Digital Repository of Scholarly Resources
The Digital Repository of Scholarly Resources (DRSR) collects, organizes, preserves, provides access to, and promotes dissemination of the scholarly output of DAU Community.
Search the Repository ...
Featured Books
Recently Added
Firki Ni Dori
(Dhirubhai Ambani Institute of Information and Communication Technology, 2023) Trivedi, Jahnvi; Gupta, Anirban Dutta; Desai, Binita
Makar Sankranti, a joyous and vibrant festival celebrated across India, brings together communities to embrace the spirit of unity, renewal, and cultural traditions. One prominent aspect of this festival is the age-old tradition of kite flying, where the sky is adorned with colourful kites soaring high. However, amidst the exhilaration of this tradition, a dark and concerning issue has recently emerged � bird injuries caused by the use of Chinese threads and glass-coated threads. Last few years, there have been more cases of Chinese thread being used for flying kites.This thesis aims to shed light on the distressing issue of bird injuries during Makar Sankranti due to using Chinese threads (manjha) and glass-coated threads (dori) in kite flying. This represents an effort to examine the underlying reasons for this issue, how it affects ecology and the environment, and possible solutions that might decrease the harm to bird species.This research uses a multidisciplinary approach to understand the situation comprehensively. It includes ecological studies, data analysis, and interviews with veterinarians, Jiv Daya Charitable Trust members, and other NGOs working on the subject. By investigating the historical context and cultural significance of kite flying during Makar Sankranti, the thesis will delve into the reasons behind the popularity of Chinese threads and glass-coated threads, exploring the factors that have led to their widespread use despite the associated risks. This thesis will also examine the ecological effects of bird injuries, including potential ecosystem imbalances, loss of avian biodiversity, and disturbance of migratory patterns. The study will evaluate the effectiveness of current initiatives made by governmental and non-governmental organizations to address this issue and will pinpoint any implementation gaps and difficulties.The findings of this study will help decision-makers make well-informed choices. They will aid in developing strategies and regulations that will increase awareness, encourage safe kite-flying, and ensure the conservation of bird species during this festive season. The results of this study can provide important light on the social, cultural, and ecological aspects of bird injuries brought on by kite flying during Makar Sankranti and how these injuries affect our environment and way of life.
Analysing User Reviews for Evaluating Game Playability of Mobile Gaming Apps
(Dhirubhai Ambani Institute of Information and Communication Technology, 2023) Thakar, Swapnil; Tiwari, Saurabh
The playability of a game depends on the players� experience in terms of functionality,usability, and satisfaction. Mobile gaming has recently evolved because ofthe availability of suitable hardware, configurable mobile devices, and the abilityto download games from the Android and iOS platforms. Most online gamingstores allow customers to submit their reviews about gameplay, issues, and functionalitiespublicly. Game developers can better grasp such consumer issues byexamining player feedback and increasing how well-liked a game is among players.We have mapped the playability of S�nchez�s model with Schwartz�s theoryof human values and analyzed 20,346 user/player reviews from the top 15 gameapps in the Google Play Store. We have also created a labelled dataset of eachplayability category of S�nchez�s model. Finally, we applied a machine learningmodel to support the automatic classification of a review to a specific playabilitycategory violation. Our analysis shows that 30% of the reviews show human valuesviolations, consequently affecting game playability. We found that Socialism isthe most violated and Emotion is the least violated value category. We also foundthat only 18% of the user reviews received responses from the game app developersfor the value violations. Using fine-grained feature extraction, we found thetop 42 functionalities, issues, and concerns for the violations. The analysis resultsof our study give developers a foundation for creating apps that consider users�values for ensuring better playability of mobile game apps.
Mental Health Matters
(Dhirubhai Ambani Institute of Information and Communication Technology, 2023) Das, Tanaya; Sharma, Preethi; Mazumdar, Madhumita
Mental health is a major concern around the world, and India isnot far behind. When we look at developments in the field ofmental health, it appears that the pace is slow. According toexperts, Mental disorders affect 20% of young peopleworldwide. Only 7.3% of India's 365 million youth report suchissues. Although public stigma associated with mental healthproblems has a particular impact on young people seeking help,the extent of stigma among young people in India is unknown.Also, the language used to describe people suffering frommental health conditions in India is frequently negative andinsensitive. Such language contributes to the stigmatization ofmental health by reinforcing negative stereotypes. Language isone of the most powerful tools humans have, and it must beused with care when dealing with those who already feelmarginalized due to their mental health. Individuals withmental health issues are commonly referred to using terms suchas "pagal" and "paagalpan" (meaning "crazy"). Theconversation about mental health has grown in recent years,which is a good sign. Sadly, despite the growing buzz aboutmental health, the language being used is far from disabilityetiquette and lacks even basic sensitivity about how to describevarious mental health difficulties or the people who live withthem. These words not only contribute to the stigmasurrounding mental health, but also reinforce the notion thatpeople with mental illnesses are unpredictable, violent, anddangerous. Mental health is a state of well-being in which an individualrecognises his or her own abilities, can cope with normal lifestresses, can work productively, and can contribute to his or hercommunity. There are numerous mental illnesses, such asdepression, suicidal ideation, bipolar disorder, autism spectrumdisorder (ASD), anxiety disorder, schizophrenia, and others, allof which can have a negative impact on an individual'sphysical health and well-being.Some of the barriers to mental health research in India includea lack of adequate mental health professionals (MHPs),insufficient funding, insufficient research trainingopportunities, and the government's low priority for mentalhealth.The goal of this project is to illustrate how language is used todescribe people with mental illnesses suffer and how languagecreates stigma in mental health. As barriers exist in society, thestigma restricts one's ability to open up to others.
