In industrial Wireless Sensor Networks (WSNs), energy efficiency and reliable data transmission are critical challenges that need to be addressed to ensure sustainable and robust network operations. This paper proposes a novel energy-efficient routing protocol that integrates a Hybrid COOT-LS (Coot- Levy Search) algorithm with Long Short-Term Memory (LSTM)-based Dominant Object Motion (DOM) prediction. The routing protocol leverages the strengths of Hybrid Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) to enhance routing efficiency and reduce energy consumption. The Hybrid PSO and ACO algorithms are employed to optimize routing paths by balancing exploration and exploitation, considering multiple factors such as energy levels, node distance, and reliability. The COOT-LS algorithm further refines these paths by incorporating a Levy flight mechanism to enhance the search process. Additionally, the LSTM-based DOM prediction provides accurate forecasts of network conditions, enabling dynamic adjustments to routing strategies in real time. Simulation results demonstrate that the proposed protocol significantly improves network lifetime, reduces energy consumption, and enhances data transmission reliability compared to traditional routing protocols. This approach provides a robust and scalable solution for industrial WSN applications, ensuring efficient and reliable network performance in dynamic and complex industrial environments.
在工业无线传感器网络（WSN）中，能效和可靠的数据传输是确保网络可持续稳健运行所面临的关键挑战。本文提出了一种新型高能效路由协议，该协议将混合 COOT-LS（Coot-Levy 搜索）算法与基于长短期记忆（LSTM）的主要物体运动（DOM）预测相结合。该路由协议充分利用了混合粒子群优化（PSO）和蚁群优化（ACO）的优势，以提高路由效率并降低能耗。混合粒子群优化算法和蚁群优化算法通过平衡探索和开发，并考虑能量水平、节点距离和可靠性等多种因素来优化路由路径。COOT-LS 算法通过采用 Levy 飞行机制来加强搜索过程，从而进一步完善这些路径。此外，基于 LSTM 的 DOM 预测能准确预测网络状况，从而实时动态调整路由策略。仿真结果表明，与传统路由协议相比，所提出的协议显著提高了网络寿命，降低了能耗，并增强了数据传输的可靠性。这种方法为工业 WSN 应用提供了稳健、可扩展的解决方案，确保在动态、复杂的工业环境中实现高效、可靠的网络性能。
{"title":"A Novel Energy-Efficient Routing Protocol for Industrial WSN Using Hybrid Coot-Ls Algorithm with LSTM-Based Dom Prediction","authors":"Er.M. Dharshini, Mr.M.Satheesh Kumar","doi":"10.55041/ijsrem36722","DOIUrl":"https://doi.org/10.55041/ijsrem36722","url":null,"abstract":"In industrial Wireless Sensor Networks (WSNs), energy efficiency and reliable data transmission are critical challenges that need to be addressed to ensure sustainable and robust network operations. This paper proposes a novel energy-efficient routing protocol that integrates a Hybrid COOT-LS (Coot- Levy Search) algorithm with Long Short-Term Memory (LSTM)-based Dominant Object Motion (DOM) prediction. The routing protocol leverages the strengths of Hybrid Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) to enhance routing efficiency and reduce energy consumption. The Hybrid PSO and ACO algorithms are employed to optimize routing paths by balancing exploration and exploitation, considering multiple factors such as energy levels, node distance, and reliability. The COOT-LS algorithm further refines these paths by incorporating a Levy flight mechanism to enhance the search process. Additionally, the LSTM-based DOM prediction provides accurate forecasts of network conditions, enabling dynamic adjustments to routing strategies in real time. Simulation results demonstrate that the proposed protocol significantly improves network lifetime, reduces energy consumption, and enhances data transmission reliability compared to traditional routing protocols. This approach provides a robust and scalable solution for industrial WSN applications, ensuring efficient and reliable network performance in dynamic and complex industrial environments.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"18 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141806079","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}
-Blockchain technology has been adopted by a number of industries, including government agencies, financial services, healthcare, and agriculture, to improve their operations in the quickly changing modern world. But the industry for tenders hasn't yet completely realized all of its advantages. Due to problems including bias, bad record- keeping, lack of transparency, vulnerability to hackers, and data tampering, inadequate tender management procedures can cause large losses. We suggest using blockchain technology to ensure improved security and effectiveness in tender management as a solution to these problems. We can create a secure transaction management system that protects important documents and transactions related to the tendering process by utilizing encryption and the immutable nature of blockchain. By safely storing bid proposals, firm profiles, historical data, tender documents, and other information, this system fosters transparency and integrity. The Admin and Company modules are the two main components of the Smart Tender Management System. Administrators can oversee applications, handle tenders, and keep an eye on transaction logs with the help of the admin module. Companies can register, submit proposals, and monitor the status of their applications using the Company module. The solution improves security, lowers expenses, and simplifies tender processing by doing away with intermediaries and utilizing strong encryption techniques. This fosters an easy- to-use and effective experience for all parties involved KeyWords: Block chain Technology, Encryption, Smart Contracts, Tender Management.
