@inproceedings{bib_LLM__2024, AUTHOR = {Prateek Sancheti, Kamalakar Karlapalem, Kavita Vemuri}, TITLE = {LLM Driven Web Profile Extraction for Identical Names}, BOOKTITLE = {Companion Proceedings of the ACM Web Conference}. YEAR = {2024}}

The number of individuals having identical names on the internet is increasing. Thus making the task of searching for a specific individual tedious. The user must vet through many profiles with identical names to get to the actual individual of interest. The online presence of an individual forms the profile of the individual. We need a solution that helps users by consolidating the profiles of such individuals by retrieving factual information available on the web and providing the same as a single result. We present a novel solution that retrieves web profiles belonging to those bearing identical Full Names through an end-to-end pipeline. Our solution involves information retrieval from the web (extraction), LLM-driven Named Entity Extraction (retrieval), and standardization of facts using Wikipedia, which returns profiles with fourteen multi-valued attributes. After that, profiles that correspond to the same real-world individuals are determined. We accomplish this by identifying similarities among profiles based on the extracted facts using a Prefix Tree inspired data structure (validation) and utilizing ChatGPT's contextual comprehension (revalidation). The system offers varied levels of strictness while consolidating these profiles, namely strict, relaxed, and loose matching. The novelty of our solution lies in the innovative use of GPT -- a highly powerful yet an unpredictable tool, for such a nuanced task. A study involving twenty participants, along with other results, found that one could effectively retrieve information for a specific individual.

@inproceedings{bib_Grap_2024, AUTHOR = {Sasanka Grs, Ayushi Kumari Agrawal, Santosh Nannuru, Kavita Vemuri}, TITLE = {Graph learning methods to extract empathy supporting regions in a naturalistic stimuli fMRI}, BOOKTITLE = {Technical Report}. YEAR = {2024}}

Functional MRI research using naturalistic stimuli (like movies) can help examine brain networks supporting empathy. Applying graph learning methods to whole-brain time-series signals, we propose a novel fMRI signal processing pipeline that includes high-pass filtering, voxel-level clustering, and windowed graph learning with a sparsity-based approach. The fMRI dataset is from passive viewing of an 8-minute movie shown to 14 healthy volunteers. The emotion rating of the movies by age-matched 40 participants is the ground truth. We considered a total of 54 regions extracted from the AAL Atlas for the study. The sparsity-based graph learning method consistently outperforms in capturing variations in the emotion scale, achieving over 88% match of the graph cluster labels averaged across participants. Temporal analysis reveals a high fit to the emotion scale supported by the method’s effectiveness in capturing dynamic connectomes through graph clustering, indicating the role of contextual inference in building empathy. While the edge-weight dynamics analysis underscores the superiority of sparsity-based learning, the connectome-network analysis highlights the crucial role of the Insula, Amygdala, and Thalamus in empathy, with lateral brain connections facilitating synchronized responses. Spectral filtering analysis by band-pass filter isolated the regions linked to emotional and empathy processing in scenes with high emotional context. We also observe strong similarities between the movies in graph cluster labels, connectome-network analysis, and spectral filtering-based analyses, revealing robust neural correlates of empathy. These findings contribute to a better understanding of the neural dynamics associated with empathy and identify regions specific to empathetic responses to naturalistic stimuli.

@inproceedings{bib_FOLK_2024, AUTHOR = {Nancy Hada, Aditya Kumar Singh, Kavita Vemuri}, TITLE = {FOLKTALENT: ENHANCING CLASSIFICATION AND TAGGING OF INDIAN FOLK PAINTINGS}, BOOKTITLE = {FOSS Approaches towards Computational Intelligence and Language Technology}. YEAR = {2024}}

Indian folk paintings have a rich mosaic of symbols, colors, textures, and stories making them an invaluable repository of cultural legacy. The paper presents a novel approach to classifying these paintings into distinct art forms and tagging them with their unique salient features. A custom dataset named FolkTalent, comprising 2279 digital images of paintings across 12 different forms, has been prepared using websites that are direct outlets of Indian folk paintings. Tags covering a wide range of attributes like color, theme, artistic style, and patterns are generated using GPT4, and verified by an expert for each painting. Classification is performed employing the RandomForest ensemble technique on fine-tuned Convolutional Neural Network (CNN) models to classify Indian folk paintings, achieving an accuracy of 91.83%. Tagging is accomplished via the prominent fine-tuned CNN-based backbones with a custom classifier attached to its top to perform multi-label image classification. The generated tags offer a deeper insight into the painting, enabling an enhanced search experience based on theme and visual attributes. The proposed hybrid model sets a new benchmark in folk painting classification and tagging, significantly contributing to cataloging India’s folk-art heritage.

