Reviewerly/exHarmony huggingface dataset:
Research on the muddy children puzzle problem

Muddy children puzzle is a well-spread mathematical puzzle. It can be solved by two ways, which are Kripke Structure and true and false statement. The model checking problem is solved by searching the state space of the system. Ideally, the verification is completely automatic. The main challenge is the state explosion problem. The problem occurs in systems with many components that can interact with each other, so that the number of global states can be enormous. This paper observes that any propositional planning problem can be modeled as an LTL model checking problem as any propositional goal g can be expressed in the form of a counterexample to the temporal formula in LTL. If the problem is solvable, the LTL model checker will return a counterexample, which manifests a solution for the planning problem. This paper shows that the puzzle is solvable for any number of agents if and only if the quantifier in the announcement is positively active (satisfies a form of variety).
A Study on the Perception of Selected Ethnic Communities Toward Communication Media : An Empirical Study

Purpose : Ethnographic marketing is an emerging area in the field of management. In a world marked by growing multiculturalism, media plays a significant role in the dissemination of information. Marketers are required to know the nature of the perception held by ethnic communities toward media. This is essential to provide tailored media content to respective targeted communities. Hence, the study was carried out to know the perception of ethnic communities toward communication media. Design/Methodology/Approach : The study was conducted using an exploratory research design on a sample of 1,200 units comprising 400 respondents from three ethnic communities selected, namely Bodo, Mishing, and Rabha. The study used a convenience sampling technique, and data were collected by a structured interview schedule. Attitudinal statements were used to record the responses. Multiple discriminant analysis was used for data processing. Findings : The study found that the Rabha community associated media with advertisement as a platform for choice alternatives of products and as an informer of offers. The Bodo community perceived media as the news channel through which information is circulated, but it is not always deemed to be authentic. Finally, the Mishing community perceived media as the educator of people, as the mobilizer of public opinion, and as the provider of information on the latest trends. Practical Implications : As ethnic communities form significant segments of target markets today, the findings are vital inputs for marketers to suitably use the right media for communication in the right perspective. It will consequently facilitate in providing tailored media content to respective communities being targeted by the stakeholders. Originality/Value : Although studies on consumers’ perception toward communication media are available, studies on the specific ethnic communities in the specific geographical region identified are rare. The research findings will go a long way in enlightening academicians as well as marketers who are related to this area and, thus, find it novel. Furthermore, people from the field of anthropology and mass communication may get vital inputs on the behavior of ethnic communities toward media..
Phase transitions for support recovery under local differential privacy

We address the problem of variable selection in a high-dimensional but sparse mean model, under the additional constraint that only privatized data are available for inference. The original data are vectors with independent entries having a symmetric, strongly log-concave distribution on $\mathbb{R}$. For this purpose, we adopt a recent generalization of classical minimax theory to the framework of local $\alpha$-differential privacy. We provide lower and upper bounds on the rate of convergence for the expected Hamming loss over classes of at most $s$-sparse vectors whose non-zero coordinates are separated from $0$ by a constant $a>0$. As corollaries, we derive necessary and sufficient conditions (up to log factors) for exact recovery and for almost full recovery. When we restrict our attention to non-interactive mechanisms that act independently on each coordinate our lower bound shows that, contrary to the non-private setting, both exact and almost full recovery are impossible whatever the value of $a$ in the high-dimensional regime such that $n \alpha^2/ d^2\lesssim 1$. However, in the regime $n\alpha^2/d^2\gg \log(d)$ we can exhibit a critical value $a^$ (up to a logarithmic factor) such that exact and almost full recovery are possible for all $a\gg a^$ and impossible for $a\leq a^\*$. We show that these results can be improved when allowing for all non-interactive (that act globally on all coordinates) locally $\alpha$-differentially private mechanisms in the sense that phase transitions occur at lower levels.
THE CORRELATION BETWEEN THE SENSE OF BELONGING AND LEARNING MOTIVATION TOWARD THE STUDENT’S SOCIAL WELFARE

This research aims to see the correlation between the Sense of Belonging and the Motivation to Study and the correlation between the Sense of Belonging and Motivation to Study toward the Student's Social Welfare. This research uses causal models. The analysis technique used is SEM (Structural Equation Modeling), operated through the LISREL program. The population in this study were all active Indonesian students studying domestically. The number of samples in this study was 227 students who filled out questionnaires online. The results of this study indicate that the Sense of Belonging has a simultaneous influence on the Motivation to Study by 63%, and The Motivation to Study and the Sense of Belonging simultaneously influence the student's social welfare by 93%. &#x0D;
Interpreting Doctor’s Handwritten Prescription Using Deep Learning Techniques

