Browsing by Author "Sadia, Farzana"

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A priority based dynamic resource mapping algorithm for load balancing in cloud
(IEEE, 2018-02-15) Sadia, Farzana; Jahan, Nusrat; Rawshan, Lamisha; Jeba, Madina Tul; Bhuiyan, Touhid
Cloud computing is a rising technology which is responsible for supplying of computing resources on the basis of demand, as and when needed. Cloud provides many facilities due to its vast resources such as sharing resources for different purposes. Cloud computing faces many challenges in respect of performance and efficiency. To increase the cloud computing environment's efficiency, Virtual Machines (VM) has been employed for resource provisioning. In this paper, we proposed an algorithm that performs load distribution of workloads among different VM based on priority. This algorithm is proposed in the aim of load balancing of different nodes by considering maximum throughput with minimum execution time. To achieve that, the VM are sorted according to their processing powers and job requests are assigned to VM based on their instruction numbers and priorities. The proposed algorithm is experimented using CloudSim simulator and the results demonstrated that the performance of the algorithm is better than other conventional algorithms.
An Investigation on Exhaustion of SAP ERP Users: Influence of Pace of Change and Technostress
(Semantic Scholar, 2017-10-01) Roy, Prashanta Kumar; Mahmud, Imran; Jahan, Nusrat; Sadia, Farzana
Despite recent growing research interest on ERP research, the understanding on ERP induced exhaustion is still limited. This study examines how the pace of change of ERP functionalities and interface causes exhaustion in workplace. For this purpose, we conducted an investigation on 128 ERP users from two different organizations in Bangladesh. We extended theory of technostress by integrating pace of change of ERP system. Result suggests that pace of change on ERP system significantly affect work-overload, work-life conflict and role ambiguity on ERP users. Result also shows that work-overload and role ambiguity are strong predictors for ERP induced exhaustion.
Dataset on the Influence of Software Development Agility on Software Firms' Performance in Bangladesh
(Data in Brief, Elsevier, 2019-04) Sadia, Farzana; Mahmud, Imran; Dhar, Eva; Jahan, Nusrat; Hossain, Syeda Sumbul; Satter, A.K.M.Zaidi
The article identifies the relationship among different agile software development approaches such as response extensiveness, response efficiency, team autonomy, team diversity, and software functionality that software teams face difficult challenges in associating and achieving the right balance between the two agility dimensions. This research strategy, in terms of quantity, is descriptive and correlational. Statistical analysis of the data was carried out, using SmartPLS 3.0. Statistical population, consist of employees of software industries in Bangladesh, who were engaged in 2017 and their total number is about 100 people. The data show that the response extensiveness, response efficiency, team autonomy, team diversity, and software functionality have impact on software development agility and software development performance.
Detection and Classification of Road Damage Using R-CNN and Faster R-CNN
(Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, Springer, 2020-07-30) Arman, Md. Shohel; Hasan, Md. Mahbub; Sadia, Farzana; Shakir, Asif Khan; Sarker, Kaushik; Himu, Farhan Anan
Road surface monitoring is mostly done manually in cities which is an intensive process of time consuming and labor work. The intention of this paper is to research on road damage detection and classification from road surface images using object detection method. This paper applied multiple convolutional neural network (CNN) algorithm to classify road damage and discovered which algorithm performs better in road damage detection and classification. The damages are classified in three categories pothole, crack and revealing. For this research data was collected from street of Dhaka city using smartphone camera and prepossessed the data like image resize, white balance, contrast transformation, labeling. This study applies R-CNN and faster R-CNN for object detection of road damages and apply Support Vector Machine (SVM) for classification and gets a better result from previous studies. Then losses are calculated using different loss functions. The results demonstrate the highest 98.88% accuracy and the lowest loss is 0.01.
Develop a System to Analyze Logs of a Given System Using Machine Learning
(Independent University, Bangladesh (IUB), 2023) Hasan, Md. Tarek; Sadia, Farzana; Hasan, Mahady; Rokonuzzaman, M.
