Abstract: With the growing interest in academics and industry towards research and the availability of large number of publishers, the frequency of publications is also on the rise. It is found that researchers are very careful about the selection of the related periodicals and the proceedings with good research index and well-known publishers. In this direction, this research performed a quantitative analysis of the publication by various authors in leading journals. We identified their interests/ selection of the periodicals for their research publication. For this purpose, a scrapping tool was developed, and data was scrapped for scientific publications published in [...]

Abstract: This study applies k-means and mini-batch clustering dataset for customer segmentation. Based on the analysis, various clusters were formed and validated. It was found that the results of both clustering techniques are same with an enhancement in processing speed via the use of mini-batch k-means. Customer segmentation can be used for market intelligence to identify interested clients by giving corporate entities in the retail sector pertinent and relevant facts periodically. It can be used as methods for examining customer purchase patterns and sales trends. The clustering has been applied over a dataset extracted from Kaggle. After performing the exploratory [...]

Abstract: Data duplication is one of the core issues in data warehouses pertaining to the quality of data. By finding and removing duplicate data, you can decrease the amount of space needed to store your data. For smooth, efficient, and fast analysis the duplicated data needs to be filtered out before using it for further process. However, very few research has been done on data deduplication for textual data. Realizing this gap, this paper presents analysis of bloom filters to detect duplicates in textual data. The paper discusses the challenges and the need for textual data deduplication. Existing literature on [...]

The effects of COVID’19 have been witnessed by every individual, and it has impacted everyone in a different way. Due to the pandemic, work from home (WFH) has become a policy priority for most organizations. We expect that the people will seem to be satisfied with their job while working from home, because of certain factors like productivity, motivation, reduces in expense, work family-life balance. And to understand the effect of social, behavioral, and physical factors on the well-being of office workstation users during COVID19 work from home (WFH), we conducted an online survey to capture the experience of people, [...]

This qualitative study investigates the relationship between cyberbullying and social withdrawal in 12–20 years teenage population. The study reviews survey data collected from students at different frequencies from own educational institutions to analyze the extent of cyberbullying, its emotional effects and leading to the behavioral changes. The results show a notable correlation between cyberbullying and social withdrawal; a large number of the surveyed teenagers reported experiencing anxiety, trust issues, and indivisibility: the preference to chat with each other online instead of meeting in person. The findings highlight the importance of systemic change and networking support in facing this growing issue. [...]

The usage of social networks is rising in the past few years. Most of the frequently used information is widely shared via social media networks including Facebook, Twitter, Instagram etc. Via these platforms, people can show their feelings, expressions, emotions, and opinions. These platforms provide meaningful content about users and their personality traits. Such information can be exploited to analyze the personality of the end-users. In this research, we explored a novel technique for personality modelling using Big 5 traits. We propose a comprehensive framework and machine learning pipeline that can be adopted for personality prediction. In order to solve [...]

Abstract: With the growing interest in academics and industry towards research and the availability of large number of publishers, the frequency of publications is also on the rise. It is found that researchers are very careful about the selection of the related periodicals and the proceedings with good research index and well-known publishers. In this direction, this research performed a quantitative analysis of the publication by various authors in leading journals. We identified their interests/ selection of the periodicals for their research publication. For this purpose, a scrapping tool was developed, and data was scrapped for scientific publications published in [...]

Abstract: This study applies k-means and mini-batch clustering dataset for customer segmentation. Based on the analysis, various clusters were formed and validated. It was found that the results of both clustering techniques are same with an enhancement in processing speed via the use of mini-batch k-means. Customer segmentation can be used for market intelligence to identify interested clients by giving corporate entities in the retail sector pertinent and relevant facts periodically. It can be used as methods for examining customer purchase patterns and sales trends. The clustering has been applied over a dataset extracted from Kaggle. After performing the exploratory [...]

Abstract: Data duplication is one of the core issues in data warehouses pertaining to the quality of data. By finding and removing duplicate data, you can decrease the amount of space needed to store your data. For smooth, efficient, and fast analysis the duplicated data needs to be filtered out before using it for further process. However, very few research has been done on data deduplication for textual data. Realizing this gap, this paper presents analysis of bloom filters to detect duplicates in textual data. The paper discusses the challenges and the need for textual data deduplication. Existing literature on [...]

