bluuebunny/crossref_metadata_2025 huggingface dataset:
Exploration of Factors That Influence Information Security Education
Authors: Gouni Ahmed Ali Otman , Saad Amna , Ali Siti Haryani Shaikh
Published: July 2024

The improvement of knowledge is very important in information security domain. due to its positive effect on usersâ€™ information security education. It is acknowledged that security education is playing a vital role to mitigate the risk of information security incidents and breaches that faced by users through their ordinary life. Although several approaches have been proposed in information security education, yet these threats continue to increase. To assist the effort of information security education, this research explores the effective factors that have been used in the approaches of information security education, investigates the gaps, and hence, proposes new factors that can help to developing an effective approach to information security education.
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
Uncovering the Satisfying MOOC Gamification Elements via fuzzy Analytic Hierarchy Process
Authors: Hui Ling Nie , Jen Chen Chwen , Siong Teh Chee
Published: July 2024

The constantly high drop-out rate in MOOCs remains as a concern of many MOOC providers. Gamification elements in MOOCs are seen to be able to alleviate this problem. As satisfaction is crucial to sustain learnersâ€™ engagement in MOOCs, this study aims to uncover the satisfying gamification elements for MOOC via Fuzzy Analytical Hierarchy Process (FAHP) approach. The study reveals learner-learner interaction as a significant criterion to provide a sense of satisfaction among MOOC learners and the most satisfying gamification elements are leaderboard, badge and opponent and thus, should be considered to be incorporated into MOOCs.Â
User Behavior towards Video Content in Mobile Devices for Designing Individualistic Prefetching Algorithm
Authors: Saaidin Shuria , Kasiran Zolidah , . .
Published: July 2024

Prefetching content in mobile network environment are meant to shorten users perceive waiting time. Different approaches have been taken by various literatures to provide an algorithm that is able to predict user request ahead of time. A questionnaire was design and distributed to verify approaches taken by those research using new respondents. Base on the response analyzed it is found that the most important aspect that influenced user behavior towards video content is the relevancy of the topics and WiFi is the most preferred type of connections to be used to download video content. Another behavior observed is that users who are willing to watch prefetched video also tends to download a new video. The analysis also confirms that user could be categorized to heavy and light users and they behave differently during weekdays and weekends. Findings from this survey would hopefully become guidance in designing a prefetching algorithm that suited individual needs.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
Analysis of the Water Availability to Irrigation Needs in Irrigation Areas Jambo Aye
Authors: . Wesli , Jalalul Akbar Said
Published: July 2024

Jambo Aye Irrigation Area serves cross-district irrigation water needs, namely North Aceh district and East Aceh district with a service area of 19,360 Ha and in accordance with the Regulation of the Minister of Public Works and Public Housing of the Republic of Indonesia Number 14/PRT/M/2015, criteria and determination of the status of irrigation areas is the authority of the Central Government. Complaints of farmers' communities, especially in North Aceh, there is always a shortage of water for the needs of rice fields, this can be caused by a lack of water supply or it could be caused by damage to irrigation infrastructure. In this study, the availability of water was analyzed from sources for irrigation needs by looking at the water balance. The research method uses the Mock method because there is no discharge measurement data in the study area. The results of the study illustrate that monthly water demand is smaller than the available water called monthly reliable discharge. Water shortages experienced by farmers are not due to supply shortages that are considered possible due to damage to irrigation infrastructureÂ
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
Using Digital Documents and Materials in Civil and Arbitration Procedures
Authors: M. Golovanov Nikolay , . .
Published: July 2024

The research topicality is due to the broad use of digital documents and materials in civil circulation, and the imperfection of the existing legislation in determining their legal status. This situation negatively influences the evidential significance of the digital documents and materials when presented in civil and arbitration procedures.The article objective is to reveal the lacunas in the legal regulation of digital documents and materials as evidences when investigating disputes in general and arbitration courts, and to elaborate proposals for their elimination.The key approach to the research was the legal analysis of legislative and departmental normative legal acts mentioning digital documents, and the analysis of special literature in this sphere of social relations.The main results of the research are: formulating the definition of a digital document setting its most general features and enabling to establish this definition as a legal one; setting the criteria for distinguishing a digital document and a digital material, an original and a copy of a digital document; defining digital documents and materials as direct or indirect evidences, depending on their evidential significance.The conclusions presented in the article can be used by legislators when correcting the norms of the Civil Procedural Code of the Russian Federation (CPC RF) and Arbitration Procedural Code of the Russian Federation (APC RF), other special laws, and by judicial agencies when administering justice on civil cases.Â Â
Plants Nutrition and Growth Stimulation with the Help of Nanotechnologies
Authors: I. Churilov G. , G. Churilov D. , G. Churilov S. , N. Borychev S. , V. Byshov N. , V. Churilova V. , D. Polischuk S.
Published: July 2024