Software error detection is a critical aspect of software development. However, due to the lack of time, budget, and workforce, testing applications can be challenging, and in some cases, bug reports may not make it to the final stage. Additionally, a lack of product domain knowledge can lead to misinterpretation of calculations, resulting in errors. To address these challenges, early bug prediction is necessary to develop error-free and efficient applications. In this study, the author proposed a system that uses machine learning to analyze system error logs and detect errors in real time. The proposed system leverages imbalanced data sets from live servers running applications developed using PHP and Codeigniter. The system uses classification algorithms to identify errors and suggests steps to overcome them, thus improving the software’s quality, reliability, and efficiency. Our approach addresses the challenges associated with large and complex software where it can be difficult to identify bugs in the early stages. By analyzing system logs, we demonstrate how machine learning classification algorithms can be used to detect errors and improve system performance. Our work contributes to a better understanding of how machine learning can be used in real-world applications and highlights the practical benefits of early bug prediction in software development.
Enhancing Game Usability: A Framework for Small-to-Medium-Sized Game Development Businesses
(Independent University, Bangladesh (IUB), 2023-10) Akthar, Sayeda Rahnuma; Islam, Muhammad Rezaul; Islam, Nabila; Sadia, Farzana
The field of Human-Computer Interaction (HCI) research has developed numerous procedures and techniques to ensure high usability when developing software. Usability in video games is also considered to be important, so it is crucial to ensure that game systems comply with usability standards. However, research has overlooked software development, specifically the stage of game development. Additionally, large gaming firms and game developers tend to keep their procedures and techniques secret. Professional reports have revealed the "ugly face" of the gaming industry. Bangladesh's slowly expanding game development sector comprises a significant number of small-to-medium-sized businesses and start-ups. These businesses require practical, developer-centric solutions to guarantee usability as they may lack the funds to engage usability specialists to oversee it. This article discusses the concept of game usability, including current research on usability techniques for game production. The literature included in this study had to meet the following requirements: (1) focused on gaming applications, including websites, PC software, smartphone, and tablet applications; (2) provided information about the usability of the application; and (3) provided experimental evidence of usability testing. The study involved conducting polls, heuristic scoring studies, and speaking with several game developers. Twelve usability heuristics were created based on the Nielsen usability technique and the stages of game software development, which help in preventing typical usability problems in games. A preliminary analysis of the heuristics indicates that they can assist in identifying game-specific usability problems that may otherwise go unnoticed.
Impact of COVID-19 on the Factors Influencing On-Time Software Project Delivery: An Empirical Study
(18th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE), April 24 - 25, 2023 Prague, Czech Republic, 2023-03) Islam, Mahmudul; Khan, Farhan; Hasan, Mehedi; Sadia, Farzana; Hasan, Mahady
The objective of this research paper is to investigate the impact of COVID-19 on the factors influencing ontime software project delivery in different Software Development Life Cycle (SDLC) models such as Agile, Incremental, Waterfall, and Prototype models. Also to identify the change of crucial factors with respect to different demographic information that influences on-time software project delivery. This study has been conducted using a quantitative approach. We surveyed Software Developers, Project Managers, Software Architect, QA Engineer and other roles using a Google form. Python has been used for data analysis purposes. We received 72 responses from 11 different software companies of Bangladesh, based on that we find that Attentional Focus, Team Stability, Communication, Team Maturity, and User Involvement are the most important factors for on-time software project delivery in different SDLC models during COVID-19. On the contrary, before COVID-19 Team Capabilities, Infrastructure, Team Commitment, Team Stability and Team Maturity are found as the most crucial factors. Team Maturity and Team Stability are found as common important factors for both before and during the COVID-19 scenario. We also identified the change in the impact level of factors with respect to demographic information such as experience, company size, and different SDLC models used by participants. Attentional focus is the most important factor for experienced developers while for freshers all factors are almost equally important. This study finds that there is a significant change among factors for on-time software project delivery before and during the COVID-19 scenario.
Modelling Consumer's Intention to Use IOT Devices
(Indonesian Journal of Electrical Engineering and Computer Science, 2021) Jahan, Nusrat; Shawon, Md. Abu Hosen; Sadia, Farzana; Nitu, Dilara Khanom; Ribon, Md. Enam Kobir; Mahmud, Imran
The present study has been conducted to examine whether skills and general technology-related value (GTV) required to operate the internet of things (IoT). This study also investigates is there any effect of technophilia to adopt IoT. The research method we use in this quantitative study was the sample survey. For investigating results, 352 surveys were conducted where 26 surveys were led through online and 292 surveys were distributed to different age groups. The proposed model was examined using partial least square structural equation model where the results revealed that IoT skills and General knowledge on technology directly contribute to technophilia which covers behavioural, emotional, and cognitive aspects. That is if people have a fascination for new technologies then they are willing to use IOT.
