International Journal of Emerging Science and Engineering最新文献

{"title":"Network Anomaly Detection System using Deep Learning with Feature Selection Through PSO","authors":"Rimjhim Rathore, Dr. Neeraj Shrivastava","doi":"10.35940/ijese.f2531.0411523","DOIUrl":"https://doi.org/10.35940/ijese.f2531.0411523","url":null,"abstract":"The more computer systems that communicate and cooperate, the more crucial it is to make our lives simpler. At the same time, it highlights faults that people are unable to correct. Due to faults, cyber-security procedures are required to communicate data. Secure communication requires both the installation of security measures and the development of security measures to address changing security concerns. In this study, it is suggested that network intrusion detection systems be able to adapt and be resilient. This could be done by using deep learning architectures. Deep learning is used in this article to find and group network attacks. There are some tools that can help intrusion detection systems that are more flexible learn to recognise new or zero-day network behaviour features, which can help them get rid of bad guys and make it less likely that they'll get into your network. The model's efficacy was tested using the KDD dataset, which combines real-world network traffic with fake attack operations.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129717070","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}

{"title":"Neighbour Node Ratio AODV (NNR-AODV) Routing Protocol for Wormhole Attack Detection in Manets","authors":"M. V. D. S. K. Murty, Dr. Lakshmi Rajamani","doi":"10.35940/ijese.d2547.0311423","DOIUrl":"https://doi.org/10.35940/ijese.d2547.0311423","url":null,"abstract":"This paper aimed at the detection of wormhole attack and proposed a new method called as Neighbour Node Ratio Adhoc On demand Distance Vector Routing (NNR-AODV). NNR-AODV is an extended version of the traditional AODV routing protocol. The proposed NNR-AODV calculates the neighbour node count for every node and based on that it will decide whether the wormhole is present or not. Furthermore, NNR-AODV is able to detect both external and internal wormhole attacked nodes. Also, NNR-AODV derived a Neighbor node Threshold value which is based on the cumulative distances between nodes present in the wormhole attack. For experimental validation, we have accomplished an extensive simulation and the performance is measured through Number of bogus links, Detection rate, False positive Rate, Packet delivery ratio and Packet loss ratio. The obtained results have shown superior performance in the detection of wormhole attacks than the existing methods.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132113761","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}

{"title":"VIPR- Vibration Induced Parkinson’s Relief","authors":"Anushka Sridhar","doi":"10.35940/ijese.c2544.0211323","DOIUrl":"https://doi.org/10.35940/ijese.c2544.0211323","url":null,"abstract":"This paper describes VIPR, an inexpensive tremor detection and mitigation device to help Parkinson’s patients. It is built using a Raspberry PI, an accelerometer, power switches and a wristband with rows of coin motors, and python code. More than 10 million people world-wide have visible symptoms of Parkinson’s disease. There is no known cure for the disease and the annual cost for treatment is estimated to be >$50Billion. Whole body vibration therapy has been widely researched but is expensive and not easily available. This device fits around a patient’s wrist and uses an accelerometer to detect the onset of tremors and turns on the vibrating coin motors in the wristband at different levels depending on the tremor intensity. The data is continuously logged and sent to a care giver via a SMART phone connection. The accelerometer in the device is used to measure the change in acceleration in X,Y, and Z directions every 0.2 seconds and the data is compared to a threshold value to determine if the movement is a tremor or not. Once its established that it’s a tremor, a relay switch turns on the coin motors on the wrist. Data was collected on Parkinson’s patients to establish the efficacy of the vibrating wrist band and the threshold. The band was found to effectively improve the motor response of the patients while performing simple tasks such as writing and moving objects. This inexpensive device was found to be effective and can be used to improve the quality of life of Parkinson’s patients.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132305407","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}

{"title":"Optimal Sizing of Hybrid Renewable Energy System using Manta Ray Foraging Technique","authors":"Priyanka Brahamne, Assoc. Prof. M. P. S. Chawla, Dr. H. K. Verma","doi":"10.35940/ijese.c2545.0211323","DOIUrl":"https://doi.org/10.35940/ijese.c2545.0211323","url":null,"abstract":"In this paper, a method for optimizing the size of a standalone hybrid that consists of a wind, PV, and biomass energy system with battery storage is discussed. Hybrid renewable energy systems are required in off-the-grid communities. For such systems, the optimal system sizing can be regarded as one of the constrained optimization issues. This research presents an intelligent approach based on modern optimization for designing the hybrid renewable energy system optimally using the manta ray foraging technique, minimizing overall annualized system cost and satisfying load demand. In order to confirm the effectiveness of the proposed method, results are compared against findings from the ABC algorithm. The results have proven that the MRFO algorithm has fast convergence properties, the ability to deliver high-quality results, and the capacity to manage a smooth power flow under the same ideal conditions.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134163249","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}

