2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)最新文献

{"title":"Phased Array of Microstrip Patch Antenna for Millimetre Wave Applications","authors":"M. N. Naik, Hassanali Gulamali Virani","doi":"10.1109/ICSTSN57873.2023.10151663","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151663","url":null,"abstract":"In this paper, the phased array of microstrip patch antenna for millimeter wave applications has been designed for 28 GHz, 38 GHz and 60 GHz. The phased array of l x2,1x4,1x8 and 4 x8 array has been designed on FR-4 substrate of height 0.2 mm with dielectric constant $varepsilon$r of 4.4 and loss tangent of 0.0004. Using the structure of arrays, the analysis of the parameters such as return loss, directivity, gain, radiation and antenna efficiency, bandwidth has been done for 28 GHz, 38 GHz and 60 GHz.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130050219","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":"Design and Implementation of Z-Shaped Polarized Micro strip Patch Antenna for Detecting Skin Cancer","authors":"D. Ruban Thomas, V. Prabhu, V. Kalyana Sundari, D. Kotteshwari, Kethineni Sai Sharanya","doi":"10.1109/ICSTSN57873.2023.10151631","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151631","url":null,"abstract":"The aim of this research is to develop a Z-shaped patch antenna to detect the skin cancer. A Z-shaped patch antenna can be implanted into human skin to detect the presence of skin cancer by using specific absorption rate (SAR) data. The RT/Duroid 5880 substrate material used in the antenna, which has a relative permittivity of3.4, operates at 6 GHz. Since the Zshaped patch antenna has a low SAR value that reduces the risk of skin radiation exposure, this design is ideal for biomedical applications. The flexible patch antenna is applied directly to the skin and tests both healthy and malignant cells using established settings. Cancer can be discovered by comparing the gain, voltage standing wave ratio (VSWR), and return loss of cancer cells to healthy cells. Cancerous cells can differ in size and structure. The Z-shaped microstrip patch antenna was created and simulated using the HFSS tool in the Ansys software.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121283113","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":"Block Chain-Based Voting System","authors":"T. Raja Sree, L. Mary Shamala","doi":"10.1109/ICSTSN57873.2023.10151630","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151630","url":null,"abstract":"A secure fair electronic voting system is required for the smooth working of any democratic process. This paper implements a voting-based system application that runs with the support of blockchain to create a decentralized voting system. The proposed system aims to eliminate the aspect of trust from an election to make it more secure and transparent.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115945498","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":"Forecasting Pre-Owned Car Prices Using Machine Learning","authors":"Challa Lakshmi Lasya, S. Pooja, S. Jeyashree, C. Ambhika, G. Eswari","doi":"10.1109/ICSTSN57873.2023.10151632","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151632","url":null,"abstract":"Over 70 million passenger cars were produced in 2016 shows that automotive manufacturing has been steadily rising during the previous ten years. As a result, the market for used vehicles was created, and it has since flourished as a separate industry. With the advent of online marketplaces, it is now simpler for buyers and sellers to comprehend the current patterns influencing the market value of worn cars. The manufacture of second-hand cars has been gradually rising due to the epidemic. Making the proper decisions while purchasing an automobile is crucial. Many internet portals are accessible to help sellers and buyers discover the market worth of used cars. Utilizing the internet, customers may quickly comprehend used car pricing. For customers, we may export used automobiles. Because of Covid, this car marketing is thriving in India right now. The project’s main crisp is moving forward with multiple machine learning models that will, without vagueness, forecast the price of the used car based on specific parameters. The buyer and seller will utilize web resources to learn about market pattern recognition for used cars. A number of strategies are employed in concert to establish a forecasting model that predicts the cost of a cast-off car. Application of Neural Network Models like penalized models, linear Regression, and Regression Trees. We’ll try to devise synthetic data that can predict the cost of a used automobile based on prior customers’ info and set of indicators. We can anticipate new outcomes using prior data from customers, and we can compare the predicted results to identify the best one.