Reviewerly/exHarmony huggingface dataset:
A Study on the Management Efficiency of Quasi-Market Type Public Firms

This study aimed to identify the management capabilities of quasi-market public corporations and examine the appropriateness of evaluation indicators by verifying the statistical relationship with management evaluation scores. In particular, by verifying how the COVID-19 crisis, which has continued since 2019, affects the management efficiency of quasi-market public corporations, it was possible to confirm how public corporations are coping with the global crisis. For verification, financial data from 2019 to 2021 of 18 quasi-market type public corporations were used, and the dependent variable, management efficiency, was measured through the DEA model. As a result of the analysis, the management efficiency value of quasi-market type public corporations has been continuously declining since 2019, and economic incompleteness and business environment deterioration caused by COVID-19 were also found in quasi-market type public corporations. In addition, these results could be reconfirmed as the dummy variable for whether or not 3 years after the occurrence of COVID-19, which can measure the cumulative impact of COVID-19, had a significant negative effect on management efficiency. Regarding the relationship between management evaluation and management efficiency, it is interpreted that the management evaluation index does not efficiently reflect the management system of quasi-market type public corporations during the COVID-19 period because the management evaluation score does not have a significant regression coefficient.
Current Status of Reshoring of Japanese Manufacturing Companies and the Japanese Government’s Support System for Attracting Businesses

Purpose: This study examines the current situation and characteristics of reshoring, manufacturers return to Japan from their production bases that have been relocated abroad amid increased instability in the global supply chain due to factors such as COVID-19 and Russia’s invasion of Ukraine. This study tried to figure out what kind of reshoring business attraction support policies are being deployed by the central government or local governments in Japan. Also the author tried to derive what implications these support policies have for Korea.&#x0D; Research design, data, and methodology: This study collects and analyzes the contents of previous research papers related to the Japanese government’s support system for attracting reshoring companies, statistical data from research institutes, press releases from media companies, and homepages of local governments regarding reshoring of Japanese manufacturing companies.&#x0D; Results: The Japanese government has executed various support policies at the central and local governments level to turn reshoring manufacturing companies into opportunities to contribute to the country’s economic regeneration and local growth, resulting in more than 500 companies returning to Japan annually in recent years. These results had the effect of creating new jobs in various parts of Japan, and the increase in local governments’ tax revenues led to the revitalization of the local economy.&#x0D; Implications: In order to induce a successful return to Korea for manufacturers wishing to reshor, policies that can provide unconventional incentives such as smart factory construction, R&amp;D support, and corporate tax cuts for reshoring companies should be reviewed and prepared.
Fighting Against Disinformation from Foreign Forces? Or Suppressing Criticism from Domestic Opposition Parties?

Abstract Every country is concerned about disinformation on the internet, especially its impact on domestic elections and domestic politics. Among them, there are concerns that mainland China will meddle in Taiwan’s elections with disinformation. In December 2018, Taiwan’s government launched a policy to combat disinformation, including proposing legal amendments. However, the laws that the Taiwanese government use to investigate and prosecute individuals are not newly revised laws, but an existing Social Order Maintenance Act. In addition, at the end of 2019, the ‘Anti-Infiltration Act’ was suddenly proposed and passed. Both laws (Taiwan’s main tools in the fight against fake news) raise questions as to potential violations of the freedom of speech, the discussion of which remains heavily influenced by the laws and jurisprudence of the United States (US). However, Taiwan’s judiciary and legislature have misunderstood the law in the US or have made amendments, resulting in divergent developmental trajectories.
Development of a basic word list for Military English using big data

The purpose of this study is to show the development process of the Military English Army Basic Word List (MEABWL), which is specifically designed for military English. The process of developing MEABWL involves the following three steps: 1) create a military English corpus (MEA_Corpus) by crawling big data composed of various military-related written and spoken texts; 2) make word lists in three ways (i.e., by using the scope of range, utilizing the corpus comparison approach, and extracting keywords) and select the most appropriate one for the study; and 3) develop a word list incorporating expert judgment in regards to
DISTRIBUTED APPLICATION FOR ORGAN DONATION

Organ donation is one of the most virtuous acts that requires transformation. This paper describes the proposed system which is an application which makes use of FIFO approach to choose an organ donor for each genuine person who requires the organ and if there's an exigency case, the precedence is given to that case. It uses Blockchain as its base Technology. Blockchain Technology is popular for its decentralized and distributed network which stores records that cannot be altered after being saved. The stability of Blockchain Technology provides the necessary security to the application. It uses electronic documents which are digitally endorsed by the users. It resolves the problem of authorizing the same user repeatedly. Key Words: Blockchain, Smart contracts, FIFO rule, security, Decentralized, authorized person
An Online Community of Data Enthusiasts Collaborates to Seek, Share, and Make Sense of Data

