bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Study on Detecting Misleading Online News Using Bigram and Cosine Similarity
Authors: Che Eembi Normala , Ishak Iskandar , Sidi Fatimah , Suriani Affendey Lilly 
Published: July 2024

Fake news can impact negatively in terms of creating negative perception towards business, organization, and government. One of the ways that fake news is created is through deceptive news writing. Many researchers have developed approaches in detecting deceptive news content using machine-learning approach and each of the approach has its own focus. Previous researches emphasis on the components of the news content such as indetecting grammar, humor, punctuation, body-dependent and body-independent features. In this paper, a new approach in detecting deceptive news based on misleading news has been developed which is focusing on the similarity between the content and its headlines using bigram and cosine similarity. Based on the experiments, the proposed approach has better performance in terms of detecting deceptive news.Â Â
RESQ Banjir: a Mobile Apps for Emergency Rescue, Evacuation and Relief Center Management
Authors: Rafie Mohd Arshad Muhammad , Hj Mohamed Hasimah , Heikal Husin Mohd , Hafinaz Hassan Fadratul , Mohd Nazmee Wan Zainon Wan , Rahim Ahmad Abdul , Sabudin Maziani , . . 
Published: July 2024

A quick response to urgent relief needs after a natural disaster is vital to the alleviation of a disasterâ€™s impact in the affected areas. Flood victims had difficulties in sending emergency relief requests as they had limited phone battery life to highlight their current location.Â Such limitation led to the difficulty in locating the victims, which affected the effectiveness of coordinating a rescue and evacuation operation. In this research, we develop ResQ Banjir application which consists of Flood Rescue & Evacuation Operation Management (FREOM) and Flood Relief Centre Management (FRCM) to assist in flood disaster management. In these system, we exploits the existing and emerging technologies on smart phones and tablet such as sensors, cameras, GPS, SMS, Location Based System (LBS) and Augmented Reality (AR). The FREOM system is a web and mobile apps based system consist of the Rescue & Evacuation Management System (server) for rescue and evacuation operation monitoring & management at the flood operation center; SOS/SMS Flood apps for sending SOS help by victims; ResQ Banjir Skuad Penyelamat apps which is used by rescue teams to locate and rescue flood victims, and an Augmented Reality (AR) guidance system for location direction navigation guide. FRCM is a web based system which integrates a number of features such as flood relief center registry, shelter activation and management, inventory management and disbursement, and relief aid and goods supplies management.Â We conducted a simulation testing that involves the overall capability of the applications. Both systems seem to be working in an efficient manner although there are some issues that exist.Â Â
Solving Classification Problem Using Ensemble Binarization Classifier
Authors: N. Shah Zainudin M. , Nasir Sulaiman Md. , Musapha Norwati , Perumal Thinagaran , Mohamed Raihani 
Published: July 2024

Binarization strategy is broadly applied in solving various multi-class classification problems. However, the classifier model learning complexity tends to increase when expanding the number of problems into several replicas. One-Versus-All (OVA) is one of the strategies which transforming the ordinal multi-class classification problems into a series of two-class classification problems. The final output from each classifier model is combined in order to produce the final prediction. This binarization strategy has been proven as superior performance in accuracy than ordinal multi-class classifier model. However, learning model complexity (eg. Random Forest-RF ensemble decision trees) tends to increase when employing a large number of trees. Even though a large number of trees might produce a decent accuracy, generating time of the learning model is significantly longer. Hence, self-tuning tree parameter is introduced to tackle this matter. In such circumstances, a number of trees in the RF classifier are defined according to the number of class problem. In this paper, the OVA with self-tuning is evaluated based on parameter initialization in the context of RF ensemble decision tree. At the same time, the performance has also been compared with two classifier models such J48 and boosting for several well-known datasets.Â Â
Case Study of UPNM Students Performance Classification Algorithms
Authors: B. Rahayu Syarifah , D. Kamarudin Nur , Zainol Zuraini 
Published: July 2024