{"title":"Smart Tender Management System Using Blockchain in Python","authors":"Shrikanth M S, A. C","doi":"10.55041/ijsrem36750","DOIUrl":"https://doi.org/10.55041/ijsrem36750","url":null,"abstract":"-Blockchain technology has been adopted by a number of industries, including government agencies, financial services, healthcare, and agriculture, to improve their operations in the quickly changing modern world. But the industry for tenders hasn't yet completely realized all of its advantages. Due to problems including bias, bad record- keeping, lack of transparency, vulnerability to hackers, and data tampering, inadequate tender management procedures can cause large losses. We suggest using blockchain technology to ensure improved security and effectiveness in tender management as a solution to these problems. We can create a secure transaction management system that protects important documents and transactions related to the tendering process by utilizing encryption and the immutable nature of blockchain. By safely storing bid proposals, firm profiles, historical data, tender documents, and other information, this system fosters transparency and integrity. The Admin and Company modules are the two main components of the Smart Tender Management System. Administrators can oversee applications, handle tenders, and keep an eye on transaction logs with the help of the admin module. Companies can register, submit proposals, and monitor the status of their applications using the Company module. The solution improves security, lowers expenses, and simplifies tender processing by doing away with intermediaries and utilizing strong encryption techniques. This fosters an easy- to-use and effective experience for all parties involved KeyWords: Block chain Technology, Encryption, Smart Contracts, Tender Management.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"46 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141807110","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}
Adhesive joints represent a significant advancement in material bonding technology, offering benefits such as reduced weight and uniform stress distribution, which distinguish them from conventional joining methods. Among the various adhesive joints, the scarf adhesive joint stands out due to its mechanical advantages and potential for high-strength applications. This research investigates the impact of key parameters on the strength of scarf adhesive joints, including scarf angle, surface roughness, adhesive type, and adhesive layer thickness. By systematically varying these parameters and employing a design of experimentation (DOE) methodology, we aim to identify the optimal conditions that maximize joint strength. A series of scarf adhesive joint specimens with diverse parameter combinations will be fabricated and tested to evaluate the resultant joint strength. Statistical analysis of the experimental data will facilitate the understanding of how each parameter influences joint performance and contribute to the development of optimized adhesive joint designs. The findings of this study are expected to advance the application of scarf adhesive joints in various high-performance engineering fields, providing insights into the critical factors that govern their strength and reliability. Key Words: Scarf Adhesive Joint, Adherend Material, SS 304 Stainless Steel, Finite Element Analysis (FEA), Tensile Strength, Max von Mises Stress, Scarf Angle, Design of Experiments (DOE), Adhesive Properties, Surface Roughness.