A Review of: Stvilia, B., &amp; Gibradze, L. (2022). Seeking and sharing datasets in an online community of data enthusiasts. Library &amp; Information Science Research 44(3). https://doi.org/10.1016/j.lisr.2022.101160 Objective – To understand the major activities, tools, sources, and challenges of online communities focused on datasets. Design – Content analysis informed by activity theory. Setting – The r/Datasets subreddit, a web forum for sharing, seeking, and discussing datasets. Subjects – 1232 “hot” or “top” discussion threads (1232 original posts and 6813 responding comments) first posted between 2010 and 2020. Methods – The researchers used Reddit’s API to collect their sample of threads. Using a random subset of the sample, the researchers developed a coding scheme for content analysis, which identified major themes in the data. Through this process, they controlled for quality: each researcher coded half the subset independently, then together evaluated their intercoder reliability and discussed and resolved disagreements. The researchers also employed labelled latent Dirchlet allocation to construct topic models corresponding to the theme’s manual content analysis, which produced profiles of the top 100 terms most likely to appear in that topic. Finally, the researchers extracted URLs from threads in the sample to ascertain types of information and data sources used by the community. Presenting their findings, the researchers discussed notable themes and proposed a metadata model for describing datasets, the Data Q&amp;A metadata (DQAM) model. Main Results – The r/Datasets community engages in three distinct activities: asking and answering questions, disseminating information, and community building. The closely related Q&amp;A and dissemination activities shared themes of obtaining and aggregating data, sensemaking, collaborating and crowdsourcing, and data evaluation. Community members frequently discussed tools, competencies, and sources for data work. Major challenges for members of the community related to the general themes of data quality, accessibility, ethics, and legality. A proposed 16-element metadata schema should meet the needs of data enthusiasts. Conclusion – The content analysis reveals a dedicated community engaged in an array of data-seeking and data-sharing activities. Data producers should be mindful of how their data can be accessed and used outside of their original professional or scholarly contexts.
Identity Generation with Deep Generative Models

Deep generative models have drawn the attention of the AI community in the last decade. The scalability of neural architectures helps solving multiple relevant problems, e.g., text-to-image generation, otherwise not addressable. In the context of image data privacy, the increasing amount of produced, shared, and stored images imposes new measures to protect personal identity information. At the same time, such protection mechanisms need to preserve the image quality. In this talk, we discuss how PiktID is using some recent deep learning-based techniques for protecting human identities in pictures. We show several examples, and we present interesting use-cases.
QUANTUM TELEPORTATION OF ENTANGLED STATES VIA GENERALIZED PHOTON-ADDED PAIR COHERENT STATE

In this paper, we study the quantum teleportation of an unknown atomic state based on the two-photon Jaynes-Cummings model, consisting of an effective two-level atom with a two-mode field in the generalized photon-added pair coherent state (GPAPCS). By applying the detecting method, we use a scheme that includes two two-level atoms and a cavity field to teleport the unknown atomic state from a sender to a receiver. The results show that the number of photons added to the field and the intensity of the initial field influence the average fidelity and success probability of the teleportation process. The time-evolution dependence of the average fidelity is also considered and compared for the field in the pair coherent state and in the GPAPCS.
Empirical investigation in embedded systems: Quality attributes in general, maintainability in particular

The quality of software systems is an important aspect, especially for embedded systems, thus strategies and actions for analyzing the trade-off between various quality attributes need to be improved. We target firstly to determine which quality attributes are important in embedded systems, and secondly to inquire about maintainability in particular, emphasizing the practices that are associated with it, i.e., coding rules, conventions, documentation, code review, and refactoring. We used interviews and surveys as means to investigate practitioners' points of view and practices. Applying quantitative and qualitative analysis, we explored a general perspective of quality attributes in embedded systems, followed by specific practices related to the maintainability attribute. At the general perspective level, we learned that the importance of security and safety is extended to all embedded systems, while maintainability remains of major importance, and there is a diversity of methods used to assure the quality of systems throughout the development cycle. At the maintainability-specific level, we learned that code review and refactoring are the most used practices and that the related activities are performed in a variety of ways. Our work recognizes various quality attributes as being important with different priorities, respectively analyses which maintainability-related activities are used.
The Effectiveness of Collaborative Strategic Reading (CSR) and Think, Predict, Read, and Connect (TPRC) Strategies to Teach Reading Comprehension to Students with Different Self-efficacy at MA Ma’arif NU 1 Kemranjen Banyumas