A Doctor’s Handwriting Recognition model can predict (recognize) the text present in the doctor’s prescription, by feeding image of that medicine name to the model, and it predicts the text present in the image and it gives the final medicine name as digital text. This model is suitable only for text written in English language and not suitable for other languages of texts written in prescription. The model based on training dataset the output it produces may get varied and based on training images count. Both convolution layers and Bi-Directional LSTM layers can be used for feature extraction and recognizing text, respectively.
Develop A Prototype Based On Wiki For Emergency Health Care

The problem of this study is embodied in the lack of health sector for a knowledge system that contains thebest health practices to deal with emergency medical cases. There was a need for a knowledge systemcontaining the best practices to deal with them. As a consequence, this study aims at finding a developingknowledge model to contain most of the experiences related to the best health care introduced to theemergency medical cases and the work to maintain this model by involving the new experiences by theexperienced medical staff so that health care provider will be able to know the best practices of theemergency cases and the mechanism of dealing with the case at its arrival time to the emergency unit in thedepartment. We have adopted the systems development life cycle (SDLC) methodology. We have used(Prototype) model and we have used (Focus Group) technique to conduct interviews with medical staff(Physicians, Nurses, Pharmacists, and Radiologists) all of them were serving in the emergency units (12participants). One of the main findings of the study was creating a knowledge-based application for themedical staff in emergency units. We recommend implementing the application in all emergency units inJordanian hospitals, In addition, this model can be integrated with (Hakeem) program in health care sector.
Research on Modern University Libraries to Serve the Development of Higher Education

With the fast expansion of higher education in China, the construction and development of university libraries cannot obviously follow behind the pace of higher education.It has to face increasing problems arising from many factors relevant.It also raise the question how to deal with the present problem and seek for further develop.In order to answer the question, this paper focuses on three aspects such as space layout, collection quality, and personnel training, aiming to explore the construction of modern university library to serve the development of higher education in China.
Analysis of Human Joint Mechanics Based on High-Precision Unmarked Motion Capture System

The analysis of human joint mechanics is of great value in rehabilitation assessment and competitive sports training.There are many limitations in the application of the existing motion capture system, which makes the usage scenarios relatively limited.To solve this problem, this paper proposes a multi-camera 3D motion capture system based on reprojection optimization, and combines the foot mechanics data to obtain the human joint torque.First, build a multi-camera-based motion capture system to obtain human body motion data, reconstruct key points to obtain 3D data, and then propose an accurate key point algorithm based on weight-based reprojection optimization to obtain precise coordinates of key points.Finally, the coordinates of the key points combined with the mechanical data of the foot are calculated by OpenSim to obtain the mechanical data of the human joints.The experimental results show that the capture accuracy of key points is 5% higher than the average accuracy of the traditional least square method, and the analysis of joint mechanics data conforms to the laws of motion, which can be used to guide rehabilitation evaluation and competitive sports.
AN EXPERIMENTAL STUDY TO ASSESS THE EFFECTIVENESS OF AEROBIC EXERCISES ON SELECTED WITHDRAWAL SYMPTOMS OF ALCOHOLIC DEPENDENTS IN SELECTED DE-ADDICTION CENTRE OF VADODARA

illness characterized by significant impairment in
Entropy bottleneck network for IR image compression

The objective of image compression is to reduce irrelevance and redundancy of the image data to be able to store or transmit data in an efficient manner by minimizing the number of bits required to represent an image accurately. JPEG is capable of achieving an image compression ratio of 10:1 with little perceptible loss in image quality using standard metrics, and has become the most widely used standard image compression in the world since its release. Traditionally, compression techniques have relied on linear transforms to approximate 2-D signals (images), and the omission of specific constituent vectors has been mostly arbitrary. These techniques can save incredible amounts of memory while retaining image integrity. Recently techniques have been developed that use neural networks to approximate these signals. These networks offer the advantage of decorrelating image data to find a series of vectors to represent an image that is smaller than traditional techniques by estimating gradient descent, thus finding the minimum number of bits required to represent an image. Expansion to the development of these architectures is happening rapidly through informed design drawing upon other fields that have recently seen increased focus such as computer vision and image analysis applications. A novel efficient neural network is proposed in this work to compress infrared images at state of the art levels while preserving overall image quality to handle the demands spanning from the daily commute to combat environments.
Virtual reality for CSI training