粘合剂连接是材料粘合技术的一大进步，具有重量轻、应力分布均匀等优点，有别于传统的连接方法。在各种粘合接头中，围巾粘合接头因其机械优势和高强度应用潜力而脱颖而出。本研究探讨了关键参数对挠性粘接强度的影响，包括挠性角、表面粗糙度、粘接剂类型和粘接层厚度。通过系统地改变这些参数并采用实验设计 (DOE) 方法，我们旨在找出能最大限度提高接头强度的最佳条件。我们将制作和测试一系列具有不同参数组合的围巾粘合接头试样，以评估由此产生的接头强度。对实验数据的统计分析将有助于了解每个参数如何影响接头性能，并有助于开发优化的粘接接头设计。本研究的结果有望推动疤痕粘接接头在各种高性能工程领域中的应用，为了解影响其强度和可靠性的关键因素提供深入的见解。关键字围巾粘接接头、粘接材料、SS 304 不锈钢、有限元分析 (FEA)、拉伸强度、最大 von Mises 应力、围巾角度、实验设计 (DOE)、粘接性能、表面粗糙度。
{"title":"Uncertainty Analysis of Tensile Strength of Scarf Adhesive Joints using Numerical Method and Validation through Experimentation","authors":"B. P. Sawant, P. Kulkarni","doi":"10.55041/ijsrem36758","DOIUrl":"https://doi.org/10.55041/ijsrem36758","url":null,"abstract":"Adhesive joints represent a significant advancement in material bonding technology, offering benefits such as reduced weight and uniform stress distribution, which distinguish them from conventional joining methods. Among the various adhesive joints, the scarf adhesive joint stands out due to its mechanical advantages and potential for high-strength applications. This research investigates the impact of key parameters on the strength of scarf adhesive joints, including scarf angle, surface roughness, adhesive type, and adhesive layer thickness. By systematically varying these parameters and employing a design of experimentation (DOE) methodology, we aim to identify the optimal conditions that maximize joint strength. A series of scarf adhesive joint specimens with diverse parameter combinations will be fabricated and tested to evaluate the resultant joint strength. Statistical analysis of the experimental data will facilitate the understanding of how each parameter influences joint performance and contribute to the development of optimized adhesive joint designs. The findings of this study are expected to advance the application of scarf adhesive joints in various high-performance engineering fields, providing insights into the critical factors that govern their strength and reliability. Key Words: Scarf Adhesive Joint, Adherend Material, SS 304 Stainless Steel, Finite Element Analysis (FEA), Tensile Strength, Max von Mises Stress, Scarf Angle, Design of Experiments (DOE), Adhesive Properties, Surface Roughness.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"52 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809000","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}
This research investigates the monitoring and management of an intravenous drip infusion system using the Internet of Things (IoT) and non- contact liquid level sensors, an Arduino circuit board, a GSM interface, and a cloud storage facility. The three sensors in the system are able to detect the presence of fluid without coming into contact with it. They can also send the data they collect to the cloud facility, where it can be used to access drip conditions and monitor fluid levels as well as control infusion flow when needed. This system can be considered an improvement over several systems on the market that are similarly intended to use optical sensors, TDR (Time domain reflectometry), and other types of sensors to monitor the IV drip flow. While it is true that each type of sensor has a combination of benefits and drawbacks, none of the other systems on the market can further regulate the drip flow like this one does. Since the sensors we've employed don't respond to fluids, the patients don't suffer any damage at all. This is now a crucial necessity in the biomedical industry since human reliance on IV drip infusions has led to a number of incidents, the most serious of which involved the patient suffering severe injuries from back blood flow in the nozzle. This system is made to guarantee that all safety precautions are taken and that the patient and attendant are in the best possible circumstances in order to minimize such incidents, accurately monitor and control fluid flow from drip to patients' veins, and prevent back blood flow. Keywords: Internet of Things, Intravenous drip infusion, Non‐contact Liquid Level Sensor, Thing speak, Esp-32, GSM.