This research aims to examine the effectiveness of Collaborative Strategic Reading (CSR) and Think, Predict, Read, and Connect (TPRC) strategies in teaching reading comprehension to students with varying levels of self-efficacy. This type of research is a 2x2 factorial design. The subjects were XI IPA 1 and XI IPS 1 classes of MA Ma’arif NU 1 Kemranjen Banyumas. They are classified into high and low self-efficacy beliefs. The instruments used were test, questionnaire, and observation checklist. This research revealed that CSR and TPRC strategies are effective to teach reading comprehension to students with high and low levels of self-efficacy. Furthermore, there was no significant difference between the students who were taught by using CSR and TPRC strategies. The mean post-test scores of students with a high level of self-efficacy in both experimental classes were 75.06 and 73.78. Meanwhile, the mean post-test scores of students with low self-efficacy were 70.86 and 69.33. Based on the results, the researchers concluded that CSR and TPRC strategies appeared to improve students’ reading comprehension with high and low self-efficacy. Keywords: Reading comprehension, CSR strategy, TPRC strategy, Self-efficacy.
Quantum annealing for the adjuster routing problem

In the event of a disaster such as an earthquake, insurance companies basically conduct on-site witnessing. Depending on the scale of the disaster, hundreds of adjusters are dispatched from each office to the affected buildings per day. In such cases, which adjusters will witness which buildings and in what order must be determined, and the route must be optimized to conduct efficient witnessing. In this study, we define this witnessing route decision as an optimization problem and propose the adjuster routing problem (ARP). The ARP can be viewed as an extension of the vehicle routing problem (VRP). We introduce constraints not to be considered in the usual VRP, such as adjuster-building matching and satisfying the desired time. The VRP is an NP-hard optimization problem and is considered difficult to solve on a classical computer. Therefore, we formulated various constraints in QUBO so that quantum annealing can be applied to the ARP. In addition, we conducted numerical experiments with D-Wave. The ARP is a real problem, and our research provides a new example of applications of quantum annealing to real-world problems.
Frequency-multiplexed Hong-Ou-Mandel interference

The implementation of quantum repeaters needed for long-distance quantum communication requires the generation of quantum entanglement distributed among the elementary links. These entanglements must be swapped among the quantum repeaters through Bell-state measurements. This study aims to improve the entanglement generation rate by frequency multiplexing the Bell-state measurements. As a preliminary step of the frequency-multiplexed Bell-state measurements, three frequency modes are mapped to a temporal mode by an atomic frequency comb prepared in ${\mathrm{Pr}}^{3+}$ ion-doped ${\mathrm{Y}}_{2}{\mathrm{SiO}}_{5}$ crystals using a weak coherent state, and Hong-Ou-Mandel interference, which is a measure of the indistinguishability of two inputs, is observed in each frequency mode by coincidence detection. The visibility for all the modes was 40%--42% (theoretically up to 50%). Furthermore, we show that a mixture of different modes is avoided. The present results are connected to frequency-selective Bell-state measurements and therefore frequency-multiplexed quantum repeaters.
Neural Ad-Hoc Retrieval Meets Open Information Extraction

This paper presents the idea of systematically integrating relation triples derived from Open Information Extraction (OpenIE) with neural rankers in order to improve the performance of the ad-hoc retrieval task. This is motivated by two reasons: (1) to capture longer-range semantic associations between keywords in documents, which would not otherwise be immediately identifiable by neural rankers; and (2) identify closely mentioned yet semantically unrelated content in the document that could lead to a document being incorrectly considered to be relevant for the query. Through our extensive experiments on three widely used TREC collections, we show that our idea consistently leads to noticeable performance improvements for neural rankers on a range of metrics.
The Role of Human Resources Management Professionals' Skills in Information Technology

The current research aims to measure the impact of the skills of human resources management professionals in information technology in Iraqi private banks, as the skills of human resources management professionals constitute the modern trend of banks' interest in employees with outstanding performance, and the presence of information technology in banks is a prerequisite for dealing with the huge amount of data. And converting it into information to support the decision-maker in light of a complex environment, and the field research problem was the presence of a clear lack of interest in the skills of human resource management professionals and the weak adoption of information technology, which was reflected negatively on the competitiveness of Iraqi private banks. The questionnaire was adopted as a main tool in collecting data and information related to the research, which was prepared based on a number of ready-made scales and using the five-point Likert scale, and was subjected to validity and reliability tests, and distributed to a sample of (91) individuals from the managers and employees of human resources departments working in Iraqi private banks. And to analyze the research data, the ready-made statistical program (SPSS V.27) was used. Among the most important statistical tools used in the analysis are: "the arithmetic mean, standard deviation, coefficient of variation, Pearson's correlation coefficient, multiple linear regression, and path analysis." The most prominent results of the research showed that there is an indirect effect relationship to the skills of human resources management professionals in information technology
IMPLEMENTATION OF COMPETENCE-BASED APPROACH IN TEACHING MATHEMATICS IN PRIMARY SCHOOL

