bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-Time Water Quality Monitoring with Multi-Sensors
Authors: Nizam Husen Mohd , Ismail Roslan , Hamzah Robiah 
Published: July 2024

Water quality monitoring plays an important role in human well-being, environmental preservation and sustainability. This paper presents the study that has been carried out on the development of water quality monitoring with the tenacity of alerting the user with real-time and online water quality information based on important parameters through a web-based dashboard. The sensors are able to measure the parameters of water quality, such as turbidity, pH, temperature, and the level of the water. Audio and coloured lightings alert are triggered when any water quality parameter reaches unsafe levels. A Wi-Fi transmitter module sends the data to the receiving node over long distance range and display the output in real-time. The result demonstrates that a real-time with multi-parameter remote monitoring of water quality data can be precisely attained and displayed in real-time by using the proposed monitoring system.Â Â
Identifying the Most Effective Feature Category in Machine Learning-based Phishing Website Detection
Authors: Lin Tan Choon , Leng Chiew Kang , Musa Nadianatra , Hanani Abang Ibrahim Dayang 
Published: July 2024

This paper proposes an improved approach to categorise phishing features into precise categories. Existing features are surveyed from the current phishing detection works and grouped according to the improved categorisation approach. The performances of various feature sets are evaluated using the C4.5 classifier, whereby the content URL obfuscation category is found to perform the best, achieving an accuracy of 95.97%. Additional benchmarking is conducted to compare the performance of the winning feature set against other feature sets utilised in existing phishing detection techniques. Results suggest that the winning feature set is indeed an effective feature category which has contributed significantly to the performance of existing machine learning-based phishing detection systems.Â Â
An Industry Involvement to Enhance the HCI Small-Scale Project Learning Experience
Authors: Kamaruddin Azrina , Indriasari Mansor Evi , Indriaty Admodisastro Novia , Mohd Norowi Noris , Abdullah Salfarina 
Published: July 2024

Human-computer interaction (HCI) is one of the courses that require in-depth involvement with the end-user to build usable and useful software. The course consists of both theory and practical aspects. One element in this course is doing project work. Throughout the semester, the project has been about a lecturer assigning groups of students with project topics for them to complete by the end of the semester. It is a common practice and has led the students to stagnant learning experience throughout the semester. In order to make studentsâ€™ learning experience more challenging and engaging, the project has included the industry as part of its 14 weeks duration. The industry was involved in giving the project title, persona, and conducted formative and summative assessments. Finally, an interview session was conducted with the students to obtain information about their learning experiences with the industry involvement while doing their project. The study received both positive and negative feedback from students about this approach.Â Â
Understanding Factors that Affect Information Technology Outsourcing of Government Shared Services
Authors: Ahmad Fadzilah , Ali Rosmah , Maarop Nurazean , Firdaus Mohd Azmi Nurulhuda 
Published: July 2024

One of the Public Sector Information Communication Technology Strategic Directions for 2016 â€“ 2020 is to optimize shared services through a centralized and structured initiative. Due to some identified problems and challenges in managing the IT outsourcing arrangement, this study aims to explore the factors that could influence the success implementation of Information Technology (IT) outsourcing of government shared services (GSS) in the case of Malaysian public sector. The motivation in this study is originated from the clear problem in outsourced GSS implementation. This study was initiated by reviewing the literature on the currents issues and best practices across countries regarding the implementation of outsourcing shared services. The result is presented based on qualitative case study entailing interviews with key informants to gather information and the data analysis was performed based on the content analysis. Subsequently, nine factors that potentially influence the successful arrangement of IT outsourcing of government shared services were identified and organized into 4-domains: Strategy, Organization, Transformation and Operation.Â Â
Knowledge Management Strategy and Initiative for Development of Digital Energy Hub
Authors: Bin Kasim Hairoladenan , . . , . . 
Published: July 2024

