Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290669
G. Khekare, Pushpneel Verma
Technology is advancing day by day. Automation is playing an important role. Internet of Everything (IoE) has emerged as a key technology that enables everything to be connected through the internet. In every field Internet of everything is generating a vast amount of data like health system, traffic system, smart city monitoring system, education system, social networking sites, government organizations, etc. So to handle this huge amount of data, a system is required through which it becomes easier to track, analyze, handle, and apply that data in a better way. A unique system is proposed in this article through which important keys are identified. From those keys, desired data can be retrieved quickly and efficiently. The proposed system uses the entire new process to get the desired output. The k-means clustering with a modified entire process is used. By using natural language processing the data is accessed by the voice command. Through simulation results, it is proved that the proposed system has given better results and the searching process becomes smoother and efficient.
科技日新月异。自动化正在发挥重要作用。万物互联(Internet of Everything, IoE)已经成为一项通过互联网连接万物的关键技术。在每一个领域，万物互联都在产生大量的数据，比如医疗系统、交通系统、智慧城市监控系统、教育系统、社交网站、政府机构等。因此，为了处理如此庞大的数据，需要一个系统，通过它可以更容易地跟踪、分析、处理和更好地应用这些数据。本文提出了一个唯一的系统，通过它可以识别重要的密钥。从这些键中，可以快速有效地检索所需的数据。提出的系统使用整个新过程来获得期望的输出。采用k-means聚类方法对整个过程进行了改进。通过使用自然语言处理，通过语音命令访问数据。仿真结果表明，该系统具有较好的搜索效果，搜索过程更加流畅、高效。
{"title":"Design of Automatic Key Finder for Search Engine Optimization in Internet of Everything","authors":"G. Khekare, Pushpneel Verma","doi":"10.1109/ICCE50343.2020.9290669","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290669","url":null,"abstract":"Technology is advancing day by day. Automation is playing an important role. Internet of Everything (IoE) has emerged as a key technology that enables everything to be connected through the internet. In every field Internet of everything is generating a vast amount of data like health system, traffic system, smart city monitoring system, education system, social networking sites, government organizations, etc. So to handle this huge amount of data, a system is required through which it becomes easier to track, analyze, handle, and apply that data in a better way. A unique system is proposed in this article through which important keys are identified. From those keys, desired data can be retrieved quickly and efficiently. The proposed system uses the entire new process to get the desired output. The k-means clustering with a modified entire process is used. By using natural language processing the data is accessed by the voice command. Through simulation results, it is proved that the proposed system has given better results and the searching process becomes smoother and efficient.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134418006","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}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290563
Soumen Swarnakar, Neeraj Kumar, Amit Kumar, Chandan Banerjee
Cloud-based Computation is one of the important computing technologies where demand-based services and resources from the user's application to cloud data center with the help of internet connection can be achieved as pay on demand. The software, resources, applications are shared among different computing devices in a cloud-based approach. Balancing of Load in cloud computation technology is meant for the distribution of workload to balance loads among different cloud servers connected with different virtual machines. The main idea of load balancing is to optimize resource usage, cost of data center and virtual machines, maximization of throughput, reduction of response time and avoidance of overloading in different virtual machines as well as cloud servers. In cloud load balancing fitness checking of different cloud servers as well as virtual machines are playing an important role in cloud applications. In this proposed research paper genetic-based algorithmic approach has been used to handle the load balancing in the cloud environment. Genetic Algorithm can be used for getting solution of an optimization problem. Here it is used to find the fittest virtual machines connected with different Data Centers. Our proposed work is more appropriate compared to different algorithms discussed in [1][2], as in proposed algorithm cloudlets are taking a smaller amount time for execution and performs the load balancing in cloud environment with more efficient way by using strong fittest function for allocating cloudlets into appropriate virtual machines of a data center in cloud environment.
