Journal of Soft Computing Paradigm最新文献

Pathshala: Student Information Management using Cutting-Edge Technology Pathshala:使用尖端技术的学生信息管理

Journal of Soft Computing Paradigm Pub Date : 2023-09-01 DOI: 10.36548/jscp.2023.3.003

Pradip Singh Saud, Apil Chand, Nitesh Kumar Chaurasia, Laxmi Prasad Bastola

{"title":"Pathshala: Student Information Management using Cutting-Edge Technology","authors":"Pradip Singh Saud, Apil Chand, Nitesh Kumar Chaurasia, Laxmi Prasad Bastola","doi":"10.36548/jscp.2023.3.003","DOIUrl":"https://doi.org/10.36548/jscp.2023.3.003","url":null,"abstract":"An Education Information Management System is developed using the Flutter framework integrated with Firebase for data storage and authentication. The system addresses the challenges faced by educational institutions in managing student information, attendance, grades, and communication with parents. Traditional methods of managing school-related tasks are often cumbersome, time-consuming, and error-prone. Thus, there is a need for an efficient and user-friendly solution that can streamline these processes and enhance productivity. The development of the school management system utilizes the Flutter framework, a cross-platform development tool, to create a mobile application as well as web application. Firebase, a comprehensive cloud-based platform, was integrated to handle data storage, authentication, and communication. The system focused on meeting the needs of school administrators, teachers, students, and parents. Key features included student enrollment, attendance tracking, grade management, and notice announcement functionalities. The implementation of this system resulted in significant benefits, such as easier student registration, efficient attendance tracking, streamlined grade management, improved communication, and enhanced engagement among administrators, teachers, students, and parents.","PeriodicalId":127196,"journal":{"name":"Journal of Soft Computing Paradigm","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133254395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An In-Depth Evaluation of Hybrid Approaches in Soft Computing for the Identification of Social Engineering 混合软计算方法在社会工程识别中的深入评价

Journal of Soft Computing Paradigm Pub Date : 2023-09-01 DOI: 10.36548/jscp.2023.3.002

Rahul Kumar Jha

{"title":"An In-Depth Evaluation of Hybrid Approaches in Soft Computing for the Identification of Social Engineering","authors":"Rahul Kumar Jha","doi":"10.36548/jscp.2023.3.002","DOIUrl":"https://doi.org/10.36548/jscp.2023.3.002","url":null,"abstract":"Social engineering attacks continue to pose significant threats to information security by exploiting human psychology and manipulating individuals into divulging sensitive information or performing actions that compromise organizational systems. Traditional defense mechanisms often struggle to detect and mitigate such attacks due to their dynamic and deceptive nature. In response, the integration of hybrid soft computing techniques has developed as a promising method to enhance the accuracy and effectiveness of social engineering detection systems. This study provides an in-depth exploration of the various hybrid soft computing methodologies applied to the detection of social engineering attacks. It discusses the synergistic combination of different soft computing techniques, such as genetic algorithms, neural networks, swarm intelligence and fuzzy logic along with their integration with other security measures. The study presents a comprehensive survey of recent research advancements, methodologies, datasets, performance metrics, and challenges in the domain of hybrid soft computing for social engineering detection. Furthermore, it offers insights into potential future directions and applications for advancing the field.","PeriodicalId":127196,"journal":{"name":"Journal of Soft Computing Paradigm","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128604756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Building Trust in AI -A Simplified Guide to Ensure Software Quality 在人工智能中建立信任——确保软件质量的简化指南

Journal of Soft Computing Paradigm Pub Date : 2023-09-01 DOI: 10.36548/jscp.2023.3.001

