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• Open Access   Article

  Impact of mBlock Interface Design on Student Interest and Motivation in Primary School Robotics: A Case Study in Indonesia

  Wisnu Priambodo, Kristiawan Nugroho, Kristophorus Hadiono

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.4 , pp.1-7, Aug-2023

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  Incorporating STEAM (Science, Technology, Engineering, Arts, and Math) into primary school education has given rise to integrating the mBlock app into robotics learning. The mBlock app is a platform to teach students basic robotics concepts and skills, encouraging intellectual development and problem-solving abilities. In particular, the design of the mBlock user interface plays a crucial role in the effectiveness of robotics education at the primary school level. A well-crafted user interface should have an intuitive and easy-to-understand layout, facilitating students` understanding of the software and allowing them to learn programming their robots. This study examines the impact of user interface design on students` interest and motivation in primary school robotics education. The findings showed a positive correlation between user interface quality and students` interest and motivation to learn robotics. The coefficient Interest value is 1.23 and intercept -3.93, while the Coefficient Motivation value is 1.03 and intercept -0.82. Meanwhile, UI design impacts student interest and motivation using a Correlation Matrix, the correlation coefficient value of enjoyable UI on Interest is 0.83 and on Motivation is 0.71. Visual appeal and clear instructions are most important.

  Key-Words / Index Term
  User Interface, Interest and Motivation, Robotics

  References
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  Citation
  Wisnu Priambodo, Kristiawan Nugroho, Kristophorus Hadiono, "Impact of mBlock Interface Design on Student Interest and Motivation in Primary School Robotics: A Case Study in Indonesia," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.4, pp.1-7, 2023

• Open Access   Article

  Transition to Value-Based Care IoT Wearable Devices in Maternity Healthcare for Low-Resource Countries

  Florence O. Elei, Charles O. Ikerionwu, Azubuike I. Erike, Yusuf U. Mshelia

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.4 , pp.8-14, Aug-2023

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  Wearable devices are used in maternity to foster remote medication and monitoring. Monitoring the mother and child`s well-being has its application with IoT devices. Without a doubt, proper pregnancy to childbirth monitoring utilizing wearable sensors contributes significantly to improving health, and decreasing mortality among mothers and children respectively. The research aims to explore how the implementation of IoT wearable devices in maternity healthcare can facilitate the transition to a value-based care model in low-resource countries. A quantitative approach to information gathering through the use of questionnaires was used to elicit information from participants. The target population was limited to women registered for antenatal visits with some hospitals located in the Owerri municipal area of Imo State in Nigeria. Results obtained through the survey sample show 60% of the women exhibit non-compliance to medical antenatal visit. 40% of the women were recorded to be aware of the use of wearables, with the rest ignorant of the use of ubiquitous wearable devices. However, 85 % of the women were found to be involved in economic activity that might not give them time for routine check. Also, it was found that women experience barriers in switching to Value-Based Care in the study area. The study therefore recommends that government subsidy and proper sensitization for pregnant mothers will enhance the acceptability and use of this technology to monitor health of women during pregnancy to ensure adherence to medication and prompt notification to visit the healthcare center whenever the need arises.

  Key-Words / Index Term
  Wearable Devices, IoT (Internet of Things), Maternity Healthcare, Low-Resource Countries, Remote Health Monitoring, Value-Based Care, Health Literacy

  References
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  Citation
  Florence O. Elei, Charles O. Ikerionwu, Azubuike I. Erike, Yusuf U. Mshelia, "Transition to Value-Based Care IoT Wearable Devices in Maternity Healthcare for Low-Resource Countries," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.4, pp.8-14, 2023

• Open Access   Article

  Dynamic User-Dependent Technique for Robust Multi-Password Generation Against Offline Cracking Attacks

  Azubuike I. Erike, Augustine C. Azubogu, Kenneth A. Akpado, Chukwudi O. Arinze, Yusuf U. Mshelia

