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Messages - Monir Hossan

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16
Dataset on the influence of software development agility on software firms' performance in Bangladesh

Abstract
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.

Authors: Farzana Sadia; Imran Mahmud; Eva Dhara; Nusrat Jahana; Syeda Sumbul Hossain; A.K.M. Zaidi Satter

Source: Data in Brief, Volume: 23
Link: https://www.sciencedirect.com/science/article/pii/S2352340919300903

17
A Comparative Analysis of Traditional and Modern Data Compression Schemes for Large Multi-Dimensional Extendible Array

Abstract:
Data analysis and mining in scientific domains involve storage of large-scale multi-dimensional datasets for scientific, statistical & engineering applications in multidimensional online analytical processing (MOLAP) databases. Because of the size of the datasets is increasing and the degree of data-sparsity is being high, it is important to find the suitable and efficient compression scheme for storing data at a minimal scheme. This paper represents a comparative analysis of Traditional and Modern Data Compression Schemes for Multi-Dimensional data ranging from dimension 1 to 3. The main idea is to compare the space savings of four different & significant compressions schemes i.e. Bit Map, Header Compression, Compressed Row Storage (CRS) & Extendible Array Based Compression Scheme (EaCRS). The results from experiments show that EaCRS scheme is better than the other schemes in case of space complexity especially for higher data density.

Authors: Md. Mushfiqur Rahmani ; Abdullah Al-Mahmud ; Md. Anwar Hossen ; Mostafijur Rahman ; Md. Raihan Ahmed; Md Fahimuzzman Sohan

Source: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019
Link: https://ieeexplore.ieee.org/document/8679182/authors#authors

18
Identifying Neuroticism from User Generated Content of Social Media based on Psycholinguistic Cues

Abstract:
Social media has become a huge repository of textual data and images as each of the users' are creating posts, sharing views or news, capturing the moments via photos etc. Sharing or posting statuses/tweets could be considered as a common feature among the popular social networking sites like Facebook, Twitter, Google+ etc. User generated textual data such as statuses or tweets could be considered as the essential language to communicate in social media with others. This paper investigates the possibilities of identifying negative personality trait based on the psycholinguistic cues extracted from the language used in social media. Predicting personality traits based on widely accepted framework of Big Five Factor Model (BFFM) is a challenging task. According to the model, there are four positive traits namely openness to experience, conscientiousness, agreeableness and extraversion, while there is only one negative trait neuroticism. The tendency of experiencing negative emotions such as anger, sad, anxiety, depression, instability are referred as neuroticism. We have used psycholinguistic cues extracted using linguistic enquiry and word count (LIWC) for predicting neuroticism. We have applied five different classifiers to evaluate the prediction model.

Authors: Ahmed Al Marouf ; Md. Kamrul Hasan ; Hasan Mahmud

Source: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019
Link: https://ieeexplore.ieee.org/abstract/document/8679505

19
Revisiting the Class Imbalance Issue in Software Defect Prediction

Abstract:
Software defect prediction is related to the testing area of software industry. Several methods have been developed for the prediction of bugs in software source codes. The objective of this study is to find the inconsistency of performance between imbalances and balance data set and to find the distinction of performance between single classifier and aggregate classifier (voting). In this investigation, eight publicly available data sets have collected, also seven algorithms and hard voting are used for finding precision, recall and F-1 score to predict software defect. In these collected data, two sets are almost balanced. For this investigation, these balanced data sets have converted into imbalanced sets as average non-defective and defective ratio of the other 6 data sets. The experiment result shows that performance of the two balanced data sets is lower than other six sets. After conversion of two data sets, the performance has increased as like as other six data sets. Another observation is the performance metric that shows the results of precision, recall and F1-score for voting are 0.92, 0.84 and 0.87 respectively, which are better than other single classifier. This study has been able to shows that- imbalance of non-defective and defective classes have a big impact on software defect prediction and the voting is the best performer among the classifiers.

Authors: Md. Fahimuzzman Sohan ; Md Alamgir Kabir ; Md. Ismail Jabiullah ; Sheikh Shah Mohammad Motiur Rahman

Source: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019
Link: https://ieeexplore.ieee.org/abstract/document/8679382

20
Prediction of possible asthma attack from air pollutants: Towards a high density air pollution map for smart cities to improve living

Abstract:
Asthma is a chronic, often devastating, condition that has no cure and causes a remarkable economic burden to the associated family as well as to the government and state. But it can be controlled and managed with personal diagnostic of triggering factors of asthma and through preventive care. Sometimes it is as simple as avoiding air pollutants like dust, tobacco smoke etc. Asthma attack triggered from air pollution could easily be avoided if there is a way to monitor air pollution level continuously in the surroundings. In this paper, we have presented a system that will be able to predict possible asthma attack for individuals and alert them. The system is developed using an air pollutant monitoring device combined with an Android application. Using supervised learning technique and analyzing (frequently taken) air pollutant data, the system will help to reduce asthma attacks for asthma patients. Also analyzing personalized data of individuals it will be possible to recommend a new user about the safe and unsafe zone of the city. As a by-product, it will be possible to create a high-density air pollution map of cities to monitor air pollution.

