G. Samara, Raed Alazaidah, Mohammad Aljaidi, S. Almatarneh, Ahmed Banimustafa, Olla Bulkrock, Nael Sweerki, Adnan A. Hnaif
Wireless Sensor Networks are becoming more prevalent in various industries, including military operations and distant environmental monitoring. This is important because sensors are getting smarter, smaller, and less expensive. The energy hole problem in the WSN has been a major focus of recent research. The mobile sink is an efficient solution for the energy hole problem in a wireless sensor network. A mobile sink gets data from sensors by moving around the network often to avoid problems with hotspots or energy holes. It gets data from network nodes by traveling regularly and visiting a group of nodes known as rendezvous points (RPs). This research will present a probability-based RP selection (PRPS) technique for data collection in wireless sensor networks. To begin, a directed spanning tree is used to construct a tree that eliminates duplication in the data forwarding path. The proposed method is employed to compute the likelihood of RPs. Finally, using the shortest path technique, a mobile sink is constructed between these locations. The path provided is the best path that connects all of the RPs. The proposed approach improves the previous solutions by choosing the nodes with the most data packets as RPs. As a result, it extends network lifetime by lowering energy consumption and addressing the energy hole problem.
{"title":"Data Collection in WSNs using a Probability-Based Rendezvous Points Selection Algorithm","authors":"G. Samara, Raed Alazaidah, Mohammad Aljaidi, S. Almatarneh, Ahmed Banimustafa, Olla Bulkrock, Nael Sweerki, Adnan A. Hnaif","doi":"10.46338/ijetae0223_06","DOIUrl":"https://doi.org/10.46338/ijetae0223_06","url":null,"abstract":"Wireless Sensor Networks are becoming more prevalent in various industries, including military operations and distant environmental monitoring. This is important because sensors are getting smarter, smaller, and less expensive. The energy hole problem in the WSN has been a major focus of recent research. The mobile sink is an efficient solution for the energy hole problem in a wireless sensor network. A mobile sink gets data from sensors by moving around the network often to avoid problems with hotspots or energy holes. It gets data from network nodes by traveling regularly and visiting a group of nodes known as rendezvous points (RPs). This research will present a probability-based RP selection (PRPS) technique for data collection in wireless sensor networks. To begin, a directed spanning tree is used to construct a tree that eliminates duplication in the data forwarding path. The proposed method is employed to compute the likelihood of RPs. Finally, using the shortest path technique, a mobile sink is constructed between these locations. The path provided is the best path that connects all of the RPs. The proposed approach improves the previous solutions by choosing the nodes with the most data packets as RPs. As a result, it extends network lifetime by lowering energy consumption and addressing the energy hole problem.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134459658","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}
Since Autonomous Driving Vehicles are directly related to human life, it is necessary to put the utmost effort into safe driving to the point of being almost perfect. Also, for the best safety, any technology should be borrowed, tested, and applied. In this paper, the method of applying sound information to the Autonomous Driving Vehicles research presented last time will be emphasized and specified. Since the sound information to be applied to Autonomous Driving Vehicles is vast, it must be made into big data and must be used in various and precise ways, so it must be made into IOT based on AI. Sound Information Technology must be equipped with technology that can perfectly judge changing conditions such as time, season, and weather depending on the location. Acoustic Information Technology can be largely divided into ES(Environmental Sounds) and TS(Things Sounds). Environmental Sound is to detect the conditions of the surrounding environment including the road or the ground on which the vehicle is traveling with sound information. Things Sounds is to detect fixed or moving Things around the vehicle with sound information. In the future, it is expected that various methods of Sound Information Technology will be able to contribute greatly to the achievement of the era of Free Driving vehicles, which is the completion stage of Autonomous Driving Vehicles.
