Reviewerly/exHarmony huggingface dataset:
Tourism High School Students Career Awareness, Career Education, and Educational Satisfaction

관광 특성화 고등학교에서 진로교육이란 단순히 취업률을 높이거나 대학 진학을 위한 활동이 아니다. ‘관광’계열에 관심과 흥미가 높은 학생들이 전문 교과를 배우면서 직업탐색을 하고 자신의 적성과 소질에 따라 진로를 준비하고 선택하도록 돕는 관광분야에 특성화된 진로교육을 담당하는 것이다. 그래서 자신의 적성과 소질에 맞추어 관광 분야의 진로를 준비하고 선택하여 나아갈 수 있게 도움을 주어야 한다. 이처럼 관광 특성화 고등학교의 설립 목적과 그에 부합하는 진로교육의 중요성에 대하여 모두 인지하고 있지만 실질적으로는 내&#8228;외부적인 환경 문제에 부딪혀효율적인 진로교육을 실천하기 어려운 실정이다. 특히, 관광 특성화 고등학교에 재학하는 학생들은 또래 아이들에 비해 진로의식과 진로성숙도가 높은 학생들이다. 대부분의 사람들이 성인이 되어서도 자신의 진로를 쉽게 결정하지 못하는데 관광 특성화 고등학교에 진학한 학생들은 대부분 호텔&#8228;항공&#8228;여행&#8228;식음료&#8228;관광사업 등의 직업의 꿈을 안고 그 꿈을 이루기 위해 입학한 학생들이 대부분이기 때문이다. 본 연구에서는 관광 특성화 고등학교 학생의 진로의식과 진로교육 실태를 다양한 측면에서 알아보고 보다 효율적인 진로교육과 관광 특성화 교육지도 방안을 모색하고자 하였으며, 이를 위하여 관련 문헌과 선행 연구를 통하여 설문지를 만들고 조사연구를 실시하였다.Career education conducted in tourism-specialized high schools is not about increasing employment or college entrance rates. Rather, it is about providing specialized career education on tourism while helping students interested in the tourism sector to learn the subject, search for jobs, and prepare for and choose their careers based on their aptitudes and talents. Therefore, the career education should practically help the students make preparations and choices for their careers in the tourism sector. While the purpose of establishing a tourism-specialized high school and the importance of career education corresponding to that purpose are well understood, it is, de facto, hard to conduct efficient career education because of internal and external environmental issues. In particular, students attending tourism-specialized high schools have better awareness of their careers and a higher sense of career maturity in their peer groups. Most people find it hard to make a decision on their career, even when they grow up, but most of these high schoolers already had dreams in their minds of getting a job in such fields as hotels, airlines, travel, food and drinks, and tourism, even before being admitted. This study aims to examine the career awareness among tourism-specialized high schoolers and the status of career education in various aspects and to seek out ways to provide more efficient career education and tourism-specialized education guidance.
Towards a Balanced State of the True Purpose of Education

A wise sage once stated, “The philosophy of the school room in one generation will be the philosophy of government in the next.” If public schools are the birthplace of future citizens and leaders, the focus on what it means to be a productive citizen must escape the contracted mindset of today’s education reform. Instead, public education needs to be reassessed, with the goal of cultivating optimal conditions for all children to grow to their full potentials
A score function for Bayesian cluster analysis

We propose a score function for Bayesian clustering. The function is parameter free and captures the interplay between the within cluster variance and the between cluster entropy of a clustering. It can be used to choose the number of clusters in well-established clustering methods such as hierarchical clustering or $K$-means algorithm.
On-demand photonic entanglement synthesizer

We demonstrate on-demand generation of photonic entanglement by dynamically controlling a loop-based circuit at nanosecond timescale. We generate 6 types of entangled states including 1000-mode lD-clustcr states without changing the circuit architecture. © 2019 The Author(s)
Improved View Selection Algorithm Using SOM and 0/1 Knapsack

