In the study of stock investment in capital market by investors in Pandemic Covid-19, it is always carried out rationally. Indeed, the decisions on stock investments are not always rational.The main purpose of this research is to analyze the behavioral factors that affect the preferences of individual’s investors and fund managers in the emerging stock market, Pakistan Stock Exchange. The data of this research were collected through interviews semi structured with the five investor and five fund managers from the stock exchange from Pakistan. The researchers used thematic analysis for data interpretation. The major findings stress that retail investors are more effected by behavioral biases in comparison with fund managers. Further, the results shows that there are some major biases which are effecting both type of investors such as: Herding, Market, Prospect, Overconfidence- gambling errors and Anchoring-ability bias. This study fills a gap in literature on investor psychological response during pandemic epidemic. According to the report, policymakers should devise a strategy to combat COVID-19. To avoid future catastrophes, government should control the health-care budget.
{"title":"ASSESSMENT OF INDIVIDUAL AND INSTITUTIONAL INVESTOR’S INVESTMENT BEHAVIOR DURING COVID-19. A CASE OF EMERGING ECONOMY","authors":"Sybert Mutereko, A. Hussain, A. Sohail","doi":"10.51380/gujr-37-03-02","DOIUrl":"https://doi.org/10.51380/gujr-37-03-02","url":null,"abstract":"In the study of stock investment in capital market by investors in Pandemic Covid-19, it is always carried out rationally. Indeed, the decisions on stock investments are not always rational.The main purpose of this research is to analyze the behavioral factors that affect the preferences of individual’s investors and fund managers in the emerging stock market, Pakistan Stock Exchange. The data of this research were collected through interviews semi structured with the five investor and five fund managers from the stock exchange from Pakistan. The researchers used thematic analysis for data interpretation. The major findings stress that retail investors are more effected by behavioral biases in comparison with fund managers. Further, the results shows that there are some major biases which are effecting both type of investors such as: Herding, Market, Prospect, Overconfidence- gambling errors and Anchoring-ability bias. This study fills a gap in literature on investor psychological response during pandemic epidemic. According to the report, policymakers should devise a strategy to combat COVID-19. To avoid future catastrophes, government should control the health-care budget.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"32 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82273909","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}
Several factors influence the employee's personality including psycho-social factors. Previously studies have conducted to investigate the influence of Big-5 traits which impact employee’s performance. This study investigated the influence of Big-5 on the employee’s performance. The study used a cross-sectional survey a 5-point Likert scale was distributed among 163 samples selected randomly. The findings report a significant relationship between the predictors and a criterion variable. The study points those two predictors i.e., openness to experience and emotional control predict 57% variance in criterion variable as compared to the extravert, agreeableness, and conscientiousness. This study concludes that teacher’s centric policies & mechanisms enhance employee trust and confidence and it overcomes the apprehensions, as result, they perform better and contribute more towards the promotion of education and research in higher educational institutions.
{"title":"DO BIG-5 PERSONALITY TRAITS CONTRIBUTE TO EMPLOYEES PERFORMANCE? AN EMPIRICAL EVIDENCE FROM HEIs IN PAKISTAN","authors":"Robina Akhtar, Mohamad Nizam Nazarudin, G. Kundi","doi":"10.51380/gujr-37-03-01","DOIUrl":"https://doi.org/10.51380/gujr-37-03-01","url":null,"abstract":"Several factors influence the employee's personality including psycho-social factors. Previously studies have conducted to investigate the influence of Big-5 traits which impact employee’s performance. This study investigated the influence of Big-5 on the employee’s performance. The study used a cross-sectional survey a 5-point Likert scale was distributed among 163 samples selected randomly. The findings report a significant relationship between the predictors and a criterion variable. The study points those two predictors i.e., openness to experience and emotional control predict 57% variance in criterion variable as compared to the extravert, agreeableness, and conscientiousness. This study concludes that teacher’s centric policies & mechanisms enhance employee trust and confidence and it overcomes the apprehensions, as result, they perform better and contribute more towards the promotion of education and research in higher educational institutions.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90872670","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 study analyses how the Information & Communication Technology sector of managers having light triad traits (altruism, empathy, compassion) associates employee innovative performance through creative self-efficacy, Self-Resilience, and psychological empowerment. This study used pro social trait theory for Light triad traits of managers and employees' perspectives to broaden and build an approach. This study hypothesized a relationship amid Light triad traits, creative self-efficacy, self-resilience and psychological empowerment, which affects the innovative performance of employee. Light triad traits have most substantial positive relationship with innovative performance when employees have high levels of the self-resilience and creative self-efficacy. The psychological empowerment mediates relationship between the Light triad traits and innovative employee performance. Data was collected in total from 650 employees, 500 employees (followers) in which they rated their managers (leaders) and after 1 week, 150 managers (leaders) rated their employee's performance and generated results to support our study hypotheses.
