge to users is the ultimate goal of a knowledge management system (KMS). Unfortunately, existing KMSâ€™s rely on human effort for access to desired knowledge. Semantic technologies have become a force for paradigm shift in KMS research. They aim to enable the delivery of the right knowledge to the right person and in the right context. Nevertheless, research gap exists on success models for the evaluation of semantic KMS. Most studies only focus on traditional KMS success. Hence, this paper proposes a model to predict the success of semantic KMS. The Relationship between two independent quality dimensions; knowledge and system quality, with two dependent constructs; perceived benefit and user satisfaction was examined through 5 formulated hypotheses. Using a survey method, questionnaires were administered to academicians in Malaysian public higher institutions. Out of a total 221 returned questionnaires, 199 valid responses were used for analysis. Contrary to the expectation, no direct relationship was found between knowledge quality, searchability, and user satisfaction. However, the result indicated that user satisfaction with semantic KM systems is positively associated with user perceived benefit of the system, which is strongly associated with the searchability of the system. Also, a weak association between knowledge quality and perceived benefit was revealed. Findings from the study highlights that, for success to be achieved, userâ€™s perception of benefit from the semantic KMS is key. This can be achieved if the system can provide adequate searchability and satisfactory quality of knowledge.Â Â Â
Recognition of Food with Monotonous Appearance using Speeded-Up Robust Feature (SURF)
Authors: Norhisham Razali Mohd , Manshor Noridayu , Abdul Halin Alfian , Yaakob Razali , Mustapha Norwati 
Published: July 2024

Food has become one of the most photographed objects since the inceptions of smart phones and social media services. Recently, the analysis of food images using object recognition techniques have been investigated to recognize food categories. It is a part of a framework to accomplish the tasks of estimating food nutrition and calories for health-care purposes. The initial stage of food recognition pipeline is to extract the features in order to capture the food characteristics. A local feature by using SURF is among the efficient image detector and descriptor. It is using fast hessian detector to locate interest points and haar wavelet for descriptions. Despite the fast computation of SURF extraction, the detector seems ineffective as it obviously detects quite a small volume of interest points on the food objects with monotonous appearance. It occurs due to 1) food has texture-less surface 2) image has small pixel dimensions, and 3) image has low contrast and brightness. As a result, the characteristics of these images that were captured are clueless and lead to low classification performance. This problem has been manifested through low production of interest points. In this paper, we propose a technique to detect denser interest points on monotonous food by increasing the density of blobs in fast hessian detector in SURF. We measured the effect of this technique by performing a comparison on SURF interest points detection by using different density of blobs detection. SURF is encoded by using Bag of Features (BoF) model and Support Vector Machine (SVM) with linear kernel adopted for classification. The findings has shown the density of interest point detection has prominent effect on the interest points detection and classification performance on the respective food categories with 86% classification accuracy on UEC100-Food dataset.Â Â
An Artificial Immune System Approach for Type E Assembly Line Balancing Problem
Authors: Nor Akmal Khalid Mohd , Kalsom Yusof Umi , Fitri Zaaba Zarul 
Published: July 2024

The manufacturing industry has evolved in the past decades, due to the competition of the global economy, where the market demands high quality and customized products, and meeting lowest possible costs are paramount. One of the many processes in manufacturing is the assembly line operation, namely the assembly line balancing (ALB) problem. ALB problem is dependent on optimum resource utilization in order to improve production output, reduces costs, and shortens production lead times. In these recent years, various approaches have been proposed to solve the complexity of assembly line balancing operations, which composed of exact, heuristic, and meta-heuristic approaches. However, little work had been done to solve the type E assembly line balancing problem. This paper proposed an approach using artificial immune system (AIS) algorithm, namely as the artificial immune cell (AIC) approach, for solving type E assembly line balancing problem. An initialization mechanism through the bone marrow model and probabilistic clonal selection mechanism had encouraged efficient exploration and exploitation of the solution space. The computational results over 242 instances of 24 datasets had demonstrated the efficiency of the proposed AIC approach by achieving high-quality solutions (up to 85.94% optimum solutions was obtained). Also, the results were statistically justified by comparing with multi-rule multi-objective simulated annealing (MRMOSA), priority-based genetic approach (PriGA), two-phased genetic approach (2P-GA), and assignment genetic approach (MA-GA).Â Â Â
A Framework for Integrating Gamification Mechanics and Dynamics to Authentic Learning Environment (Ale) in Non-Game Context
Authors: Nafisah Syed Muhammad Sharifah , Idrus Rosnah , Lee Abdullah Nasuha , Keikhosrokiani Pantea 
Published: July 2024