Data warehouse is designed for answering analytical queries. Data warehouse saves historical data. In the data warehouse, the response time to analytical queries is long. So reducing the response time is a critical problem. There are a lot of algorithms to solve the problem. Some of them, materialize frequent views. The previously posed queries have important information that will be used in the future. This paper proposes an algorithm for view materialization. The proposed algorithm finds proper views using previous queries and materializes them. The views are able to answer future queries. The view selection algorithm has four steps. At first, it clusters previous queries by SOM method. Then frequent queries are found by Apriori algorithm. In the third step the problem is converted to 0/1 knapsack equations and finally, optimal queries are joined to create only one view for each cluster. This paper improves the first and third step. This paper uses the SOM algorithm for clustering previous queries in the first step and it solves the 0/1 knapsack equations according to shuffled frog leaping algorithm in the third step. Experimental results show that it improves the previous view selection algorithms according to response time and storage space factor.
Blockchain for cloud backup system

Blockchain Technology is an emerging technology in the software world. In order to understand the applications of the blockchain, it is necessary to understand how blockchain works. Blockchain was first introduced by Satoshi Nakamoto in 2008, which serve a Peer-to-Peer ledger for registering cryptocurrency bitcoin transactions. The blockchain is a list of records stored in the form of a chain. A blockchain is a decentralized distributed ledger which means a number of records are stored in a block and the block is added to the chain. Each block consists of a number of transactions for each transaction there will be a unique hash value, all hash values of the number of the transaction are combined and made a single hash value of the block and this follows Merkle root hash method. The invention of blockchain in cryptocurrency bitcoin solved the issue of double spending. The invention of blockchain in data backup can decrease the security complexity and duplication of the data. Rather than storing the data in one single hub that is the centralized system we can store the data in the blockchain which is a decentralized distributed ledger. In this decentralized system, the file is divided into a number of chunks stored into the blockchain which makes it difficult for data hacking and data tampering. In a centralized system if a server goes down then data is lost forever and in centralized system records can easily be altered because it does not have a backup to verify the records but in the blockchain, every peer in the network has the copy of the records and it is difficult to tamper the records. The files can be divided by a technology called Reed-Soloman erasure coding, generally used in CDs and DVDs. Reed-Soloman erasure coding allows dividing files in a redundant manner, where any 1 of 3 segments can fully recover a user's file.
The hybrid Morse code

In this research, Morse code was introduced in a new type, which we called the hybrid to be appropriate between the code itself and the theory of fragmentation, which could later be used as a type of encryption in messages between two or more parties.
PENERAPAN ALGORITMA C4.5 UNTUK PENENTUAN KELAYAKAN PEMBERIAN KREDIT (Studi Kasus : Koperia - Koperasi Warga Komplek Gandaria)

&lt;p&gt;&lt;em&gt;Current credit giving in KOPERIA (Koperasi Warga Komplek Gandaria) is still based on an objective process. Difficulties in determining the feasibility of giving credit are often experienced by cooperative managers, so that problems arise in the cooperative is a default payment of credit installments of customers in KOPERIA. This study aims to form a decision tree classification model to determine the customer's credit worthiness. In this study the application of C4.5 Algorithm, based on the Sets and Attributes used in this study, namely, the amount of income divided into 2 categories&amp;gt; 5 million and 3-5 million, the amount of balance divided into three, namely&amp;gt; 3 million, 1-3 million and &amp;lt;1 Million, The Loan Amount is divided into three, namely 1-4 Months, 5-8 months, and 9-12 Months and Requirements with attributes of Business Capital, buying goods and others. In this study determine the appropriate root nodes, the classification results using C4.5 Algorithm shows that the accuracy of 97.5% is obtained, based on the results obtained shows that the c4.5 algorithm is suitable to be used to determine the feasibility of lending customers to KOPERIA.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords&lt;/em&gt;&lt;/strong&gt;&lt;em&gt;: Data Mining, C4.5 Algorithm&lt;/em&gt;&lt;em&gt;, loan feasibility&lt;/em&gt;&lt;/p&gt;
Towards a Skeleton-Based Action Recognition For Realistic Scenarios