云计算是一种重要的计算技术，通过互联网连接，用户的应用到云数据中心的按需服务和资源可以按需付费。软件、资源和应用程序以基于云的方式在不同的计算设备之间共享。云计算技术中的负载均衡(Balancing of Load)是指负载的分配，在连接不同虚拟机的不同云服务器之间实现负载均衡。负载平衡的主要思想是优化资源使用，数据中心和虚拟机的成本，最大限度地提高吞吐量，减少响应时间，避免不同虚拟机和云服务器的过载。在云计算负载平衡中，不同云服务器和虚拟机的适应度检查在云应用中起着重要的作用。本文提出了一种基于遗传算法的方法来处理云环境下的负载均衡。遗传算法可用于求解优化问题。这里使用它来查找与不同数据中心连接的最合适的虚拟机。与[1][2]中讨论的不同算法相比，我们提出的工作更合适，因为在我们提出的算法中，cloudlets的执行时间更短，并且通过使用强拟合函数将cloudlets分配到云环境中数据中心的适当虚拟机中，以更有效的方式在云环境中执行负载平衡。
{"title":"Modified Genetic Based Algorithm for Load Balancing in Cloud Computing","authors":"Soumen Swarnakar, Neeraj Kumar, Amit Kumar, Chandan Banerjee","doi":"10.1109/ICCE50343.2020.9290563","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290563","url":null,"abstract":"Cloud-based Computation is one of the important computing technologies where demand-based services and resources from the user's application to cloud data center with the help of internet connection can be achieved as pay on demand. The software, resources, applications are shared among different computing devices in a cloud-based approach. Balancing of Load in cloud computation technology is meant for the distribution of workload to balance loads among different cloud servers connected with different virtual machines. The main idea of load balancing is to optimize resource usage, cost of data center and virtual machines, maximization of throughput, reduction of response time and avoidance of overloading in different virtual machines as well as cloud servers. In cloud load balancing fitness checking of different cloud servers as well as virtual machines are playing an important role in cloud applications. In this proposed research paper genetic-based algorithmic approach has been used to handle the load balancing in the cloud environment. Genetic Algorithm can be used for getting solution of an optimization problem. Here it is used to find the fittest virtual machines connected with different Data Centers. Our proposed work is more appropriate compared to different algorithms discussed in [1][2], as in proposed algorithm cloudlets are taking a smaller amount time for execution and performs the load balancing in cloud environment with more efficient way by using strong fittest function for allocating cloudlets into appropriate virtual machines of a data center in cloud environment.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132266989","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}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290530
Soumyadip Jana, Souradeep Mullick, Sayan Sarkar, P. Pal
In reference to general mathematics, Pulse is mainly a rapid, momentary change in the amplitude of any signal from a value of baseline to a higher or lower value, followed by a swift return to the baseline value. In the context of medical science, pulses (heart-pulse) are very useful for diagnosing a patient suffering from cardiac anomalies such as arrhythmia, in which the patient suffers from irregular heartbeat when some of the pulses in his cardiac pulse chain are failed to occur which have a predefined interval of time. Hence, the prototype is to be designed such that any such skipped beats do not go undetected. Therefore, in this paper, a novel, simple solution technique is proposed, in which a condition is simulated where one or more pulse would go missing, a process named Missing Pulse Generation, after which, detection of the missing pulses and their counting after a certain time, have been executed, and along with an external PPG (Photoplethysmogram) based Pulse sensing mechanism has been used to measure patient’s heart beats per minute (BPM) physically, so that, a specialist can prescribe a suitable solution for the patient’s recovery. In heart rate monitoring system, conventional missing pulse detection technique has been used since long time by which only the presence of unnatural missing pulses can be detected but here our approach is more effective than the conventional one as the detection & counting of missing & extra cardiac pulses have been brought together from human cardiac pulse chain and heart rate sensing mechanism in an automated & accurate way by minimizing the diagnosis time which is very much useful for long continuous heart-rate monitoring.
