GR-136 - Students Certification Management (SCM): Hyperledger Fabric-Based Digital Repository

Abstract: The higher education sector has been heavily impacted financially by the economic downturn caused by the pandemic that has resulted a decline in student enrollments. Finding cost-effective novel technology for storing and sharing student\u27s credentials among academic institutions and potential employers is a demand. Within the current conventional approach, ensuring authentication of a candidate’s credentials is costly and time-consuming which gives burdens to thousands of prospective students and potential employees. As a result, candidates fail to secure opportunities for either delay or non-submission of credentials all over the world. Blockchain technology has the potential for students\u27 control over their credentials; degrees and transcripts for instance that will allow seamless streamlining of the sharing of educational records during changing and transferring schools, higher education, or even employment processes when need to show credentials. To implement the novel idea, we conduct a preliminary survey, study the existing applications, and investigate the feasibility of a Blockchain-based system to exploit the potential. Based on our findings, we propose a Students Certification Management System (SCM) by adopting Emerging Hyperledger Fabric that will offer a universal, tamper-evident, immutable, and secure educational certificate storing and sharing network. Our primary aim is to construct the proposed system into an educational certificate repository network using consortium blockchain for different entities including, (i) educational institutes to manage the network (ii) students and authorized third parties to access verifiable digital certificates and transcripts. Initially, we introduce an advanced architectural framework of the proposed system that has the potential in improving data flow between academic institutions, students, and potential employers. For ensuring transparency, each attempt in storing, sharing, and accessing credentials by the authenticated users within the proposed network shall be stored in the ledger which is secure and non-corruptible. Our future direction is to implement the architectural framework into an educational certification repository network within a private blockchain network.Department: Software Engineering and Game Design and DevelopmentSupervisor: Dr. Hossain Shahriar Dr. Maria ValeroTopics: Software Engineerin

GR-53 An Investigation on Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset and Its Effectiveness

Neurotechnology describes as one of the focal points of today’s research around the domain of Brain-Computer Interfaces (BCI). The primary attempts of BCI research are to decoding human speech from brain signals and controlling neuro-psychological patterns that would benefit people suffering from neurological disorders. In this study, we illustrate the progress of BCI research and present scores of unveiled contemporary approaches. First, we explore a decoding natural speech approach that is designed to decode human speech directly from the human brain onto a digital screen introduced by Facebook Reality Lab and University of California San Francisco. Then, we study a recently presented visionary project to control the human brain using Brain-Machine Interfaces (BMI) approach. We also investigate well-known electroencephalography (EEG) based Emotiv Epoc+ Neuroheadset and present experimental studies to identify six emotional parameters using brain signals by experimenting the neuroheadset among three human subjects.Advisors(s): Prof. Maria Valero Prof. Hossain ShahriarTopic(s): Other (explain in the comments section

GC-250 Object Detection and Tracking: Deep Learning-based Framework with Euclidean Distance, IoU, and Hungarian Algorithm

Object tracking is an important basis for the logistics industry where multiple packages are moved on conveyor belts at a time. Accurate datasets and efficient benchmarks are a few of the several problems for both object detection and tracking for training the deep learning-based framework. Preparing 100% accurate correspondence between objects throughout different frames by assigning human annotated unique_attributes to train framework efficiently over ground truth data. In this research, we develop an (i) OpenCV-based framework that allows the user to assign human-annotated identification between objects and (ii) a novel application for object detection and tracking. We utilize the assigned attributes to train the deep learning model accurately and adopt various evaluation parameters including euclidean distance, intersection over union (IoU), and scale-invariant feature transform (SIFT) to measure the accuracy of an object correspondence or tracking. We also adopt the Hungarian algorithm to increase the efficiency in determining correspondences between objects and apply our framework to human-annotated ground truth datasets comprising ~1,000 images and the same amount of JSON files. Our demonstration achieved 94.53 % accuracy in object detection, finding correspondence, and object tracking. In future studies, we are aiming to apply a neural network to draw a comparison of identified accuracy

