Proceeding International Conference on Science and Engineering最新文献_第5页

IoT Based Solar E-Uniform for Soldiers 基于物联网的士兵太阳能电子制服

Proceeding International Conference on Science and Engineering Pub Date : 2023-02-18 DOI: 10.52783/cienceng.v11i1.321

Shaik Mohammad Rasool et al.

{"title":"IoT Based Solar E-Uniform for Soldiers","authors":"Shaik Mohammad Rasool et al.","doi":"10.52783/cienceng.v11i1.321","DOIUrl":"https://doi.org/10.52783/cienceng.v11i1.321","url":null,"abstract":"The soldiers working in harsh weather conditions are better protected by solar-powered E-Uniforms. The E-internal uniform's electronics is powered by solar panels. 12 V DC lead acid battery, Energy is stored using a rechargeable battery. Additionally, we use a typical battery charging machine to deliver power to the circuits. The ESP32 microcontroller, which manages every function, is the brains of the circuit. In order to display the voltage generated by the battery on a 16X2 LCD, a voltage sampler is interfaced with the system using an ADC inbuilt in the ESP32.Both a summer and a winter operating mode is used for the project. Control operations through advance ICs so that it can drive the body heater/cooler by choosing the mode of operation. To enable the soldier adapt to any type of external climate, we will use the heater or cooler to deliver a warming or cooling effect within the uniform.The metal sensor will alert the soldier with a buzzer indication if it finds a metal-like explosive. The microcontroller and IOT are interfaced, and the GPS is also interfaced, allowing for the tracking of the entire soldier. Additionally, the location is messaged to the department or person of interest. The soldier will be able to work in any area thanks to this uniform.","PeriodicalId":214525,"journal":{"name":"Proceeding International Conference on Science and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128985484","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

Dangerous Driving Detection Based on IoT 基于物联网的危险驾驶检测

Proceeding International Conference on Science and Engineering Pub Date : 2023-02-18 DOI: 10.52783/cienceng.v11i1.297

Nagendran, Sugan Raj, Mohamed Anaz

引用次数: 0

The Mean Duration of COVID-19 Found Closely Associated with the Ayurvedic Pathognomic Model Shatkriyakala (SKK): Inference of an Observational Cross-Sectional Exploratory Study 新冠肺炎的平均持续时间与阿育吠陀病理学模型Shatkriyakala (SKK)密切相关:一项观察性横断面探索性研究的推断

Proceeding International Conference on Science and Engineering Pub Date : 2023-02-18 DOI: 10.52783/cienceng.v11i1.248

Charu Sharma et al.

{"title":"The Mean Duration of COVID-19 Found Closely Associated with the Ayurvedic Pathognomic Model Shatkriyakala (SKK): Inference of an Observational Cross-Sectional Exploratory Study","authors":"Charu Sharma et al.","doi":"10.52783/cienceng.v11i1.248","DOIUrl":"https://doi.org/10.52783/cienceng.v11i1.248","url":null,"abstract":"A valid measurement for Corona virus disease is needed for case definition and adopting appropriate therapeutic measures. Identification of epidemiology and etio-pathogenesis is must for case definitions. The incubation period The incubation period is the time elapsed between pathogen exposure and appearance of symptoms. It can be utilized to trace the contact history of population at high risk. Incubation, latent and generation periods may help both in understanding transmission and developing therapeutic measures. The evidenced incubation period of covid-19 infection is found to be 5.6-6.7 days. Ayurveda advocates Shatkriyakala pathognomic model i.e. six stage model of disease progression. Aims and Objective: The present study focused to trace –pathological model in context of covid-19. Material and method: This study was conducted in Government ayurvedic institute, COVID testing centre, New Delhi. The tool of data collection was Questionnaire 1 &2. Result:We report a temporal pattern of COVID-19 pathology which corresponds to six-stages of disease progression.(shadvidh kriyakala). \u0000Discussion: Assessment of relationship between the variables (Hetu-dosha and Dushya) responsible for pathogenesis temporal dynamics of covid-19 may serve as an instrument for mapping the pathogenesis. \u0000Conclusion: Clinical staging of covid-19 can be potentially mapped by six stage classical pathological model.","PeriodicalId":214525,"journal":{"name":"Proceeding International Conference on Science and Engineering","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114116695","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 Investigation in Assessing the Main Metrics of Using Machine Learning Approaches for Bank Risk Management in the Current Era 评估当前时代使用机器学习方法进行银行风险管理的主要指标的关键调查

Proceeding International Conference on Science and Engineering Pub Date : 2023-02-18 DOI: 10.52783/cienceng.v11i1.210

Preety Tak

{"title":"A Critical Investigation in Assessing the Main Metrics of Using Machine Learning Approaches for Bank Risk Management in the Current Era","authors":"Preety Tak","doi":"10.52783/cienceng.v11i1.210","DOIUrl":"https://doi.org/10.52783/cienceng.v11i1.210","url":null,"abstract":"In a variety of application fields, including image classification, recognition of speech, and machine interpretation, machine learning (ML) and artificial intelligence (AI) have attained human-level performance. Nonetheless, master based credit risk models keep on administering in the monetary business. To continuously present new strategies, it is important to lay out significant benchmarks and correlations on AI approaches and human master based models. The progressions in banking and chance administration, as well as the present and future issues, have been the subject of much exploration in both scholarly community and business. Through an examination of the current writing, this paper expects to distinguish regions or issues in risk the board that poor person been adequately investigated and might be great contender for additional exploration. It additionally examinations and assesses AI methods that have been explored with regards to banking risk the executives. The comparison's main results showed that machine-learning models outperformed traditional methods. The neural networks also demonstrated excellent results when compared to other methods of machine-learning (ML) in relations of AUC and precission/ accuracy.","PeriodicalId":214525,"journal":{"name":"Proceeding International Conference on Science and Engineering","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116334910","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