{"title":"A Simple Approach to Detect and Count Missing Cardiac Pulses and PPG Based Heart Rate Sensing","authors":"Soumyadip Jana, Souradeep Mullick, Sayan Sarkar, P. Pal","doi":"10.1109/ICCE50343.2020.9290530","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290530","url":null,"abstract":"In reference to general mathematics, Pulse is mainly a rapid, momentary change in the amplitude of any signal from a value of baseline to a higher or lower value, followed by a swift return to the baseline value. In the context of medical science, pulses (heart-pulse) are very useful for diagnosing a patient suffering from cardiac anomalies such as arrhythmia, in which the patient suffers from irregular heartbeat when some of the pulses in his cardiac pulse chain are failed to occur which have a predefined interval of time. Hence, the prototype is to be designed such that any such skipped beats do not go undetected. Therefore, in this paper, a novel, simple solution technique is proposed, in which a condition is simulated where one or more pulse would go missing, a process named Missing Pulse Generation, after which, detection of the missing pulses and their counting after a certain time, have been executed, and along with an external PPG (Photoplethysmogram) based Pulse sensing mechanism has been used to measure patient’s heart beats per minute (BPM) physically, so that, a specialist can prescribe a suitable solution for the patient’s recovery. In heart rate monitoring system, conventional missing pulse detection technique has been used since long time by which only the presence of unnatural missing pulses can be detected but here our approach is more effective than the conventional one as the detection & counting of missing & extra cardiac pulses have been brought together from human cardiac pulse chain and heart rate sensing mechanism in an automated & accurate way by minimizing the diagnosis time which is very much useful for long continuous heart-rate monitoring.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132873900","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}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290581
Mou De, A. Kundu, S. Guha
In cloud datacenter, job scheduling is used to manage real-time user data for improving response time of user query. Completion of tasks depends on datacenter availability, the capacity of virtual machines, network connection, and broker management policies. We propose a cloud-based architecture with a cloud service manager to select virtual machines from vmpool for optimizing tasks in the datacenter. The scheduling algorithm decides which virtual machine executes the task according to the nature and size of the task with minimal waiting time for execution.
{"title":"Advanced Cloud based Task Scheduling Architecture to Optimize Performance in Datacenter","authors":"Mou De, A. Kundu, S. Guha","doi":"10.1109/ICCE50343.2020.9290581","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290581","url":null,"abstract":"In cloud datacenter, job scheduling is used to manage real-time user data for improving response time of user query. Completion of tasks depends on datacenter availability, the capacity of virtual machines, network connection, and broker management policies. We propose a cloud-based architecture with a cloud service manager to select virtual machines from vmpool for optimizing tasks in the datacenter. The scheduling algorithm decides which virtual machine executes the task according to the nature and size of the task with minimal waiting time for execution.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115488284","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}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290680
Jasmin B. Mulla, A. Khandare, R. Patil
In a radar application, Time Signal Generator (TSG) is used to generate timing and control signals which helps radar to operate in different functions. The functions include tracking, detection, and hold mode. Timing Signal Generator is the heart of radar applications. Timing Signal Generator is the main part of radar application, which is responsible for synchronization between Transmitter and receiver for the transmitted signal. In this work, an implementation of timing signal using a Hardware Description Language (HDL) language-based state machine which is responsible for enabling Direct Digital Synthesis and Analog to Digital Converter in the Transmitter and receiver window. Timing Signal Generator implementation on Field Programmable Gate Array is preferred as the entire Timing signal generator unit can be assembled on a single Field programmable gate array chip, and conditional modification can be performed remotely, which is cost-effective. Timing signal generator generation begins by providing an arbitrary frequency and phase signal configuration to DDS-AD9854 from Field programmable gate array. Direct digital synthesis block generates a single-tone signal and Binary Phase Shift Keying signal and a chirp signal based on an input arbitrary signal sent by ZYBO-7010 FPGA.