The effects of COVID’19 have been witnessed by every individual, and it has impacted everyone in a different way. Due to the pandemic, work from home (WFH) has become a policy priority for most organizations. We expect that the people will seem to be satisfied with their job while working from home, because of certain factors like productivity, motivation, reduces in expense, work family-life balance. And to understand the effect of social, behavioral, and physical factors on the well-being of office workstation users during COVID19 work from home (WFH), we conducted an online survey to capture the experience of people, [...]

This qualitative study investigates the relationship between cyberbullying and social withdrawal in 12–20 years teenage population. The study reviews survey data collected from students at different frequencies from own educational institutions to analyze the extent of cyberbullying, its emotional effects and leading to the behavioral changes. The results show a notable correlation between cyberbullying and social withdrawal; a large number of the surveyed teenagers reported experiencing anxiety, trust issues, and indivisibility: the preference to chat with each other online instead of meeting in person. The findings highlight the importance of systemic change and networking support in facing this growing issue. [...]

The usage of social networks is rising in the past few years. Most of the frequently used information is widely shared via social media networks including Facebook, Twitter, Instagram etc. Via these platforms, people can show their feelings, expressions, emotions, and opinions. These platforms provide meaningful content about users and their personality traits. Such information can be exploited to analyze the personality of the end-users. In this research, we explored a novel technique for personality modelling using Big 5 traits. We propose a comprehensive framework and machine learning pipeline that can be adopted for personality prediction. In order to solve [...]

This qualitative study investigates the relationship between cyberbullying and social withdrawal in 12–20 years teenage population. The study reviews survey data collected from students at different frequencies from own educational institutions to analyze the extent of cyberbullying, its emotional effects and leading to the behavioral changes. The results show a notable correlation between cyberbullying and social withdrawal; a large number of the surveyed teenagers reported experiencing anxiety, trust issues, and indivisibility: the preference to chat with each other online instead of meeting in person. The findings highlight the importance of systemic change and networking support in facing this growing issue. [...]

During the past few years, cybersecurity has gained a lot of prominence. In this paper, phishing attacks are discussed in detail. In a phishing attack, an attacker disguises itself as a genuine user and deceives the end-user to gains its personal information such as credit card, usernames/ passwords etc. There are a number of ways to perform phishing attacks such as via email, spear phishing, clone phishing, whaling etc. This paper talks about phishing attacks in detail along with its techniques, counter-measures and recent trends directions for research. Phishing is a significant threat to every individual, organization, and in general [...]

Abstract: With the growing interest in academics and industry towards research and the availability of large number of publishers, the frequency of publications is also on the rise. It is found that researchers are very careful about the selection of the related periodicals and the proceedings with good research index and well-known publishers. In this direction, this research performed a quantitative analysis of the publication by various authors in leading journals. We identified their interests/ selection of the periodicals for their research publication. For this purpose, a scrapping tool was developed, and data was scrapped for scientific publications published in [...]

Cloud computing is the transformation of IT infrastructure into a utility which allows the users to plug-in infrastructure over the internet, and utilizes the computing resources without their installation and maintenance on-premises. It is time-consuming and a headache to manage resources on your own. Cloud computing provides shared and dedicated resources to facilitate large scale tasks or time-consuming tasks. To get the full benefit from cloud computing we need algorithms to allocate resources according to client needs and algorithms for fast access to the cloud servers. Here comes load balancing. Load balancing is a technique to distribute load among various [...]

The usage of social networks is rising in the past few years. Most of the frequently used information is widely shared via social media networks including Facebook, Twitter, Instagram etc. Via these platforms, people can show their feelings, expressions, emotions, and opinions. These platforms provide meaningful content about users and their personality traits. Such information can be exploited to analyze the personality of the end-users. In this research, we explored a novel technique for personality modelling using Big 5 traits. We propose a comprehensive framework and machine learning pipeline that can be adopted for personality prediction. In order to solve [...]

Abstract: This study applies k-means and mini-batch clustering dataset for customer segmentation. Based on the analysis, various clusters were formed and validated. It was found that the results of both clustering techniques are same with an enhancement in processing speed via the use of mini-batch k-means. Customer segmentation can be used for market intelligence to identify interested clients by giving corporate entities in the retail sector pertinent and relevant facts periodically. It can be used as methods for examining customer purchase patterns and sales trends. The clustering has been applied over a dataset extracted from Kaggle. After performing the exploratory [...]