Pub Date : 2021-08-26DOI: 10.1109/SPIN52536.2021.9565944
Anamika Maurya, S. Chand
Autonomous vehicles will decrease the number of accidents on the road caused by human error. Intelligent vehicles have traditionally advanced in a step-by-step manner. These developments boost the automation scene in vehicles by incorporating systems that facilitate the driver in maintaining a constant speed, adhering to a lane, or transferring control over vehicle and driver. Autonomous vehicles must have a thorough understanding of their surroundings. As a result, object detection and road scene segmentation are critical in navigation for recognizing the drivable and non-drivable areas. Towards the development of the completely automated framework for road scene segmentation, we propose an RFB-SELinkNet that utilizes the SEResNeXt model as a feature extractor and receptive field block (RFB) with squeeze and excitation (SE) module for better feature representations. Our proposed framework outperforms D-LinkNet, Eff-UNet, and other state-of-art models. According to the experiments, the proposed model achieves 0.698 mloU and produces good segmentation outcomes on the validation set of the India Driving Lite (IDD Lite) dataset.
{"title":"Exploiting Pre-trained Encoder with Receptive Fields and Squeeze-Excitation module for Road Segmentation","authors":"Anamika Maurya, S. Chand","doi":"10.1109/SPIN52536.2021.9565944","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9565944","url":null,"abstract":"Autonomous vehicles will decrease the number of accidents on the road caused by human error. Intelligent vehicles have traditionally advanced in a step-by-step manner. These developments boost the automation scene in vehicles by incorporating systems that facilitate the driver in maintaining a constant speed, adhering to a lane, or transferring control over vehicle and driver. Autonomous vehicles must have a thorough understanding of their surroundings. As a result, object detection and road scene segmentation are critical in navigation for recognizing the drivable and non-drivable areas. Towards the development of the completely automated framework for road scene segmentation, we propose an RFB-SELinkNet that utilizes the SEResNeXt model as a feature extractor and receptive field block (RFB) with squeeze and excitation (SE) module for better feature representations. Our proposed framework outperforms D-LinkNet, Eff-UNet, and other state-of-art models. According to the experiments, the proposed model achieves 0.698 mloU and produces good segmentation outcomes on the validation set of the India Driving Lite (IDD Lite) dataset.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130536915","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9565999
A. Garg, U. Lilhore, Pinaki A. Ghosh, D. Prasad, Sarita Simaiya
During the pandemic time, most students are learning in online mode without any physical interaction with a trainer. In this pandemic time, in the absence of physical interaction with students, it became very difficult to predict the performance of students. It's important in particular to support high-risk learners and ensure hisher retention, and perhaps to provide outstanding teaching materials and experiences, and also to improve the institution's rating and brand. This research article presents a machine learning-based model for predicting students' performance in higher education. The work also looks at the possibilities of utilizing visualizations & classification techniques to find significant factors in a small number of features that are used to build a predictive model. The research study analysis revealed that SVM (support vector machine), K*, random forest, and Naive Bayes techniques effectively train limited samples and generate appropriate prediction performance based on various parameters, i.e. precision, recall, F-measure.
{"title":"Machine Learning-based Model for Prediction of Student’s Performance in Higher Education","authors":"A. Garg, U. Lilhore, Pinaki A. Ghosh, D. Prasad, Sarita Simaiya","doi":"10.1109/SPIN52536.2021.9565999","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9565999","url":null,"abstract":"During the pandemic time, most students are learning in online mode without any physical interaction with a trainer. In this pandemic time, in the absence of physical interaction with students, it became very difficult to predict the performance of students. It's important in particular to support high-risk learners and ensure hisher retention, and perhaps to provide outstanding teaching materials and experiences, and also to improve the institution's rating and brand. This research article presents a machine learning-based model for predicting students' performance in higher education. The work also looks at the possibilities of utilizing visualizations & classification techniques to find significant factors in a small number of features that are used to build a predictive model. The research study analysis revealed that SVM (support vector machine), K*, random forest, and Naive Bayes techniques effectively train limited samples and generate appropriate prediction performance based on various parameters, i.e. precision, recall, F-measure.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131162908","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9565987
Abhijit Chandra, Subhabrata Roy
Early detection of Alzheimer’s disease (AD) has drawn enough attention of researchers throughout the globe because of the lack of well-defined diagnosis of the disease. This has become one of the major threats for the elderly people in particular. This work makes a novel attempt to classify the brain MRI images into two classes viz. AD and non-AD using the volumetric information of white matter (WM), grey matter (GM) and cerebro spinal fluid (CSF). This has been accomplished with the help of three parallel support vector classifiers followed by a majority voter classifier. Performance of this proposition has been measured with the help of accuracy, sensitivity & specificity and subsequently is compared with some of the existing methods.