The EU-funded project, Real-Time On-Site Forensic Trace Qualification (RISEN) aims to enable the use of advanced sensors in the field in order to get results in near real-time. The project also aims to visualize the data by innovative means, such as in virtual reality (VR). The Swedish National Forensic Centre, NFC, has been developing methods for 3D modeling of crime scenes since 2016, and have conducted several studies in the use of VR for CSI application. This paper describes the status and possibilities with VR for CSI training and how the results from the RISEN project can be utilized within forensic training.
Research on P2P Default Risk Prediction Based on Logistic Regression

With the rapid development of the Internet, a variety of traditional industries use information technology and Internet platform closely derived from a variety of emerging industries. In the financial field, traditional banks cannot meet the needs of small and medium-sized enterprises with rapid growth. Thanks to the mature development of Internet platforms, various P2P(Peer to Peer Lending) platforms have emerged as the times require. They provide a simple reception approval process and provide investors and borrowers with convenient lending channels. However, with the rapid development of the P2P industry, P2P has frequent security problems. The main reason for this phenomenon is that the personal credit evaluation of the borrower is inaccurate, which leads to a chain reaction. Therefore, the effective estimation of the credit data of the borrower is the key to solving the credit risk. With the rapid development of machine learning, various risk prevention and control models are more and more accurate in predicting personal credit. However, default data accounts for only a small part of the massive credit data, so it is particularly important to process the data set, especially to balance the sample data. Traditionally, SMOTE(Synthetic Minority Oversampling Technique) algorithm is generally used for oversampling of data. However, when there are noise samples in the auxiliary samples of the samples synthesized by this algorithm, the new samples may become the noise sample interference model. In this paper, the Borderline-SMOTE algorithm is used to oversample the data features. The results show that the model trained by the processed data set is better than the control model, both in accuracy and recall rate.
Natural Communication Technologies Providing Information through Natural Exchanges that Do Not Interfere with Human Activities

NTT Service Evolution Laboratories is conducting research on providing high-presence viewing experiences involving virtual people and objects as if they have been brought to life right in front of the viewers.This article introduces natural communication technologies providing natural and valuable user experiences by creating people, objects, and space that emulate an incredibly realistic presence and seamlessly linking them to the real world through natural interactions without any sense of latency.
Multi-chain Deployment over Smart Contracts to Enhance Security

A blockchain is a data structure in which each block is linked to the next in a time-stamped chronological manner. Each block is cryptographically linked to the others. This is a global distributed ledger that contains an immutable public record of financial transactions. Every new record will be reviewed across the distributed network before being saved in a block. All information is verifiable and auditable once it is deposited on the ledger, but it cannot be edited. It will be an underestimation to say that Blockchain Technology is one of the most inventions of this 21st century. More people are considering that the decentralization and translucence that comes along with blockchain technology have the prospective to jiggle multiple industries to its very staple. This article reconnoiters different blockchain applications and their deployment approaches. In other facets, Multichain is a platform for the creation and distribution of private blockchains, either within or between organizations. Likewise, there are many more blockchain applications than just cryptocurrency, and they can unsettle way more sectors than just the finance sector. We intentionally avoided showing the Blockchain’s impact on the banking sector to keep the list as non-fintech as possible. Smart contracts are well customary as the greatest enabling technology for blockchains. With them, a blockchain ecosystem becomes self-governing, open, consent, and credible. It is through a compilation of smart contracts that blockchains can operate without human intervention. The smart contracts are established to deploy at the predefined blockchain nodes. They can be entreated by the call-backs either from the blockchain system, the other smart contracts, or the participants’ information systems. Usually, blockchain operations and application-related rules can be predetermined as smart contracts. The use cases and their real-world functions differ, but the benefits derived from using the technology remain unchanged: immutability, transparency, redundancy, and security.
Cyber Laws and Cyber Security in Pakistan: Myths and Realities