@inproceedings{bib_Deep_2023, AUTHOR = {Nancy Hada, Kavita Vemuri}, TITLE = {Deep Learning-Driven Feature Extraction for Classification of Indian Tribal Paintings}, BOOKTITLE = {Cultural Data Analytics Conference}. YEAR = {2023}}

The proposed work endeavors to support the preservation of tribal arts in their original art form with their unique colors, shapes, and objects. Tribal arts of each region of India is a ‘message’ of their life, traditions, and history, requiring preservation in its pristine, unique form. For example, dotted patterns in Bhil, geometric figures in Warli, dashes in Gond, deities’ expressions in Pichwai paintings, etc., are some notably diverse visual patterns that depict the profound stories of their wholesome culture. In this preliminary work, a dataset is collected by mining the websites, which are direct outlets of tribal arts, thereby ensuring the authenticity of the images included. The collected dataset includes 863 paintings across five different classes of tribal arts viz Warli, Bhil, Gond, Pichwai, and Kalighat, as described in Figure 1. Furthermore, image classification baselines on the collected dataset are developed by fine-tuning the pre-trained ResNet50, InceptionV3, and EfficientNetB0 models. The classification accuracy for the aforementioned baselines is reported in Table 1. Among the baselines, the best testing accuracy of 91.57 % is observed for EfficientNetB0; the confusion matrix for which is shown in Figure 2. The associated F1-scores for this baseline model across all five classes, namely Warli, Bhil, Gond, Pichwai, and Kalighat, were found to be 0.958, 0.882, 0.875, 0.909, and 0.958, respectively which suggests that the dataset is balanced in nature. Furthermore, class activation maps are generated for each image of the collected dataset across all baselines to ascertain the alignment of results generated with the ground truth, which offers a means to comprehend and compare the regions of focus in decision-making. Figure 3 provides an example of a class activation map revealing the salient focus areas, such as human figures represented by triangles and circles in a Warli painting. This analysis can also be used by artists for designing the artwork. The extension of the classification work is to detect counterfeit tribal paintings and quantify the extent of deviation from the original art form, ultimately contributing towards tribal arts preservation and safeguarding their invaluable cultural heritage.

@inproceedings{bib_The__2023, AUTHOR = {BHUPATHIRAJU KRISHNA SRIJA, Ayushi Agrawal, Kavita Vemuri}, TITLE = {The Objectifying Gaze: Impact of sexualised media..}, BOOKTITLE = {Annual Meeting of the Cognitive Science Society}. YEAR = {2023}}

The Objectifying Gaze: Impact of Sexualized Media on Viewer Gaze Behavior towards (Non)Traditional Attire Anonymous CogSci submission Abstract In this study, we investigate the priming effect of camera- induced objectifying-gaze, operationalised via sexualised mu- sic video(MV), on university students when looking at tar- get female images in traditional (saree, salwar) and western (shirt-pant, short-dress) attires in the Indian demographics. We showed participants two videos where female leads wore un- revealing Indian attire (saree) and revealing western clothing in sexualised and traditional MVs respectively. We quantified gaze as fixation-duration and visit-count (revisit frequency) metrics. Our findings report that there is a priming effect of sexualised media. Female images in all attires are equally objectified and body-biased gaze is more pronounced in sex- ualised MV priming, short-dress is more objectified in tradi- tional MV priming, and saree is less objectified overall, which confirms the social stereotypes on attire and respectability — traditionally clad (vs. non-traditional) women are seen as more moral and worthy of respect and protection compared to women in hypersexualized and objectified roles.

@inproceedings{bib_Asse_2023, AUTHOR = {Bhumika Sahu, Ayush Kumar Dwivedi, Kavita Vemuri, Sachin Chaudhari}, TITLE = {Assessing the Impact of Air Pollution on Physiology: Implications and Prospects}, BOOKTITLE = {India Council International Conference}. YEAR = {2023}}

Air pollution due to industrial activity, vehicles, and construction has shown immediate and long-term effects on human health. While respiratory condition manifests directly, long-term conditions like heart diseases, cancer, lung damage, and the impact on fetal health have been established. This study is aimed to explore the effects of air pollution on the physiological health of humans using a smart wearable watch. A total of 8 healthy security guards posted at the institute gate close to a very busy traffic junction for 12 hours a day were recruited. The physiological indicators such as heart rate (HR), body temperature (BT), and SPO2 levels were recorded by the wearable device for changes during the day/night for two seasons (summer and winter). Air pollution monitoring sensors were also deployed at the same site to record PM2.5, PM10, relative humidity (RH), and environmental temperature (ENT). A survey of 43 questions under three different sections: demographic, medical condition, and quality of life (QoL) were also filled by each participant. Descriptive statistics and inferential statistical analysis (Wilcoxon, Correlation) have been presented based on the collected data. The research shows an association between short-term fluctuations in physiological parameters due to air pollution. Still, the findings need to be weighted with the accuracy and consistency of the wearable devices.

@inproceedings{bib_Impa_2023, AUTHOR = {Kunal Rajesh Lahoti, Shivani Hanji, pratik Kamble, Kavita Vemuri}, TITLE = {Impact of Loss-Framing and Risk Attitudes on Insurance Purchase: Insights from a Game-like Interface Study}, BOOKTITLE = {Technical Report}. YEAR = {2023}}

This study investigates the impact of loss-framing and individual risk attitude on willingness- to purchase insurance products utilizing a game-like interface as choice architecture. The application presents events as experienced in real life. Both financial and emotional loss-framing events are followed by choices to purchase insurance. The participant cohorts considered were undergraduate students and older participants; the latter group was further subdivided by income and education. The within-subject analysis reveals that the loss framing effect on insurance consumption is higher in the younger population, though contingent on the insurance product type. Health and accident insurance shows a negative correlation with risk attitudes for younger participants and a positive correlation with accident insurance for older participants. Risk attitude and life insurance products showed no dependency. The findings elucidate the role of age, income, family responsibilities, and risk attitude in purchasing insurance products. Importantly, it confirms the heuristics of framing/nudging.

