Browsing by Author "Kabir, S. Rayhan"

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A Cloud of Things (CoT) Approach for Monitoring Product Purchase and Price Hike
(Lecture Notes in Networks and Systems, Springer, 2020-05-15) Sadeq, Muhammad Jafar; Kabir, S. Rayhan; Haque, Rafita; Ferdaws, Jannatul; Akhtaruzzaman, Md.; Forhat, Rokeya; Allayear, Shaikh Muhammad
Price hike is common and one of the major issues all over the world. The prices of daily necessities are increasing day by day. Many shops, restaurants and transport systems are charging extra price from the customers over the products’ expected or maximum retail price. Moreover, in special occasions, such as festivals, the sellers take high price from customers. Furthermore, unauthorized VAT or other taxes are charged on products on which such taxes are exempted by the government. This study proposes a Cloud of Things (CoT)-based model for monitoring the products’ price during transactions, where a cloud server maintains historical pricing data and maximum retail prices. Two algorithms run on the server based on live invoice data from sellers and customer feedback to detect unfair price hike.
A computational technique for intelligent computers to learn and identify the human's relative directions
(IEEE Xplore, 2018-06-21) Kabir, S. Rayhan; Allayear, Shaikh Muhammad; Alam, Mirza Mohtashim; Munna, Md Tahsir Ahmed
The most broadly perceived relative directions are right, left, up, down, backward and forward. This research paper presents a new computational technique to learn human's relative directions, where one intelligent computer can learn any human's right, left, up, down, backward and forward or different relative directions. The present paper portrays models describing the essential structures of relative direction learning process between human and intelligent machine. We developed two proficient algorithms for solving this approach. In our experiment we propose Human Relative Direction Learning (HRDL) algorithm for learning human's relative directions and Human Direction Identification (HDI) algorithm for tracking any human position and identity human's relative directions from different direction points. Full Text Link: http://doi.org/10.1109/ISS1.2017.8389336
Identification of Construction Era for Indian Subcontinent Ancient and Heritage Buildings by Using Deep Learning
(Scopus, 2021) Hasan, Md. Samaun; Kabir, S. Rayhan; Akhtaruzzaman, Md.; Sadeq, Muhammad Jafar; Alam, Mirza Mohtashim; Allayear, Shaikh Muhammad; Uddin, Md. Salah; Rahman, Mizanur; Forhat, Rokeya; Haque, Rafita; Arju, Hosne Ara; Ali, Mohammad
The Indian subcontinent is a south geographic part of Asia continent which consists of India, Bangladesh, Pakistan, Sri Lanka, Bhutan, Nepal, and Maldives. Different rulers or the empire of different periods have built various buildings and structures in these territories like Taj Mahal (Mughal Period), Sixty Dome Mosque (Sultanate Period), etc. From archaeological perspectives, a computational approach is very essential for identifying the construction period of the old or ancient buildings. This paper represents the construction era or period identification approach for Indian subcontinent old heritage buildings by using deep learning. In this study, it has been focused on the constructional features of British (1858–1947), Sultanate (1206–1526), and Mughal (1526–1540, 1555–1857) periods’ old buildings. Four different feature detection methods (Canny Edge Detector, Hough Line Transform, Find Contours, and Harris Corner Detector) have been used for classifying three types of architectural features of old buildings, such as Minaret, Dome and Front. The different periods’ old buildings contain different characteristics of the above-mentioned three architectural features. Finally, a custom Deep Neural Network (DNN) has been developed to apply in Convolutional Neural Network (CNN) for identifying the construction era of above-mentioned old periods.
Identification of Construction Era for Indian Subcontinent Ancient and Heritage Buildings by Using Deep Learning
(Springer, 2020-10-22) Hasan, Md. Samaun; Kabir, S. Rayhan; Akhtaruzzaman, Md.; Sadeq, Muhammad Jafar; Alam, Mirza Mohtashim; Allayear, Shaikh Muhammad; Uddin, Md. Salah; Rahman, Mizanur; Forhat, Rokeya; Haque, Rafita; Arju, Hosne Ara; Ali, Mohammad
The Indian subcontinent is a south geographic part of Asia continent which consists of India, Bangladesh, Pakistan, Sri Lanka, Bhutan, Nepal, and Maldives. Different rulers or the empire of different periods have built various buildings and structures in these territories like Taj Mahal (Mughal Period), Sixty Dome Mosque (Sultanate Period), etc. From archaeological perspectives, a computational approach is very essential for identifying the construction period of the old or ancient buildings. This paper represents the construction era or period identification approach for Indian subcontinent old heritage buildings by using deep learning. In this study, it has been focused on the constructional features of British (1858–1947), Sultanate (1206–1526), and Mughal (1526–1540, 1555–1857) periods’ old buildings. Four different feature detection methods (Canny Edge Detector, Hough Line Transform, Find Contours, and Harris Corner Detector) have been used for classifying three types of architectural features of old buildings, such as Minaret, Dome and Front. The different periods’ old buildings contain different characteristics of the above-mentioned three architectural features. Finally, a custom Deep Neural Network (DNN) has been developed to apply in Convolutional Neural Network (CNN) for identifying the construction era of above-mentioned old periods.