Optimizing B2B Relationships with Post-Covid Sales and Marketing Automation through ERP Implementation: A Value-Driven Approach in Bangladesh
(Independent University, Bangladesh, 2023-05) Akthar, Sayeda Rahnuma; Khan, Mohammad Sajjad; Sadia, Farzana; Hasan, Mahady
Enterprise Resource Planning (ERP) is a powerful software program created to combine and streamline several company processes. Companies in developed countries frequently use it to increase their general effectiveness. ERP enables companies to meet the specific demands, interests, and behaviours of their customers, who are increasingly seeking individualized experiences. Even with the help of an implementation partner, deploying ERP properly necessitates a solid understanding of the involved process. During the implementation stage, effective communication and responsibility sharing can be challenging. The main goal of this paper is to create a thorough guidebook that offers insightful advice to businesses and their clients throughout the whole ERP deployment process. Six interviews were done to obtain information and address any implementation-related worries in order to accomplish this. These talks led to the creation of an implementation handbook that addressed important challenges and offered useful solutions. A methodology model diagram is also suggested to act as a visual roadmap for an organized and fruitful ERP installation. The objective is to equip businesses and their clients with the information and resources they need to successfully complete the deployment process and get the most out of their ERP system.
Social Crisis Detection Using Twitter Based Text Mining-A Machine Learning Approach
(Springer Nature, 2023-04-15) Rahman, Shoaib; Jahan, Nusrat; Sadia, Farzana; Mahmud, Imran
Social-media and blogs are increasingly used for social-communication, an idea and thought publishing platform. Public intentions, wisdom, problems, solutions, mental states are shared in social media. Text is being the best and the most common way to communicate over social networks. All kinds of data shared in social sites like Facebook, Twitter, and Microblogs. People from different pursuance uses these media to publish thoughts and convey messages through text. Consequently, occurrences in social life are rapidly discussed in social blogs in daily manner. This work aims at discovering ongoing social crisis from the Twitter data. Text mining technique and sentiment analysis were applied to detect the current social crisis from the social sites. Twitter data were collected to identify the recent social crisis. Furthermore, the identified crisis was compared to reputed newspapers. A hybrid method used to detect recent social issues resulted nicely. However, our proposed analysis shows identifying rate 89%, 95%, 83%, 53%, and 98% for the top 5 identified crisis accordingly in the date between 27 February and 11 March 2020. The strategy used in this study for the detection of recent social crisis will contribute to the social life and findings of crisis will be eliminated easily.
To Post or Not to Post: An Empirical Investigation on the Factors Influencing Student’s Knowledge Sharing Behaviour Through Facebook
(Daffodil International University, 2017-03-22) Mahmud, Imran; Md. Shohel Arman; Jahan, Nusrat; Sadia, Farzana; Rumel, Rayhanul Islam
Since the number of posts and social relationships are implanted in the largest social network sites, the use of Facebook is increasing, and the number of knowledge sharing behaviour of individuals is increasing as well. This paper aims to illustrate the relationship between the constructs of social cognitive theory and social exchange theory on students’ knowledge sharing through Facebook. This research was administrated to 101 students using self-administrative survey questionnaire. Structural equation modelling technique was employed to examine the hypothesized relationship between the variables. The findings of this study will help researchers to understand why students choose to engage in social network, specifically Facebook, to share knowledge. This research will also assist educators and practitioners to understand the factors behind knowledge sharing behaviour of the students. Most previous studies have examined in knowledge sharing attitude or intention in industry settings. This study is conducted in educational settings and particularly focused on the influence of institutional climate and outcome expectations on students’ knowledge sharing attitude.
Usability and Accessibility Testing
(2020) Jeba, Madina Tul; Sadia, Farzana; Rahman, Tasnim; Hossain, Kazi Md Istiyak; Bhuiyan, Touhid
People around the world use the information and avail services from government websites, thus the usability and accessibility of these websites are few of the main concerns for digital literacy of e-government system. The main objective of this study is to find out the usability and accessibility including broken links of the public sector and government websites of Bangladesh. Data was collected from 140 government web pages which are openly accessible for people of Bangladesh. Then data was analyzed by different online tools; usability and accessibility were tested by Web Site Optimization Tool, IDI Web Accessibility Checker along with 2bone Link Checker respectively. Results show that government websites have 37% usability error rate which was measured with respect to some attributes like HTML, CSS and Scripts. On the other hand, accessibility error rate for these websites are 92% where per website there are 5% of broken links. The demonstration of result concludes that the usability and accessibility of government web sites of Bangladesh is alarming and not optimized.