Chronic Kidney Diseases Detection Using machine Learning 使用机器学习检测慢性肾脏疾病

Proceeding International Conference on Science and Engineering Pub Date : 2023-02-18 DOI: 10.52783/cienceng.v11i1.124

Swati Salunkhe, D. Gaikwad, Poonam Humbe, Shubham Kale, Sakshi, Lokhande

{"title":"Chronic Kidney Diseases Detection Using machine Learning","authors":"Swati Salunkhe, D. Gaikwad, Poonam Humbe, Shubham Kale, Sakshi, Lokhande","doi":"10.52783/cienceng.v11i1.124","DOIUrl":"https://doi.org/10.52783/cienceng.v11i1.124","url":null,"abstract":"Chronic kidney disease (CKD) and chronic renal disease (CRD) (CKD). Chronic renal disease refers to illnesses that affect your kidneys and reduce their ability to keep you healthy. Consequences include nerve damage, high blood pressure, anaemia, weak bones, and a lack of nourishment. Early detection and treatment can frequently stop chronic renal disease from getting worse. Data mining is the technique of obtaining knowledge from huge datasets. Utilizing previous data to find trends and guide decisions going forward is the aim of data mining. This task is the result of the convergence of a number of recent trends, including the declining cost of large data storage devices, the increasing simplicity of data collection over networks, the expansion of dependable and efficient machine learning algorithms, and the declining cost of computational power, which enables the use of computationally intensive techniques for decision-making. Machine learning has already produced useful applications in fields like assessing results from medical research, spotting fraud, spotting bogus users, etc.For the purpose of predicting chronic diseases, various data mining categorization methodologies and machine learning algorithms are used. The goal of this study is to develop a new decision-support system for forecasting chronic renal disease. This study compares the accuracy, precision, and execution time of Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) classifiers for the prediction of CKD.","PeriodicalId":214525,"journal":{"name":"Proceeding International Conference on Science and Engineering","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126531521","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 Wi-Fi Doorbell Using Esp32cam with IoT 智能Wi-Fi门铃使用esp32摄像头与物联网

Proceeding International Conference on Science and Engineering Pub Date : 2023-02-18 DOI: 10.52783/cienceng.v11i1.283

Jagadeesh, S. Dhanush, Vinethra, Siva Kumar

引用次数: 0

Some More Properties of Micro SP-Continuous using Micro SP-open Sets. 利用微sp开集的微sp连续的更多性质。

Proceeding International Conference on Science and Engineering Pub Date : 2023-02-18 DOI: 10.52783/cienceng.v11i1.209

M. Maheswari, S. Dhanalakshmi, N. Durgadevi

引用次数: 0

Incorporating a New Pseudorandom Number Generator in AES Algorithm to Improve Its Security Level 在AES算法中加入新的伪随机数生成器以提高其安全级别

Proceeding International Conference on Science and Engineering Pub Date : 2023-02-18 DOI: 10.52783/cienceng.v11i1.343

Dilshad Akhtar, M. R. Hassan, Neda Fatma

引用次数: 0

Optimal Design of Two Junction Four Reservoir Water Transmission System 二结四水库输水系统优化设计

Proceeding International Conference on Science and Engineering Pub Date : 2023-02-18 DOI: 10.52783/cienceng.v11i1.228

A. R. Bansod, R. S. Tatwawadi

引用次数: 0

Review of Counter-Based Digester ACK's Effectiveness in MANET Packet Loss Prevention 基于计数器的消化器ACK在MANET防丢包中的有效性综述

Proceeding International Conference on Science and Engineering Pub Date : 2023-02-18 DOI: 10.52783/cienceng.v11i1.355

Afsha Nishat, Mohd. Abdul Bari, Guddi Singh

{"title":"Review of Counter-Based Digester ACK's Effectiveness in MANET Packet Loss Prevention","authors":"Afsha Nishat, Mohd. Abdul Bari, Guddi Singh","doi":"10.52783/cienceng.v11i1.355","DOIUrl":"https://doi.org/10.52783/cienceng.v11i1.355","url":null,"abstract":"a wireless peer-to-peer network with a mobile component adaptability and self-formation characteristics that lacks infrastructure. The network is ideal for use in emergency and disaster assistance applications that need reliable communication.. Finding the channel between communicative entities and sending information across it enables communication. There are several routing protocols in the literature that are developed to achieve reliable communication. Routing protocols are susceptible to packet losses because they consider network nodes to be receptive to communication. Due to malicious behavior or a shortage of resources, nodes trash packets. To address the problem, a number of intrusion detection systems have been suggested in the literature. In order to prevent packet losses in MANET, the newly created counter-based digested Acknowledgement (CDACK) was developed. This study's objective is to assess the CDACK protocol's performance in relation to current MANET intrusion detection systems. The findings demonstrate that, in terms of avoiding packet dropping nodes from the routing path, the CDACK protocol is a good fit for MANET.. \u0000 ","PeriodicalId":214525,"journal":{"name":"Proceeding International Conference on Science and Engineering","volume":"87 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131844676","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