Reviewerly/exHarmony huggingface dataset:
Pixel re-representations for better classification of images

Conventional image capture approaches usually try the best to obtain high-resolution images to allow people to see details of the objects. Still, the high-resolution images do not always imply efficient classification accuracy. Holistic information of images has a more critical influence on the identification of the corresponding objects than detailed information of images. In this paper, we propose to attain optimal pixel re-representations of images and exploit them to perform classification. The merits of the proposed approach are as follows. (1) It automatically selects optimal re-representations for original images from a number of candidates by virtue of a feasible procedure. (2) Maximizing the ratio of the between-class distance to the within-class distance not only allows the optimal re-representations to be attained but also can adequately prompt sparse representation and collaborative representation to attain a better classification accuracy. The procedure of maximizing the ratio makes the obtained optimal re-representations of all objects as diverse as possible. Therefore, the attained linear combination of all training samples, in the form of vectors, of all objects can better express the test sample and has less expression error in comparison with the corresponding case based on original training samples of all objects. The experiments also prove that the optimal pixel re-representations are helpful to improve not only the sparse representation and collaborative representation but also other classification image classification approaches, to obtain more satisfactory classification accuracy.
Meta Learning and Software Effort Estimation

Studies in software effort estimation typically seek to discover the best estimator which will perform best in any circumstances. However, the present study opposes that such a single best estimator may not exist, and rather suggests to seek the solution to determine the most suitable estimator for a given dataset. This study proposes MLS (short for a meta-learning framework for software effort estimation) to explore the possibility to apply meta learning to the software effort estimation problem. The approach hypothesizes that the same estimation algorithm will offer similar accuracy for similar datasets, where the similarity between datasets is determined by quantifying their meta characteristics, such as the mean absolute correlation between all the numeric variables. Based on the performance evaluation undertaken on ten industrial datasets, together with six robust performance measures, and Brunner's robust statistical test method, MLS outperforms 48 other effort estimators. It can be preliminary concluded that the meta-learning approach developed in the study is able to provide higher accuracy than to use only one single estimator on all the datasets. More studies on meta learning would be greatly useful to establish a greater degree of accuracy on the estimation activities in empirical software engineering.
Research on the Performance Test Method of Information System Based on the Domestic Software and Hardware Platform

In order to more accurately evaluate the requirement-meeting situation and scalability of performance index of the information system based on the domestic software and hardware platform, this paper proposes a performance test method that integrates performance, margin, capacity and strength tests. The test result shows that the method is of guiding significance for evaluating the performance index of the system and exploring its boundary strength.
Supply Chain Performance in the era of Digitisation: The role of Electronic Supply Chain Management

The advancements in information technology have enabled the supply chain members to share real-time information, which further facilitates the integration of supply chain members. Since supply chain integration is a prerequisite in achieving superior supply chain performance, the objective of the current study is to determine the relationship between IT-enabled supply chain management (e-supply chain management), supply chain integration, information sharing and the performance of supply chain as a whole. Also, many authors are of the view that e-SCM and information sharing can positively enhance the integration among supply chain members, thus, another objective is to determine whether supply chain integration mediates the relationship between e-SCM and supply chain performance or not. Similar relationship is tested with information sharing as a mediator. For this, samples of 293 respondents are taken from the pharmaceutical manufacturing units and pharmacies in India. Structural equation modelling is applied to test these relationships.
Design of ecological environment monitoring platform for substituting small hydropower for fuel area

Based on the current situation and urgent needs of China's substituting small hydropower for fuel engineering ecological environment, a small-scale substituting hydropower for fuel engineering ecological environment monitoring platform based on wireless sensor network was designed and proposed. Focus on real-time dynamic acquisition of eco-environment parameters of sensor nodes integrating water quality sensors, soil sensors and gas sensors on the on-site inspection platform. The ZigBee technology is used in close proximity, and the GPRS wireless communication technology is used to realize the establishment and data transmission of the sensor network. The system effectively improves the convenience and reliability of the ecological environment monitoring of substituting small hydropower for fuel engineering.
Influence of Perspective on Dynamic Tasks in Virtual Reality

Users are increasingly able to move around and perform tasks in virtual environments (VEs).Such movements and tasks are typically represented in a VE using either a first-person perspective (1PP) or a third-person perspective (3PP).In Virtual Reality (VR), 1PP is almost universally used.3PP can be represented as either egocentric or allocentric.However, there is little empirical evidence about which view may be better suited to dynamic tasks in particular.This paper compares the use of 1PP, egocentric 3PP and allocentric 3PP for dynamic tasks in VR.Our results indicate that 1PP provides the best spatial perception and performance across several dynamic tasks.This advantage is less pronounced as the task becomes more dynamic.
Towards a Decision Support System Based on a Multi-Agent Systems for Educational Management by School Project

In Moroccan context, ministerial directives insist on the adoption of the school project as a tool for educational management of a school. But for this, actors need some tools to help in the development of the project such as the diagnosis of the current situation and the classification of priorities. The quantitative data provided by the MASSAR information system and other sources of information must be used scientifically to generate new knowledge useful for the decision-making of education managers and which will consequently contribute to improving the performance of the Moroccan school, this on the one hand. On the other hand, a school project is designed for a period of three years; it would be interesting to be able to predict the expected results of such a project and to be able to regulate it as and when it is implemented. In this work, we propose a new approach that aims to contribute to the development of a decision support system in the field of educational piloting based on the multiagent approach.
Spatial-color mode detection in UV pairwise projection of the CIE LUV color space

In this work, we present a color image segmentation algorithm considering pairwise color projection. Our approach is based on mode detection of the 2-D histogram. The pairwise projection is chosen by considering the most relevant color components to represent the chromatic information. For this purpose we consider a luminance-chrominance space where the chromatic information is presented by two ones components and other one component presents the achromatic information (called luminance). In this work, we consider the CIE LUV color space which is more even in distribution and more accordant with humans perceive color. The modes detection process consists in the first step of partitioning the 2-D histogram in the UV chromaticity plane using the watershed transform, followed by a mode merging algorithm taking into account both the pixel color distribution in the pairwise color projection and their spatial arrangement in the image. We show on various images that the expected modes are correctly identified.
Genesis of Information Technologies as a Marker of the Genesis of Hierarchies in the Humankind’s System: A Model Representation

According to the informatics-cybernetic model of the Humankind’s hierarchical system, information technologies (IT) appear historically: 1) IT signal poses/sounds/movements: the characteristic size (radius of the same area circle) is ~64 m, the anthropogenic impact accuracy is ~28 cm, start ~28.23, culmination ~9.26 million years ago, carrier of pre-humans Hominoidea; 2) IT mimics/gestures: ~1 km and ~1.8 cm, ~1.86 and ~0.612 million years ago, Homo archaeo-paleolithicus and Homo mezo-paleolithicus; 3) IT speech/language: ~15 km, production technology accuracy ~1.8 mm, ~123 and ~40 thousand years ago (near the IT-initiated Upper Paleolithic revolution), Homo sapiens’ (H.s. paleolithicus superior and H.s. neolithicus); 4) IT writing: ~222 km and 80 μm, ~6100 and ~700 years BC (near the Urban revolution of “axial” time), Homo sapiens’’ (H. paleometallicus and H.s. neometallicus); 5) IT replicating texts: ~3370 km and 5 μm, ~1446 and ~1806 years AD (near the industrial revolution), Homo sapiens’’’; 6) IT computer: ~51 thousand km (planetary) and 0.35 μm, ~1946 and ~1970 (near the computer revolution – the creation of microprocessors), Homo sapiens ‘‘‘‘; 7) IT network: ~773 thousand km (Near Cosmos) and 23 nm, ~1979 and ~2003 (about the revolution of mobile telephony, Internet, etc.), Homo sapiens’’’’’; 8) nano-IT (possibly, nano-hardware supported selective telepathy): ~11.7 million km (Intermediate Cosmos) and 1.5 nm, ~1981 and ~2341, Homo sapiens’’’’’’ (H.s. informaticus, according to the extrapolation of the archaeological epoch “Fibonacci’s” model). This list reflects the genesis of IT – part of the genesis of hierarchies (subsystems) in the Humankind’s system. The main components of the genesis of hierarchies include anthropo-, psycho-, techno-, culture-, socio-, ideal-genesis, etc. Thus, the genesis of IT, which has quantitative (model) estimates of the characteristic times of its course, can act as a marker both for the genesis of hierarchies in general and for its components.
A Comprehensive Mentoring Model for Cybersecurity Education

There has been a significant and fast growing workforce demand for qualified cybersecurity professionals. Cybersecurity education should help students to acquire professional knowledge, skills and abilities (KSAs) that are essential to success in cybersecurity careers. Mentoring should be an integral component of cybersecurity curriculum and learning activities. This research paper proposes a comprehensive model of mentoring for cybersecurity education that consists of the key components of career guidance, academic advising, as well as guidance and mentoring in research, certifications, service learning, ethics, professional skills and extracurricular activities. The goal of this research is to contribute an effective model with practical strategies, methods and experience for preparing cybersecurity professionals.
Long Short-Term Memory based Conversation Modelling