Feature for Live and Spoofed Speech Detection
(Dhirubhai Ambani Institute of Information and Communication Technology, 2023) Gupta, Priyanka; Patil, Hemant A.
The authorization to access specific information is given by a biometric system.Biometric systems are used for security purposes in a way that they prevent unauthorized access to important information or data (information privacy). The accessgranted by the biometric is done by capturing traits of humans, which make allhuman beings unique w.r.t. that particular trait. This thesis focuses on voicebased biometric systems, also known as Automatic Speaker Verification (ASV)systems, given that speech is the most natural and powerful form of communication used by humans to communicate with the outside world. It is the most intuitive, simple, and easy-to-produce characteristic. Since ASV systems have beenused for applications, such as in banking transactions and access to buildings associated with classified information, only authorized legitimate or genuine usersare granted access.ASV systems suffer from vulnerabilities to attacks and can be compromisedat various stages. The attacks may be categorized as direct and indirect attacks,depending on the extent of the attacker�s accessibility to the ASV framework. Besides, due to the recent commercial success of several Intelligent Personal Assistants (IPAs), also known as voice assistants, such as Speech Interpretation andRecognition Interface (SIRI), Amazon Alexa, Google Home, and so on, manyvoice-enabled devices in Internet of Things (IoT) have been commonly prone tospoofing attacks. To that effect, there is active research in the direction of designing countermeasure systems for ASV systems, particularly for spoofing attacks,namely, Speech Synthesis (SS), Voice Conversion (VC), and replay.This thesis is a humble attempt to alleviate some of the research gaps in designing features for countermeasure systems. In particular, this thesis proposesQuadrature Energy Separation Algorithm (QESA) in the light of incorporating thequadrature-phase component with the in-phase component of the signal. To thateffect, an existing feature set for replay Spoofed Speech Detection (SSD), namely,CFCCIF-ESA is extended to the CFCCIF-QESA feature set for enhanced performance of the countermeasure system. The performance of the proposed CFCCIFQESA feature set is evaluated on various datasets for various spoofing attacksgiven in the literature. Furthermore, the existing Linear Frequency Residual Cepstral Coefficients (LFRCC) feature set is optimized w.r.t. to its Linear Prediction(LP) order for the replay SSD task. In particular, it is found that the LP orderneeded for a good prediction of speech is not the same as that needed for thereplay SSD task. The resulting optimized LFRCC feature set is evaluated on theASVSpoof 2019 PA dataset. In addition to this, another feature, known as the uncertainty vector (u-vector), is developed from the Heisenberg�s uncertainty principle in the signal processing framework. The proposed u-vector is evaluated usingthe ASVSpoof 2017 dataset for replay attacks.Furthermore, in the direction to make countermeasure systems independent ofthe type of spoofing attack, features have been proposed for the Voice LivenessDetection (VLD) task. VLD is performed by the detection of pop noise which is thediscriminating acoustic cue present in live speech, produced due to the breathingeffect captured by the microphone when the speaker�s mouth is close to the microphone. The work on VLD in this thesis is based on two key hypotheses, namely,Parseval�s energy equivalence for STFT, CWT, and analytic CWT, whereas the second hypothesis is that the energy of pop noise decreases with the distance of a microphone from the speaker that is used to capture genuine speech. The proposedfeatures for VLD in this thesis are wavelet-based, wherein three wavelets are used,namely, Bump, Morlet, and Morse wavelet, where Morse wavelet is presented as asuperfamily of analytic wavelets, called as Generalized Morse Wavelets (GMWs).Detailed experimental analysis such as speaker-microphone proximity, the effectof phoneme type, and the effect of frequency range is studied.Apart from this, the security of speech data is also taken into account and thisthesis proposes an improved Voice Privacy (VP) system, which is based on Linear Prediction (LP) of speech. Furthermore, the VP system is studied along withthe attacker�s perspective using the target selection approach, and particularly,target selection w.r.t. twins is studied, wherein the most vulnerable twin-pair(i.e., target) is selected. Lastly, some of the proposed feature sets in this thesis arealso evaluated for tasks related to other Assistive Speech Technologies (AST) applications, such as the classification of healthy vs. pathological infant cries, anddysarthric severity-level classification.
Image Processing Using Digital Programming on FPGA
(Dhirubhai Ambani Institute of Information and Communication Technology, 2023) Kachchhi, Hardi; Agrawal, Yash; Khare, Manish
Image processing is a way to transform an image into digital form and after thatperform some operations on it that helps to improve images for human interpretationand extract useful information from it. It is essential for a wide range ofapplications. It allows for enhancing and restoring images, extracting featuresfor object recognition, compressing images for efficient storage and transmission,analyzing images for computer vision tasks, enabling medical diagnostics andtreatment, and interpreting data from remote sensing.Field Programmable Gate Array (FPGA) is preferred for image processing dueto their parallel processing capabilities, reconfigurability, low latency, energy efficiency,pipelining support, customization options, real-time processing capabilities,and ease of integration. These advantages make FPGAs a powerful tool forimplementing high-performance and efficient image processing solutions acrossvarious applications.To implement various filters in Image processing, we have developed a methodthat performs various edge detection techniques using FPGAs and displaying theimage on the monitor through Video Graphics Array (VGA)Controller. Edge detectionfilters and blurring filters are an indispensable part of Image processing invarious fields due to their ability to extract information, enhance visual quality,and enable decision-making based on visual data .