The consistent use of some branches of agrochemical science in crop growing is in the concept of a comprehensive system approach we propose to the issue of plants nutrition and growth stimulation with the help of nanobiopreparations based on copper and cobalt nanopowders. We propose to optimize the technology of a number of agrochemical measures, and more precisely, to reduce them to a single pretreatment of seeds with a preparation containing necessary trace elements in the nano form.This article presents toxic and stimulating effects of using nanoparticles in agro and biotechnology. The developed bio preparations, based on nanoparticles of metal-trace elements (iron, cobalt, copper), have a number of advantages over existing analogues and they are as it follows:â€¢ multifunctional action;â€¢ low consumption rates of preparations up to 1.0 g per hectare seeding rate, while pre-sowing treatment can be combined with dressing, which does not require additional energy costs;â€¢ a comparative assessment of the toxicity of nanopreparations compared with salts of trace elements (iron and copper sulphates, cobalt chloride) proves that salts are 8-10 times more toxic than nanopreparations;â€¢ low cost of nanopreparations (NP) compared with the cost of an equivalent dose of traditional mineral micro fertilizers and drugs to prevent plant diseases;â€¢ ecological safety.The uniqueness of the proposed technology lies in the fact that its use in agriculture does not require any special equipment or an increase in the staff of the enterprise. In the process of applying the proposed preparations, the natural processes of agrobiocenosis are not disturbed and soil fertility is preserved.The effect of nanobiopreparations on living organisms and the effect of â€œlow dosesâ€ compared to substances in the usual physical-chemical state, make possible to obtain scientifically based and objective results of the effect of nanoparticles on plants nutrition and growth stimulation.Â Â
Design of an On-Chip Tracking ADC
Authors: Mohan Manju , Seenu N , R Nair Shyam , Vignesh U P
Published: July 2024

Data acquisition and conversion systems require analog signals to be converted into a digital form that can be used for further analysis. The analog signals are mostly output of sensors and transducers which transform the real-world signals into electrical signals. These electrical signals are modified to digital form by using Analog to Digital Converters (ADC). This conversion involves sampling followed by a quantizationÂ of the input signal thus will be converted to digital signal. The bandwidth of the ADC is restricted by the sampling rate and the quantization error should be kept as low as possible for better accuracy. This paper emphasis on the On-Chip design of a 12-bit Tracking ADC using PSoC which is highly reliable for digitizing the slowly varying signals. Complication encumbered in the logic that connects comparator and counter is replaced by using dual comparators, and an XOR gate. The proposed design has immense leverage in providing stable and constant data for instantaneous signal value. The major involvement is shown in making the design very simple, by efficiently using the available components, thus providing much accurate and stable digital data for further processing the slowly varying signal.Â Â
Knowledge-Based Requirements Engineering in Detecting Ambiguity
Authors: Sudah Sinpang Jacline , Sulaiman Shahida , Idris Norsham
Published: July 2024

Requirements engineering is a phase where the elicitation and analysis of requirements are crucial. Low quality requirements could cost a software project to experience failure, as it does not meet usersâ€™ needs. One of the causes of poor quality requirements is ambiguity. Software engineers or more specifically system analysts normally gather requirements in natural language where it is easy for both developer and stakeholders to understand each other. However, natural language in requirements gathering is prone to ambiguity. Ambiguous requirements will cause developers to understand differently from what the stakeholders actually require. Thus, it is important to avoid ambiguous requirements. As there are many types of ambiguity, this study focuses on the vagueness of functional requirements. The study implements rule-based reasoning in knowledge-based requirements engineering to detect vagueness. Rules for the proposed prototype tool are obtained from journals and experts in requirements engineering. The evaluation shows that diverse categories of vagueness can be detected earlier using the proposed technique and its tool.Â Â
The Role of Denisonâ€™s Organisational Culture on Email Usage among Academician in Malaysian Private Universities
Authors: SHAH BALI MAHOMED ANUAR , G. MCGRATH MICHAEL , ZHI YUH BONG , OTHMAN ZULBASRI , SALWA SHEIKH MOKHTARe SITI
Published: July 2024