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132555311","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":"Development of peak detection algorithm using window variance for physiological variability monitoring","authors":"Sushma N Bhat, G. Jindal, Uttam Rajaram Bagal, Gajanan D. Nagare","doi":"10.1109/ICSTSN57873.2023.10151557","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151557","url":null,"abstract":"Physiological variability has gained importance in the assessment of autonomic function as well as monitoring of severity and prognosis of various diseases in last 5 decades. Electrocardigram or peripheral arterial pulse is generally used for deriving variability spectrum. Presently manual processing and analysis of these signals are done in the absence of a rugged peak detection method yielding no false positive with few false negatives. Continuous patient monitoring demands automatic peak detection without any manual intervention. False positive peak detection can result in erroneous variability spectrum, though false negatives can be interpolated within limits (1-5%). With above in view, an algorithm named window variance is proposed which uses a moving window of the input signal (0.3 seconds) with a shift of 0.025 seconds to locate peaks and use variance to eliminate false positives. This algorithm has been tested in 5 minutes of continuous data (with and without superimposed random noise) from 5 volunteers, comprising 1907 true peaks yielding no false positives and very few false negatives (0.1573%).","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131019532","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":"DQ-WiAPDoM: A DQN-based AP Deployment Optimization Method for Wi-Fi FTM Positioning","authors":"Zihao Liu, Han Li, Bo Gao, Ke Xiong, Pingyi Fan","doi":"10.1109/ICSTSN57873.2023.10151521","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151521","url":null,"abstract":"This paper focuses on how to optimize the deployment location of the anchor Wi-Fi access points (APs) in order to enhance the indoor positioning performance of the finetime measurement (FTM) protocol. Compared to conventional Wi-Fi positioning, FTM protocol is able to achieve relatively good indoor positioning performance since it estimates distance between a sender and its receiver with the flight duration of Wi-Fi signals. However, the FTM-based positioning accuracy in NLoS environments is still not high, which restricts its application in indoor scenarios. To this end, we formulate an optimization problem to maximize the total number of LoS paths by optimizing the locations of the anchor APs. To solve the problem, we propose a Deep Q-Network (DQN)-based AP deployment optimization method (DQ-WiAPDoM), which utilizes DQN to optimize the locations of APs such that the total number of LoS paths over all covered area is maximized. Experimental results show that DQ-WiAPDoM converges well and is able to reduce the average positioning error efficiently.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131411606","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":"Malware Detection Using Ensemble Learning and File Monitoring","authors":"Tilak Vignesh, Sowhith Reddy, Sonit Kumar, Akshat Chourey, Chandrashekhar Pomu Chavan","doi":"10.1109/ICSTSN57873.2023.10151567","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151567","url":null,"abstract":"In essence, malware refers to harmful programs that cybercriminals use to infiltrate a specific machine or an organisation’s complete network. It takes advantage of flaws in legitimate software (such a browser or plugin for an online application) that can be hijacked. ML is widely used to mitigate this problem which is an excellent solution but the problem with this is that it’s possible for ML to falsely detect some files causing system exploits. This paper aims to provide a method to detect malware using ensemble learning and further monitor files based on a probability value assigned to it by the model.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124391823","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":"Design and Analysis of Microstrip Yagi Uda Antenna for 5G Communication on FR4 Substrate","authors":"V. Pavidha, A. Jayakumar","doi":"10.1109/ICSTSN57873.2023.10151514","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151514","url":null,"abstract":"For 5G communication, this study offers the Microstrip Yagi Uda antenna on FR4 substrate with microstrip line feed. The six element Yagi antenna is used for 5G communication. The microstrip feed Yagi antenna reduces the size, improve efficiency, Gain and Directivity of an antenna. The Element of Yagi Uda antenna are Driven element, Reflector and Directors. The proposed antenna was analysed using High frequency structure simulator tool. The High Frequency Structure Simulator (HFSS) is utilised for three-dimensional visualisation simulations in the field of antenna design, as well as for Electromagnetic simulations in high frequency electronic devices. The Structure is analysed for various antenna parameters such as Bandwidth, Gain, Directivity, Beam Area, Radiation Pattern and Input impedance. The Proposed antenna structure provides a gain of 5.7 dBi at frequency of24GHZ. The Proposed Antenna provides Return loss of 2. 