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.4 , pp.15-23, Aug-2023

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  Abstract
  This research presented a user-dependent robust multi-password generation technique for authentication. Dynamic chaffing-with-tough-nuts technique was used to dynamically generate real-user triplicate passwords and multiple honey passwords. These combinations stored in a single password relation leaves authentication to a correct combination of the real user triplicate password. A character transformation function used for the implementation leaves a 47% increase in the character length of the already supplied user-password with mandatory inclusion of an array of symbols in the given password, thereby creating a high entropy password. The strength of the generated password analysed against the Hive Systems` report shows that passwords generated through the techniques even with weak hashing algorithm like MD5 would take approximately 7trillion years to crack, thus becomes near impossible to crack using rainbow table attack. Upon successful password cracking, it would take a correct combination of the triplicate model for access to be granted.

  Key-Words / Index Term
  Cybercrime, Cracking attacks, Time-to-crack, Cyber-Protection, Security

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  Citation
  Azubuike I. Erike, Augustine C. Azubogu, Kenneth A. Akpado, Chukwudi O. Arinze, Yusuf U. Mshelia, "Dynamic User-Dependent Technique for Robust Multi-Password Generation Against Offline Cracking Attacks," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.4, pp.15-23, 2023

• Open Access   Article

  Exploring the Impact of User Interface Design on User Experience in Unity VR Games

  Bundit Anuyahong, Wipanee Pengnate

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.4 , pp.24-30, Aug-2023

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  Abstract
  This study sought to investigate the relationship between user interface (UI) design and user experience (UX) in Unity VR games and identify effective UI design strategies to enhance UX and engagement. The research conducted a literature review to identify established design strategies and best practices in UI design and UX in VR games. An experimental design was then developed to measure the impact of different UI design strategies on UX, which involved selecting appropriate VR games, identifying specific design elements to test, and developing user testing protocols. The data was collected through user testing sessions and analyzed through statistical analysis and data visualization techniques. The findings of this study demonstrate that effective UI design has a strong correlation with a positive UX in VR games. The study found that clear and intuitive navigation, consistent color schemes, and appropriate use of 3D space are crucial for enhancing UX in VR games. The research also identifies effective UI design strategies, such as incorporating haptic feedback and sound effects, to enhance the immersive quality of VR interfaces and using minimalistic UI designs that prioritize functionality over visual embellishments. Moreover, specific design strategies, such as in-game tutorials or a seamless inventory system, can lead to increased player engagement and retention. This study provides valuable insights into the relationship between UI design and UX in VR games and offers actionable recommendations for game developers to create engaging, immersive, and cost-effective VR experiences. The findings of this study have implications not only for gaming but also for other applications such as education, healthcare, and training. Therefore, effective UI design is a critical factor in enhancing the user experience and engagement in VR games, and this study emphasizes the importance of implementing best practices in UI design for optimal results. Overall, this study highlights the significance of the relationship between UI design and UX in VR games and provides valuable insights for designing effective VR experiences.

  Key-Words / Index Term
  User Interface Design, User Experience, Unity VR Games

  References
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  [18]. H. J. Kim, M. J. Kim, and F. A. Biocca, "The impact of stereoscopic 3D displays and user self-efficacy on presence and perceived usability in mobile 3D games," Journal of Broadcasting & Electronic Media, Vol.63, Issue.3, pp.435-453, 2019.
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  Citation
  Bundit Anuyahong, Wipanee Pengnate, "Exploring the Impact of User Interface Design on User Experience in Unity VR Games," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.4, pp.24-30, 2023

• Open Access   Article

  Diabetes Mellitus Detection Using Information Gain and Machine Learning Algorithms

  Olayinka Ayodele Jongbo, Idris-Tajudeen Rashidat, Mary Aina Ogbonna, Adebayo Olusola Adetunmbi

