Browsing by Author "Rahman, Tasnim"

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A Comparative Study on GA-based Scheduling on Cloud Computing
(Scopus, 2020) Rawshan, Lamisha; Rahman, Tasnim; Begum, Afsana; Hossain, Syeda Sumbul; Bhuiyan, Touhid
Cloud computing provides data storage and computing power based on user demand by assigning tasks to virtual resources. To deliver overall improved performance and meet challenges such as availability, resource utilization and reliability in the cloud, appropriate resource scheduling methods are needed. A number of metaheuristic optimization algorithms are used to solve the problem of resource scheduling. This work lists challenges and analyzes previous scheduling methods based on Genetic Algorithm (GA). It classifies the GA-based scheduling methods with respect to many parameters. At last, it presents the scopes of enhancement for future researchers.
Aspect Based Sentiment Analysis in Bangla Dataset Based on Aspect Term Extraction
(Springer, 2020-07-30) Haque, Sabrina; Rahman, Tasnim; Shakir, Asif Khan; Arman, Md. Shohel; Biplob, Khalid Been Badruzzaman; Himu, Farhan Anan; Das, Dipta; Islam, Md Shariful
Recent years have seen rapid growth of research on sentiment analysis. In aspect-based sentiment analysis, the idea is to take sentiment analysis a step further and find out what exactly someone is talking about, and then measuring the sentiment if she or he likes or dislikes it. Sentiment analysis in Bengali language is progressing and is considered as an important research interest. Due to scarcity of resources like proper annotated dataset, corpora, lexicon such as part of speech tagger etc. aspect-based sentiment analysis hardly has been done in Bengali language. In this paper, we have conducted our experiments based on a recent work from 2018 using conventional supervised machine learning algorithms (RF, SVM, KNN) to perform one of the ABSA’s tasks - aspect category extraction. The work is done on two datasets named – Cricket and Restaurant. We then compared our results with the existing work. We used two traditional steps to clean data and found that less preprocessing leads to better F1 Score. For Cricket dataset, SVM and KNN performed better, resulting F1 score of 37% and 27%. For Restaurant dataset, RF and SVM achieved improved score of 35% and 39% respectively. Additionally, we selected two more algorithms LR and NB, LR achieved best F1 score (43%) for Restaurant dataset among all.
Classroom Management of Spoken English Language Courses in Private Universities
(East West University, 5/12/2018) Rahman, Tasnim
English spoken courses have been included, due to the current uprising demands, in the curricula of private universities in Bangladesh, regardless of any faculties. However, very few studies conducted on the classroom management of spoken English language courses, especially at the tertiary level. Teaching and learning being interlinked to each other, classroom management, by drawing a congenial environment, plays a vital role to the purpose of both teaching and learning to its fruitful end. It is, therefore, essential to explore the managerial styles and strategies practiced in spoken classrooms. The study is anticipated to be helpful for teachers, researchers and course-designers altogether to make them realize the importance of classroom management at tertiary level as well as at other levels of education in Bangladesh. During the course of the study, ten universities were visited. Data were collected through observation of twenty English language classes and interviews of ten English language teachers. Moreover, there were total of 218 students divided into 27 focus groups who were interviewed to collect the required data. In order to examine the data, two theories had been applied—one was about style and the other, was about strategy as mentioned in the section of theoretical framework. Upon analysis of the obtained data, the research findings indicate that authoritarian style and improper preventive strategies were being applied to handle the managerial matters of spoken courses that lead to an ineffective environment for learning speaking in English as a language skill. The investigation concluded with a couple of recommendations for new measures, which ideally will refresh the teaching of speaking skill in private universities with far more prominent extension and achievement.
