Reviewerly/exHarmony huggingface dataset:
A Comparative Study on the Efficiency of AEO Authorized Export Companies Using DEA and Malmquist Index

본 연구는 AEO 공인 수출제조기업의 생산성 및 효율성을 분석하고 변화에 영향을 미치는 요인을 분석하는데 연구 목적을 두고 있다. 연구분석을 위해 표본 기업의 2016년부터 2019년까지 최근 4년간의 DEA 및 Malmquist 생산성 지수 분석을 실시하였다. 연구 결과 첫째, 최적의 효율성을 보이고 기업은 2016년 19개 , 2017년 15개, 2018년 13개, 2019년 17개로 나타났다. 산업별의 경우 2016년 ‘C30’(자동차 및 트레일러 제조업) 5개 기업, ‘C20’(화학물질제조업) 10개 기업, ‘C26’(전자부품, 컴퓨터,영상,음향 통신장비제조) 4개 기업으로 나타났으며, 2017년 ‘C30’ 2개 기업, ‘C20’ 8개 기업, ‘C26’ 5개 기업, 2018년 ‘C30’ 1개기업, ‘C20’ 6개기업, ‘C26’ 6개기업, 2019년 ‘C30’ 4개기업, ‘C20’ 8개기업, ‘C26’ 5개기업으로 나타났다. 둘째, Malmquist 지수에 의한 생산성 변화를 추정한 결과 2016년부터 2019년까지 기업 규모별 결과는 전체 3기간의 총생산성 변화는 진보한 것으로 나타나고 있으며, 총생산성 변화가 감소하는 것으로 나타난 기간은 중소기업의 2016년-2017년의 단기간으로 나타났다. 상장기업과 비상장기업간의 Malmquist 지수 변화를 추정한 결과 상장기업의 생산성 지수 평균이 비상장기업에 비해 높게 나타나고 있음을 확인 할 수 있다. 셋째, 비교대상 기업군의 기업 규모 및 상장여부에 따르는 집단 간 차이의 윌콕슨 순위합 검정(Wilcoxson rank sum test) 결과 기업 규모별 평균값의 차이는 Mann-Whitney U 검정통계량 779.000, Wilcoxon W 검정통계량 1559.000에 대한 양측 근사유의확률(p-value)은 .018로 나타났으며, 상장여부에 따른 검정의 경우 Mann-Whitney U 검정통계량 857.000, Wilcoxon W 검정통계량 1677.00 양측 근사유의확률(p-value)은 .050로 나타나 상장 여부에 따르는 집단간 차이 역시 유의미한 것으로 나타났다.The purpose of this study is to analyze the efficiency of AEO authorized export manufacturing enterprises and to analyze the factors affecting efficiency. For analysis, a sample entity s analysis of the DEA and Malmquist productivity indices was conducted over the last four years from 2016 to 2019. The results of the study are as follows: First, the optimal efficiency was shown, and the number of companies was 19 in 2016, 15 in 2017, 13 in 2018, and 17 in 2019. In the case of industries, five companies were listed as C30 in 2016, 10 companies were listed as C20 and 4 companies were listed as C26 . In 2017, there were 2 companies for C30 , 8 companies for C20 , 5 companies for C26 , 1 company for C30 in 2018, 6 companies for C20 , 6 companies for C26 , 4 companies for C30 in 2019, and 5 companies for C20 and C26 . Second, the estimation of productivity changes by the Malmquist index showed that from 2016 to 2019, the results by size of the company showed that the change in gross domestic product for the entire three periods was advanced, and the period in which the change in the gross domestic product was reduced was short-term between 2016 and 2017 for small and medium companies. Estimating the change in the Malmquist index between listed and unlisted companies confirms that the average productivity index of listed companies is higher than that of unlisted companies. Third, the Wilcoxon rank-sum test for companies scale showed that the difference in average value by enterprise size was Mann-Whitney U test statistic 779.000, Wilcoxon W test statistic was 1559.000, and the probability of p-value for both sides was .018. As a result of the test according to whether or not the listing was conducted, Mann-Whitney U test statistics were 857,000, Wilcoxon W test statistics were 1677.00, and the probability of approximate oil on both sides was .050, which showed significant results.
UKBI: Experimental development of web-based Indonesian language proficiency test for foreign speakers