@inproceedings{bib_Unde_2023, AUTHOR = {Kunal Rajesh Lahoti, Hanji Shivani Sunil, pratik Kamble, Kavita Vemuri}, TITLE = {Understanding the effect of loss-framing in insurance purchase decisions – using a game of life like interface}, BOOKTITLE = {Behavioral Research in Economics Workshop-Economic science Associationn}. YEAR = {2023}}

This study investigates the impact of loss-framing and individual risk attitude on the willingness- to purchase insurance products, utilizing a game-like interface in a choice architecture. The application presents events as experienced in real-life , as a young adult searching for employment to retirement. Both financial and emotional loss-framing events are followed by choices to purchase insurance. The participant cohorts considered were undergraduate students and older participants, the latter group was further subdivided by income and education. From the within-subject analysis, the preliminary findings reveal that the loss framing effect on insurance consumption is higher in the younger population though contingent on the insurance product type. Health and accident insurance shows a negative correlation with risk attitudes for the younger age and a positive correlation with accident insurance for older participants. Risk attitude and life insurance products willingness-to-purchase showed no dependency. The findings elucidate the role of age, income, family responsibilities, and risk attitude in purchasing insurance products. Importantly, it confirms the correlation between age and the effect heuristics of framing/nudging.

@inproceedings{bib_The__2023, AUTHOR = {Harsh Sharma, SUPREETH S KARAN, Ayushi Kumari Agrawal, Kavita Vemuri}, TITLE = {The role of individ- ual physical body measurements and activity on spine kinematics during flexion, lateral bending and twist tasks in healthy young adults – Comparing marker(less) data}, BOOKTITLE = {Biomedical Signal Processing and Control}. YEAR = {2023}}

Unde rstan din g th e relationship betwee n phys ica l characte ristics an d acti vit y to kinemati c properties of th e spin e ha s impl ication s fo r sports , occupational tasks, clin ica l diagnosi s an d prognosis. This stud y aime d to ca t egorize spin e kinema tic s from flexion, la teral -bend , an d twis t exercise s by examinin g th e co rrelation s to body -mass inde x (BMI), wais t -to -hi p rati o (WHR), an d phys ica l acti vit y le vel s in health y youn g adults . Th e data wa s co llected from a marker -base d optoelectronic motion ca pture setu p an d a marker -less motion ca pture with th e RG B ca m - er a of a standard mobile phone. Co mpa rin g th e accuracies of th e tw o techniques on th e same data se t is impo r - tant to develo p inexpe nsive (RGB ca mera) diagno stics . Sixt y -tw o pa rti c ipant s (4 0 Male , 22 female ) pa rti c ipate d in th e study. Th e angula r di splac ement of th e spin e fo r each exercise wa s extracte d by ve cto r anal ysi s usin g a si n - gl e re ference node /marker . Th e anal ysi s showed no si gni ficant co rrelation s of angula r di splac ement s va lue s fo r th e thre e movement s with BM I or WHR. Th e phys ica l acti vit y leve l of male pa rti c ipant s is si gni ficantly co rrelate d with angula r di splac ement s fo r th e flexio n (p < 0.001) an d la teral -bend (p -valu e ranges from 0.00 1 to 0.04 ) an d weakly co rrelate d (but no t si gni ficant ) fo r twis t exercises. Th e phys ica l acti vit y leve l show s a si gni ficant co rrela - tion fo r only flexio n (p < 0.001) in female pa rti c ipants. Th e findings emph asize th e crit ica l role of phys ica l acti v - it y on mu sculoskel eta l flex ibi lit y in young, health y adults . Th e angles estimate d usin g both techniques were co m - parabl e an d si gni ficantly co rrelate d across pa rti c ipant s an d exercises.

@inproceedings{bib_Obje_2022, AUTHOR = {BHUPATHIRAJU KRISHNA SRIJA, Ayushi Kumari Agrawal, Priyanka Srivastava, Kavita Vemuri}, TITLE = {Objectifying gaze: An empirical study with non sexualized images.}, BOOKTITLE = {Annual Conference of the Cognitive Science Societ}. YEAR = {2022}}