Comparison of automated system D2 Mini with conventional method and VITEK-2 for identification and antibiotic susceptibility pattern of gram-negative fermentative bacteria
(BRAC University, 2025-02) Fatema, Kaniz; Rahman, Tasnim; Jilani, Md. Shariful Alam; Hossain, Mahboob
This study evaluates and compares the performance of the automated D2 Mini system with conventional microbiological methods and the VITEK-2 system for the identification and antibiotic susceptibility testing (AST) of gram-negative fermentative bacteria. A total of 34 clinical isolates were analyzed, including Escherichia coli (n=9), Klebsiella pneumoniae (n=7), Klebsiella oxytoca (n=1), Salmonella Typhi (n=7), Salmonella Paratyphi (n=1), Serratia marcescens (n=3), Aeromonas hydrophila (n=2), Morganella morganii (n=1), Proteus hauseri (n=1), Proteus mirabilis (n=1), and Edwardsiella hoshinae (n=1). The isolates were recovered from various clinical specimens, including blood, urine, pus, wound swabs, catheter tips, and bronchial wash. Identification was performed using conventional methods, including Gram staining, biochemical tests, and antibiotic susceptibility testing (AST) by the disk diffusion method, followed by automated systems (VITEK-2 and D2 Mini). The results showed that both the VITEK-2 and conventional methods achieved 100% concordance for genus and species identification. However, the D2 Mini system demonstrated high genus-level concordance (100%) for most isolates, except for Klebsiella pneumoniae (85.7%) and Serratia marcescens (66.7%) at the species level. The D2 Mini system failed to identify Salmonella species at the species level. Antibiotic susceptibility testing revealed that both automated systems (VITEK-2 and D2 Mini) exhibited high concordance with the disk diffusion method for several antibiotics, including amoxicillin-clavulanate, ceftazidime, ciprofloxacin, gentamicin, and amikacin. However, discrepancies were observed for antibiotics such as netilmicin and colistin, with low concordance values. The D2 Mini demonstrated a restricted antibiotic panel, lacking profiles for antibiotics such as ceftriaxone colistin, and TZP, while VITEK-2 showed higher concordance but also displayed limitations for certain antibiotics. This study highlights the strengths and limitations of automated systems in microbial diagnostics, emphasizing the need for further improvements in their antibiotic testing capabilities, particularly for last-resort antibiotics and non-fermenting bacteria.
Impact of treatment size and therapy type in phase II clinical trials of non-small cell lung cancer
(BRAC University, 2023-03) Rahman, Tasnim; Azam, Faruque
In spite of recent developments in cancer therapy that are specifically targeted, a frightening number of individuals still pass away every year from lung cancer around the world. Because of this, we decided to focus our research on non-small cell lung cancer. As a consequence of the high degree of heterogeneity that characterizes lung carcinoma, the unsatisfied clinical need is the determination of a suitable combination of medications. The requirement for the validation of efficacy endpoint methods in clinical trials, which are methods by which the effectiveness of cancer medicines is determined, is one possible cause of the problem that was described above. We intend to help investigators design clinical trials by establishing two predictive efficacy models, and we plan to optimize the combination treatment for certain lung malignancies by examining a substantial amount of clinical trial efficacy data. This will allow us to do both.
IOT Based Smart Health Monitoring System for Diabetes Patients Using Neural Network
(Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Springer, 2020-07-30) Efat, Md. Iftekharul Alam; Rahman, Shoaib; Rahman, Tasnim
In improvement of the quality of health care services, Internet of Things (IoT) has evolved rapidly for monitoring patient from distance. However, notifying health status based on continuous change of health condition for immediate healing to patient, existing systems has some limitations. In this paper, we demonstrate a smart health monitoring technology for diabetic patients which follows up their health condition depending on sugar level, heart pulse, food intake, sleep time and exercise. To illustrate, this technology takes the variables (data) as input through sensors continuously and process with neural network to evaluate the data, resulting four modes of health risk status: low, medium, high and extreme. The range of the risk status can differ based on patient’s type and previous histories of their health. In addition, an automatic phone call and/or SMS notification is being sent to patient’s relative along with patient’s location if his/her health condition is at high or extreme risk. Besides, it also calls patients nearest hospital in case of extreme risk. However, the system provides allied instruction as voice command to patient’s mobile in both cases. This technology has been experimented on 25 diabetic patients successfully and achieved 84.29% accuracy to identify the proper risk level, which is a highly acceptable level of identifying health risk status.