{"title":"On the Detection of Alzheimer’s Disease using Support Vector Machine Based Majority Voter Classifier","authors":"Abhijit Chandra, Subhabrata Roy","doi":"10.1109/SPIN52536.2021.9565987","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9565987","url":null,"abstract":"Early detection of Alzheimer’s disease (AD) has drawn enough attention of researchers throughout the globe because of the lack of well-defined diagnosis of the disease. This has become one of the major threats for the elderly people in particular. This work makes a novel attempt to classify the brain MRI images into two classes viz. AD and non-AD using the volumetric information of white matter (WM), grey matter (GM) and cerebro spinal fluid (CSF). This has been accomplished with the help of three parallel support vector classifiers followed by a majority voter classifier. Performance of this proposition has been measured with the help of accuracy, sensitivity & specificity and subsequently is compared with some of the existing methods.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132997914","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9565957
Feisal Alaswad, P. E, Hazem Issa
Arabic alphabets are used in more than 25 languages such as Arabic, Persian, Kurdish, Urdu etc. In this research work it is planned to build a computer system for recognizing handwritten Arabic words. We used sequence vector technique to recognize the Arabic words. Multi-layer Networks structure and Back-propagation Training are used as tools to decide. Also, for special cases of handling identicalness vectors, special feature extraction technique is applied. Experiments were performed by writing code in MATLAB, which achieved average accuracy of more than 92%.
{"title":"Off-Line Recognition System for Handwritten Arabic Words Using Artificial Intelligence","authors":"Feisal Alaswad, P. E, Hazem Issa","doi":"10.1109/SPIN52536.2021.9565957","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9565957","url":null,"abstract":"Arabic alphabets are used in more than 25 languages such as Arabic, Persian, Kurdish, Urdu etc. In this research work it is planned to build a computer system for recognizing handwritten Arabic words. We used sequence vector technique to recognize the Arabic words. Multi-layer Networks structure and Back-propagation Training are used as tools to decide. Also, for special cases of handling identicalness vectors, special feature extraction technique is applied. Experiments were performed by writing code in MATLAB, which achieved average accuracy of more than 92%.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133718767","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566104
Shubham Purohit, Yash Agrawal, Bakul Gohel, Vinay S. Palaparthy, R. Parekh
In recent years, advancements in medical and healthcare-based embedded systems have increased rapidly. Such systems include magnetic resonance imaging (MRI), computed tomography (CT) scanners, ultrasound imaging, digital flow sensors, electrocardiogram (ECG), an electroencephalogram (EEG) monitoring appliances. With the advancements in VLSI and e-technology, the overall chip size has reduced, and eventually, the functionality of the system has increased manifolds. In bio-medical applications, electrodes are widely incorporated to sense the electrical activity of the human body. One of the vital use of the electrodes is to sense the ECG signal of the patient’s body for monitoring the activity of the heart. For this purpose, several electrodes like dry or wet are used. In this paper, an effective capacitive electrode-based single-lead ECG system has been explored and its performance is accessed using Wilson central terminal ECG database. The proposed system has a very good correlation with the original ECG signal database. The presented capacitive-based electrode is proposed to be an optimal electrode for ECG signal detections in upcoming bio-medical applications.
