2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)最新文献_第4页

Prediction of Chronic Kidney Disease Using Machine Learning Technique 使用机器学习技术预测慢性肾脏疾病

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058678

Rajeshwari, H. Yogish

{"title":"Prediction of Chronic Kidney Disease Using Machine Learning Technique","authors":"Rajeshwari, H. Yogish","doi":"10.1109/CCIP57447.2022.10058678","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058678","url":null,"abstract":"One of the most crucial problems with artificial intelligence systems is thought to be the identification of correct kidney diseases through machine learning. Manual diagnosis for predicting the kidney disease by doctors is time consuming and may raise the workload on doctors. So, the developed system uses a machine learning technique for predicting the chronic kidney disease which may help the doctors in early prediction of the kidney disease. In order to diagnose chronic kidney disease four Machine Learning technique namely Naïve Bayes, Random Forest, Decision Tree and Support Vector Machine is used. Naive Bayes uses probability to forecast kidney disease, whereas decision trees are used to generate categorized reports for the disease. This system will compare the accuracy score of each Machine Learning technique. Hence, Random Forest gives the better performance compared to other classification methods with accuracy score of 98.75%, $mathbf{F1}=mathbf{score}=boldsymbol{99%},mathbf{ Precision}=boldsymbol{99%},mathbf{Recall} =boldsymbol{99%}$. This paper shows the efficiency and accuracy of the predicted chronic kidney disease.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120989686","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: 3

Acquisition and Identification of Vata, Pitta and Kapha of an individual 获取和识别个人的Vata, Pitta和Kapha

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058666

S. G C, S. T. Veerabhadrappa, Abhishek Gosh

{"title":"Acquisition and Identification of Vata, Pitta and Kapha of an individual","authors":"S. G C, S. T. Veerabhadrappa, Abhishek Gosh","doi":"10.1109/CCIP57447.2022.10058666","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058666","url":null,"abstract":"With the ever-increasing number of diseases in today's world, there is a need for a system to provide early diagnosis and the root cause of human health. Indian and Chinese traditional medicine system provides natural and simple solutions to detecting health issues. Nadi-Nidan is an ancient medical technique, traced back to ancient Indian traditional health monitoring, known to indicate all the health features of a human body. In Nadi Nidan, Wrist pulses or arterial pulses are sensed to diagnose the health status. The study was carried out to design a non-invasive system for wrist pulse analysis that gives us the heartbeat, IBI (Inter-Beat-Interference) and the body type, to support doctors in routine diagnostic procedures and provide detailed procedure for obtaining the complete set of the Nadi signals as a time series. An Ayurveda practitioners and physicians can use this prototype for pulse reading and uniformate in analysis. The proposed model specifically deals with data acquisition of three Nadi signals Vata, Pitta and Kapha. Signals are obtained by using PPG sensors. Arduino is used as the data acquisition hardware. Identification of Prakruthi of the subject was carried out based on the amplitude of Vata, Pitta and Kapha signal acquired at the wrist and achieved 83% accurarcy. Vata, Pitta and Kapha of diabetic and normal subject were analyzed.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114430490","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 Fuzzy Approach for Opinion Summarization of Product Reviews 产品评论意见汇总的模糊方法

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058643

Gunjan Ansari, Seema Shukla, Medhavi Gupta, Himanshi Gupta

引用次数: 0

Analysis of weather monitoring system integrated with renewable energy using IoT technology 利用物联网技术分析与可再生能源集成的天气监测系统

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058667

V. K, G. Shanthi, D. Kesavan, S. S, T. Kokilavani, Gunapriya Devarajan

{"title":"Analysis of weather monitoring system integrated with renewable energy using IoT technology","authors":"V. K, G. Shanthi, D. Kesavan, S. S, T. Kokilavani, Gunapriya Devarajan","doi":"10.1109/CCIP57447.2022.10058667","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058667","url":null,"abstract":"This paper consists of in-depth analysis of IoT based Solar Power and Weather Monitoring System as all know Renewable energy sources are proven to be one of the most reliable and accepted worldwide as source of energy which can fulfill needs of human without any wastage of resource. In this the Solar power is the one of the emerging and cleanest sources of energy which is present in today's modern world, up to this has zero carbon emission. To use this energy, one should know all about it and its application with respect to the subject so that one can harness this solar power generation. The IoT based Solar Power and Weather Monitoring System has been proposed to collect, evaluate and analyze the solar energy parameters along with weather monitoring so that one can predict the performance and ensure accurate use of solar power and its surrounding parameters. The main advantage of the system it helps in monitoring of both solar power and the weather parameters around it. This will lead to optimal performance for better understanding of solar Power. The main target of this IoT based Solar Power and Weather Monitoring System is to offer an understanding on monitoring of solar power and weather parameters, this monitoring will be useful for data analysis of a particular region where this system will be installed.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134146328","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

Water Animosity Detection and Tainting Emulsion Remover for Lakes 湖泊水敌意检测及去污剂

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058658

Sunanda Dixit, Dr. Anjan K Koundinya

引用次数: 0

Visual Cryptography: A Detailed Analysis 视觉密码学:详细分析

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058629

Tanusha Mittal, S. Christa

引用次数: 0

A Comprehensive Study on Geometric, Appearance, and Deep Feature based Methods for Automatic Facial Expression Recognition 基于几何、外观和深度特征的面部表情自动识别方法的综合研究