Seqdev: an algorithm for constructing genetic elements using comparative assembly
(© 2016 Bangladesh Association for Plant Tissue, 2016) Rahman, Tasnim; Heickal, Hasnain; Tabrejee, Shamira; Chowdhury, Md Miraj Kobad; Sarwar, Sheikh Muhammad; Shoyaib, Mohammad
With the availability of recent next generation sequencing technologies and their low cost, genomes of different organisms are being sequenced frequently. Therefore, quick assembly of genome, transcriptome, and target contigs from the raw data generated through the sequencing technologies has become necessary for better understanding of different biological systems. This article proposes an algorithm, namely SeqDev (Sequence Developer) for constructing contigs from raw reads using reference sequences. For this, we considered a weighted frequency‐based consensus mechanism named BlastAssemb for primary construction of a sequence with gaps. Then, we adopted suffix array and proposed a gap filling search (GFS) algorithm for searching the missing sequences in the primary construct. For evaluating our algorithm, we have chosen Pokkali (rice) raw genome and Japonica (rice) as our reference data. Experimental results demonstrated that our proposed algorithm accurately constructs promoter sequences of Pokkali from its raw genome data. These constructed promoter sequences were 93 ‐ 100% identical with the reference and also aligned with 96 ‐ 100% of corresponding reference sequences with eValue ranging from 0.0 ‐ 2e-14. All these results indicated that our proposed method could be a potential algorithm to construct target contigs from raw sequences with the help of reference sequences. Further wet lab validation with specific Pokkali promoter sequence will boost this method as a robust algorithm for target contig assembly.
The air borne disease becoming a blessing in disguise for the IT sectors in Bangladesh: a perspective on Ogroni Informatix Limited CRM
(BRAC University, 2021-09) Rahman, Tasnim; Khan, Tanzin
This report provides a perspective on the B2B IT firm, Ogroni Informatix Ltd. It has specifically described the operation of B2B digital services during the pandemic and how Ogroni is adding value to it. The objective was to gather knowledge on how the pandemic has provided them a golden gate to attract new clients as well as provide valuable digital solutions to the existing ones to maintain excellent client relationship management (CRM). The report further exhibits the strategic tools used to assess Ogroni’s potential positioning within the industry. The tools that were used to evaluate the business are SWOT and Porter's Five Forces. At first, the report started with a brief description of the B2B IT sector during the pandemic and how they are operating in Dhaka city. The methods used to collect data were through observation, online survey and lastly, secondary data from the internet. It also gives an overview of Ogroni’s flagship products practices and its integration with digital marketing. The values and culture of the company and its interlinkage have been mentioned. The research topic of the report has been the operational benefits Ogroni has gathered during the pandemic. What marketing strategies did the company take to maintain and strengthen its CRM. Whether it was effective to reach goals and objectives. The major findings of the reports have been solely focused on how the pandemic has helped Ogroni to provide satisfying digital solutions to their clients and how more opportunities are garnered by them as the country shifts towards more virtually oriented business operations. Since the company does not have its in-house marketing department however, through the Business Analyst department they are providing marketing solutions as an outsourcing company to the client's target group. So that the client's marketing segmentation can be done smoothly. However, I have examined that the lack of specialized market researchers has been an aspect that Ogroni needs to exercise to make effective use of marketing resources. As a result, sometimes the company was unable to deliver required marketing solutions to specific client demands. A proper market researching team performing focus group discussion and in-depth interview from Ogroni will determine what tools to use for providing digital marketing solutions just like any marketing agency does. Lastly, I have provided my recommendations based on the areas of bottlenecks and what new changes could be made to overcome that.
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.