8203dB, Voltage standing wave ratio of 1.5, Input Impedance of 11 Ohm, Beam Area of 7.05 Watts were calculated.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"71 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123179343","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":"Energy Aware Node deployment using Ant Lion optimization algorithm in underwater acoustic sensor Network","authors":"R. S. Kumar, G. Sivaradje","doi":"10.1109/ICSTSN57873.2023.10151482","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151482","url":null,"abstract":"underwater wireless sensor networks were created as a result of the spread of wireless sensor networks. Because of its extensive and in-the-moment applications, it has had a significant impact on research. However, there are numerous challenges to successfully implementing underwater wireless sensor networks. The issue of energy depletion in sensor nodes is the biggest concern in the underwater sensor network. In this article, the Ant Lion optimization algorithm (ALOA) is employed to extend the lifespan of the underwater wireless sensor network, collect information from inner sub-cluster sensor nodes, and shorten the relay nodes’ multi-hop transmission distance. The undersea network area is modeled as a set of three-dimensional concentric cylinders with many stages. Each stage is also separated into a number of blocks, each of which represents a single cluster. The suggested algorithm operates in a bottom-up Vertical communication from the ocean floor to the surface. The communication problems caused by strong water pressure toward the sea floor are resolved by using many levels of differing heights. Simulations are run to demonstrate the effectiveness of the suggested approach, which performs better in terms of throughput of 297.99 kbps, PDR of 46.34%, energy usage of 13%, and packet loss of 165.6 kbps.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123416664","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":"Performance Evaluation of Data Mining and Neural Network Based Models For Diabetes Prediction","authors":"Priyabrata Sahu, J. K. Mantri","doi":"10.1109/ICSTSN57873.2023.10151474","DOIUrl":"https://doi.org/10.1109/ICSTSN57873.2023.10151474","url":null,"abstract":"Diabetes, often known as diabetes mellitus, is a disease that disrupts the body’s normal response to blood sugar. The pancreas releases insulin, which aids in the uptake of glucose from meals into cells to be used as fuel. Hyper-glycemia,or high blood sugar, is a typical result of uncontrolled diabetes and is associated with several significant health complications, most notably those affecting the nerves and blood vessels. Statistics indicate that in 2014, adults 18 and above had diabetes, and in 2019, diabetes was responsible for 1.5 million fatalities worldwide. Machine learning and deep learning predictive models have seen tremendous development throughout industries, including health care, making early diagnosis of diabetes a breeze. Many potentially fatal diseases, such as cancer, diabetes, heart disease, thyroid disease, etc., may be predicted or diagnosed with the use of machine learning classifiers. The treatment of chronic diabetes, one of the world’smost prevalent illnesses, might benefit greatly from improved diagnostic efficiency.Here, we examine the relative merits among several ML and DL approaches to the problem of early diabetic illness prediction. The fundamental purpose of this research is to organize and conduct out diabetes prognosis with several ML learning approaches and then analyze the results of these methods to determine which one is the most accurate classifier. In this work, we take a multifaceted approach to diabetes and its prediction by investigating a wide range of disease-related characteristics. We use the classic Dataset Based on PIDD, and we apply several Machine Learning and Deep learning classifiers to it, including Random Forest (RF), Logisticregression (LR), Support Vector Machine, Artificial Neural Network (ANN), Multilayer Perceptron (MLP), and Decision Tree, Gradient Boost (GB), XGBoost (GB), Adaboost (GB), CATBOOST (GB), and LightGBM (LGBM). There is a wide range of precision amongst the models used here. A technology that can precisely predict diabetes is shown in this research. The findings of this research indicate that one of the Data mining models, random forest (RF), and the ANN Model from the category of neural network models have superior accuracy in making diabetes forecasts.","PeriodicalId":325019,"journal":{"name":"2023 2nd International Conference on Smart Technologies and Systems for Next Generation Computing (ICSTSN)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127752132","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}