1 Introduction Recent studies show that sexually-objectified women are not only treated as sex objects but also visually processed similar to objects (local processing)[1,2]. However, Sexual objectification(SO) research has predominantly studied western society's perceptions, with few empirical studies examining other cultures. In this study, we explore SO of women in an Asian-Indian cultural/social setting using a novel design and stimuli representative of the culture. We conduct an eye tracking study that uses Navon local/global and body inversion[3] paradigms to investigate the gaze behavior and underlying visual processing when looking at non-sexualized male and female images. 2 Methods The study sample consists of Ninety-four (24 women, 70 men, age=18-27, mean=21, stdev=±2.1) undergraduate and graduate students. There are 20 trial blocks. Each trial block consists of a male/female image in upright/inverted orientation, off-centre to the screen for 7 seconds followed by a plus sign for 1 second, followed by a Navon letter identification task. The priming condition and Navon task are randomised to minimise confounding effects. The Navon image is a large letter made of small letters. The participants press 'B' if they identify either one of the target letters ('H'/‘O') either as a contour or a feature (the letter itself) otherwise press ‘N’. The classification of local/global recognition is implicit as the participants press the same key ‘B’ for both local and global images. We selected black and white male images(MI) and female images(FI) wearing casual attires like jeans/pant and top/shirt. The experiment is designed using Tobii Studio. Tobiix120 eye tracker is used to capture the gaze. We mark face, chest, hip as our Areas of Interest(AoIs) and calculate the fixation duration(FD), revisit frequency(RF), first fixation duration(FFD) for the AoIs. We define sexual body(SB) parts as sum of hip and chest AoIs. For gaze analysis, 5 participants data with poor sampling rate (below 40%) are excluded. We use Tukey Fence outlier detection method to remove outliers and removed 10 participants data for first fixation duration analysis. We measure Response Time(RT) as the time taken to press the key from the onset of the Navon image presentation. For RT analysis, we consider only the data points with at least one correct response in each priming condition, reducing our data to 59 participants. The alpha level for p-value is set to 0.05 in all tests. 3 Results There is a main effect of target (priming stimulus) gender and orientation on the FD and RF. • FD: Face FD of upright > inverted and SB parts FD of upright < inverted for both MI and FI. Face FD of FI < MI and SB parts FD of FI > MI in both upright and inverted orientation. Face FD > SB parts FD for all target images. • RF: Face RF of upright > inverted for both MI and FI. SB parts RF of inverted > upright for FI. Importantly, SB parts RF of FI > MI in upright and inverted orien-tation. Face RF < SB parts RF for all target images. • FFD: There is significant effect of orientation for FI but not for MI. Face FFD of upright FI > inverted FI and SB parts FFD of inverted FI > upright FI. • RT: Global recognition is faster in female priming for both orientations. Local recognition is faster in male priming, but the significance is found only for inverted image. The participant gender effect on RT is not significant. There is no significant correlation between local/global RT and FD. 4 Discussion Objectification theory states that women have a greater propensity to be sexually objectified than men do. This is evident from our data, female sexual body parts received greater attention than male sexual body parts and vice versa for face. However the visual attention is still greatest on the face for both male and female images, in line with [4,5,6,7,8]. As for global/local perception, non-sexualized males are processed similar to objects more than females. This is in contrast to[3,1,6] but find support in a study on Chinese population [9]. We can attribute our findings to the choice of the stimuli being personalised as against sexualized. There is a strong inversion effect on gaze, both gender images are more objectified in inverted than upright position but this doesn’t affect the underlying cognitive processing implying that the difference in the visual processing between objectified and non-objectified is more quantitative than qualitative. References 3) Bernard, P., Gervais, S. J., & Klein, O. (2018). Objectifying objectification: When and why people are cognitively reduced to their parts akin to objects. European Review of So-cial Psychology, 29(1), 82–121. 4) Bernard, P., Rizzo, T., Hoonhorst, I., Deliens, G., Gervais, S., B, Bayard, C., Deltenre, P., Colin, C., & Klein, O. (2018). The Neural Correlates of Cognitive Objectification. So-cial Psychological and Personality Science, 9, 550–559. 2) Bernard, P., Gervais, S. J., Allen, J., Campomizzi, S., & Klein, O. (2012). Integrating Sexual Objectification with Object Versus Person Recognition: The Sexualized-Body-Inversion Hypothesis. Psychological Science, 23(5), 469–471. 1) Bareket, O., Shnabel, N., Abeles, D., Gervais, S., & Yuval-Greenberg, S. (2019). Evi-dence for an Association between Men’s Spontaneous Objectifying Gazing Behavior and their Endorsement of Objectifying Attitudes toward Women. Sex Roles, 81(3–4), 245–256. 5) Cogoni, C., Carnaghi, A., Mitrovic, A., Leder, H., Fantoni, C., & Silani, G. (2018). Understanding the mechanisms behind the sexualized-body inversion hypothesis: The role of asymmetry and attention biases. PLOS ONE

@inproceedings{bib_Inve_2022, AUTHOR = {SUPREETH S KARAN, Harsh Sharma, Ayushi Kumari Agrawal, Kavita Vemuri}, TITLE = {Investigation of microstates extracted from EEG signals of tip-pinch and wrist flexion/extension movement}, BOOKTITLE = {SOCIETY OF APPLIED NEUROSCIENCE}. YEAR = {2022}}

Investigation of microstates extracted from EEG signals of tip-pinch and wrist flexion/extension movement