Conversation models are becoming more popular with every day. Major companies like Apple, Microsoft, Google and Amazon have invested major funds and time and effort into such models. However, at present, these conversation models are predominantly voice chat. This does not create much difference because all the algorithms and methodologies all of the deep natural language processing techniques are all applicable to both text and voice. Our model predicts the next sentence given the previous sentence. We have developed a neural network-based model to answer questions in the form of generating sequences about the data it has been trained upon. Our model makes use of two popular neural network architecture: Sequential Learning using Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM).
PACFR: Pixel Arithmetic Computation based Face Recognition

The face recognition approach plays an important role in electronic security systems. In this paper, we propose Pixel Arithmetic Computation based Face Recognition (PACFR). The color face images are changed into grey scale images and also the different sizes of face images to 90 × 90 size in pre-processing unit. The novel concept of Pixel Arithmetic Computation (PAC) is introduced for sharp representation of edges and extracts more stable features for local changes in images. The pre-processed image is segmented into overlapped 3 × 3 matrices. The PAC technique I is used to extract sharp edge information using arithmetic operations on pixel values of 3 × 3 matrix The middle pixels of borders of 3 × 3 matrix are considered and multiplied by power of two in PAC technique II to enhance pixel values. The final features are obtained by concatenative PAC I and PAC II techniques. The Euclidian Distance (ED) is used here to evaluate final features of database and test images to calculate performance parameters. It is seen that the performance parameters of the proposed technique is improved compared to existing technique.
Investigating the Necessity of Meaningful Context Anchoring in Augmented Reality Smart Glasses Interaction for Everyday Learning

The wearable nature of smart glasses opens up many possibilities for these devices to support informal and everyday learning. A key question arises: is physical contextualization necessary for smart glasses to support learning? This is a within-subjects study comparing the use of meaningful anchoring (MA) and arbitrary anchoring (AA) smart glasses in a simulated learning scenario. Results showed AA performed better on learning scores and task performance, but that AR immersion and system usability were better for MA. The necessity varies depending on usage scenarios. MA is more suitable for UX-oriented scenarios, while AA is preferred for efficiency-driven scenarios.
Actual problems of modern software engineering

Abstract The article discusses some pressing issues of training specialists in the field of software engineering. The characteristic problems of this scientific field are presented. The main standards, methodologies and training programs for software engineering specialists are briefly described. Based on the statistical data for 2019, the place of the programs 09.03.00 and 09.04.00 in the educational structure of the Russian Federation and the Krasnoyarsk Territory is shown. The problem of reducing the gap between the formation of software engineering and the requirements of the IT industry is considered.
Affective Embodiment: Embodying emotions through postural representation in VR

The Proteus effect suggests that users try to behave according to the perceived identity of their avatar. However, what happens when the way an avatar moves communicates an emotional state? Transforming movement is a unique quality of VR, allowing avatars to represent user behavior in a novel way. We conducted a within-subjects study to investigate the potential of transformed embodied experiences on users’ emotional states. We assigned participants to embody three generic avatars that moved in ways that evoked positive and negative emotional states. Each avatar followed the participant’s tracked movements, but these movements were transformed to present exaggeratedly open, closed or neutral postures. Participants self-reported Positive and Negative Affect, embodiment, and Beck Depression Inventory scores. We discuss the relationship between the avatar postures and participants’ self-reports, along with the clinical implications of experiencing a transformed virtual body.
Library: Illustration: Find Books

Illustration is a type of art that is a visual explanation or interpretation of a written text.
Analysis of Depth-First Search Based Mousavian Technique’s Scalability for Software Bug Localization

Debugging in software development is one of the most time-consuming processes. To that end, various bug localization techniques have been developed. One approach showing great result is the graph mining-based bug localization techniques. Unfortunately, the graph mining algorithm tends to scale poorly when dealing with large graph input. Mousavian et al. developed a new bug localization technique that replaces the graph mining algorithm with a new, more scalable graph analyzing technique. However, the mousavian technique has not been tested using highly complex graphs as input. In addition, its suspicious paths generation algorithm was not explained in detail to enable complete implementation. The test result shows a suspicious paths generation algorithm can be implemented using a modified depth- first search algorithm. Furthermore, the mousavian technique can be categorized as a scalable bug localization technique because it has a polynomial growth pattern for both processing time and maximum memory usage. However, the proposed depth-first search algorithm shows an exponential growth pattern for its process time. The processing time of the depth-first search algorithm can be significantly reduced by limiting the depth-first search depth limit at the cost of information completeness.
Methodological Features of the Development of Creative Abilities in the Framework of “Cryptography” Elective Course for Students in 10–11 Grades