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.4 , pp.31-37, Aug-2023

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  Abstract
  Diabetes is a dreadful disease triggered as a result of hyperglycemia. An early detection of this ailment using efficient and intelligent diagnostic tools is very essential to save patients life so as to prevent untimely death and further complications of cardiovascular related issues in the body. Data mining techniques are getting prominence in medical domains in making predictions of chronic health conditions which has the potentials to efficiently diagnose diabetes mellitus disease. The study aims to develop an intelligent diagnostic tool for early prediction of diabetes disease. Data mining algorithms such as k-nearest Neighbor (KNN), Naïve Bayes and Logistic regression were employed in making prognostications. Attribute selection was performed on information gain attribute evaluator based on the data obtained from Pima Indian dataset to determine the best subset of attributes for disease classifications. Experimental result attained from the study using selected features revealed that KNN and Naïve Bayes achieved accuracy of 75.2% and 80.9% respectively while Logistic regression attained the utmost prediction accuracy of 82.2% capable of predicting diabetes mellitus disease efficiently. The model is suitable in medical domains for early prognosis of diabetes disease to assist medical personnel in making intelligent decisions.

  Key-Words / Index Term
  Diabetes, Data mining, Feature selection, K Nearest Neighbor, Naïve Bayes, Logistic Regression

  References
  [1]. Benhalima, Katrien, Paul Van Crombrugge, Carolien Moyson, Johan Verhaeghe, Sofie Vandeginste, Hilde Verlaenen, Chris Vercammen et al. "The sensitivity and specificity of the glucose challenge test in a universal two-step screening strategy for gestational diabetes mellitus using the 2013 World Health Organization criteria." Diabetes care. Vol.41, Issue.7, pp.e111-e112, 2018.
  [2]. Durairaj, Manoj, and Veera Ranjani. "Data mining applications in healthcare sector: a study." International journal of scientific & technology research , Vol.2, Issue.10, pp.29-35, 2013.
  [3]. Jongbo, Olayinka Ayodele, Adebayo Olusola Adetunmbi, Roseline Bosede Ogunrinde, and Bukola Badeji-Ajisafe. "Development of an ensemble approach to chronic kidney disease diagnosis." Scientific African 8, e00456, 2020.
  [4]. Li, Yukai, Huling Li, and Hua Yao. "Analysis and study of diabetes follow-up data using a data-mining-based approach in new urban area of Urumqi, Xinjiang, China, 2016-2017." Computational and mathematical methods in medicine, 2018.
  [5]. Mirza, Shuja, Sonu Mittal, and Majid Zaman. "A review of data mining literature." International Journal of Computer Science and Information Security (IJCSIS) Vol.14, Issue.11, pp.437-442, 2016.
  [6]. Chang, Victor, Jozeene Bailey, Qianwen Ariel Xu, and Zhili Sun. "Pima Indians diabetes mellitus classification based on machine learning (ML) algorithms." Neural Computing and Applications, Vol.35, Issue.22, pp.16157-16173, 2023.
  [7]. Iyer, Aiswarya, S. Jeyalatha, and Ronak Sumbaly. "Diagnosis of diabetes using classification mining techniques." arXiv preprint arXiv, pp.1502.03774, 2015.
  [8]. Priyadarshini, Rojalina, Nilamadhab Dash, and Rachita Mishra. "A novel approach to predict diabetes mellitus using modified extreme learning machine." In 2014 International Conference on Electronics and Communication Systems (ICECS), IEEE, pp.1-5, 2014.
  [9]. Kaur, Paramjot, and Ramanpreet Kaur. "Comparative analysis of classification techniques for diagnosis of diabetes." In Advances in Bioinformatics, Multimedia, and Electronics Circuits and Signals: Proceedings of GUCON 2019, Springer Singapore, pp.215-221, 2020.
  [10]. Orabi, Karim M., Yasser M. Kamal, and Thanaa M. Rabah. "Early predictive system for diabetes mellitus disease." In Advances in Data Mining. Applications and Theoretical Aspects: 16th Industrial Conference, ICDM 2016, New York, NY, USA, July 13-17, 2016. Proceedings 16, pp.420-427, 2016. Springer International Publishing.
  [11]. Apoorva, S., K. Aditya S, P. Snigdha, P. Darshini, and H. A. Sanjay. "Prediction of diabetes mellitus type-2 using machine learning." In Computational Vision and Bio-Inspired Computing: ICCVBIC, Springer International Publishing 9, pp.364-370, 2020.
  [12]. Kishore, G. Naveen, V. Rajesh, A. Vamsi Akki Reddy, K. Sumedh, and T. Rajesh Sai Reddy. "Prediction of diabetes using machine learning classification algorithms." International Journal of Scientific & Technology Research, Vol.9, Issue.1, pp.2277-8616, 2020.
  [13]. Pratiwi, Asriyanti Indah, and Adiwijaya. "On the feature selection and classification based on information gain for document sentiment analysis." Applied Computational Intelligence and Soft Computing, pp.1-5, 2018.
  [14]. Kaviani, Pouria, and Sunita Dhotre. "Short survey on naive bayes algorithm." International Journal of Advance Engineering and Research Development Vol.4, Issue.11, pp.607-611, 2017.
  [15]. Gazalba, Ikbal, and Nurul Gayatri Indah Reza. "Comparative analysis of k-nearest neighbor and modified k-nearest neighbor algorithm for data classification." In 2017 2nd international conferences on information technology, information systems and electrical engineering (ICITISEE), IEEE, pp.294-298, 2017.