{"title":"THE LIGHT TRIAD TRAITS, PSYCHOLOGICAL EMPOWERMENT, CREATIVE SELF-EFFICACY, SELF-RESILIENCE AND INNOVATIVE PERFORMANCE IN ICT OF PAKISTAN","authors":"I. Khan, Umar Safdar, Zohair Durrani","doi":"10.51380/gujr-37-03-05","DOIUrl":"https://doi.org/10.51380/gujr-37-03-05","url":null,"abstract":"This study analyses how the Information & Communication Technology sector of managers having light triad traits (altruism, empathy, compassion) associates employee innovative performance through creative self-efficacy, Self-Resilience, and psychological empowerment. This study used pro social trait theory for Light triad traits of managers and employees' perspectives to broaden and build an approach. This study hypothesized a relationship amid Light triad traits, creative self-efficacy, self-resilience and psychological empowerment, which affects the innovative performance of employee. Light triad traits have most substantial positive relationship with innovative performance when employees have high levels of the self-resilience and creative self-efficacy. The psychological empowerment mediates relationship between the Light triad traits and innovative employee performance. Data was collected in total from 650 employees, 500 employees (followers) in which they rated their managers (leaders) and after 1 week, 150 managers (leaders) rated their employee's performance and generated results to support our study hypotheses.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"18 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72774628","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 : 2021-09-20DOI: 10.36548/jscp.2021.3.006
H. Andi
In recent years, there has been an increase in demand for machine learning and AI-assisted trading. To extract abnormal profits from the bitcoin market, the machine learning and artificial intelligence (AI) assisted trading process has been used. Each day, the data gets saved for the specified amount of time. These approaches produce great results when integrated with cutting-edge algorithms. The results of algorithms and architectural structures drive the development of cryptocurrency market. The unprecedented increase in market capitalization has enabled the cryptocurrency to flourish in 2017. Currently, the market accommodates totally 1500 cryptocurrencies, all of which are actively trading. It is always possible to mine the cryptocurrency and use it to pay for online purchases. The proposed research study is more focused on leveraging the accurate forecast of bitcoin prices via the normalization of a particular dataset. With the use of LSTM machine learning, this dataset has been trained to deploy a more accurate forecast of the bitcoin price. Furthermore, this research work has evaluated different machine learning methods and found that the suggested work delivers better results. Based on the resultant findings, the accuracy, recall, precision, and sensitivity of the test has been calculated.