academician in Malaysian private universities. For the research, a scale of measurement was used based upon the concepts that are found in values as well as practices in regards to organisational culture developed by Denison and Mishra (1995) model namely Involvement- Capability Development (ICD), Consistency-Agreement (CA), Adaptability-Organisational Learning (AOL) and Mission- Goals & Objectives (MGO). In this study, Technology Acceptance Model (TAM) developed by Davis (1989) was used as part of the perspective theory on technology adoption, using the constructs; perceived ease of use (PEOU) and perceived usefulness (PU) as mediator for organisational culture and email usage. Data used in the study were based on questionnaires of 128 academician from two Malaysian private universities. The study found that all constructs of organisational culture were having significant in the relationship to the perceived ease of use (PEOU) and perceived usefulness (PU) with ICD, AOL and MGO having significant positive relationship with PEOU and PU while CA has significant negative relationship with PEOU and PU on email usage. Finally, PU and PEOU had significant positive relationship with email usage while PEOU had significant positive relationship with PU on email usage. This means that the usage of email among academician in Malaysian private universities depend on both the userâ€™s perception of email usefulness and the perception of ease of use.Â Â Â
Performance Comparison Between Balloon Active Contour and Seed Based Region Growing Methods in Segmenting Breast Ultrasound Images
Authors: Abdul Malek Aminah , Mohamed Norlyda , Nadiah Muhammad Nurul , Adillah Muhammad Nahar Shaffiqah , Khadijah Mohd Asri Siti
Published: July 2024

Segmentation images have been widely used in the medical field, especially in detecting breast cancer. Ultrasound images can be used as modalities in early detection of breast cancer. However, the detection becomes difficult due to speckle noise and unwanted information in the ultrasound images. In this study, performance comparison between Balloon Active Contour (BAC) and Seed-Based Region Growing (SBRG) methods in segmenting breast ultrasound images was carried out. The performance of segmentation results for both methods was measured in terms of accuracy and sensitivity. Results obtained showed that the accuracy for SBRG and BAC methods was 90.55% and 87.41%, respectively. In addition, sensitivity for both methods was 83.3 and 79.0, respectively. This implies that the SBRG method has better performance compared to the BAC method in segmenting breast cancer in ultrasound images.Â
The Effects of Physical Property Estimation on Packed Column Distillation Simulation with a Rate-based Mode
Authors: Sei Lee Young , Mori Hideki , Lee Kiyoung , Man Lee Joon
Published: July 2024

Background/Objectives: we investigate the effects of estimation models for physical properties on the rate-based simulation and discuss what we should be aware of for obtaining better simulation results.Methods/Statistical analysis: Three kinds of physical property models considered are an activity coefficient, a thermodynamic factor, and a liquid excess molar volume. We use experimental data obtained from a pilot-scale plant for comparison with numerical examples. We investigate the effects of estimation models for physical properties on the rate-based simulation and discuss what we should be aware of for obtaining better simulation results.Findings: The thermodynamic factor models do not affect largely the simulation results in the distillation simulation where the mass transfer resistance of the vapor phase film is dominant.The liquid excess molar volume of the ternary mixture of Methanol, Ethanol, and Water shows at most 3% deviations from the averaged molar volume. It affects the simulation results markedly where the composition of the liquid mixture passes through the region of the large excess molar volume.Improvements/Applications: The simulation results indicate that even small difference in continuous operation becomes much pronounced in batch operation with multicomponent systems.Â Â
Toward Accurate Music Classification Using Local Set-based Multi-label Prototype Selection
Authors: Seo Wangduk , Seo Sanghyun , Lee Jaesung
Published: July 2024

Background/Objectives: Multiple music tags enable quick searching and selection of music clips for by end-users to listen to. Our goal is to improve the accuracy of automatic music categorization.Methods/Statistical analysis: We propose a local set-based multi-label prototype selection to remove noisy samples in datasets without transforming multi-label datasets to single-label datasets by searching the local set of each sample. To validate the superiority of the proposed method, we use ten multi-label music datasets and Hamming loss as a performance measurement, which counts the symmetric difference between predicted labels and ground truth labels.Findings: Considering time and cost, manual categorization of a large collection of music clips is generally impractical. As such, an automated approach for addressing this task through the training of music tags annotated from an online system is employed. In the real world, multiple labels can be annotated to a music clip by users of an online system, resulting in unintended noisy samples due to inaccurate annotations. Conventional methods attempt to transform multi-label datasets to single-label datasets that can yield additional computational cost and unintended removal of non-noisy samples. In this paper, we propose a novel prototype selection method for multi-label music categorization. Experimental results indicate that the proposed method performed the best performance on nine music datasets. From the experiment of CAL500 dataset, multi-label classification performance based on the training samples selected by our proposed method was 0.1402, which indicates that 15,020 labels on average were correctly classified for 100 test samples. Compared to the second-best performance by the compared method, our method was able to classify 245 more labels.Improvements/Applications: Experiments using ten different musical datasets showed that the proposed method demonstrated better performance than the compared methods.Â Â
Loss Analysis in Accordance Switching State of 3kW Full-bridge Converter with Current Doubler Rectifier
Authors: Park Je-Suk , Park Young-Un , Shin Duck-Shick , Kim Dae-Kyong
Published: July 2024

