Reviewerly/exHarmony huggingface dataset:
Estimation of stature using cephalic and facial measurements

Stature (living height) is one of the primary characteristics for the identification of a person along with other biological profiles - age, sex, and race. The need for Identification of a person can occur in situations like a mass disaster, unidentified bodies, and many civil cases and criminal cases. As any part of the human body can be found as evidence, there is a need for a study to investigate the significant correlation between stature and cephalon-facial dimensions in the human body. The study was done on 400 medical students of south Indian origin. The study showed a significant correlation between cephalic measurements and stature.
Predicting Effective Arguments with A Natural Language Processing Model

Text is the main carrier of information on the Internet. More and more researchers are committed to mining textual information for great value. In terms of education, text mining can greatly help teachers and students to improve their writing. Computers can assist teachers in grading and classifying students' argumentative essays into three kinds: effective, adequate, ineffective. In this paper, we use data consisting of students' discourse and annotation provided by Kaggle platform. We utilize DeBERTa for Predicting Effective Arguments. We represent related work in section II, and introduce our methodology and experiment in section III and IV. To evaluate our experiment's performance, we do compared competitions. The predicting can be converted into a classification problem. We use the cross entropy as the metrics. Our Deberta-large owns the lowest metric 0.619 among these models, which is 0.007, 0.114, 0.030 lower than BERT, RoBERTa respectively, which shows our model has the best performance among them.
Impact of Distance Measure on Kriging Interpolation on Natural Images Corrupted by Drop-Out Noise

An impact of distance measurement using the Kriging interpolation technique is implemented on natural images for the removal of drop-out noise. The data drop-out can cause pointed unforeseen disturbances in the image signal. A technique of approximation known as kriging may be used to anticipate values that have not yet been seen based on observations of the value at adjacent places. Kriging assigns weights to each point based on how far it is from the unknown values at the time of calculation. The thoroughgoing testing was on natural images of a standard database. In this study, the application of Kriging interpolation depending on a distance metric between the suggested drop-out noise pictures and non-noisy images resulted in a more significant improvement in the performance of the method. Pixels that are not impacted by the effect always stay unaltered. The amount of noise is often expressed as a percentage of the total number of distorted pixels.
STRUCTURAL CONDITIONS OF POLYMETAL MINERALIZATION LOCALIZATION IN THE CHO DIEN ORE CLUSTER IN THE LO GAM METALLOGENIC ZONE, NORTHERN VIETNAM

Structural research in the Cho Dien ore cluster and its environs has revealed that folds and faults were formed by sublatitudinal stresses. At the Nam Lung deposit, the stratified ore-bearing strata show evidences for upward interlayer migration of ore constituents, which is associated with wide development of interstratal thrusts during the anticline formation. Migrating ore constituents constrained by step faults cutting the anticline hinge zone accumulate to form low-angle ore shoots. Such a mechanism of structural control to mineralization is probably one of the conditions for most commercially important Pb-Zn deposits to be confined to the anticline hinge zone in the Cho Dien ore cluster.
Development of a 3D decontamination robot for decommissioning work and its social implementation through a contest

Technology contests are based on the competition rules of a certain field. Participating in this is a kind of social implementation research. Authors developed a remote-controlled mobile robot to decontaminate the inside of a nuclear reactor building, and participated in the Decommissioning Robot Contest. In this paper, we report on robot research and development through technology-based contests from the perspective of social implementation-oriented research.
Performance Evaluation of Modified Best First Decreasing Algorithms for Dynamic Virtual Machine Placement in Cloud Computing

Cloud computing has become the popular choice in developing countries such as Nigeria where access to high performance computing facilities is inadequate. Individuals, organizations and institutions in need of high performance computing facilities can subscribe to cloud computing facilities on a pay-as-you-go basis. Whenever a customer requests for cloud computing services, there is a problem of allocating virtual machines for such services on available physical machines while minimizing energy consumption and carbon-dioxide emission, as well as maximizing resource utilization. The Modified Best First Decreasing(MBFD) algorithm is a baseline algorithm for evaluating the performance of virtual machine placement algorithms in cloud computing. This research carries out a performance evaluation of the MBFD algorithms in the CloudSim 3.0.3 simulator under three different configurations A, B and C. Configuration A has fewer processor resources than configuration B which has fewer processor resources than configuration C. CloudSim 3.0.3 is installed in Eclipse Integrated Development Environment on a Laptop with two Intel Celeron Processors at 1.60 GHz each and 4 GB memory. Configurations B and C have lower energy consumption and faster computation time compared to configuration A. The lowest average energy consumption is 101.97 KWh and standard deviation of 8.63 KWh when Local Regression Robust with minimum utilization heuristic algorithm was executed under configuration B. The fastest average computation time is 0.21898 s for static threshold with minimum utilization heuristic algorithm under configuration B. This work recommends evaluating the adaptive heuristics on real-life cloud computing testbed to further validate the results.
Investigating User Control to Mitigate Bias When Searching African Historical Data

