Neuro Imaging Papers & Publications

India is a country of immense diversity. It is home to people of many different racial, languages, ethnic, religious, and national backgrounds. Groups of people in India differ from each other not only in physical or demographic characteristics but also in distinctive patterns of behavior and these patterns are determined by social and cultural factors like language, region, religion, and caste. Apart from behaviour, economic development, level of education and political culture of the people in various social segments differ from region to region. More you can say that economy and cultures have been enriched by the contributions of migrants from round the globe. In an increasingly globalised world, migratory movements is continuously shaping the countries all over the world. Some countries like India and Ireland, which set the example of economic development and social integration, have the positive impact of the migration by globalisation and some countries like USA, which recently witness racism, xenophobia and discrimination have the negative impact on the migrants. It does not mean India do not face fragmentation and USA do not have cohesion. USA have many stories which show successful integration process, that facilitated the lives of immigrant communities, but being a developed country it still suffers from cultural alienation. In these countries, borders are built within borders to create cultural divides that do not allow people to integrate. Recently, this problem has become more prominent due to the rise of terrorism, clash of cultures in the world, leading to the glorification of stereotypes. People are becoming less accepting towards anyone who does not belong to their region. Migration does not stop after people move from one place to another place. The main question start after that ‘now what’ they will do. That is why this topic needs to be discussed thoroughly in order to find better solutions. This paper will begin with an analysis of different approaches to Migration, discuss the target groups for integration policies, provide indicators of the current situation of migrants and proceed to an analysis of integration tools: legislation, social policies and participatory processes. It will focus not only on the impact of migration but also on social integration, mix culture like indo-western culture in a comparative basis.

Ekta Meena

India is a country of immense diversity. It is home to people of many different racial, languages, ethnic, religious, and national backgrounds. Groups of people in India differ from each other not only in physical or demographic characteristics but also in distinctive patterns of behavior and these patterns are determined by social and cultural factors like language, region, religion, and caste. Apart from behaviour, economic development, level of education and political culture of the people in various social segments differ from region to region. More you can say that economy and cultures have been enriched by the contributions of migrants from round the globe. In an increasingly globalised world, migratory movements is continuously shaping the countries all over the world. Some countries like India and Ireland, which set the example of economic development and social integration, have the positive impact of the migration by globalisation and some countries like USA, which recently witness racism, xenophobia and discrimination have the negative impact on the migrants. It does not mean India do not face fragmentation and USA do not have cohesion. USA have many stories which show successful integration process, that facilitated the lives of immigrant communities, but being a developed country it still suffers from cultural alienation. In these countries, borders are built within borders to create cultural divides that do not allow people to integrate. Recently, this problem has become more prominent due to the rise of terrorism, clash of cultures in the world, leading to the glorification of stereotypes. People are becoming less accepting towards anyone who does not belong to their region. Migration does not stop after people move from one place to another place. The main question start after that ‘now what’ they will do. That is why this topic needs to be discussed thoroughly in order to find better solutions. This paper will begin with an analysis of different approaches to Migration, discuss the target groups for integration policies, provide indicators of the current situation of migrants and proceed to an analysis of integration tools: legislation, social policies and participatory processes. It will focus not only on the impact of migration but also on social integration, mix culture like indo-western culture in a comparative basis.

Ekta Meena

In this paper, investigations are made to analyze the human body temperature during wound healing process due to surgery. Wound is considered after the skin graft. Skin graft is a technique used in plastic surgery. Skin is the first line of defense between the human and environment, it is very susceptible to damage. Internal body or core temperature (Tb) is one of the clinical vital signs along with pulse and respiratory rates. Any disturbance in body temperature will drive complexities in wound healing process. These studies are important in the mechanism of establishing the limits of thermal regulation of human body during the healing process in different situations and conditions. The Finite element method is used to analyze tissues temperature for normal tissues (donor site) and abnormal tissues (tissues after surgery). Appropriate boundary conditions have been framed. Numerical results are obtained using Crank Nicolson Method.

Manisha Jain

Physically unclonable function (PUF) is a hardware security module preferred for hardware feature based random number and secret key generation. Security of a cryptographic system relies on the quality of the challenge-response pair, it is necessary that the key generation mechanism must unpredictable and its response should constant under different operating condition. Metastable state in CMOS latch is undesirable since it response becomes unpredictable, this feature used in this work to generate a unique response. A feedback mechanism is developed which forces the latch into the metastable region; after metastable state, latch settle to high or state depends on circuit internal condition and noise which cannot be predicted. Obtained inter hamming variation for 8 PUF is 51% and average intra hamming distance is 99.76% with supply voltage variation and 96.22% with temperature variation.

Abhishek Kumar

One of the unique features of Indian society is prevalence of caste system which was originated thousands of years back to demarcate the people engaged in different occupation or jobs. Initially it was not much rigid but gradually people belonging to upper castes for their own selfish means to maintain their monopoly made this arrangement hereditary and started treating people of lower castes disgracefully. For preservation of this system, people started controlling their women to prevent inter-caste marriages and the concept of endogamy came up. This robbed away many types of freedom from women. For women belonging to lower castes, this situation is worse as they are doubly subjugated on the basis on caste as well as gender. Men belonging to their own caste treat them as secondary beings. This paper throws light on this intersection. How intersection of these two kinds of inequalities place them at the lowest position in Indian society. Dr. B.R. Ambedkar rises as their leader who all his life worked for empowerment of downtrodden section of society. He argues that education is the primary tool for evading these differences among people. He further emphasizes to adopt the concept of exogamy to break the backbone of Indian caste system and to immediately leave a religion or culture which legitimizes such system of inequality among people of the same land.