  Citation
  Olayinka Ayodele Jongbo, Idris-Tajudeen Rashidat, Mary Aina Ogbonna, Adebayo Olusola Adetunmbi, "Diabetes Mellitus Detection Using Information Gain and Machine Learning Algorithms," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.4, pp.31-37, 2023

• Open Access   Article

  Load Balancing Techniques and comparison of Load scheduling Agorithms in Cloud Computing Infrastructure

  Prabhat Bisht

  Review Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.4 , pp.38-44, Aug-2023

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  Abstract
  Cloud computing is one of the latest and fastest growing technologies in the field of computation, computation strength of cloud based virtual machines is rapidly increasing because of smart resource provisioning feature. Because of this dynamic resource provisioning smart feature, virtual machines resources can be provisioned dynamically from the pool of available resources which become one of the biggest milestones for the success of mission critical web applications in cloud computing infrastructure. In brief, mission critical web application can be defined as an application whose downtime cannot be affordable at any time. Incoming traffic on such applications cannot be predictable. Applications like Facebook, Google, YouTube or Amazon are few example of mission critical web application and these applications are highly scalable in terms of availability. Success of mission critical web applications totally depends upon the efficient load balancer or load balancing techniques or load balancing algorithms, these algorithms distribute HTTP/HTTPS traffic or load in between different nodes of server cluster in the best optimized way. Implementation of efficient load balancer for load sharing among the server cluster nodes in an optimized way is still a great challenge. This paper describes cloud computing technology in brief and highlights positive and negative aspects of load balancing techniques and also describes different load balancing algorithms with comparison chart based on load balancing metrics.

  Key-Words / Index Term
  Virtual Machine (VM) Load balancing, load balancing techniques, cloud computing, fault tolerance design patterns (FTDP)