Most students have a problem to keep track on their learning performance.Â Some lecturers with high teaching hours and burden of administration jobs may have difficulty to identify weak and low performance students. In this study, three classification techniques are applied on educational datasets to predict the studentsâ€™ performance based on coursework assessments. Thus, this prediction results may help lecturers and students to improve their teaching and learning process. The objective of study is to predict studentsâ€™ performance based on coursework assessments using classification algorithms. The selected classification algorithms applied in this study such as J48 Decision Tree, NaÃ¯ve Bayes and kNN. WEKA is used as an experimental tool. The selected algorithms are applied on a data of student database of Data Mining subject. Findings shows NaÃ¯ve Bayes outperforms other classification algorithms with above 80% prediction rate. Thus, the studentsâ€™ performance for Data Mining Subject is improved. As a conclusion, the classification algorithms can predict studentsâ€™ performance on a particular subject based on coursework assessments.Â Â
Near Field Communication (NFC) Technology Security Vulnerabilities and Countermeasures
Authors: Mahinderjit Singh Manmeet , Aina Afiqah Ku Adzman Ku , Hassan Rohail 
Published: July 2024

Nowadays; the adoption of Internet of things (IoT) technologies and applications in everyday is rising. IoT technology such as Near Field Communication (NFC) is vastly adopted due to its short range frequencies, making it a good candidate for token based security access control applications such as door systems and attendance systems. However, due to the miniature size of NFC tags; its clear text contents and unprotected communication channel between tag-reader-database; NFC technology is prone to security attacks such as the man in the middle; denial of services (DOS) and etc. These attacks lead to leakage of user critical data which could impact any organization adopting NFC applications and technologies. In this paper; NFC vulnerability, causing both security and privacy attacks studies in depth. By focusing on attacks such as DOS and data corruptions; existing risk assessment models are evaluated using Analytical Hierarchy Process (AHP) approach. Best practice in mitigating these attacks is presented as well. A case study on an existing NFC access control application is then used to demonstrate the effectiveness of best practice solutions proposed.Â Â Â
Optimising the Space Utilisation in Real-Time Flash Translation Layer Mapping Scheme
Authors: Bazli Ab. Karim Mohd , Rizaan Rahiman Amir , Latip Rohaya Solid-State Disk (SSD) is a semic , Ibrahim Hamidah 
Published: July 2024

Solid-State Disk (SSD) is a semiconductor storage device and it has become a preferred choice for many storage sub-systems solutions to replace the classical hard drives due to its high performance and durability. Moreover, NAND flash memory has become cheaper in costs. However, this flash memory type has its own limitations due to its erase-before-write operations nature. This limitation will cause the memory to wear faster and consuming higher cost when initiating the cleaning process. To overcome the limitation, an address mapping in NAND flash memory namely Flash Translation Layer (FTL) plays important role in handling I/O operations. Several studies on the FTL have been carried out to manage the IO operations in NAND flash device efficiently. This paper proposed an optimized address-mapping scheme called Optimized Real-Time Flash Translation Layer (ORFTL). In order to increase the NAND flash space utilization, the proposed scheme reduces idle buffer blocks and reassigns the blocks as new Logical Block Addressing (LBA) in order to optimize blocks in flash memory for more space utilization. In addition, the scheme introduces a pool of buffer blocks with the same bandwidth throughput size of IO interface that connects the SSD to the host system in order to guarantee available free spaces to serve write operations. By optimizing both types of blocks, the proposed scheme has shown significant increases in the NAND flash memory space utilization as compared to the existing FTL schemes.Â Â Â
Performance Evaluation of Load Balancing Algorithm for Virtual Machine in Data Centre in Cloud Computing
Authors: A/P Parmesivan Yuganes , Hasan Sazlinah , Muhammed Abdullah 
Published: July 2024