{"title":"An Accurate Bitcoin Price Prediction using logistic regression with LSTM Machine Learning model","authors":"H. Andi","doi":"10.36548/jscp.2021.3.006","DOIUrl":"https://doi.org/10.36548/jscp.2021.3.006","url":null,"abstract":"In recent years, there has been an increase in demand for machine learning and AI-assisted trading. To extract abnormal profits from the bitcoin market, the machine learning and artificial intelligence (AI) assisted trading process has been used. Each day, the data gets saved for the specified amount of time. These approaches produce great results when integrated with cutting-edge algorithms. The results of algorithms and architectural structures drive the development of cryptocurrency market. The unprecedented increase in market capitalization has enabled the cryptocurrency to flourish in 2017. Currently, the market accommodates totally 1500 cryptocurrencies, all of which are actively trading. It is always possible to mine the cryptocurrency and use it to pay for online purchases. The proposed research study is more focused on leveraging the accurate forecast of bitcoin prices via the normalization of a particular dataset. With the use of LSTM machine learning, this dataset has been trained to deploy a more accurate forecast of the bitcoin price. Furthermore, this research work has evaluated different machine learning methods and found that the suggested work delivers better results. Based on the resultant findings, the accuracy, recall, precision, and sensitivity of the test has been calculated.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"53 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76336072","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 major premise of this research was to get the perception of university teachers about the process of teacher evaluation in one private university in Lahore. Focusing on the actual practices of teacher evaluation process (TEP), this paper attempts to get opinion of university teachers regarding the effectiveness of TEP. This research was quantitative in its nature in which a survey questionnaire was used to collect data. The population of the study included all the faculty members (both male and female) of the private sector university in Lahore. 150 faculty members were selected through simple random sampling from all faculties/departments of the sampled university. The data was analyzed on SPSS 21. Results were drawn from the interpretation of quantitative data. Results indicated that university teachers had very positive perceptions of the teacher evaluation process. The process of the teacher evaluation contributes to teachers teaching performance a lot.
{"title":"TEACHERS PERCEPTION ABOUT PROCESS OF TEACHER EVALUATION: A CASE STUDY OF A PRIVATE UNIVERSITY OF LAHORE","authors":"Shahid Rafiq, Shahzada Qaisar","doi":"10.51380/gujr-37-03-09","DOIUrl":"https://doi.org/10.51380/gujr-37-03-09","url":null,"abstract":"The major premise of this research was to get the perception of university teachers about the process of teacher evaluation in one private university in Lahore. Focusing on the actual practices of teacher evaluation process (TEP), this paper attempts to get opinion of university teachers regarding the effectiveness of TEP. This research was quantitative in its nature in which a survey questionnaire was used to collect data. The population of the study included all the faculty members (both male and female) of the private sector university in Lahore. 150 faculty members were selected through simple random sampling from all faculties/departments of the sampled university. The data was analyzed on SPSS 21. Results were drawn from the interpretation of quantitative data. Results indicated that university teachers had very positive perceptions of the teacher evaluation process. The process of the teacher evaluation contributes to teachers teaching performance a lot.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"6 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82535571","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 : 2021-09-20DOI: 10.36548/jtcsst.2021.3.001
J. Chen, Kong-Long Lai
Stochastic Geometry has attained massive growth in modelling and analysing of wireless network. This suits well for analysing the performance of large scale wireless network with random topologies. Analytical framework is established to evaluate the performance of the network. Here we have created a mathematical model for uplink analysis and the gain of uplink and downlink is obtained. Then ad-hoc network architecture is designed and the performance of the network is compared with the traditional method. Finally, a new scheduling algorithm is developed for cellular network and the gain parameter is quantified with the help of Stochastic Geometry tool. The accuracy is acquired from extensive Monte Carlo simulator.
{"title":"Stochastic Geometry and Performance Analysis of Large Scale Wireless Networks","authors":"J. Chen, Kong-Long Lai","doi":"10.36548/jtcsst.2021.3.001","DOIUrl":"https://doi.org/10.36548/jtcsst.2021.3.001","url":null,"abstract":"Stochastic Geometry has attained massive growth in modelling and analysing of wireless network. This suits well for analysing the performance of large scale wireless network with random topologies. Analytical framework is established to evaluate the performance of the network. Here we have created a mathematical model for uplink analysis and the gain of uplink and downlink is obtained. Then ad-hoc network architecture is designed and the performance of the network is compared with the traditional method. Finally, a new scheduling algorithm is developed for cellular network and the gain parameter is quantified with the help of Stochastic Geometry tool. The accuracy is acquired from extensive Monte Carlo simulator.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"2019 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73493861","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 purpose of the study is to investigate the role of stress upon academic performance of students. Stress is faced by each individual in academic, professional as well as daily routine life. The current study has identified different sources of stress which might be controlled to enhance academic performance of students. For this purpose cross-sectional design survey approach was conducted from two different universities from the different faculties. The development of scientific knowledge in current study is based on the positivism philosophy. The non probability convenience sampling technique was used. Population of the study was students from public and private universities. 210 students have participated in the study. Cronbach alpha, correlation and regression were used for analysis of data. SPSS 25 was used. Findings of study revealed that scale adopted from past studies was found reliable and there is significant positive relationship between factors of stress and academic performance of students. It was also found that academic factors were most dominant factors which played significant role in affecting students’ performance. This study is original contribution and has extended the body of knowledge of stress and student academic performance.
