Reviewerly/exHarmony huggingface dataset:
공급사슬 리스크에서 공급사의 중요도에 따른 모니터링의 효과

As the competition among firms has become more intensive, risk drivers in the supply chain have also become more diverse, emphasizing the need to apply effective control mechanisms according to supplier importance. Based on contingency and agency theories, this study intended to empirically investigate the effect of monitoring as an ex-post control mechanism on buyer’s performance according to the degree of supplier’s importance and the types of monitoring. We use a random sample of 479 manufacturing firms collected from the Korea Productivity Center. Our results show that buyer can effectively control supplier through process monitoring as supply chain risk increases. The results provide theoretical and practical insights on monitoring according to a degree of supplier’s importance under supply chain risk.
Sequential End-to-End Intent and Slot Label Classification and Localization

Human-computer interaction (HCI) is significantly impacted by delayed responses from a spoken dialogue system. Hence, end-to-end (e2e) spoken language understanding (SLU) solutions have recently been proposed to decrease latency. Such approaches allow for the extraction of semantic information directly from the speech signal, thus bypassing the need for a transcript from an automatic speech recognition (ASR) system. In this paper, we propose a compact e2e SLU architecture for streaming scenarios, where chunks of the speech signal are processed continuously to predict intent and slot values. Our model is based on a 3D convolutional neural network (3D-CNN) and a unidirectional long short-term memory (LSTM). We compare the performance of two alignment-free losses: the connectionist temporal classification (CTC) method and its adapted version, namely connectionist temporal localization (CTL). The latter performs not only the classification but also localization of sequential audio events. The proposed solution is evaluated on the Fluent Speech Command dataset and results show our model ability to process incoming speech signal, reaching accuracy as high as 98.97 % for CTC and 98.78 % for CTL on single-label classification, and as high as 95.69 % for CTC and 95.28 % for CTL on two-label prediction.
Lockable Signatures for Blockchains: Scriptless Scripts for All Signatures.

Payment Channel Networks (PCNs) have given a huge boost to the scalability of blockchain-based cryptocurrencies: Beyond improving the transaction rate, PCNs enabled cheap cross-currency payments and atomic swaps. However, current PCNs proposals either heavily rely on special scripting features of the underlying blockchain (e.g. Hash Time Lock Contracts) or are tailored to a handful of digital signature schemes, such as Schnorr or ECDSA signatures. This leaves us in an unsatisfactory situation where many currencies that are being actively developed and use different signature schemes cannot enjoy the benefits of a PCN.In this work, we investigate whether we can construct PCNs assuming the minimal ability of a blockchain to verify a digital signature, for any signature scheme. In answering this question in the affirmative, we introduce the notion of lockable signatures, which constitutes the cornerstone of our PCN protocols. Our approach is generic and the PCN protocol is compatible with any digital signature scheme, thus inheriting all favorable properties of the underlying scheme that are not offered by Schnorr/ECDSA (e.g. aggregatable signatures or post-quantum security).While the usage of generic cryptographic machinery makes our generic protocol impractical, we view it as an important feasibility result as it may serve as the basis for constructing optimized protocols for specific signature schemes. To substantiate this claim, we design a highly efficient PCN protocol for the special case of Boneh-Lynn-Shacham (BLS) signatures. BLS signatures enjoy many unique features that make it a viable candidate for a blockchain, e.g. short, unique, and aggregatable signatures. Yet, prior to our work, no PCN was known to be compatible with it (without requiring an advanced scripting language). The cost of our PCN is dominated by a handful of calls to the BLS algorithms. Our concrete evaluation of these basic operations shows that users with commodity hardware can process payments with minimal overhead.
Semiparametric tests for equality of two independent variances

In this article, we propose new semiparametric and bootstrap tests based on the ratio of two variances under a density ratio model and compare them with existing tests for testing the equality of two variances from two independent populations. We showed that the ratio of two independent variances follows an asymptotic log-normal distribution. Also presented in this article are large sample asymptotic results of the semiparametric estimator of the ratio of the two sample variances. We also present a theoretical comparison of our semiparametric test on the ratio of two variances with the existing non parametric test using Pitman’s relative efficiency. Numerical comparisons of the performance of various tests are performed via simulation studies. We also use two numerical examples to illustrate the implementation of new tests.
THE IMPLEMENTATION OF WEB BASED PEN PAL IN LEARNING WRITING RECOUNT TEXT

