Reviewerly/exHarmony huggingface dataset:
MetaWood: manipulation of the elastic properties of wood plates by periodic hole patterns

Recent research has numerically shown the possibility of manipulating the elastic properties of wood plates through periodic hole patterns. In this work we focus on experimentally testing these results, changing the stiffness and density of Spruce Engelmann plates, a traditional wood for guitar soundboards. These results pave the way for applications in luthiery and beyond.
The Communicative Approach Implementation to Improve Speaking Ability Students of Class VIII-2 SMP Negeri 7 Ambon Indonesia

This study aims to improve the speaking ability of students in class VIII-2 at SMP Negeri 7 Ambon through the communicative approach. The research data is in the form of speaking ability test results in each cycle. The research subjects were students of class VIII-2 SMP Negeri 7 Ambon. The final score of each student is obtained from the acquisition score divided by the total score then multiplied by the ideal score (100). The final value is then converted according to the specified criteria. The results showed that there was an increase in students' speaking ability at class VIII-2 SMP Negeri 7 Ambon through communicative approach. This can be seen from the number of students who achieved the minimum completeness criteria (in Indonesia = KKM) in the first cycle, namely 12 students (54,54%) to 18 students (81,81%) in the second cycle.
An Analysis of Articles Published in Research In Ancient Chinese Language(古汉语研究) and Studies of The Chinese Language(中国语文) from 2012 to 2022

This article reviews recent research trends in Historical Grammar of Chinese based on 212 articles published in Research In Ancient Chinese Language(古汉语研究) and Studies of The Chinese Language(中国语文) from 2012 to 2022. In this field, ‘words’ are being studied more than ‘constructions’, and ‘adverbs’ are being studied the most. There are the most studies on the period of ‘Archaic Chinese’ among three periods of Ancient Chinese, that is Archaic, Middle Ancient and Modern Ancient Chinese. Diachronic research is more focused rather than synchronic research. Research methods of Historical Grammar of Chinese can be largely classified into two types: simple descriptions and theoretical interpretations, and we find more studies of the former than the latter. Theoretical interpretations studies can be subdivided into five types: (1) studies on mechanisms and motivations of grammaticalization, (2) linguistic typology based studies, (3) construction grammar theory based studies, (4) cognitive grammar theory based studies, (5) generative grammar theory based studies. Among these five types, (1) accounts for the highest proportion and (4), (5) accounts for a relatively low proportion. The article concludes by suggesting that theoretical interpretations studies should be conducted more actively, and the subjects should be more associated with Modern Chinese. There also should be a unified understanding of mechanisms and motivations of grammaticalization and the key elements should be found among these.
Analysis of Difference between the Learning Flow and Learners" Interest based on the Types of Teaching Style: A Study on the Application of Blended Learning in University Physical Education Class Changed to "COVID-19"

The purpose of this study is that we analysis of difference between the learning flow and Learners’ interest based on the types of teaching style by applying blended learning to university physical education classes. For data collection, we conducted the questionnaires on the 110 participants who are taking the researcher’s 2 classes. A total of 107 (online 54, blended 53) data were used for the final analysis. For the analysis frequency, descriptive, reliability, correlation analysis and 2-way mixed ANOVA. The results are follows: First, as a result that analyzed the difference between pre test and post test of the learning flow showed blended learning is more statistically significant than online learning. Second, as a result that analyzed the difference between pre test and post test of the interest of the learners showed blended learning is more statistically significant than online learning. Based on these results, practical and improved blended learning should be applied in university physical education classes to prepare for the pandemic.
Direct Adaptive Fuzzy Control with a Self-regulated Structure

AbstractFuzzy systems with fixed structures were used in most of the adaptive fuzzy control methods proposed by different papers. Thus, a designer should determine the number of membership functions through trial and error. In many cases, the designated structure is larger or smaller than the proper structure.
The Future of the Body in Tomorrow’s Workplace

Even in the most hectic or time-conscious workplace, employees gather in person to chat. And even in the most networked workplace, employees still make time for face-to-face collaboration. This isn’t surprising if we consider that the ability and desire to engage in face-to-face communication (using eye gaze to manage turn-taking, head nods to indicate listening, and smiles to indicate attention) starts soon after birth – well before infants even learn to talk. We might say that we are built to communicate face-to-face! But what role will embodied interaction play in the future workplace, when we will be interacting with autonomous robots, engaging with other people through presence robots, and working in a virtual world where we and our colleagues are represented by avatars? In this talk I will describe some of the ways that embodied interaction is likely to change in the future, and some of the ways that we need to take those future scenarios into account as we design and implement multimodal interfaces.
Towards Integration of Embodiment Features for Prosodic Prominence Prediction from Text