Background/Objectives: The losses mostly dissipate to the thermal and reduce the output efficiency of the power conversion system.Methods/Statistical analysis: loss analysis of the 3kW DC-DC converter in accordance switching state through thermal module of circuit analysis tool.Findings: Loss analysis of a DC-DC converter was performed using the thermal module function of circuit analysis tool. Loss of power semiconductor is analyzed by modeling power semiconductor device for loss analysis with device database editor.Improvements/Applications: The thermal of power semiconductors analyzes the thermal by adding a thermal equivalent resistor to the device for power semiconductor loss analysis. The results are expected to be helpful for heat dissipation design. Future research will add inductor loss analysis.Â Â
Indirect Photon-Counting Detector with a GAGG Scintillator for Low-Energy Photon Detection
Authors: Baek Cheol-Ha , Lee Hakjae , Kim Daehong
Published: July 2024

Background/Objectives: The aim of this study was to explore the properties of indirect detection using a scintillator and silicon photomultiplier, as scintillators are highly sensitive for breast cancer detection.Methods/Statistical analysis: Silicon photomultipliers (SiPM) and Cerium-doped Gd3Al2Ga3O12 (GAGG) scintillator crystals were used to fabricate a scintillation detector, and its characteristic of spectroscopy were compared to the results of LYSO and CsI using Î³-ray spectroscopic measurement. The resulting energy resolutions of each scintillation detector, comprising a single crystal scintillator (volume size: 3Ã—3Ã—2 mm3) and a SiPM (active area: 3Ã—3 mm2) for a Î³-ray source, such as 241Am, were measured and compared.Findings: The 137Cs source yields an energy resolution of 5.23 and 20.31% at 661 keV for the GAGG and LYSO scintillators, respectively. Alternatively, because the CsI scintillator did not yield a distinct energy peak, an energy resolution was not measured. The 241Am source yields an energy resolution of 28.88 and 36.12% at 59.5 keV for the GAGG and LYSO scintillators, respectively. Measured energy peaks of the 241Am source were 62.7 and 64.6 keV for GAGG and LYSO scintillators, respectively. The energy peak of the 241Am source for CsI was not measured because the CsI scintillator did not yield a distinct energy peak of 137Cs source for calibration.Improvements/Applications: The GAGG scintillator could improve the energy resolution of low-energy source than LYSO and CsI scintillators.Â Â
The Combined Effects of Lee Silverman Voice Treatment and Abdominal Respiration on the Maximum Phonation Time in Parkinson's Disease
Authors: Byeon Haewon
Published: July 2024

Background/Objectives: The purpose of the our study was to evaluate the effects of a respiratory rehabilitation the forced vital capacity, voice intensity, and maximum phonation time (MPT) of patients with hypokinetic dysarthria.Methods/Statistical analysis: This study was carried out on 32 patients with Parkinson's disease (PD). All subjects were randomly assigned to a treatment group (n = 17), which received both abdominal breathing training and LSVT, and a control group (n = 15), which only received abdominal breathing training. The forced expiratory volume at one second (FEV1) was measured in the sitting positing. The coordination of respiration and vocalization was measured by using MPT.Findings: The results of ANCOVA, which controlled the pre-test with a covariate, showed that the control group (CG) and the treatment group (TG) were significantly (p<0.05) different in FEV1, MPT, and vocal intensity. The results of parameter estimation revealed that the TG had significantly longer MPT (1.9 seconds longer on average) than the CG and the vocal intensity of the TG was significantly stronger (3.1dB higher on average). On the other hand, FEV1 significantly increased in the TG and the CG after 4 weeks of treatments compared to the baseline. However, there was no significant difference between TG and CG.Improvements/Applications: The respiratory rehabilitation composed of LSVT and abdominal breathing was effective in improving not only the vocal intensity of patients with PD but also the coordination of respiration and vocalization.Â Â
An Investigation on Placing the Application of Mathematics at Ecological Research
Authors: Archana Reddy R. , . .
Published: July 2024