{"title":"IoT-Driven Infusion Monitoring & Management System","authors":"Srashti Shukla, Prof. Dr. Meghana Mishra","doi":"10.55041/ijsrem36742","DOIUrl":"https://doi.org/10.55041/ijsrem36742","url":null,"abstract":"This research investigates the monitoring and management of an intravenous drip infusion system using the Internet of Things (IoT) and non- contact liquid level sensors, an Arduino circuit board, a GSM interface, and a cloud storage facility. The three sensors in the system are able to detect the presence of fluid without coming into contact with it. They can also send the data they collect to the cloud facility, where it can be used to access drip conditions and monitor fluid levels as well as control infusion flow when needed. This system can be considered an improvement over several systems on the market that are similarly intended to use optical sensors, TDR (Time domain reflectometry), and other types of sensors to monitor the IV drip flow. While it is true that each type of sensor has a combination of benefits and drawbacks, none of the other systems on the market can further regulate the drip flow like this one does. Since the sensors we've employed don't respond to fluids, the patients don't suffer any damage at all. This is now a crucial necessity in the biomedical industry since human reliance on IV drip infusions has led to a number of incidents, the most serious of which involved the patient suffering severe injuries from back blood flow in the nozzle. This system is made to guarantee that all safety precautions are taken and that the patient and attendant are in the best possible circumstances in order to minimize such incidents, accurately monitor and control fluid flow from drip to patients' veins, and prevent back blood flow. Keywords: Internet of Things, Intravenous drip infusion, Non‐contact Liquid Level Sensor, Thing speak, Esp-32, GSM.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"50 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809561","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}
There are many avenues in financial market. An Investor can invest in Bank deposit, corporate debenture and bonds which has law risk with low return. He may also Investor in stock of company which has high risk with hight return. Investors look for safer investment avenues and want to maximize their returns in according to their risk. Whereas people also tries to invest money as early as possible so that the money will grow accordingly in his lifetime. Choose a good investing option is very critical because a balance is required to be maintained between the risks and returns involved in investment. Return is inspiring force and principal reward in the investment process. One of the essential, reason because ofwhich one needs to invest fairly is to meet the cost of inflation. Inflation is the rate at which the cost of living increases at that time. A mutual fund is an expertly overseen company of collective investments that swimming pools money from numerous buyers and puts it in stocks, bonds, momentary money market instruments, as nicely as distinct securities. Mutual money is emerging as helpful instrument for a large scope of speculators, from people looking to put some thing aside for retirement to subtle socialites concentrated on defending their belongings and businesspeople to make wealth. Mutual Fund is a trust that pools the reserve funds of various buyers who share a typical financial objective. Anyone with an investible overflow of as little as two or three thousand rupees can put resources into mutual fund devices as indicated by means of their expressed objective and strategy. Mutual Fund Company pools money from a gathering of individuals with normal hypothesis targets to buy securities, for example, stocks, bonds, money market instruments, a mixture of these instruments, or significantly unique belongings so as to acquire the reward of enhancement and expertly oversaw container of protections at a reasonably ease. In a mutual fund, the fund manager, who is likewise excellent as the portfolio manager, trades the funds underlying securities, acknowledging capital positive factors or losses, and gathers the dividend or hobby income. The income are passed alongside to the investors. The charge of a share of the mutual fund, acknowledged as the net asset value (NAV), which is determined on day through day base, in mild of the absolute estimation of the mutual fund divided by the extent of high-quality shares presently issued.
{"title":"STUDY OF RISK AND RETURN OF MUTUAL FUNDS","authors":"Aditya Gupta, of Dr. Shilpa Bahl","doi":"10.55041/ijsrem36743","DOIUrl":"https://doi.org/10.55041/ijsrem36743","url":null,"abstract":"There are many avenues in financial market. An Investor can invest in Bank deposit, corporate debenture and bonds which has law risk with low return. He may also Investor in stock of company which has high risk with hight return. Investors look for safer investment avenues and want to maximize their returns in according to their risk. Whereas people also tries to invest money as early as possible so that the money will grow accordingly in his lifetime. Choose a good investing option is very critical because a balance is required to be maintained between the risks and returns involved in investment. Return is inspiring force and principal reward in the investment process. One of the essential, reason because ofwhich