Reviewerly/exHarmony huggingface dataset:
Experimental validation of elderly support robot integrated with knowledge representation interface

Abstract As the population of modern society ages, accidents involving the elderly are increasing and there is a shortage of caregivers. Care robots are currently being developed, but they are not yet widely used. One of the reasons for this is that complex systems with numerous sensors are costly and require substantial maintenance. Another reason is that it is difficult for people to understand complex automatic systems, and physical contact with such systems can cause a sense of unease. For this reason, the authors have been researching a user state estimation method for care robots using a small number of sensors and an information presentation method that generates a sense of ease. The center of gravity (CoG) is an effective indicator of the state of the human body, but it generally requires many sensors to accurately determine. To solve this problem, we developed a method for calculating candidates for the CoG using a small number of sensors. In our previous studies, we validated the experimental method via off-line state estimation simulations on the measured data when the robot was moved without any state estimation. However, this technique was insufficient for validating real-time state estimation with an actual robot and for operating the robot based on the estimation. In addition, the care robot developed in previous studies was equipped with an interface to reduce the user's sense of unease, and it presented the estimated user status and timing of user movements on the screen and described them with audio. However, the system was limited to presenting information while providing standing support only, and did not communicate with the user while they were walking, sitting, or oriented abnormally. In this study, we prototyped an interface that presents information on all user movements, such as standing, walking, sitting, and abnormal states, and that links those movements to the care robot's response to the estimated user state. The effectiveness of the interface was validated through experiments using an actual robot with several participants. In all cases, the robot estimated the user's state, raised and lowered the armrest to allow the user to stand up and sit down, and stopped its motion and reverted to its original state when it detected an anomaly. The effectiveness of the interface was also confirmed by participant interviews. These results confirmed the effectiveness of the proposed method in estimating the user's state, providing support based on that state, and presenting information through the interface with a sense of ease.
Decicion Suport System Pemilihan Pestisida Terbaik Pada UD. Pupuk Jasa Tani Menggunakan Metode Weighted Product

Pesticides are materials to kill pests and diseases in plants. Pesticides are chemicals that are commonly used in agriculture, to kill pests and diseases that exist in agricultural crops. Based on the problems that exist in the community, researchers are trying to help the community to be able to identify the right type of pesticide for the plants that are being planted. Artificial intelligence is transferring the intelligence possessed by humans into a computer machine so that it is able to behave which is considered as intelligent as human abilities. An expert system is a branch of artificial intelligence that transfers the expertise of an expert into a system so that it can imitate the way of thinking of an expert in solving a problem. This expert system application produces output in the form of the best value for selecting the right pesticide based on the criteria inputted by the user and produces conclusions in the form of the best pesticide decision results based on the results of system analysis. The method used in this expert system is the weighted product method which was built using the PHP programming language and MySQL database.
On the Concept of Model in Physics

The concept of model is the basis for theoretical and experimental research in physics.A model is defined as an application of physical theories to the description of a physical system.As a premise to the introduction of models, physical theories are defined as mathematical frameworks with a hypothetical-deductive structure, provided with a mapping on the real world, allowing the description of a class of phenomena.The main characteristics of theories are discussed, in particular the domain of application and the relationships between different theories.The concept of physical system is introduced as a subset of the universe that is defined thanks to the property of separability and is characterized by appropriate boundary conditions.The structure and the main characteristics of models are then discussed and the steps to be taken to construct a model are considered.The role of assumptions is underlined and different kinds of models are illustrated.Finally, four examples of simple physical models are described, that are fit to be used for didactic purpose.
Rancangan Sistem Informasi Perpustakaan Berbasis Website Menggunakan Barcode Di Sekolah MA Raden Rahmat

Internal libraries are usually for example bookstores, where books, research results and journals are neatly stored. So that people who read it have to go to the library and look for the desired book. Many sources of scientific information, books, documents, library facilities, can be disseminated according to certain systems. . Methodology is doing something to achieve a goal. The framework describes the stages of conducting research. Because it helps researchers to explain the work steps that will be carried out in solving the problem. Based on the waterfall model, a discussion of each can be described, such as Analysis. Author's Design, Testing, Support or maintenance After Realizing the system design At this stage, the author implements the design results obtained previously. before the system is actually used properly by the user, the system requires a test phase first to ensure there are no problems in using the PHP programming language and the MySQL database is used as a programming language. The design of this barcode-based library information system is used to make it easier for librarians and members to borrow library books in managing library data. Based on the discussion and conclusions presented, a development proposal for further research.
Construing Language Communities through New Media: A Literature Review

