𝑱𝒐𝒖𝒓𝒏𝒂𝒍 𝒐𝒇 𝑪𝒐𝒎𝒑𝒖𝒕𝒆𝒓 𝑺𝒄𝒊𝒆𝒏𝒄𝒆 𝑹𝒆𝒔𝒆𝒂𝒓𝒄𝒉 | 𝑽𝒐𝒍.4, 𝑰𝒔𝒔.1

       👇👇👇👇👇𝑸𝒖𝒊𝒄𝒌 𝑮𝒖𝒊𝒅𝒆👇👇👇👇👇👇

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𝙀𝙛𝙛𝙞𝙘𝙞𝙚𝙣𝙩 𝙁𝙚𝙖𝙩𝙪𝙧𝙚 𝙎𝙚𝙡𝙚𝙘𝙩𝙞𝙤𝙣 𝙖𝙣𝙙 𝙈𝙇 𝘼𝙡𝙜𝙤𝙧𝙞𝙩𝙝𝙢 𝙛𝙤𝙧 𝘼𝙘𝙘𝙪𝙧𝙖𝙩𝙚 𝘿𝙞𝙖𝙜𝙣𝙤𝙨𝙩𝙞𝙘𝙨

DOI: https://doi.org/10.30564/jcsr.v4i1.3852

Abstract

Machine learning algorithms have been deployed in numerous optimization, prediction and classification problems. This has endeared them for application in fields such as computer networks and medical diagnosis. Although these machine learning algorithms achieve convincing results in these fields, they face numerous challenges when deployed on imbalanced dataset. Consequently, these algorithms are often biased towards majority class, hence unable to generalize the learning process. In addition, they are unable to effectively deal with high-dimensional datasets. Moreover, the utilization of conventional feature selection techniques from a dataset based on attribute significance render them ineffective for majority of the diagnosis applications. In this paper, feature selection is executed using the more effective Neighbour Components Analysis (NCA). During the classification process, an ensemble classifier comprising of K-Nearest Neighbours (KNN), Naive Bayes (NB), Decision Tree (DT) and Support Vector Machine (SVM) is built, trained and tested. Finally, cross validation is carried out to evaluate the developed ensemble model. The results shows that the proposed classifier has the best performance in terms of precision, recall, F-measure and classification accuracy.

Keywords

Accuracy; Classifier; Ensemble; F-measure; Machine learning; Precision; Recall

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𝙀𝙢𝙗𝙚𝙙𝙙𝙞𝙣𝙜 3-𝘿 𝙂𝙖𝙯𝙚 𝙋𝙤𝙞𝙣𝙩𝙨 𝙤𝙣 𝙖 3-𝘿 𝙑𝙞𝙨𝙪𝙖𝙡 𝙁𝙞𝙚𝙡𝙙: 𝘼 𝘾𝙖𝙨𝙚 𝙤𝙛 𝙏𝙧𝙖𝙣𝙨𝙥𝙖𝙧𝙚𝙣𝙘𝙮

DOI: https://doi.org/10.30564/jcsr.v4i1.4037

Abstract

The paper seeks to demonstrates the likelihood of embedding a 3D gaze point on a 3D visual field, the visual field is inform of a game console where the user has to play from one level to the other by overcoming obstacles that will lead them to the next level. Complex game interface is sometimes difficult for the player to progress to next level of the game and the developers also find it difficult to regulate the game for an average player. The model serves as an analytical tool for game adaptations and also players can track their response to the game. Custom eye tracking and 3D object tracking algorithms were developed to enhance the analysis of the procedure. This is a part of the contributions to user interface design in the aspect of visual transparency. The development and testing of human computer interaction uses and application is more easily investigated than ever, part of the contribution to this is the embedding of 3-D gaze point on a 3-D visual field. This could be used in a number of applications, for instance in medical applications that includes long and short sightedness diagnosis and treatment. Experiments and Test were conducted on five different episodes of user attributes, result show that fixation points and pupil changes are the two most likely user attributes that contributes most significantly in the performance of the custom eye tracking algorithm the study. As the advancement in development of eye movement algorithm continues user attributes that showed the least likely appearance will prove to be redundant.

Keywords

User Behaviour; 3D gaze point; Eye movement; User behaviour; 3D visual interface; 3D game console; User experience

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𝘼 𝘾𝙖𝙨𝙚 𝙎𝙩𝙪𝙙𝙮 𝙤𝙛 𝙈𝙤𝙗𝙞𝙡𝙚 𝙃𝙚𝙖𝙡𝙩𝙝 𝘼𝙥𝙥𝙡𝙞𝙘𝙖𝙩𝙞𝙤𝙣𝙨: 𝙏𝙝𝙚 𝙊𝙒𝘼𝙎𝙋 𝙍𝙞𝙨𝙠 𝙤𝙛 𝙄𝙣𝙨𝙪𝙛𝙛𝙞𝙘𝙞𝙚𝙣𝙩 𝘾𝙧𝙮𝙥𝙩𝙤𝙜𝙧𝙖𝙥𝙝𝙮