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058627

Naveen Kumar H N, C. Patil, Amith K. Jain, Sudheesh K V, Mahadevaswamy

{"title":"A Comprehensive Study on Geometric, Appearance, and Deep Feature based Methods for Automatic Facial Expression Recognition","authors":"Naveen Kumar H N, C. Patil, Amith K. Jain, Sudheesh K V, Mahadevaswamy","doi":"10.1109/CCIP57447.2022.10058627","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058627","url":null,"abstract":"Facial Expression (FE) is one kind of communication that, despite its non-verbal nature, predates verbal communication in terms of both its genesis and its conception. Automatic Facial Expression Recognition (AFER) is a predominant facet in analyzing facial images and thus has been an in-demand research problem for decades in the emerging field of Computer Vision (CV) & Artificial Intelligence (AI). Recent works on AFER systems focused on the following issues: insufficient training data which causes overfitting; robustness to identity bias, illumination & head pose variation, partial occlusion; generalization power; transformation from controlled to uncontrolled environments; cross dataset experiments. A comprehensive study on existing methods for the design and development of AFER systems is presented in the proposed study. The benchmark datasets and its characteristics are summarized. The advantages and limitations of the existing methods to extract the highly discriminative and abstract distributions are discussed. The evaluation methods to assess the performance of AFER systems, along with comparative analysis of various methods implemented on benchmark datasets are summarized. Furthermore, unresolved challenging issues in the field of AFER are presented in detail, which serves as an open-ended research area concerning the AFER problem.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132498314","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

Pest Detection and Recognition: An approach using Deep Learning Techniques 害虫检测和识别:一种使用深度学习技术的方法

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058692

N. C. Kundur, P. Mallikarjuna

引用次数: 0

Detection of Chronic Lung Disorders using Deep Learning 使用深度学习检测慢性肺部疾病

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058633

Anupama H.S, Pradeep K.R., Shreeya G, Pratiksha Rao, Tejasvi S.K

{"title":"Detection of Chronic Lung Disorders using Deep Learning","authors":"Anupama H.S, Pradeep K.R., Shreeya G, Pratiksha Rao, Tejasvi S.K","doi":"10.1109/CCIP57447.2022.10058633","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058633","url":null,"abstract":"Lung disorders can be fatal if not treated in the right manner. Symptoms of respiratory disorders include wheezing, breathlessness or difficulty in breathing, cough, hoarseness, and chest pain to name a few. Although the symptoms look common, lung disorders often go undetected due to various reasons such as misdiagnosis, expensive diagnostic techniques, lack of awareness and negligence. In most cases, the patient is required to take a pulmonary function test which includes thoracoscopy, chest imaging (X-rays), electrocardiography and bronchoscopy. In this paper we explore an alternative technique for detecting respiratory disorders through analysis of lung sounds. Lung sounds are vital factors of respiratory health and disorders. They are produced due to the movement of air and secretions in lung tissue or they might also be generated due to the presence of any infection or anomalies. Asthma or Chronic Obstructive Pulmonary Disease (COPD) patients often wheeze as a result of an obstructive airway disease. These sounds can be captured using digital stethoscopes which can then be converted into audio signals for further processing. This audio data gives us the opportunity to diagnose respiratory disorders like pneumonia, asthma and bronchiolitis using deep learning techniques such as convolutional neural networks. We also propose a design for the digital stethoscope which can help record lung audio samples.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124408658","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 Comprehensive Study on Routing Protocol for IoT-enabled WSNs using Deep Reinforcement Learning Strategy 基于深度强化学习策略的物联网wsn路由协议综合研究

2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2022-12-23 DOI: 10.1109/CCIP57447.2022.10058657

S. Regilan, L. Hema

{"title":"A Comprehensive Study on Routing Protocol for IoT-enabled WSNs using Deep Reinforcement Learning Strategy","authors":"S. Regilan, L. Hema","doi":"10.1109/CCIP57447.2022.10058657","DOIUrl":"https://doi.org/10.1109/CCIP57447.2022.10058657","url":null,"abstract":"Internet of Things enabled Wireless Sensor Networks (IoT-enabled WSNs) rely heavily on routing protocols because of the importance of various system performance parameters, such as end-to-end delay, system capacity, data delivery rate, and energy efficiency. As a result of this, sensor nodes may have a detrimental effect on the routing protocol's reliability and power tolerance when compared to other nodes in the network. As a result, the IoT-enabled WSNs' wide-field applications necessitate a self-driven energy intelligent routing protocol. Reinforcement Learning (RL) strategy has recently been used to support the development of an intelligent routing protocol that has a high potential for energy conservation while also increasing system performance above the typically achieved target. Deep Reinforcement Learning (DRL) routing protocols for IoT-enabled WSNs have been studied in this paper, and the current state-of-the-art algorithms have been compared. It is the purpose of this study to evaluate the operational characteristics and key features of the current DRL algorithms. In addition, the practical difficulties of routing protocol design and implementation were discussed.","PeriodicalId":309964,"journal":{"name":"2022 Fourth International Conference on Cognitive Computing and Information Processing (CCIP)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125025380","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