在雷达应用中，时间信号发生器(Time Signal Generator, TSG)用来产生定时和控制信号，帮助雷达完成不同的功能。功能包括跟踪、检测和保持模式。定时信号发生器是雷达应用的核心。授时信号发生器是雷达应用的主要部分，它负责对发射信号在发射机和接收机之间进行同步。在这项工作中，使用基于硬件描述语言(HDL)语言的状态机实现定时信号，该状态机负责在发送和接收窗口中实现直接数字合成和模数转换。首选在现场可编程门阵列上实现定时信号发生器，因为整个定时信号发生器单元可以组装在单个现场可编程门阵列芯片上，并且可以远程进行有条件的修改，具有成本效益。时序信号发生器的生成首先从现场可编程门阵列向DDS-AD9854提供任意频率和相位信号配置。直接数字合成模块根据ZYBO-7010 FPGA发送的任意输入信号，产生单音信号、二相移键控信号和啁啾信号。
{"title":"Timing Signal Generator for High Frequency Radar","authors":"Jasmin B. Mulla, A. Khandare, R. Patil","doi":"10.1109/ICCE50343.2020.9290680","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290680","url":null,"abstract":"In a radar application, Time Signal Generator (TSG) is used to generate timing and control signals which helps radar to operate in different functions. The functions include tracking, detection, and hold mode. Timing Signal Generator is the heart of radar applications. Timing Signal Generator is the main part of radar application, which is responsible for synchronization between Transmitter and receiver for the transmitted signal. In this work, an implementation of timing signal using a Hardware Description Language (HDL) language-based state machine which is responsible for enabling Direct Digital Synthesis and Analog to Digital Converter in the Transmitter and receiver window. Timing Signal Generator implementation on Field Programmable Gate Array is preferred as the entire Timing signal generator unit can be assembled on a single Field programmable gate array chip, and conditional modification can be performed remotely, which is cost-effective. Timing signal generator generation begins by providing an arbitrary frequency and phase signal configuration to DDS-AD9854 from Field programmable gate array. Direct digital synthesis block generates a single-tone signal and Binary Phase Shift Keying signal and a chirp signal based on an input arbitrary signal sent by ZYBO-7010 FPGA.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131208363","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}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290730
S. singh, S. Bose, P. Dwivedi
Switched inductor topology is an advanced byproduct of Z-Source inverter which is equipped with enlarged voltage boost factor capability, employing less duty ratio and high modulation index. A well established closed loop power control requires high quality waveform followed by a good current controller which should be precise and should have significant effect on the dynamics of the system. Transient modelling is performed to widen the investigative study of non-minimum phase behaviour caused by right hand plane zeroes exhibited due to the impedance network on the DC side of these inverters. Also the independency of DC side and AC side control has been kept in discussion with separate controller designs. This paper presents an idea of decoupled AC side control in synchronous reference frame to eliminate the cross coupled behaviour of d-q axes during independent control of active and reactive powers. Simulation result shows good reference tracking and disturbance rejection property, which is recognised to be evident and substantial using MATLAB as testing platform.
{"title":"Decoupled MultiLoop Control of Switched Inductor Z-Source Inverters for Distributed Generations","authors":"S. singh, S. Bose, P. Dwivedi","doi":"10.1109/ICCE50343.2020.9290730","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290730","url":null,"abstract":"Switched inductor topology is an advanced byproduct of Z-Source inverter which is equipped with enlarged voltage boost factor capability, employing less duty ratio and high modulation index. A well established closed loop power control requires high quality waveform followed by a good current controller which should be precise and should have significant effect on the dynamics of the system. Transient modelling is performed to widen the investigative study of non-minimum phase behaviour caused by right hand plane zeroes exhibited due to the impedance network on the DC side of these inverters. Also the independency of DC side and AC side control has been kept in discussion with separate controller designs. This paper presents an idea of decoupled AC side control in synchronous reference frame to eliminate the cross coupled behaviour of d-q axes during independent control of active and reactive powers. Simulation result shows good reference tracking and disturbance rejection property, which is recognised to be evident and substantial using MATLAB as testing platform.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128884716","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}
Permanent Magnet Synchronous (PMS) motor has huge applications in Electric Vehicles. Therefore, a correct prediction of both speed and torque is required for satisfactory result. A dataset is considered having real time data of ambient temperature, coolant temperature, direct axis and quadrature axis voltage and current, yoke temperature, rotor temperature and stator temperature for prediction of motor speed and torque. This dataset is collected from the test bench of University of Paderbon laboratory. Various machine learning models have been applied on the dataset. The result shows that Fine Tree is the best model for prediction of both speed and torque of the permanent magnet synchronous motor having lowest RMSE of 0.029224 and 0.052538 for prediction of speed and torque respectively.