This article revised several Knowledge Management (KM) strategies and initiatives, in order to develop the digital energy hub. This digital platform employs robust computers and network technology to cater for a wide-range exchange of information and knowledge, which eventually supports new businesses, collaboration and globalization for the energy players. The objective of this article is to analyze KM strategy and initiative for the purpose of developing a digital energy hub. Among the important strategies are goal setting, KM leadership, structure and skill; supported by essential initiatives such as knowledge creation, transfer and sharing.Â Thus, by accurately identifying the relevant KM strategies and initiatives, the probability for future development and deployment of this platform to be successful can be enhanced.Â
Enhancing Scrum Framework: a Case at a Multinational Manufacturing Company in Malaysia
Authors: Mariyappan Shalini , Lee Abdullah Nasuha , Idrus Rosnah 
Published: July 2024

Many organizations today are adopting Scrum, an Agile methodology for handling complex software project. Despite all the benefits, there are still issues and challenges in adapting to Agile and some refusals to move from traditional method. This research aims to assess the perception of effectiveness of implementation of Scrum and identify the challenges after adopting Scrum in an information Â Â Â Â Â Â Â Â Â technology (IT) department of company X, a multinational manufacturing company in Malaysia. The findings of this study revealed that after one year of adopting Scrum, the perceptions from the staff is there is no significant improvement made. Five challenges wereÂ Â Â identified: team members unaware of each otherâ€™s tasks, difficulty in handling daily task priorities, no work synchronization among Â Â Â Â Â Â Â Â Â Â Â management and delivery team, too many tasks at the middle of sprints and poor attendance during daily stand up meeting. An enhanced Scrum framework that uses Scrum and Kanban is proposed to address the identified challenges. The insights gained from this research hope to provide practitioners with useful reference for adopting scrum.Â Â
Systematic Review on Ear Identification
Authors: Alemran Ahmad , Binti Rahmatullah Bahbibi , Hadi Ali 
Published: July 2024

Context: The topic is permitted from modern topics of interest for researchers to find logical solutions to problems of detection and recognition for ear identification. Therefore, we are looking for a solution to the problem of occlusion, detection and recognition of the person create an integrated system based on the latest research and to find new results in terms of accuracy and time and be comprehensive for everything.Objective: To survey researchersâ€™ efforts in response to the new and disruptive technology of ear identification systems, mapping the research landscape form the literature into a coherent taxonomy.Method: We use a systematic review as the basis for our work. a systematic review builds on 249 peer-reviewed studies, selected through a multi-stage process, from 1960 studies published between 2005 and 2017.Results: We develop a taxonomy that classifies the ear identification systems. The results of these articles are divided into three main categories, namely review and survey article, studies conducted on ear biometrics and development of ear biometric applications.Conclusion: The paper is, to our knowledge, the largest existing study on the topic of ear identification. This typically reflects the types of available systems. Researchers have expressed their concerns in the literature, and many suggested recommendations to resolve the existing and anticipated challenges, the list of which opens many opportunities for research in this field.Â Â
Privacy Preserving Technique for Mitigating Anonymity Attack in Pervasive Social Networking Applications
Authors: Ayuni binti Adnan Nurâ€™ , Mahinderjit Singh Manmeet , Jantan Aman 
Published: July 2024

Pervasive Social Networking (PSN) applications become more popular in the last few years. The uses of PSN applications through mobile devices such as smartphones, tablets will lead to the security and privacy issues. This is because users tend to share their personal information with the third party organizations such as applications in mobile devices. Due to the development of social network, the security and privacy need to be improved as well as others to make sure that all the userâ€™s information is protected securely in social network (SN). In this study, we will focus more on the privacy issues on how to preserve the privacy of userâ€™s data from being known by the third party. The dataset of PSN application will be tested using data mining tool, which is Weka, in order to identify the optimal technique and classifier that can be applied to conceal the information. Then, a new enhanced base learner will be proposed, which is masking technique algorithms will be implemented into the dataset of PSN application at the end of this research.Â Â
Attributes Correspondence Discovery in Ontology Instance-based Matching and RDF Data Linkage using Clustering Method
Authors: Abubakar Mansir , Hamdan Hazlina , Mustapha Norwati , Noranis Mohd Aris Teh 
Published: July 2024