Writing is one of the skills that should be mastered by students in learning English. One of the ways to know the skill of the students in mastering the language is by looking at their writing. However, many students still have the low ability in writing. The researcher found this problem occurred in 8th graders of SMPN 1 Wonoayu after the researcher observed the field. The students felt difficult to establish their writing and felt bored when the teacher asked them to write. Reflecting on those issues, it is very important to apply the best and suitable method and tool in the learning writing process. The use of various ways of teaching and learning process is needed to motivate the students to learn English. In this case, the teacher used a web-based pen pal as a tool to learn writing. A pen pal is the term of writing and exchanging letters to interact with others. Writing letters is a simple way to make the students write, and exchanging letters can be a fun way to learn English. Usually, the pen pal project is done traditionally using paper and pen, but this study used a web-based pen pal which is more innovative, flexible, and effective. This research study aimed to know the implementation of a web-based pen pal as a tool to learn writing recount text, and the students’ responses toward the implementation of a web-based pen pal. This study used descriptive qualitative research. The subject was the students of 8th graders of SMPN 1 Wonoayu. To know the implementation of a web-based pen pal in learning writing recount text, the researcher used observation sheets. Moreover, to find out the students’ responses, the researcher interview with some of the students. The result of the study showed that the implementation of a web-based pen pal could be a good tool in the process of learning writing recount text since the web site is interactive. The web-based pen pal also provided facilities that could make the learning process of writing became easier. Furthermore, many students enjoyed the use of modern technology and pen pal activity using websites since it could give them many benefits in the learning writing process. Keywords : Writing, Recount text, Pen pal, Web-based learning tools.
Optimizing Word Alignments with Better Subword Tokenization

Word alignment identify translational correspondences between words in a parallel sentence pair and are used and for example and to train statistical machine translation and learn bilingual dictionaries or to perform quality estimation. Subword tokenization has become a standard preprocessing step for a large number of applications and notably for state-of-the-art open vocabulary machine translation systems. In this paper and we thoroughly study how this preprocessing step interacts with the word alignment task and propose several tokenization strategies to obtain well-segmented parallel corpora. Using these new techniques and we were able to improve baseline word-based alignment models for six language pairs.
Multimedia Learning Theory: Preparing for the New Generation of Students

Due to the ever-changing world, educational environments have greatly shifted leading to the necessity to adapt our teaching and learning styles. Nowadays, a technological development plays a significant role in our life. The book entitled “Multimedia Learning Theory: Preparing for the New Generation of Students”, which was edited by Patrick M. Jenlink and published in 2019, would be one of the resourceful books for today educators. In ten chapters, the five contributors including Abbey N. Boorman, Charles L. Lowery, Brooks Knight, Richard E. Mayer and Scott McLeod have demonstrated a great panoramic idea of the current media and technological trend to be applied in current and forthcoming instructions.
Linking Employee Engagement to Employee Performance Moderating Effect of Organizational Politics

Extensive growth of service sector organization and changing work place dynamics and work environment call management to device mean of employee engagement and improve work performance. Organizational politics has been prevalent in most of the organizations and always being influencing the work dynamics as well as work culture affecting employee performance. The aim of present study is to analyse the linkage between drivers of employee engagement and employee performance and analyse whether organizational politics moderates the relationship between employee engagement and work performance. Descriptive research design has been used by the researcher in the present research work. The objective of the study and hypothesis was tested through collecting data for the problem under investigation using survey method. Structured questionnaire covering different dimension of objective was piloted on 169 employee associated with service sector organization located at Agra and Mathura Vrindavan of UP state. Confirmatory factor of employee engagement practices to identify the strength of factors of employee engagement and relationship with employee performance. Regression analysis was carried out to assess the moderating role of organization politics in the relationship between employee engagement and work performance. SPSS 22 software was used to carry out statistical analysis and testing the proposed hypothesis. Outcome of the research finding indicates that employee engagement practices significantly influence the employee performance. The study further support the hypothesis that organizational politics moderates the relationship between employee engagement practices and employee performance Service Sector organization is labour intensive organsiation where human resource and values plays an important role. Extensive research is carried out to identify the determinants of employee engagement to boost employee performance. Organization politics is an important issue and its positive intervention bring positive outcome in the organsiation Organizations recognize the importance of organizational politics with suitable work engagement practices to achieve greater performance. The management must follow the holistic approach for balancing employee activities so as to gain intended outcome.
Online Electrical Goods And Crew

Agriculture is said to be the backbone of the economy. Farmers toil hard with different kinds of crops to make good and healthy food for the country. There are more existing systems but uses outdated machine-learning techniques based on RNN( Recurrent neural network) which makes the process slower and more time-consuming. Here We are proposing a new CNN(Convolutional neural network ) based system which is fast and gives accurate results within seconds. CNN is power-efficient and is more suitable for real-time implementation. In this project, we use CNN algorithms which is very much better than the RNN algorithms used in the existing system.More parameters will be taken for the consideration of prediction in the proposed system. And we use Random Forest Regression, Multiple Linear Regression
Image Mining Based on Deep Belief Neural Network and Feature Matching Approach Using Manhattan Distance

