Reviewerly/exHarmony huggingface dataset:
A Comprehensive Study of Performance Appraisal of the Business Entity

Purpose: Performance appraisal is described as the measurement of outcome to generate reliable data on its effectiveness and efficiency. Performance appraisal measures the business activities and implements a strategy to bring them back to the desired position. This paper is useful in presenting a systematic understanding of the performance appraisal concept of the business entity.Research Methods: The Study of performance appraisal of a business entity has been performed using the literature review and case study analysis, interviews, and personal observation as the secondary source of data.Findings:  It could be interpreted that the selection of methodology for performance appraisal should be based on the objective, strategy, mission, and vision of the company. The performance indicators could be financial and nonfinancial. Therefore, for a precise performance appraisal, the purpose and subjective methods needed to be combined based on the organisation's requirement. Conclusion: The performance appraisal's primary objective is to measure the business working by aligning the long term and short-term strategy. Long-term performance reflects the vision, while short term business performance is related to operations. The performance appraisal method should create an alignment between the measurement of procedures and strategies.
Fastformer: Additive Attention is All You Need

Transformer is a powerful model for text understanding. However, it isinefficient due to its quadratic complexity to input sequence length. Althoughthere are many methods on Transformer acceleration, they are still eitherinefficient on long sequences or not effective enough. In this paper, wepropose Fastformer, which is an efficient Transformer model based on additiveattention. In Fastformer, instead of modeling the pair-wise interactionsbetween tokens, we first use additive attention mechanism to model globalcontexts, and then further transform each token representation based on itsinteraction with global context representations. In this way, Fastformer canachieve effective context modeling with linear complexity. Extensiveexperiments on five datasets show that Fastformer is much more efficient thanmany existing Transformer models and can meanwhile achieve comparable or evenbetter long text modeling performance.
Bitcoin’s energy consumption and social costs in relation to its capacity as a settlement layer

Bitcoin runs on energy. The decentralized network’s amount of energy consumption has resulted in multifaceted discussions about its efficiency and environmental impact. To put Bitcoin’s energy consumption into perspective, we propose to relate (a) the energy consumption in TWh and (b) resulting social costs in the form of carbon emissions to the Dollar value settled on the Bitcoin network. Both metrics allow to relate and quantify the capacity of Bitcoin as a settlement layer to the network’s energy consumption and resulting carbon emissions, or social costs. We find that in early 2021 Bitcoin (a) settles between $2,333 and $7,555 for each Dollar spent on energy and (b) that, on average, a Dollar settled on the Bitcoin blockchain causes in social costs between 0.007% and 0.01%, depending on the estimated energy consumption converted into the costs of carbon emissions. These results help to assess the efficiency, cost and sustainability of Bitcoin and may allow a comparison of Bitcoin with existing settlement base layers such as Fedwire or gold.
Spire Muse: A Virtual Musical Partner for Creative Brainstorming

We present Spire Muse, a co-creative musical agent that engages in different kinds of interactive behaviors. The software utilizes corpora of solo instrumental performances encoded as self-organized maps and outputs slices of the corpora as concatenated, remodeled audio sequences. Transitions between behaviors can be automated, and the interface enables the negotiation of these transitions through feedback buttons that signal approval, force reversions to previous behaviors, or request change. Musical responses are embedded in a pre-trained latent space, emergent in the interaction, and influenced through the weighting of rhythmic, spectral, harmonic, and melodic features. The training and run-time modules utilize a modified version of the MASOM agent architecture.
Grouping of E Learners Using Fuzzy K-Medoid Clustering

The process of clustering in the general perspective is limited to the grouping of data into clusters and finds its applications in the fields of information retrieval, text ranking and classification and more. The dimension of e-Learning is to improve learning with various tools and technologies. Grouping of learners based on their learning levels is found to improve the learning abilities. Scientific method to cluster the learners is not available in literature, which can further simplify the amalgamation of learning complemented through clustering. This paper is an attempt to examine the aspects of implementing clustering to group the learners according to their learning abilities.
A general nonlinear neuron model