{"title":"AN INVESTIGATION ON ROLE OF STRESS ON ACADEMIC PERFORMANCE OF STUDENTS","authors":"Y. H. Mughal","doi":"10.51380/gujr-37-03-04","DOIUrl":"https://doi.org/10.51380/gujr-37-03-04","url":null,"abstract":"The purpose of the study is to investigate the role of stress upon academic performance of students. Stress is faced by each individual in academic, professional as well as daily routine life. The current study has identified different sources of stress which might be controlled to enhance academic performance of students. For this purpose cross-sectional design survey approach was conducted from two different universities from the different faculties. The development of scientific knowledge in current study is based on the positivism philosophy. The non probability convenience sampling technique was used. Population of the study was students from public and private universities. 210 students have participated in the study. Cronbach alpha, correlation and regression were used for analysis of data. SPSS 25 was used. Findings of study revealed that scale adopted from past studies was found reliable and there is significant positive relationship between factors of stress and academic performance of students. It was also found that academic factors were most dominant factors which played significant role in affecting students’ performance. This study is original contribution and has extended the body of knowledge of stress and student academic performance.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77175019","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}
Education is considered critical for both showing positive behaviour and regulating negative social behaviour and affecting the social attitudes by improving one's ability to perceive others. Hence, this research examined the push and pull factors of Negative Social Behaviour among secondary school students. In this research, we collect data over two self-developed questionnaires. Thus, total 500 students (252 female, 248 male) and 120 teachers (60 male, 60 female) from 04 districts of Punjab were selected conveniently. The EFA revealed 06 dimensions possibly be extracted from two questionnaires designed for the students and teachers separately. Multilevel analyses mean SD, Pearson correlation, and independent-sample t-test were performed. Findings reveal that parents’ conflicts, peer’ bullying, teachers’ insulting behaviours and students’ sarcastic attitude are the major push factors that cause de-motivation and promote NSB among students. These factors severely influence students’ personality, and as a result, students lost study interest, behave roughly and violate the institutions’ rules.
{"title":"PUSH AND PULL FACTORS OF NEGATIVE SOCIAL BEHAVIOURS AMONG SECONDARY SCHOOL STUDENTS","authors":"Syed Zubair Haider, Uzma Munawar, Shaista Noreen","doi":"10.51380/gujr-37-03-06","DOIUrl":"https://doi.org/10.51380/gujr-37-03-06","url":null,"abstract":"Education is considered critical for both showing positive behaviour and regulating negative social behaviour and affecting the social attitudes by improving one's ability to perceive others. Hence, this research examined the push and pull factors of Negative Social Behaviour among secondary school students. In this research, we collect data over two self-developed questionnaires. Thus, total 500 students (252 female, 248 male) and 120 teachers (60 male, 60 female) from 04 districts of Punjab were selected conveniently. The EFA revealed 06 dimensions possibly be extracted from two questionnaires designed for the students and teachers separately. Multilevel analyses mean SD, Pearson correlation, and independent-sample t-test were performed. Findings reveal that parents’ conflicts, peer’ bullying, teachers’ insulting behaviours and students’ sarcastic attitude are the major push factors that cause de-motivation and promote NSB among students. These factors severely influence students’ personality, and as a result, students lost study interest, behave roughly and violate the institutions’ rules.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"60 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84547457","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}
With the COVID-19 pandemic gripping world, there has been an alarming increase in role of conspiracy theories generated surrounding COVID-19. Thus, this research aims to understand what conspiracy beliefs Pakistani Muslims may possess about COVID-19. The research followed correlational research design. The data was collected through an online self-reported COVID-19 Conspiracies Belief Questionnaire from 110 Pakistani Muslims with a mean age of 25.40 and SD of 5.73. Descriptive statistics explained that 59%, 60%, 79% of the participants agree with the conspiracy that it accidentally escaped from the Chinese lab, planted by the American Army in China to destroy China's economy, and it is a punishment from Allah for human sins respectively. Chi-square analysis revealed that females believe more in conspiracies as compare to male research participants. Moreover, binary logistic regression explained that COVID-19 is a way to control the world by developing psychological fear. The findings may enable local and national governing bodies to develop the knowledge-based strategies to tackle conspiracy beliefs.
