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31

Research Publications / স্কোপাস ইনডেক্সড গবেষণায় বেসরকারি বিশ্ববিদ্যালয়ে ড্যাফোডিল বিশ্ববিদ্যালয় প্রথম

« on: March 12, 2020, 04:39:56 PM »

স্কোপাস ইনডেক্সড গবেষণায় বেসরকারি বিশ্ববিদ্যালয়ের মধ্যে ড্যাফোডিল বিশ্ববিদ্যালয় প্রথম

স্কোপাস ইনডেক্সড (অধিভূক্ত) গবেষণাপত্রের ভিত্তিতে ২০১৯ সালে বাংলাদেশের সকল সরকারি ও বেসরকারি বিশ্ববিদ্যালয়গুলোর মধ্যে পঞ্চম এবং বেসরকারি বিশ্ববিদ্যালয়গুলোর মধ্যে প্রথম স্থান অর্জন করেছে ড্যাফোডিল ইন্টারন্যাশনাল ইউনিভার্সিটি। স্কোপাসের ওয়েবসাইট থেকে এ তথ্য জানা গেছে। গত ২ ফেব্রুয়ারি, ২০২০ তারিখে ওয়েবসাইটের তথ্য অনুযায়ী ২০১৯ সালে ড্যাফোডিল ইন্টারন্যাশনাল ইউনিভার্সিটির গবেষণা পত্র প্রকাশনা সংখ্যা ২৮০ টি।  একই সময়ে ব্র্যাক বিশ্ববিদ্যালয়ের গবেষণা পত্র প্রকাশনা সংখ্যা ২৬৫ এবং নর্থ সাউথ বিশ্বব্যিালয়ের গবেষণা পত্র প্রকাশনা সংখ্যা ২১৬।

এর আগে বৈজ্ঞানিক গবেষণাপত্র প্রকাশের দিক থেকে ২০১৯ সনে বেসরকারি বিশ্ববিদ্যালগুলোর মধ্যে দ্বিতীয় স্থান অর্জন করে ড্যাফোডিল ইন্টারন্যাশনাল ইউনিভার্সিটি। ঊখঝঊঠওঊজ এর ‘স্কোপাস ডাটাবেইজ’-এর বিভিন্ন উপাত্ত বিশ্লেষণ করে গত ৬ জানুয়ারি এ তথ্য প্রকাশ করেছিল বাংলাদেশের গবেষণা পরিস্থিতি পর্যবেক্ষণকারী ম্যাগাজিন ‘সায়েন্টিফিক বাংলাদেশ’।  বৈজ্ঞানিক গবেষণাপত্র প্রকাশের ভিত্তিতে ওই তালিকা করা হয়। তালিকায় দেশের সরকারি ও বেসরকারি বিশ্ববিদ্যালয় ও গবেষণা প্রতিষ্ঠানগুলোর মধ্যে ২০১৯ সনে সম্মিলিতভাবে ড্যাফোডিল ইন্টারন্যাশনাল ইউনিভার্সিটির অবস্থান ছিল অষ্টম।

এছাড়াও কিউএস (কোয়াককোয়ারেল সাইমন্ডস) এশিয়া ইইউনিভার্সিটি র‌্যাংকিং-২০১৯ এ এশিয়ার ৫০০ সেরা বিশ্ববিদ্যালয়ের তালিকায় অন্তর্ভূক্তিসহ বাংলাদেশের পাবলিক এবং প্রাইভেট বিশ্ববিদ্যালয়ের মধ্যে ষষ্ঠ স্থান অর্জন ছাড়াও টাইমস হায়ার এডুকেশন (টিএইচই) ইউনিভার্সিটি ইম্প্যাক্ট র‌্যাংকিং ২০১৯ এ মর্যাদাপূর্ণ অবস্থান অর্জন করেছে ড্যাফোডিল ইন্টারন্যাশনাল ইউনিভার্সিটি।

Source: https://the-prominent.com/others-article-6351/

32

Robotics Club / Robotic Process Automation (RPA)

« on: August 31, 2019, 10:58:34 AM »

Robotic Process Automation (RPA)

What is Robotic Process Automation?