The relationship between language and society not only discovers social and cultural issues through language phenomena but also explores the social meaning behind language from a social context.Without language, society cannot be formed and maintained; The combination of the two makes studying sociolinguistics particularly necessary.Social Networking Sites (SNS), as a non-regional speech community, break through geographical restrictions and forms a new speech community network.Regions do not limit new media, and many people question whether it constitutes a "speech community" precisely because it is a developmental theory, and it is even more necessary to conduct in-depth research on non-regional speech communities.Some scholars propose four critical consequences of SNS: the benefits to communication, information, community, and identity.This paper gives previous studies conducted to investigate using new media from these four perspectives.Framework of Communities of Practice and the five super-strategies of impoliteness can be applied in the power-related discourse analysis in professional groups.
Does Online Learning Impact Accounting Students’ Performance? An Empirical Answer from Kuwait

This study aimed to empirically assess and document the impact of online learning on the academic performance of accounting students at a business college in Kuwait.The main value of this study would be its effort to fill some of the gaps in the existing local and regional remote (distance) accounting education literature as e-learning is considered to be a new phenomenon in most developing countries including Kuwait.A linear regression model (OLS), correlation, and t-tests analyses using a sample of 143 accounting students, who were enrolled before and during the COVID-19 pandemic, were used to test the study's hypotheses.The results indicate that there was a statistically significant association between learning systems (class delivery models) and accounting students' performance explaining the superiority of the academic performance of accounting students utilizing online learning over the performance of the same group of students using traditional learning and showing the significant impact of learning systems on accounting students' performance.The study concluded by considering the implications of these findings, which can provide decision-makers with a useful benchmark for improving accounting programs by considering online learning as an alternative system to traditional learning and provide insights for future academic research.
Connotation and Present Situation of Basic Teaching Skills of Rural Teachers

The policy of government-funded normal university students is one of the important measures taken by the state to improve the education level in rural and remote areas.In order to supply more qualified teachers to rural middle schools, Taishan University has built a teaching resource base of basic teaching training courses through the Internet, including teachers' oral practice, standard writing of Chinese characters and multimedia courseware production.It has also created a mixed teaching model combining offline classroom teaching and online independent learning, combining theory with practice.Forming a complete training curriculum system of basic teaching skills with clear division of labor and mutual connection can not only enable public funded normal university students to master advanced teaching theories and professional knowledge, but also enable them to have solid basic teaching skills and teaching practical ability.It is of great significance to improve the level of education in rural areas and promote the balanced development of education.
Techno Smart Digitalization of Currency: e-Rupee, The Indian Prospective

“Central Bank Digital Currency” is the new buzzword in world economy in recent past. Digital currency has a potential to bring revolutionary shift in the economy and uplift the monetary infrastructure of global economy. Till December 2022, 11 countries had launched their digital currencies in pilot survey or fully functional form. Recently, India has launched Digital Rupee -Wholesale (e₹-W), on November 1, 2022, and Retail (e₹-W), on December 1, 2022. The Global digital payment market has marked exponential growth in past few years. Even in India the value of e-payment market grew from ₹1393 lakh crore in 2016 to ₹3,000 lakh crore in 2021. With increasing user-friendly interfaces like UPI, also convenient modes like internet banking, debit cards, credit cards, NEFT, RTGS etc. and cutting-edge technologies, the population is livered to digital platform for payments. And hence it can be assumed that people would respond to e-rupees as a digital currency as well.
Mediating Role of Customer Relationship Management between Buying Behavior and Critical Risk Factors via Digital Buying

