Mr Mudigonda Himansh, a 3rd-year BTech-CSE student, has presented a research paper in the IEEE International Conference on Innovations in Information Technology-2022 organised by IIIT Kottayam, Kerala India, in Feb-2022. The paper will be published in IEEE Xplore (Scopus indexed). Dr V M Manikandan, Assistant Professor in Computer Science and Engineering at SRM University-AP, is the co-author of the presented paper titled “A Statistical Study and Analysis to Identify the Importance of Open-source Software”.

Open-source software has picked up pace in the past decade with support from multinational conglomerates and huge open-source communities. We hear a lot about the success of many open-source projects, but we fail to understand how many do not make it. In this paper, Mr Himansh and Dr Manikandan understand the dynamics behind open-source software. They start with the need for open-source alternatives. Then look at a few concerns open-source software developers and maintainers face. Next, we would understand the various requirements of open-source software. Later, we would touch upon the different attributes that affect the selection of open-source software and the decisions to make while building general-purpose, open-source software. Then we would analyse the 5-determinants of open-source software success. Finally, we would look at the data collected from 482 data points from 24 countries and then analyse the data by forming graphs and charts.

This research provides the required knowledge to the open-source and non-open source software developers before-during-after development and production of the software or project. “Our future work is focused on the applications and predicting the scalability of large-scale OSS with machine learning,” says Dr Manikandan.

The healthcare system across the globe has been under colossal pressure since the emergence of novel coronavirus pandemic. The pandemic has also unveiled some of the greatest gaps in the existing healthcare systems. The research paper authored by Dr Ashok Kumar Pradhan and his PhD student E Bhaskara Santhosh, Department of Computer Science and Engineering, proposing a blockchain-based pandemic detection model was recognised by WHO and the paper was listed in COVID-19 Global literature on coronavirus disease. The paper titled “iBlock: An Intelligent Decentralised Blockchain-based Pandemic Detection and Assisting System” was published in collaboration with Saraju Mohanty, University of North Texas and Dr Venkata Ramana Badarla, Associate Professor, IIT Tirupati. The authors have expressed their deepest gratitude to Science and Engineering Research Board (SERB) for Grant number TAR/2019/000286 and SRM University-AP for supporting this work.

Abstract of the Research

The recent COVID-19 outbreak highlighted the requirement for a more sophisticated healthcare system and real-time data analytics in the pandemic mitigation process. Moreover, real-time data plays a crucial role in detection and alerting process. Combining smart healthcare systems with accurate real-time information about medical service availability, vaccination, and how the pandemic is spreading can directly affect the quality of life and economy. The existing architecture models become inadequate in handling the pandemic mitigation process in a real-time dataset. This is because, the present models are server-centric and controlled by a single party, hence to manage confidentiality, integrity, and availability (CIA) of dataset is a challenging task. Therefore, a decentralised user-centric model is essential, where the CIA of user data can be assured. In this paper, we have suggested a decentralized blockchain-based pandemic detection and assistance system named as (iBlock) that uses robust technologies like hybrid computing and IPFS to support system functionality. Moreover, a pseudo-anonymous personal identity is suggested using H-PCS and cryptography for anonymous data sharing. The distributed data management module guarantees data CIA, security, and privacy using cryptography mechanisms. Furthermore, it delivers useful intelligent information in the form of suggestions and alerts to assist the users. Finally, the iBlock reduces stress on healthcare infrastructure and workers by providing accurate predictions and early warnings using AI/ML technology.

Contributions of the Research

i) Proposes a novel architecture model for pandemic detection and alertness using a blockchain called as “iBlock”. It supports sharing of real-time data utilization.
ii) The proposed system introduces suitable privacy and security mechanisms to cover system-level data privacy and security.
iii) It also suggests a logical combination of blockchain and AI/ML on hybrid computing to support global level requirements during pandemic mitigation and alerting the systems.

Social Implications

The proposed system helps in the early detection of Covid-19 and encourages people to use their health data anonymously in pandemic detection and mitigation process. Moreover, iBlock maintains all crucial data on blockchain for future sustainable healthcare solutions. The majority of pandemic detection and alerting systems are limited to prediction, however iBlock further simplifies the area-labelling to cover area wise mitigation mechanisms. The classification of areas helps the government and healthcare organizations to plan sustainable preventive measures in a real-time scenario. It also helps in prediction of new cases and death rates with the aid of a dedicated AI/ML detection engine module. To motivate the people to share legitimate data, the proposed model even suggests a reward mechanism to influence the participants.

The research investigates the advanced possibilities in smart healthcare architecture to bring down the time and effort for pandemic mitigation activities. Read to know more.

“The correct analogy for the mind is not a vessel that needs filling, but wood that needs igniting” – Plutarch

Where would you go to get the most appropriate feedback to improve your learning? Whom would you approach? An active learner requires continuous assessment. Exposure to relevant remarks can make a significant impact in the learning output. Choosing the right source of feedback is important to locate your position in the learning ecosystem. This is where C-SMILE enters the frame.

The Department of Computer Science and Engineering is delighted to inform you that the patent application (202241010415) entitled ‘Classification of Student’s Misconceptions in Individualized Learning Environments (C-SMILE)’ got published. The patent application was submitted by Associate professor Dr Sobin C C and BTech final year student Meka Varsha as part of the Capstone Project.