Cloud computing has become biggest buzz in the computer era these days. It runs entire operating systems on the cloud and do everything on cloud to store data off-site. Cloud computing is primarily based on grid computing, but itâ€™s a new computational model. Cloud computing has emerged into a new opportunity to further enhance way of hosting data centre and provide services. The primary substance of cloud computing is to deal the computing power, storage, different sort of stages and services which assigned to the external users on demand through the internet. Task scheduling in cloud computing is vital role optimisation and effective dynamic resource allocation for load balancing. In cloud, the issue focused is under utilisation and over utilisation of the resources to distribute workload of multiple network links for example, when cloud clients try to access and send request to the same cloud server while the other cloud server remain idle at that moment, leads to the unbalanced of workload on cloud data centers. Thus, load balancing is to assign tasks to the individual cloud data centers of the shared system so that no single cloud data centers is overloaded or under loaded. A Hybrid approach of Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm is combined in order to get effective response time. The proposed hybrid algorithm has been experimented by using CloudSim simulator. The result shows that the hybrid load balancing algorithm improves the cloud system performance by reducing the response time compared to the Honey Bee (HB) and Particle Swarm Optimisation (PSO) load balancing algorithm.Â Â
Ilung: Interactive Holographic Medical Application for Lung CT Scans Using Hololens
Authors: Al Khayer Aala , Indriasari Mansor Evi 
Published: July 2024

This research aims to design a holographic medical application for lung CT scans using Microsoft HoloLens. iLung application offers users the possibility to interact with the actual lung of a patient in a mixed reality and 3D environment. A prototype of the iLung was developed based on raw CT scans data and converted into 3D model generation. This paper reports the earlier stage in designing the application. Based on the applicationâ€™s overview with a group of users, the findings gathered showed that iLung prototype facilitates interactive manipulation and exploring of the 3D lung object. Feedback and comments were recorded for future improvements such as air taping interaction method and voice command.Â Â Â
Elderly Experience Evaluation through Medication Learning Application with Augmented Reality
Authors: Alnabit Nuha , Indriasari Mansor Evi 
Published: July 2024

Technology advancement has been providing innovative solutions to assist elderly to overcome many challenges they face when learning about their medication due to their declining abilities. However, due to the lack of proper understanding of elderly experience and poor representation of their requirements, many of these solutions are rejected.Â Natural and simple interactions are one of the main features elderly require to adopt technology which can be supported through the integration of augmented reality technology with these solutions. This paper focused on studying elderly interaction with an augmented reality medication learning application and evaluating their experiences as a user from the perspective of visceral, behavioral and reflective levels at an early stage of the development process. The results indicated positive feedbacks with considerations when developing similar application for the future.Â Â Â
Musafir Ilmu Apps Development Using Mobile Application Development Life Cycle
Authors: Azma Nasruddin Zan , Mazlin Irwan , Abdul Aziz Maslina , Shukor Abd Rahman Mohd , Adilah Wan Adnan Wan 
Published: July 2024

The presence of mobile wireless technology has changed the current learning culture environment. Today, smartphone has become an essential device for effective learning. Many mobile apps have been developed coveringÂ digital contents for all sorts of disciplines. This paper presents the development of mobile application for Muslims which is focusing on Hijaiyyah pronunciation.Â Â This application is named Musafir Ilmu Application with aims to help improve the learning process of Hijaiyyah pronounciation. The Mobile Application Development Life Cycle is employed in the development of the apps. This application has been tested on 32 UiTM students by observation method. Performance of the application is measured using Confusion matrix which calculate the precision and recall rates. The results have indicated the app is an effective learning tool.Â Â
Automatic Lexical Alignment between Relational Database and Heterogeneous Big Data Based on NOSQL Systems
Authors: BATOUTA Zouhair IBN , Omar HAJOUI , Mohamed TALEA 
Published: July 2024