{"title":"Machine Learning: A Literature Review for Breast Cancer","authors":"Vaishnavi Karma, Prateek Nahar","doi":"10.35940/ijese.b2543.0111223","DOIUrl":"https://doi.org/10.35940/ijese.b2543.0111223","url":null,"abstract":"Breast cancer is, after lung cancer, the most prevalent form of the disease in the globe. Women are the demographic most likely to be affected by this condition. Breast cancer is the most common kind of cancer to result in a woman's death if she is of childbearing age. Because there is always more to learn and there is room for improvement in every line of work, medical imaging is not an exception to this rule. It is expected that the death rate associated with cancer would decrease if it is discovered early and effectively treated. The diagnosis accuracy of persons working in the health care profession may be improved via the use of machine learning techniques. The technique known as deep learning has the potential to differentiate between breasts that are healthy and those that have cancer also known as neural networking. This method might be used to differentiate between healthy breast tissue and breast tissue affected by illness. Long-term research on the topic aimed, among other things, to examine breast cancer and screening practises among Indian women. This was one of the primary goals of the inquiry. A literature study was carried out with the assistance of several databases along with additional sources. Participants in the study were instructed to use phrases linked to breast cancer such as \"breast carcinoma\" and \"breast cancer awareness,\" in addition to terms such as \"knowledge\" and \"attitude,\" as well as the gender neutral term \"women.\" In addition, India had a role in the study that was done. This search does not look for articles that have been published in the English language in the last 12 years.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121213910","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}

{"title":"Artificial Intelligence Based Optimal Placement of PMU","authors":"Rachana Pandey, Dr. H. K. Verma, Dr. Arun Parakh, Dr. Cheshta Jain Khare","doi":"10.35940/ijese.i2541.10101122","DOIUrl":"https://doi.org/10.35940/ijese.i2541.10101122","url":null,"abstract":"The investigation of power system disturbances is critical for ensuring the supply’s dependability and security. Phasor Measurement Unit (PMU) is an important device of our power network, installed on system to enable the power system monitoring and control. By giving synchronised measurements at high sample rates, Phasor Measurement Units have the potential to record quick transients with high precision. PMUs are gradually being integrated into power systems because they give important phasor information for power system protection and control in both normal and abnormal situations. Placement of PMU on every bus of the network is not easy to implement, either because of expense or because communication facilities in some portions of the system are limited. Different ways for placing PMUs have been researched to improve the robustness of state estimate. The paper proposes unique phasor measurement unit optimal placement methodologies. With full network observability, the suggested methods will assure optimal PMU placement. The proposed algorithm will be thoroughly tested using IEEE 7, 9, 14, and 24 standard test systems, with the results compared to existing approaches.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129146507","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}

{"title":"Comparative Study of Electric Vehicle Battery Systems with Lithium-Ion and Solid State Batteries","authors":"Himanshi Koli, Prof. M. P. S. Chawla","doi":"10.35940/ijese.i2540.09101022","DOIUrl":"https://doi.org/10.35940/ijese.i2540.09101022","url":null,"abstract":"Due to mechanical advancements, a continued emphasis on sustainable power, and the typical decrease of transportation's impact on ecological change and other regular difficulties, EVs are currently seeing a renaissance. Electric automobiles are portrayed by Project Drawdown as one of the top 100 modern solutions for monitoring climate change. Despite the traction battery specialty systems utilized for modern (or wearing) automobiles, an electric-vehicle battery (EVB) is a battery used to control the stimulus plan of an electric vehicle (BEVs). These batteries are typically assistance (battery-controlled) batteries, and they typically include lithium ions. Forklifts, electric golf trucks, riding floor scrubbers, electric bicycles, electric cars, trucks, vans, and other types of vehicles all employ traction batteries, which are categorically arranged with a high ampere-hour limit.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"258263 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133216561","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}