The web-based test is one of the tools for testing the learners' ability and skills of a language. The research emphasized on UKBI-Uji Kemahiran Berbahasa Indonesia (Test of Indonesian Language Proficiency). In this context, testing of foreign language tests such as Bahasa Indonesia increasingly plays a prominent role in Indonesia because every foreign worker is required to qualify certification of Indonesian language proficiency at the standardized level. The requirement complies with Regulation of the President of the Republic of Indonesia No. 20, 2018. This study aims to propose the development of Indonesian language proficiency test for foreign speakers. The initiative of development contributes to foreign learners' improvement beneficially. In this vein, it measures the ability of test-takers and then hones the language skills according to the description of the test results of the skills. This qualitative research involved 28 foreign students at BINUS University. This research revealed that the program accommodated students' learning development plan effectively, especially the skills of Indonesian language. In addition, this test will assist the stakeholders such as the Indonesian government, foreign learners, teaching associations of BIPA (Indonesian for Foreign Speaker) and activists, and BIPA teachers in long term eventually.
A Relative Study on Image Eminence while Sharing via Different Apps

With the advancement of communication and media technologies, the scope of research is also widening continually. In today’s media world, there exist numerous different applications and devices which facilitate fast and smooth transmission of information of any type. With the advent of smart phones and fast image capturing technologies, capturing and storing of images has become a very common activity. Also, the transmission or sharing of images, between two mobile devices via social media is trending high and has become the part of daily lifestyle. Various applications facilitate the quality transmission of images. Different applications follow different compression and transmission protocols and hence affect the quality of the images on sharing. In this paper, variation in the size and quality of images while their transmission using different mobile applications has been comparatively studied w.r.t. primary, secondary and few other tertiary colors using a mobile application viz. Portfolio RAW Photo Manager. The results are depicted to justify the variations.
문법 탐구 질문 저해 요인과 질문 과정과의 구조적 관계 분석

This paper attempted to explore the hesitation factors of questions of grammar learners and to objectify learner questionrelated aspects that have been discussed at an abstract level by presenting empirical verification results.To this end, first of all, through the conceptualization of grammar inquiry questions, the meaning and educational value of learner questions in grammar education were reviewed. In addition, exploratory factor analysis and confirmatory factor analysis were conducted to find out what the grammar learner’s questions were in the grammar class. In addition, this paper analyzed the structural relationship between the learner’s questioning process and the hesitation factors of questions by reconstructing hesitation factors of questions as internal and external factors of the learners.The results of this study confirm that the value and meaning of learner’s question formation and question behavior in grammar education are never light. I hope my studies related to learner’s questions in grammar education will be more active.
Experimental Demonstration of Multimode Fiber Imaging Based on Pre-trained Autoencoder

We propose to use autoencoder and a two-stage training strategy for image reconstruction in multimode fiber imaging system. Compared with the conventional method of U-net, this approach achieves higher reconstruction accuracy and faster convergence speed.
Rating Distribution and Personality Prediction for ImageAesthetics Assessment

Aesthetics has been an area of intensive interests and continuing exploration for long in multiple disciplines, such as philology, psychology, arts, photography, computer graphics, media, industrial design, and so on. Objective image aesthetic assessment (IAA) is related to three major considerations. First of all, technical quality assessment (TQA) of images still plays an important role in general, because basic visual features (e.g., contrast, brightness, colorfulness and semantic information) definitely influence humans' perception and experience. TQA has been already relatively better developed during the past two decades, so to be successful, IAA needs to focus more on the other two considerations that are special to it. The first consideration special to IAA is generic IAA (GIAA) which deals with aesthetic factors common to a typical human being or user, with examples of Rule of Thirds, symmetry, depth of field, object saliency, color Harmony, etc. The last special consideration is personalized IAA (PIAA) that is crucial in enabling many practical tasks, because "beauty is in the eye of the beholder".
Sistem Pakar Sistem Pakar Diagnosa Penyakit Osteoarthritis Menggunakan Metode Certainty Factor Berbasis Web