Understanding human actions is a crucial problem for service robots. However, the general trend in Action Recognition is developing and testing these systems on structured datasets. That's why this work presents a practical Skeleton-based Action Recognition framework which can be used in realistic scenarios. Our results show that although non-augmented and non-normalized data may yield comparable results on the test split of the dataset, it is far from being useful on another dataset which is a manually collected data.
Σχεδίαση και ανάπτυξη smartphone εφαρμογών με σύγχρονες τεχνολογίες σε android studio

This project is intented to develop an application for mobile phones using the Google Android software. The choice of this theme was made according to the fact that in modern times too many users use the Android software. So, we decided to create an electronical alarm application for devices that support Android 8.0 and above. The goal is to provide wake-up services to users with a more modern design and many different functions. Finally, for the development of our app we used the Android Studio tool as it is considered the best and most powerful application development tool.
The Implementation Of Bellman-Ford Algorithm In Rembang Tourism Mobile Application As A Tourism Information Media

Tourism is one of the methods to publish the beauty of nature or the uniqueness of culture in a region that spreads from the coast up to the mountains. The distribution and the access to tourist attractions require mobile application. In creating the application, Bellman – Ford algorithm was used to get the shortest route. The algorithm was the Bellman – Ford algorithm which was used to calculate the shortest distance to the tourist attraction on the weighted graph. Testing the functionality of the application used a black box. The results showed that functions on the mobile application could run well. The compatibility testing showed 100% compatibility with a number of Android devices. In addition, the usability testing showed that the application was appropriate to use with percentage by 82.7% of the 30 respondents. The "Rembang tourism" mobile application can be used by users of information about tourism.
Are System on Chip Displays the future of Digital Signage?

The global market for digital signage has been growing at an accelerated pace for the last ten years. The present paper provides a brief discussion about the Digital Signage concept mentioning some implementation areas, functions and new technologies. The benefits of System-on-Chip (SoC) technology and its implications for the Digital Signage industry are examined. Organizations like big retailers with a large quantity of stores, quick-serve restaurants, banks, hospitals and universities are more and more making use of dynamic digital signage displays to deliver their content and message instead of static signs. With Digital Signage this can be carried out easily and affordably at its core. This paper provides an overview of a Digital Signage software, DS SUIT, which is developed as a platform independent CMS, supporting SoC displays as well.
Multi-Model Investigative Exploration of Social Media Data with boutique: A Case Study in Public Health

We present our experience with a data science problem in Public Health, where researchers use social media (Twitter) to determine whether the public shows awareness of HIV prevention measures offered by Public Health campaigns. To help the researcher, we develop an investigative exploration system called boutique that allows a user to perform a multi-step visualization and exploration of data through a dashboard interface. Unique features of boutique includes its ability to handle heterogeneous types of data provided by a polystore, and its ability to use computation as part of the investigative exploration process. In this paper, we present the design of the boutique middleware and walk through an investigation process for a real-life problem.
Analisis Penggunaan Afiks pada Karangan Siswa Kelas VII C SMP Negeri 3 Bringin Kabupaten Semarang