Authors: Md Nazmul Hoq ; Rakibul Alam ; Ashraful Amin

Source: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019
Link: https://ieeexplore.ieee.org/document/8679335

21
Automated Prediction of Heart Disease Patients using Sparse Discriminant Analysis

Abstract:
Linear Discriminant Analysis (LDA) is an easy and efficient method for pattern classification, while it is also broadly utilized for the initial discovery of diseases using Electronic Health Records (EHR) data. Nonetheless, the performance of LDA for EHR data classification is recurrently influenced by two major factors: poor evaluation of LDA parameters (e.g., covariance matrix), and “linear inseparability” of the EHR data for classification. In this paper, we propose a novel classifier SDA -Sparse Discriminant Analysis method for heart disease detection. The time complexity will be reduced in this algorithm by optimal scoring analysis of LDA and will be comprehensive to execute sparse discrimination through the combination of Gaussians if limits between classes are nonlinear or if subgroups are available inside every class. On the whole, compared to previous techniques, our proposed technique is more appropriate for the diagnosis of heart disease patients with higher accuracy.

Authors:
K. M. Zubair Hasan ; Shourob Datta ; Md Zahid Hasan ; Nusrat Zahan

Source: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019
Link: https://ieeexplore.ieee.org/document/8679279

22
Runtime Optimization of Identification Event in ECG Based Biometric Authentication

Abstract:
Biometric Authentication has become a very popular method for different state-of-the-art security architectures. Albeit the ubiquitous acceptance and constant development of trivial biometric authentication methods such as fingerprint, palm-print, retinal scan etc., the possibility of producing a highly competitive performance from somewhat less-popular methods still remains. Electrocardiogram (ECG) based biometric authentication is such a method, which, despite its limited appearance in earlier research works, are currently being observed as equivalently high-performing as other trivial popular methods. In this paper, we have proposed a model to optimize the runtime of identification event in ECG based biometric authentication and we have achieved a maximum of 79.26% time reduction with 100% accuracy.

Authors: Nafis Neehal, Dewan Ziaul Karim, Sejuti Banik, Tasfia Anika

Source: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019
Link: https://arxiv.org/abs/1805.05986

23
A Novel Approach of Fair Scheduling to Enhance Performance of Hadoop Distributed File System

Abstract:
Nowadays, big data is one of the most challenging issues for managing big amounts of data more effectively and efficiently. It widely used in E-commerce, social media, online business and such types of applications. Hadoop Distributed File System (HDFS) is one of the widely used frameworks which can easily handle and store large amounts of data set frequently. For HDFS job scheduling is more challenging because it plays an important role in time optimization in big data. For resolving this issue in this paper, we introduce a job scheduling algorithm which is more time efficient and accurate than existing fair job scheduling algorithm. We optimize the time cycle of fair scheduling by minimizing iteration. We have accelerated with the different number of jobs in the existing algorithm and proposed an algorithm for experimentally proving the time complexity and time measurement. It is observed that the proposed method is computationally efficient than the existing one and our algorithm has reduced the number of iterations and improved the time efficiency on average 26.719%.

Authors: Rubayet Hussain ; Mostafijur Rahman ; Khawja Imran Masud ; Sheikh Md Roky ; Md. Nasim Akhtar ; Tanjila Akter Tarin

Source: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019
Link: https://ieeexplore.ieee.org/abstract/document/8679252/authors#authors

24
Modelling and Optimization of Hybrid Power System at Coastal Area

Abstract:
As a developing country, Bangladesh is badly in need to get their power distribution to all sections of people. However, the amount of fossil fuel is decreasing gradually and in near future, it will be a burning question that how it could be possible to generate energy without this fuel. On the other hand, energy generation through fossil fuel is much more costly and environmentally harmful for such type of situation. In this study, we choose the most renowned heritage place in Bangladesh named Saint Martin Island. In this island, people are isolated from the main land of Bangladesh and also from the energy sector. It is literally impossible to get connected with national grid because of inconvenient placement of Saint Martin. Two renewable sources have been considered for this study- PV and Wind. For study and design the model HOMER software has been used. This hybrid power system solution can provide least cost and no harmful element for the environment. Resulted COE ($0.227/kWh) has been found through this system. Also on the basis of results, it has been proved that renewable energy perhaps replaces the conventional energy and would be a feasible solution for the generation of electric power at remote locations with a reasonable investment.