Degenerative diseases are diseases that accompany the aging process. Around the world, the number of degenerative diseases continues to grow. One degenerative disease that is often experienced is osteoarthritis. Osteoarthritis is one of the most common types of arthritis. This condition causes the joints to feel painful and stiff. Initially, osteoarthritis sufferers do not realize and respond seriously to the symptoms they feel. Whereas medically the symptoms they feel and if these symptoms are often felt then more serious consultation and examination should be done. Therefore, an expert system for diagnosing osteoarthritis was created using the web-based Certainty Factor method. Certainty Factor is a method that proves that a fact is certain or uncertain. With a web-based feature, an expert system to diagnose osteoarthritis can help the public to find out the percentage, type of disease, and advice from osteoarthritis. Based on system validation testing using certainty factor methods, it can be concluded that the system accuracy is 85%.
Statistical Guarantees and Algorithmic Convergence Issues of Variational Boosting

We provide statistical guarantees for Bayesian variational boosting by proposing a novel small bandwidth Gaussian mixture variational family. We employ a functional version of Frank-Wolfe optimization as our variational algorithm and study frequentist properties of the iterative boosting updates. Comparisons are drawn to the recent literature on boosting, describing how the choice of the variational family and the discrepancy measure affect both convergence and finite-sample statistical properties of the optimization routine. Specifically, we first demonstrate stochastic boundedness of the boosting iterates with respect to the data generating distribution. We next integrate this within our algorithm to provide an explicit convergence rate, ending with a result on the required number of boosting updates.
Attention-Based Network for Semantic Image Segmentation via Adversarial Learning

As a fundamental research, semantic image segmentation is widely used in the computer vision system. In this paper, we explore the attention mechanism for semantic segmentation to improve the extraction and recovery of information efficiently. Mixed attention modules are designed for the segmentation task, and the attention-based network is the combination by the encoder of Xception and the decoder of residual connections. Experiments are conducted on the PASCAL VOC dataset, and the proposed method outperforms DeepLabV3Plus. In addition, the adversarial training is deployed based on the attention-based segmentation network, and the experimental results show the performance is further advanced with the addition of adversarial learning.
Modulation pattern recognition of M-QAM signals based on convolutional neural network and extreme learning machine

In this paper, we propose a workflow and a deep learning algorithm for recognizing Quadrature amplitude modulation signal(QAM), this design adopts a convolutional neural network (CNN) and Extreme Learning Machine (ELM) as the core，leverage the powerful feature extraction of CNN and fast classification learning of ELM. The spectrogram image features of the signal obtained by short-time Fourier transform (STFT) are input to the CNN-ELM hybrid model, the modulation mode of the QAM signal is finally recognized by ELM. This algorithm surmounts the shortcomings of traditional methods well, Simulation results also verify the superiority of the proposed system whose classification accuracy is beyond 99.86%.
A Nonlinear Master Equation for Open Quantum Systems

A nonlinear master equation is derived, reflecting properly the entropy of open quantum systems. In contrast to linear alternatives, its equilibrium solution is exactly the canonical Gibbs density matrix. The corresponding nonlinear equation for the Wigner function accounts rigorously for the thermo-quantum entropy. It reduces at large friction to the Smoluchowski-Bohm equation in the coordinate subspace, which reflects the stochastic Langevin-Bohm dynamics. The previously derived Maxwell-Heisenberg relation for the nonequilibrium momentum dispersion of quantum Brownian particles is confirmed as well as the related quantum generalization of the classical Einstein law of Brownian motion.
Butson full propelinear codes