{"title":"Application of Machine Learning for Speed and Torque Prediction of PMS Motor in Electric Vehicles","authors":"Debottam Mukherjee, Samrat Chakraborty, Pabitra Kumar Guchhait, Joydeep Bhunia","doi":"10.1109/ICCE50343.2020.9290632","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290632","url":null,"abstract":"Permanent Magnet Synchronous (PMS) motor has huge applications in Electric Vehicles. Therefore, a correct prediction of both speed and torque is required for satisfactory result. A dataset is considered having real time data of ambient temperature, coolant temperature, direct axis and quadrature axis voltage and current, yoke temperature, rotor temperature and stator temperature for prediction of motor speed and torque. This dataset is collected from the test bench of University of Paderbon laboratory. Various machine learning models have been applied on the dataset. The result shows that Fine Tree is the best model for prediction of both speed and torque of the permanent magnet synchronous motor having lowest RMSE of 0.029224 and 0.052538 for prediction of speed and torque respectively.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122824458","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}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290583
Abhimanyu Roy, Akash Singh, A. Saha, Suvranil Saha, V. Gupta, Zhu Qingyi, S. Bhattacharya, Subhankar Bhattacharjee
Quantum computing is one of the emerging technologies which is an alternative for Complementary Metal Oxide Semiconductor (CMOS) based design approaches such as VLSI and ULSI. The advantage of this new domain includes substantially faster processing speed and requirement of very less area for circuit integration as compared to CMOS technology. Quantum-dot Cellular Automata (QCA) is the backbone of quantum computing for integrated circuit designing with the execution of conventional logical operations. Implementation of the reversible gate using QCA is one of the fundamental requirements to design complex logic circuits because such a reversible gate is advantageous not only in terms of power consumption and energy dissipation but also in terms of functional area requirements for the physical integration of digital circuits. There are multiple applications of reversible logic circuits in various fields such as low power CMOS, Nanotechnology, DNA computing, quantum computing, etc. This paper provides modified and efficient designs of several reversible logic gates using QCA in optimum requirements.
{"title":"A Novel Design of Reversible Gate using Quantum-Dot Cellular Automata (QCA)","authors":"Abhimanyu Roy, Akash Singh, A. Saha, Suvranil Saha, V. Gupta, Zhu Qingyi, S. Bhattacharya, Subhankar Bhattacharjee","doi":"10.1109/ICCE50343.2020.9290583","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290583","url":null,"abstract":"Quantum computing is one of the emerging technologies which is an alternative for Complementary Metal Oxide Semiconductor (CMOS) based design approaches such as VLSI and ULSI. The advantage of this new domain includes substantially faster processing speed and requirement of very less area for circuit integration as compared to CMOS technology. Quantum-dot Cellular Automata (QCA) is the backbone of quantum computing for integrated circuit designing with the execution of conventional logical operations. Implementation of the reversible gate using QCA is one of the fundamental requirements to design complex logic circuits because such a reversible gate is advantageous not only in terms of power consumption and energy dissipation but also in terms of functional area requirements for the physical integration of digital circuits. There are multiple applications of reversible logic circuits in various fields such as low power CMOS, Nanotechnology, DNA computing, quantum computing, etc. This paper provides modified and efficient designs of several reversible logic gates using QCA in optimum requirements.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121031330","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}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290631
S. Garai, Soumyadip Sharma, Biswarup Ganguly
This paper aims to propose the design and implementation of a microcontroller-based autonomous trash collection device for indoor applications in smart cities. The proposed work demonstrates the working of a prototype model: ROBOBIN along with its accessories using Atmega328p. The different ways of implementations are discussed. This model uses a combination of passive infrared (PIR) sensor, ultrasonic sensor, and optical tracker for navigation. The device is specifically designed to be installed inhospitals and food courts. Experimental results reveal that the device is cost-effective and outperforms the state- of- the- art methods.
