This is to inform Ashfaq and Shochcho that two of our undergrad research students got selected for the ACM SIGCHI Winter School. Only 5 applicants received travel grants and Ashfaq is one of them.
We are happy to announce that one of our papers, “An Integrated System for Stroke Rehabilitation Exercise Assessment using KINECT v2 and Machine Learning, “ has been accepted and presented at the “15th International Conference on Intelligent Human-Computer Interaction, South Korea”. This work is an outcome of a CCDS project on “Automated and Computerized Rehabilitation Systems for Stroke Patients”. This work is jointly supervised by CCDS professors Dr. M Ashraful Amin, Dr. Amin Ahsan Ali, Dr. A K M Mahbubur Rahman, and Dr. Ashraful Islam and collaborated with Eshtiak Ahmed from Tampere University, Finland.
In this work, a home-based rehabilitation system is designed to address these challenges by leveraging the capabilities of the KINECT v2 3D camera. Our system, equipped with a graphical user interface (GUI), allows patients to perform, monitor, and record their exercises. By utilizing advanced machine learning algorithms, specifically G3D and disentangled multi-scale aggregation schemes, the system can analyze exercises, generating both primary objective (PO) and control factor (CF) scores out of 100.
We are happy to announce that five of our papers have been accepted in “the first Bangla Language Processing (BLP) Workshop will be co-located with EMNLP in Singapore. Papers are titled with:
We are happy to announce that one of our papers titled “Early Stage Design of a mHealth Intervention for Managing Gestational Diabetes Mellitus in Bangladeshi Women”, has been accepted and presented at “25th International Conference on Human-Computer Interaction, Denmark (Acceptance Rate: 26.42%; Ranked 18th for combined HCI Journal and Conference ranking by Google Scholar)”. This work was a joint collaboration between CCDS professor Dr. Ashraful Islam and collaborators from the University of Wisconsin, USA and Tampere University, Finland.
In this work, the authors propose an early-stage design of user interfaces (UIs) for a mobile health (mHealth) intervention using the Bengali language that allows users to input daily measures of blood glucose, weight, and other GDM-related health data. The intervention is designed to provide users with personalized feedback based on their input and the necessary coaching for managing GDM. It also reminds users to take medication if prescribed by their doctors. The app has six key features: blood glucose tracking, food logging, medication reminders, activity tracking, educational resources, and personalized recommendations.
We are happy to announce that one of our papers titled “Low-cost relay selection in multihop cooperative networks”, has been accepted and published in “Journal of King Saud University – Computer and Information Sciences (Q1, Impact Factor: 6.9)“. This work was a joint collaboration between CCDS professors Dr. Md Zahangir Alam and Dr. Ashraful Islam and collaborators from Department of CSE, IUB. The paper can be read at https://doi.org/10.1016/j.
In this work, the authors presented algorithmic strategies to simplify a multihop parallel single-input single-output (SISO) relay network into a series multi-hop network by finding the best path having the maximum received signal-to-noise ratio (SNR). The best relay selection by using dynamic programming search entails high computations and large memory requirements, as well as involves the full CSI information, making this approach impractical for large-scale networks. The goal of the proposed low-cost near-optimal routing strategy in this work is to provide close to optimal performance with much less complexity compared to traditional routing.
We are happy to announce that one of our papers titled “A Framework for Lung Cancer Detection at Early Stages with IoT and Decision Support System”, has been accepted in “IEEE International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT)”, Bahrain. This work was a joint collaboration between CCDS professor Dr. Ashraful Islam and collaborator from the University of Information Technology & Sciences, Bangladesh.
In this work, an innovative framework based on a decision support system (DSS) and IoT is proposed to facilitate faster and earlier detection of lung cancer to assist physicians in making informed treatment recommendations following the detection. By integrating IoT with a DSS, this paper advocates for improved early detection of lung cancer, leveraging insights from existing literature on machine learning (ML), deep learning (DL), and IoT-based diagnosis of lung cancer.
We are happy to announce that one of our papers titled “A Comparative Overview of Local Mobile Financial Services Smartphone Apps Available in Bangladesh”, has been accepted in “IEEE 64th International Scientific Conference on Information Technology and Management Science (ITMS 2023)”, Latvia. This work is completely researched by the CCDS professor Dr. Ashraful Islam and the 2nd year BSc in CSE students of IUB.
In this work, the authors conducted a comprehensive comparative analysis of the various official MFS apps (n=13) available in Bangladesh, evaluating their features, functionalities, operational aspects, security measures, and overall facilities. The comprehensive exploration identified 18 distinct elements spanning four primary themes that stand out in the functionality of these apps: (1) Money Transfers and Transactions, (2) Financial Services and Bill Payments, (3) Service-related Charges, and (4) Consumer Finance.
We are happy to announce that one of our papers titled “Initial Development and Performance Evaluation of a Bengali Voice-Operated Virtual Assistant for Personal Computer Control”, has been accepted in “IEEE 64th International Scientific Conference on Information Technology and Management Science (ITMS 2023)”, Latvia. This work was a joint collaboration between CCDS professor Dr. Ashraful Islam and collaborators from the University of Louisiana at Lafayette, USA.
In this work, the authors conducted a preliminary development and performance evaluation of a personal computer assistant designed for voice-operated interaction in Bengali. A bespoke phonetic grammar has been devised to map Bengali phonemes onto English representations, and an algorithm has been developed to mitigate the confusion of the machine in recognizing the same type of phonetics in the language, which helps to enhance the precision in comprehending Bengali commands.
We are happy to announce that one of our papers titled “EDAL: Entropy based Dynamic Attention Loss for HateSpeech Classification”, has been accepted in the “37th Pacific Asia Conference on Language, Information and Computation”.
In this work, the authors introduce the “Entropy-based Dynamic Attention Loss” (EDAL) to enhance model interpretability by incorporating an additional attention layer. EDAL encourages attention scores that provide valuable insights and boosts the performance of pretrained models during fine-tuning for downstream tasks. We conduct extensive experiments on six diverse datasets, confirming that EDAL effectively enhances classification performance while maintaining interpretability. Additionally, experiments with various pretrained models demonstrate EDAL’s significant performance improvements during fine-tuning. In summary, EDAL holds promise for creating more transparent and reliable hate speech classifiers, contributing to a safer online environment.
