Miracle-dz/UniFAR-FTUs huggingface dataset:
The Jallikattu Fiasco: Week Long Protest against the Ban Enforced and the Role Played by Print Media

As the fourth pillar of democratic governments, media has a significant influence in the formation of general conclusions among the masses. The bull has stomped its way into featured news story in Tamil Nadu several times in the last decade. From the time that people of Tamil Nadu prepared to celebrate Pongal in 2017, a large number of individuals from different urban communities of the state came together in open spaces, such as coastal areas and playgrounds, challenging a Supreme Court directive prohibiting the essentially provincial spectacle of Jallikattu. Convenient conclusions have frequently been drawn with regard to debilitating injuries and even deaths. The ‘game’ has never been directed by anyone with precise control. The present paper is an attempt to understand how a section of media, mostly newspapers, portrayed this sensitive issue. The review conducts a comparison between one English daily and one vernacular daily, both covering the Chennai locale in Tamil Nadu and attempts to examine the stand taken by print media in the projection of Jallikattu.
Hierarchical Goal Networks and Goal-Driven Autonomy: Going where AI Planning Meets Goal Reasoning

Planning systems are typically told what goals to pursue and cannot modify them. Some methods (e.g., for contingency planning, dynamic replanning) can respond to execution failures, but usually ignore opportunities and do not reason about the goals themselves. Goal-Driven Autonomy (GDA) relaxes some common assumptions of classical planning (e.g., static environments, fixed goals, no unpredictable exogenous events). This paper describes our Hierarchical Goal Network formalism and algorithms that we have been working on for some time now and discusses how this particular planning formalism relates to GDA and may help address some of GDA’s challenges.
Prediction of interest for dynamic profile of Twitter user

Numerous studies have been conducted to explore the social network of Twitter; some have been conducted to predict the interest or the topic of the user's tweet. In this study, we investigate the best classification model for determining the user's interest based on the bio and a collection of tweets. We use the supervised learning-based classification with the lexical features. Two approaches were proposed; they are the classification that was made based on the user's tweet using multilabel classification method and the classification that was made based on specific accounts. From the result of experimental result, it could be concluded that the employment of the classification using specific accounts approach led to better accuracy.
System Interface and User ’ s Guide

Under the supervision of Professor Frédo Durand, I have designed and implemented a software system that provides users flexibility in controlling the exposure of selective areas of a high-dynamic-range image. When the user selects an area of the image to modify, the system renders an alpha channel using a non-linear bilateral algorithm. This algorithm takes into account both spatial information provided by the user’s selection and intensity information calculated using a Gaussian similarity function. The bilateral algorithm allows for precise and naturallooking alpha channels to be rendered even when the user makes imprecise, hand-drawn selections on the image. These alpha channels control the strength of the local exposure adjustments to yield aesthetically-pleasing results. This work was inspired by research on bilateral filtering [Tomasi et al. 1998], contrast management of high-dynamicrange images using bilateral filtering [Durand and Dorsey 2002], and local exposure management in traditional film photography using Ansel Adams’ Zone System. This paper contains an introduction to the system, a user’s guide, and developer’s notes on selected implementation details.
Large scale ad latency analysis

Late web display advertisements are problematic for both the user experience and the monetary machinery powering the display advertising industry. If a web page is delivered to a user but the ad fails to load in time, the publisher cannot charge the advertiser for that impression. Detecting whether a specific ad will render in time could give the publisher a choice to show that ad or another one. Further, discovering the root causes of latency, possibly over time as new violators emerge, would allow the publisher to address the actionable issues. We propose a system that predicts, at serve time, which ads are likely to have high latency. Once identified we can either ignore those ads, even if they win the auction, or apply a penalty to those ads. In addition, our system collects the daily impression logs, consisting of different types of observations measured at serve time and the associated latency in milliseconds, and analyzes the data to identify the features associated with late ads and likely to be causing the delay.
Preparing Adolescents for Life after School (PALS) Project: A Randomised Controlled Trial of a Coaching Intervention for Young People with Acquired Brain Injury

Introduction: Existing resources to support adolescents with acquired brain injury (ABI) in transition from school to the ‘adult world’ are variable. This study evaluated an intervention using a coaching approach to support adolescents during this transition phase. Method: The study design was a parallel-group randomised controlled trial (RCT). Participants (n = 43) aged 14–19 years were randomised to intervention (n = 21) or no-intervention control (n = 21) conditions. The intervention group received six coaching sessions over an average of 22 weeks. Outcome measures evaluated changes reported by the adolescent (satisfaction, emotional functioning and hope) and their parent (participation, behaviour and support needs). Results: Relative to baseline, there was no significant improvement for those in the intervention group in comparison to the control group on any of the outcome measures. Conclusion: The results of this RCT do not support coaching as an intervention for adolescents with ABI.
Developing and Testing a Model of Knowledge Utilisation through Marketing Research