In the absence of a universal consensus governing the use of models, the IDM has led to the creation of a large number of heterogeneous (distinct) meta-model systems with similar or complementary uses and objectives. To solve this problem of increasing heterogeneity of meta-models, we proposed an approach that we named generative automatic matching GAM. In this approach, we have dealt with the problem of the heterogeneity of meta-models in a new way that uses automatic matching, the alignments found are then took into profit to facilitate generation between source and target models which are conform to the linked meta-models.Â This article presents an application of our GAM approach on a case study composed of heterogeneous meta-models of relational databases and big data, we specially treat the application of lexical automatic matching based on hybrid meta-heuristic. We have selected three types of databases and big data based on NoSql: Key Store, Document Store and Columnar Store; at the end of our article we present an evaluation of the results found based on quality mathematical measurements.Â Â
Multi-Objective Optimization of a Family House Performance and Forecast of its Energy Needs by 2100
Authors: Serbouti Abdelhadi , Rattal Mourad , Boulal Abdellah , Oualim El Mostafa , Mouhsen Azeddine 
Published: July 2024

This paper describes a general multi-objective optimization approach of the energy performance of buildings using genetic algorithms, and the forecast of future energy needs according to the IPCC climate change scenarios. To this end, the energy performance of a family house is optimized and the optimal solution is studied in a future context marked by global warming and rise of temperatures.Â Â Â
The Recommending Courses based on the Similarity of Studentsâ€™ Preferences
Authors: Hachem Alaoui Harouni Moulay , Hachem El-Kaber , Ziti Cherif , Bassiri Mustapha , Lu Joan 
Published: July 2024

To keep students in touch, they need to be caught through proposing different courses similar to the ones they are interested in. The present paper is going to discuss the idea of recommending courses and how it will be applied into student profiles as the result of clustering the books or courses as well as the student preferences. It will illustrate the way the item and student profiles enable to recommend courses in our system.Â Â
Low-cost Smart Architecture for Classroom Response System Using Raspberry: RaspCRS
Authors: Moulay Taj A. , Abouhilal A. , Taifi N. , Antari J. , Malaoui A. 
Published: July 2024

The purpose of this paper is to present a low-cost architecture based on embedded systems for the operation of a Classroom Response System (CRS). In order to validate the proposed architecture, various tests were conducted with 30 students enrolled in a renewable energy master. As part of this study, a mobile-based CRS has been developed using web-based technologies that makes the system very easy to use in educational environments. It allows the teacher to interview students using multiple-choice questions, in order to test their understanding of a concept discussed in class, the results of a question are displayed in real time on the mobile of the teacher. This tool has a strategic character because it allows improving the image of our university, pursuing the paths of smart cities. The results of test show the advantages and limitations of this architecture.Â Â Â
Laser Technology of Optical Meta-Materials
Authors: D. Volpyan O. , I. Kuzmichev A. , A. Obod Yu. , S. Sigov A. 
Published: July 2024

The basic methods of laser technology used to obtain 2D and 3D meta-materials are considered. The main attention is paid to the methods of forming submicron and nanometer structures using the two-photon polymerization effect and various types of laser interference lithography. It is shown that these technological methods, being planar and scalable, are promising for use in industrial optical production due to their potentially high productivity and low cost compared to many other methods of nanotechnology, in particular, with electronic lithography and processing with focused ion beams.Â Â
Prospects for The Use of Nanotechnology for The Manufacture of Optical Meta-Materials.
Authors: D. Volpyan O. , I. Kuzmichev. A. , A. Obod Yu. , S. Sigov A. 
Published: July 2024

Nanotechnology methods for obtaining 2D and 3D meta-materials are considered. The main attention is paid to the methods of forming submicron and nanometer structures using nanotechnology methods, first of all laser methods. It is shown that these technological methods, being planar and scalable, are promising for use in industrial optical production due to their potentially high productivity and low cost compared to many other methods of nanotechnology, in particular, with electronic lithography and processing with focused ion beams.Â Â
Combination of Technology Blockchain and Multiversion Concurrency Control for Developing Database with Peer-to-Peer Atomic Safe Transactions
Authors: A. Ivanova I. , D. Kotilevets I. , S. Karbova E. , A. Pavelyev S. 
Published: July 2024