@inproceedings{bib_Expl_2022, AUTHOR = {Aadilmehdi J Sanchawala, Adhithya Arun, Rahul Sajnani, Rohan Chacko, Kavita Vemuri}, TITLE = {Exploring Empathy and a Range of Emotions Towards Protest Photographs}, BOOKTITLE = {Annual Meeting of the Cognitive Science Society}. YEAR = {2022}}

Images are a powerful medium known to induce empathy and emotional response in people. In political protests it has the power for a people-initiated policy change and signifies the deep symbolism of a political system. In this study, we aim to quantify the range of emotional connection a person experiences for photographs of a farmers' protest.The protest was the headlines in all media at the time this experiment was conducted and had polarized public opinion. Each photograph is identified to have a set of physical and semantic features. The three selected features were presence of police, gender and close-up (vs.long-shot) in the frame. The intensity on a range of emotions (fear, disgust, anger, sadness, optimism, pessimism, surprise, shock, happiness, and respect) experienced by the viewer for each feature was collected. By statistical and dimensionality analyses, we isolate and identify influencing factors in an image. We found that the presence of police in aggressive actions and close-up shots of had the highest variation in the emotional responses of participants. Interestingly, the gender of the protesters did not show statistically significant effects. The findings from the exploratory investigation highlights the powerful role photographic features have on emotional responses of people, an understudied but critical factor in a world immersed in social media.

@inproceedings{bib_Clic_2022, AUTHOR = {Vivek Kaushal, Sawar Sagwal, Kavita Vemuri}, TITLE = {Clickbait’s Impact on Visual Attention–An Eye Tracker Study}, BOOKTITLE = {Annual Meeting of the Cognitive Science Society}. YEAR = {2022}}

In this paper, we have studied the impact of clickbait headlines on the distribution of visual attention on hyperlinked news articles. Visual attention is a driving factor in ad-based revenue models that support online journalism. Importantly, it is also an indicator of cognitive processes involved in reading and comprehension. We hypothesize that articles with clickbait headlines receive lesser visual attention when controlled for articles’ content. This is based on the premise that a significant proportion of clicks on clickbait headlines are driven by readers’ specific epistemic curiosity rather than knowledge acquisition. An eye-tracker setup was used to infer visual attention from the gaze-fixation analysis conducted on data from 60 participants. Our results suggest that clickbait headlines significantly reduce the visual attention on news articles. Though, article content comprehension measured by a recall test was comparable for clickbait and non-clickbait headlines. Our findings add to the discussions on the cognitive attention and the implications of using clickbait headlines for news publishers, newsreaders, and advertising agencies alike.

@inproceedings{bib_Acce_2022, AUTHOR = {Medha Sharma, Kavita Vemuri}, TITLE = {Accepting Human-like Avatars in Social and Professional Roles}, BOOKTITLE = {ACM Transactions on Human-Robot Interaction}. YEAR = {2022}}

Humans report perceptions of unease or eeriness as humanoid/android robots and digital avatars approach human-like physical resemblance, a phenomenon alluded by the Uncanny Valley theory. This study extends the discussions on interactions and acceptance of digital avatars with findings from three experiments. In the first, perceptive evaluation of actors in clips from computer-generated animation and a live-action version of the same movie was examined. In the second experiment, we considered short clips with highly realistic digital avatars to measure recognition ability, the extent of eeriness, and specific physical features identified as unreal. The fixation area and pupil size variation recorded using an eye tracker were analyzed to infer attention to the body, face, and emotional response, respectively. Building on these findings, the third experiment looked at acceptance in roles requiring human skill, empathy, and cognitive ability. The results show that based on perceptions from physical attributes, the eeriness scores diverge from the uncanny valley theory as human-likeness increases. The realistic CGI and mocap technology could have helped cross the valley. Visual attention inferred from gaze behavior was similar for live-action and CGI. At the same time, we observe pupil size changes reflecting emotions like eeriness when the avatars either talked or smiled. Proficiency and acceptance scores were lower for roles requiring complex social cognition processes, such as friends and judicial decision-making. Interestingly, real-life stereotypes of gender roles were transferred to digital avatars too. The findings suggest an ambiguity in accepting human-like avatars in social and professional interactions, emphasizing the need for a multi-dimensional approach when applying the uncanny valley theory. A detailed and contextual examination is imperative as technological advancements have placed humans closer to co-existing with digital or physical android/humanoid robots.

@inproceedings{bib_Deve_2022, AUTHOR = {Ayu Parmar, Spanddhana Sara, Ayush Kumar Dwivedi, Chinthalapani Rajashekar Reddy, Ishan Patwardhan, Sai Dinesh Bijjam, Sachin Chaudhari, Krishnan Sundara Rajan, Kavita Vemuri}, TITLE = {Development of End-to-End Low-Cost IoT System for Densely Deployed PM Monitoring Network: An Indian Case Study}, BOOKTITLE = {Technical Report}. YEAR = {2022}}

Particulate matter (PM) is considered the primary contributor to air pollution and has severe implications for general health. PM concentration has high spatial variability and thus needs to be monitored locally. Traditional PM monitoring setups are bulky, expensive and cannot be scaled for dense deployments. This paper argues for a densely deployed network of IoT-enabled PM monitoring devices using low-cost sensors. In this work, 49 devices were deployed in a region of the Indian metropolitan city of Hyderabad out-of this, 43 devices were developed as part of this work and 6 devices were taken off the shelf. The low-cost sensors were calibrated for seasonal variations using a precise reference sensor. A thorough analysis of data collected for seven months has been presented to establish the need for dense deployment of PM monitoring devices. Different analyses such as mean, variance, spatial interpolation and correlation have been employed to generate interesting insights about temporal and seasonal variations of PM. In addition, event-driven spatiotemporal analysis is done for PM values to understand the impact of the bursting of firecrackers on the evening of the Diwali festival. A web-based dashboard is designed for real-time data visualization.

