2022 4th International Conference on Advancements in Computing (ICAC)最新文献_第3页

Investigation of Routing Techniques to Develop a Model for Software-Defined Networks using Border Gateway Protocol 利用边界网关协议开发软件定义网络模型的路由技术研究

2022 4th International Conference on Advancements in Computing (ICAC) Pub Date : 2022-12-09 DOI: 10.1109/ICAC57685.2022.10025097

Banuka Dayapala, Palanisamy Vigneshwaran, S. Suthaharan

{"title":"Investigation of Routing Techniques to Develop a Model for Software-Defined Networks using Border Gateway Protocol","authors":"Banuka Dayapala, Palanisamy Vigneshwaran, S. Suthaharan","doi":"10.1109/ICAC57685.2022.10025097","DOIUrl":"https://doi.org/10.1109/ICAC57685.2022.10025097","url":null,"abstract":"Software-Defined Network (SDN) is a networking opportunity that brings together all control functions in one place and changes traditional network architecture by making centralized decisions. In SDN architecture, controllers perform control decision-making functions when directing packets. Unlike traditional routing protocols, efficient r outing protocols are required for efficient data center infrastructure services. The separation of the network data plane from the network control plane is advocated by SDN in a networking design concept. Traditional networks mix data and control planes on the same device and forcing each device to make its own routing decisions based on distributed routing protocols. In this paper, we develop Microsoft Azure Software Defined-Wide Area Networks (SD-WAN) with the concept of HUB-SPOKE to show how the controller’s centralized decision-making capability changes network architecture with network flexibility and programming capability by taking the SPOKE network. This research also focuses on the key status of controllers used in the network industry. Further, we analyze the performance of SD-WAN routing against conventional routing with respect to routing convergence time and address how much efficient SDN routing rather than the conventional routing in various network topology using real-time SD-WAN on corporate environment of Microsoft Azure Cloud Tenant.","PeriodicalId":292397,"journal":{"name":"2022 4th International Conference on Advancements in Computing (ICAC)","volume":"254 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121171209","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

Classification of Documents and Images Using an Enhanced Genetic Algorithm 基于增强遗传算法的文档和图像分类

2022 4th International Conference on Advancements in Computing (ICAC) Pub Date : 2022-12-09 DOI: 10.1109/ICAC57685.2022.10025121

Nirmani Athuraliya, H.L.S.R.P De Silva, Dulshani Dasanayake, K. Fernando, P. Haddela, Adeepa Gunarathne

{"title":"Classification of Documents and Images Using an Enhanced Genetic Algorithm","authors":"Nirmani Athuraliya, H.L.S.R.P De Silva, Dulshani Dasanayake, K. Fernando, P. Haddela, Adeepa Gunarathne","doi":"10.1109/ICAC57685.2022.10025121","DOIUrl":"https://doi.org/10.1109/ICAC57685.2022.10025121","url":null,"abstract":"In 1975, John Holland proposed the Genetic Algorithm (GA). The algorithm is widely used to provide superior solutions for optimization and search problems by relying on biologically inspired operators including mutation, crossover, and selection. The fittest individuals are chosen for reproduction in this algorithm to generate the next generation’s offspring. Classification is a technique used in data mining to analyze the collected data and to divide them into different classes. The relationship between a known class assignment and the properties of the entity to be classed may serve as the foundation for the classification procedure. Through this research, it has mainly consider classification for documents and images using GA. In order to enhance the accuracy and to reduce the error rate of traditional models, a new approach is proposed which is based on GA. The primary benefit of using GA in conjunction with classification is the efficiency in which it can address optimization issues. The experiment results are used to verify the suggested algorithm using benchmark data sets gathered from the UCI machine learning repository.","PeriodicalId":292397,"journal":{"name":"2022 4th International Conference on Advancements in Computing (ICAC)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126034122","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

Real-time Smart Navigation System for Visually Impaired People 视障人士实时智能导航系统

2022 4th International Conference on Advancements in Computing (ICAC) Pub Date : 2022-12-09 DOI: 10.1109/ICAC57685.2022.10025323

S.R.D. Sudaraka Keshara, W.R.J.M. Weragoda, S. Chandrasiri, Jathusanan Ellankovan, W.A Madushan.

引用次数: 0

Mobile Base Solution for Individuals with Limited Knowledge About Cars 针对汽车知识有限的个人的移动基地解决方案

2022 4th International Conference on Advancements in Computing (ICAC) Pub Date : 2022-12-09 DOI: 10.1109/ICAC57685.2022.10025183

Heshan Nammunige, Tharindu Chamuditha, S. Udara, Devmith Athapaththu, A. Gamage, N. Gamage

{"title":"Mobile Base Solution for Individuals with Limited Knowledge About Cars","authors":"Heshan Nammunige, Tharindu Chamuditha, S. Udara, Devmith Athapaththu, A. Gamage, N. Gamage","doi":"10.1109/ICAC57685.2022.10025183","DOIUrl":"https://doi.org/10.1109/ICAC57685.2022.10025183","url":null,"abstract":"Different modes of transportation were discovered by our ancestors from ancient times. Currently, the majority of people choose to purchase a personal automobile for transport needs. However, the vast majority of people are not automobile industry experts. As a result, the majority of people have trouble when recognizing cars. Due to numerous variations of a single vehicle model, even an expert has trouble correctly identifying a certain car model. People must take into account a number of factors before purchasing a specific automobile. Some of crucial factors are service costs and future market prices. Ordinary people require the assistance of a professional when estimating the market price of a car and calculating the cost of servicing a car. Accidents can also occur at any time when driving a car often. In similar circumstances, consumers require the assistance of an insurance agent or a technician to estimate the cost of damage repair. In this study, we provide a way for non-automotive experts to use their smartphones to identify car models, forecast future market prices, determine and forecast servicing costs, and estimate minor damage repair costs. This paper demonstrates how we accomplished aforementioned tasks using YOLO V4, Multiple Linear Regression, Random Forest Classifier and Faster RCNN.","PeriodicalId":292397,"journal":{"name":"2022 4th International Conference on Advancements in Computing (ICAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130948337","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

“SmartGo” – Intelligent Traffic Controlling System with Violators Detection “SmartGo”-具有违规者检测功能的智能交通控制系统

2022 4th International Conference on Advancements in Computing (ICAC) Pub Date : 2022-12-09 DOI: 10.1109/ICAC57685.2022.10025205

D.M.K.P. Dissanayake, W.B.W.M.R.U.P.U. Aluvihare, K.T. Weerasooriya N, Rajapaksha K.D, G.W.D. Gunarathne A, M.G.N. Pemadasa M

{"title":"“SmartGo” – Intelligent Traffic Controlling System with Violators Detection","authors":"D.M.K.P. Dissanayake, W.B.W.M.R.U.P.U. Aluvihare, K.T. Weerasooriya N, Rajapaksha K.D, G.W.D. Gunarathne A, M.G.N. Pemadasa M","doi":"10.1109/ICAC57685.2022.10025205","DOIUrl":"https://doi.org/10.1109/ICAC57685.2022.10025205","url":null,"abstract":"Road traffic is mostly regulated by Traffic Light Control Systems (TLCS) in Sri Lanka. Conventional traffic signals have many problems, including unproductive time management at road intersections. Drivers and pedestrians would prefer to use the TLCS without any difficulties. The study aims to implement a system on a real-time basis using video monitoring and image processing technology. The system will facilitate vehicles to pass the traffic lights within a minimum waiting time and utilize time according to the number of disabled persons. Emergency vehicles will be released soon by detection using real-time data processing. This system includes the highest vehicle count detection accuracy level, nearly 92%. and the red-light violators’ detection system with an accuracy of 88.6%. SmartGo also detects emergency vehicles and smooths the way of passing through the traffic lights, including a YOLOv5 model with an accuracy of 82.3%. Subsequently, a fine-tuning YOLOv5 is then used to detect vehicles and pedestrians. According to experimental data, the suggested method provides a detection accuracy of 90%. SmartGo is a comprehensive system different from the existing traffic light control system in Sri Lanka which provides flexible and efficient service to both drivers and pedestrians.","PeriodicalId":292397,"journal":{"name":"2022 4th International Conference on Advancements in Computing (ICAC)","volume":"394 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116329849","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

Smart UML - Assignment Management Tool for UML Diagrams 智能UML - UML图的分配管理工具

2022 4th International Conference on Advancements in Computing (ICAC) Pub Date : 2022-12-09 DOI: 10.1109/ICAC57685.2022.10025080

D.N.H Weerasinghe, K.A.T Thiwanka, H.B.C Jayasith, P.A.D Onella Natalie, U. U. Samantha Rajapaksha, A. Karunasena

引用次数: 0

System to Improve the Quality of Water Resources in Sri Lanka Using Machine Learning and Image Processing 利用机器学习和图像处理改善斯里兰卡水资源质量的系统

2022 4th International Conference on Advancements in Computing (ICAC) Pub Date : 2022-12-09 DOI: 10.1109/ICAC57685.2022.10025290

M.H. Samindi Liyanage, G.M.B. Gajanayake S, Oshini Wijewickrama, S.D.S. Fernando A, D. Wijendra, A. I. Gamage

引用次数: 0

Model Development for Child Developmental Milestone Assessment 儿童发展里程碑评估的模型开发

2022 4th International Conference on Advancements in Computing (ICAC) Pub Date : 2022-12-09 DOI: 10.1109/ICAC57685.2022.10025170

M. Mudannayake, Gayara Kumari, Sandun Abeygunawardana, Nethmi Amaranayake, Pradeepa Samarasinghe, Sanka Mohottala, S. Wijethunga

