Computer Science & Engineering: An International Journal最新文献

Data Mining for Students’ Employability Prediction 通过数据挖掘预测学生的就业能力

Computer Science & Engineering: An International Journal Pub Date : 2024-02-28 DOI: 10.5121/cseij.2024.14101

S.M.M Malika

{"title":"Data Mining for Students’ Employability Prediction","authors":"S.M.M Malika","doi":"10.5121/cseij.2024.14101","DOIUrl":"https://doi.org/10.5121/cseij.2024.14101","url":null,"abstract":"This study has been undertaken to predict the student employability.Assessing student employability provides a method of integrating student abilities and employer business requirements, which is becoming an increasingly important concern for academic institutions. Improving student evaluation techniques for employability can help students to have a better understanding of business organizations and find the right one for them. The data for the training classification models is gathered through a survey in which students are asked to fill out a questionnaire in which they may indicate their abilities and academic achievement. This information may be used to determine their competency in a variety of skill categories, including soft skills, problem-solving skills and technical abilities and so on.The goal of this research is to use data mining to predict student employability by considering different factors such as skills that the students have gained during their diploma level and time duration with respect to the knowledge they have captured when they expect the placement at the end of graduation. Further during this research most specific skills with relevant to each job category also was identified. In this research for the prediction of the student employability different data mining models such as such as KNN, Naive Bayer’s, and Decision Tree were evaluated and out of that best model also was identified for this institute's student’s employability prediction.So, in this research classification and association techniques were used and evaluated.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"20 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140418269","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

Soft Computing: Contents, Techniques and Application 软计算:内容、技术与应用

Computer Science & Engineering: An International Journal Pub Date : 2023-06-27 DOI: 10.5121/cseij.2023.13301

Michael Gr. Voskoglou

引用次数: 0

A Review of Agent-Based Simulation for University Students Admission 基于agent的大学生录取仿真研究综述

Computer Science & Engineering: An International Journal Pub Date : 2023-04-29 DOI: 10.5121/cseij.2023.13202

Suha Khalil Assayed, P. Maheshwari

{"title":"A Review of Agent-Based Simulation for University Students Admission","authors":"Suha Khalil Assayed, P. Maheshwari","doi":"10.5121/cseij.2023.13202","DOIUrl":"https://doi.org/10.5121/cseij.2023.13202","url":null,"abstract":"Multiple factors influence college selection and admission behaviors. Most researchers focused on the academic and socioeconomic factors; the academic factors are high school GPA, SAT, admission tests, etc. On the other hand, the socioeconomic factors could be family income and first-generation students, which means parents did not complete their bachelor's degrees. However, some universities admission policies do not pay any attention to the race or to the minorities even though some of them might be from the lowincome students which could not afford any admission tests, and they might lose their chance to get admitted into their preferred universities. Therefore, most universities want a fairness admission system that include both the disadvantaged students along with other high-score achievement students. Thus, several simulations have been developed by using the agent-based models in order to simulate a real world system by considering other factors and domains that are varied in the complexities. This paper aimed to review several Agent-Based Models that are deployed by different admission offices from several international universities and colleges around the world, which is classified based on the main contribution of the simulations including the level of educational attainment as well as the universities selection behaviors.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114394739","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

Fuzzy Assessment of the “5 E’s” Instructional Treatment for Teaching Mathematics to Engineering Students 工科学生数学教学“5e”教学方式的模糊评价

Computer Science & Engineering: An International Journal Pub Date : 2023-04-29 DOI: 10.5121/cseij.2023.13201

M. Voskoglou

引用次数: 1

A Cybersecurity and Digital Risk Assessment: A Family Case Study 网络安全和数字风险评估:一个家庭案例研究

Computer Science & Engineering: An International Journal Pub Date : 2023-04-29 DOI: 10.5121/cseij.2023.13204