Historians have argued that common information retrieval algorithms may bias results presented to users searching through pre-colonial historical collections. This study therefore investigates how users experience and control bias in the context of commonly used information retrieval pre-processing algorithms for both the textual and image data that are available in typical historical archives. Users were presented with the results generated by multiple algorithmic variations, and the ability to select algorithms. The results show that users have justifiable preferences for multimodal result modes to improve user experience, and, that users believe they can control bias using algorithmic variation.
A Grid-Aware Consensus Protocol for Energy Trading

Fast-paced technological advances in power devices and system operations along with policy mandates stemming from climate change, sustainability and environmental concerns are driving remarkable transformations in the modern power grid. Distributed energy resources (DERs) such as renewables and energy storage systems play an important role in decarbonizing the electric grid. In order to incentivize the grid-wide integration of DERs by independent energy producers, a trustworthy decentralized energy trading platform is necessary. As such, Blockchain has been widely investigated in the literature for this purpose. Inefficiencies and computational overheads are inevitable when adopting existing Blockchain protocols that were originally designed for the crypto-currency application to the energy domain. In this paper, we propose a novel consensus protocol that allows energy traders to verify the validity of energy transactions in a decentralized manner by leveraging on the inherent electrical interdependencies naturally present in the power grid. We demonstrate via theoretical and simulation studies conducted on IEEE 118-bus system that in addition to validating energy transactions, our proposed protocol is effective against dishonest transactors.
Psychological portrait of a successful leader: research methodology

Annotation. In modern conditions, society makes various demands on managers, which are aimed not only at professional skills, but also at the psychological characteristics of the leader. The effectiveness of all employees and a particular boss depends on the extent to which the leader is able to interact with subordinates, to understand the psychological climate in the team. The purpose of this work was to select psychodiagnostic techniques that adequately address the research request to study the psychological portrait of a successful leader. Using the sources of the scientometric databases Web of Science, Scopus, Index Copernicus (2011-2019), the selection of psychological tools was carried out, which is due to the theoretical ambiguity and multidimensionality of the problem of the formation of psychologically significant qualities of leaders. The issues of ways to identify, interpret and verify the qualities of successful leaders are covered. Attention is paid to the problem of application of tests in the improvement of methods of work with staff, evaluation and selection of management personnel, the skillful application of which will help to improve the process of regulation of social and labor relations and increase the efficiency of the work process. The results of a comprehensive study help to determine the selection of developmental training, training programs, business and management games to improve the managerial competence of the head. It is possible to introduce a system of socio-psychological forecasting of managers' success.
Pemanfaatan Learning Management System dengan Moodle dalam Menunjang Pembelajaran Daring Interaktif

Interactive online learning requires information and communication technology assisted to carry out effective and efficient learning. One of the online learning strategies that utilizes information and communication technology is using a management system (LMS) by moodle. The purpose of this study was to analyze the use of LMS with moodle in supporting interactive online learning activities at SMP Methodist 8 Medan. A qualitative study was conducted with a descriptive research approach and the sampling technique was purposive sampling. Data collection techniques were carried out by conducting observations, interviews and documentation. Meanwhile, data analysis was carried out through several steps, namely: data collection, data reduction, data presentation, and data verification. The results of the study showed that: 1) the use of moodle is very effective and efficient in delivering learning materials because learning materials that have been uploaded into the system can be accessed easily at any time and any where; 2) the use of various features in moodle support interactive online learning; 3) the use of the page feature in integrating moodle into other systems/websites such as the use of student worksheet and interactive quiz respectively into live worksheet and quiziz increase student enthusiasm and learning activities.&#x0D;
UNDERSTANDING VIRTUAL REALITY GAME PLAYERS' SATISFACTION, LOYALTY, AND EXPERIENCE VALUE: A CASE STUDY OF THE BEATSABER

In recent years, the emergence of VR technology provides game players immersive experience in a 3D virtual world. This study investigated virtual reality gamers' experience value, customer satisfaction, and customer loyalty in China with online
Pengembangan Bahan Ajar Teks Deskripsi dengan Memanfaatkan Media Gambar Motif Kain Sumba Barat Daya Siswa Kelas VII SMPN I Kodi Tahun Ajaran 2020