The article discusses the mechanisms of consensus algorithms used in a blockchain without connection with crypto-currencies, compares with the functionality of competitive access control technology to the database, and combines the functions of blockcahin and MultiVersion Concurrency Control in databases to obtain peer-to-peer atomic safe transactions of strictly defined "facts", written down in an irrefutable audit journal.Â Â
Modeling of Fast Neutral Atoms Flow Generation in Channel Rays of Glow Discharge
Authors: D. Volpian O. , I. Kuzmichev A. , A. Obod Yu. , S. Sigov A. 
Published: July 2024

A physical-kinetic approach has been used for modeling of fast neutral atoms flow generation in the channel rays of abnormal glow discharge. The fast atoms are generated due to charge exchange of ions accelerated by voltage drop on the cathode layer of positive space charge. The limits of applicability of the created model and the range of operating parameters of the fast atom source are established for the Ar (gas) â€“ Ta (cathode) pair. The work is directed towards implementation of the beam processing of dielectric optical nanostructured metamaterials with help of fast neutral atoms.Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â
Temperature Deformation of Cylinder-Piston Group Parts of Uprated Diesels and Gas Engines for Kamaz Vehicles
Authors: A. Nikitin D. , D. Mezhetsky G. , S. Denisov A. , N. Baskov V. , V. Chekmarev V. 
Published: July 2024

The paper describes the effect of temperature on the deformation of cylinder-piston group parts of uprated diesel engines and gas engines of the KAMAZ family. Based on the 3-D model with the use of the finite element method, the hypothesis proposed by the authors on the necessity to change a number of limiting dimensions of the cylinder-piston group parts is confirmed. The purpose is to ensure their performance at elevated temperatures in comparison with the basic engines. It is also shown that the design model is adequate to the actual operating conditions of the engines under consideration.Â Â
A Survey on Clustering Density Based Data Stream algorithms
Authors: Aljibawi Mayas , Zakree Ahmed Nazri Mohd , Othman Zalinda 
Published: July 2024

With the rapid evolution of technology, data size has increased as well. Thus, open the door to a new challenge of finding patterns such as the limitation of memory and time and the one pass to the whole data. Many clustering techniques has been developed to overcome these issues. Streaming data evolve with time, and that makes it almost impossible to define clusters number in that data. Density-based algorithm is one of the significant data clustering class to overcome this issue due to it doesnâ€™t require an advance knowledge about the number of clusters. This paper reviewed some of the existing density-based clustering algorithms for the data stream with the measurement used to evaluate the algorithm.Â Â
Evaluating the Performance of Machine Learning Techniques in the Classification of Wisconsin Breast Cancer
Authors: Ibrahim Obaid Omar , Abed Mohammed Mazin , Khanapi Abd Ghani Mohd , A. Mostafa Salama , Taha AL-Dhief Fahad 
Published: July 2024

Breast cancer is a considerable problem among the women and causes death around the world. This disease can be detected by distinguishing malignant and benign tumors. Hence, doctors require trustworthy diagnosing process in order to differentiate between malignant and benign tumors. Therefore, the automation of this process is required to recognize tumors. Numerous research works have tried to apply the algorithms of machine learning for classifying breast cancer and it was proven by many researchers that machine learning algorithms act preferable in the diagnosing process. In this paper, three machine-learning algorithms (Support Vector Machine, K-nearest neighbors, and Decision tree) have been used and the performance of these classifiers has been compared in order to detect which classifier works better in the classification of breast cancer. Furthermore, the dataset of Â Â Wisconsin Breast Cancer (Diagnostic) has been used in this study. The main aim of this work is to make comparison among several classifiers and find the best classifier which gives better accuracy. The outcomes of this study have revealed that quadratic support vector machine grants the largest accuracy of (98.1%) with lowest false discovery rates. The experiments of this study have been carried out and managed in Matlab which has a special toolbox for machine learning algorithms.Â Â Â