Reviewerly/exHarmony huggingface dataset:
Energy Audit of Data Centers and Server Rooms on an Academic Campus—A Case Study

The main goal of the work reported here was to analyze the energy consumption profile needs and identify conservation opportunities in data centers and server rooms on a research-oriented major university campus. This study describes the energy audit of more than thirty small to medium size server rooms on the University of Maryland, College Park, Campus. Comprehensive energy audit investigations were carried out for each site to (1) determine existing infrastructure conditions and operational issues, and (2) identify growth opportunities and consolidation potential, as well as to (3) define low cost/no cost energy conservation measures to improve the power utilization effectiveness through the overall reduction in the energy usage. The validity of the energy conservation measures was tested through computational fluid dynamics analysis using 3D models, created using 6-sigma software from Future Facilities. Some of the energy conservation measures are quantitative, such as increasing the cooling unit return air set point temperature and number of cooling units in use, whilst other energy conservation measures are qualitative, such as optimizing the location of the vented floor tiles and modification of site layout to optimize air management. For three case study sites, the energy audit study reveals potential power utilization effectiveness improvement accompanied with annual energy savings of 93.7 MWh.
Detection of Non-Standard English Expressions by Language Sense

Abstract This paper proposes an algorithm for perception English essay, in order to improve the ability of Chinese students’ writing which expressing more standard. Because students are influenced by their mother tongue in second language acquisition, English expression is not accurate enough. From the lexical and syntactic aspects, this paper uses the language sense relevance analysis algorithm (N-LanSen) based on the N-model to deeply perceive the students’ inappropriate expression in the essay. Different extraction methods are used to extract different features, and the corresponding feedback can be given to the places where the expression is not standard. The experimental results show that the algorithm can detect the place where English expression is not standard with high accuracy.
Linked open knowledge organization systems

The Web is the most used Internet's service to create and share information. In large information collections, Knowledge Organization plays a key role in order to classify and to find valuable information. Likewise, Linked Open Data is a powerful approach for linking different Web datasets. Today, several Knowledge Organization Systems are published by using the design criteria of linked data, it facilitates the automatic processing of them. In this paper, we address the issue of traversing open Knowledge Organization Systems, considering difficulties associated with their dynamics and size. To fill this issue, we propose a method to identify irrelevant nodes on an open graph, thus reducing the time and the scope of the graph path and maximizing the possibilities of finding more relevant results. The approach for graph reduction is independent of the domain or task for which the open system will be used. The preliminary results of the proof of concept lead us to think that the method can be effective when the coverage of the concept of interest increases.
Introduction to R and Python

R is a programming language and environment for statistical computing and graphics, while Python is an interpreted, general-purpose, object-oriented, and high-level programming language. Since R and Python are open source languages and freely distributed, usage of both languages in scientific computation and data analysis have substantially increased in the last decade. R and Python are widely used for academic and commercial purposes, and it is possible to find rich information on their usage through help documentations, user communities, internet resources, and books. In this chapter, a brief introduction to R and Python programming languages is given, including their developments, advantages over other languages, package systems and structural components, installation instructions, and editing tools.
A Hand Gesture Recognition Model Using Fuzzy Directional Encoding of Polygonal Approximation

Sign Language is the basic communication medium for interacting with deaf and dumb people. Hand gesture is usually regarded as one of the principal components of Sign Language. Each gesture has a unique meaning assigned to it. This paper proposes a framework for hand gesture-based Sign Language recognition from a video stream using computer vision approaches. The proposed framework segments hand-palm region in the video stream using background subtraction method and skin color models. Thereafter, a fuzzy directional encoding strategy is employed on the polygonal approximation of a gesture to form features which are used to train an ANN classifier for developing a gesture prediction model. This proposed model considers digits as a significant part of Sign Language and the model seems working with acceptable accuracy in predicting hand gestures representing various digits in Sign Language.
Influence of Student Computer Literacy on Qualifications for Creating Virtual Learning Environments

This paper presents the results of research into computer literacy among students from informatics study programmes, and their qualifications in the area of creating virtual learning environments. The participants in the study were students from Serbia, Croatia, Hungary, Macedonia and Slovakia. It is evident that clear differences exist, but similarities as well in terms of computer literacy among students at technical universities in the region. Computer literacy is seen to influence the choice of methods employed for testing the effectiveness of web applications. It is necessary to make changes to the curricula at informatics faculties, and to highlight web usability terms, as well as to introduce subjects that will deal with testing web applications in the context of virtual learning environments.
Immersive Professional Gaming in the Higher Educational Establishments in Montenegro and Ukraine

This article reveals the meaning of the concept of immersive professional gaming (IPG) for the student's professional learning. Summarized results of an experiment conducted among students from Montenegro and Ukraine using IPG and virtual learning spaces are presented and discussed. The results of the experiment indicate a high interest and satisfaction after the use of IPG in the educational process in higher education institutions.
Image Super Resolution Based on Gradient Constrained POCS Method

Abstract A gradient constraint set based on edge detection is proposed to solve the problem of edge blurring in traditional projections onto convex sets (POCS) images reconstruction. Using the complete edge information of the original low-resolution(LR) image, the edge gradient constraint is applied to the reconstructed image, and the high-frequency information of the reconstructed image is retained to solve the problem of blurring the reconstructed image edge. And this paper uses the resolution test card to carry out simulation experiments, quantitative evaluation of the reconstructed image with respect to the LR images to improve the actual resolution of multiple. Simulation results show that the proposed method can reduce the edge blur of the reconstructed image, and the actual resolution is greatly improved compared with the traditional convex set projection method.
Reader System for Transliterate Handwritten Bilingual Documents

India is a Multistate- Multilingual country. Most of the people in India used their state official language and English is treated as a binding language used for form filling or some official work. So there is a need to create a system which will convert the handwritten bilingual document into digitized form. This paper aims at development of reader system for handwritten bilingual (Marathi-English) documents by recognizing words. This facilitates many applications such as Natural language processing, School, Society, Banking, post office and Library automation. The proposed system is divided into two phases. The first phase focuses on recognition of handwritten bilingual words using two different feature extraction methods including combination of structural and statistical method and Histogram of Oriented Gradient Method. K-Nearest Neighbor classifier is used for recognition. This classifier gives 82.85% recognition accuracy using Histogram of Oriented Gradient method. The dataset containing 4390 words collected from more than 100 writers. The second phase focuses on digitization and transliteration of recognized words and conversion of transliterated text into speech, which is useful in the society for visually impaired people.
Change Your Mind

Among the most challenging Learning Objectives are those that require the learner to unlearn behavior - especially behavior deeply rooted in ancient evolutionary selection [1]. One such challenge is the mitigation of cognitive bias. After observing that traditional linear training does not reliably deliver lasting improvement to such deeply held cognitive behavior [2], a group of researchers began to experiment with game-based learning. Much of the success of the game experiments can be attributed to the efficacy of Adaptive Instruction Systems (AIS). The principles of AIS are usually applied consciously to the design of game-based learning. Even when they are not explicitly invoked, the nature of good game design is inherently one of adaptive instruction. This is most easily demonstrated with a case study of one of the games - Enemy of Reason. Enemy of Reason has been shown to be a particularly efficacious tool for mitigating Cognitive Bias. A large scale and complex game, it employs a variety of mechanics rooted in game design, adaptive instructional design and in the literature of intelligence analysis. Enemy of Reason is acutely relevant to the current moment. It treats cognitive bias not only as a natural phenomenon but as the result of an attack by an enemy determined to wage psychological warfare.
A Secure Steganography Scheme Using LFSR

Steganography is a technique to hide the secret data inside some other cover files (like text, image, audio, etc.) in such a way that it prevents the detection of the secret data within the cover files. In this paper, a new scheme of concealing secret data has been introduced where the locations of hiding the secret bits will be generated by linear feedback shift register (LFSR). Using LFSR, we will compute random numbers (within a given range) which will determine the specific pixels where secret bits of the secret data will be concealed. We use least significant bit (LSB) technique where the secret bit will be stored at the least significant bit position of the pixel. Choosing the cover pixels from cover image randomly will strengthen the security of LSB technique.
The Elusive Model of Technology, Media, Social Development, and Financial Sustainability

We recount in this essay the decade-long story of Gram Vaani, a social enterprise with a vision to build appropriate ICTs (Information and Communication Technologies) for participatory media in rural and low-income settings, to bring about social development and community empowerment. Other social enterprises will relate to the learning gained and the strategic pivots that Gram Vaani had to undertake to survive and deliver on its mission, while searching for a robust financial sustainability model. While we believe the ideal model remains elusive, we conclude this essay with an open question about the reason to differentiate between different kinds of enterprises—commercial or social, for-profit or not-for-profit—and argue that all enterprises should have an ethical underpinning to their work.
Multiprecision ANSI C Library for Implementation of Cryptographic Algorithms on Microcontrollers