Sahithi Devalla, Manas Kumar Yogix

{"title":"Building Trust in AI -A Simplified Guide to Ensure Software Quality","authors":"Sahithi Devalla, Manas Kumar Yogix","doi":"10.36548/jscp.2023.3.001","DOIUrl":"https://doi.org/10.36548/jscp.2023.3.001","url":null,"abstract":"In recent years, Artificial Intelligence (AI) has emerged as an innovative technology in a variety of areas, including software development. The demand for high-quality software has grown in tandem with the increasing complexity of applications and user expectations.AI-driven approaches are revolutionizing traditional software development methodologies by automating and augmenting various stages of the development life cycle, leading to improved efficiency, reduced costs, and enhanced software quality. This research explores the crucial role of AI in developing high-quality software and its impact on the software development process. Firstly, it discusses how AI technologies like machine learning, natural language processing, and deep learning can facilitate requirements gathering, analysis, and validation, leading to better understanding and refinement of user needs. Next, it delves into the significance of AI in automating the coding process, such as generating code snippets, fixing bugs, and optimizing performance, thus accelerating development and reducing human errors. Moreover, the paper highlights the pivotal role of AI in software testing and quality assurance. AI-powered testing tools can execute comprehensive tests more efficiently, detect defects, and predict potential software vulnerabilities, thereby enhancing the overall reliability and robustness of the software product. Additionally, AI techniques can enable real-time monitoring and analytics, allowing developers to identify and address issues promptly during the software's operational phase. Furthermore, the paper addresses the ethical considerations and challenges associated with AI in software development, including bias in training data, interpretability of AI-driven decisions, and potential job displacement for software developers.","PeriodicalId":127196,"journal":{"name":"Journal of Soft Computing Paradigm","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126379351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Comparative Study of Machine Learning-based Approaches for Battery Prognostic Health Analysis using MATLAB 基于机器学习的电池预测健康分析方法的比较研究

Journal of Soft Computing Paradigm Pub Date : 2023-06-01 DOI: 10.36548/jscp.2023.2.002

A. M., Hemkumar G, Karun Rs, Mohammed Siddique M, Vasanthan B

引用次数: 0

Snake Optimization Technique for Spectrum Handoff in Cluster based Cognitive Radio Network 基于聚类认知无线电网络频谱切换的Snake优化技术

Journal of Soft Computing Paradigm Pub Date : 2023-06-01 DOI: 10.36548/jscp.2023.2.004

Judith J, Rahul Raj K, Prawin A, Jothi Venkatajalapathi T G

{"title":"Snake Optimization Technique for Spectrum Handoff in Cluster based Cognitive Radio Network","authors":"Judith J, Rahul Raj K, Prawin A, Jothi Venkatajalapathi T G","doi":"10.36548/jscp.2023.2.004","DOIUrl":"https://doi.org/10.36548/jscp.2023.2.004","url":null,"abstract":"In Cognitive Radio (CR) networks, the use of Secondary Users (SU) in the spectrum has an undesirable effect on spectrum handoff, which causes a handoff delay. The handoff procedure can result in service outages and considerable transmission quality delays, making it a regular source of concern for the SU. An effective spectrum handoff strategy that utilizes the Spectrum Binary Snake Optimization (SBSO) algorithm and the M/G/1 queuing model has been proposed in this study. The use of Cluster Based Cooperative Spectrum Sensing improves SU performance and reduces channel congestion. In order to report the active and inactive channels in the spectrum, the cluster head is connected to the SU base station, and a decision report is subsequently generated by the fusion center. With the use of a bitwise and mutation operator format, SBSO reduces the overall service time required for handoff in the approach that is being proposed. The proposed methodology also provides a framework for observing how primary user activity and spectrum handoff delays behave in the presence of potential interruptions in a CR network. The simulation model of the proposed work optimizes the packet delivery ratio with the three benchmark functions, and provides optimal handoff, and is compared to SBSO and other models that offer a better trade off over delay achievement.","PeriodicalId":127196,"journal":{"name":"Journal of Soft Computing Paradigm","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130919085","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Weeds Classification using Convolutional Neural Network Architectures 基于卷积神经网络架构的杂草分类

Journal of Soft Computing Paradigm Pub Date : 2023-06-01 DOI: 10.36548/jscp.2023.2.003

S. Suriya, H. A

引用次数: 0

Machine Learning Techniques for Intrusion Detection of Fishermen and Trespassing into Foreign Seas 渔民入侵检测与外海入侵的机器学习技术

Journal of Soft Computing Paradigm Pub Date : 2023-06-01 DOI: 10.36548/jscp.2023.2.001

