Reviewerly/exHarmony huggingface dataset:
Chapter 2. The control and censorship of linguistic resources in an online Community of Practice

This research utilises a corpus of one million posts retrieved from Popheads, an online Reddit-based Community of Practice (CoP), to analyse the power dynamics associated with language censorship in online CoPs. In 2018, the moderators of the community banned the community-salient word wig (‘surprised’ or ‘impressed’). Ostensibly, this was a top-down performance of linguistic control where the officially-appointed moderators put a stop to the diffusion of a seemingly beloved part of the community’s shared linguistic repertoire. However, through a mixed-methods analysis of the events surrounding the banning of wig, this research shows that moderators have not unilaterally enforced linguistic censorship. Instead, moderators have seemingly responded to a call, led primarily by members with markers of unofficial power, to restrict usage.
<i>Mind the Body: An Exploration of Bodily Self-Awareness</i>, by Frédérique de Vignemont

Frédérique de Vignemont’s Mind the Body is the most comprehensive study of bodily awareness and the sense of body ownership (SoBO) there is. She brings together relevant work from philosophy and from the brain, cognitive, and clinical sciences in a way that is unprecedented. She systematises the debate on SoBO by cataloguing different views and structuring the dialectic. She synthesises her published work into a new overall narrative, with some key changes. The key new developments are the phenomenal contrast argument for a positive phenomenology of SoBO and the bodyguard hypothesis about SoBO. Other highlights include: her critique of the notions of body image and body schema and her suggestions how to move beyond that tired dichotomy, her bold account of how multimodal bodily self-ascriptions can be immune to error through misidentification, and her discussion of why bodily awareness is constitutively multimodal. Anyone interested in these topics will be indebted to her work.
Sentiment Lexicon for Chinese College Students to Build and Apply

Reviews from social media are considered as a significant information resource, which is useful for analyzing college students' sentiment and views. Students are eager to express and share their views on web regarding day-to-day activities. That information can be used to understand Chinese college students and their preference. Our research is meaningful in analyzing the psychological processes of students. In order to extract the fundamental student' associated sentiments from those reviews of plain texts, sentiment analysis has emerged and is regarded as a promising technology. In this regard, this paper proposes a novel lexicon model used in college students' domain to exploit semantic relationships between words in natural language text. The sentiment words are initially extracted through lexicon to describe the orientation and the polarity of the attitudes (positive, neutral or negative). Finally, sentiment strength of opinion is calculated and cause event is identified according to the finegrained lexicon. Comparison experimental results on real data from QQ speaking data validate the effectiveness and feasibility of the proposed lexicon model, providing high accuracy levels and low false positive rates. The described lexicon model gives the valuable knowledge to college manager who should detect the students' opinion trends.
Asocial: Adaptive Task Re-Allocation in Distributed Computing Systems with Node Failures

Task allocation-the problem of efficiently allocating a set of M tasks to a set of N nodes-is a fundamental issue in distributed computing systems (DCSs). The problem is particularly challenging in the presence of fail-prone nodes. In this work, we design an adaptive task (re-)allocation mechanism, named Asocial. The Asocial allows us to optimize the utilization of system resources (including computing resources and network resources) while increasing service-level fault tolerance as well as failure resilience. In addition, we propose a cooperative game model based task (re-)allocation approach for cooperation among Physical Nodes (PNs). We consider both the performance states and reliability levels of candidate PNs when deploying tasks. Specifically, we exploit failure prediction techniques to evaluate PNs' reliability levels. As a result, we can utilize the resources efficiently and thus improve the service reliability (i.e., the probability of serving all the tasks before their delivery time). We show by means of numerical evaluations that the proposed Asocial can significantly improve service reliability, system availability as well as resource utilization. In particular, by using failure prediction result (F-measure is around 0.8), the application completion rate (ACR), the task completion rate (TCR) and the computing resource utilization (CRU) reach 85.20%, 85.67% and 78.34%, respectively. Compared with 67.30%, 70.07% and 65.79% of the initial allocation scheme, the performance achieves a significant improvement (26.60%, 22.26% and 19.08%, respectively).
Fundamental resource trade-offs for encoded distributed optimization