  References
  [1]. S Afzal, G Kavitha, “Load balancing in cloud computing A hierarchical taxonomical classification,” Journal of Cloud Computing, Vol.8, Issue.1, pp.386-398, 2019.
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  [4]. Hyame Almandine, Sara Ayoubi, “An Efficient Survivable Design with Bandwidth Guarantees for Multi-Tenant Cloud Networks,” IEEE Transaction on network and service management, Vol.14, Issue.2, pp.357-372, 2017.
  [5]. Jula, Amin, Elankovan Sundarajan and Zalinda Othman, “Cloud Computing Service Composition: A systematic review,” Journal of information systems and communications, Vol.3, Issue.1, pp.87-91, 2012.
  [6]. Talwana Jonathan Charity, Gu Chun Hua ,”Resource Reliability using Fault Tolerance in Cloud Computing,” In the proceedings of the 2016 International Conference on Next Generation Computing Technologies-IEEE , India , 2016.
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  [9]. Foram F Kherani, Prof Jignesh Vania, “Load Balancing in cloud computes,” The International journal of Engineering development and research , Vol.2, Issue.1, pp.907-912, 2014.
  [10]. Kaur, A., Luthra, M. P, “ A Review on Load Balancing In Cloud Environment,” International journal of computers and technology, Vol.17, issue.1, pp.7120–7125 ,2018
  [11]. R Mishra, Sambit Kumar, Bibhudatta Sahoo, and Priti Paramita Parida, "Load balancing in cloud computing: a big picture," Journal of King Saud University-Computer and Information Sciences , Vol.32 , Issue.2 , pp.149-158, 2020.
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  Citation
  Prabhat Bisht, "Load Balancing Techniques and comparison of Load scheduling Agorithms in Cloud Computing Infrastructure," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.4, pp.38-44, 2023

• Open Access   Article

  Improving the Markov Chain Approach for Generating Text Used for Ideation Tasks

  Isaac Terngu Adom

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.4 , pp.45-50, Aug-2023

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  Abstract
  The increased demand for text-related solutions from generation, learning, classification, and several other tasks has motivated the use of different techniques and tools of Artificial intelligence. Creative text ideas have been sought after for innovation, problem solving, and improvements, and coming up with them can be a daunting task. In this work, an idea generation system based on improvements to the Markov chain approach using a corpus of text is presented. First, a web system was created to collect solutions from people on a case study problem. They were required to make submissions based on purpose and mechanism, with examples to guide them. Next, the solution text from 200 participants was clustered based on similarity measures into groups, and abstractive summaries of the respective groups were computed. The Markov chain model was then used for the generation of new text from the submitted text corpus, and the most similar Markov chain-generated text was compared with each clustered group’s abstractive summary using a similarity measure and returned as an idea result. Finally, a pipeline to execute all the components of the system at once was developed. The result was sent for human evaluation based on the metrics of quality, novelty, and variety and compared with output from a Generative Pretrained Transformer system using the same text corpus, and this work’s system performed better.

  Key-Words / Index Term
  Computational Creativity, Ideation, Markov Chain, Text Generation, Artificial Intelligence, Innovation, Crowd Sourcing

  References
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  Citation
  Isaac Terngu Adom, "Improving the Markov Chain Approach for Generating Text Used for Ideation Tasks," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.4, pp.45-50, 2023

• Open Access   Article

  Stylized Art Generator – An CNN Based Effective Tool for Gaming

  Dhiviya Rose J, Shubham Sundriyal, Harshwardhan Kumar Bhagat, Harshvardhan Sharma

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.4 , pp.51-57, Aug-2023

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  Abstract
  Stylization refers to the process of simplifying or exaggerating the visual appearance of an object or a scene in a particular style, such as cartoonish, sketchy, or cubism. A neural network is a method in artificial intelligence that teaches computers to process data in a way that is inspired by the human brain. Convolutional Neural Networks (CNNs) are a type of deep neural network that is commonly used in computer vision tasks, such as image recognition and classification. Style representation refers to the visual patterns, textures, and color palettes that make up the artistic style of an image. The ”Stylized Art Generator” project is an AI-based system that uses deep learning techniques to generate stylized art from input images. The system is designed to provide users with an easy-to-use interface to generate art that is unique and visually appealing. The system has the potential to be used in various applications such as creating customized artwork for advertising, graphic design, or even as a tool for artists to explore new styles and forms of expression. Overall, the ”Stylized Art Generator” project aims to demonstrate the power of AI and its potential in the field of art and design.