Little research has examined the return on marketing research, be that financial or knowledge acquisition. Furthermore, there has been insufficient research into the factors affecting the conduct of marketing research. This paper investigates and reports on a conceptual model proposed by Yaman (2000), which explores knowledge acquisition, dissemination, and utilisation through marketing research. The study specifically explores and attempts to replicate the model’s conceptual structure. The data were collected electronically via emails and an HTML web-form questionnaire, with a sample of 182 being obtained. Using structural equation modelling, the results obtained indicated an adequate fit for a modified Yaman model to the data from this particular sample.
A HYBRID CONTINUUM-RIGID MANIPULATION APPROACH FOR ROBOTIC MINIMALLY-INVASIVE FLEXIBLE CATHETER BASED PROCEDURES

In recent years, minimally-invasive surgical systems based on flexible robotic manipulators have met with success. One major advantage of the flexible manipulator approach is its superior safety characteristics as compared to rigid manipulators. However, their soft compliant structure, in combination with internal friction, results in poor position and force regulation which have limited their use to simpler surgical procedures. In this paper, we discuss a new approach to continuum robotic manipulation, interleaved continuum-rigid manipulation, which combines flexible, actively actuated continuum segments with small rigid-link actuators. The small rigid-link joints are interleaved between successive continuum segments and provide a redundant motion and error correction capability. We describe the overall approach including kinematic, design, and control considerations and investigate its performance using a one degree-of-freedom testbed and two degree-of-freedom planar simulation.
Maladaptive perfectionism as mediator among psychological control, eating disorders, and exercise dependence symptoms in habitual exerciser

Background and aims The current study examined the mediating role of maladaptive perfectionism among parental psychological control, eating disorder symptoms, and exercise dependence symptoms by gender in habitual exercisers. Methods Participants were 348 Italian exercisers (n = 178 men and n = 170 women; M age = 20.57, SD = 1.13) who completed self-report questionnaires assessing their parental psychological control, maladaptive perfectionism, eating disorder symptoms, and exercise dependence symptoms. Results Results of the present study confirmed the mediating role of maladaptive perfectionism for eating disorder and exercise dependence symptoms for the male and female exercisers in the maternal data. In the paternal data, maladaptive perfectionism mediated the relationships between paternal psychological control and eating disorder and exercise dependence symptoms as full mediator for female participants and as partial mediator for male participants. Discussion Findings of the present study suggest that it may be beneficial to consider dimensions of maladaptive perfectionism and parental psychological control when studying eating disorder and exercise dependence symptoms in habitual exerciser.
Biologically inspired decision making for collective robotic systems

Practical collective robotic systems likely will be confronted with problems which have more than one unique solution. When deciding on which of a set of candidate solutions to a problem to pursue, a collective system should ensure that its members reach a unanimous decision regarding which solution to implement so that the system itself does not split apart with different members pursuing different solutions. If such a split were to occur, much of the collective system's functionality could be lost. In this paper, we present a unique approach to collective decision making that is based on an algorithm employed by a particular species of ant when it chooses a new nest site. We expand the ants' algorithm into a general purpose decision making scheme and apply it to the collective relocation problem. A detailed study of the performance of our decision making algorithm was carried out in simulation using the collective relocation task as a test bed. Consistent system performance was observed across three robot populations. It was found that one particular system variable, the decision quorum threshold played a large role in determining the system's behaviour and that system behaviour was maximized when this variable was set to 50% of the system's population.
I promise this is my favorite brand! A digital ethnography of the person-as-brand as expressed in sponsored, affiliate, and non-sponsored beauty videos on YouTube

This digital ethnographic study explored branding principles as portrayed in sponsored, affiliate, and non-sponsored video content created by three YouTube beauty influencers. Utilizing Aaker's (1996) model of brand identity, suggestions for how digital influencers can effectively expand their presence through monetization activities with brands, as well as keep their standing in a digital community, are explored.
Reconstructing personalized anatomical models for physics-based body animation