The article is devoted to the development of creative abilities of students in the framework of elective course on the example of the topic “Cryptography”. These recommendations can be used not only during extracurricular activities: assignments can be adapted to many topics of the discipline “Computer Science and ICT”, as well as for other disciplines of primary and secondary general education.
Moving to Client-Side Hashing for Online Authentication

Credential leaks still happen with regular frequency, and show evidence that, despite decades of warnings, password hashing is still not correctly implemented in practice. The common practice today, inherited from previous but obsolete constraints, is to transmit the password in cleartext to the server, where it is hashed and stored. We investigate the advantages and drawbacks of the alternative of hashing client-side, and show that it is present today exclusively on Chinese websites. We also look at ways to implement it on a large scale in the near future.
A Comparative Study of Representation Learning Techniques for Dynamic Networks

Representation Learning in dynamic networks has gained increasingly more attention due to its promising applicability. In the literature, we can find two popular approaches that have been adapted to dynamic networks: random-walk based techniques and graph-autoencoders. Despite the popularity, no work has compared them in well-know datasets. We fill this gap by using two link prediction settings that evaluate the techniques. We find standard node2vec, a random-walk method, outperforms the graph-autoencoders.
A Systematic Survey on Load Balancing in the Cloud

Web growth has been driven by a number of techniques. In massive scale processing, cloud computing is the rising technology. It is a method that consists of varied software and Web-enabled services. As cloud computing grows speedily and purchasers are stringent a lot of services, the traffic on the cloud increases tremendously. Thus, managing load balance is very interesting and important research area nowadays. A decent load balancing algorithm can enhance the performance and resource utilization by dynamically distributing workload among a range of nodes within the system. This paper addresses a comprehensive summary on load balancing algorithms, challenges, and various presently offered load balancing software and its features.
Relative Room Size Judgments in Impossible Spaces

In VR, “impossible spaces” allow virtual rooms to occupy overlapping portions of physical space. We investigated how size judgments of impossible spaces are influenced by the ratio of the sizes of overlapping rooms. Participants (n=36) were randomly assigned to one of three conditions and completed 13 trials. Participants’ reports accurately reflected the true ratio of the rooms in all conditions; however, participants reported less extreme ratios as the ratio increased. The results suggest that important spatial relationships are preserved in impossible spaces, namely 1) judged sizes of individual rooms, and 2) judgments concerning the relative sizes of different rooms.
A Survey on Load Balancing in Cloud Computing

Cloud is a medium for providing virtual services and resources that can be accessed and utilized easily. Along mechanism in Internet storage content is saved online, retrieved from various distributed and interconnected resources which form a cloud across the network. The prime concern faced by the Internet content system securing, as a result the owner encrypts and utilizes an search technique for accessing the data. When using a cloud storage mechanism, the third party gains the control to import your highly secured and private data to put up in the cloud. The data owners have to deal with various security issues because of entailing intense safety and confidentiality. The present paper outlines the cloud types based on cloud usage and services offered. The focus of the research being to provide secured data sharing by comparing and assessing the functionality of different symmetric encryption algorithms like parallel homomorphic encryption algorithm (PHEA), KUNodes, triple data encryption algorithm (3DEA), Also by implementing PHEA there is flexibility in data sharing, fine-grained access control, improvised average execution time and memory and data size. The research work concludes that PHEA is highly suitable for data sharing compared to other techniques of symmetric encryption.
Gold metallogeny: A tribute to Academician Yusheng Zhai

• A brief summary of the major accomplishments of Academician Zhai in the study of ore deposits is provided. • A set of outstanding contributions on various types of gold deposits are summarized. • An introduction to the papers in this special issue related to gold deposits from different tectonic units is provided.
A Pragmatic Logic for Expressivism

Abstract This article aims to show that the incompatibility between the application of logic to norms and values and the expressive conception of these notions – basically summed up by the Frege–Geach problem – can be overcome. To this end, a logic is constructed for the expressive conception of norms and values which provides a solution to the Frege–Geach problem and is not affected by the limitations that occur in some previous attempts. More specifically, a pragmatic language LP is introduced which is an extension of the language L of standard propositional logic, obtained by adding two categories of logical‐pragmatic signs to the vocabulary of L : the signs of pragmatic mood ( , , , standing for assertion, obligation and approval, respectively) and the pragmatic connectives (∼, ∩, ∪, ⊃, ≡, standing for pragmatic negation, conjunction, disjunction, implication and bi‐implication, respectively). The notions of pragmatic validity, consistency (satisfiability), compatibility, equivalence and inference are then defined, and some criteria of pragmatic validity are given. It is thus possible to carry out in LP inferences on norms and values expressively understood, adequately formalizing Geach's problematic inferences.