Over the past few decades multimedia content, particularly digital images, has increased at a rapid pace, with several complex images being uploaded to various social websites such as Instagram, Facebook and Twitter. Therefore, it is difficult to search and retrieve the relevant image in seconds. Search engines retrieve images based on traditional textbased methods that depend on metadata and captions. In the last few years, a wide range of research has focused on content-based image retrieval (CBIR) based on image mining approaches. This is a challenging research area due to the ever-increasing multimedia database and other image libraries. In order to offer an effective search and retrieval, a novel CBIR system is proposed using the image mining-based deep belief neural network (IMDBN) technique. The proposed method is designed to enhance retrieval accuracy while diminishing the semantic gap between human visual understanding and image feature representation. To achieve this objective, the proposed system carries several steps like preprocessing, feature extraction, classification, and feature matching. Initially, the input database images are fed into the proposed image mining-based CBIR system, whereas colour-shape-texture (CST) feature extraction technique is applied to extract relevant feature set. The extracted features are fused and stored in the feature vector and aresubjected to the proposed IMDBN classification step to retrieve similar images in one label. Whenever a new query content is created, the most relevant images are retrieved. This, in turn, achieves 94% accuracy, which is higher than in existing approaches.
A Framework for Software Clone Management

Software development is frequently accompanied by activities such as adapting existing software, with or without change, and developing applications from the ground up. Copy-paste actions that reuse software result in clones, which are replicated code fragments. Because code clones impair the maintainability of the system being built, a variety of code clone detecting approaches and tools have been developed. This paper proposes a method for generating a prioritised list of code clones based on their detection. The code clones are graded according to their severity or criticality.
Awardee Solution of KDD Cup 2021 OGB Large-Scale Challenge Graph-Level Track

In this technical report, we present our solution of KDD Cup 2021 OGBLarge-Scale Challenge - PCQM4M-LSC Track. We adopt Graphormer and ExpC as ourbasic models. We train each model by 8-fold cross-validation, and additionallytrain two Graphormer models on the union of training and validation sets withdifferent random seeds. For final submission, we use a naive ensemble for these18 models by taking average of their outputs. Using our method, our teamMachineLearning achieved 0.1200 MAE on test set.
영유아교사의 마음챙김이 공감능력에 미치는 영향: 정서의 매개효과를 중심으로

This purpose of this study was to investigate the level of ECEC teachers’ mindfulness, affect, and empathy as well as the mediating effect of their positive and negative affect in the relationship between mindfulness and empathy. The participants who agreed to participate in the subvey were 201 ECEC teachers recruited from Seoul and five different provinces working at the kindergartens and childcare centers. The data were analyzed by means of frequency, percentages, and Pearson’s correlation using SPSS 25.0 and model 4 provided in The PROCESS macro for SPSS 3.4 version for parallel dual mediating effects. The findings of this study were as follows. First, the levels of ECEC teacher’s mindfulness, positive and negative affect, and empathy were above the median. Second, the ECEC teachers’ positive affect showed the full mediating effect in the relationship between their mindfulness and perspective taking of empathy, and a partial mediating effect in the relationship between their mindfulness and imaging of empathy. In addition, the positive and negative affect revealed parallel dual mediating effects in the relationships between their mindfulness and empathic concern and personal distress of empathy. These results implied that it is necessary to provide continuous year-long programs to promote ECEC teachers mindfulness and empathy.
El camino de la Biblioteca "Guillermo Bonfil Batalla" hacia una nueva realidad

Faced with the SARS-CoV-2 virus pandemic, the processes, work policies, and user care at the Guillermo Bonfil Batalla Library of the Escuela Nacional de Antropologia e Historia, had to change to adapt to a new reality in which the priority is the health of the staff and users, considering the proper handling of bibliohemerographic material to avoid the spread and contagion of the virus. After drawing on information from various sources and experts in various subjects, the head of the library produced the document Sanitary measures for the reincorporation of library staff and reopening of services to the public, with sections focused on: protection of library staff, cleaning of workspaces, user service protocol and services provided, bibliographic material, use and management of personal protective equipment, reinstatement of library staff and documentary references for the preparation of the document. The most important factor is the treatment that will be given to the books and magazines that will be consulted, since a “quarantine” will be assigned prior to your next consultation, the result of studies on the permanence of the virus on paper surfaces.
Log-Seed Pseudorandom Generators via Iterated Restrictions.