Prosodic prominence prediction is an important task in the area of speech processing and especially forms an essential part of modern text-to-speech systems. Previous work has broadly focused on acoustic and linguistic features (such as syntactic and semantic features) for predicting prosodic prominence. However, human models of prosody are known to be highly multimodal and grounded on denotations of physical entities and embodied experience. In this paper we present a first study where we integrate multimodal sensorimotor associations by exploiting the Lancaster Sensorimotor Norms towards prosodic prominence prediction. Our results highlight the importance of sensorimotor knowledge especially for models in low-data regimens where we show that it improves the performance by a significant margin.
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A photovoltaic array's output characteristic is non-linear, and its behavior varies with solar radiation and module temperature fluctuations. Therefore, a maximum power point tracking strategy is needed to improve the energy delivered by the photovoltaic systems. Due to multiple peak occurrences on the P-V curve, conventional techniques are restricted to the mismatch case. Consequently, this inquiry focused on a comparative assessment of four prevalent meta-heuristic methods for the stochastic search paradigm, including particle swarm optimization (PSO), gray wolf optimizer (GWO), artificial bee colony optimization (ABC), and cuckoo optimization (Cuckoo). MATLAB is utilized to develop the photovoltaic model, the Buck-boost converter, and the GMPPT algorithm implementation. The simulation outcomes demonstrate that the advanced GMPPT approach can handle the maximum power holding under a quick external environmental change and effectively manage the partial shading occurrences. Finally, this analysis suggests the potential use of PSO and GWO algorithms owing to the faster joining of the PV array's maximum power point compared to the Cuckoo and ABC strategies, considering well-dimensioned initial duty cycle values.
RIChEx: A Robust Inter-Frame Change Exposure for Segmenting Moving Objects

Moving object segmentation in video plays an important role in many computer vision applications such as outdoor video surveillance, robotics, self-driving cars, etc. Existing work comprises complicated training procedures considering more number of history frames, fine-tuning on test sequences, and pre-trained models adopted from other applications. Therefore, this paper proposes an end-to-end robust inter-frame change exposure (RIChEx) framework for segmenting moving objects using three consecutive frames. The RIChEx consists inter-frame change gradient (IFCG) aggregation approach responsible for extracting the relevant foreground features to capture substantial changes and spatio-temporal structural dependencies between the consecutive frames. This module consists of multi-scale addition (MSA) blocks for extracting multi-scale features in early layers. Furthermore, to enhance the temporal learning capability of the module, previous recurrent responses and optical flow information are integrated to estimate probable foreground availability and salient object motions. We have evaluated the proposed framework on the benchmark DAVIS-16 dataset to validate the model’s performance.
Learning Graph Features for Colored Mesh Visual Quality Assessment

This paper proposes a novel method for colored mesh visual quality assessment based on graph features learning. We first extract color features from each distorted colored mesh data. Then, we map them into a weighted graph with weights derived from the color features. One then computes various local topological properties of the network nodes (Degree, Strength, Clustering coefficient). Estimates of their statistical properties (Mean, Variance, Skewness, Kurtosis, Entropy) form a signature vector are used by a machine learning algorithm. The random forest regression is used to predict the quality score. Experiments are conducted on the publicly available CMDM database specifically constructed for the colored mesh quality assessment task. The proposed method is compared to the most influential and effective full and no-reference methods (CMDM and NR-NSS). The excellent correlations with subjective decisions prove its good performance.
PET/CT Co-Segmentation Based on Hybrid Active Contour Model

This paper proposes a hybrid active contour model for tumor co-segmentation from PET/CT images. We incorporate the foreground of the CT image and the background of the PET image into a co-segmentation framework to establish a new energy functional. Different from existing methods, the proposed model incorporates an edge stopping function based on PET images. The proposed method has been evaluated on a data set of 50 pairs of PET/CT images of non-small cell lung cancer patients and compared with other single-mode segmentation methods and co-segmentation methods. Experimental results show that our model is more robust than other strategies in complex backgrounds.
The Ability of Eleventh Grade Students at SMA Negeri 3 Ambon in Write Poetry Using Natural Media