This study has two objectives. 1) Describe the use of affixes in narrative essays and 2) describe the highest mistakes in using affixes in narrative essays of Class VII C students at SMP Negeri 3 Bringin Semarang Regency. The analytical approach used in this study is the Qualitative Descriptive Research Method. Data collection techniques in this study are by observation, implementation and evaluation. Validity Test The data of this study used the data validation test that was used, namely triangulation of data sources. Data analysis showed the use of affixes in essays of class VII C students of Bringin State Middle School found that there were 129 uses of affixes. The various types used include 79 uses of prefixes (di-, ke, bert, se, pen-, meN-, me, and ter-), 12 the use of suffixes (-an, -i, and), and 39 the use of confix (per-kan, kan, ber-kan, ke-an, me-i, di-i, pen-an). In this essay 106 data are written correctly and 23 are written incorrectly. The level of morphological errors in the narrative text consisting of affixation errors which include di-prefixes as many as 11 errors, as many prefixes as errors, as many as 5 error prefixes, ter prefixes as many as 1 error, suffix-1 error, suffix- 1 error.
Teaching Agents Through Correction

We motivate and describe a novel task which is modelled on interactions between apprentices and expert teachers. In the task an agent must learn to build towers constrained by rules. The teacher provides verbal corrective feedback from which the agent learns. The agent starts out unaware of the constraints as well as the domain concepts in which the constraints are expressed. Therefore an agent that takes advantage of the linguistic evidence must learn the denotations of neologisms and adapt its conceptualisation of the planning domain to incorporate those denotations. We show that an agent which does utilise linguistic evidence outperforms a strong baseline which does not.
Fooling Computer Vision into Inferring the Wrong Body Mass Index

Recently it's been shown that neural networks can use images of human faces to accurately predict Body Mass Index (BMI), a widely used health indicator. In this paper we demonstrate that a neural network performing BMI inference is indeed vulnerable to test-time adversarial attacks. This extends test-time adversarial attacks from classification tasks to regression. The application we highlight is BMI inference in the insurance industry, where such adversarial attacks imply a danger of insurance fraud.
Intelligent Realization of Big Data in Procuratorate

With the gradual transformation of information society to intelligent society, it is imperative for procuratorial organs to use big data services for procuratorial work. Big data reveals the rules and links behind the data by processing valuable data. Big data investigation is different from the traditional process of reconstructing crime by consequence tracing. It is an effective clue to mine the relationship between various clues by analyzing and processing data. On this basis, an effective model is constructed to predict the direction of investigation. Investigation means have changed from ex post investigation to ex ante investigation, from passive investigation to active investigation, from single thread investigation mode to multi-thread cooperation investigation, which will surely lead the development direction of investigation in the future.
Developing secure Bitcoin contracts with BitML

We present a toolchain for developing and verifying smart contracts that can be executed on Bitcoin. The toolchain is based on BitML, a recent domain-specific language for smart contracts with a computationally sound embedding into Bitcoin. Our toolchain automatically verifies relevant properties of contracts, among which liquidity, ensuring that funds do not remain frozen within a contract forever. A compiler is provided to translate BitML contracts into sets of standard Bitcoin transactions: executing a contract corresponds to appending these transactions to the blockchain. We assess our toolchain through a benchmark of representative contracts.
Teaching Social Behavior through Human Reinforcement for Ad hoc Teamwork - The STAR Framework: Extended Abstract

As AI technology continues to develop, more and more agents will become capable of long term autonomy alongside people. Thus, a recent line of research has studied the problem of teaching autonomous agents the concept of ethics and human social norms. Most existing work considers the case of an individual agent attempting to learn a predefined set of rules. In reality however, social norms are not always pre-defined and are very difficult to represent algorithmically. Moreover, the basic idea behind the social norms concept is ensuring that one's actions do not negatively influence others' utilities, which is inherently a multiagent concept. Thus, here we investigate a way to teach agents, as a team, how to act according to human social norms. In this research, we introduce the STAR framework used to teach an ad hoc team of agents to act in accordance with human social norms. Using a hybrid team (agents and people), when taking an action considered to be socially unacceptable, the agents receive negative feedback from the human teammate(s) who has(have) an awareness of the team's norms. We view STAR as an important step towards teaching agents to act more consistently with respect to human morality.
Using Entity Relations for Opinion Mining of Vietnamese Comments