Abstract Dealing with the shear size and complexity of today’s massive data sets requires computational platforms that can analyze data in a parallelized and distributed fashion. A major bottleneck that arises in such modern distributed computing environments is that some of the worker nodes may run slow. These nodes a.k.a. stragglers can significantly slow down computation as the slowest node may dictate the overall computational time. A recent computational framework, called encoded optimization, creates redundancy in the data to mitigate the effect of stragglers. In this paper, we develop novel mathematical understanding for this framework demonstrating its effectiveness in much broader settings than was previously understood. We also analyze the convergence behavior of iterative encoded optimization algorithms, allowing us to characterize fundamental trade-offs between convergence rate, size of data set, accuracy, computational load (or data redundancy) and straggler toleration in this framework.
ICT Use in Higher Education in Eastern States of India

Information and communication technology (ICT) cannot be separated from our daily needs. ICT helps in reducing the disparity in wealth of educational resources. The uses of ICT in education add value in teaching and learning by enhancing the effectiveness of learning or by adding a dimension to learning. ICT may also be a significant motivational factor in students' learning. Uses of ICT in eastern states in India are lagging behind all other regions of India. In this background, the authors review the use of ICT by higher education students of four states in eastern India. They have attempted to find the factors responsible for use of ICT by the students. As the findings suggest, region, gender, education levels of households, type of courses, possession of computer and internet facility, consumption levels of households, and whether students stay in institutional hostel or not are the influencing factors to use of ICT.
A Quest to Detect Novelty Using Deep Neural Nets

In the present era, an abundance of data is found including images, videos and documents. Novelty has become an important matter to deal with. Here, focus is given on the novelty of documents specifically. In a sea of available documents how do we recognize the novel ones? With the help of deep neural networks an attempt is made to detect the novelty of documents. Detecting novelty of target documents follow the idea of binary classification. First, the similarity distance between a target document and some source document is calculated. Then a target document to source document mapping is done based on the distance value. This mapping is used as the input to a CNN model. We have also tried to analyse the effectiveness of Word Mover's Distance in detecting the novelty of the documents.
On the Effectiveness of Two-Step Learning for Latent-Variable Models

Latent-variable generative models offer a principled solution for modeling and sampling from complex probability distributions. Implementing a joint training objective with a complex prior, however, can be a tedious task, as one is typically required to derive and code a specific cost function for each new type of prior distribution. In this work, we propose a general framework for learning latent variable generative models in a two-step fashion. In the first step of the framework, we train an autoencoder, and in the second step we fit a prior model on the resulting latent distribution. This two-step approach offers a convenient alternative to joint training, as it allows for a straightforward combination of existing models without the hustle of deriving new cost functions, and the need for coding the joint training objectives. Through a set of experiments, we demonstrate that two-step learning results in performances similar to joint training, and in some cases even results in more accurate modeling.
Comparison of secure communication with AES between embedded system and general purpose computer

Embedded systems are the combination between hardware and software designed to perform some specifics functions. An embedded system is generally a part of a larger system that uses a computer network to communicate with other devices. For this reason, secure communication is of great importance to guarantee the confidentiality of the transmitted information, which can be provided by using encryption algorithms. The security is usually not a requirement when designing an embedded system, causing few techniques to be implemented for the security of these devices. This paper presents an evaluation of run-time performance of AES using a cryptography library developed for embedded systems, called Relic in a communication between two process in a general purpose computer, between a general purpose computer and a embedded system and between two embedded systems. It is considered the key sizes supported by the algorithm, the size of the transmitted data and the architecture used, also measuring the relation of the time spent by encryption and decryption and the total time for the secure communication. The results demonstrated that the architecture has a greater impact on the encryption and decryption times along with the message sizes. However, even for the communication between embedded systems, the percentage of the encryption and decryption time on the entire secure communication is smaller than 14%.
SIQA Based on 2D IQA Weighting Strategy

As image quality assessment (IQA) methods for plant images have been explored thoroughly, some SIQA algorithms apply 2D IQA methods on both stereoscopic views independently and then combine the two scores to obtain an overall quality score by a dedicated strategy. The early algorithms only combine the two scores simply to obtain the final quality score, and some improved algorithms utilize both the stereoscopic views and the depth/disparity information. All of these algorithms could achieve fairly good performance. The mainstream and state-of-art SIQA based 2D IQA weighting strategy are introduced in detail in this chapter.
POSSIBILITIES OF APPLYING A SET OF METHODS OF MATHEMATICAL STATISTICS AND INFORMATION TECHNOLOGIES IN THE BUSINESS SPHERE

The paper describes the best use of the synergy of mathematical statistics methods and the opportunities provided by information technologies for business development and a significant increase in the profitability of fixed assets of medium and large companies with a high level of competition in the occupied market.
Identification of the user by using a hardware device

In real life, people treat with their interlocutors face-to-face. In virtual life, our interlocutors are behind the walls of internet, and we do not whether they are human beings or programs. Thus, an issue of identity rises. Special attention is given to on-line banking since it is a delicate issue. We propose a hybrid software/hardware solution to overcome this problem of identity identification. The bank provides the client with a hardware device including a set of passwords. Each password is valid for only one on-line transaction. If a password is intercepted by an unauthorized person then it is useless. The password is entered by a device with a USB connector after a validation of the identity through fingerprints or other biometric measures. The concept has been validated by designing a USB card including a fingerprint reader.
Good Vibrations: An IoPT Testbed for Infotainment in a Football Stadium

A football game is an event that offers unique opportunities to research, design, and implement an extensive testbed and applications for the Internet of People and Things (IoPT). We report on the IoPT testbed we developed in the football stadium at Georgia Tech (GT), which gathers information from and about the game from multiple sources and integrates it with information about the structural dynamics of the stadium to provide a unique experience for football fans. Its capabilities are demonstrated with an analysis of the information gathered from a particular football game.
Embodied cognition significance for the ecologically valid psychological research in virtual reality

The close relationship between mind and body is neglected, but important aspect of human cognition. As anticipated by great thinkers like Vygotsky, after decades of indifference, the concept of embodied cognition finds its place in the modern research practice, partially based on the technological progress, partially based on reflection of crisis in psychological research. Embodied context like body postures or movements hugely influences various cognitive processes, special attention should be paid to sensory-motor processes. Since the majority of psychological researches stresses experimental control on the expense of ecological validity (including embodiment), practical usability of psychological findings is questionable. Recent technological development brought virtual reality (VR) systems and immersive virtual environments (IVEs) as a tools, which can provide both experimental control and ecological validity. Using VR technologies in research may not only promote knowledge about the role of body in cognitive processes, but regarding its computational capacity it may also offer a great deal of information about human behavior in environmentally valid context. These advantages are valid especially in intercultural studies, helping to understand processes standing behind human performance.
A Study on Applying Mobility Patterns for Multi-UAV Trajectory Planning

Trajectory planning tends to become one of the most important topics related to unmanned aerial vehicles (UAVs) in the past years. The reasons for this include: hardware and software development, specific legislation that covers this topic, an increase interest from end-users or manufacturers and the list can continue. Scientific literature has unlimited information related to UAV influence on various fields, but limited on multi-UAV path planning, synchronization and cooperation. For this reason, the current paper has the objective to reveal a study on trajectory planning that will underline the importance of this topic in nowadays. A series of advantages and disadvantages will be covered throughout this paper to offer readers a clear perspective on applying mobility patterns for trajectory planning.
Practical Game Design Tool: State Explorer

This paper introduces a computer-game design tool which enables game designers to explore and develop game mechanics for arbitrary game systems. The tool is implemented as a plugin for the Godot game engine. It allows the designer to view an abstraction of a game's states while in active development and to quickly view and explore which states are navigable from which other states. This information is used to rapidly explore, validate and improve the design of the game. The tool is most practical for game systems which are computer-explorable within roughly 2000 states. The tool is demonstrated by presenting how it was used to create a small, yet complete, commercial game.
Monte Carlo Tree Search Strategies in 2-Player Iterated Prisoner Dilemma Games

This study compares a player using Monte Carlo Tree Search (MCTS) against a variety of well-known Prisoner's Dilemma strategies in 2-player tournaments. The MCTS player has a simple structure and a reasonable computation budget. Nevertheless, it is highly competitive against all tested strategies. As the MCTS player constructs its game tree, it updates the probability of cooperation in response to an opponent's cooperation or defection. The trajectories of these updatings over the course of play are found to converge toward optimal counter-strategies against the particular opponent being played. In some cases the speed of progress toward an optimal counter strategy hinders the MCTS player.
Face Sketch-Image Recognition for Criminal Detection Using a GAN Architecture