@inproceedings{bib_VR-P_2021, AUTHOR = {VUDDAGIRI SAI SRINIVAS, Kavita Vemuri, Male Shivaram, Rishi Bhardwaj}, TITLE = {VR-Phore: A Novel Virtual Reality system for Diagnosis of Binocular Vision}, BOOKTITLE = {IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops}. YEAR = {2021}}

Binocular vision (BV) is the result of fusion between inputs from each eye to form a coherent image. BV anomalies are evaluated using different diagnostic tests and instruments. One such instrument is the Synoptophore, which evaluates three grades of BV. This equipment though efficient has certain limitations like ambient light while testing, bulky and expensive. We propose VR-Phore, application of a VR head-mounted display for diagnostics based on principle of the haploscope similar to Synoptophore. The proposed system addresses the limitations of Synoptophore with added advantage of a software platform to incorporate testing modules for a range of clinical conditions.

@inproceedings{bib_IoT__2021, AUTHOR = {Souradeep Deb, Chinthalapani Rajashekar Reddy, Sachin Chaudhari, Kavita Vemuri, Rajan Krishnan Sundara}, TITLE = {IoT Network Based Analysis of Variations in Particulate Matter due to COVID-19 Lockdown}, BOOKTITLE = {International Conference on Electronics, Computing and Communication Technologies}. YEAR = {2021}}

During the COVID-19 pandemic, India’s complete lockdown was implemented from March 24 to May 3 2020, to minimize the effects of community transfer and control the rapidly growing rate of the virus spread. In this paper, we focus on quantifying the change in air pollution due to Hyderabad’s lockdown, the capital of Telangana State. For this, two datasets are employed. The first dataset is from the Central Pollution Control Board (CPCB) stations in the city. In contrast, the second dataset is the dense IoT network of PM monitors deployed in the educational campus of IIITH in Gachibowli, Hyderabad. An analysis is done on the collected data to understand the effect of lockdown on PM values while considering the yearly and seasonal variations. It has been shown that while there has been a significant drop in PM values. However, through correlation analysis between the temperature and the PM values during the regular times, not all PM values decrease because of the lockdown. Index Terms

@inproceedings{bib_Clic_2021, AUTHOR = {Vivek Kaushal, Kavita Vemuri}, TITLE = {Clickbait - Trust and Credibility of Digital News}, BOOKTITLE = {IEEE Transactions on Technology and Society}. YEAR = {2021}}

Clickbait headlines are compelling and designed to lure readers to click on the linked article. To understand their impact on the credibility of news items, we designed and conducted an experiment on news articles from the WebisClickbait-17 dataset. The role of readers’ age and epistemic curiosity on clickbait propensity was also studied. Two datasets of 6 articles each of news relevant to North America and India were selected and each article was assigned a clickbait and a non-clickbait headline based on a pre-test for clickbait perception. 200 participants (100 each of English-speaking American and English-speaking Indian) were instructed to click and read through any two articles of their choice and fill a credibility questionnaire. Epistemic curiosity and demographic data were collected at the end of the experiment. Clickbait headlines significantly reduced the credibility of news items. A correlation between age and propensity for clickbait was observed. No correlation was observed between diversive epistemic curiosity and clickbait propensity, while a weakly negative correlation was observed between specific epistemic curiosity and clickbait propensity. We hope that our findings may lead to a better end-user experience in terms of access to credible information for news readers, bereft of clickbait. Keywords— clickbait, credibility, journalism, digital media, social

@inproceedings{bib_Unlo_2020, AUTHOR = {Aadilmehdi J Sanchawala, Adhithya Arun, Rahul Sajnani, Kavita Vemuri}, TITLE = {Unlocked: A Game On Human Trafficking}, BOOKTITLE = {IEEE conference on Games}. YEAR = {2020}}