GR-342 Integration of Blockchain in Computer Networking: Overview, Applications, and Future Perspectives for Software-defined Networking (SDN), Network Security and Protocols

The rapid advancement and increasing complexity of computer networks have created a need for robust, secure, and scalable solutions to manage and protect network resources. Blockchain, an emerging distributed ledger technology, offers enhanced security, transparency, and privacy preservation, making it a promising solution for addressing networking challenges. This paper presents a comprehensive survey of blockchain integration in computer networking, focusing on its potential applications, benefits, and future perspectives in Software-defined Networking (SDN), network security, and networking protocols. We identify that blockchain\u27s tamper-proof nature could significantly improve network security by mitigating risks associated with centralized control and single points of failure. The integration of blockchain in computer networking has the potential to increase trust and transparency among network participants, as it allows for secure, verifiable, and auditable transactions and communication. Blockchain also can streamline the management of Software-defined Networking (SDN) by enabling decentralized and automated network control, resource allocation, and orchestration. We also find that utilizing blockchain can address network challenges, such as mitigating DDoS attacks, enhancing intrusion detection and prevention, and securing routing protocols. However, we identify potential limitations of blockchain integration in computer networking, such as scalability challenges arising from the growing size of the distributed ledger and increasing network traffic. We emphasize the need for further research in optimizing consensus mechanisms, enhancing scalability and privacy preservation techniques interoperability, and facilitating standardization of networking protocols and practices

Compliance of IFRS 7: A Study on the State Owned Specialized Banks of Bangladesh

This study is aimed to scrutinize the existing reporting standard for the Specialized Banks of Bangladesh and find out the extent of compliance by them. To find out the degree of compliance the study has gone through the Financial Reports of the entire sample Banks. Very naturally, it is hoped that all of them are required to comply the standard to uphold the shareholder’s interest. Recognizing this aspect some specific IFRSs (International Financial Reporting Standards) have been prescribed for reporting to outsiders. One of which important standard IFRS # 7 (Financial Instruments: Disclosures) which was formulated by IASB in 2005 and obliged to comply from on after 1st January, 2007. The Institute of Chartered Accountants of Bangladesh (ICAB) prescribed to form on or after 1st January, 2010 in Bangladesh. Consider the importance of this standard securitization has been conducted on six Specialized Banks of Bangladesh.. The result of the study shows that all of the Specialized Banks compliance almost 55% of the IFRS # 7 requirements. Finally this study recommend on the degree of compliance for the Specialized Banks financial reporting. Keywords: Compliance, IFRS, Bank, Specialized Banks

Regulatory Compliance of IAS # 30 of the Private Commercial Banks Disclosure of Bangladesh: An Empirical Study on Ten Selected Banks

The paper is an effort to scrutinize the prevailing accounting standard for the private Commercial Banks in Bangladesh and find out the extent of compliance by them. Banking industry’s nature of operation is totally different from others. Recognizing this aspect some specific IASs (International Accounting Standards) have been prescribed for them. One of which is IAS#30 (Disclosures requirements for Banks and similar financial institutions). Institute of Chartered Accountants of Bangladesh (ICAB) prescribed to comply with IAS#30 from on or after 1st January, 2010. Hence compliance of IAS 30 (superseded as IFRS 7) is of importance here. Scrutinization has been operated on 10 private commercial Banks. As per requirement, all the Commercial Banks are required to comply with the standard to uphold the stakeholders’ interest .And the result of the study shows that all of the private Commercial Banks compliance almost 87.5% of the IAS#30 (IFRS 7) requirements. Finally this study recommend on the degree of compliance for the Commercial Banks financial reporting. Keywords: Compliance IAS, IFRS, Bank, Private Commercial Banks

Corporate Social Responsibility Practices of Private Commercial Banks in Bangladesh: A Case Study on Southeast Bank Ltd.