Robotic Process Automation is the technology that allows anyone today to configure computer software, or a “robot” to emulate and integrate the actions of a human interacting within digital systems to execute a business process. RPA robots utilize the user interface to capture data and manipulate applications just like humans do. They interpret, trigger responses and communicate with other systems in order to perform on a vast variety of repetitive tasks. Only substantially better: an RPA software robot never sleeps, makes zero mistakes and costs a lot less than an employee.

How is RPA different from other enterprise automation tools?

In contrast to other, traditional IT solutions, RPA allows organizations to automate at a fraction of the cost and time previously encountered. RPA is also non-intrusive in nature and leverages the existing infrastructure without causing disruption to underlying systems, which would be difficult and costly to replace. With RPA, cost efficiency and compliance are no longer an operating cost but a byproduct of the automation.

For more please click the following link:
https://www.uipath.com/rpa/robotic-process-automation
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Essential Skills for 21st Century / Academia not preparing youths rightly for job market: executives..........

« on: July 18, 2019, 02:12:00 PM »

Academia not preparing youths rightly for job market: executives..



Academic grading like CGPA has become a tool to reduce the number of jobseekers against the high demand because such achievement does not necessarily reflect the competency sought by companies, top private sector officials said yesterday.

There is a gap between students’ learning from universities and what the companies look for in jobseekers.

As a result, companies have to put in additional effort like arranging skills training programme or recruiting from abroad to meet their requirements, they said in a roundtable.

The Office of Professional Development of the Bangladesh Youth Leadership Centre (BYLC) and The Daily Star organised the discussion styled “Skill strategies for jobs: How Bangladesh can meet skills demand for a new era of work and technology while ensuring diversity” at The Daily Star Centre in Dhaka.

“Young people who are entering the job market have huge incapacity to learn,” said Mominul Islam, managing director of IPDC Finance.


The financial sector is rapidly changing around the world and Bangladesh may fail to keep pace because of lack of skills, he added.

Shaheen Khan, CEO of supermarket chain Meena Bazar, said during hiring they look for people with skills in supply chain management.

“But these things are not taught at universities.”

Khan said they tried to collaborate with some private universities to overcome the issues but could not succeed.

“So, what we had to do was recruiting people as management trainee and teach them from scratch,” he said.

Quazi Mohammad Shahed, CEO of Partex Star Group, said in his career he has seen people coming out of universities “with no clue on how work gets done”.

He recommended that business houses offer students part-time job at different stages of their university education so that they can graduate with some practical knowledge.

As a local business group they want to ensure diversity and for this they recruit from different universities and not only from Dhaka, Shahed added.

The nature of jobs is changing, which the academia does not take into account, said Eleash Mridha, managing director of Pran Group.

For example, basic knowledge on accounting and bookkeeping is no longer required because accounting software now takes care of it.

“I think day-to-day accounting, what we learnt during academic life, is gone now. What we need is someone who can design the software,” he said.

Hossain Khaled, managing director of Anwar Group, said in some of their recent recruitments they did not include CGPA (cumulative grade point average) as requirement but preferred experiences.

Organisations like the BYLC that work on skills development can collaborate with private companies on what kind of skills are being developed among students at present and what kind of job they can do.

A significant amount of remittance is going overseas because of a lack of middle management in the country.

“It’s because we cannot find people here,” Khaled added.

Maliha M Quadir, managing director of Shohoz, said as a new sector in Bangladesh they found it difficult to find people who could “think and adapt to new things”.

Employees of start-ups like Shohoz have to face new situations every day, she said.

“So people need to be very agile in their way of thinking, adapting and doing things,” she added.

“As a journalist I have learned over the many years that there is a part where many jobs are actually going after few people,” said Mahfuz Anam, editor and publisher of The Daily Star.

“But that’s at one level. But at a larger level that too few jobs are beingchased by three, four, five, ten times multiple of that job. So, that is a mismatch.”

The youth unemployment rate in Bangladesh is 12 percent, in contrast to 3.5 percent in India and 4.05 percent in China, according to the World Bank.

Digital journalism is the field where media houses like The Daily Star will find their future growth, he said.

“So those who want to be journalists in the future will have to be digital or multimedia journalists and they need to have digital skills as well as the ability to write,” he added.

The country’s education system does not equip the youth with critical thinking capacity, which is required for the 21st century, said Ejaj Ahmad, founder and president of the BYLC.

And this is where the BYLC comes in: it offers world-class curriculum to overcome such challenges, he said.

Syed Farhad Ahmed, managing director of Aamra Companies; Rashed Noman, country director of Augmedix Bangladesh; Manjur Mahmud, director and chief operating officer of DataSoft; and Rahel Ahmed, CEO of Prime Bank, also spoke, among others.

Source: The Daily Star
Link: https://www.thedailystar.net/business/news/academia-not-preparing-youths-rightly-job-market-executives-1773247

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2019 / Exploring Significant Family Income Ranges of Career Decision Difficulties......

« on: May 21, 2019, 03:58:21 PM »

Exploring Significant Family Income Ranges of Career Decision Difficulties of Adolescents in Bangladesh Applying Regression Techniques

Abstract:
Career Decision Making is essential part of human life. Most of the people are thinking about this since adolescence. Therefore, we should analyze significant features about career decision difficulties of adolescents in Bangladesh. The goal of this work to explore the most affected class of adolescents about career decision difficulties considering family income ranges in Bangladesh. In this situation, we gathered several records of high school going adolescents at Faridganj, Chandpur, Bangladesh using career decision difficulties questionnaire which was proposed by I. Gati et. al. Hence, several regression algorithms were considered for experimental analysis based on the characteristics of our primary career decision difficulties dataset. After that, these algorithms were applied into career decision difficulties dataset of adolescents and explored the best regression algorithm based on experimental results from them. Then, our selected best algorithm was implemented throughout different datasets (split from primary dataset) and interpreted their findings. Finally, we observed that middle level family income ranges (10000-21000 BDT) of adolescents were faced more difficulties to take proper decision about career than others. This analysis is suggested as a complementary tool for further psychological treatment about career decisions.

Authors:
Md. Shahriare Satu ; Sharif Ahamed ; Asive Chowdhury ; Md Whaiduzzaman

Source: IEEEXplore
Link: https://ieeexplore.ieee.org/document/8679415

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2019 / An Optimization Approach to Improve Classification Performance in Cancer and....

« on: May 21, 2019, 02:10:12 PM »

An Optimization Approach to Improve Classification Performance in Cancer and Diabetes Prediction

Abstract:
There are many destructive diseases in the world which cause rapid death by taking time to affect such as cancer and diabetes. They take a lot of time to spread, thus they are curable or somewhat scalable to a great extent if they are diagnosed soon after introduced into the human body. Research shows that almost all type of cancer can be cured if they are detected in the early stage. It is also true for diabetes as they can be controlled if they are detected at the right time. So, a prediction technique that takes help from the computer and processes data from affected user to detect possible contamination can be a great tool for assisting both the doctors and patients with these diseases. A challenge in the process is that the detection accuracy has to be acceptable in order to make the system a reliable one. In this study, we have analyzed medical data using several classification algorithms in order to optimize classifier performance for cancer and diabetes prediction.

Authors:
Mustakim Al Helal ; Atiqul Islam Chowdhury ; Ashraful Islam ; Eshtiak Ahmed ; Md. Swakshar Mahmud

Source: IEEEXplore

Link: https://ieeexplore.ieee.org/abstract/document/8679413

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2019 / Analyzing Performance of Different Machine Learning Approaches with Doc2vec ...

« on: May 21, 2019, 01:52:41 PM »

Analyzing Performance of Different Machine Learning Approaches with Doc2vec for Classifying Sentiment of Bengali Natural Language

Abstract:
Vector or numeric representation of text documents has been a revolution in natural language processing as it represents similar parts of text in such a way that they are very close to each other, making it very easy to classify or find similarities among them. These vectors also represent the way we use the words or parts of documents as well which helps finding similarity even between pair of words. While word2vec is such a technique that represents each word as a vector, doc2vec takes it to another level by representing a whole sentence or document as a vector. Being able to represent an entire document as a vector allows comparing a substantial number of words or sentences at a time which can save computational power as well as bandwidth. This relatively newer doc2vec technology has not yet been implemented for Bengali sentiment analysis and its feasibility is also unknown. In this study, we have trained a doc2vec model using a corpus constructed with 7,000 Bengali sentences. The model consists of two types of data differentiated by their polarity i.e. positive and negative. Later, we have employed several machine learning algorithms for comparing the accuracy of classification among which Bi-Directional Long Short-Term Memory (BLSTM) has obtained the highest accuracy of 77.85% along with precision, recall and F-1 score of 78.06%,77.39% and 77.72% respectively.