Authors: Morsalin Bin Mosharof Fardun ; Kazi Shaidul Islam Sunny ; Md. Dara Abdus Satter

Source: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019
Link: https://ieeexplore.ieee.org/document/8679410?denied=

25
A Novel Approach for Client Side Encryption in Cloud Computing

Abstract:
Cloud computing has become the latest technological computing area providing a large number of advantage to the different organization with its different business model at low cost. Nevertheless, there is always a security concern when uploading sensitive data in the cloud server. Client-side encryption is a common and better solution for ensuring end users that a third party user cannot access the uploading data. Cloud service providers maintain different techniques to protect data but like google drive, most of the company do not use client- side encryption. In this paper, we propose a way to protect the data from hacking or losing when storing or uploading the data in the cloud server using the combination of Advanced Encryption Standard and Secure Hash Algorithm with Initial Vector.

Authors: Md. Mahidul Islam ; Md. Zahid Hasan ; Rifat Ali Shaon

Source: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019
Link: https://ieeexplore.ieee.org/document/8679151

26
Suffix Based Automated Parts of Speech Tagging for Bangla Language

Abstract:
Natural language processing (NLP) is the technique by which we process the human language with the computer. Parts-of-Speech (POS) tagging is one of the fundamental requirements for some NLP applications. It is considered as a solved problem for some foreign languages, such as English, Chinese, due to higher accuracy (97%), where it is still an unsolved problem for Bangla because of its ambiguity. Although making a POS tagger for Bangla is not a new work, but each one of available POS taggers has different kinds of limitations. We choose to develop an unsupervised system rather than a supervised system, because a supervised system needs a huge data resource for training purpose and available resources in Bangla is really poor. Here we develop a POS tagger mainly based on Bangla grammar especially suffixes. Because Bangla is a very inflectional language, where a single word has many variants based on their suffixes. In this POS tagger, we assign 8 base POS tags, where some rules, based on Bangla grammar and suffix, are applied to identify POS tags with the cooperation of verb root dataset. To handle non-suffix words, a dataset of almost 14500 Bangla words, with having their default POS tags, is added with the system, which helps to increase the efficiency of this POS tagger. A modified version of previously used algorithm for suffix analysis is applied, which result in a satisfactory level of about 94.2%.

Authors:
Monjoy Kumar Roy ; Pinto Kumar Paull ; Sheak Rashed Haider Noori ; S M Hasan Mahmud

Source: 2nd International Conference on Electrical, Computer and Communication Engineering, ECCE 2019

Link: https://ieeexplore.ieee.org/document/8679161

27
Use of e-learning at higher educational institutions in Bangladesh: Opportunities and challenges

Abstract:
Purpose
Although e-learning has already been accepted globally as an effective medium of delivery of quality education and ensure optimum student participation, Bangladeshi higher educational institutions are still at a very early stage of adopting such technologies. Therefore, the purpose of this paper is to critically examine the suitability of implementing effective e-learning through learning management system (LMS) at the tertiary educational institutions in Bangladesh, and how both students and teachers experience and respond to this new learning platform. Following mixed-methods techniques, data for this study were collected from students and respective course teachers of a private university in Bangladesh by administering questionnaires and in-depth interviews. The findings of this paper reveal that e-learning has been well accepted by most of the students as they are found routinely spending time on the LMS on a regular basis for watching lecture videos, viewing course information, reading postings of the fellow students in the forum. However, there are constraints as well, since the learning materials are poorly designed that do not allow much interaction between students and lecturers. There are also some technical problems such as poor internet connection which restrict access to e-learning platforms. To harness the optimum benefit of e-learning, this paper recommends a concerted effort by all stakeholders, such as students, lecturers, administrators and policy makers so that each of their priorities and expectations are reflected in the designing and implementing e-learning platforms.

Design/methodology/approach
This paper is based on the qualitative evaluation of Education 3.0 platform. Primary data were collected from the students using a well-structured survey questionnaire, and the findings of the survey have subsequently been cross-referred and supplemented by non-participatory observations with semi-structured interviews which allowed a better in-depth understanding of the issue at hand.

Findings
The findings of the study suggest that a majority of the students are found to be highly enthusiastic about the online courses. They are eager to participate and interact in the online platforms, which are somehow limited in the traditional classroom settings. However, there are several institutional, administrative and technical limitations of implementing e-learning in Bangladesh. It is recommended that better orientation of the users, quality content distribution though user-friendly systems and enhanced asynchronous interaction between the lecturers and students are the key pre-requisites to harness the optimum benefit from e-learning technologies in Bangladesh.