one needs to invest fairly is to meet the cost of inflation. Inflation is the rate at which the cost of living increases at that time. A mutual fund is an expertly overseen company of collective investments that swimming pools money from numerous buyers and puts it in stocks, bonds, momentary money market instruments, as nicely as distinct securities. Mutual money is emerging as helpful instrument for a large scope of speculators, from people looking to put some thing aside for retirement to subtle socialites concentrated on defending their belongings and businesspeople to make wealth. Mutual Fund is a trust that pools the reserve funds of various buyers who share a typical financial objective. Anyone with an investible overflow of as little as two or three thousand rupees can put resources into mutual fund devices as indicated by means of their expressed objective and strategy. Mutual Fund Company pools money from a gathering of individuals with normal hypothesis targets to buy securities, for example, stocks, bonds, money market instruments, a mixture of these instruments, or significantly unique belongings so as to acquire the reward of enhancement and expertly oversaw container of protections at a reasonably ease. In a mutual fund, the fund manager, who is likewise excellent as the portfolio manager, trades the funds underlying securities, acknowledging capital positive factors or losses, and gathers the dividend or hobby income. The income are passed alongside to the investors. The charge of a share of the mutual fund, acknowledged as the net asset value (NAV), which is determined on day through day base, in mild of the absolute estimation of the mutual fund divided by the extent of high-quality shares presently issued.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"31 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809081","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}
Today’s mobile devices contain densely packaged system-on-chips (SoCs) with multi-core, high frequency CPUs and complex pipelines. In parallel, sophisticated SoC-assisted security mechanisms have become commonplace for protecting device data, such as trusted execution environments, full disk and file-based encryption. Both advancements have dramatically complicated the use of conventional physical attacks, requiring the development of specialised attacks Our proposed classification system allows to analyze side-channel attacks systematically, and facilitates the development of novel countermeasures. Besides this new categorization system, the extensive survey of existing attacks and attack strategies provides valuable insights into the evolving field of side-channel attacks, especially when focusing on mobile devices.. Key Words: Side-channel Attack, active, passive
当今的移动设备包含密集封装的系统芯片（SoC），具有多核、高频 CPU 和复杂的流水线。与此同时，复杂的片上系统辅助安全机制也已成为保护设备数据的常用机制，例如可信执行环境、全磁盘和基于文件的加密。我们提出的分类系统可以对侧信道攻击进行系统分析，并促进新型对策的开发。除了这一新的分类系统，对现有攻击和攻击策略的广泛调查也为不断发展的侧信道攻击领域提供了宝贵的见解，尤其是在关注移动设备时。关键字侧信道攻击、主动、被动
{"title":"Threats due To Side Channel Attacks (SCA) in Smartphones","authors":"Anushka Naik","doi":"10.55041/ijsrem36777","DOIUrl":"https://doi.org/10.55041/ijsrem36777","url":null,"abstract":"Today’s mobile devices contain densely packaged system-on-chips (SoCs) with multi-core, high frequency CPUs and complex pipelines. In parallel, sophisticated SoC-assisted security mechanisms have become commonplace for protecting device data, such as trusted execution environments, full disk and file-based encryption. Both advancements have dramatically complicated the use of conventional physical attacks, requiring the development of specialised attacks Our proposed classification system allows to analyze side-channel attacks systematically, and facilitates the development of novel countermeasures. Besides this new categorization system, the extensive survey of existing attacks and attack strategies provides valuable insights into the evolving field of side-channel attacks, especially when focusing on mobile devices.. Key Words: Side-channel Attack, active, passive","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"39 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809622","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}
In the today’s society the major issue facing by the student is to catch the college bus on time to reached the destination, the student will be unaware of the college bus whether it has already left the place of the pickup or not?, where is bus? in that case there is no proper solution which identifies the location of a bus. Henceforth in the order to help the students in finding the accurate location of bus, the proposed system implements an Android applications which could help in finding the solution to this problem. By applying latest idea regarding the solution based on GPS (global positioning system) on Internet of Things(IoT), the college students can effectively organize and schedule the bus movement on a campus and also helps to tracking and document it in real time. Thus, the user’s application receives from the Google Map API the map that highlights the recent position of bus. This system also included with the emergency panic button if any accident occur in between the travelling by clicking the panic button student has sent to the notification of alert message to the admin it is equipped with exact location of bus through Gmail. Key Words: Android, GPS, Google Map API, Gmail.
