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, [...]

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 [...]

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: 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: The focus of this study is the design, development, and impact of an example of no-code software application builder using drag and drop. By using programming visually, automating workflows, and integrating autonomously with different backends, this research also mitigates the traditional software development and the non-programmer spends on software development, simplifying and making app building development speedier, easier, and more scalable. This study focuses on architectural structures and the logic building processes coupled with the database, and aims at custom tailoring unmodifiable software that belt on security worries, unreachable deployment, and more, toward problematic customization, unchecked triangulation, unbounded cooperation, [...]

Abstract: With the expansion of online platforms, new rooms are opening to extract full insights from huge textual data. Aspect-Based Sentiment Analysis (ABSA) is rising as an essential Artificial Intelligence (AI) discipline that employs Natural Language Processing (NLP) to associate sentiments with specific attributes of entities. In this systematic review, we focused on ABSA studies published between 2020 and 2024, encompassing 66 primary research articles focusing on advancements in AI methodologies, including transformer-based models and generative AI techniques. The novel ABSA taxonomy developed in this study defines methodological categories and analyzes the use of commercial and domain-specific datasets. This research [...]

Abstract: During the past few years, there have been a surge in the use of social media. Various social media platforms have emerged such as Twitter, WhatsApp, Facebook and LinkedIn. The existing studies reveal that there has been a relation between social media usage and mental health. The objective of this study is to explore age biasness related to mental health data on social media platforms. Some studies have already been done on analysis of the effect of social media platforms on mental health. However, it has been observed that there is an issue of lack of inclusiveness towards the [...]

Risk assessment is one of the complex issues that determines the probability of occurrence of the events. The purpose of this paper is to present the various types of cyber risks and attacks that can significantly affect organizational performance. This research study is qualitative research in which data has been collected from various respondents operating in the field of cyber security in Pakistan’s telecommunication sector. This paper follows the convenience sampling technique to collect data from various participants. The sample size of 5 participants consisting of cyber security experts has been chosen for this research. In-depth qualitative interviews were conducted [...]

Abstract: This paper talks about a novel comparison of two deep learning models namely Long short-term memory (LSTM) and Gated recurrent unit (GRU). The target domain is e-commerce sales prediction applied on behavioral data from a Shopify store. The dataset comprises 87000 records stepped by hours. The dataset contains details about various features such as session duration, bounce rate, cart addition, checkout activity. It has been found that LSTM and GRU both were able to learn the spatiotemporal dependencies present in the data. These models predict with good accuracy the probability of making a purchase in a session. By means [...]

Abstract: This work presents a systematic literature review of smart library management system. By studying different papers for past 10 years to address several research questions, the findings are presented. A smart library is based on employing smart information and communication technologies (ICT) to facilitate readers. Five major research questions are answered. What is smart library, the major research challenges in implementing smart library, the advantages of smart library, and the enabling technologies for smart library. Finally, this work presents a smart library management system based on deep learning technique. An android mobile application is developed that digitizes the book [...]