The article deals with the formation of key competencies in primary school students. In the state standards of the Kyrgyz Republic, when determining the complexes of competencies, special attention is paid to the fulfillment of the requirements of the standard in the process of teaching mathematics in elementary school. When implementing the training of the competency-based approach, the formation of subject competencies along with key competencies is important. The goals and objectives of teaching mathematics in the context of student-centered learning have been established
A COMPETENT APPROACH TO TEACHING COMPUTER SCIENCE

This article describes the activities of the teacher, work experience aimed at the formation of core competencies in the computer science lesson. When implementing the competence approach, the emphasis is on developing new teacher positions, organizing such a lesson, the main purpose of which is to teach how to learn.
How to Generalize Causal Processes

Transcript Auto scroll search expand close Search Transcript Search Up Search Down Close Search Tools Tools icon close Download PDFopens in new window Cite Cite icon close Format APA APA Chicago Harvard MLA AMA Beach, D. (Academic). (2023). How to generalize causal processes [Video]. Sage Research Methods. https://doi.org/10.4135/9781529670066 Beach, Derek. "How to Generalize Causal Processes." In Sage Video. : SAGE Publications, Ltd., 2023. Video, 00:26:53. https://doi.org/10.4135/9781529670066. Beach, D., 2023. How to Generalize Causal Processes, Sage Video. [Streaming Video] London: Sage Publications Ltd. Available at: <https://doi.org/10.4135/9781529670066 & gt; [Accessed 17 Mar 2023]. Beach, Derek. How to Generalize Causal Processes. Online video clip. SAGE Video. London: SAGE Publications, Ltd., 31 Jan 2023. doi: https://doi.org/10.4135/9781529670066. 17 Mar 2023. How to Generalize Causal Processes [Streaming video]. 2023. doi:10.4135/9781529670066. Accessed 03/17/2023 copy to clipboard or Export to your reference manager Endnote Endnote Reference Manager ProCite RefWorks BibTeX Zotero Medlars Mendeley Word Export Cancel Share Share icon close Share via Email Please log in from an authenticated institution or log into your member profile to access the email feature. Sign in/register Embed Embed icon close Embed this Content Add this content to your learning management system or webpage by copying the code below into the HTML editor on the page. Look for the words HTML or </>. Learn More about Embedding Video icon link (opens in new window) Clip - https://methods.sagepub.com/video/how-to-generalize-causal-processes Embed code: Copy to clipboard Select a length: Entire video Entire video Select a size: 420x236 640x360 853x480 Sample View: (opens in new window) Cancel Get link Get link icon close Select a length: Entire video Entire video Link to this page directly with a permalink: https://methods.sagepub.com/video/how-to-generalize-causal-processes Copy to clipboard Cancel
Exploring Latent Sparse Graph for Large-Scale Semi-supervised Learning

We focus on developing a novel scalable graph-based semi-supervised learning (SSL) method for input data consisting of a small amount of labeled data and a large amount of unlabeled data. Due to the lack of labeled data and the availability of large-scale unlabeled data, existing SSL methods usually either encounter suboptimal performance because of an improper graph constructed from input data or are impractical due to the high-computational complexity of solving large-scale optimization problems. In this paper, we propose to address both problems by constructing a novel graph of input data for graph-based SSL methods. A density-based approach is proposed to learn a latent graph from input data. Based on the latent graph, a novel graph construction approach is proposed to construct the graph of input data by an efficient formula. With this formula, two transductive graph-based SSL methods are devised with the computational complexity linear in the number of input data points. Extensive experiments on synthetic data and real datasets demonstrate that the proposed methods not only are scalable for large-scale data, but also achieve good classification performance, especially for an extremely small number of labeled data.
PERAN PRODUK MANAGER DALAM PENGEMBANGAN APLIKASI SI CANTIK

Si Cantik stands for Integrated Licensing Service Application for the Public in the form of a cloud system that can be used by government agencies for free. Si Cantik itself is a web-based application that is integrated with online single submission (OSS) for licensing and non-licensing carried out by the government's One Stop Service (PTSP), both at the central and regional levels. This application was developed to facilitate transparent, effective and efficient licensing services. Product Manager or product management is a strategic function within a company organization that deals directly with matters related to product development, business improvement, product launches, to determining the marketing strategy of a product in the company. Product manager is concerned with product development. Therefore, a product manager is needed to develop the Si Cantik application. This type of research is a qualitative research with a descriptive approach, as well as data collection techniques with literature or literature studies. Si Cantik is designed to handle licensing and non-licensing processes, from the application stage to document issuance, and integrated executive report generation. The role of the product manager will help in developing the Si Cantik application. The product manager will use 12 tools to make his job easier. These 12 tools will be used for the development of the Si Cantik application and also add features that will provide convenience and convenience of service for the community.