由于自动驾驶汽车直接关系到人类的生命，因此必须在安全驾驶方面付出最大的努力，达到近乎完美的程度。此外，为了最佳的安全性，任何技术都应该借鉴、测试和应用。本文将重点阐述上一篇文章提出的将声音信息应用到自动驾驶车辆研究中的方法。由于需要应用于自动驾驶汽车的声音信息非常庞大，因此必须将其制成大数据，并且必须以各种精确的方式使用，因此必须将其制成基于AI的IOT。健全的信息技术必须配备能够根据地点准确判断时间、季节和天气等变化条件的技术。声学信息技术在很大程度上可以分为ES(环境声音)和TS(事物声音)。环境声是用声音信息探测车辆行驶的道路或地面等周围环境的状况。物体声音是用声音信息探测车辆周围固定或移动的物体。未来，各种声音信息技术(Sound Information Technology)的方法有望为实现自动驾驶汽车(Autonomous Driving vehicles)的完成阶段——自由驾驶汽车(Free Driving vehicles)时代做出巨大贡献。
{"title":"A Study on the Application of Advanced Acoustic Information Technology for the Completion of Autonomous Driving Vehicles","authors":"I. Ahn","doi":"10.46338/ijetae0223_10","DOIUrl":"https://doi.org/10.46338/ijetae0223_10","url":null,"abstract":"Since Autonomous Driving Vehicles are directly related to human life, it is necessary to put the utmost effort into safe driving to the point of being almost perfect. Also, for the best safety, any technology should be borrowed, tested, and applied. In this paper, the method of applying sound information to the Autonomous Driving Vehicles research presented last time will be emphasized and specified. Since the sound information to be applied to Autonomous Driving Vehicles is vast, it must be made into big data and must be used in various and precise ways, so it must be made into IOT based on AI. Sound Information Technology must be equipped with technology that can perfectly judge changing conditions such as time, season, and weather depending on the location. Acoustic Information Technology can be largely divided into ES(Environmental Sounds) and TS(Things Sounds). Environmental Sound is to detect the conditions of the surrounding environment including the road or the ground on which the vehicle is traveling with sound information. Things Sounds is to detect fixed or moving Things around the vehicle with sound information. In the future, it is expected that various methods of Sound Information Technology will be able to contribute greatly to the achievement of the era of Free Driving vehicles, which is the completion stage of Autonomous Driving Vehicles.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126053999","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}
The periodically exchanged basic safety messages (BSM) in vehicular networks have become a new attack target for jamming attacks that are easy to conduct in a vehicular environment. The detection and mitigation must be cordially integrated to provide acceptable communication latency under attacking conditions. This paper considers a comprehensive defense system detecting and mitigating jamming attacks. We analyze the impact of the jamming attack on BSMs on our initially proposed random channel surfing scheme coupling with a detection method. The detection method can hardly provide 100% accuracy, and this consequently delays the reaction. We study the defense system by a mathematical model which is validated by simulations in NS-3. The obtained results depict how the performance of the channel surfing scheme depends on its preinstalled detection method
{"title":"A Defense System: Jamming Detection and Mitigation for Safety Applications in Vehicular Networks","authors":"H. Minh, Tran Hoang Tung, H. Nam, P. T. Giang","doi":"10.46338/ijetae0223_05","DOIUrl":"https://doi.org/10.46338/ijetae0223_05","url":null,"abstract":"The periodically exchanged basic safety messages (BSM) in vehicular networks have become a new attack target for jamming attacks that are easy to conduct in a vehicular environment. The detection and mitigation must be cordially integrated to provide acceptable communication latency under attacking conditions. This paper considers a comprehensive defense system detecting and mitigating jamming attacks. We analyze the impact of the jamming attack on BSMs on our initially proposed random channel surfing scheme coupling with a detection method. The detection method can hardly provide 100% accuracy, and this consequently delays the reaction. We study the defense system by a mathematical model which is validated by simulations in NS-3. The obtained results depict how the performance of the channel surfing scheme depends on its preinstalled detection method","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115090589","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}
Aiman Yusoff, N. Kamarudin, Nabil Ali Al-Emad, Khusairi Sapuan
— The difficulties to drive away the durian farm threatens animals such as wild boars, monkeys, foxes, and squirrels during nighttime often experienced by durian farmers. Therefore, the Pro Durian application is proposed that allows farmers to identify durian threats through a camera phone with an alert feature activation when the system detects an animal to drive away those animals. The application implements a deep learning algorithm of Convolutional Neural Network (CNN)-YOLO3in order to receive the best output results in identifying the different datasets of durian farm threats. The classification accuracies reached 80% in detecting the animal’s images. Keywords— Durian Farm, Recognition Image, TensorFlow lite, Android Studio, Convolution Neural Network