We present a method to create personalized anatomical models ready for physics-based animation, using only a set of 3D surface scans. We start by building a template anatomical model of an average male which supports deformations due to both 1) subject-specific variations: shapes and sizes of bones, muscles, and adipose tissues and 2) skeletal poses. Next, we capture a set of 3D scans of an actor in various poses. Our key contribution is formulating and solving a large-scale optimization problem where we compute both subject-specific and pose-dependent parameters such that our resulting anatomical model explains the captured 3D scans as closely as possible. Compared to data-driven body modeling techniques that focus only on the surface, our approach has the advantage of creating physics-based models, which provide realistic 3D geometry of the bones and muscles, and naturally supports effects such as inertia, gravity, and collisions according to Newtonian dynamics.
Improving the Hadoop map/reduce framework to support concurrent appends through the BlobSeer BLOB management system

Hadoop is a reference software framework supporting the Map/Reduce programming model. It relies on the Hadoop Distributed File System (HDFS) as its primary storage system. Although HDFS does not offer support for concurrently appending data to existing files, we argue that Map/Reduce applications as well as other classes of applications can benefit from such a functionality. We provide support for concurrent appends by building a concurrency-optimized data storage layer based on the BlobSeer data management service. Moreover, we modify the Hadoop Map/Reduce framework to use the append operation in the "reduce" phase of the application. To validate this work, we perform experiments on a large number of nodes of the Grid'5000 testbed. We demonstrate that massively concurrent append and read operations have a low impact on each other. Besides, measurements with an application available with Hadoop show that the support for concurrent appends to shared file is introduced with no extra cost, whereas the number of files managed by the Map/Reduced framework is substantially reduced.
Influencing factors of relationship benefit based on consumer-brand relationship

As two important concepts of relationship marketing, brand relationship and relationship benefits have received more and more attention by marketing scholars. Previous research focused on relationship based on personal relationship and the outcomes of relationship benefits. This paper investigated the relationship among brand personality, consumer personality traits and their perception of relationship benefits by means of empirical study of 204 consumers. Using SEM (Structural Equation Model), the results indicate that different dimensions of brand personality have different effects on the different kinds of relationship benefit. Also, need for social affiliation and Need for variety of the consumer have different influences on relationship benefits.
Buffer transport mechanisms in intentionally carbon doped GaN heterojunction field effect transistors

Temperature dependent pulsed and ramped substrate bias measurements are used to develop a detailed understanding of the vertical carrier transport in the buffer layers in a carbon doped GaN power heterojunction field effect transistor. Carbon doped GaN and multiple layers of AlGaN alloy are used in these devices to deliver an insulating and strain relieved buffer with high breakdown voltage capability. However, understanding of the detailed physical mechanism for its operation is still lacking. At the lowest electric fields (<10 MV/m), charge redistribution within the C doped layer is shown to occur by hole conduction in the valence band with activation energy 0.86 eV. At higher fields, leakage between the two-dimensional electron gas and the buffer dominates occurring by a Poole-Frenkel mechanism with activation energy ∼0.65 eV, presumably along threading dislocations. At higher fields still, the strain relief buffer starts to conduct by a field dependent process. Balancing the onset of these leakage mechanisms is essential to allow the build-up of positive rather than negative space charge, and thus minimize bulk-related current-collapse in these devices.
Connected Baby Bottle: A Design Case Study Towards a Framework for Data-Enabled Design

This paper presents the design case study of a connected baby bottle, which is used as an exploration towards a data-enabled design framework for designing intelligent products, services and ecosystems targeting behavior change. We explore how contextual, behavioral and experiential data can be used as design material for remote insight collection and remote design intervention. The first "contextual" iteration sets out to understand the design context with its complexities, based on a combination of quantitative sensor data and qualitative interview sessions. The second "informed" iteration utilizes design probes, remotely connected to a data-canvas, to explore behavioral, experiential and contextual consequences of design interventions. The dynamic and open character of the introduced data-canvas allowed us to iterate quickly without requiring physical presence of the designer. Finally, we translate the findings from this case study into a two step model for data-enabled design that we further discuss to outline what next steps are required towards constructing a framework for data enabled design.
Simulation and Modelization of Multimode Interference Demultiplexer by using BPM Method

Optical switches based on planar lightwave technology offer stable and robust means of achieving space- division switching. One form of integrated switch that shows some promise is the generalized Mach-Zehnder optical switch. This switch normally comprises two multimode interference (MMI) couplers connected by an array of phase shiffers. We show through detailed simulations that the length of conventionally designed multimode-interference couplers. A 1310 and 1550 nm coarse wavelength multi/demultiplexer based on polymer is demonstrated for the first time. The device is designed based on a combination of general interference and paired interference mechanisms of multimode interference (MMI). Short tuning of the device makes it possible to fabricate MMI coupler with larger free spectral range, significantly increases the 3-dB bandwidth for the total transmittance. By the structure improvement by S-curve we increase the normalized output power of the field for A=1310 nm from 0.8 to 0.95.
Study on casting ultrasonic signal extraction algorithm based on improved MP