Abstract In this paper we study Butson Hadamard matrices, and codes over finite rings coming from these matrices in logarithmic form, called BH-codes. We introduce a new morphism of Butson Hadamard matrices through a generalized Gray map on the matrices in logarithmic form, which is comparable to the morphism given in a recent note of Ó Catháin and Swartz. That is, we show how, if given a Butson Hadamard matrix over the $$k{\mathrm{th}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>k</mml:mi> <mml:mi>th</mml:mi> </mml:mrow> </mml:math> roots of unity, we can construct a larger Butson matrix over the $$\ell \mathrm{th}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>ℓ</mml:mi> <mml:mi>th</mml:mi> </mml:mrow> </mml:math> roots of unity for any $$\ell $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ℓ</mml:mi> </mml:math> dividing k , provided that any prime p dividing k also divides $$\ell $$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ℓ</mml:mi> </mml:math> . We prove that a $${\mathbb {Z}}_{p^s}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>Z</mml:mi> <mml:msup> <mml:mi>p</mml:mi> <mml:mi>s</mml:mi> </mml:msup> </mml:msub> </mml:math> -additive code with p a prime number is isomorphic as a group to a BH-code over $${\mathbb {Z}}_{p^s}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>Z</mml:mi> <mml:msup> <mml:mi>p</mml:mi> <mml:mi>s</mml:mi> </mml:msup> </mml:msub> </mml:math> and the image of this BH-code under the Gray map is a BH-code over $${\mathbb {Z}}_p$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>Z</mml:mi> <mml:mi>p</mml:mi> </mml:msub> </mml:math> (binary Hadamard code for $$p=2$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>p</mml:mi> <mml:mo>=</mml:mo> <mml:mn>2</mml:mn> </mml:mrow> </mml:math> ). Further, we investigate the inherent propelinear structure of these codes (and their images) when the Butson matrix is cocyclic. Some structural properties of these codes are studied and examples are provided.
Higher accuracy and lower complexity: convolutional neural network for multi-organ segmentation

In computed tomography (CT), segmentation of organs-at-risk (OARs) is a key task in formulating the radiation therapy (RT) plan. However, it takes a lot of time to delineate OARs slice by slice in CT scans. The proposal of deep convolutional neural networks makes it possible to effectively segment medical images automatically. In this work, we propose an improved 2D U-Net to segment multiple OARs, aiming to increase accuracy while reducing complexity. Our method replaces vanilla convolutions with Octave Convolution (OctConv) units to reduce memory use and computation cost without accuracy sacrifice. We further plug a ‘Selective Kernel’ (SK) block after the encoder to capture multi-scale information and adaptively recalibrate the learned feature maps with attention mechanism. An in-house dataset is used to evaluate our method, where four chest organs are involved: left lung, right lung, heart, and spinal cord. Compared with the naive U-Net, the proposed method can improve Dice by up to nearly 3% and has fewer float-point operations (FLOPs).
Listening-oriented response generation by exploiting user responses

Although listening to a conversation partner is a key factor in the success of dialogue systems or conversational agents, recent neural conversation systems have no interest in generating listening-oriented responses. In this paper, we propose an end-to-end dialogue system that generates listening-oriented responses, which make users disclose themselves and feel positive emotions. Our model uses ‘self-disclosure’ and ‘positiveness’ as listening features and generate responses in an appropriate manner to the features. Furthermore, the model infers a user response that will be brought out at the end of the dialogue and uses the inferred user response for generating a system response. By utilizing both listening features and user responses, our model becomes capable of generating listening-oriented responses. In quantitative and qualitative experiments, our model turned out to be capable of generating listening-oriented responses that induce users to disclose themselves and talk positively. The results also show that the model utilizing user responses generates more listening-oriented responses than those only using listening features.
Dynamically-Passed Contextual Information Network for Saliency Detection