This paper is committed into this group of versions in direction of arithmetic from ecology. It addresses identifying categories of engineering models sensed to the cornerstone of the the traits of this main topics research and appraisal project. Each type of scientific types is represented by references into special assessments. This characterization expects to enable Experts, scientists and also gritty people research better compared to ordinary Variety of methods and approaches from numerical demonstrating and Produce a organized strategy to Handle the use of arithmetic in ecological investigation.Â
Fake Currency Detection Using Image Processing
Authors: Saxena Ankur , Kumar Singh Pawan , Prasad Pal Ganesh , Kumar Tewari Ravi
Published: July 2024

Since last few years, as a result of the great technological advances in color printing, duplicating and scanning, counterfeiting problems have become more and more serious. In the past, only the printing house has the ability to make counterfeit note, but today it is possible for any person to print counterfeit bank notes simply by using a computer and a laser printer at house. Therefore the issue of efficiently verifying counterfeit banknotes from real ones via automatic machines has become more and more important. Counterfeit notes are a problem of almost every country but India has been hit really hard and has become a very acute problem. There is a need to design a system that will helpful for recognition of paper currency notes with fast speed and in less time. This proposed system describes an approach for verification of Indian banknotes. The currency will be checked out by using image processing techniques. The approach consists of a number of elements including processing of image, detection of edge, image segmentation, drawing out characteristic, comparing both images. The image processing approach is discussed with MATLAB to verify the parameters of note. Image processing involves changing the nature of an image in order to improve its visual information for human interpretation. The image processing software is a collection of functions that extends the capability of the MATLAB numeric computing environment. The result will be whether note is real or fake.Â Â
A Mixed Approach for Approximation of Higher Order Linear Time Invariant Systems
Authors: Singh Ramveer , Chatterjee Kalyan , Singh Jay
Published: July 2024

This work suggests a technique for order reduction of larger order mathematical model into lower order by combining Modified Inverse Distance Measure (MIDM) and time moment matching criterion. The constant coefficients of the denominator of reduced model are attained by proposed algorithm named MIDM and numerator coefficients of the same are obtained by using the suitable number of time moments and Markov parameters in the set of equations of Improved Pade Approximations (IPA). The suggested method of order reduction is equally useful for both Single-Input Single-Output (SISO) and Multi-Input Multi-Output (MIMO) dynamic systems. The simplicity of the proposed method has been validated through various linear mathematical models taken from literature. To get into the touch of a researcher, the qualitative measure and dynamic analysis of the proposed reduced model output has been elaborated via error index and time/frequency response comparisons respectively.Â Â Â
Issues of Accountability in Cloud Computing Environment
Authors: Kanta Mohanty Surjya , Mishra Samaresh , Kumar Pattnaik Prasant
Published: July 2024

In an accountable Cloud Computing Environment the system able to handle Â even the smallest action being performed by any entity in the environment and trace the entity that performed such as action to hold same accountable for mishap/risk if any. It is very essential that evidence of all the activity stored and processed may be maintained and stored for recovery in the future if required. This stored/maintained data are required to have enough information so that a particular activity can be properly scrutinized. This process should be an iterative process in order to achieve excellence in the system of the Cloud. This paper addresses the issues of accountability in a cloud computing environment.Â
Object Recognition with Improved Features Extracted from Deep Convolution Networks
Authors: Manohar K , Irfan S , Sravani K
Published: July 2024

Object identification is a method for identify an exact object in an image. Object identification algorithm depends on matching, learning, and pattern recognition using appearance based feature technique. Object recognition has various method to detect objects itâ€™s include feature extraction and machine learning methods, deep learning search as CNN. The deep learning convolution neural network (CNN) has been proved to be very efficient in feature extraction. CNN is compressed of one or more convolution layers and then follow by one or more totally connected layers. In Image types, the work with classifiers aims at explore the most appropriate types for high level deep features. The feature extracted from the image plays a significant role in image type. It is the process of retrieving the main data from the raw data, its finding the set of parameters that recognize the object uniquely. In feature extraction every nature is represent by a feature vector itâ€™s become identity. In this work the features extracted from CNN applied as input to train machine learning classifiers and perform image classification. A systematic comparison between various classifiers is made for object recognition.Â Â