The evolving nature of warfare is characterized by technology's ability to adapt and attack enemies in different ways at different times and places. This adaptability also extends to the realm of cybersecurity, where billions of dollars are illegally transferred, data breaches occur, national secrets are compromised, and critical public infrastructure is hacked. Pakistan, like many other countries, is not immune to these challenges. Pakistan recently experienced a massive cyberattack against a major institutional website, resulting in a successful intrusion by hackers. In response, Pakistani lawmakers introduced a cyber law, but at the time the scale and complexity of these new threats were not fully recognized. To protect itself from such risks, it is important for Pakistan to stay vigilant and continuously adapt its cybersecurity measures to meet the evolving cyber threat landscape.
Research on the Application Strategies of Teaching Methods in Physics Teaching

Social and economic development increasingly relies on education and technology, posing new requirements for the development of education.China implements the strategy of revitalizing the country through science and education, and continuously deepens educational reform.In physics teaching, it is required that the teaching content be close to life, linked to life, and cultivate students' abilities of cooperation, exploration, and independent thinking.Traditional teaching methods can no longer fully meet the new requirements of current society.By studying traditional and new teaching methods in physics teaching, we can obtain application strategies that better meet the development needs of students.This article investigates the research achievements of middle school physics teachers on teaching methods and the current teaching activities in middle school physics classrooms, and proposes the problems that exist in current teaching.Propose practical and feasible teaching strategies based on the laws of student psychological development and the requirements of society for student development.Emphasize teaching reflection, help teachers optimize teaching methods, and truly improve the efficiency of physics classroom teaching.
AgroCare - an android application for smart monitoring of agriculture

Agriculture technologies have shown potential to improve agriculture management.This awareness has attracted researchers to develop technologies for farmers to ease their daily routine and also to reduce cost of labor and increase the yield production.Smartphone is one of the gadgets that can be useful in agriculture because of its useful functions, portability and affordable.It helps users to find locations, access information and capture images and sound.Smartphone functions can be combined to build v ersatile mobile agriculture applications.These helps to deliver information about crops and management needs.This paper develops an Android application for smart farming in crop management known as Agrocare.Agrocare is a mobile application developed to help farmers in their field management.The application is developed using android studio, firebase etc. that is used to create mobile applications.The system is very efficient and accurate in diagnosing diseases using plant leaves, fetching live weather data and location/area calculations.All information is described in the English language.Final results of this project is the mobile application which will is useful to manage crops and improve the management.The same method can be applied to different crops in the future.
The data turn of scientific cognition and the research program of philosophy of data

We entered the age of big data characterized by data revolution at the beginning of the 21st Century.In this new age, data has become an economic resource, and an important component of scientific cognition as well.Compared with natural language and logic language, data is a scientific language with higher accuracy and convenience.With the advent of the age of big data, ways of scientific cognition are bound to be transformed from the language turn of the 20th Century to the data turn of the 21st Century.And the possible conditions for this data turn have been prepared in terms of scientific premise, technical conditions, social background, and philosophical basis.At present, the ways of scientific cognition have begun to change from language to data, from logic to algorithm, from analysis to synthesis, from proof to discovery, and from causality to relevance.The language turn in the 20th Century will be replaced by the data turn in the 21st Century, and efforts shall be made to construct the philosophy of data, in which data is recognized as the object, algorithm as the tool, and synthesis as the method, and a wide variety of issues such as data and the world, data and language, data and algorithm, data and knowledge, data and truth, and data and ethics will be explored comprehensively.
Research on the Framework of the Evaluation System of College Students&amp;apos; Learning Process

To construct the evaluation system of college students' learning process, there are three layers: target layer, criterion layer and sub-criterion layer.There are five first-level indicators in the criteria layer, which are the individuation of learning process, the individuation of learning analysis, the coupling of learning, the autonomy of learning process and the creativity of learning process.There are 17 secondary indicators in the sub-criteria layer.The establishment of a good hierarchical structure is the premise of using AHP to solve problems.The basis of analyzing problems is to build a multi-level structure by layering various influencing factors.To determine the relationship between the elements, and according to the controlling relationship of the upper layer to the factors of the lower layer, the influencing factors are hierarchical, and then the hierarchical structure model of the upper layer and the lower layer is constructed, the geometric average method is used to calculate the average of the experts.The geometric average method ensures the reciprocal character of the matrix.Six judgment matrices are obtained by sorting the data, using MATLAB tool to calculate the weight value of each layer index of each judgment matrix, and carry on the consistency test, obtain the weight value of each layer index, the judgment matrix has passed the consistency evaluation, to achieve the overall objectives of the system and put forward all the measures, decision-making programs.