Current cryptographic algorithms work with operands that are several times wider than the machine word, e.g., the still popular RSA algorithm shall use at least 2048-bit keys. Such algorithms therefore require libraries that implement multiprecision arithmetic. Existing libraries are either not tailored for microcontrollers, or they implement an incomplete set of multiprecision operations, which limits the implementation of some unusual cryptographic algorithms on microcontrollers. In this work, we present a novel ANSI C library that implements also some less common operations like, e.g., multiprecision integer division. The library was designed with respect to the use on microcontrollers and has been tested on ARM M4-based microcontroller Microchip CEC1302.
Applications of Fuzzy Expert Systems in Farming

Agriculture, cattle breeding, and poultry farming constitute the backbone of the Indian economy. Today, India is ranked first worldwide in terms of milk production, second in terms of farm output, and third in terms of poultry output (eggs production). Over the year, agriculture, poultry farming, and cattle breeding have contributed towards India's GDP but is narrowly declining with the country's economic growth due to lack of initiatives. Fuzzy expert systems are used for various activities with an objective to get better results and good yield. Expert systems combine the experimental and experiential knowledge with the intuitive reasoning skills of a multitude of specialists to aid farmers in making the best decisions to improve the quality and increase the production. Weather and climatic changes play important roles. Thus, any changes in them affect the quantity and quality of production. Therefore, weather prediction plays an important role and helps the farmers to take right decisions and precautions to safeguard the production.
Data Analytics for Engagement In Stem Education

It has always been a great challenge to inspire young generation to pursue in STEM education. This paper aims to provide a thorough analysis on the application of a data analytics model-Principal Component Analysis (PCA) to analyze statistically the parameters or the probability of youth who may opt for STEM education. Therefore, many policy makers can take proactive measures to strategize to elevate the engagement of people in the STEM sector.
Capabilities of Email Forensic Tools

In many digital forensic investigations, the analysis of email data may be necessary. However, this may violate the privacy of the person whose emails are being analyzed. To avoid this violation, investigators generally run keyword searches to reveal only those emails that contain at least some of the keywords. Forensics investigators need to choose an email forensics tool that supports comprehensive keyword search and reporting. Selection of an appropriate tool requires knowledge of the capabilities of the tool. In this research, our aim is to help the investigators in the tool selection process by experimentally examining four different email forensics tools and evaluating their keyword search and report generation capabilities as well as some other features. The other features include but not limited to email format they support, size of the file they accept, format of the reports, etc. We use Enron email dataset as input to the tools.
A Framework to Identify People in Unstructured Environments Incorporating Biometrics

We outline our computational framework for identity. We have a prototype web application, but this paper is a conceptual level. The interest is in identity as an equivalence relation and how information can be evidence for identity hypotheses. Our account is based on the situation theory of Barwise and Perry. We consider a (legal) identity case to be a constellation of situations, and we indicate how the structure of such a case facilitates discounting and combining evidence using Dempster-Shafer theory. Semantic Web resources are used to capture the structure of evidence as it relates to situations. We have developed OWL ontologies and use the concepts therein defined in RDF triple stores to capture case data. URIs (as used in the Semantic Web) are used for unambiguous references to individuals. We sketch a scenario that uses two biometric modalities in an uncontrolled environment and show how our framework applies. Recently, biometrics has gained the limelight as a means to identify individuals, but much else may be available for this task, including sensor data, witness reports, and data on file. To our knowledge, this is the only framework that in principle can accommodate any kind of evidence for identity. It is not an alternative to biometrics, but rather provides a way to incorporate biometrics into a larger context.
A Hybrid Mining Approach: Gender Prediction from Handwriting

Although after many current technological achievements, there is still not any methodology which will allow a computer to perfectly copy the content of any complex handwritten document. The handwriting recognition problem presents many difficulties as There are two variants of the handwriting recognition problem Online recognition problem deals with handwriting written with some electronic device that means it deals with real-world problems. whereas offline handwriting problem deals with handwriting which has been written previously and is kept stored. In the field of Human and Computer Interaction, if the gender of a user can automatically be predicted, just by using his or her signature, the system could offer him/her a more personalized interaction and care. In spite of the fact that the facts confirm that females composing is alluring and neater than male one, this isn't valid for every one of the cases. There are numerous precedents where we can discover ladylike appearance in manly penmanship. we intend to investigate the connections between the penmanship of various sexual orientations. To foresee the sexual orientation of people from examined pictures of their penmanship. This is finished by removing the arrangement of highlights from composing tests and preparing classifier to learn and separate between them. Highlights which is utilized for arrangement is tortuosity, shape, heading, chain code, and edge bearing. In this article, we mean to break down the connections between the penmanship of various sexual orientations. In this examination utilized, half breed classifiers are utilized and dissected their resultant. Furthermore, the resultant demonstrates the half and half classifiers give better outcomes.
Collaborative diversity control strategy for random drift particle swarm optimization