Swati sharma

One of the unique features of Indian society is prevalence of caste system which was originated thousands of years back to demarcate the people engaged in different occupation or jobs. Initially it was not much rigid but gradually people belonging to upper castes for their own selfish means to maintain their monopoly made this arrangement hereditary and started treating people of lower castes disgracefully. For preservation of this system, people started controlling their women to prevent inter-caste marriages and the concept of endogamy came up. This robbed away many types of freedom from women. For women belonging to lower castes, this situation is worse as they are doubly subjugated on the basis on caste as well as gender. Men belonging to their own caste treat them as secondary beings. This paper throws light on this intersection. How intersection of these two kinds of inequalities place them at the lowest position in Indian society. Dr. B.R. Ambedkar rises as their leader who all his life worked for empowerment of downtrodden section of society. He argues that education is the primary tool for evading these differences among people. He further emphasizes to adopt the concept of exogamy to break the backbone of Indian caste system and to immediately leave a religion or culture which legitimizes such system of inequality among people of the same land.

Swati sharma

The subjective experience of consciousness, a cornerstone of human existence, is profoundly disrupted in disorders of consciousness (DOC) arising from severe brain injuries, spanning-states from coma to the minimally conscious state. A significant challenge in clinical practice is the phenomenon of covert consciousness, in which individuals may retain awareness despite the absence of overt behavioral responsiveness. Diagnosis based solely on observable behavior is inherently limited by factors such as co-occurring motor impairments, the fluctuating nature of consciousness, and subjective interpretation, potentially leading to misclassification. To overcome these limitations, neuroscientific methodologies have advanced significantly. To address these limitations, neuroscientific methods have advanced considerably. Functional magnetic resonance imaging (fMRI) and positron emission tomography (PET) provide objective evidence of preserved brain activity and cognitive processing, enabling detection of willful modulation and offering prognostic insight. Electrophysiological techniques—including electroencephalography (EEG), event-related potentials (ERPs), transcranial magnetic stimulation combined with EEG (TMS-EEG), and advanced downstate analysis—further reveal dynamic neural patterns indicative of residual awareness. The detection of covert consciousness has profound ethical, clinical, and societal implications. It necessitates a re-examination of patient rights, end-of-life decision-making, the use of brain-computer interfaces, and societal conceptions of personhood. This evolving understanding mandates a shift towards integrating objective neuroscientific assessments with compassionate, person-centered care, aiming to preserve dignity and navigate the complex ethical landscape of severe brain injury.

Mostafa Eissa

This paper proposes EPyNet, a deep learning architecture designed for energy reduced audio emotion recognition.In the domain of audio based emotion recognition, where discerning emotional cues from audio input is crucial, the integration of artificial intelligence techniques has sparked a transformative shift in accuracy and performance.Deep learning , renowned for its ability to decipher intricate patterns, spearheads this evolution. However, the energy efficiency of deep learning models, particularly in resource-constrained environments, remains a pressing concern. Convolutional operations serve as the cornerstone of deep learning systems. However, their extensive computational demands leading to energy-inefficient computations render them as not ideal for deployment in scenarios with limited resources. Addressing these challenges, researchers came up with one-dimensional convolutional neural network (1D CNN) array convolutions, offering an alternative to traditional two-dimensional CNNs, with reduced resource requirements. However , this array-based operation reduced the resource requirement, but the energy-consumption impact was not studied. To bridge this gap, we introduce EPyNet, a deep learning architecture crafted for energy efficiency with a particular emphasis on neuron reduction. Focusing on the task of audio emotion recognition, We evaluate EPyNet on five public audio corpora-RAVDESS, TESS, EMO DB, CREMA D, and SAVEE.We propose three versions of EPyNet, a lightweight neural network designed for efficient emotion recognition, each optimized for different trade-offs between accuracy and energy efficiency. Experimental results demonstrated that the 0.06M EPyNet reduced energy consumed by 76.5% while improving accuracy by 5% on RAVDESS, 25% on TESS, and 9.75% on SAVEE. The 0.2M and 0.9M models reduced energy consumed by 64.9% and 70.3%, respectively. Additionally, we compared our Proposed 0.06M system with the MobileNet models on the CIFAR-10 dataset and achieved significant improvements. The 1035 proposed system reduces energy by 86.2% and memory by 95.7% compared to MobileNet, with a slightly lower accuracy of 0.8%. Compared to MobileNetV2, it improves accuracy by 99.2% and reduces memory by 93.8%. When compared to MobileNetV3, it achieves 57.2% energy reduction, 85.1% memory reduction, and a 24.9% accuracy improvement. We further test the scalability and robustness of the proposed solution on different data dimensions and frameworks.

Jiby Mariya Jose

s deep learning models continue to grow in complexity, the computational and energy demands associated with their training and deployment are becomingincreasingly significant, particularly for convolutional neural networks (CNNs) deployed on CPU-bound and resource- limited devices. Fully connected (FC)layers, while vital, are energy-intensive, accounting for 85.7% of a network’s parameters but contributing only 1% of the computations. This research proposes anovel approach to optimising these layers for greater energy efficiency by integrating low-rank factorisation with differential partial differential equations (PDEs).The introduction of the LowRankDense layer, which combines low-rank matrix factorisation with a differential PDE solver, aims to reduce both the parametercount and energy consumption of FC layers. Experiments conducted on the MNIST, Fashion MNIST, and CIFAR-10 datasets demonstrate the effectiveness ofthis approach, yielding promising results in terms of reduced energy usage and maintaining comparable performance, thereby enhancing the practicality andsustainability of CNNs for widespread use in environments with limited computational resources

Jiby Mariya Jose