A behaviourally transformative experience via a strong theme, narrative, and gameplay is a powerful learning paradigm when presented coherently. The interplay of these factors facilitates learning and allows for an immersive experience. It enables players to explore their options and deliberate on the outcomes of their decisions. In this paper, we focus on the socially relevant theme of human trafficking. With Unlocked, we present a perspective that has not been addressed by similarly themed games so far. Understanding such an outlook is crucial to connect with the realities of human trafficking. Our game demonstrates the obstacles in real-life escapes and rescue operations while using well-established literature on learning as guiding principles to create an effective transformative experience. It allows the player to identify with victims and understand their mindset and thought processes. We measure our game’s efficacy in educating players about factors like socio-economic and cultural predicaments, and latent conditions that influence these crimes. Such factors are often overlooked and are hard to understand until they are experienced first-hand. Our study attempts to show that transformative games can help recognize the role that these factors play by placing the player in the victim’s position and building a strong narrative around it. We evaluate the learning process by having two phases of survey, pre-test, and post-test. The pre-test survey tests the player’s knowledge about the current state of human trafficking. In the post-test survey, players rate the experience, gameplay, and effectiveness of the game in educating them about the trafficking scenario. The game was tested and validated by social activists who work to rescue trafficked women and children. They acknowledged the potential impact our game could have on raising awareness. Our findings establish that transformative games grounded with a strong narrative and built with a meticulous design guided by principles of transformation and learning prove to be highly effective in propagating social messages on the perils of human trafficking. Index Terms—Transformative play, Game based learning, Serious games, Human Trafficking, Role playing

@inproceedings{bib_Clic_2020, AUTHOR = {Vivek Kaushal, Kavita Vemuri}, TITLE = {Clickbait in Hindi News Media : A Preliminary Study}, BOOKTITLE = {International Conference on Natural Language Processing}. YEAR = {2020}}

A corpus of Hindi news headlines shared on Twitter was created by collecting tweets of 5 mainstream Hindi news sources for a period of 4 months. 7 independent annotators were recruited to mark the 20 most retweeted news posts by each of the 5 news sources on its clickbait nature. The clickbait score hence generated was assessed for its correlation with interactions on the platform (retweets, favorites, reader replies), tweet word count, and normalized POS (part-of-speech) tag counts in tweets. A positive correlation was observed between readers’ interactions with tweets and tweets’ clickbait score. Significant correlations were also observed for POS tag counts and clickbait score. The prevalence of clickbait in mainstream Hindi news media was found to be similar to its prevalence in English news media. We hope that our observations would provide a platform for discussions on clickbait in mainstream Hindi news media.

@inproceedings{bib_Impr_2020, AUTHOR = {Chinthalapani Rajashekar Reddy, Mukku Tanmai, Ayush Kumar Dwivedi, AUROPRAVA ROUT, Sachin Chaudhari, Kavita Vemuri, Rajan Krishnan Sundara, Aftab M. Hussain}, TITLE = {Improving Spatio-Temporal Understanding of Particulate Matter using Low-Cost IoT Sensors}, BOOKTITLE = {International Symposium on Personal, Indoor and Mobile Radio Communications}. YEAR = {2020}}

Current air pollution monitoring systems are bulky and expensive resulting in a very sparse deployment. In addition, the data from these monitoring stations may not be easily accessible. This paper focuses on studying the dense deployment based air pollution monitoring using IoT enabled low-cost sensor nodes. For this, total nine low-cost IoT nodes monitoring particulate matter (PM), which is one of the most dominant pollutants, are deployed in a small educational campus in Indian city of Hyderabad. Out of these, eight IoT nodes were developed at IIIT-H while one was bought off the shelf. A web based dashboard website is developed to easily monitor the real-time PM values. The data is collected from these nodes for more than five months. Different analyses such as correlation and spatial interpolation are done on the data to understand efficacy of dense deployment in better understanding the spatial variability and time-dependent changes to the local pollution indicators.

@inproceedings{bib_Expe_2019, AUTHOR = {DHRITI S GOYAL, Jagadale Dhiraj Vasant, Kavita Vemuri}, TITLE = {Experimental Study on the Decision Making process in a Centipede Game}, BOOKTITLE = {Cognitive Science}. YEAR = {2019}}

The studys objective was to measure the somatic state response (skin conductance and heart rate) and understand the decision making processes in a two-player Centipede game, an extensive form game, with a modified payoff. The experiment included fixed and random termination for analyzing the effect of players mutual trust on risk-taking behavior. The behavioral results reveal that trust controls the game rounds (that is, the number of pass decisions) in known or random termination game conditions, though the exit points were higher in the former compared to the latter condition. Higher skin conductance and heart rate during the game-play is noticed as compared to the baseline data showing anxiety during the gameplay and interestingly opponents action induced higher skin conductance amplitude than during self-play for the same decision. The data provides strong preliminary evidence of trust influencing cooperative gameplay.

@inproceedings{bib_Anal_2019, AUTHOR = {VATSAVAYI SRAVYA, Priyanka Srivastava, Kavita Vemuri}, TITLE = {Analyzing Performance Differences in Artists and Engineers- An RPM Study}, BOOKTITLE = {Cognitive Science}. YEAR = {2019}}

Analytic reasoning differences, as gauged from intelligence metrics, in students engaged in streams requiring a predominantly divergent (arts) or convergent thinking (science and engineering) is a topic of interest. In this paper we have examined this difference by a modified sequence of two sections (D & E) of the Standard Ravens Progressive matrices (RPM). The scan path gaze behavior was analyzed with an eye tracker. The 30 engineering students (half of them are also trained in fine arts) scored higher than the 15 fine arts students. In the former cohort, the artistic and the non-artistic set show no difference in performance but the scan path, fixation count and time taken indicate possible differences in visual strategies for pattern identification. From the detailed analysis, we argue that intelligence as measured by RPM is enhanced by training in reasoning and logic as in engineering streams and might not reflect an innate ability