One important aspect of ontology instance matching process is elements or attributes discovery. It specifies element correspondences in order to produce potential matching elements; otherwise, all elements of a class in the source ontology have to be compared with all elements of class in the target ontology. This heavy comparison is time-consuming and resulted in the poor performance of the matching system and makes the matching incomplete. Matching two or more ontologies and RDF datasets requires complete instance matching so as to establish logically equivalent relation among semantically related entities of the data sources. This deems challenging because of the existence of semantic heterogeneity and presence of irregular data in the RDF data sources which makes elements discovery and feature value extractions difficult. Thus, we proposed a four-step elements discovery method that utilizes unsupervised K-Medoids clustering algorithm in discovering potential matching elements pairs. To ensure generalization, we take unsupervised Canopy Clustering method to be the baseline for our evaluation. In terms of scalability, our method outperforms the baseline method with approximately 99% in both Pair Completeness and Reduction Ratio as against 60% and 86% respectively in the baseline. In mapping pattern generation, our method also outperforms the baseline algorithm with the overall F-Measure of ~91% against ~85%. The result of comparism with other methods justifies the significance effect of clustering attributes in the initial stage of the instance matching which can save about 50% of the comparism.Â Â
Role Minimization as an Optimization Metric in Role Mining Algorithms: a Literature Review
Authors: Abd. Hamid Nazirah , Ahmad Rabiah , Rahayu Selamat Siti 
Published: July 2024

A recent access control model that could accommodate a dynamic structure such as cloud computing can be recognized as role based access control and the role management process of this access control can be identified as role mining. The current trend in role based access control is the role mining problem that can be described as the difficulty to uncover an optimum set of roles from the user-permission assignment. To solve this problem, the researchers have proposed role mining algorithms to produce role set and among the existing algorithms there is an intrinsic topic of the common perception to evaluate the goodness of the generated role set. Eventually, the value of the identified roles could be measured by the preferred metric of optimality namely the number of roles, sizes of user-assignment and permission-assignment and Weighted Structural Complexity. Until now, there is some disagreement on the optimization metric but notably many researchers have agreed on the minimization of the number of roles as a solid metric. This paper discusses an overview of the current state-of-the-art on the recent role mining algorithms that focus on role minimization as an optimization metric to evaluate the goodness of the identified roles.Â Â
HARIRAYA: a Novel Breast Cancer Pseudo-Color Feature for Multimodal Mammogram using Deep Learning
Authors: Shahrel Ahmad Nazri Azree , Agbolade Olalekan 
Published: July 2024

Breast cancer is the leading cancer in the world. Mammogram is a gold standard for detecting breast cancer at earlier screening because of its sensitivity. Standard grayscale mammogram images are used by expert radiologists and Computer Aided-Diagnosis (CAD) systems. Yet, this original x-ray color provides little information to human radiologists and CAD systems to make decision. This binary color code thus affects sensitivity and specificity of prediction and subsequently affects accuracy. In order to enhance classifier modelsâ€™ performance, this paper proposes a novel feature-level data integration method that combines features from grayscale mammogram and spectrum mammogram based on a deep neural network (DNN), called HARIRAYA. Pseudo-color is generated using spectrum color code to produce Spectrum mammogram from grayscale mammogram. The DNN is trained with three layers: grayscale, false-color and joint feature representation layers. Empirical results show that the multi-modal DNN model has a better performance in the prediction of malignant breast tissue than single-modal DNN using HARIRAYA features.Â Â Â
Channel Estimation in OFDM Multipath Fading Channel Systems According to Modulation Schemes
Authors: Abdullah Al-Saadi Alaa , Latip Rohaya , Muhammed Abdullah , Helmy Abd Wahab Mohd 
Published: July 2024