S. S, Anuharshini B, Charanya A G, H. S, Preethika P, S. M

引用次数: 0

Design of a Music Recommendation Device Using Mini-Xception CNN and Facial Recognition 基于Mini-Xception CNN和人脸识别的音乐推荐设备设计

Journal of Soft Computing Paradigm Pub Date : 2023-06-01 DOI: 10.36548/jscp.2023.2.007

C. Singh, V. Himayanth, B. Balakiruthiga

{"title":"Design of a Music Recommendation Device Using Mini-Xception CNN and Facial Recognition","authors":"C. Singh, V. Himayanth, B. Balakiruthiga","doi":"10.36548/jscp.2023.2.007","DOIUrl":"https://doi.org/10.36548/jscp.2023.2.007","url":null,"abstract":"Due to the emerging developments in Artificial Intelligence and Machine Learning Technologies, various prediction systems are been developed based on human emotions and real time aspects of human psychology as well. Facial recognition system is one such mechanism which is the most vibrant strategy used for predicting human emotions. It is extensively applied in surveillance systems, fault identification and other security related aspects. Based on the human emotions researchers have already proposed several music recommendation systems. This paper aims to propose a Facial recognition-based music recommendation system to treat the psychology patients. This helps to recover the patients from mental stress, anxiety, and depression. The suggested method aims to take into account the limitations of the face recognition system in current frameworks, such as the requirement to lower the processing delay for deep feature extraction and the necessity to design a Mini exception technique based on Deep Convolutional Neural Network (DCNN) architecture. The FER- 2013 image dataset, which consists of 35000 face photos with automated labelling is considered. It is used to determine how well the proposed approach would detect the various emotion classes. In comparison to other states of methods, the Mini exception technique utilised in CNN layers acts as a lightweight system. The proposed solution has a 92% accuracy rate and removes the barrier between the current frameworks. The suggested music is taken from a music database and then further mapped in accordance with the algorithm's output.","PeriodicalId":127196,"journal":{"name":"Journal of Soft Computing Paradigm","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122857564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Implementations of Golden Jackal Algorithm for Solving CCFELD Problems 金豺算法求解CCFELD问题的实现

Journal of Soft Computing Paradigm Pub Date : 2023-06-01 DOI: 10.36548/jscp.2023.2.006

R. Ramamoorthi, R. Balamurugan

引用次数: 0

Drowsy Driver Detection with Crash Alert Mechanism using Arduino and Image Processing 基于Arduino和图像处理的困倦驾驶员检测与碰撞警报机制

Journal of Soft Computing Paradigm Pub Date : 2023-06-01 DOI: 10.36548/jscp.2023.2.008

A. Pokhrel, Laxmi Mahara, Monika Upadhyaya, Shikshya Shrestha, Badri Raj Lamichhane

{"title":"Drowsy Driver Detection with Crash Alert Mechanism using Arduino and Image Processing","authors":"A. Pokhrel, Laxmi Mahara, Monika Upadhyaya, Shikshya Shrestha, Badri Raj Lamichhane","doi":"10.36548/jscp.2023.2.008","DOIUrl":"https://doi.org/10.36548/jscp.2023.2.008","url":null,"abstract":"Driver drowsiness is a major cause of automobile accidents, resulting in many fatalities each year. The use of face detection techniques for identifying and warning fatigued drivers can solve this problem and improve transportation safety. This technique detects drowsiness using computer vision technologies based on facial landmarks. Image processing is used by the system to recognize the driver’s face, extract pictures of the eyes, and detect tiredness. The camera monitors the driver’s eyes in real-time, processing visual data to detect symptoms of tiredness. When sleepiness is detected, an alarm sounds to wake and notify the driver. Furthermore, the system is deployed with an Arduino UNO board with GSM, GPS, and MPU 6050 models to detect and alert emergency services in the case of a car accident, as well as to notify the driver’s family. Here the MPU- 6050 sensor detects angular position changes, while the NEO- 6m GPS module identifies the vehicle’s location. The SIM800L GSM module delivers an SMS including the location as well as a warning message. This system could be kept in automobiles to improve driver and passenger safety and security.","PeriodicalId":127196,"journal":{"name":"Journal of Soft Computing Paradigm","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127542991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0