An accepted conclusion for modeling a physiological neuron is its divisibility into two mathematical processes. These are the digital process and the analog process. In a 1943 paper McCulloch and Pitts presented a neural model performing switching logic (an IT digital process). Their model represents the basis of the model used in the well-known Perceptron, devised by Rosenblatt in 1957. The Perceptron is a neural network of models that included varying weights, which corresponds to a neuron’s analog process. This talk will define the digital and the analog processes. These processes will be associated with a physiological neuron’s anatomy. The Perceptron’s neuron model continues to be used in current neural networks despite a serious limitation of only realizing linearly separable switching functions. Linearly separable switching functions will also be defined. The currently used “linear” neuron model will be shown to have severely limited switching logic realizations. Linear separability will also be defined. A general non-linear neuron model will be defined, which is capable of performing all possible switching logic realizations. Examples of both a linear neuron model’s and nonlinear neuron models’ switching logic realizations will be included. The proposed nonlinear neuron model, which more accurately takes into account actual neurophysiologic mechanisms, can form the basis of modeling network processes at all levels of the nervous system, including the brain.
Design A Multi Biometric System for Safe Access to Buildings

Designing a multi-biometric system for safe access to buildings is a very critical process because this system will act as an alternative of humans in observation, and must make smart decisions to protect the building from any intruder depending on the biometric information of the entering persons. In this paper a full design of a proposed multi-biometric system will be presented, two sensors are used (Visible and Thermal). the proposed system consists of several subsystems The first is the construction of a database that contains all the photos and information about each person who belongs to the building, the central system using visible and thermal cameras, and the peripheral system using visible cameras only. The central system is capable of remotely identifying and ensure of the health condition (Temperature, Heart Rate, Respiration Rate) of each entering person which is a very important process, especially with the COVID-19 pandemic. The peripheral system monitors any suspicious issue like crowed or walking outside allowed lines.
The Mediating Effect of Creative Self-Efficacy on the Relation between Empowering Leadership and Organizational Innovation

The field of organizational behavior has seen an expanding enthusiasm for understanding elements that advance employee creativity; the development of new and valuable thoughts concerning items, administrations, procedures, and systems in associations. In this study, the main objective is to examine the direct and indirect impact of empowering leadership through the mediating effect of creative self-efficacy on the organizational innovation within police sector in the United Arab Emirates (UAE). The questionnaire was utilized in this study to collect data from the population of police sector in the UAE by using probability random sampling. Structural Equation Modeling-Variance Based (SEM-VB) was utilized to examine the research model in this research, by using the Smart PLS 3.0 software. The result from the analysis shed lights on the impact of empowering leadership on organizational innovation. Moreover, the impact of creative self-efficacy on the organizational innovation. Empowering leadership had a positive direct effect on the OI within the police sector in the UAE. Moreover, creative self-efficacy mediates the relation between empowering leadership and the innovation of organization. The results of the current study have the potential to give further insights into the innovation of organizations strategies.
Quantum Tree-Based Planning

Reinforcement Learning is at the core of a recent revolution in the Artificial Intelligence community. Simultaneously, we are witnessing the emergence of a new field: Quantum Machine Learning. In this work, we reach for the interplay between Quantum Computing and Reinforcement Learning. Learning by interaction is possible in the quantum setting using the concept of oraculization of environments. The paper extends previous oracular instances to address more general stochastic environments. In this setting, we developed a novel quantum algorithm for near-optimal decision-making based on the Reinforcement Learning paradigm known as Sparse Sampling. The proposed algorithm exhibits a quadratic speedup compared with its classical counterpart. To the best of the authors’ knowledge, this is the first quantum planning algorithm exhibiting a time complexity independent of the number of states of the environment, which makes it suitable for large state space environments, where planning is otherwise intractable.
Factors Affecting the Intellectual Dynamics of the Individual

In this article, the factors that provide the dynamics of intelligence in the process of personal development, the transfer of intellectual activity methods to new conditions, students have proven that the components of general intelligence have a specific dynamics in educational stages and areas of study. Factors influencing the dynamics of general intelligence and correlations in the process of student professional formation are analyzed. The general intellectual potential of students studying at different stages of education is identified. It has been found that a student can achieve professional maturity if the interactive methods are chosen correctly and the psychological pedagogical and didactic bases are taken into account. The results obtained on the psychological impact of interactive methods on the mental development of students were analyzed. It has been proven that the dynamics of general intelligence in the development of the student's personality is very important and has different characteristics. The results of the study were processed by statistical methods and scientific conclusions were made.
The Formation and Development of Educational Technoparks

Introduction. In the new digital and networked world a different culture arises, which actualizes the ability of man in mobility, adaptation. Besides knowledge and skills modern schoolchildren need qualities which contribute to successful personal socialization. In this regard, it is important to look for new formats of educational activities, which allow acquiring and developing competencies, which later can contribute to professional self-determination. One of the possible instruments for creating such a space can be an innovative space-educational environment – a techno-park. In order to effectively ensure the formation of social competencies of students it is important to consider the evolution of formation and development of technological parks. Studies on the development of technoparks are mainly focused on the analysis of socio-economic factors, leaving out the features of educational technoparks, which have their own specifics in the children’s environment. This makes it difficult to determine the prospects of their further functioning and features in relation to the problems of modern technological education and socialization of the younger generation. The aim of the article is to characterize the existing models of existence and the specifics of national development of educational technoparks based on the analysis of evolution. Methodology and research methods. The theoretical and methodological basis of the study are the provisions of the theory of social education in the context of socialization (A.V. Mudrik, T.A. Romm, B.V. Kupriyanov and others) using methods of analysis of statistical, theoretical, comparative and pedagogical data. Research results. The stages of technopark development in the world practice are analyzed; the models (American, European, Japanese, mixed, Russian) of their organization are generalized. The features and prospects of development of children’s technoparks are shown. Conclusion. The formation of model structures of technoparks has a cultural and historical character. The peculiarity of educational technopark is that educational, research and project activities of students are enriched with clear practical meaning, which can significantly influence motivation to study school disciplines, to form a socially active attitude towards own self-determination, choice of life path, responsibility and readiness for constructive interaction and socially significant activities.
IDENTIFICATION FACTORS INFLUENCING E-LEARNING SATISFACTION DURING COVID-19 PANDEMIC PERIOD AMONG STUDENTS AT A MALAYSIA PRIVATE INSTITUITION

The rapid occurrences of Corona Virus Disease (Covid-19) have posed various challenges to our society, including the quality of the education system in Malaysia. The current study aims to first measure the impact of demographic variables (gender, age, and education level) and non-demographic variables (perceived usefulness, perceived ease of use, and technological factor) on e-learning satisfaction among students from a higher education institution in Malaysia, and to construct a student satisfaction prediction model subsequently. A structured questionnaire survey was administered to a total of 344 respondents and the statistical analysis of the Chi-Square test and Multiple Regressions was performed. The result of the study reveals that the satisfaction of students on e-learning experience during the pandemic is significantly correlated to gender. The study further shows that three dominant variables, namely perceived usefulness, perceived ease of use, and technological factors are significant factors that influence the satisfaction level of student's learning in the e-learning environment. The findings of the study will be beneficial to policymakers to identify the level of student satisfaction on e-learning education during the COVID-19 pandemic and may provide evidence-based data to improve the learning performance of students.
No evidence for gender and cultural differences in eye movements – a meta-analysis

Analyzing data by ethnicity and/or gender is not common in eye-tracking studies. Though this practice was initiated as a response to discrimination, it preempts the recognition of group differences and thus impedes psychological research. This study seeks to assess the state of the literature and provide insight as to whether ethnicity and gender warrant further investigation.
Neural Machine Translation with Inflected Lexicon

The paper presents experiments in neural machine translation with lexical constraints into a morphologically rich language. In particular and we introduce a method and based on constrained decoding and which handles the inflected forms of lexical entries and does not require any modification to the training data or model architecture. To evaluate its effectiveness and we carry out experiments in two different scenarios: general and domain-specific. We compare our method with baseline translation and i.e. translation without lexical constraints and in terms of translation speed and translation quality. To evaluate how well the method handles the constraints and we propose new evaluation metrics which take into account the presence and placement and duplication and inflectional correctness of lexical terms in the output sentence.
ViBERT: Visual Behavior Regression Testing

Regression testing is a type of software testing that aims at identifying faults caused by code changes.Regression testing is important especially during software evolution and maintenance.As developers integrate programs or make updates to a software system, they need to make sure the changes do not adversely affect other parts of the system.Using dynamic analysis, behavioral regression testing (BERT) is one of the techniques proposed to solve the problem by re-executing test cases that target the affected area.It compares the behavior of a program before and after the changes upon certain test cases.This paper proposes Visual BEhavioral Regression Testing (ViBERT), a visualization approach to comparing the behavioral differences between the new and old versions of a program in regression testing.We build a prototype called SoftLink, a visual environment that shows correlation/difference between two versions of a program behavior.SoftLink displays call graphs of two executions on angled parallel planes in a 3D space, and constructs correlations between them.It provides developers with an intuitive interpretation of the testing results.A case study is presented.
Leveraging Compiler Optimization for Code Clone Detection