  Key-Words / Index Term
  Stylist Art, Deep Learning 2, Image Tranformation3, CNN

  References
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  Citation
  Dhiviya Rose J, Shubham Sundriyal, Harshwardhan Kumar Bhagat, Harshvardhan Sharma, "Stylized Art Generator – An CNN Based Effective Tool for Gaming," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.4, pp.51-57, 2023

• Open Access   Article

  An Investigation of Non-Cooperative Spectrum Sensing Techniques Used In CR-VANET

  Md. Asif Hossain, Md. Ashifur Rahman, Baker Hosen, Mohammad Toriqul Islam, Md. Nasim Miah, Md. Sadikur Rahman

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.4 , pp.58-66, Aug-2023

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  Abstract
  Cognitive radio vehicular networks (CR-VANETs) have gained significant attention as a means to improve spectrum utilization and communication efficiency in vehicular environments. A critical duty in CR-VANETs is spectrum sensing, which enables secondary users (SUs) to utilize underused frequency bands without interfering with prime users (PUs). Non-cooperative spectrum sensing techniques have emerged as an alternative to cooperative approaches due to practical challenges in achieving cooperation among vehicles. In this investigation, we review and categorize existing non-cooperative spectrum sensing techniques in CR-VANETs, including individual sensing, decision fusion, and game-theoretic methods. We analyze the advantages, limitations, and trade-offs of each approach, and investigate the impact of factors such as fading, interference, and mobility. Match filter detection, energy detection, and cyclo-stationary feature detection, the three widely used sensing techniques, have all been contrasted.

  Key-Words / Index Term
  Vehicular Network, Cognitive Radio, Spectrum Sensing, Energy Detection, Matched Filter detection, Cyclo-stationary Detection

  References
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  Citation
  Md. Asif Hossain, Md. Ashifur Rahman, Baker Hosen, Mohammad Toriqul Islam, Md. Nasim Miah, Md. Sadikur Rahman, "An Investigation of Non-Cooperative Spectrum Sensing Techniques Used In CR-VANET," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.4, pp.58-66, 2023

• Open Access   Article

  Optimization of the Guidance Process for New Bachelors for the Choice Of Training in Higher Education in Cameroon Using ICT

  ABESSOLO ALO’O Ghislain, OLLE OLLE Daniel Georges, SOKOUDJOU TATSINKE Loveline

  Research Paper | Journal-Paper (IJSRCSE)

  Vol.11 , Issue.4 , pp.67-74, Aug-2023

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  Abstract
  Entering higher education in Cameroon is an important moment for young people who have completed their secondary education. It is a time when they lay the foundations for their future careers. They are called upon to make a decision: to choose a course of study. This decision is very important and can be influenced by a number of formal and informal factors. The academic guidance services responsible for helping these young people make their choices are facing enormous difficulties, including a quantitative and qualitative shortage of staff. This situation has a number of consequences, including wasted education, unresolved choices and mismatches between education and employment. The problem identified here is known in the literature as a decision support problem. Two categories of approaches are proposed to solve this type of problem, namely multi-criteria decision support algorithms and solutions based on machine learning and recommendation systems. This second category of methods puts much more emphasis on the profile, which refers to the academic background of the actor, and seems to neglect the actor`s preferences, which are very important in the selection process. Consequently, taking into account the actor`s preferences in the selection process remains an open problem in the scientific community. In this paper, we propose an optimized school selection process based on ICT. The process integrates an actor`s profile and preferences to better refine his choice. The proposed process has made it possible to develop a prototype that guides a new bachelor to the best higher education in Cameroon.

  Key-Words / Index Term
  QoS, Business Process Optimization, Business Process Modeling, School Guidance

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  Citation
  ABESSOLO ALO’O Ghislain, OLLE OLLE Daniel Georges, SOKOUDJOU TATSINKE Loveline, "Optimization of the Guidance Process for New Bachelors for the Choice Of Training in Higher Education in Cameroon Using ICT," International Journal of Scientific Research in Computer Science and Engineering, Vol.11, Issue.4, pp.67-74, 2023