{"title":"Capacitive Electrode Based Single Lead ECG Detection","authors":"Shubham Purohit, Yash Agrawal, Bakul Gohel, Vinay S. Palaparthy, R. Parekh","doi":"10.1109/SPIN52536.2021.9566104","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566104","url":null,"abstract":"In recent years, advancements in medical and healthcare-based embedded systems have increased rapidly. Such systems include magnetic resonance imaging (MRI), computed tomography (CT) scanners, ultrasound imaging, digital flow sensors, electrocardiogram (ECG), an electroencephalogram (EEG) monitoring appliances. With the advancements in VLSI and e-technology, the overall chip size has reduced, and eventually, the functionality of the system has increased manifolds. In bio-medical applications, electrodes are widely incorporated to sense the electrical activity of the human body. One of the vital use of the electrodes is to sense the ECG signal of the patient’s body for monitoring the activity of the heart. For this purpose, several electrodes like dry or wet are used. In this paper, an effective capacitive electrode-based single-lead ECG system has been explored and its performance is accessed using Wilson central terminal ECG database. The proposed system has a very good correlation with the original ECG signal database. The presented capacitive-based electrode is proposed to be an optimal electrode for ECG signal detections in upcoming bio-medical applications.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132579909","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9565989
P. Rajagopalan, Shrikant Dubey, Rajat Arora, Sanjay. D. Mehta, T. Ram
Onboard digital processors are the emerging technological developments in the arena of satellite communication for its on-board flexibility, configurability and programmability. SSPAs (Solid State Power amplifiers) are common components in the RF chain of payloads. It can be sourced by multi carriers and can be driven into saturation by any of the individual carriers. Therefore, power limiter is required per channel for controlling the input power to SSPA from digital processor. Since the processor comprise of digital subsystems the work aims at a FPGA based design and development of feed-forward configurable power limiter having 30dB dynamic range. The architecture comprises of power detector, real time input maximum detector and input signal normalizing modules. It has two modes of operation: linear power mode and limiting power mode. It can be configured with thresholds from 0 dB to -5dB in steps of 0.5dB.
{"title":"Design and Implementation of Feed Forward Configurable Digital Power Limiter for On-Board Digital Processor","authors":"P. Rajagopalan, Shrikant Dubey, Rajat Arora, Sanjay. D. Mehta, T. Ram","doi":"10.1109/SPIN52536.2021.9565989","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9565989","url":null,"abstract":"Onboard digital processors are the emerging technological developments in the arena of satellite communication for its on-board flexibility, configurability and programmability. SSPAs (Solid State Power amplifiers) are common components in the RF chain of payloads. It can be sourced by multi carriers and can be driven into saturation by any of the individual carriers. Therefore, power limiter is required per channel for controlling the input power to SSPA from digital processor. Since the processor comprise of digital subsystems the work aims at a FPGA based design and development of feed-forward configurable power limiter having 30dB dynamic range. The architecture comprises of power detector, real time input maximum detector and input signal normalizing modules. It has two modes of operation: linear power mode and limiting power mode. It can be configured with thresholds from 0 dB to -5dB in steps of 0.5dB.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133092793","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566091
V. Khandelwal, V. Bhatia, V. Dogra, S. Sharma, V. Chhabra, R. Singh, D. Kumar, T. K. Bera
In construction industry, the conventional way of construction of buildings is a costly, time consuming and a labour-intensive job. Besides that, many on-site fatalities happen during the construction activity and the climate can delay construction activity. 3-D printer robot resolves all these problems. Also, it can be used for intricate building designs and for construction of buildings in remote locations or in epidemic situations. The objective of the project is to make an autonomous robot for 3-D printing a simple civil structure. Three lead screws will provide the movement in the vertical as well as in horizontal directions and a nozzle connected to the horizontal lead screw will be used for pouring the construction-material layer by layer. Thereafter, structural analysis using Finite Element Method (FEM) has been done on critical parts like lead screw and top plate. Bond graphs for buggy and overall lead screw system have also been used to analyze the response of the system. Furthermore, the wring diagram is also developed and presented in the paper. Future research is required for the development of actual robot for building multi-storied structures, on the design of nozzle and type of material used for pouring.