DOI: https://doi.org/10.30564/jcsr.v4i1.4271

Abstract

Mobile devices are being deployed rapidly for both private and professional reasons. One area of that has been growing is in releasing healthcare applications into the mobile marketplaces for health management. These applications help individuals track their own biorhythms and contain sensitive information. This case study examines the source code of mobile applications released to GitHub for the Risk of Insufficient Cryptography in the Top Ten Mobile Open Web Application Security Project risks. We first develop and justify a mobile OWASP Cryptographic knowledgegraph for detecting security weaknesses specific to mobile applications which can be extended to other domains involving cryptography. We then analyze the source code of 203 open source healthcare mobile applications and report on their usage of cryptography in the applications. Our findings show that none of the open source healthcare applications correctly applied cryptography in all elements of their applications. As humans adopt healthcare applications for managing their health routines, it is essential that they consider the privacy and security risks they are accepting when sharing their data. Furthermore, many open source applications and developers have certain environmental parameters which do not mandate adherence to regulations. In addition to creating new free tools for security risk identifications during software development such as standalone or compiler-embedded, the article suggests awareness and training modules for developers prior to marketplace software release.

Keywords

OWASP mobile threats; Cryptography; Mobile application; mHealth; Healthcare; Android

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𝙋𝙚𝙧𝙞𝙤𝙙𝙞𝙘 𝙎𝙤𝙡𝙪𝙩𝙞𝙤𝙣 𝙛𝙤𝙧 𝙖 𝘾𝙤𝙢𝙥𝙡𝙚𝙭-𝙫𝙖𝙡𝙪𝙚𝙙 𝙉𝙚𝙩𝙬𝙤𝙧𝙠 𝙈𝙤𝙙𝙚𝙡 𝙬𝙞𝙩𝙝 𝘿𝙞𝙨𝙘𝙧𝙚𝙩𝙚 𝘿𝙚𝙡𝙖𝙮

DOI: https://doi.org/10.30564/jcsr.v4i1.4374

Abstract

For a tridiagonal two-layer real six-neuron model, the Hopf bifurcation was investigated by studying the eigenvalue equations of the related linear system in the literature. In the present paper, we extend this two-layer real six-neuron network model into a complex-valued delayed network model. Based on the mathematical analysis method, some sufficient conditions to guarantee the existence of periodic oscillatory solutions are established under the assumption that the activation function can be separated into its real and imaginary parts. Our sufficient conditions obtained by the mathematical analysis method in this paper are simpler than those obtained by the Hopf bifurcation method. Computer simulation is provided to illustrate the correctness of the theoretical results.

Keywords

Complex-valued neural network model; Delay; Periodic solution

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𝘼 𝙎𝙩𝙪𝙙𝙮 𝙤𝙣 𝘼𝙪𝙩𝙤𝙢𝙖𝙩𝙞𝙘 𝙇𝙖𝙩𝙚𝙣𝙩 𝙁𝙞𝙣𝙜𝙚𝙧𝙥𝙧𝙞𝙣𝙩 𝙄𝙙𝙚𝙣𝙩𝙞𝙛𝙞𝙘𝙖𝙩𝙞𝙤𝙣 𝙎𝙮𝙨𝙩𝙚𝙢

DOI: https://doi.org/10.30564/jcsr.v4i1.4388

Abstract

Latent fingerprints are the unintentional impressions found at the crime scenes and are considered crucial evidence in criminal identification. Law enforcement and forensic agencies have been using latent fingerprints as testimony in courts. However, since the latent fingerprints are accidentally leftover on different surfaces, the lifted prints look inferior. Therefore, a tremendous amount of research is being carried out in automatic latent fingerprint identification to improve the overall fingerprint recognition performance. As a result, there is an ever-growing demand to develop reliable and robust systems. In this regard, we present a comprehensive literature review of the existing methods utilized in latent fingerprint acquisition, segmentation, quality assessment, enhancement, feature extraction, and matching steps. Later, we provide insight into different benchmark latent datasets available to perform research in this area. Our study highlights various research challenges and gaps by performing detailed analysis on the existing state-of-the-art segmentation, enhancement, extraction, and matching approaches to strengthen the research.

Keywords

Fingerprint identification system; NIST; Latent fingerprints; Forensics fingerprint database

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𝙍𝙚𝙘𝙚𝙣𝙩 𝘼𝙙𝙫𝙖𝙣𝙘𝙚𝙢𝙚𝙣𝙩 𝙞𝙣 𝙩𝙝𝙚 𝙃𝙚𝙖𝙡𝙩𝙝𝙘𝙖𝙧𝙚 𝘿𝙤𝙢𝙖𝙞𝙣 𝙐𝙨𝙞𝙣𝙜 𝙑𝙖𝙧𝙞𝙤𝙪𝙨 𝙈𝙚𝙩𝙝𝙤𝙙𝙨

DOI: https://doi.org/10.30564/jcsr.v4i1.4471

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