There are only a few known general approaches for constructing explicit pseudorandom generators (PRGs). The approach, pioneered by Ajtai and Wigderson [2], has provided PRGs with seed length polylog n or even O(log n) for several restricted models of computation. Can this approach ever achieve the optimal seed length of O(log n)?In this work, we answer this question in the affirmative. Using the iterated restrictions approach, we construct an explicit PRG for read-once depth-2 AC0[⊕] formulas with seed length[MATH HERE].In particular, we achieve optimal seed length O(log n) with near-optimal error e = exp(-ΩT(log n)). Even for constant error, the best prior PRG for this model (which includes read-once CNFs and read-once F2-polynomials) has seed length Θ(log n · (log log n)2) [22].A key step in the analysis of our PRG is a tail bound for subset-wise symmetric polynomials, a generalization of elementary symmetric polynomials. Like elementary symmetric polynomials, subset-wise symmetric polynomials provide a way to organize the expansion of [MATH HERE]. Elementary symmetric polynomials simply organize the terms by degree, i.e., they keep track of the number of variables participating in each monomial. Subset-wise symmetric polynomials keep track of more data: for a fixed partition of [m], they keep track of the number of variables from each subset participating in each monomial. Our tail bound extends prior work by Gopalan and Yehudayoff [17] on elementary symmetric polynomials.
Research On The Aesthetic Experience of Social Media Textual Language

After the public relations crisis, the endless roar of network public opinion brings great pressure of public opinion and economic benefit to the operation of social media. This paper discusses the public opinion of social media, which will highlight the concept of “user center” of social media, attach importance to the user value of social media, re-examine the “expected vision” of social media, pay attention to the “aesthetic experience” of social media, and improve the acceptance effect. Pay attention to social media aesthetic field and their own experience fusion.
Glocalized Experiential Learning Infused Resource Package in Earth and Life Science

The study aimed towards the development and evaluation of glocalized experiential learning-infused resource package in Earth and Life Science. The study used the educational design research method and involved the generation of a learning resource package. Participants of the study include the Grade 11 students of LNFVHS, S.Y. 2019-2020, as well as learning experts. Both qualitative and quantitative data were gathered for the study. Qualitative data came from focus group discussions, while quantitative data came from the results of the Bioenergetics test and Learning Material Evaluation Form. The least mastered competencies generated were The Cell, Photosynthetic Reactions, and Acquisition and Utilization of Energy. From this result, a glocalized experiential learning infused resource package was developed consisting of three learning materials based on the least mastered concepts--two (2) print materials (Learner’s Material and Teacher’s Guide) and one (1) non-print (Video-Based Module). The resource package was rated as very acceptable (3.70 for Learner’s Material, 3.65 for Teacher’s Guide, and 3.62 for the Video-Based Module). The study revealed that when learning materials were glocalized, contextualized, and infused with experiential learning activities, learners were more likely to be engaged in learning the concepts. The learning package developed helped in encouraging independent learning and a good source of supplemental learning material for Grade 11 and other grade levels.
Quality Of Management And Digital Learning Platform In Higher Educational Institution During Covid-19

The outbreak of COVID-19 raised significant disruption across many industries, including education, forcing organizations to modify their operations in order to stay in business. Technology has become an important tool and the rise of digital learning platforms has brought new perspectives to a range of companies. Education institutes have been forced to implement a wide range of digital platforms in order to support their learners, teachers, educators, and other staff members. The objective of this study was to help higher educational institutions to maintain their competitive advantages during the crisis by improving understanding of the incentives and barriers in relation to employing the most cost-effective approaches to providing a quality service and quality education for all learners during the pandemic. The findings reveal that the dimensions of information, system, and service quality, were found to be significant predictors of varied levels of user satisfaction. This means that overall quality management has a significant impact on user satisfaction. Analysis and implications of the findings are discussed. © 2012,ABAC Journal.All Rights Reserved.
Identifying Ransomware Actors in the Bitcoin Network

Due to the pseudo-anonymity of the Bitcoin network, users can hide behind their bitcoin addresses that can be generated in unlimited quantity, on the fly, without any formal links between them. Thus, it is being used for payment transfer by the actors involved in ransomware and other illegal activities. The other activity we consider is related to gambling since gambling is often used for transferring illegal funds. The question addressed here is that given temporally limited graphs of Bitcoin transactions, to what extent can one identify common patterns associated with these fraudulent activities and apply them to find other ransomware actors. The problem is rather complex, given that thousands of addresses can belong to the same actor without any obvious links between them and any common pattern of behavior. The main contribution of this paper is to introduce and apply new algorithms for local clustering and supervised graph machine learning for identifying malicious actors. We show that very local subgraphs of the known such actors are sufficient to differentiate between ransomware, random and gambling actors with 85% prediction accuracy on the test data set.