Purpose: To examine the mediating effect of Customer Relationship Management (CRM) amid Digital Buying Behaviour (DBB) and Risk Factors (RF).Methods: The structured questionnaire was adopted to analyse critical factors of DBB, RF and CRM.The instrument was designed and validated with the help of exploratory factor analysis and confirmed the items by confirmatory factor analysis.The model fitness is verified.The reliability of the scale was tested along with CR.The field testing is done to remove ambiguity.The nativity changes were incorporated to align the current study.The responses were collected using convenience sampling method through the e-mail survey and 410 valid responses (digital consumers) considered.The data were collected during August -November 2022.Quantitative approach is used to examine both directions of the considered variables.First, the direct effect of DBB on RF is examined.Secondly, the direct effect of CRM is studied.Further, mediating effect of CRM in relationship amid DBB and RF is established.Findings: The DBB is significant and directly connected with RF (β = 0.952, p < .001),CRM is significant and positively allied with RF (β = 0.471, p < .001).DBB is significant and positively related to CRM (β = 0.779, p < 0.001), after removal of mediating variable (CRM), β weight of DBB is reduced from 0.952 to 0.703.Sobel test is steered to confirm the significance of the mediation effect of CRM, test statistic (z= 3.09, p <.001).Thus, CRM act as a partial mediator amid DBB and RF.Novelty: The present study integrates DBB, RF and CRM features associated in digital buying in solitary manner unlike sliced approach.The study of CRM role especially in digital buying is a uniqueness of the present research.Further, studying the partial mediating effect of CRM amid DBB and RF itself is a new attempt.
FACIAL EXPRESSION BASED EMOTION DETECTION SYSTEM FOR ANALYSIS OF SENTIMENTS IN ELDERLY

This article addresses the use of extraction of characteristics for facial expressions in conjunction along a neural network to identify various sentiments (happy, sad, angry, fear, surprised, neutral etc..).The rapid advancement of artificial intelligence has made significant contributions to the field of technology.One of the most crucial aspects of human communication that aids in our understanding of what the other person is attempting to say is the expression on their face.Only one-third of the message is understood vocally, and the other two-thirds are understood nonverbally.There are numerous face emotion recognition (FER) systems in use today, however they are ineffective in real-world situations.Despite the fact that many assert that their system is nearly perfect.The testing data then examines the information and its classification report names the testing data and indicates how accurately it was classified.For better data categorization, many strategies are used, modifying the images using the Histogram of Oriented Gradients (HOG) and Discrete Wavelet Transform or passing the training images through a Gabor filter (DWT).The training images are first run through The Histogram of Oriented Gradients (HOG) produces the best results to date, with an average precision of 92%.
Half-Tone Visual Cryptography Scheme For RGB Color Images

Objectives: Currently used visual-cryptography methods which use binary and gray-level images have some shortcomings such as large pixel expansion, poor visual quality of the reconstructed image, etc.Further modifications in visualcryptography methods are required to provide error-free and better results.It has been observed that the use of color images is more convenient and accurate in approach.Method: This research study presents a new and optimal scheme for the visual-cryptography which is centered on RGB color images.Jarvis halftoning is applied on each decomposed color channel that is used in share generation.A special code matrix is defined for the generation of color shares and the optimal reconstruction of the original image.The method is tested with color images of different sizes, no specific dataset is required.Pixel Expansion, The Aspect Ratio, and Contrast of the method is compared with the existing method, and found more enhanced result.Findings: The scheme projected eliminates the problems of large pixel expansion and poor visual quality in the reconstructed images.The performance of the method is tested with the different statistical measures and values obtained as Mean Square Error (MSE):0, Peak-Signal-to-Noise-Ratio (PSNR): ∞, Universal Index Quality (UIQ):1, etc.This means that the original image is completely recovered with good contrast.Novelty: Color images of varied sizes and channels can be processed by applying the Jarvis half-toning technique through the codebook calculated to abolish the problems of pixel expansion and to improve the superiority of the renovated image.
Research Trends in Adversarial Machine Learning

The field of machine learning artificial intelligence algorithms has made significant progress.With the development of the times, the security brought by machine learning is worthy of consideration, and adversarial machine learning improves the reliability of machine learning algorithms through continuous training algorithms.Hence, the research of adversarial machine learning based on network security is well worth exploring.
<i>TRIMM</i>: A Propagation Model Based on Authentic Data