Orthogonal Frequency Division Multiplexing system (OFDM) is a very popular communication technique. It is applied nowadays in several wireless network modern systems. Wireless communication system has some limitations; one of them is Multi Path Fading Channel. This issue leads to impact and deteriorate data signal severely which causes the inter channel interferences (ICI). Therefore, our paper is specifically focused on study of the importance of applying channel estimation in OFDM system which leads to be close to an accurate data. Basically, there are many types of channel estimation techniques, e.g., Least Square Error Estimation (LSE) and Minimum Mean-Square (MMSE). In our study, we utilised LSE and proved the necessity of applying channel estimation in multi path fading channel based on QPSK modulation scheme. We verify that by applying simulation codes in Matlab. Moreover, we make a comparison by sending data, e.g., Baboon image with and without channel estimation technique. Our study is to proof the importance of channel estimation with multi path fading channel in OFDM technique.Â Â
A Logical Approach for Real Time Big Data Analytics on Heterogeneous Nosql Databases
Authors: HAJOUI Omar , Talea Mohamed 
Published: July 2024

NoSQL databases are developed to provide a set of new big data management features while overcoming certain limitations of relational databases. However, these databases are heterogeneous; they provide different mechanisms for storing and retrieving data, which directly affect the performance, consistency and availability of data. In addition, they offer different models of data storage, different implementations, query languages and APIs. This wide variety of platforms makes data interoperability difficult. Data interoperability can be defined as the ability of an application to interact at the same time with a set of different and heterogeneous systems. The goal of our research is to design a new approach that makes it easy for applications to analyze and explore data stored in multiple NoSQL databases. Our approach is based on a Meta model for transforming data from one model to another. Also, we have developed a common API that hides the access specificities of each NoSQL database while allowing the transformation of this data into JSON format.Â Â
Novel Hsv Colour Space based Threshold Method for Vegetation Extraction and its Performance on Landsat TM Images
Authors: Maarir Abdelkrim , Benyoucef Abdelhalim , Bouikhalene Belaid 
Published: July 2024

This paper deals with a novel proposed vegetation extraction method applied in multi spectral satellite images (Landsat TM). This proposed method essentially consists of three steps: image enhancement using histogram equalisation, image transformation to new colour model called HSV (Hue, Saturation, and Value) and thresholding application on Hue and Saturation components.Â For post-processing a hybrid filter median has been used to improve the results and remove isolated pixels. The proposed method is applied to three different scenes of Beni Mellal region in Morocco. The obtained results are compared with two other thresholding methods. Pixels identified as vegetation have an average sensitivity value of 95.88% and an accuracy value of 93.02%.Â Â
Adsorption of Organic Dye Methylene Blue on Activated Carbon Prepared from Wood
Authors: Elmerzouki Khadija , Bimaghra Itto , Sahlaoui Ahmmed , Lghazi Youssef , Ait himi Mohamed 
Published: July 2024

Developing countries are the most exposed to pollution problems. To cope, they must develop integrated environmental management policies (water management, air treatment, treatment of industrial effluents, etc.). As a result, different treatment methods must be used to reduce these problems. This work aimed to evaluate the feasibility of fixing organic dye such as methylene blue using activated carbon (ACW) prepared from inexpensive precursor (sawdust) by chemical and thermal activation. The adsorption efficiency depends on several parameters such as the initial pH of the solution, the contact time and the mass of ACW. The adsorption isotherms were studied according to the Freundlich and Langmuir models, and the best was chosen on the basis of the comparison of their correlation coefficient results.Â Â
Extended Enterprise Metamodeling for Strategic Information System Alignment: Case Study
Authors: Falih N. , Abouhilal A. , . . 
Published: July 2024