Finding similar code in software systems can guide several software engineering tasks such as code maintenance, program understanding, and code reuse.Similar code detection has been actively studied in the past.In the paper, we propose a novel approach that leverages compiler optimizations to transform semantically similar code and detect similar programs.The key observation of our work is that the compiler optimizations can be used to smooth out source code level idiosyncrasies introduced by the developers, thus making the optimized programs, for the same task, similar in structure.The similarity in structure can then be used to classify the programs.We conducted experiments on the Google CodeJam dataset to demonstrate the effectiveness of our approach.The experimental results show that our technique can achieve up to 85% accuracy on the program classification task, which is an improvement of more than 25% over the source code level classification.
Back to Our Future: Text Analytics Insights

Abstract–Each year, the Journal of the American Statistical Association (ASA) publishes the presidential address from the Joint Statistical Meetings (JSM). Here, we present the 2020 address verbatim save for the addition of references and a few minor editorial corrections.
Light Scalar and Lepton Anomalous Magnetic Moments

Recent precise determination of the electron anomalous magnetic moment (AMM) adds to the longstanding tension of the muon AMM and together strongly point towards physics beyond the Standard Model (BSM).Here we present a solution to both anomalies via a light scalar that emerges from a second Higgs doublet and resides in the O(10)-MeV to O(1)-GeV mass range.A scalar of this type is subject to a number of various experimental constraints, however, as we show, it can remain sufficiently light by evading all experimental bounds and has the great potential to be discovered in the near-future low-energy experiments.In addition to the light scalar, our theory predicts the existence of a nearly degenerate charged scalar and a pseudoscalar, which have masses of the order of the electroweak scale.This scenario can be tested at the LHC by looking at the novel process pp → H ± H ± jj → l ± l ± jj + E / T via same-sign pair production of charged Higgs bosons.
Penerapan Data Mining Korelasi Penjualan Spare Part Mobil Menggunakan Metode Algoritma Apriori (Studi Kasus: CV. Citra Kencana Mobil)

&#x0D; &#x0D; &#x0D; &#x0D; By utilizing customer data that has been stored in the database, the management can find out how the current sales system is less efficient, therefore a system is needed to process information data more quickly and accurately in increasing sales of car spare parts using the Data Mining application. The Apriori Algorithm method that works by searching for and finding associated patterns among the products being marketed, so that later it can help companies improve the associated items. And with the sales transaction data, the company can know better how they should increase the spare part stock in the company. From the results of testing the sale of car spare parts with 589 data, it was found that 81 rules were formed and the highest Best Rule was obtained and a minimum support value of 1% and a confidence value of 11% If the type of car is Avanza / Xenia and the brand is Toyota, the spare parts used are filters. Air. With supporting spare parts in the database of 1% and certainty of spare parts of 11.&#x0D; &#x0D; &#x0D; &#x0D;
AAA4LLL - Acquisition, Annotation, Augmentation for Lively Language Learning

In this paper we describe a method for enhancing the process of studying Japanese by a user-centered approach. This approach includes three parts: an innovative way of acquiring learning material from topic seeds, multifaceted sentence analysis to present sentence annotations, and the browser-integrated augmentation of perusing Wikipedia pages of special interest for the learner. This may result in new topic seeds to yield additional learning content, thus repeating the cycle.
Tolerance to foreign students in Russian Universities (a case study of Perm State University)

The competitiveness of a university is one of the requirements of the modern education market. In order to achieve it, Russian universities increase their educational and research potential. They invite foreign students and staff. This process requires methodological and cultural changes at the university. The creation of the environment fostering tolerant interaction between foreign and Russian students, the development of tolerance are among the mandatory changes. Tolerance reduces conflicts in society as a whole and diminishes intolerance towards other cultures, nations, races, and genders. This requires a lot of control during implementation and constant monitoring of the situation. Tolerance is manifested in the process of communication and is determined through the category «attitude» and its three components — emotional, behavioral, cognitive. The purpose of this article is to characterize the current state of tolerant relations between Russian and foreign students at Perm State University. The empirical base of the study is a survey of Russian students at Perm State University about their attitude to foreign students. The authors evaluate: 1) the current state of the three components of tolerant relationships (emotional, behavioral, cognitive); 2) students’ understanding of tolerant relations; 3) attitude to the foreigners’ adaptation to educational and extracurricular activities. Perm University has a favorable environment for the development of intercultural interaction among students. Respondents adequately understand tolerance and its features and are ready to respect the cultural, national characteristics of foreign students. In practical terms, the study can clarify ideas about successful ways of developing communication among representatives of different cultures and about ways of developing tolerant relations among students from different countries.