{"title":"3-D Printer Robot for Civil Construction: A Bond Graph Approach","authors":"V. Khandelwal, V. Bhatia, V. Dogra, S. Sharma, V. Chhabra, R. Singh, D. Kumar, T. K. Bera","doi":"10.1109/SPIN52536.2021.9566091","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566091","url":null,"abstract":"In construction industry, the conventional way of construction of buildings is a costly, time consuming and a labour-intensive job. Besides that, many on-site fatalities happen during the construction activity and the climate can delay construction activity. 3-D printer robot resolves all these problems. Also, it can be used for intricate building designs and for construction of buildings in remote locations or in epidemic situations. The objective of the project is to make an autonomous robot for 3-D printing a simple civil structure. Three lead screws will provide the movement in the vertical as well as in horizontal directions and a nozzle connected to the horizontal lead screw will be used for pouring the construction-material layer by layer. Thereafter, structural analysis using Finite Element Method (FEM) has been done on critical parts like lead screw and top plate. Bond graphs for buggy and overall lead screw system have also been used to analyze the response of the system. Furthermore, the wring diagram is also developed and presented in the paper. Future research is required for the development of actual robot for building multi-storied structures, on the design of nozzle and type of material used for pouring.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130040289","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566023
Shubhamshree Avishek, S. Samantaray
Invasive thermal therapies have proved their significance as a better substitute to eradicate tumors of various types especially patients with surgical intolerance. The primacy of operating Microwave Ablation (MWA) over other thermal therapies is due to the prospect of the treatment of >3cm dia tumors which is a major setback in the RFA. Therefore, MWA is favored as a better thermal therapy for treating lung, breast, liver, and kidney comparable to other treatment techniques. In this respect, the current study is made to inspect the factors like Applied Power & Frequency on the dimension of the Ablation zone achieved post Microwave Thermal Ablation. The numerical approach with the Finite Element Method-based analysis has been accounted for to obtain the impact of input factors on the size of the Ablation Zone. For this study Lungs has been considered and results are simulated for the ablation zone impacted by power and frequency. It has been observed that as the Power Applied and Frequency are increased, the Dimension of the Ablation Zone grows eventually. Both the input factors have a positive impact on the response proving the possibility of treating larger tumors with correct input settings. The results derived from the entire study would be highly useful for the radiologist and other medical departments to gain a good understanding of the role of input factors while providing initial information in the pre-treatment stage.
{"title":"Effect of Power and Frequency on Microwave Ablation on Lungs","authors":"Shubhamshree Avishek, S. Samantaray","doi":"10.1109/SPIN52536.2021.9566023","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566023","url":null,"abstract":"Invasive thermal therapies have proved their significance as a better substitute to eradicate tumors of various types especially patients with surgical intolerance. The primacy of operating Microwave Ablation (MWA) over other thermal therapies is due to the prospect of the treatment of >3cm dia tumors which is a major setback in the RFA. Therefore, MWA is favored as a better thermal therapy for treating lung, breast, liver, and kidney comparable to other treatment techniques. In this respect, the current study is made to inspect the factors like Applied Power & Frequency on the dimension of the Ablation zone achieved post Microwave Thermal Ablation. The numerical approach with the Finite Element Method-based analysis has been accounted for to obtain the impact of input factors on the size of the Ablation Zone. For this study Lungs has been considered and results are simulated for the ablation zone impacted by power and frequency. It has been observed that as the Power Applied and Frequency are increased, the Dimension of the Ablation Zone grows eventually. Both the input factors have a positive impact on the response proving the possibility of treating larger tumors with correct input settings. The results derived from the entire study would be highly useful for the radiologist and other medical departments to gain a good understanding of the role of input factors while providing initial information in the pre-treatment stage.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115171660","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566068
D. Tripathi, Subodh Wairya
In comparison to CMOS technique, quantum-dot cellular automata (QCA) is a cutting-edge computation approach that recommends reduced dimension and fast speed. Furthermore, the Full Adder is a fundamental unit in many important circuits such as ALUs, Processors, and so on. An efficient QCA 1-bit Full Adder (FA) topology is planned in this article, and we offer an energy and cost competent 4-bit Ripple Carry Adder architecture employing this suggested optimal full adder topology. The projected QCA layout is modest in architecture and strong in standings of executing digital circuits. Energy and cost proficient design of the suggested adder can lead to the efficient design of any digital system architecture. We planned an energy and cost efficient 4-bit RCA by employing the projected efficient full adder. In order to construct 4-bit QCA RCA, the triplet design technique was used. Those structures are simple in design and take up a little portion of the land, similar to prior designs. The projected efficient 1-bit Full adder topology consists only 11 and 16 QCA cells and having 0.013 μm2 and 0.011μm2 area. A 4-bit RCA topology contains 53 and 49 QCA cells and triplet approach 4-bit RCA design of containing 59 QCA cells, which is the smallest among all past designs. The simulation results demonstrate that the suggested digital design and architecture have achieved significant improvements in circuit complexity positions. The proposed architecture of 4 bit RCA involves just around 39% less area as equated with the previously existing designs. The functionality of projected structures estimated in the QCADesigner simulation environment.