{"title":"Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development","authors":"Aiman Yusoff, N. Kamarudin, Nabil Ali Al-Emad, Khusairi Sapuan","doi":"10.46338/ijetae0223_02","DOIUrl":"https://doi.org/10.46338/ijetae0223_02","url":null,"abstract":"— The difficulties to drive away the durian farm threatens animals such as wild boars, monkeys, foxes, and squirrels during nighttime often experienced by durian farmers. Therefore, the Pro Durian application is proposed that allows farmers to identify durian threats through a camera phone with an alert feature activation when the system detects an animal to drive away those animals. The application implements a deep learning algorithm of Convolutional Neural Network (CNN)-YOLO3in order to receive the best output results in identifying the different datasets of durian farm threats. The classification accuracies reached 80% in detecting the animal’s images. Keywords— Durian Farm, Recognition Image, TensorFlow lite, Android Studio, Convolution Neural Network","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129476480","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}
Nur Syahirah Harun, Anisah Abd Wahab, Mimi Faisyalini Ramli, Z. Ngadiron, M. Rahiman, Jiangtao Sun
Recent advancements in microwave tomography (MT) imaging studies have stimulated interest in antenna array development for medical imaging. An antenna and a model of the human head are required for the medical MT system, particularly in detecting brain tumors. Previous studies have shown that antenna arrays are more reliable as compared to a single element of patch antenna in detecting brain tumors. In this study, a single patch antenna is first designed to work at 3.2GHz using CST Studio software. To evaluate the effectiveness of antenna arrays in microwave imaging systems, the patch antenna is then improved into a 2x1 and 4x1 array. The gain, directivity, return loss (S11), Voltage Standing Wave Ratio (VSWR), and bandwidth are compared between single and arrays of antenna models. It has been proved that 2x1 and 4x1 antenna arrays resulted in higher performance. With a maximum gain of 7.11 dB, the 4x1 rectangle patch antenna has 11.3 dBi directivity, -13.88 dB return loss, and 91.1 MHz bandwidth, meanwhile single patch antenna has a gain of 3.34 dB, 5.68 dBi directivity, - 17.33 dB return loss, and 132 MHz bandwidth. Overall, a 4x1 patch antenna is made reliable and sensitive to be used in detecting brain tumors as higher gain and directivity may be useful to penetrate multilayer human head.
{"title":"Antenna Array Performance in Microwave Imaging Technique for Brain Tumor Detection","authors":"Nur Syahirah Harun, Anisah Abd Wahab, Mimi Faisyalini Ramli, Z. Ngadiron, M. Rahiman, Jiangtao Sun","doi":"10.46338/ijetae0223_15","DOIUrl":"https://doi.org/10.46338/ijetae0223_15","url":null,"abstract":"Recent advancements in microwave tomography (MT) imaging studies have stimulated interest in antenna array development for medical imaging. An antenna and a model of the human head are required for the medical MT system, particularly in detecting brain tumors. Previous studies have shown that antenna arrays are more reliable as compared to a single element of patch antenna in detecting brain tumors. In this study, a single patch antenna is first designed to work at 3.2GHz using CST Studio software. To evaluate the effectiveness of antenna arrays in microwave imaging systems, the patch antenna is then improved into a 2x1 and 4x1 array. The gain, directivity, return loss (S11), Voltage Standing Wave Ratio (VSWR), and bandwidth are compared between single and arrays of antenna models. It has been proved that 2x1 and 4x1 antenna arrays resulted in higher performance. With a maximum gain of 7.11 dB, the 4x1 rectangle patch antenna has 11.3 dBi directivity, -13.88 dB return loss, and 91.1 MHz bandwidth, meanwhile single patch antenna has a gain of 3.34 dB, 5.68 dBi directivity, - 17.33 dB return loss, and 132 MHz bandwidth. Overall, a 4x1 patch antenna is made reliable and sensitive to be used in detecting brain tumors as higher gain and directivity may be useful to penetrate multilayer human head.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129696458","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}
Stock is a good investment tool, keeping money from inflation, and very trendy to earn a living nowadays by becoming a trader. There is always a risk, especially when trading, because stocks can fluctuate easily depending on the company. One of the data science capabilities, prediction modeling, can help lower the risk by predicting the stock price movement. This research proposed a prediction sequential data model, an optimized hyperparameter LSTM Network using hybrid GA-PSO (LSTM-GA-PSO). Hybrid GA-PSO aims to overcome the GA problem in terms of slow execution time and PSO that tend to be trapped in the local optimum. With the characteristics of both algorithms, the hybrid algorithm can solve each other algorithms downside. The low fluctuation stock of the Indonesian Index LQ45 dataset will be used to train and test the model and compare the proposed model with LSTM-GA and LSTM-PSO. Experiment results show that the hybrid LSTM-GA-PSO has a promising performance. Hybrid GA-PSO improved 18.18% of its time execution to GA and 29.07% accuracy to PSO.