With the outbreak of COVID-19, considerable attention has been attached to the trade of wild animals, which is suspected to be the cause of the pandemic.It is main concern of all nations to excavate factors responsible for such emergence in particular.As a response, we elaborate novel model TRIMM so as to reveal the correlation between wild animal markets and epidemic situation of major infectious diseases.The TRIMM is modified and extended from the well-known propagation model SIS.Specifically, comparing to the original model, the TRIMM model is relatively transparent and rigorous.Furthermore, the TRIMM model is specialized for indicating correlation between wildlife trading and epidemic situation of major infectious diseases.Noticing the complexity of transmission of infectious diseases in reality, our model put 9 factors into consideration.To be precise, we consider the number of susceptibles that infectives in contact with per unit of time, the probability that susceptibles infected after being exposed to infectives and the recovery probability as the key indicators.In order to verify the effectiveness and fully unleash the potential ability of our model, we modify TRIMM model by utilizing SIR propagation model.In this way, we finds our model functioning well in more realistic environment.Eventually, sensitivity analysis is adapted to the model.We discuss strengths and weaknesses and discuss our future work with TRIMM model.
Optimized Data Hiding Method based on Meerkat Clan Algorithm for Image Steganography

To fulfill the security criterion of imperceptibility, the secret info is hidden in the cover image using image steganography. To do this, a hidden data bit swaps out the least important part of the cover image. The replacement process produces variability, which has an effect on the imperceptibility parameter. To address this restriction, this research proposes a unique optimal data concealing approach based on the meerkat clan optimization algorithm. This method seeks the best secret data to conceal in the cover image to be able to improve the imperceptibility parameter. The secret data is also divided into 2:4 ratios. The cover image is then divided into smooth and edge regions. A 2-bit LSB technique is utilized to hide data in the smooth area, whereas data hiding in the edge region is accomplished with a 4-bit LSB approach. The simulation is evaluated using multiple performance measures to compare its performance to existing approaches. The suggested technique outperforms the previous method in terms of imperceptibility.
DIGITAL IMAGE RESTORATION USING LINEAR PDE-BASED FILTERING MODELS

The linear partial differential equation (PDE) - based models for Gaussian noise removal are discussed in this paper. The digital image denoising and restoration solutions based on linear diffusion equations are surveyed first. Then, our own contributions in this image processing domain, representing some effective linear PDE-based filtering models based on hyperbolic and stochastic differential equations, are presented. The results of our denoising experiments are also provided in this article.
Low-Space Complexity Finite Field Multiplier Using Both Dickson and Polynomial Bases

Finite field arithmetic is one of the most commonly mathematic operations for cryptography.The finite field arithmetic operations over GF(2 m ) are largely utilized for point multiplication in elliptic curve cryptography.The most important arithmetic operation in GF(2 m ) is multiplications.Therefore, low-space complexity multipliers over GF(2 m ) have received significant attention in the hardware implementation of elliptic curve cryptosystems for resource-restricted devices such as smart phones.In finite fields, the implementation of multiplication depends heavily on the choice of basis used to represent field elements, e.g., the polynomial basis (PB), the dual basis (DB), and the normal basis (NB).Each basis has their advantages.Dickson basis is a new one in recent years.In this paper, we derive a low-space complexity multiplier using a double basis that consists of polynomial and Dickson bases.The proposed multiplier employs a linear-feedback shift register to process weight multiplications and has a linear space complexity that is significantly less than that of the recently developed subquadratic space complexity multipliers.The first multiplier which employs both polynomial and Dickson bases will be presented.
"Lesson Research" as a tool to improve teaching and learning

Annotation: This article discusses ways to implement the Lesson Study approach within the professional community of teachers, using the project's capabilities in their teaching practice. Interest in this topic is expressed in the improvement of teaching methods and increasing the level of knowledge of students in key subjects in secondary school
An end-to-end neural framework using coarse-to-fine-grained attention for overlapping relational triple extraction

Abstract In recent years, the extraction of overlapping relations has received great attention in the field of natural language processing (NLP). However, most existing approaches treat relational triples in sentences as isolated, without considering the rich semantic correlations implied in the relational hierarchy. Extracting these overlapping relational triples is challenging, given the overlapping types are various and relatively complex. In addition, these approaches do not highlight the semantic information in the sentence from coarse-grained to fine-grained. In this paper, we propose an end-to-end neural framework based on a decomposition model that incorporates multi-granularity relational features for the extraction of overlapping triples. Our approach employs an attention mechanism that combines relational hierarchy information with multiple granularities and pretrained textual representations, where the relational hierarchies are constructed manually or obtained by unsupervised clustering. We found that the different hierarchy construction strategies have little effect on the final extraction results. Experimental results on two public datasets, NYT and WebNLG, show that our mode substantially outperforms the baseline system in extracting overlapping relational triples, especially for long-tailed relations.