The enterprise meta-modeling is an important process for studying and managing organizations in order to improve their performance; it allows representing all views of the company for better governance. In this paper, we propose an extension of the ISO/DIS 19940 Meta-model by adding strategic constructs and specific tools from the Cobit framework. This extended meta-modeling allows a systemic and holistic analysis based on Galois lattices to intelligently drive the alignment of several components of the company. We also present a case study in a Moroccan transport company. We analyze a particular structural matrix to identify any relevant information that may contribute to process reengineering for Information System governance.Â Â
Application of Artificial Intelligence Technologies for the Monitoring of Transactions in AML-Systems Using the Example of the Developed Classification Algorithm
Authors: G. Magomedov S. , S. Dobrotvorsky A. , M.P. Khrestina M. , A. Pavelyev S. , R. Yusubaliev T. 
Published: July 2024

The article describes the application of artificial intelligence technologies in Anti Money Laundering (AML) systems for the purpose of transaction monitoring by the example of the developed transaction classification algorithm using machine learning methods. To improve the effectiveness of the algorithm a novel mechanism for forming a unique set of characteristics for the transactions and the participants of financial processes has been developed and a method for constructing a transaction graph has been proposed.Â Â
The Procedure for Identifying the Compliance of the Performerâ€™s Competencies with the Stated Requirements Based on The Bayesian Approach
Authors: V.Zaitseva T. , V. Lomakin V. , P. Putivtseva N. , P. Pusnaya O. , V. Ilyinskaya E. 
Published: July 2024

Â The article proposes a procedure for the selection of personnel to perform specific activities based on a comparison of the general professional and professional competences obtained in the training process to the required level of qualification in order to effectively allocate labor resources. In this paper, a fragment of an example of the implementation of the procedure based on the use of professional standards for the large group 06.000 - Communication, information and communication technologies. The use of posterior probabilities calculated during the implementation of the procedure allows management personnel to make a decision on the selection of personnel with the most appropriate qualification for solving a particular task.Â Â
A Study on Ship Manoeuvring Simulation and Ship Trajectory Optimization Based on Sqp and Bfgs Algorithms from Sea Trials
Authors: Khanh Toan Tran , . . 
Published: July 2024

In this study, a procedure is proposed to optimize the shipâ€™s trajectory by identification of optimal hydrodynamic coefficients from sea trials, which coupled the dynamic ship motion model with optimization techniques. In order to assess efficiently the hydrodynamic parameters, a sensitivity analysis is first per- formed to identify the most sensitive coefficients, then an identification procedure, based on SQP and BFGS algorithms, is carried out to determine optimal hydrodynamic parameters. The validation of this procedure is done for Turning Circle and Zig-Zag tests by using experimental data of sea trials of the Esso Bernicia 193000DWT Tanker model. Comparisons between experimental and computed data show a fair agreement of overall tendency in ship trajectories. The RMSD (Root-Mean-Square Deviation) of ship trajectory decreases from 68.0m to 5.8m in Turning Circle test, and RMSD of yaw angle decreases from 17.3deg to 6.6deg in Zig-Zag test.Â Â Â
Comparative Analysis of Tools for Modelling Business Processes of Organization Management
Authors: Lomakin V. , P. Putivtseva N. , V. Zaitseva T. , P. Pusnaya O. , M. Zaitsev I. 
Published: July 2024

The article presents the result of a comparative analysis of software tools that allow modelling business processes of organizations. For comparison, those software tools for modelling business processes that support the BPMN methodology were chosen. As a method of conducting a comparative approach, a comprehensive approach was used, including the use of the hierarchy analysis method, which allows us to find the weight of comparison criteria that were identified on the basis of the analysis of literature sources, Internet resources, and features of the functionality of the business process modelling tools selected for comparison , and a formalized approach that allows calculating the priorities of alternative software modelling tools depending on their grades by dedicated channels on each criterion.Â Â