{"title":"Network Intrusion Detection Systems: A Systematic Literature Review o f Hybrid Deep Learning Approaches","authors":"S. Wanjau, G. Wambugu, A. Oirere","doi":"10.35940/ijese.f2530.0610722","DOIUrl":"https://doi.org/10.35940/ijese.f2530.0610722","url":null,"abstract":"Network Intrusion Detection Systems (NIDSs) have become standard security solutions that endeavours to discover unauthorized access to an organizational computer network by scrutinizing incoming and outgoing network traffic for signs of malicious activity. In recent years, deep learning based NIDSs have emerged as an active area of research in cybersecurity and several surveys have been done on these systems. Although a plethora of surveys exists covering this burgeoning body of research, there lacks in the literature an empirical analysis of the different hybrid deep learning models. This paper presents a review of hybrid deep learning models for network intrusion detection and pinpoints their characteristics which researchers and practitioners are exploiting to develop modern NIDSs. The paper first elucidates the concept of network intrusion detection systems. Secondly, the taxonomy of hybrid deep learning techniques employed in designing NIDSs is presented. Lastly, a survey of the hybrid deep learning based NIDS is presented. The study adopted the systematic literature review methodology, a formal and systematic procedure by conducting bibliographic review, while defining explicit protocols for obtaining information. The survey results suggest that hybrid deep learning-based models yield desirable performance compared to other deep learning algorithms. The results also indicate that optimization, empirical risk minimization and model complexity control are the most important characteristics in the design of hybrid deep learning-based models. Lastly, key issues in the literature exposed in the research survey are discussed and then propose several potential future directions for researchers and practitioners in the design of deep learning methods for network intrusion detection.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"108 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120898400","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}

{"title":"Simulation of Maralal Water Flow Distribution Network using EPANET Model in Samburu County, Kenya","authors":"Paul Lolmingani, Prof. Dr.-Ing. Benedict M. Mutua, Dr. Eng. David N. Kamau","doi":"10.35940/ijese.f2533.0510622","DOIUrl":"https://doi.org/10.35940/ijese.f2533.0510622","url":null,"abstract":"Majority of people in developing countries do not have access to clean and potable water due to inadequate supply and distribution system challenges. While the rationale of water distribution systems is to deliver to each consumer safe drinking water that is adequate in quality and quantity at an acceptable delivery pressure, this has been a major drawback for many distribution networks. In addition, the design spans of many urban and peri-urban water distribution networks managed by the Water Service Providers (WSPs) are being exceeded without augmentation. Maralal water distribution network is one of such distribution systems with poor system performance that has been the main contributor of high Non-Revenue Water (NRW). This coupled with significant mismatch between water supply and water demand makes Maralal Water and Sanitation Company to resort to hedging/intermittent flow leading to water rationing. One of the ways of predicting the flow dynamics within the distribution system is the use of hydraulic simulation models. This study therefore applied the Environmental Protection Agency Network (EPANET) simulation model to predict the dynamic state of the hydraulics and water quality behaviour for Maralal water distribution system operating over an extended period of time. The general objective was to simulate water flow for Maralal water distribution system using the EPANET model for efficient planning, operation and maintenance protocol for the system. The study focused on the steady state (static), extended period (dynamic), and water quality analyses. The model calibration results from four statistical criteria; Nash-Sutcliffe model efficiency coefficient (E), Sum of Squares Error (SSE), Percentage Bias (PB) and Root Mean Square Error (RMSS) of 0.99, 0.01, 0.05 and 0.03 respectively show that the model performed within acceptable range of the selected statistical criteria. The findings of this study were: The roughness coefficients for a water distribution network that contribute to erratic pressure-dependent flows can be determined at any time using the regression analysis of the measured head loss and flow rate, EPANET model can predict the steady and dynamic hydraulic parameters for the current and future water distribution systems and Chlorine decay with respect to pipe diameter impacts on hydraulic performance and quality of water in a distribution network. The results from this study would assist water service providers and managers to make informed decisions in relation to water distribution system planning, operation and maintenance to achieve the desired current and future water demands.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125716270","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}

{"title":"State-of-the Art Review on Seismic Design of Retaining Wall","authors":"Nabam Nakia, Talkeshwar Ray","doi":"10.35940/ijese.g2534.0510622","DOIUrl":"https://doi.org/10.35940/ijese.g2534.0510622","url":null,"abstract":"This paper provides an insight information about performance of retaining wall considering seismic condition by referring the past studies. As a result of inappropriate analysis and design leads to poor construction of retaining wall due to which losses occurs economically as well as in physical aspect, to avoid this situation especially in highly seismic zone, types and behavior of soil condition should be well known by the designer before the design of structure. So far many approaches has been carried out by the different researchers are reviewed in this paper.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122323037","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}