Writing is one of four language skills. Of the four language skills, writing ranks last. That is, the ability to write can be achieved if the other three skills (listening, speaking, and reading) have been acquired first. The ability to write poetry is one of the competencies that must be mastered by junior high school students. The fact proves that not all junior high school students are able to write well, especially writing poetry. Therefore, it is necessary to conduct research to identify and overcome these problems. The purpose of this study was to describe the ability to write poetry through natural media of class XI students of SMA Negeri 3 Ambon. The method used is descriptive quantitative method using statistical formulas and calculations. The main data of this study were collected by test technique. The test was conducted on 30 students. The results showed that the ability of eleventh grade students at SMA Negeri 3 Ambon in write poetry using natural media was good.
POS Tagging for the Primitive Languages of the World and Introducing a New Set of Universal POS Tagging for Sanskrit

The digital structuring of a language depends on how their parts of speech are classified to make the language the most compatible for the user. The parts of speech (POS) of a language is defined as the word classifiers which classify a word more precisely for using it in the sentence properly for expressing the emotions or feelings of human beings through natural languages. The natural language processing in the research arena already classifies the exhaustive forms of POS of many languages in the world. Among all such languages, the POS of SANSKRIT language is also introduced by many eminent scholars. Here, an attempt is made to give the new set of POS of the SANSKRIT language with their proper definitions and explanations with examples and they are termed as Universal POS (UPOS). The set so defined that universally everybody can understand, and the further use of these tags can be made available to the researchers of the world. The new set is highly expected to be the most exhaustive form.
About the Fujisaki-Okamoto Transformation in the Code-Based Algorithms of the NIST Post-quantum Call

Post-quantum encryption schemes use variants of the Fujisaki-Okamoto transformation in order to construct a highly secure key encapsulation mechanism from a weakly secure public key encryption scheme. In the third round of the NIST post-quantum cryptography standardization call, all the candidates for the key encapsulation mechanism category use some of these transformations. This work studies how the mentioned transformations are applied in the code-based candidates of the NIST third round. These are Classic McEliece (finalist), BIKE (alternative) and HQC (alternative). Studying the differences between the transformations gives a better understanding of these candidates.
Features of awareness-raising work at the higher educational institution at the present stage of geopolitical development

In the conditions of the special operation, sanctions oppression, and information war, which has been waged against Russia by Western countries constantly since 1945, but with particular intensity since 2014 and especially in the current situation, the goals of awareness-raising work at the higher educational institution are being utterly concretized. This is not only the development of sought-after cross-professional competencies like innovation, creativity, communication, and solidarity, but also, and perhaps, most importantly, the formation of a holistic worldview of young people, i.e. a worldview based on the values of patriotism, morality, legal awareness, healthy lifestyle, family values, and on reliable knowledge of the processes that occur in society, their causes and understanding. This situation required a rethinking of many components of the very process of awareness-raising in universities and higher educational institutions of the country and the management of this process. On the recommendation of the Ministry of Science and Higher Education of the Russian Federation, lectures, aimed at clarifying the realities in a changing world and the threats in the field of information security, were held in all higher educational institutions of the country in March-April 2022.
Data Classification Using Mesh Generation and Hough Transform

Linear regression is a well-known method used in statistic to determine correlation between two or more variables, in machine learning for data classification and for prediction. This paper deals with data classification using a composition of two techniques of classification such as mesh generation, followed by the Hough transform method, in order to define a linear regression on the dataset. The purpose is to use analytical straight lines as a regression technique. The proposed method is a technique of data reduction through a mesh generation, which creates a virtual grid where each continuous point is localized in a cell corresponding to a pixel in the virtual grid. The standard Hough transform method establishes a relation between an image space and a parameter space through the definition of a sine function. The values of variables are represented by the coordinates of continuous points in the image space. The standard Hough transform is applied to each cell. The coordinates parameters with the high number of votes superior to a threshold that appears in the parameter space or the accumulator correspond to the parameters of analytical straight lines. Straight line recognition achieves linear regression and establishes correlation between the initial variables. Our analysis presents difference between classical linear regression and the proposed alternative which gives more visibility between data relation and accept a level of error in the dataset.
Situational and environmental approach in the design of personal-developing educational systems: the study continues

The article reveals the essence and foundations of the situational-environmental approach in pedagogy (N.V. Khodyakova) as a new strategy for designing personality-developing educational systems. The main methodological regulatives of this approach are defined: its basic concepts (personality, personality development, educational environment, personality development situation, and others); structural models of the educational environment and the situation of personality development in the educational environment; psychological and pedagogical patterns of the process of personality development in the educational environment; situational mechanisms of personal growth and the corresponding typology of personality-developing situations in education; the procedure of situational-environmental design of the educational process, the indicative basis of the relevant activity of the teacher and its specific functions in the implementation of the situational-environmental approach in education. The theoretical conclusions are illustrated by examples of designing various educational systems based on the situational-environmental approach. Promising directions of continuing research are shown, including the development of the concept of pedagogical support for personal self-development in continuing education (T.S. Kupavtsev), the study and modeling of personality-oriented environments in the context of designing the individual trajectory of personal development of the subject of education (D.V.Litvin), the application of the methodology of situational-environmental approach to the scientific and pedagogical justification of solving various learning tasks and education (E.M. Shevchenko, E.N. Gordeeva, L.A. Mangasarova).
Information and communication technology in emergency organizations: Applications, opportunities, and challenges