&#x0D; Teaching materials are a set of learning materials arranged systematically, showing a complete figure of the competencies that will be mastered by students in learning activities. The formulation of the problems in this study include: 1) how to develop teaching materials for descriptive text using Sumba cloth motif image media that has a language eligibility test ?, 2) How to develop teaching materials for descriptive text using Sumba cloth motif image media that has a material feasibility test ?, 3) how is the development of descriptive text teaching materials using the Sumba cloth motif image media that has a design feasibility test? The research objectives correlate with the formulation of the problem. The type of research used in this research is research and development (R &amp; D) with the 4D development model consisting of four stages, namely: 1) Define, 2) Design, 3) Development and 4) Disseminate, research is carried out with the aim of producing a product in the form of descriptive textbooks, students of SMPN I Kodi were the samples. The instruments in this study used questionnaires, interviews, and documentation. The book is said to be feasible from the results of the validation by material, language and design experts, as for the evaluation of the validator, namely the material expert validator obtains a total score of 10.08 and an average value of 3, the total score of the linguist validator gets a total score of 9.5 with average value 3, design expert validator with a total score of 12.5 a mean value of 4 and obtaining the results of student trials with a total score of 23.49 a mean value of 4, so that the teaching material is declared feasible to be implemented in Indonesian language learning using image media Southwest Sumba cloth motif suitable for grade VII junior high school students.&#x0D;
The role of e-learning resources in modeling physical processes

Now, as a result of the development of Science, Technology and innovation technologies, interest in increasing the effectiveness of education through the use of interactive methods (innovative pedagogical and information technologies, attention is increasing day by day. The article focuses on the aspects of the use of e-learning resources in modeling physical processes.
Trial of the divided production PBL for robot hands and SCARA robots

We conduct Project Based Learning training for third-year students in the robotics course of the Department of Mechanical Engineering. In the past two years of training, students have been able to make the robot hand grip an object by manually manipulating the robot arm. However, the problem was that there were no students who could automatically control the robot arm. Therefore, this year, we focused on this issue and conducted practical training by sharing the training between the students in charge of the robot arm and the students in charge of the hand, and they were able to realize a series of movements through mutual communication.
Cloud Security by LZW Technique and Fast Searching by Genetic Data Clustering

Digital text content is unstructured in nature as each document writer as its own flow of delivering thoughts. This nature of data leads to searching and retrieval issue for the cloud service providers. Many of researcher get motivated to proposed different approaches for fast retrieval. This paper has developed a model that can provide a secured data storage technique with relevant fetching. Input text data is preprocessing to transform into appropriate format and pass through the LZW technique to encode input data for security. This transformed data was analyzed to get the appropriate cluster. Clustering was done by the firefly genetic algorithm where each document act as firefly. As per patterns similarity from the transformed data, documents were clustered by estimating a fitness value. Experimental work was done on dataset obtained from international journal. It was obtained that the proposed LZWFDS (LZW Firefly Document Searching) improved the relevancy and reduce computational time as compared to other comparing algorithms.
CAI: Complex Ontology Alignments Using Lexical Indexation

Ontology matching is the process of automatically determining the semantic equivalences between the concepts of two ontologies. However, simple ontology alignments are a domain largely studied. It link one entity of source ontology to one entity of target ontology. In this paper, we present a complex ontology alignment system CAI. In contrast to most existing tools, CAI is a matching system that can deal with complex and simple ontology alignments.
Similarity Measures in Decision Making

In this paper, the authors present two similarity measure-based approaches. First, the problem is studied when multiple experts’ opinions are available. The purpose of using the similarity measure-based approach is to find the similarities between the different opinions. In this process, the maximum value of the fuzzy sets represents the degree of confidence of each expert. Furthermore, the authors propose a similarity measure-based process to monitor the current results of a real time system. In this method, the desired output is specified and then the current system output can be compared to the desired ones, so as to be able to recognize the abnormal values immediately.
Mixed-Initiative PCGML

In the previous chapters we introduced different machine learning paradigms and discussed how they could be leveraged for PCGML. What each of those previous chapters had in common was that they treated training and generation as static processes. That is, model training and content generation were processes that someone would start and then wait for the outcome. In this chapter we will introduce a different viewpoint that positions user input and interaction more prominently during training and generation. This viewpoint is helpful when thinking about designer and user-facing tools that leverage PCGML techniques. Specifically, this chapter introduces Mixed-initiative PCGML (sometimes co-creative instead of mixed-initiative).
A Comparative Study on the Impact of the Capabilities of Manufacturing and Service Firms on Export Performance: Focusing on the Interaction Effect of R&amp;D