{"title":"Model Development for Child Developmental Milestone Assessment","authors":"M. Mudannayake, Gayara Kumari, Sandun Abeygunawardana, Nethmi Amaranayake, Pradeepa Samarasinghe, Sanka Mohottala, S. Wijethunga","doi":"10.1109/ICAC57685.2022.10025170","DOIUrl":"https://doi.org/10.1109/ICAC57685.2022.10025170","url":null,"abstract":"This paper presents the implementation of models for assessing the developmental milestone of children below age five on physical, cognitive, social, and emotional factors, which is a crucial aspect of human development. To the best of our knowledge, we are the first to design and evaluate models assessing the developmental delays of Sri Lankan children. The primary goal of this study is to analyze the ability of children to reach the relevant milestones in their childhood using video recordings and parents’ feedback. Out of the different models we experimented with, we selected the best models in our final evaluation. As the principal contribution, we developed a model to decide whether the child has typical developmental growth or otherwise using parents’ feedback and obtained 92.31% accuracy. Furthermore, we achieved 92.76% for the social and emotion detection model and 88.44% accuracy for the child action recognition model using video-based datasets. In the future implementation, the derived models will be integrated to build a mobile application.","PeriodicalId":292397,"journal":{"name":"2022 4th International Conference on Advancements in Computing (ICAC)","volume":"31 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132364434","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

Development of Low Resource Machine Learning Models for Child Cognitive Ability Assessments 儿童认知能力评估的低资源机器学习模型开发

2022 4th International Conference on Advancements in Computing (ICAC) Pub Date : 2022-12-09 DOI: 10.1109/ICAC57685.2022.10025049

Adithya Kahawanugoda, Kulanika Gnanarathna, Nilan Meegoda, Randika Monarawila, Pradeepa Samarasinghe, A. Lindamulage

{"title":"Development of Low Resource Machine Learning Models for Child Cognitive Ability Assessments","authors":"Adithya Kahawanugoda, Kulanika Gnanarathna, Nilan Meegoda, Randika Monarawila, Pradeepa Samarasinghe, A. Lindamulage","doi":"10.1109/ICAC57685.2022.10025049","DOIUrl":"https://doi.org/10.1109/ICAC57685.2022.10025049","url":null,"abstract":"Automated cognitive assessment tools are state-of-the-art in assessing cognition development. Due to the low availability of resources, building automated cognitive ability evaluation tools is challenging. This study focuses on developing machine learning models using a limited amount of data to assess Reasoning IQ, Knowledge IQ, Mental Chronometry and Attention-levels of Sinhala-speaking children between the age of 7 to 9 years. Our solution includes Sinhala speech recognition systems, image classification models, gaze estimation, blink count detection and facial expression recognition models to evaluate the above four cognitive ability measuring factors. Open domain speech recognition has been used to evaluate complex Sinhala child verbal responses and limited vocabulary responses were assessed using an end-to-end speech recognition system, respectively achieving 40.1% WER and 97.14% accuracy. Additionally, the image classification models for handwritten Sinhala letter recognition and two shape recognition models have gained 97%, 89% and 99% accuracy. The linear regression model for attention level evaluation that utilizes the inputs from a combination of eye-gaze estimation, facial expression recognition and blink rate detection models has gained 85% accuracy.","PeriodicalId":292397,"journal":{"name":"2022 4th International Conference on Advancements in Computing (ICAC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133971765","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

Solution to Measure Employee Productivity with Employee Emotion Detection 用员工情绪检测来衡量员工生产力的解决方案

2022 4th International Conference on Advancements in Computing (ICAC) Pub Date : 2022-12-09 DOI: 10.1109/ICAC57685.2022.10025132

T.R.S. De Silva, K.Y. Dayananda, R.C. Galagama Arachchi, M.K.S.B. Amerasekara, S. Silva, N. Gamage

{"title":"Solution to Measure Employee Productivity with Employee Emotion Detection","authors":"T.R.S. De Silva, K.Y. Dayananda, R.C. Galagama Arachchi, M.K.S.B. Amerasekara, S. Silva, N. Gamage","doi":"10.1109/ICAC57685.2022.10025132","DOIUrl":"https://doi.org/10.1109/ICAC57685.2022.10025132","url":null,"abstract":"Health and safety of workers has become a top priority in modern businesses. The reason is that it will have an impact on both individual and team output. In the last few decades, automatic facial expression analysis using machine learning has emerged as a promising and bustling field of study. In this study, the system primarily evaluates the efficiency of workers and, through the detection of their emotional states, determines their levels of motivation. The task completion rate of employees is measured by the system in the first component, and the system predicts the level of satisfaction that the employees will have. In place of linear regression, this component makes use of random forest regression, which boasts a higher degree of precision than its counterpart. The performance of workers on their tasks will be evaluated periodically, about once every fifteen minutes, and the results will be shown on a dashboard. The system will pick up on the emotions of the staff members throughout the second phase of the process. These characteristics will be used to assess the level of motivation inside the organization, with the end goal of increasing overall productivity. The accuracy of this emotion detection will also be checked periodically, namely once every fifteen minutes. The following part of the process monitors the use of the PC and calculates the level of productivity. It will be possible to get an increase in productivity if one monitors and keeps track of the application usage of each employee. The final components monitor the websites that employees visit and how they use the network. This component makes it easier to generate reports based on the utilization of the internet and the network, as well as information on performance and reports that summarize website traffic. When it is fully operational as an integrated system, most businesses will rely on this system as their primary driver of success.","PeriodicalId":292397,"journal":{"name":"2022 4th International Conference on Advancements in Computing (ICAC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130301470","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