The increasing complexity of the globally connected world in the twenty-first century leads to an expansion of the area of operations of so-called emergency organizations* with regard to their aims, tasks, and exposure to risks by fulfilling their intended mission. On the other side, the process of globalization is accompanied by continuous further development of existing information technologies (ICTs) as well as exploration of new forms of ICT. These technologies provide the chance for emergency organizations to gain the ability to act more flexible and effective within their prescribed tasks. As aspects of digitization could have a great impact on many parts of the processes and domains in emergency organizations, a broad view on the topic area is needed. To that end, this article at hand deals with the development of a systematic approach to structure ICT technologies and further approaches and corresponding elements of emergency organizations to find connecting links between both areas. For this purpose, a literature review was conducted. It takes up exemplary sources from literature and describes them along a standardized emergency process. The results of this review led to the development of an ad hoc classification system, which structures and clusters relevant information technologies for emergency organizations. It builds upon the standardized emergency process and could provide a foundation for emergency organizations as well as academic scholars for further information gathering and research. Furthermore, exemplary challenges and opportunities-based on the findings of the review-are provided.
Work-in-Progress: Accuracy-Area Efficient Online Fault Detection for Robust Neural Network Software-Embedded Microcontrollers

Detecting transient faults in safety-critical neural network (NN) applications operated on embedded systems has become a concern, but it is challenging to achieve high accuracy because of the open context problem and resource constraints. This study proposes an accuracy-area efficient, data-analysis-based online soft errors (SEs) and control flow errors (CFEs) detection, applicable to any NN application with low overhead. We insert code for runtime monitoring data assertion, and the data are distributed to shallow or deep detection models selectively. The shallow detection model detects CFEs by verifying runtime signatures with values obtained from simulations, and detects SEs of data having constant values according to program input. SEs of other data are verified by a deep detection model using a sliding window one-class support vector machine. Fault injection experiments on an image classification NN showed that our detector has significant detection accuracy in fault conditions.
PENERAPAN METODE CERTAINTY FACTOR PADA SISTEM PAKAR DIAGNOSA GANGGUAN MENTAL PADA ANAK BERBASIS WEB

CCM (Care for Children's Mental) is a diagnostic expert system with a certainty factor method that can be done in various places and chooses some of the symptoms that occur in children so that the system can diagnose the child's mental disorders that are experienced.It is hoped that this expert system can help parents in early diagnosis of mental disorders that their children experience independently with the help of an expert based on the symptoms felt so that parents are sensitive to the child and do not take it for granted.Another benefit of this expert system is that it makes it easy to access anywhere, and it makes it easier for parents to diagnose children's disorders easily.Certainty Factor is a method of defining a measure of expert facts or rules to describe a person's beliefs about a problem.To help and make it easier for parents in the media to diagnose mental disorders in children, the certainty factor method can be used as a solution.The application of the Certainty Factor method to the expert system for diagnosing mental disorders in children with the web-based certainy factor method is built using the PHP programming language and MySQL databases and uses the CodeIgniter (CI) framework.
The Multi-User Security of Triple Encryption, Revisited

We study the security of triple encryption in the multi-user setting with its application to Triple DES (TDES) in mind. Although depreciation of TDES is a global trend, the migration will take the next decade, considering the billions of TDES hardware the industry has invested so far. The multi-user security captures the reality of practical systems with multiple users, substantially impacts security, and is already considered in practical protocols such as TLS 1.3. The best multi-user lower bound of TDES is 43-(3/2) \cdot łog_2 u bits with u users, which is tractable with a standard PC and is unacceptably low. We devise a new proof to improve the multi-user security and show its tightness by giving a concrete attack. The new bound with the TDES parameters is 79-(1/2) \cdot łog_2 u bits. We also propose TEFX that strengthens triple encryption with the FX construction while preserving the compatibility with legacy hardware. TDES with TEFX achieves the multi-user security of 114-(1/2) \cdot łog_2 q bits with q TEFX calls: it achieves 84.5 bits with 2^40 users and 2^21 TEFX calls for each user, which is comparable to that of AES (128-40=88 bits).