One of the most important factors for studentsâ€™ development and achievement is their engagement level with the learning activities.Â However, some students are lacking in essential 21st century skills that are important for their working life and daily activities.Â The essential skills are associated with high level thinking skill.Â Authentic learning environments promote the environment for high-level thinking skills.Â In order to engage students and confront their motivational problems, gamification approach is integrated into the authentic learning environment.Â Gamification uses game mechanics and dynamics in a non-game context to motivate, engage and reward user for completing tasks.Â This paper proposes a conceptual framework and for gamified learning environment according to the guideline and characteristics of authentic learning and integrates it with the relevant gamification mechanics and dynamics embedded into an application prototype.Â The prototype, named Time+ (Time Plus), is developed with an example topic of Time Management as the non-game context of higher order thinking skills.Â The aim of this study is to help students improve their engagement positively and enrich the educational experiences for the current millennial students by adapting the gamification concepts in a non-game context.Â Furthermore, it can also encourage students to learn while engaging with the gamified learning environment and enhance the modern teaching and learning methods.Â Â Â
Designing an Expressive Virtual Kompang on Mobile Device with Tri-Axial Accelerometer
Authors: Yong Leng Hoo , Mohd. Norowi Noris , Hazri Jantan Azrul 
Published: July 2024

The paper presents an expressive virtual percussion instrument for Kompang on mobile devices that closely replicate the actual instrument. In nowadays, most available applications are lacking expressiveness control as these applications only use trigger-type event to play corresponding sound. This paper is therefore implemented a simple extraction method by extracting percussive features from embedded sensors to map with the output sound with minimum delay. Multiple features related to the shape of the drum hit are extracted by using tri-axis accelerometer sensors of the mobile device. These features provide an expressive percussion experience that closely imitates playing an actual instrument. An application of the virtual instrument for Kompang is described with an evaluation of the system with ideas for future developments. Result from the study showed that the feature extraction algorithm had an accuracy of 86.78% at detecting drum hit at its peak acceleration value. The questionnaire results also indicated the participants were satisfied with the system in overall.Â Â
Smart Educational System: Web-based Low-Cost Remote Laboratory for Electronic Practical Work
Authors: Abouhilal A. , Moulay taj A. , Taifi N. , Malaoui A. 
Published: July 2024

The implementation of smart technologies is an important part of scientific research especially in the areas of new information and communication technologies, the Internet of Things, wireless sensor network. Among other things, smart educational systems have been a success through videoconferences, classroom response systems and remote labs. Scientific research on remote laboratories has undergone remarkable development in recent years. The remote practical work often uses very expensive proprietary instruments and software. The purpose of this paper is to present a low-cost architecture based on the co-operation of two embedded systems, Raspberry and Arduino. The student accesses the practical work via a web page developed with HTML / Javascript provided by a NodeJs server hosted in the Raspberry. A software oscilloscope has been developed with Processing integrable in the web page to visualise the measured signals from the practical work board.Â Â Â
The Use of EDM on Predicting the Rate of Moroccan University Dropouts: Sharia university, Fez as A Case Study
Authors: Hachem Alaoui Harouni Moulay , Hachem El-Kaber , Ziti Cherif , Bassiri Mustapha 
Published: July 2024

The present article is going to highlight the concept of educational data mining (EDM) and discuss how it can be mainly used to predict Shariaa University dropouts; in other words, it may demonstrate how to enable academics to help students not to drop out their studies, the collected data were taken from our previous study of dropouts at Shariaa University, Fez-Morocco. Using the Bayes theorem that is stimulated from the statistical learning theory to resolve classification problems, we can determine the strengths and weaknesses of those students who are probably to dropout.Â The reasons of conducting this second research on dropping out are to provide the support of continuous university self-evaluation and improvement through using educational data mining, and to help those students who will be expected to leave their university.Â Â
How To Motivate Students Through mining Educational Data
Authors: Hachem Alaoui Haroun Moulay , Hachem El-Kaber , Ziti Cherif , Bassiri Mustapha 
Published: July 2024

Despite having educational data mining as a new research area, it has already made contributions to the learning theories and their teaching practices. The aims of this article are to present a way of improving both the student and the teacher performance, and to empower educational institutions through exploring data and through examining them with the purpose of motivating students in different aspects of their performance.Â Â
The Reasons for The Degradation of the Technological Structure of the National Economy of the Russian Federation in the 1990s.
Authors: V. Bodrova E. , V. Kalinov V. 
Published: July 2024

On the basis of published materials and archival documents, the extremely topical problem of determining the causes of the fall in innovation activity in the real economy, the catastrophic state of the country's scientific and technical complex in the context of the implementation of liberal reforms of the 1990s is investigated. Evaluations of leading experts are analyzed. It is concluded that as a result of flaws in conceptual approaches, poor management of scientific and technological activities, uncontrolled and forced privatization, implemented at the time of financial and credit, tax and pricing policies, completely insufficient state support, Russian fundamental and, especially, branch science was brought into a state of deep crisis, losing its accumulated potential, which caused irreparable damage to its economy and national security.Â Â
Increasing the Efficiency of Microprocessors in an Access Control Systems
Authors: G. Magomedov S. , . . , . . 
Published: July 2024

This paper is devoted to the problem of improving the performance of microprocessors used in access control systems. The requirements are described, and a set of commands is proposed, that are necessary for efficient design of microprocessors working on the basis of the residue number system for the purpose of monitoring and access control. The proposed approach is aimed at improving the efficiency of microprocessor operation as part of the access control system.Â Â
Application of Panel Method to Calculate Ship Resistance
Authors: Ngoc Tu Tran , Manh Chien Nguyen 
Published: July 2024

In this study, the ship resistance in calm water was calculated using panel method under potential flow theory. This is a CFD (Computational Fluid Dynamic) approach with the assumption that the fluid is non-viscosity. Therefore, only wave resistance is calculated by solving nonlinear free surface problems. The frictional resistance is predicted by ITTC formula. The calculation is performed with well-known benchmark case â€“ Kriso Container ship (KCS) â€“ where the experiment result of ship resistance is available to compare and validate the calculation.Â Â
A Multi-Objective Particle Swarm Optimization for Wireless Sensor Network Deployment
Authors: S. Ibrahem Mohammed , Zakree ahmad nazri Mohd , Othman Zalinda 
Published: July 2024

The use of wireless sensor networks nowadays is imperative for different domain of interests. One of the challenging task in deploying such networks lies on the efficient deployment that guarantees least number of sensors while assuring the connectivity and the coverage among these sensors. This would significantly contribute toward longer lifetime of the network. Several studies have addressed this problem by proposing various meta-heuristic approaches. One of these approaches is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) which has been extensively used for WSN deployment. However, such approach suffers of the inaccurate fitness values provided for criteria in the same front. Therefore, this paper aims to propose an alternative approach which is called Multi-Objective Particle Swarm Optimization (MOPSO). The proposed method has been compared against the NSGA-II and the results showed that the proposed method has superior performance.Â Â Â