{"title":"Design and Implementation of Trash Collection System for Smart Cities","authors":"S. Garai, Soumyadip Sharma, Biswarup Ganguly","doi":"10.1109/ICCE50343.2020.9290631","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290631","url":null,"abstract":"This paper aims to propose the design and implementation of a microcontroller-based autonomous trash collection device for indoor applications in smart cities. The proposed work demonstrates the working of a prototype model: ROBOBIN along with its accessories using Atmega328p. The different ways of implementations are discussed. This model uses a combination of passive infrared (PIR) sensor, ultrasonic sensor, and optical tracker for navigation. The device is specifically designed to be installed inhospitals and food courts. Experimental results reveal that the device is cost-effective and outperforms the state- of- the- art methods.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"535 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133389530","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}
Pub Date : 2020-09-05DOI: 10.1109/ICCE50343.2020.9290740
H. Rai, K. Chatterjee, Apita Gupta, Alok Dubey
the segmentation of brain tumor and its classification in the early stage is very important for the purpose of diagnosis and treatment. This work introduces a new deep neural network model Lu-Net with less layers, less complexity and very efficient for identifying tumors. The work involves classifying brain magnetic resonance (MR) images from a dataset of 253 images of high pixels into two categories of tumors and non-tumors. MR images are initially resized, cropped, preprocessed, and augmented for accurate and rapid training of deep convolutional neural network (CNN) models. The performance of the Lu-Net model has been evaluated using five types of statistical evaluation matrix accuracy, recall, specificity, F-score and accuracy, and its performance also compared with other two types of model Le-Net and VGG-16. CNN models were trained and evaluated on augmented dataset and tested on untrained datasets. The overall accuracy of Le-Net, VGG-16 and the proposed model is 88%, 90% and 98%, respectively, indicating the superiority of the proposed model.
{"title":"A Novel Deep CNN Model for Classification of Brain Tumor from MR Images","authors":"H. Rai, K. Chatterjee, Apita Gupta, Alok Dubey","doi":"10.1109/ICCE50343.2020.9290740","DOIUrl":"https://doi.org/10.1109/ICCE50343.2020.9290740","url":null,"abstract":"the segmentation of brain tumor and its classification in the early stage is very important for the purpose of diagnosis and treatment. This work introduces a new deep neural network model Lu-Net with less layers, less complexity and very efficient for identifying tumors. The work involves classifying brain magnetic resonance (MR) images from a dataset of 253 images of high pixels into two categories of tumors and non-tumors. MR images are initially resized, cropped, preprocessed, and augmented for accurate and rapid training of deep convolutional neural network (CNN) models. The performance of the Lu-Net model has been evaluated using five types of statistical evaluation matrix accuracy, recall, specificity, F-score and accuracy, and its performance also compared with other two types of model Le-Net and VGG-16. CNN models were trained and evaluated on augmented dataset and tested on untrained datasets. The overall accuracy of Le-Net, VGG-16 and the proposed model is 88%, 90% and 98%, respectively, indicating the superiority of the proposed model.","PeriodicalId":421963,"journal":{"name":"2020 IEEE 1st International Conference for Convergence in Engineering (ICCE)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124057478","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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