{"title":"Real-time College Bus Tracking System","authors":"Divya R, Hemanth Kumar","doi":"10.55041/ijsrem36730","DOIUrl":"https://doi.org/10.55041/ijsrem36730","url":null,"abstract":"In the today’s society the major issue facing by the student is to catch the college bus on time to reached the destination, the student will be unaware of the college bus whether it has already left the place of the pickup or not?, where is bus? in that case there is no proper solution which identifies the location of a bus. Henceforth in the order to help the students in finding the accurate location of bus, the proposed system implements an Android applications which could help in finding the solution to this problem. By applying latest idea regarding the solution based on GPS (global positioning system) on Internet of Things(IoT), the college students can effectively organize and schedule the bus movement on a campus and also helps to tracking and document it in real time. Thus, the user’s application receives from the Google Map API the map that highlights the recent position of bus. This system also included with the emergency panic button if any accident occur in between the travelling by clicking the panic button student has sent to the notification of alert message to the admin it is equipped with exact location of bus through Gmail. Key Words: Android, GPS, Google Map API, Gmail.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"41 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141809750","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}
K. Lakshmipriya, S.P. Charu Prafulla, S. Lokesh, O. U. Maheswari
Unmanned aerial vehicle(UAV) technology is the rapid growing technology in the field of monitoring for security purposes, pesticides spraying and various other applications. In the recent days, one of the major concerns is entering of malicious UAVs into the secured perimeter that might result in Drone-based cyberattacks. So, the detection of these malicious UAVs are crucial. In this work, an acoustic method of detecting malicious UAVs is proposed. The mixed form of the acoustic signals of two kinds of drones, namely, Fixed- wing and Multi- rotor are passed through the Blind Source Separation (BSS) block, where the kurtosis is measured along with Independent Component Analysis (ICA) for the separation of the signals. Then the distinctive features, Mel-Frequency Cepstral Coefficient(MFCC), Gamma tone-Frequency Cepstral Coefficient(GTCC) and short time energy are extracted from the acoustic signal and are trained using Neural Network(NN) classifier to identify the malicious UAV. The proposed method under different conditions outperforms the existing techniques with an accuracy of 100% in identification of malicious UAV. Key Words: Blind Source Separation Algorithm, kurtosis, Independent Component Analysis, Mel-Frequency Cepstral Coefficient(MFCC), Gamma tone-Frequency Cepstral Coefficient(GTCC), short time energy, Neural Networks
{"title":"Malicious UAV Detection Using Blind Source Separation Algorithm and Neural Network Classifier","authors":"K. Lakshmipriya, S.P. Charu Prafulla, S. Lokesh, O. U. Maheswari","doi":"10.55041/ijsrem36797","DOIUrl":"https://doi.org/10.55041/ijsrem36797","url":null,"abstract":"Unmanned aerial vehicle(UAV) technology is the rapid growing technology in the field of monitoring for security purposes, pesticides spraying and various other applications. In the recent days, one of the major concerns is entering of malicious UAVs into the secured perimeter that might result in Drone-based cyberattacks. So, the detection of these malicious UAVs are crucial. In this work, an acoustic method of detecting malicious UAVs is proposed. The mixed form of the acoustic signals of two kinds of drones, namely, Fixed- wing and Multi- rotor are passed through the Blind Source Separation (BSS) block, where the kurtosis is measured along with Independent Component Analysis (ICA) for the separation of the signals. Then the distinctive features, Mel-Frequency Cepstral Coefficient(MFCC), Gamma tone-Frequency Cepstral Coefficient(GTCC) and short time energy are extracted from the acoustic signal and are trained using Neural Network(NN) classifier to identify the malicious UAV. The proposed method under different conditions outperforms the existing techniques with an accuracy of 100% in identification of malicious UAV. Key Words: Blind Source Separation Algorithm, kurtosis, Independent Component Analysis, Mel-Frequency Cepstral Coefficient(MFCC), Gamma tone-Frequency Cepstral Coefficient(GTCC), short time energy, Neural Networks","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"51 11","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141806904","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}
This paper reviews applications of machine learning (ML) predictive models in the diagnosis of chronic diseases. Chronic diseases (CDs) are responsible for a major portion of global health costs. Patients who suffer from these diseases need lifelong treatment. Nowadays, predictive models are frequently applied in the diagnosis and forecasting of these diseases. In this study, we reviewed the state-of-the-art approaches that encompass ML models in the primary diagnosis of CD. This analysis covers 453 papers published between 2015 and 2019, and our document search was conducted from PubMed (Medline), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) libraries. Ultimately,22 studies were selected to present all modeling methods in a precise way that explains CD diagnosis and usage models of individual pathologies with associated strengths and limitations. Our outcomes suggest that there are no standard methods to determine the best approach in real-time clinical practice since each method has its advantages and disadvantages. Among clustering were the most used. These models are highly applicable in classification, and diagnosis of CD and are expected to become more important in medical practice in the near future. Keywords: chronic diseases; prediction models; pathologies; accuracy; disease classification; K-Nearest Neighbors (KNN); Convolutional Neural Networks(CNN); disease forecasting; disease management.
本文回顾了机器学习（ML）预测模型在慢性病诊断中的应用。慢性疾病（CD）占全球医疗成本的很大一部分。这些疾病的患者需要终生治疗。如今，预测模型经常被应用于这些疾病的诊断和预测。在本研究中，我们回顾了将 ML 模型应用于 CD 初诊的最先进方法。该分析涵盖了2015年至2019年期间发表的453篇论文，我们的文献检索来自PubMed（Medline）和Cumulative Index to Nursing and Allied Health Literature（CINAHL）图书馆。最终，我们选择了 22 篇研究，以精确的方式介绍所有建模方法，解释 CD 诊断和个别病症的使用模型，以及相关的优势和局限性。我们的研究结果表明，在实时临床实践中没有标准方法来确定最佳方法，因为每种方法都有其优缺点。其中使用最多的是聚类。这些模型非常适用于慢性疾病的分类和诊断，预计在不久的将来会在医疗实践中变得更加重要。关键词： 慢性疾病；预测模型；病理；准确性；疾病分类；K-近邻（KNN）；卷积神经网络（CNN）；疾病预测；疾病管理。
{"title":"Predictive Models in the Chronic Disease Diagnosis","authors":"Anshuman Samantaray, Dr. Sujit Ku Panda","doi":"10.55041/ijsrem36558","DOIUrl":"https://doi.org/10.55041/ijsrem36558","url":null,"abstract":"This paper reviews applications of machine learning (ML) predictive models in the diagnosis of chronic diseases. Chronic diseases (CDs) are responsible for a major portion of global health costs. Patients who suffer from these diseases need lifelong treatment. Nowadays, predictive models are frequently applied in the diagnosis and forecasting of these diseases. In this study, we reviewed the state-of-the-art approaches that encompass ML models in the primary diagnosis of CD. This analysis covers 453 papers published between 2015 and 2019, and our document search was conducted from PubMed (Medline), and Cumulative Index to Nursing and Allied Health Literature (CINAHL) libraries. Ultimately,22 studies were selected to present all modeling methods in a precise way that explains CD diagnosis and usage models of individual pathologies with associated strengths and limitations. Our outcomes suggest that there are no standard methods to determine the best approach in real-time clinical practice since each method has its advantages and disadvantages. Among clustering were the most used. These models are highly applicable in classification, and diagnosis of CD and are expected to become more important in medical practice in the near future. Keywords: chronic diseases; prediction models; pathologies; accuracy; disease classification; K-Nearest Neighbors (KNN); Convolutional Neural Networks(CNN); disease forecasting; disease management.","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"62 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141806955","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}
AI is the use of computers that can do things that only humans can do, such as thinking, making decisions, and solving problems. In today’s world, artificial intelligence (AI) refers to a vast array of technologies that drive many of the products and services we use on a daily basis – from TV show recommendations to chatbots providing real-time customer support. But is AI really what most of us think it is? If not, why do we keep hearing the term ‘AI’ so often? In this article, researcher will cover everything you need to know about AI, what it does, and how it is used in e-commerce. Researcher will cover some of its advantages and disadvantages as well as impact of artificial intelligence(AI) on e- commerce. Keywords - E-commerce, Artificial Intelligence (AI).
{"title":"A STUDY ON IMPACT OF AI ON E-COMMERCE IN MUMBAI REGION","authors":"Dipali Gopane","doi":"10.55041/ijsrem36712","DOIUrl":"https://doi.org/10.55041/ijsrem36712","url":null,"abstract":"AI is the use of computers that can do things that only humans can do, such as thinking, making decisions, and solving problems. In today’s world, artificial intelligence (AI) refers to a vast array of technologies that drive many of the products and services we use on a daily basis – from TV show recommendations to chatbots providing real-time customer support. But is AI really what most of us think it is? If not, why do we keep hearing the term ‘AI’ so often? In this article, researcher will cover everything you need to know about AI, what it does, and how it is used in e-commerce. Researcher will cover some of its advantages and disadvantages as well as impact of artificial intelligence(AI) on e- commerce. Keywords - E-commerce, Artificial Intelligence (AI).","PeriodicalId":504501,"journal":{"name":"INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT","volume":"94 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141808118","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：