In this paper, we propose several novel techniques to extract and mining opinions of Vietnamese reviews of customers about a number of products traded on e-commerce in Vietnam. The assessment is based on the emotional level of customers on a specific product such as mobile and laptop. We exploit the features of the products because they are much interested by customers and have many products in the Vietnam e-commerce market. Thence, it can be known the favorites and dislikes of customers about exploited products.
Research on Predicament and Outlet of Piano Microteaching

In recent years, the rise of piano micro-class has changed the traditional teaching mode of piano, which is convenient for students to learn independently and is not limited by time and space. Teachers can expand piano teaching more comprehensively by using piano micro-lessons, and extend the teaching after class. Students can also use micro-class to practice knowledge points in class repeatedly after class to improve learning efficiency, and share better educational resources on the Internet. Although piano micro-class teaching has many advantages and is the general trend in the Internet environment, it also has many problems such as fragmentation, non-systematicness, lack of communication between teachers and students, etc. This paper focuses on the current situation and predicament of piano micro-teaching in order to make full usage of its advantages, foster strengths and avoid weaknesses, and seek a better way out and development for piano micro-teaching.
Stick-Slip Vibrations in Violin Strings

The vibrations of a bowed violin string have been studied since the 19th century. Today these vibrations are known as stick and slip vibrations (self-excited vibration) caused by friction. The theoretical analysis of stick-slip vibrations was solved by Cellular Automaton Method during prior research. However, it is not solved by Modal Analysis Method. In this research, stick-slip vibration is solved by Modal Analysis Method. At the time of stick and slip, as a result of the simulation, it was possible to obtain results by Modal Analysis Method which is reasonable compared with Cellular Automaton Method.
An exploratory factor analysis (EFA) in determining dimensions of school culture in morality of secondary school students South-Western Nigeria

Students do not develop in isolation because they need to mingle with their colleagues in order to develop physically, academically and morally; which will assist the students in all spheres of life. Few studies however have been conducted to empirically examine the underlining factors determining the influence of School culture on the morality of secondary school students in southwestern part of Nigeria. The primary objective of this study was to validate the major components of School culture by using explanatory factor analysis (EFA). The cross sectional research design was utilized to answer the research questions. A sample comprised 365 respondents was selected from the population of secondary school students in southwestern Nigeria to answer a self-developed questionnaire. The study validates the factors structure of School culture using SPSS version 24. From the Exploratory Factor Analysis (EFA), the findings from the study have successfully identified four factors with (52%) percentage of total variance explained.
Contrast Optimization And Local Adaptation (COALA) for HDR Compression

This paper develops a novel approach for high dynamic-range compression. It relies on the widely accepted assumption that the human visual system is not very sensitive to absolute luminance reaching the retina, but rather responds to relative luminance ratios. Dynamic-range compression is then formulated as a regularized optimization in which the image dynamic range is reduced while the local contrast of the original scene is preserved. Our method is shown to be capable of drastic dynamic-range compression, while preserving fine details and avoiding common artifacts such as halos, gradient reversals, or loss of local contrast.
Non-Determinism in Neural Networks for Adversarial Robustness

Recent breakthroughs in the field of deep learning have led to advancements in a broad spectrum of tasks in computer vision, audio processing, natural language processing and other areas. In most instances where these tasks are deployed in real-world scenarios, the models used in them have been shown to be susceptible to adversarial attacks, making it imperative for us to address the challenge of their adversarial robustness. Existing techniques for adversarial robustness fall into three broad categories: defensive distillation techniques, adversarial training techniques, and randomized or non-deterministic model based techniques. In this paper, we propose a novel neural network paradigm that falls under the category of randomized models for adversarial robustness, but differs from all existing techniques under this category in that it models each parameter of the network as a statistical distribution with learnable parameters. We show experimentally that this framework is highly robust to a variety of white-box and black-box adversarial attacks, while preserving the task-specific performance of the traditional neural network model.