@inproceedings{bib_Anal_2019, AUTHOR = {MAYANK AGRAWAL, Kavita Vemuri}, TITLE = {Analyzing High Decibel Honking Effect on Driving Behavior Using VR and Bio-Sensors}, BOOKTITLE = {International Conference on Automotive User Interfaces and Interactive Vehicular Applications}. YEAR = {2019}}

Honking in traffic is an auditory warning to indicate: driver’s actions, alert pedestrians and to convey an emergency situation requiring right of way. Though studies have shown the importance of honking in maintaining traffic flow, there have been cases where irrational use leads to an increase in stress/irritation with effects on driver decision making. Most drivers are unaware of the adverse health effects of high decibel honking. In this report, we looked at the effects of honking on driving behavior in a lab-developed VR driving simulator and anxiety/stress as indicated by changes in skin conductance /pulse rate measured using sensors.

@inproceedings{bib_Eye__2018, AUTHOR = {U NITHIYA SHREE, Aditi Ashutosh Mavalankar, Kavita Vemuri}, TITLE = {Eye tracking in naturalistic badminton play — comparing visual gaze pattern strategy in world-rank and amateur player}, BOOKTITLE = {Pervasive Eye Tracking and Mobile Eye-Based Interaction.}. YEAR = {2018}}

A professional player's expertise rests on the ability to predict action by optimally extracting the opponent's postural cues. Eye tracking (head-mounted system) data in a naturalistic singles badminton play was collected from one professional wor0ld-ranked player facing five amateur players (10 serves or 50 trials) and two amateurs playing against four other amateur players each (10 serves or 80 trials). The visual gaze on the opponent body, segregated into 3 areas-of-interest covering the feet, face/torso, and hand/racket of the opponent and the shuttle, was analysed for a) the period just before the serve, b) while receiving the serve and c) the entire rally. The comparative analysis shows the first area-of-interest for professional player as the opponent's feet while executing the serve and the hand/racket when receiving a serve. On the other hand, the amateur players show no particular strategy of fixation location either for the serve task or while facing a serve. The average fixation duration (just before serve) for the professional was 0.96s and for the amateurs it was 1.48s. The findings highlight the differences in the postural cue considered important and the preparatory time in professional and amateur players. We believe, analytical models from dynamic gaze behavior in naturalistic game conditions as applied in this study can be used for enhancing perceptual-cognitive skills during training.

@inproceedings{bib_Geog_2018, AUTHOR = {Srishti Dang, Arunima Ved, Kavita Vemuri}, TITLE = {Geography Map Knowledge Acquisition by Solving a Jigsaw Map Compared to Self-Study: Investigating Game Based Learning}, BOOKTITLE = {International Journal of Game Based Learning}. YEAR = {2018}}

Efficacy of games aslearning medium is of interest to researchers and the gaming industry. A critical metric for learning is knowledge retention and very few studies have conducted in-depth comparisons of: a) game versus no-game learning, b) collaborative versus individual learning. Towards this, the study reported in this article will present the findings from an experiment using Asia and world maps, cut into pieces as in a jigsaw puzzle. The participants were primary school children who were randomly assigned to the puzzle and no-puzzle group. To understand the role of collaborative interactions in learning, each group was further divided into two subgroups. Each subgroup either solved the puzzle or studied the full map (no-puzzle) individually or collaboratively. Three post-tests were conducted over a period of 10 days. The mean scores and Mann Whitney test shows: a) In the no-puzzle condition, no difference in the average scores of the individual and collaborative groups for both maps was observed, b) In the puzzle condition, the collaborative group score was slightly more than that of the individual group for Asia map, while the difference was significant for the continent map, and c) Puzzle and no-puzzle individual group scores were comparative for Asia map but the continent map groups showed a major difference. The findings are mixed with collaborative puzzle solving showing higher retention while puzzle solving does not show significant effect on learning and retention.

@inproceedings{bib_An_e_2015, AUTHOR = {Kavita Vemuri, Bapiraju Surampudi}, TITLE = {An exploratory investigation of functional network connectivity of empathy and default mode networks in a free-viewing task}, BOOKTITLE = {Brain Connectivity}. YEAR = {2015}}

This study reports dynamic functional network connectivity (dFNC) analysis on time courses of putative empathy networks—cognitive, emotional, and motor—and the default mode network (DMN) identified from independent components (ICs) derived by the group independent component analysis (ICA) method. The functional magnetic resonance imaging (fMRI) data were collected from 15 subjects watching movies of three genres, an animation (S1), Indian Hindi (S2), and a Hollywood English (S3) movie. The hypothesis of the study is that empathic engagement in a movie narrative would modulate the activation with the DMN. The clippings were individually rated for emotional expressions, context, and empathy self-response by the fMRI subjects post scanning and by 40 participants in an independent survey who rated at four time intervals in each clipping. The analysis illustrates the following: (a) the ICA method