This paper explores how private commercial banks practices Corporate Social Responsibility (CSR) in Bangladesh in conserved the case of Southeast Bank Ltd.. In keeping with global movement, CSR is being seen as the source of new competition edge for the banking sectors of Bangladesh. Banks’ of Bangladesh practices CSR not only to improve community relations but also as source of significant commercial benefit. Southeast Bank Ltd. practices CSR under the rules and regulation of Bangladesh Bank. The study based on annual report of 2012 of Southeast Bank Ltd. This study shows that Southeast Bank expenses BDT36.85 million in the year 2012 at the area of education, health, community development, environmental issue, art and culture, sports etc..  Nevertheless, bank expenses highest amount in education sector through scholarship program in Bangladesh whereby school, college and university education tuition and expenses have fully paid for unconditionally.   The study can help banking manger’s understand what should be done for the benefits of customers and the community for sustainability.   Keywords - Corporate Social Responsibility, Commercial Bank, Donatio

GR-100 - Non-Invasive Monitoring of Human Hygiene using Vibration Sensor and Classifiers

Abstract: Personal hygiene is how people take care of their bodies. Maintaining hygiene practice reduces the spread of illness and the risk of medical conditions. With the current pandemic situation, practices like washing hands and taking regular showers have taken major importance among people, especially for senior populations that live alone at home. Having an understanding of the human hygiene habits of our seniors is fundamental to monitoring health conditions.This research work presents the concept and idea of a noninvasive monitoring system for human hygiene using only vibration sensors. The approach is based on a geophone, a digitizer, and a cost-efficient computer board (raspberry pi). We capture the vibration of the water flow while people perform activities in the bathroom (open faucet, flush toilets) and kitchen (open kitchen sink). Results show that our approach can distinguish from these different activities with an accuracy higher than 90%. With this approach, we hope to start a new tendency of monitoring people activities without using cameras or other privacy-invasive methods.Department: Information TechnologySupervisor: Dr. Maria ValeroTopics: IoT/Cloud/Networkin

Emotional Analysis of Learning Cybersecurity with Games using IoT

The constant rise of cyber-attacks poses an increasing demand for more qualified people with cybersecurity knowledge. Games have emerged as a well-fitted technology to engage users in learning processes. In this paper, we analyze the emotional parameters of people while learning cybersecurity through computer games. The data are gathered using a non-invasive Brain-Computer Interface (BCI) to study the signals directly from the users’ brains. We analyze six performance metrics (engagement, focus, excitement, stress, relaxation, and interest) of 12 users while playing computer games to measure the effectiveness of the games to attract the attention of the participants. Results show participants were more engaged with parts of the games that are more interactive instead of those that present text to read and type

Machine Learning-Oriented Predictive Maintenance (PdM) Framework for Autonomous Vehicles (AVs): Adopting Blockchain for PdM Solution

Autonomous Vehicles (AVs) refers to smart, connected and multimedia cars with technological megatrends of the fourth industrial revolution (Industry 4.0) and have gained huge strive in today\u27s world. AVs adopt automated driving systems (ADS) technique that permits the vehicle to manage and control driving points without human drivers by utilizing advanced equipment including a combination of sensors, controllers, onboard computers, actuators, algorithms, and advanced software embedded in the different parts of the vehicle. These advanced sensors provide unique inputs to the ADS to generate a path from point A to point B. Ensuring the safety of sensors by limiting maintenance costs has become a major challenge for AVs community. The predictive maintenance (PdM) approach has the potential to address the AVs failures. In this paper, we propose a novel, conceptual, and high-level domain-specific software architecture for the machine learning-oriented predictive maintenance (PdM) framework that shall enable predicting early malfunctioning, quality, safety, and performance deficiencies of AVs. The novel framework collects the data from sensors and major equipment and stores the collected data in immutable and transparent blockchain technology. Collected data shall be validated, extracted, and classified by adopting machine learning (ML) techniques. ML module shall predict the possible malfunctioning of the sensors while providing potential solutions from the stored data in the blockchain network. In this paper, our effort was to conduct a feasibility study, elicit and specify all the requirements for the proposed framework. In future research, we aim to extend the conceptual work and implement a prototype in real-world scenarios