This paper empirically examined the impact of firm capabilities and the interaction effect of R&D on the export performance of service firms in comparison with manufacturing firms. To this end, a total of 1,968 Korean firms were analyzed: 243 from service and 1,725 from manufacturing, and two-stage analysis was performed using multiple regression and hierarchical regression analysis. This research confirmed that network and customer capabilities played critical roles in the internationalization of service firms and R&D positively interacted with entrepreneurship and customer capabilities for export performance. These findings suggest valuable policy considerations for government trade policy and academic motivation for further research on the capabilities and R&D of service firms.
Analysis of Methods of Error Correction of Measuring Devices

The article is devoted to the study of methods for correcting errors of measuring devices. Features of the application of correction of multiplicative and additive component errors are considered. The article investigated the methods of correcting the errors of the measuring instruments as part of the measuring systems. This made it possible to find ways to improve the accuracy of measurements. Sample signal methods and test methods based on the functional transformation of measuring devices during a cycle of specially organized measurements were studied. An analysis of various error correction methods caused by static and dynamic factors has been carried out. Literary sources were studied, which consider ways to eliminate the influence of instrumental error. Thus, to eliminate the instrumental error, separate correction coefficients representing the relative values of the probabilities of erroneous decisions were considered. During the study, inverse mathematical models of measuring channels were considered, as which Lagrange interpolation polynomials are used. A method of eliminating the influence of the parameters of the additive and multiplicative component of the measurement on the accuracy of the test method is proposed by creating additional inverse converters and a system of equations describing the transformation of the input values of the measuring converter in each measuring cycle, which can be used to obtain the adjusted value of the measured value. The effectiveness of this improvement for use as part of the information and measurement system is substantiated. It is shown that the most important directions for improving the efficiency of such a system are the provision of the necessary experimental base, as well as the accuracy of setting correction algorithms.
Study on soil conductive path based on micro-element statistical method

Soil conductivity will directly determine the stability of grounding system, and the cost of grounding system will vary up to 100 times due to the difference of soil resistivity in different areas under the same grounding resistance. Soil, as a porous medium, has a large number of pores between solid mineral particles, and ions can migrate through the channels formed by pore water, thus forming electric currents. Existing studies have found that the resistivity of the soil will change constantly with the change of water content, and there is a mutation phenomenon, but considering the soil water conductivity is highest, so can only guess at mutation reason is caused by the connectivity of water distribution. In this paper, MATLAB software was used to write a program to establish a soil fractal model, and then ANSYS simulation software was used to solve the problem, so as to analyze the conductivity of the soil model, and statistical analysis of the apparent conductivity of water micro-element in the soil and study its distribution in the soil model. In addition, the connectivity of soil resistivity at different times before and after the mutation was further studied and the number of cells contained in the conduction path of soil was counted. By controlling the variation of soil water content parameter, the distribution of cell number in soil conduction path in each column of soil model was studied. It was found that with the increase of soil water content, the distribution range of cell number in each column increased, and the fluctuation of numerical value decreased significantly. Therefore, the mean value and variance were introduced to analyze the variation rule of data. On the basis of this study, the influence of porosity on soil conductive path can be studied by changing the size of porosity.
IBE with Incompressible Master Secret and Small Identity Secrets

Side-stepping the protection provided by cryptography, exfiltration attacks are becoming a considerable real-world threat. With the goal of mitigating the exfiltration of cryptographic keys, big-key cryptosystems have been developed over the past few years. These systems come with very large secret keys which are thus hard to exfiltrate. Typically, in such systems, the setup time must be large as it generates the large secret key. However, subsequently, the encryption and decryption operations, that must be performed repeatedly, are required to be efficient. Specifically, the encryption uses only a small public key and the decryption only accesses small ciphertext-dependent parts of the full secret key. Nonetheless, these schemes require decryption to have access to the entire secret key. Thus, using such big-key cryptosystems necessitate that users carry around large secret-keys on their devices, which can be a hassle and in some cases might also render exfiltration easy. With the goal of removing this problem, in this work, we initiate the study of big-key identity-based encryption (bk-IBE). In such a system, the master secret-key is allowed to be large but we require that the identity-based secret keys are short. This allows users to use the identity-based short keys as the ephemeral secret keys that can be more easily carried around and allow for decrypting ciphertexts matching a particular identity, e.g. messages that were encrypted on a particular date. In particular: