2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)最新文献

Convolutional Neural Networks based Liver Tumor Classification 基于卷积神经网络的肝脏肿瘤分类

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10011017

Keshali Pathak, D. Singh

{"title":"Convolutional Neural Networks based Liver Tumor Classification","authors":"Keshali Pathak, D. Singh","doi":"10.1109/ICAISS55157.2022.10011017","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10011017","url":null,"abstract":"The most common and widespread disease among today's population is liver disease, which is caused by excessive alcohol consumption, polluted gas produced by various chemical factories, drugs, spoiled or tainted food, and obesity. Liver is the most important body organ as it performs the detoxification process. As a result, early disease detection plays a crucial role in the disease diagnosis and recovery process. Early prediction of liver disease has been made possible with the introduction of machine learning technology. This technology provides significant benefits to the healthcare sector by developing new ways to deploy early disease prediction system even in a remote location. SVM, KNN, K-Mean clustering, neural networks, decision trees, and other machine learning techniques are used to implement liver disease diagnosis in order to provide varying levels of accuracy, precision and sensitivity. Unsupervised learning, supervised learning, semi-supervised learning, and reinforcement learning can also be used. This research study intends to compare all the machine learning algorithms to investigate and predict the liver disease and the resultant performance is evaluated based on sensitivity, relevance, accuracy, and precision.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"1 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123137306","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

Artificial Intelligence System based Embedded Real-Time System Power Optimization and Adaptability 基于人工智能的嵌入式实时系统功率优化与自适应

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10011023

Nilamani Ganesan, T. Muthumanickam

引用次数: 0

Intelligent Speed Breaker Using Internet of Things 基于物联网的智能断路器

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010581

S. Ashwin, G. Paulraj, I. Jebadurai, Jebaveerasingh Jebadurai

引用次数: 0

QoS-Enhancement Adaptive OpenFlow Rule Integration in Software Defined WSN for IoT Applications 面向物联网应用的软件定义WSN qos增强自适应OpenFlow规则集成

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10011102

K. P. kumar, P. Sivanesan, P. Sathyaprakash

引用次数: 0

Average Intensity Sign (AIS) Feature based Offline Signature Verification for Forgery Detection using Machine Learning 基于平均强度符号(AIS)特征的离线签名验证:基于机器学习的伪造检测

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010812

R. Sathya, S. Ananthi, R. Rupika, N. Santhiya, K. Lavanya

{"title":"Average Intensity Sign (AIS) Feature based Offline Signature Verification for Forgery Detection using Machine Learning","authors":"R. Sathya, S. Ananthi, R. Rupika, N. Santhiya, K. Lavanya","doi":"10.1109/ICAISS55157.2022.10010812","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010812","url":null,"abstract":"The human offline signs are the utmost extensively approved biometric verification procedures in colleges, industries, banking and various domain due to its easiness and exclusivity. Numerous computerized technologies have been established to predict the human offline signature for forgery detection. Because, the offline biometric identification system has expanded a histrionic movement. This paper Suggests a technique for offline sign identification system using image processing techniques. The proposed offline sign identification system has four stages. In the first stage, the pre-processing of human sig can be done. The pre-processing stage can be done by means of image processing concepts which includes color conversion and next smoothening technique can be done using Gaussian filter. And followed by noise removal method can be done using morphological operation. The second stage of proposed system is sign detection using various edge detection algorithm. In the third stage, extract the Average Intensity Sign (AIS) featurefrom detected sign image. Finally, signature verification system can be utilized for forgery detection using machine learning SVM techniques. The proposed sign identification method demonstrations that the real time experimental output has extreme achievement ratio. This proposed algorithm yields average accuracyof 98.91% in SVM (RBF) in 36 AIS features when associated to an SVM(polynomial) classifier.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"695 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124901893","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: 4

Future Trends and Short-Review on Fish Species Classification Models Based on Deep Learning Approaches 基于深度学习方法的鱼类分类模型的发展趋势及综述

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10011087

M. Bhanumathi, B. Arthi

{"title":"Future Trends and Short-Review on Fish Species Classification Models Based on Deep Learning Approaches","authors":"M. Bhanumathi, B. Arthi","doi":"10.1109/ICAISS55157.2022.10011087","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10011087","url":null,"abstract":"An automatic fish species classification system is highly essential to track, classify and detect marine species and fishes in complex underwater backgrounds without any manual help. Existing computer vision-based approaches didn't offer effective performance rates underwater because the textural features and shape of fish species are not apparent. The data-driven classification approach needsa superior amount of labeled data;otherwise, they leadtooverfitting at the time of data training, and also, the unseen test data are not utilized for training.Ecologists, researchers, taxonomists, and geneticists from different biological fields wished to accept fish as a significant element in their research. Theywere discouraged from finding ichthyology,a highly complex task. In fish-based studies, failing to recognize fishes as distinct biological units can lead to thewrong diagnosis. Hence, this survey paper tries to discuss and clarify the recent research on species identification with their algorithmic categorization. This review explores the performance measures compared, the number of fish families/species recognized, datasets used, and tools utilized for implementation. Further, future research directions and compensation for current research gaps are discussed. This review of state-of-the-art fish identification tools shows their potential for providing the right solution in real-life situations.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"70 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123259762","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 Critical Simulated Analysis of 5G based Aerial Vehicle Routings using NS3 基于NS3的5G无人机路由关键仿真分析

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010870

Hemant Kumar Saini, Gurleen Kaur, Kusum Lata Jain

{"title":"A Critical Simulated Analysis of 5G based Aerial Vehicle Routings using NS3","authors":"Hemant Kumar Saini, Gurleen Kaur, Kusum Lata Jain","doi":"10.1109/ICAISS55157.2022.10010870","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010870","url":null,"abstract":"In this paper a quick survey and similar investigation of the adhoc steering conventions utilized in aerial network will be introduced. The exploration documented in airborne adhoc network (AANET) is growing exceptionally quick. A broad assortment of usages has been served under different circumstances (Roadway, metropolitan, and Urban communities). Numerous conventions have been taken on to serve different geography and situations, these conventions confronted different difficulties. AANETs give correspondence between vehicles continuing on the air. The steering conventions in AANET are impacted by the vehicle fast which prompts oftentimes connect breaks between the conveyed vehicles, so the adhoc directing conventions are adjusted with the AANET attributes to convey the information between vehicles in brief time frame. The fundamental objective of AANET is to collect an information framework among vehicles that are continuing broadcasting in real time, which empowers the vehicles to speak with one another for the security habits. In this paper, an undertaking has been made to think about the aerial vehicles in both 3D and 2D situations which without a doubt comprehended conventions AODV, DSR, OLSR, DSDV utilized in AANET according to the viewpoint of PDR, end to end delay, throughput, signifies the suitability of uavs in 3D and also proven the best routing for flight performance is by AODV. This effects a great deal in helping the 5G correspondence at high elevations with same environmental factors of UAVs to keep up with the organization.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123310405","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

Wireless Sensor & RFID Based Smart Energy Management for Automated Home 基于无线传感器和RFID的自动化家庭智能能源管理

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010710

Senthilkumar Subramanian, M. Bindhu, S. Umathe, Sarveswara Rao, Shanmugavel Deivasigamani, M. Ramarao

{"title":"Wireless Sensor & RFID Based Smart Energy Management for Automated Home","authors":"Senthilkumar Subramanian, M. Bindhu, S. Umathe, Sarveswara Rao, Shanmugavel Deivasigamani, M. Ramarao","doi":"10.1109/ICAISS55157.2022.10010710","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010710","url":null,"abstract":"A common misconception is that people often forget to turn off their electrical appliances. Individuals may also be more concerned about their safety as a result, which increases energy use, electricity costs, and increases energy usage. An electric appliance can be turned off both automatically and manually with this PLC-based smart home automation system. The result is a reduction in energy consumption and an improvement in safety. An integrated PLC system has the advantage of being easy to program and offers a variety of solutions. To turn the electrical equipment on or off manually, the RFID tag is used. The devices are capable of measuring, sensing and positioning using triangulation and time-of-flight. Triangle-based sensors are ideal for measuring close distances with extreme accuracy. A PLC is being used in this research to locate misplaced RFID tags independently. An RFID reader is an electronic device that is used to read tags attached to objects using radio waves (the interrogator and transponder). Generally, RFID readers and tags communicate wirelessly, so line of sight between them is not necessary. There will be benefits from this research if an application utilizes more than two cards. Biometrics and RFID technology are employed in security measures.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126638589","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

Enhancing Lifespan of Battery Storage System in Energy and Regulation Markets through Power Stabilization Using Heuristic Concept 基于启发式概念的电力稳定提高能源调控市场下电池储能系统寿命研究

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010586

Papumoni Saikia, M. Buragohain, Nipan Das

{"title":"Enhancing Lifespan of Battery Storage System in Energy and Regulation Markets through Power Stabilization Using Heuristic Concept","authors":"Papumoni Saikia, M. Buragohain, Nipan Das","doi":"10.1109/ICAISS55157.2022.10010586","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010586","url":null,"abstract":"In the battery storage system, scheduling is required for performing the short-term operation concerning the regulation market with the consideration of longer-term impacts for extending the lifespan of the battery, which is highly challenging to perform and has been focused on in the research works. This can be illustrated through the short-term mechanism that includes the frequent and sharp discharges and charges of the battery, which may effectively, be achieved through short-term operation. But, it makes a significant impact on the lifespan of the battery to get long-running stability. Hence, the scheduling issues need to be rectified by finding the optimum short-term contribution strategy when involved in the regulated markets and day-ahead energy at the time of considering the long-term lifespan problems. Hence, this paper plans to develop a new method for scheduling battery storage systems for participation in frequency regulation and energy markets, simultaneously. A long-term optimization process is proposed, in which the short-term participation strategy defines the battery's lifespan. The proposed long-term model is linearized by the implementation of Benders' decomposition. Here, the limiting factors of energy and regulation markets are optimized by the Squirrel Search Algorithm (SSA) with the consideration of maximizing the battery lifespan. Finally, the applicability of the proposed method is analyzed by comparing it with existing methods.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"250 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116047404","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

Energy Management Strategies for Educational Campus Buildings in a Virtual Power Plant Environment with Demand Response 基于需求响应的虚拟电厂环境下教育校园建筑能源管理策略

2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS) Pub Date : 2022-11-24 DOI: 10.1109/ICAISS55157.2022.10010863

N. Dahlan, Kader Saddiq Kader Ridzwan, S. S. Sivaraju, T. T. Putra

{"title":"Energy Management Strategies for Educational Campus Buildings in a Virtual Power Plant Environment with Demand Response","authors":"N. Dahlan, Kader Saddiq Kader Ridzwan, S. S. Sivaraju, T. T. Putra","doi":"10.1109/ICAISS55157.2022.10010863","DOIUrl":"https://doi.org/10.1109/ICAISS55157.2022.10010863","url":null,"abstract":"The electricity consumption in educational campuses in Malaysia continues to increase as more education buildings are developed to accommodate approximately one million students' placements as highlighted by Malaysia's Ministry of Higher Education (MOHE) in its Education Development Plan 2015–2025. Concurrently, the distributed energy resources mainly solar photovoltaic in Malaysia has increased over the past few years as the nation is moving towards a sustainable energy development. Therefore, an efficient way to pursue these agendas should be developed through integrated approaches to optimise the overall usage of energy in educational campuses. This paper aims to study on the technoeconomic of a microgrid system with grid-connected photovoltaic and battery storage in a Virtual Power Plant (VPP) environment. The VPP operates to manage the energy in an economical way. The energy management strategy is analysed for several buildings in Universiti Teknologi MARA in Shah Alam, Selangor as a case study. In this study, the buildings inside the campus are being connected as a microgrid by performing simulation for three different models (Grid-PV-Diesel Generator, Grid-PV-Battery, Diesel Generator-PV-Battery) using HOMER software. The buildings' load profile, solar irradiation data and other electrical and grid component's parameters are provided to minimise the system's Net Present Cost (NPC). The findings show that the Grid-PV-Diesel generator has the lowest cost. However, considering grid rates hike, the Diesel Generator-PV-Battery show a better result as it is not influenced by any grid rates fluctuations. Therefore, this study would further enhance the public agenda as a public educational institute to support the current changing sustainable energy development.","PeriodicalId":243784,"journal":{"name":"2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122965310","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