Random drift particle swarm optimization (RDPSO) is a swarm intelligence algorithm inspired by the trajectory analysis of the canonical particle swarm optimization (PSO) and the free electron model in metal conductors placed in an external electric field. However, the RDPSO algorithm may easily encounter premature convergence when solving multimodal optimization problems. In order to deal with this issue, a new collaborative diversity control strategy for RDPSO is presented in this paper. Within this strategy, two kinds of diversity measures are used and changed in a collaborative manner to make the evolving process of the RDPSO controllable, so that premature convergence can be avoided and a final good solution can be found. Experimental results, when comparing with the canonical RDPSO and the canonical RDPSO using ring neighborhood topology, show that the proposed collaborative diversity control strategy can significantly improve the performance of the RDPSO algorithm for multimodal optimization problems in most cases.
Improving Visual Quality for Vector Schemes

To further improve the visual quality for grayscale secret images, we introduce the vector VC approach that encodes one block as a unit. First, we outline the basic vector VC for binary secret images. Then, we combine the AbS framework with vector VC to get better visual quality than AbS-based probabilistic VC and AbS-based random grid VC. For separate halftoning and VC encryption, we use the blackness preserving algorithm. For grayscale secret image, we develop an AbS-based vector VC algorithm.
Lunar Rover Path Planning Based on Comprehensive Genetic Algorithm Based on Slip Prediction

Abstract Aiming at the problem that the lunar rover path planning algorithm generally has slow convergence rate, falls into local optimal solution, neglects the mutual applicability of environment modeling technology and path planning algorithm, a comprehensive genetic algorithm based on virtual three-dimensional model is proposed. By setting the genetic factor unchanged, the terrain comprehensive cost function is added to set the fitness function. Using genetic algorithm and improved comprehensive genetic algorithm, after 100 simulation experiments, the improved comprehensive genetic algorithm has good search performance, fast convergence and high stability. The key words of this paper are as follows: path planning, terrain comprehensive cost function, genetic algorithm.
A demonstration of using the model reference principle to develop the function-oriented adaptive pulse-coded neural network

How can one design an adaptive pulsed neural network that is based on psycho-phenomenological foundations? In other words, how can one migrate the adaptive capability of a psychologically modeled neural network to a pulsed network? Neural networks that model psychological phenomena are at a larger scale than physiological models. There is a common presumption that pulse-coded neural network analogs to non-pulsing networks can be obtained by a simple mapping and scaling process of some sort. But the actual in vivo environment of pulse-coded neural network systems produces a much more diverse set of firing patterns. Thus, functional mapping from traditional neural network systems to pulse-coded neural network systems is much more challenging than has been presumed. This paper demonstrates that the employment of model reference adaptation as a method for applying scientific reduction is a powerful design tool for the development of a function-oriented adaptive pulse-coded neural network. The performance surface is empirically obtained by comparing the performance of the pulsed network to the non-pulsing network. Based on this surface, the adaptive algorithm is a combination of gain scheduling and steepest-descent method. Therefore, the adaptive property of the pulse-coded neural network is built upon a psycho-physiological foundation.
Explorations in AR: Finding Its Value

This paper presents the main findings regarding the overall effectiveness of an AR-based wearable device for different types of users performing basic, common tasks throughout a few demo scenarios, thus identifying opportunities for improvement and further investment. A series of user tests were carried out among participants using this head-mounted prototype while different aspects of their interaction and overall experience were evaluated. It was given special attention to desirability factors, as well as pain points and obstacles to completing the different scenarios. This paper presents main insights regarding several features for an ideal head-mounted AR experience to the user, as well as their view regarding the future of digital media consumption. It also discusses some limitations and lessons learned for future work. Our results allow us to shed light onto the scope of expectations of potential end users, in order to help in the design and engineering of these devices. We argue that the value of exploratory studies of such as these lies in its potential to delve into innovative paths and their potential implications, otherwise difficult to trace.