C-SMILE is an innovative platform which allows students to take assessment and receive feedback based on their performance and misconceptions. This targets to refine their conceptual and individualised learning. The platform offers the benefits of automated identification of misconceptions and classification of their level of conceptual clarity. This eventually leads to pertinent feedbacks and ensures quality learning. It also helps engineering educators to classify their students into different categories based on their level of conceptual clarity. Short quizzes and multi-level assessments can utilise the objective of this platform.

Dr Sobin C C and Meka Varsha have collaborated with Mr Subheesh N P from IIT Madras and Mr Jahfar Ali from IIT Hyderabad as part of this work. The team has already published 2 conference papers. One of them is in the prestigious IEEE Global Engineering Education Conference (EDUCON 2022), which is the flagship conference of IEEE Education Society.

The researchers are now working on to extend this concept to incorporate Bloom’s taxonomy to formulate more specific questions based on their level in the cognitive domain.

Deaf and mute people have used sign language to communicate their thoughts and feelings for a long time. Since there is no universal sign language, the needy people use country-specific sign languages. An automated sign language recognition system is a universal solution to this impediment. Dr Manikandan V M, Assistant Professor, Department of Computer Science Engineering, and his student, Ms Bhavana Siddineni, have been working in this regard to ease the communication technology. They have published a chapter in the book, ‘Challenges and Applications for Hand Gesture Recognition’. The book is published by IGI Global Publishers, a leading international academic publisher. The chapter is titled “Recent Advancements in Design and Implementation of Automated Sign Language Recognition Systems”.

Sign language systems in practice are invariably specific to a territory. For example, American Sign Language (ASL) is popularly used by Americans, and Indian Sign Language (ISL) is commonly practised in India. Communication between two people who know the specific sign language is relatively easy. But, if a mute person wants to communicate with another person who is not familiar with sign language, it is a difficult task, and a sign language interpreter is required to translate the signs. This issue motivated the computer scientist to work on automated sign language recognition systems capable of recognizing the signs from specific sign languages and converting them into text information or audio so that the common people can understand them easily.

Through the proposal put forward in the publication, our researchers are planning to design and implement a reliable Automated Sign Language Recognition system in the future. This book chapter will be a useful reference for students who wish to start their research work in the domain of Automated Sign Language Recognition.

The Department of Computer Science and Engineering is pleased to announce the publication of three different patent applications from the department. The patent applications were submitted by the BTech students; Mr Kandala Sree Rama Murthy, Ms Padmaja Buggaveeti, Ms Yadlapalli Sai Harshini, Mr Jagruth K, Ms Shikha Chauhan, and Ms Ravi Srihitha under the guidance of Assistant Professor Dr V M Manikandan. They are making the institution proud with their passion and enthusiasm for the research domain.

The invention of a new scheme that will help to retrieve relevant videos from a large pool based on the given keyword is an impressive concept with societal relevance. Dr V M Manikandan and BTech students; Ms Yadlapalli Sai Harshini, Mr Jagruth K, Ms Shikha Chauhan, and Ms Ravi Srihitha got their patent application titled A novel video retrieval system and method based on textual information (application number: 202241002653) published.

The conventional video retrieval system uses the metadata to retrieve the appropriate videos. The new scheme processes the video and identifies the text information within the video, which will be compared with the given keyword. They introduced a scene change detection technique to select the frames for further processing in the new system to reduce the overall processing time.

The new scheme will help to retrieve appropriate educational videos from a large video pool based on the given keyword. The processing time is a significant concern in the scheme proposed. The researchers’ future work will be focused on improving the time complexity of the scheme.

The other research team invented a prediction error histogram shifting-based approach to hide secret messages in a cover image. The patent application submitted by Dr V M Manikandan and Third-year BTech-CSE Student, Ms Padmaja Buggaveeti, is titled A reversible data hiding system and method for image transmission (application number: 202241002654). The method ensures the lossless recovery of the original image during data extraction. The researchers considered the overflow issues in the histogram shifting approach and proposed an efficient method to handle this.

Reversible Data Hiding (RDH) provides a way to embed some data in a selected image so that in the future, the hidden data can be extracted along with the recovery of the original image. The new RDH scheme  invented by the researchers can be used in the healthcare sector to embed patient reports in medical images, or cloud service providers can use it to embed metadata in the digital data. Their future work will focus on designing and implementing robust reversible data hiding schemes capable of resisting attacks.

A system to facilitate secure transmission of an image along with embedded text (application number: 202241005221) is the third patent application that got published and was submitted by Dr V M Manikandan and Final year B.Tech-CSE Student Mr Kandala Sree Rama Murthy. The researchers invented a method to embed a message into a selected image during the image encryption process, which provides secure transmission of messages. The receiver will be able to extract the hidden message during decryption. The presented method is useful in medical image transmission to store patient details in the medical image.

The transmission of medical images and health reports from one hospital to another is widespread in the healthcare sector. Hospitals may want to handle many medical images and health reports every day and ensuring the one-to-one correspondence between them is a tedious task. The invented method will help embed health reports in medical images during encryption. The encrypted medical images (embedded with health reports) can be transmitted securely. The receiver will be able to extract the hidden message after medical image decryption. The researchers’ future work will focus on improving the invented method’s embedding capacity so that lengthy reports can be embedded into the medical images.