One of the important cues in solving crimes and apprehending criminals is matching sketches with digital face images. The problem of matching a forensic sketch to a gallery of mugshot images is addressed in this paper. Feature-based technique is implemented and compared against proposed generative adversarial networks (GANs). The designed GAN projects alternate accuracy for the generator and the discriminator for various batch sizes, dropouts, and learning rate and is able to identify the corresponding image in the CUHK database. Simulation results show that while the feature-based matching fails the holistic method having been trained as an innovation process produced promising results.
An Approach for Bengali Automatic Question Answering System using Attention Mechanism

Question answering is a set of tools for obtaining detailed answers from user questions. At present, it is gaining very popularity day by day in the area of NLP research. There is a lot of work done in English. Still, become the seventh spoken language has not notable development at all. In Bengali very little work we've seen so far. Many types of problems can be solved by answering questions. Automatic question answering system is very much needed to solve various problems through Q&A. It is a very challenging task to create this type of system. In our paper we developed an automatic context based Question&Answering system using sequence to sequence architecture. An encoder layer will be used with a bi-directional LSTM and a decoder layer followed by an attention mechanism. The main challenge of this work is - data collection, finding the right vocabulary for word mapping and lots more. The main function of our model is to answer the questions. We have been able to successfully answer the question and reduce our training loss to 0.003.
Syntax vs Semantics

Consistency is a key property of any logical system. However, proofs of consistency usually rely on heavy proof theory notions like admissibility of cut. A more semantics-based approach to consistency proofs explores the correspondence between a logic and its relationship with the evaluation in a λ-calculus, known as Curry-Howard isomorphism. In this work, we present a comparison between two formalizations of consistency for minimal propositional logic: one using a semantic-based approach and another following the (traditional) syntactic, proof-theoretical approach in both Coq proof assistant and Agda programming language. We conclude by discussing the lessons learned during the cerfication of these results in both languages.
Virtual Memory Management using Memory Ballooning in OpenStack Cloud Platform

Management of memory in an efficient manner is one of the very important topics these days in Cloud environment. Optimized memory management techniques play the important role to handle the large amount data and processes in cloud environment. The smart memory management techniques should be integrated in cloud computing to do to memory optimization. The load balancing issues and the problem of latency can be resolved with the memory optimization. The efficiency of data optimization in cloud depends upon the resource allocation based on user demand. This is the key factor of resource optimization. As the allocation of resources are done as per the user demand then in most of the case resources are underutilized and remain idle. It causes the unused resources across the cloud platform. To get rid on this problem there is need to have continues resource monitoring and check system which will monitor the idle resources across the cloud. The various virtual memory optimization techniques are available. The cloud hypervisors uses the different memory optimization techniques which follows different principal. To handle memory optimization. The Ballooning is one of the important memory management technique in which memory of ideal virtual machine is used for the virtual machines which needs more memory to run the application.
Research on Rapid extraction of Android Backup Data based on UI-Automator

With the improvement of security regarding mobile phones and applications, incomplete data extraction arose due to utilizing one single method. In addition, there are various authority verification windows that need to be clicked manually, which affects the investigation efficiency. In this paper, a new automatic backup method of Android is proposed using UI-Automator automatic test mode to monitor, identify and click the prompt window of Android terminal intelligently. At the same time, this method utilizes the automatic backup module to simulate backup protocol of various manufacturers, and extract the backup of Android terminal through self-realized protocol.
Digital literacy as a part of continuing education library efforts

As the information technology (IT) continues being a part of everyone life, or, at least, of everyone being in position to use any device connected to some type of a communication network including mobile networks, it has become extremely critical for a person to become digitally literate. Younger generations receive education in digital literacy education during their schooling, while adults are frequently lacking such competences once they leave formal education and find employment. Public libraries aim to bridge the digital divide and provide access to critical information and activities to anyone interested in acquisition of knowledge and skills for use of IT and use of digital information sources. The purpose of the research conducted in form of a survey was to confirm an important role of public libraries as places of informal and continuing education in digital literacy in an environment different from schools and universities (places of formal education). The research results in this paper show that public libraries are active facilitators and educational partners in introducing digital literacy to their users. In spite of some obstacles, public libraries remain determined to provide access to critical information sources and activities, which would lead to greater proficiency in digital literacy.