Authors:
Md. Tazimul Hoque ; Ashraful Islam ; Eshtiak Ahmed ; Khondaker A. Mamun ; Mohammad Nurul Huda

Source:
IEEEXplore

Link: https://ieeexplore.ieee.org/document/8679272

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2019 / Looking behind the Mask: A framework for Detecting Character Assassination via..

« on: May 21, 2019, 01:29:37 PM »

Looking behind the Mask: A framework for Detecting Character Assassination via Troll Comments on Social media using Psycholinguistic Tools

Abstract:
With the facilities of social media platforms like Facebook, Twitter, Google+, YouTube etc. people are capable of expressing their views & news, sharing moments via photos, liking, commenting and sharing others posts. The online social networks (OSNs) are not only giving positive supports to its users, but also creating opportunities to assassin personals by the trolls. Trolls are usually the OSN users who try to hide themselves while doing bad comments, false accusations, starting controversies, spreading fake news or rumors which could be considered as character assassination of individuals. The online behavior of an OSN user could be tracked via his/her digital footprints. Though tracking huge number of users who are generating billions of textual and image data every day, could be considered as a challenging task. In this paper, we have proposed a novel detection system for identifying character assassination from social media platforms. The proposed method first predicts the personality traits using users' textual data. Therefore, LIWC, SlangNet, SentiWordNet, SentiStrength, Colloquial WordNet has been utilized as psycholinguistic tool. LIWC-based feature engineering has been performed on the comments of the trolls as well as the victim user. SlangNet and Colloquial WordNet is used for detecting English slang words in the comments as it is evident that slangs are the basic communicative way to defame someone.

Authors:
Ahmed Al Marouf ; Rasif Ajwad ; Adnan Ferdous Ashrafi

Source: IEEEXplore
Link: https://ieeexplore.ieee.org/document/8679154

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2019 / Classification on BDHS data analysis: Hybrid approach for predicting pregnancy..

« on: May 21, 2019, 01:18:14 PM »

Classification on BDHS data analysis: Hybrid approach for predicting pregnancy termination

Abstract:
Pregnancy termination is a trivial anomaly for third world countries like Bangladesh. The greater aspiration of this research is to downturn the rate of pregnancy termination. This research finds out the attributes that contribute to pregnancy termination and leads to propose a hybrid of supervised machine learning approach for predicting “Pregnancy Termination” in Bangladesh. The Bangladesh Demographic and Health Survey (BDHS), 2014 dataset has been used to perform analysis containing two or more variables. This dataset is further reduced by analyzing attributes that exhibit information of interest to explore the current reasons for pregnancy termination. After extracting out the features of interest with the help of Weka provided feature ranking attribute evaluator, hybridization of supervised machine learning classifiers are done concerning the negatively biasedness of the dataset with respect to pregnancy termination. On this investigation, we've developed a hybrid approach with 67.2% accuracy considering the biasedness of the dataset which is relatively better than other classifiers in terms of performance metrics.

Authors:
Faisal Ahmed ; Md. Montasir Bin Shams ; Pintu Chandra Shill ; Majidur Rahman

Source: IEEEXpore
Link: https://ieeexplore.ieee.org/document/8679302

39

2019 / Dataset on the influence of software development agility on software firms' perf

« on: May 14, 2019, 02:31:52 PM »

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

40

2019 / A Comparative Analysis of Traditional and Modern Data Compression Schemes for La

« on: May 14, 2019, 02:30:07 PM »

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

41

2019 / Identifying Neuroticism from User Generated Content of Social Media based on Psy

« on: May 14, 2019, 02:28:49 PM »

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

42

2019 / Revisiting the Class Imbalance Issue in Software Defect Prediction

« on: May 14, 2019, 02:27:34 PM »

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

43

2019 / Prediction of possible asthma attack from air pollutants: Towards a high density

« on: May 14, 2019, 02:23:08 PM »

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

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2019 / Automated Prediction of Heart Disease Patients using Sparse Discriminant Analy..

« on: May 14, 2019, 02:21:51 PM »

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

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2019 / Runtime Optimization of Identification Event in ECG Based Biometric Authenticati

« on: May 14, 2019, 02:20:24 PM »

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