Suha Khalil Assayed

引用次数: 0

A Wireless Device to Modular Robotized Instrument for Health Information 从无线装置到模块化机器人健康信息仪器

Computer Science & Engineering: An International Journal Pub Date : 2023-04-29 DOI: 10.5121/cseij.2023.13203

V. Ivanova, A. Boneva, Stoyan Ivanov, P. Vasilev

{"title":"A Wireless Device to Modular Robotized Instrument for Health Information","authors":"V. Ivanova, A. Boneva, Stoyan Ivanov, P. Vasilev","doi":"10.5121/cseij.2023.13203","DOIUrl":"https://doi.org/10.5121/cseij.2023.13203","url":null,"abstract":"This article is referred to an innovative wireless device for ECG patient monitoring during minimally invasive surgery. Our aim is to create new type of laparoscopy instruments to improve healthcare. The work presents a wireless device for ECG (DECG) as part of a robotic modular laparoscopic instrument (RMLI). Thus, the device allows ECG analysis and monitoring of the patient to be carried out complexly in combination with other diagnostic and therapeutic (RMLI) mode of operation activities. The proposed device provides detection and rapid warning of abnormal heart rate during surgery. Innovative uMAC wireless network stack is designed for module-control block communication. Control computer program processes and monitors (remotely or directly) received information from wireless device that is connected to patient. The software of the device is developed in Tcl/Tk scripting language for operation under Windows. A shared reality upgrade for Android has also been developed for it. The novelty of the solution is related to the construction and connection of the ECG with the used RMLI robotic module. In the future the designed instrument will can work autonomous. The team has worked in the field of minimally invasive and laparoscopic surgery roboticized instrumentation and the presented development is a continuation of this work.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"195 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124343033","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

AGENT-BASED SIMULATION FOR UNIVERSITY STUDENTS ADMISSION: MEDICAL COLLEGES IN JORDAN UNIVERSITIES 基于agent的大学生入学模拟:约旦大学医学院

Computer Science & Engineering: An International Journal Pub Date : 2023-02-27 DOI: 10.5121/cseij.2023.13101

Suha Khalil Assayed, P. Maheshwari

{"title":"AGENT-BASED SIMULATION FOR UNIVERSITY STUDENTS ADMISSION: MEDICAL COLLEGES IN JORDAN UNIVERSITIES","authors":"Suha Khalil Assayed, P. Maheshwari","doi":"10.5121/cseij.2023.13101","DOIUrl":"https://doi.org/10.5121/cseij.2023.13101","url":null,"abstract":"Medical colleges are considered one of the most competitive schools compared to other university departments. Most countries adopted the particular application process to ensure maximum fairness between students. For example, in UK students apply through the UCAS system, and most of USA universities use either Coalition App or Common App, on the other hand, some universities use their own websites. In fact, a Unified Admission Application process is adopted in Jordan for allocating the students to the public universities. However, the universities and colleges in Jordan are evaluating the applicants by using merely the centralized system without considering the socioeconomics factor, as the high school GPA is the essential player their selection mechanism. In this paper, the authors will use an Agent Based model (ABM) to simulate different scenarios by using Netlogo software (v. 6.3). The authors used different parameters such as the family-income and the high school GPA in order to maximize the utilities of the fairness and equalities of universities admission. The model is simulated into different scenarios. For instance, students with low family income and high GPA given them the priority in studying medicine comparing with same high school GPA and higher family-income, as a results, after several rotations of the simulation the reputation of medical schools are identified based on students’ preferences and seats’ allocated as it shows that high ranking universities are mainly allocated with have high cut-off GPA score.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"258 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116201122","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: 1

Attack Detection Availing Feature Discretion using Random Forest Classifier 基于随机森林分类器特征自由裁量的攻击检测

Computer Science & Engineering: An International Journal Pub Date : 2022-12-30 DOI: 10.5121/cseij.2022.12611

Anne Dickson, Ciza Thomas

引用次数: 0

Workflow Scheduling in Cloud Computing Environment by Combining Particle Swarm Optimization and Grey Wolf Optimization 结合粒子群优化和灰狼优化的云计算环境下工作流调度

Computer Science & Engineering: An International Journal Pub Date : 2022-12-30 DOI: 10.5121/cseij.2022.12601

Divya Makhija, P. B. Reddy, Ch. Sudhakar, V. Kumari

{"title":"Workflow Scheduling in Cloud Computing Environment by Combining Particle Swarm Optimization and Grey Wolf Optimization","authors":"Divya Makhija, P. B. Reddy, Ch. Sudhakar, V. Kumari","doi":"10.5121/cseij.2022.12601","DOIUrl":"https://doi.org/10.5121/cseij.2022.12601","url":null,"abstract":"Scheduling workflows is a vital challenge in cloud computing due to its NP-complete nature and if an efficient workflow task scheduling algorithm is not used then it affects the system’s overall performance. Therefore, there is a need for an efficient workflow task scheduling algorithm that can distribute dependent tasks to virtual machines efficiently. In this paper, a hybrid workflow task scheduling algorithm based on a combination of Particle Swarm Optimization and Grey Wolf Optimization (PSO GWO) algorithms, is proposed. PSO GWO overcomes the disadvantages of both PSO and GWO algorithms by improving the exploitation (local search) of PSO algorithm and exploration (global search) of GWO algorithm. This leads to better balance between exploration and exploitation, consequently it minimizes the makespan with 5.52% compared to GWO and 3.68% compared to PSO. The degree of imbalance reduced upto 33.22% compared to GWO and 17.61% compared to PSO, improves the convergence rate as well depending on number tasks and iterations. CloudSim tool is used to evaluate the proposed algorithm. The simulation results confirmed that the proposed method performs better than both of the standard PSO and GWO in terms of makespan, degree of imbalance and convergence rate","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115713049","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

Noise Removal in Traffic Sign Detection Systems 交通标志侦测系统的噪音去除

Computer Science & Engineering: An International Journal Pub Date : 2022-12-30 DOI: 10.5121/cseij.2022.12608

Mohan Kumar G, M. Shriram, Rajeswari Sridhar

{"title":"Noise Removal in Traffic Sign Detection Systems","authors":"Mohan Kumar G, M. Shriram, Rajeswari Sridhar","doi":"10.5121/cseij.2022.12608","DOIUrl":"https://doi.org/10.5121/cseij.2022.12608","url":null,"abstract":"The application of Traffic sign detection and recognition is growing in traffic assistant driving systems and automatic driving systems. It helps drivers and automatic driving systems to detect and recognize the traffic signs effectively. However, it is found that it may be difficult for these systems to work in challenging environments like rain, haze, hue, etc. To help the detection systems to have better performance in challenging conditions like rain and haze, we propose the use of a deep learning technique based on a Convolutional Neural Network to process visual data. The processed data could be used in the detection. We are using the NoiseNet model [11], a noise reduction network for our architecture. The model is trained to enhance images in patches instead of as a whole. The training is done using the Challenging Unreal and Real Environment - Traffic Sign Detection Dataset(CURE-TSD) which contains videos of different roads in various challenging situations. The enhanced images obtained are compared using the object detection algorithms YOLO and Faster RCNN. The Mean Absolute Error(MAE) of original and enhanced images are calculated and compared for two classes of images - rain and haze for both the algorithms. The proposed approach achieved an average Peak Signal to Noise Ration(PSNR) of 25.30 and an Structural Similarity(SSIM) of 0.88. The average MAE values of YOLO and Faster RCNN model reduced by 0.11 and 0.30 respectively on using enhanced images.","PeriodicalId":361871,"journal":{"name":"Computer Science & Engineering: An International Journal","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114524423","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

Computer Science &amp; Engineering: An International Journal最新文献

Computer Science & Engineering: An International Journal最新文献