Murshed Al Amin, MD. Jawad‑Al‑Mursalin Hoque, Zakia Nazzum, Md Abu Sayed, Sarker Tanveer Ahmed Rumee, and Moinul Islam Zaber. “Data Quality Assessment of Substation Data in Bangladesh: Insights from Handwritten Data Digitization”. 2023 10th International Conference on Power Systems (ICPS), Cox’s Bazar, Bangladesh, 13 – 15 December, 2023. https://www.icps23.com/

The assessment of power quality is vital for evaluating the existing state of the electricity supply, pinpointing its deficiencies, and guiding enhancements to guarantee a stable and consistent power supply, particularly in the face of rising demands from both industrial and residential sectors. In the context of Bangladesh, however, most substation data are still recorded manually, despite ongoing digitization efforts. This paper focuses on the quality of digitized transcription of handwritten substation data to determine its suitability for further analytical use. Our analysis revealed that the paper-based data from the substations exhibited significant gaps, undermining its reliability and accuracy. Through comprehensive evaluation, we concluded that the data, in its current state, is inadequate for in-depth analysis without the application of robust imputation methods. By tackling these challenges, our research aims to contribute to more informed decision-making and the efficient management of Bangladesh’s electrical infrastructure. This study not only diagnoses the current shortcomings in data quality but also lays the groundwork for future improvements in the country’s approach to energy data management.

Shamim Bin Zahid, Aishwarya Ghosh Bristy, Sarker Tanveer Ahmed Rumee, and Moinul Islam Zaber. “Safeguarding User Privacy through Effective Information Disclosure Summary from the Software End-User License Agreements(EULAs)”. 2023 5th International Conference on Informatics, Electronics and Vision (ICIEV), London, UK, 26 – 29 October, 2023. http://cennser.org/ICIEV/

An End-User License Agreement (EULA), a significant precursor to modern privacy policies, are essential documents that communicate with people about how their personal information is collected, used, and protected by organizations/companies, especially through software. EULAs serve as a legal framework to govern product usage. However, the current standard of representing privacy policy documents is often composed of legal jargon, which makes them lengthy, complex, and challenging for the average user to comprehend. Not everything mentioned in a protracted EULA document is meant to be vital for a user’s information safety. But proper representation of the document is crucial. There has been research on standardizing and summarizing privacy policies, A properly usable representation is yet to be standardized. This paper investigates a novel strategy to summarize the privacy-sensitive information from the EULA of a software or web application which involves exploring security critical keywords in the EULA and finding the correlation and meaning of such sentences in perspective of sensitive data access and disclosure. A detailed use experiment was performed and the findings show that the proposed methodology can better inform the users about their private data access by the applications.

Firoza Tabassum, Humaira Islam, Matin Saad Abdullah and Moinul Zaber. “Network Dynamics of Bangladesh Inland Waterways Augmented with Complex Network Analysis of Vessels and Connectivity”. 2023 5th International Conference on Informatics, Electronics and Vision (ICIEV), London, UK, 26 – 29 October, 2023. http://cennser.org/ICIEV/

The Bengal Delta is considered as world’s largest delta with the three largest rivers flowing across Bangladesh. As the cheapest medium of transportation, inland waterways vehicles play the most significant role in connecting the habitats making them the most economically significant means for goods and human transportation. To understand the inland waterway structure, complex network analysis has proven to be an important tool through which we can identify port connectivity, bottlenecks, significant ports, and clusters. Several authors have conducted such analysis to ascertain various networks including transportation and port connectivity networks. However, data scientific research works on connectivity networks focusing on the developing world are scarce. In previous research, researchers analyzed on port connectivity of districts indicating the structure of the river-based connectivity looking from the administrative perspective. However, the analysis lacked more information such as vessel frequency from the ports in the districts. Vessel frequency is necessary to understand the significance of the ports. The analysis of this paper is based on a uniquely developed dataset of ports and their vessel frequency giving a more complete picture of port conditions and characteristics of inland waterways of Bangladesh. Our analysis identifies the important ports and the dependency of the network on one city- Dhaka capital of Bangladesh. These findings can be helpful in understanding and modeling how the migration of a vast number of economically challenged populations actually happens. This can also help to ascertain many other socio-economic factors that are affected by inland waterways transportation, such as poverty, local business and trades, and transportation of goods and humans.

Md. Mehedi Hasan, Sarker Tanveer Ahmed Rumee, Moinul Islam Zaber. “An Experimental Study on Speech Emotion Recognition for Bangla Language”. 2023 5th International Conference on Informatics, Electronics and Vision (ICIEV), London, UK, 26 – 29 October, 2023. http://cennser.org/ICIEV/

Embedding speech recognition has increased the usability of artificial intelligence (AI) applications (e.g. smart home, chatbots, etc.). Recent research works have focused on increasing usability further enabling personalized applications. Speech emotion recognition (SER) is one of the building blocks of speech-enabled personalized systems. However, recognition of emotion from speech is complex as the intensity of the emotion, also known as arousal, can vary from person to person and change within a very short time. Data is another major challenge, especially for low-resource languages such as Bangla. To our knowledge, only two datasets are available open-sourced for Bangla speech emotion recognition. Considering the gaps, we have decided to focus on this problem. Our goal is to study the existing system, experiment, and evaluate the usability of available resources. In this work, we are focusing on applying deep learning techniques to available data resources in the Bangla language and evaluating their performance to find suitable techniques for Bangla SER. We have utilized two publicly available datasets, SUBESCO and BanglaSER. We have used a set of 11 different features as the audio representation. Convolutional neural networks and artificial neural networks have been used as deep learning techniques for this study. We have performed three types of experimental study on three different setups of datasets. We have achieved more than 70% accuracy for all setups without cross-validation. After cross-validation, we have achieved 68.08% average accuracy on setup 3 (only BanglaSER). After regularization with cross-validation, we have achieved 62.62% average accuracy on setup 3. We have evaluated the performance of SUBESCO and BanglaSER for other setups and approaches. This work will summarize the current state of Bangla SER which will help research communities to improve the existing system accordingly.