Sparse signal decomposition from overcomplete dictionaries are the most recent technique in the signal processing community. In this paper, this technique is utilized to cope with ultrasonic flaw detection problem. But its calculation is huge. A new improved algorithm is proposed which combine genetic algorithm with matching pursuit together. The improved algorithm is employed to search the best matching atoms. It can reduce complexity of matching pursuit. According to the characteristic of ultrasonic echo, the best Gabor atom is selected to self-adaptive match atomic ultrasonic flaw signals. Experimental results shows that four parameters of ultrasonic signal blurred by noise can be estimated according to the proposed algorithm, and the signal quality and performance parameters are improved obviously.
A Political Ecology of Solid Waste Management in Niadub, Panama

of a thesis at the University of Miami. As indigenous communities across Latin America embrace modernization and undergo rapid development, safe and effective waste management becomes an important environmental and public health concern. Far too often, these marginalized groups are excluded from decision-making in the development processes and international conservation projects that address a host of population, health and environmental issues in their own communities. Waste Management projects and initiatives led by international organizations have not only excluded local interest groups from planning and administration, they disregard socio-cultural values and community needs in the process. This has led to far too many failed attempts at addressing pollution concerns and waste-management in developing countries and exacerbates the marginalization of these cultures. This case study assessed the potential of ethnography and political ecology as valuable tools in the waste management-planning framework. The application of these research methodologies was evaluated in Niadub, Panama, by using this approach to attempt to understand the social and cultural context of waste management in the small indigenous Guna community. Through in depth life & work histories and semi-structured interviews, an understanding of Guna cosmology, cultural norms and community values was developed. Discussion groups were organized with select interest groups to collect their perspectives on current waste-management strategies, perceived impacts of waste management practices and the potential for an improved waste management plan. What this research showed was a long-standing cultural understanding of garbage, its potential negative impacts and the need for proper management. Even as Niadub has modernized and the waste stream has become inundated with modern plastics, the social organization and cultural values have remained fundamentally the same. Although fragmented by foreign funding and exclusionary conservation projects, community interest groups remain concerned and motivated to improve the village's waste management strategy. Waste management is a complicated affair that transcends the political, economic, social and environmental realms. Understanding the complexity of these issues and the interest groups involved necessitates a deeper level understanding of the socio-cultural context. In using the ethnographic and political ecology approach, this study was able to validate their application towards developing that in-depth appreciation.
Capacity of the watermark channel: how many bits can be hidden within a digital image?

An evaluation of the number of bits that can be hidden within an image by means of frequency-domain watermarking is given. Watermarking is assumed to consist in the modification of a set of full-frame DCT (DFT) coefficients. The amount of modification each coefficient undergoes is proportional to the magnitude of the coefficient itself, so that an additive- multiplicative embedding rule results. The watermark-channel is modeled by letting the watermark be the signal and the image coefficients the noise introduced by the channel. To derive the capacity of each coefficient, the input (i.e. the watermark) and the output (i.e. the watermarked coefficients) of the channel are quantized, thus leading to a discrete- input, discrete-output model. Capacity is evaluated by computing the channel transition matrix and by maximizing the mutual input/output information. Though the results we obtained do not take into account attacks, they represent a useful indication about the amount of information that can be hidden within a single image.
Two-dimensional correction for min-sum decoding of irregular LDPC codes

Two-dimensional (2-D) correction schemes are proposed to improve the performance of conventional min-sum (MS) decoding of irregular low density parity check codes. An iterative procedure based on parallel differential optimization is presented to obtain the optimal 2-D factors. Both density evolution analysis and simulation show that the proposed method provides a comparable performance as belief propagation (BP) decoding while requiring less complexity. Interestingly, the new method exhibits a lower error floor than that of BP decoding. With respect to conventional MS and 1-D normalized MS decodings, the 2-D normalized MS offers a better performance. The 2-D offset MS decoding exhibits a similar behavior.
The Virtual Power System Testbed and Inter-Testbed Integration

The Virtual Power System Testbed (VPST) at University of Illinois at Urbana-Champaign is part of the Trustworthy Cyber Infrastructure for the Power Grid (TCIP) and is maintained by members of the Information Trust Institute (ITI). VPST is designed to be integrated with other testbeds across the country to explore performance and security of Supervisory Control And Data Acquisition (SCADA) protocols and equipment. We discuss potential use cases in order to motivate the integration of VPST with other testbeds, identify requirements of interconnected testbeds, and describe our design for integration with VPST.