{"title":"An Energy Dissipation and Cost Optimization of QCA Ripple Carry Adder","authors":"D. Tripathi, Subodh Wairya","doi":"10.1109/SPIN52536.2021.9566068","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566068","url":null,"abstract":"In comparison to CMOS technique, quantum-dot cellular automata (QCA) is a cutting-edge computation approach that recommends reduced dimension and fast speed. Furthermore, the Full Adder is a fundamental unit in many important circuits such as ALUs, Processors, and so on. An efficient QCA 1-bit Full Adder (FA) topology is planned in this article, and we offer an energy and cost competent 4-bit Ripple Carry Adder architecture employing this suggested optimal full adder topology. The projected QCA layout is modest in architecture and strong in standings of executing digital circuits. Energy and cost proficient design of the suggested adder can lead to the efficient design of any digital system architecture. We planned an energy and cost efficient 4-bit RCA by employing the projected efficient full adder. In order to construct 4-bit QCA RCA, the triplet design technique was used. Those structures are simple in design and take up a little portion of the land, similar to prior designs. The projected efficient 1-bit Full adder topology consists only 11 and 16 QCA cells and having 0.013 μm2 and 0.011μm2 area. A 4-bit RCA topology contains 53 and 49 QCA cells and triplet approach 4-bit RCA design of containing 59 QCA cells, which is the smallest among all past designs. The simulation results demonstrate that the suggested digital design and architecture have achieved significant improvements in circuit complexity positions. The proposed architecture of 4 bit RCA involves just around 39% less area as equated with the previously existing designs. The functionality of projected structures estimated in the QCADesigner simulation environment.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"444 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116392269","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 : 2021-08-26DOI: 10.1109/SPIN52536.2021.9566057
Sapna Arora, Ruchi Kawatra, Manisha Agarwal
Teaching Job Performance is one of the salient and sensitive issues when it is associated with the recruitment and deployment of faculty for Higher Education Institutions. Recruiting effective faculty contributes to the growth and enhancement in the quality of education. Considering this, the study unveils the importance of four cardinal factors on a real dataset sample of 520 faculty, from different departments of Indian Institutes. Cardinal factors such as Faculty’s Experience, National Eligibility Test, Student Feedback, and Faculty’s Highest Qualification are taken into consideration. The classifiers used to strengthen research are Logistic Regression, Support Vector Machine, K-Nearest Neighbors, and Decision Tree. The results prove that the correlation between Faculty’s Experience, Faculty’s Highest Qualification with Student Feedback is the best way to analyze a Faculty's Teaching Performance. Analyzing and predicting the importance of four cardinal parameters will help educational institutions, regulatory and accreditation bodies improve education quality.
{"title":"An Empirical Study - The Cardinal Factors towards Recruitment of Faculty in Higher Educational Institutions using Machine Learning","authors":"Sapna Arora, Ruchi Kawatra, Manisha Agarwal","doi":"10.1109/SPIN52536.2021.9566057","DOIUrl":"https://doi.org/10.1109/SPIN52536.2021.9566057","url":null,"abstract":"Teaching Job Performance is one of the salient and sensitive issues when it is associated with the recruitment and deployment of faculty for Higher Education Institutions. Recruiting effective faculty contributes to the growth and enhancement in the quality of education. Considering this, the study unveils the importance of four cardinal factors on a real dataset sample of 520 faculty, from different departments of Indian Institutes. Cardinal factors such as Faculty’s Experience, National Eligibility Test, Student Feedback, and Faculty’s Highest Qualification are taken into consideration. The classifiers used to strengthen research are Logistic Regression, Support Vector Machine, K-Nearest Neighbors, and Decision Tree. The results prove that the correlation between Faculty’s Experience, Faculty’s Highest Qualification with Student Feedback is the best way to analyze a Faculty's Teaching Performance. Analyzing and predicting the importance of four cardinal parameters will help educational institutions, regulatory and accreditation bodies improve education quality.","PeriodicalId":343177,"journal":{"name":"2021 8th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133103497","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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