Originality/value
The data have been analyzed and discussed using qualitative framework which allows an in-depth understanding of the opportunities and challenges of the use of e-learning technologies at the higher educational institutions in Bangladesh.

Authors:

Md Fouad Hossain Sarker, Rafi Al Mahmud, M. Saiful Islam, Md Kabirul Islam,

Source: Journal of Applied Research in Higher Education, 11(2)

Link: https://www.emeraldinsight.com/doi/abs/10.1108/JARHE-06-2018-0099

28
An approach to building energy clusters using particle swarm optimization algorithm for allocating the tasks in computational grid

Abstract
The proper mapping in case of allocation of available tasks among particles is a challenging job to accomplish. It requires proper procedural approach and effectual algorithm or strategy. The deterministic polynomial time for task allocation problem is relative. The existence of proper and exact approach for allocation problem is void. However, for the survival of the grid and executing the assigned tasks, the reserved tasks need to be allocated equally among the particles of the grid space. At the same time, the applied model for task allocation must not consume unnecessary time and memory. We applied Particle Swarm Optimization (PSO) for allocating the task. Additionally, the particles will be divided into three clusters based on their energy level. Each cluster will have its own cluster header. Cluster headers will be used to search the task into space. In a single cluster, particles member will be of same energy level status such as full energy, half energy, and no energy level. As a result, the system will use the limited time for searching task for the remaining tasks in it if a particular task requires allocating half task to a particle.

Authors:
Rashedul Islam; Md Nasim Akhtar; Badlishah R Ahmad; Utpal Kanti Das; Mostafijur Rahman; Zahereel Ishwar Abdul Khalib

Source: Indonesian Journal of Electrical Engineering and Computer Science, 14(2)

Link: http://www.iaescore.com/journals/index.php/IJEECS/article/view/16734

29
Design of Ge 20 Sb 15 Se 65 embedded rectangular slotted quasi photonic crystal fiber for higher nonlinearity applications

Abstract
In quasi pattern, photonic crystal fiber (PCF) with Ge20Sb15Se65 rectangular core is modeled. In this article, few optical properties of PCFs like power fraction, nonlinearity, effective mode area, birefringence, beat length, waveguide dispersion are obtained using finite element method (FEM). The proposed structure demonstrates significant effect on few optical properties for two polarization modes. It produces a high nonlinearity of 6.161 × 103 W−1Km−1and birefringence of 1.46 × 10−1 inside infrared region (IR). This proposed structure may play a vital role in multitasking applications.

Authors:
I.S. Amiriab Md. Abdul Khalek Sujan Chakm Bikash Kumar Paul Kawsar Ahmed Vigneswaran Dhasarathan M.S.Mani Rajan

Source: Optik, Volume: 184

Link: https://www.sciencedirect.com/science/article/pii/S0030402619300063?dgcid=rss_sd_all

30
Refractive Index-Based Blood Components Sensing in Terahertz Spectrum

Abstract:
In this paper, a novel partial type-b crystalline core with more compact cladding in hexagonal packing photonic crystal fiber (CC-PCF)-based optical sensor has been proposed for sensing different blood components. This fiber has investigated in terahertz (THz) region from 1.5 to 3.50 THz, intending to superior relative sensitivity with low confinement loss (CL). Circular air holes have been employed in the formation of the partial type-b crystalline core in a symmetric manner. A significant relative sensitivity response of 80.93%, 80.56%, 80.13%, 79.91%, and 79.39% are achieved for the targeted analytes such as RBCs, hemoglobin, WBCs, plasma, and water at frequencyf = 1.5 THz. In X-polarization mode, a negligible CL of 1.23 × 10 -11 dB/m, 8.63 × 10 -12 dB/m, 4.93 × 10 -12 dB/m, 2.93 × 10 -12 dB/m, and 1.13 × 10 -12 dB/m are also gained, respectively, for same analytes and at same THz frequency. Moreover, effective area (A eff ), V-Parameter (V eff ), dispersion (β 2 ), spot size (W eff ), and beam divergence (θ) have been determined over the investigated region. The improved outcomes are anticipated that the proposed CC-PCF sensor will be opened a new epoch in biomedical sensing purposes.

Authors:
Kawsar Ahmed  ; Fahad Ahmed ; Subrata Roy ; Bikash Kumar Paul ; Mst. Nargis Aktar ; Dhasarathan Vigneswaran ; Md. Saiful Islam

Source: IEEE Sensors Journal, 19(9)

Link: https://ieeexplore.ieee.org/document/8626199

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