{"title":"AN INVESTIGATION ON COVID-19 CONSPIRACY THEORY BELIEFS AMONGST PAKISTANI MUSLIMS","authors":"Mujeeba Ashraf","doi":"10.51380/gujr-37-03-10","DOIUrl":"https://doi.org/10.51380/gujr-37-03-10","url":null,"abstract":"With the COVID-19 pandemic gripping world, there has been an alarming increase in role of conspiracy theories generated surrounding COVID-19. Thus, this research aims to understand what conspiracy beliefs Pakistani Muslims may possess about COVID-19. The research followed correlational research design. The data was collected through an online self-reported COVID-19 Conspiracies Belief Questionnaire from 110 Pakistani Muslims with a mean age of 25.40 and SD of 5.73. Descriptive statistics explained that 59%, 60%, 79% of the participants agree with the conspiracy that it accidentally escaped from the Chinese lab, planted by the American Army in China to destroy China's economy, and it is a punishment from Allah for human sins respectively. Chi-square analysis revealed that females believe more in conspiracies as compare to male research participants. Moreover, binary logistic regression explained that COVID-19 is a way to control the world by developing psychological fear. The findings may enable local and national governing bodies to develop the knowledge-based strategies to tackle conspiracy beliefs.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87130853","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 : 2021-09-20DOI: 10.36548/jiip.2021.3.008
R. Kanthavel
To solve the challenges in traffic object identification, fuzzification, and simplification in a real traffic environment, it is highly required to develop an automatic detection and classification technique for roads, automobiles, and pedestrians with multiple traffic objects inside the same framework. The proposed method has been evaluated on a database with complicated poses, motions, backgrounds, and lighting conditions for an urban scenario where pedestrians are not obstructed. The suggested CNN classifier has an FPR of less than that of the SVM classifier. Confirming the significance of automatically optimized features, the SVM classifier's accuracy is equal to that of the CNN. The proposed framework is integrated with the additional adaptive segmentation method to identify pedestrians more precisely than the conventional techniques. Additionally, the proposed lightweight feature mapping leads to faster calculation times and it has also been verified and tabulated in the results and discussion section.
{"title":"Construction of LWCNN Framework and its Application to Pedestrian Detection with Segmentation Process","authors":"R. Kanthavel","doi":"10.36548/jiip.2021.3.008","DOIUrl":"https://doi.org/10.36548/jiip.2021.3.008","url":null,"abstract":"To solve the challenges in traffic object identification, fuzzification, and simplification in a real traffic environment, it is highly required to develop an automatic detection and classification technique for roads, automobiles, and pedestrians with multiple traffic objects inside the same framework. The proposed method has been evaluated on a database with complicated poses, motions, backgrounds, and lighting conditions for an urban scenario where pedestrians are not obstructed. The suggested CNN classifier has an FPR of less than that of the SVM classifier. Confirming the significance of automatically optimized features, the SVM classifier's accuracy is equal to that of the CNN. The proposed framework is integrated with the additional adaptive segmentation method to identify pedestrians more precisely than the conventional techniques. Additionally, the proposed lightweight feature mapping leads to faster calculation times and it has also been verified and tabulated in the results and discussion section.","PeriodicalId":10896,"journal":{"name":"Day 1 Tue, September 21, 2021","volume":"12 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82623040","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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