{"title":"Long Short-Term Memory Network Hyperparameter Optimization using Hybrid Algorithm GA-PSO on LQ45 Stock Prediction","authors":"Adriel Lazaro Fitzhan, Antoni Wibowo","doi":"10.46338/ijetae0223_08","DOIUrl":"https://doi.org/10.46338/ijetae0223_08","url":null,"abstract":"Stock is a good investment tool, keeping money from inflation, and very trendy to earn a living nowadays by becoming a trader. There is always a risk, especially when trading, because stocks can fluctuate easily depending on the company. One of the data science capabilities, prediction modeling, can help lower the risk by predicting the stock price movement. This research proposed a prediction sequential data model, an optimized hyperparameter LSTM Network using hybrid GA-PSO (LSTM-GA-PSO). Hybrid GA-PSO aims to overcome the GA problem in terms of slow execution time and PSO that tend to be trapped in the local optimum. With the characteristics of both algorithms, the hybrid algorithm can solve each other algorithms downside. The low fluctuation stock of the Indonesian Index LQ45 dataset will be used to train and test the model and compare the proposed model with LSTM-GA and LSTM-PSO. Experiment results show that the hybrid LSTM-GA-PSO has a promising performance. Hybrid GA-PSO improved 18.18% of its time execution to GA and 29.07% accuracy to PSO.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114500894","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 this paper, a novel observer-based modelreference technique is developed to control the performance of nonlinear discrete-time systems. Firstly, a linear or nonlinear model is chosen for which the dynamics are designed to satisfy the pre-specified performance behaviours of the nonlinear system as stated by the designer. The proposed approach is then used with the system to fulfil a point-by-point tracking of the pre-designed model trajectories. To achieve this goal, an observer is firstly used to predict the states and the output(s) at the next sampling point of the system to be controlled from the received set of measurements. The differences between the achieved predicted estimates and those of the model are then used to generate the necessary online closed-loop control actions to force the system trajectories to track those of the model at the next sampling instant of time, as desired. The stability of the closed-loop control system is investigated. To check the performance of the developed approach, it is then used to control the performance of a synchronous machine and a permanent magnet synchronous motor. The achieved results are presented to illustrate the effectiveness, simplicity, and applicability of the proposed design procedure
{"title":"A New Observer-based Model- Reference Approach for Nonlinear Discrete-Time Systems with Application to Power Systems","authors":"M. F. Hassan, E. Aljuwaiser","doi":"10.46338/ijetae0223_12","DOIUrl":"https://doi.org/10.46338/ijetae0223_12","url":null,"abstract":"In this paper, a novel observer-based modelreference technique is developed to control the performance of nonlinear discrete-time systems. Firstly, a linear or nonlinear model is chosen for which the dynamics are designed to satisfy the pre-specified performance behaviours of the nonlinear system as stated by the designer. The proposed approach is then used with the system to fulfil a point-by-point tracking of the pre-designed model trajectories. To achieve this goal, an observer is firstly used to predict the states and the output(s) at the next sampling point of the system to be controlled from the received set of measurements. The differences between the achieved predicted estimates and those of the model are then used to generate the necessary online closed-loop control actions to force the system trajectories to track those of the model at the next sampling instant of time, as desired. The stability of the closed-loop control system is investigated. To check the performance of the developed approach, it is then used to control the performance of a synchronous machine and a permanent magnet synchronous motor. The achieved results are presented to illustrate the effectiveness, simplicity, and applicability of the proposed design procedure","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133037495","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}
Nurul Fatehah Abdul Ghafar, A. M. Markom, M. Q. Lokman, Z. Jusoh, Y. Yusof, H. Haris, A. R. Muhammad, Z. Yusoff, I. Saad, S. Harun