Integration of Block chain and Remote Database Access Protocol-Based Database
(2021) Sadeq, Muhammad Jafar; Kabir, S. Rayhan; Akter, Marjan; Forhat, Rokeya; Haque, Rafita; Akhtaruzzaman, Md.
Many companies are relying on software to manage their businesses. Usually, the software, especially those used by smaller companies, is not secure against unauthorized or unethical data manipulation on the database level. This paper recommends and demonstrates the use of block chain for securing small enterprises against hacking by alerting the management whenever a change is made to the data without using the authorized channels. This is done through block chain technology’s inherent hash replication and mining algorithm. The paper shows an application where this idea has successfully been implemented for a desktop application built upon a remote database access (RDA) protocol-based relational database management system (RDBMS) such as remote MySQL and remote Oracle database.
Integration of Blockchain and Remote Database Access Protocol-Based Database
(Fifth International Congress on Information and Communication Technology, Springier, 2020-10-10) Sadeq, Muhammad Jafar; Kabir, S. Rayhan; Akter, Marjan; Forhat, Rokeya; Haque, Rafita; Akhtaruzzaman, Md.
Many companies are relying on software to manage their businesses. Usually, the software, especially those used by smaller companies, is not secure against unauthorized or unethical data manipulation on the database level. This paper recommends and demonstrates the use of blockchain for securing small enterprises against hacking by alerting the management whenever a change is made to the data without using the authorized channels. This is done through blockchain technology’s inherent hash replication and mining algorithm. The paper shows an application where this idea has successfully been implemented for a desktop application built upon a remote database access (RDA) protocol-based relational database management system (RDBMS) such as remote MySQL and remote Oracle database.
Modeling the Role of C2C Information Quality on Purchase Decision in Facebook
(The International Federation for Information Processing, 2018-10-12) Haque, Rafita; Mahmud, Imran; Sharif, Md. Hasan; Kabir, S. Rayhan; Chowdhury, Arpita; Akter, Farzana; Akhi, Amatul Bushra
A market which provides an innovative way to allow customers to interact with each other called Customer-to-customer (C2C) market. In C2C communications, online communities play an important role in decision making to buy a product. This investigation develops a research model for online communities of Facebook commerce (F-Commerce) in Bangladesh region, which is based on Information Adoption Model (IAM). This study exhibits a model to influences of C2C communication on Bangladeshi consumers’ purchase decision in the online communities of F-Commerce. The proposed model used the Partial Least Squares (PLS) technique to test 120 effective survey data. This survey data has been taken from the Bangladesh Facebook users and strongly involved in product buy-sell at F-Commerce. The analyzed results show that Argument Quality (AQ), Source Credibility (SC) and Tie Strength (TS) positively influence Purchase Decision (PD) through Product Usefulness Evaluation (PUE). In addition, Tie Strength exhibits difference effect on Product Usefulness Evaluation between the contexts of consumers communicating with virtual consumers relationships. Theoretical and executive implications are discussed for constructing our proposed model.
Relative Direction: Location Path Providing Method for Allied Intelligent Agent
(Springer Nature, 2018-10-31) Kabir, S. Rayhan; Alam, Mirza Mohtashim; Allayear, Shaikh Muhammad; Munna, Md Tahsir Ahmed; Hossain, Syeda Sumbul; Rahman, Sheikh Shah Mohammad Motiur
The most widely recognized relative directions are left, right, forward and backward. This paper has presented a computational technique for tracking location by learning relative directions between two intelligent agents, where two agents communicate with each other by radio signal and one intelligent agent helps another intelligent agent to find location. This proposed method represents an alternative approach to GSM (Global System for Mobile Communications) for the AI (Artificial Intelligence), where no network may not be available. Our research paper has proposed Relative Direction Based Location Tracking (RDBLT) model for understanding how one intelligent agent assists another intelligent agent to find out the location by learning and identifying relative directions. Moreover, three proficient algorithms have been developed for constructing our proposed model.