For many industries, the ability to distinguish between different solution concentrations is crucial. Modern sensors necessitate a labour-intensive and difficult approach. These problems are addressed by tapered fibre optic sensors. This fibre can be used as citric acid sensors because to its effectiveness, high sensitivity, stability, compact size, low cost, and tolerance to electromagnetic interference. The use of a tapered single-mode fibre sensor to monitor citric acid levels in deionized water is presented in this research. With increasing citric acid content, the wavelength shift of light transmitted from the fibre sensor is tracked and studied. Using a heat-pulling technique, the tapered fiber's waist diameter is reduced to 6 m. As the solution concentration increased from 400 ppm to 700 ppm, the wavelength shifted to the right, from 1524.86 nm to 1530 nm, with a sensitivity of 0.0169 nm/ppm and a linearity of 93%. This sensor has the benefits of being simple to use, inexpensive, and responsive.
{"title":"Tapered Fiber Sensor for Citric Acid Detection","authors":"Nurul Fatehah Abdul Ghafar, A. M. Markom, M. Q. Lokman, Z. Jusoh, Y. Yusof, H. Haris, A. R. Muhammad, Z. Yusoff, I. Saad, S. Harun","doi":"10.46338/ijetae0123_14","DOIUrl":"https://doi.org/10.46338/ijetae0123_14","url":null,"abstract":"For many industries, the ability to distinguish between different solution concentrations is crucial. Modern sensors necessitate a labour-intensive and difficult approach. These problems are addressed by tapered fibre optic sensors. This fibre can be used as citric acid sensors because to its effectiveness, high sensitivity, stability, compact size, low cost, and tolerance to electromagnetic interference. The use of a tapered single-mode fibre sensor to monitor citric acid levels in deionized water is presented in this research. With increasing citric acid content, the wavelength shift of light transmitted from the fibre sensor is tracked and studied. Using a heat-pulling technique, the tapered fiber's waist diameter is reduced to 6 m. As the solution concentration increased from 400 ppm to 700 ppm, the wavelength shifted to the right, from 1524.86 nm to 1530 nm, with a sensitivity of 0.0169 nm/ppm and a linearity of 93%. This sensor has the benefits of being simple to use, inexpensive, and responsive.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134147660","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}
The relationship among the on-to-off current ratio, threshold voltage, and the gate metal work-function is investigated for a junctionless (JL) Gate-All-Around (GAA) MOSFET with a gate oxide film in which SiO2 and a high-k dielectric material are stacked. The JL structure works in the accumulation state, and the threshold voltage is defined as the gate voltage when the minimum potential in the channel becomes Fermi potential. The on-to-off current ratio Ion/Ioff is obtained by obtaining on-current Ion at the threshold voltage and off-current Ioff at the gate voltage of 0 V. As a result, if the channel doping concentration and silicon radius are increased to reduce the channel resistance, the on-to-off current ratio decreases along with the threshold voltage, but this problem can be solved through the increasing of the gate metal workfunction. In addition, even when the relative permittivity of the high-k dielectric is increased from 3.9 to 20, the gate metal work-function to maintain any on-to-off current ratio and threshold voltage is very slightly changed. Therefore it will be possible to improve the controllability of the gate by increasing the permittivity of the high-k dielectric without change in the work-function. The reduction of the channel resistance of the JL GAA MOSFET is possible with the stacked gate oxide while maintaining a reasonable on-to-off current ratio and threshold voltage by adjusting the gate metal work-function
{"title":"Impact of Gate Metal Work-function for On-to-off Current Ratio and Threshold Voltage in Junctionless Gate-All-Around (GAA) MOSFET Stacked with SiO2 and High-k Dielectric","authors":"H. Jung","doi":"10.46338/ijetae0123_13","DOIUrl":"https://doi.org/10.46338/ijetae0123_13","url":null,"abstract":"The relationship among the on-to-off current ratio, threshold voltage, and the gate metal work-function is investigated for a junctionless (JL) Gate-All-Around (GAA) MOSFET with a gate oxide film in which SiO2 and a high-k dielectric material are stacked. The JL structure works in the accumulation state, and the threshold voltage is defined as the gate voltage when the minimum potential in the channel becomes Fermi potential. The on-to-off current ratio Ion/Ioff is obtained by obtaining on-current Ion at the threshold voltage and off-current Ioff at the gate voltage of 0 V. As a result, if the channel doping concentration and silicon radius are increased to reduce the channel resistance, the on-to-off current ratio decreases along with the threshold voltage, but this problem can be solved through the increasing of the gate metal workfunction. In addition, even when the relative permittivity of the high-k dielectric is increased from 3.9 to 20, the gate metal work-function to maintain any on-to-off current ratio and threshold voltage is very slightly changed. Therefore it will be possible to improve the controllability of the gate by increasing the permittivity of the high-k dielectric without change in the work-function. The reduction of the channel resistance of the JL GAA MOSFET is possible with the stacked gate oxide while maintaining a reasonable on-to-off current ratio and threshold voltage by adjusting the gate metal work-function","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123019912","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 suggests a hybrid movie recommendation system and optimization approach based on weighted classification and user collaborative filtering algorithm to address the issue that the single model of the standard recommendation system cannot adequately reflect user preferences. The top-N personalized movie recommendations are made by fusing the weighted classification model with the local recommendation model, which is trained based on user clustering, and the sparse linear model, which serves as the fundamental recommendation model. The scoring matrix is transformed into a low-dimensional, dense item category preference matrix based on item category preference, multiple cluster centers are obtained, the distance between each cluster center and the target user is calculated, and the target user is categorized into the closest cluster. Finally, a suggestion list is created using the collaborative filtering algorithm to forecast the scores for the target user's unrated items. The highdimensional rating matrix is transformed into a lowdimensional item category preference matrix, which further reduces the sparsity of the data. The items are then grouped based on item category preference. The recommendation algorithm suggested in this article addresses some of the limitations of a single algorithm model and enhances the suggestion effect, according to experiments using the MovieLens movie dataset.
{"title":"Hybrid Movie Recommendation System Using Machine Learning","authors":"Saurabh Sharma, H. K. Shakya","doi":"10.46338/ijetae0123_12","DOIUrl":"https://doi.org/10.46338/ijetae0123_12","url":null,"abstract":"This research suggests a hybrid movie recommendation system and optimization approach based on weighted classification and user collaborative filtering algorithm to address the issue that the single model of the standard recommendation system cannot adequately reflect user preferences. The top-N personalized movie recommendations are made by fusing the weighted classification model with the local recommendation model, which is trained based on user clustering, and the sparse linear model, which serves as the fundamental recommendation model. The scoring matrix is transformed into a low-dimensional, dense item category preference matrix based on item category preference, multiple cluster centers are obtained, the distance between each cluster center and the target user is calculated, and the target user is categorized into the closest cluster. Finally, a suggestion list is created using the collaborative filtering algorithm to forecast the scores for the target user's unrated items. The highdimensional rating matrix is transformed into a lowdimensional item category preference matrix, which further reduces the sparsity of the data. The items are then grouped based on item category preference. The recommendation algorithm suggested in this article addresses some of the limitations of a single algorithm model and enhances the suggestion effect, according to experiments using the MovieLens movie dataset.","PeriodicalId":169403,"journal":{"name":"International Journal of Emerging Technology and Advanced Engineering","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114609285","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}
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