Nowadays, deep convolutional neural networks (CNNs) have made significant improvement in detecting salient objects by integrating multi-level convolutional features or exploiting the advantage of dilated convolution. However, how to construct finer structure to produce effective features for saliency detection is still a challenging task. In this paper, we propose a novel deep learning based network by dynamically incorporating multi-level feature maps. The proposed Dynamically-passed Contextual Information Network (DCI-Net) can effectively control the information passage process, incorporate multi-scale context information and alleviate the distraction of background noise to improve the performance of saliency detection. Specifically, we first integrate an effective Passage Unit (PU) that progressively incorporates the low-level information with the high-level cues, in order to preserve the boundary details of salient objects. Second, a Spatial Pyramid Dilation (SPD) module is used to enhance the multi-scale feature representation by using multiple convolution dilations to handle the varied size of salient objects. Finally, we apply a Residual Attention module (RA) to further reinforce the saliency detection. Quantitative and qualitative experiments demonstrate the effectiveness of the proposed framework. Our method can significantly improve the performance based on five popular benchmark datasets.
Methods and Techniques of Data Mining

Nowadays, there is an increasing number of applications where artificial intelligence has fuelled the research and development of new methods, techniques, and tools related to knowledge acquisition and data mining. The development of data mining and other related disciplines has benefited from the existence of large volumes of data proceeding from the most diverse sources and domains. KDD process and methods of data mining allows for the discovery of knowledge in data that is hidden to humans, presenting this knowledge under different ways. In this chapter, the relation of data mining with other disciplines is analyzed, an overview of data mining tasks and methods is presented, and also a possible classification of them is given. Finally, a brief discussion on issues associated to the discipline and future research directions are also given.
Educational seismology in Nepali schools: tailored solutions to start a program

&amp;lt;p&amp;gt;Nepal is located above the convergent India-Eurasia plate boundary and has repeatedly experienced devastating earthquakes. During the 2015 magnitude 7.8 Gorkha earthquake, an often-reported experience was that people were not aware of the threatening seismic hazard and have insufficient level of preparedness. An important source of the problem is that earthquake-related topics are not part of the school curriculum. Earthquake education reaching a broad group of the population early in their lives is therefore strongly needed.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We have established an initiative in Nepal to introduce seismology in schools, which relies on two pillars: a low-cost seismic network with stations installed in schools (presented in another session) and educational activities in schools on earthquakes and the related hazards. For classical teaching, we have prepared educational materials adapted to the Nepali school system, labels and language. By using these materials, not only students in the schools but also local people in the community can learn earthquake education and follow guidelines for better preparedness. We also developed educational sessions using Raspberry Shake low-cost seismometers, for example to record earthquake waveforms and to allow learning-by-doing classroom activities.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;For efficient implementation, we have organized a 2-day workshop for the school teachers to prepare them for the new teaching, which was presented by experts in the field and included lots of discussion to find the adapted level. Moreover, during our field visits, we give special lectures and also perform earthquake drills with the students. Well-prepared educational materials such as flyers and stickers are distributed to students, and demonstration tools for physics to schools. All the material from our project is freely available on our program&amp;amp;#8217;s website: http://seismoschoolnp.org.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We have started the program by choosing 22 schools in the region, and establishing direct contact with the teachers, principals and the local communities. We found this was an efficient way to implement the project, especially in rural areas. The preliminary and personal feedbacks reflect that this program is well received. A survey-based evaluation on the program&amp;amp;#8217;s impact on the local community is being carried out, and we plan to present results at the conference. We hope that the project is able to help this region to prepare for future earthquakes, and we seek that the initiative is spread to other regions &amp;amp;#160;to make earthquake-safer communities across Nepal.&amp;lt;/p&amp;gt;
The Fundamental Theorem of Finite Fields: A Proof from First Principles

A mathematics student’s first introduction to the fundamental theorem of finite fields (FTFF) often occurs in an advanced abstract algebra course and invokes the power of Galois theory to prove it. Yet, the combinatorial and algebraic coding theory applications of finite fields can show up early on for students in STEM. To make the FTFF more accessible to students lacking exposure to Galois theory, we provide a proof from algebraic “first principles.”
Deep Relevance Feature Clustering for Discovering Visual Representation of Tourism Destination

Discovering the visual representation(s) of a tourism destination is a challenging problem because it should be highly discriminating and frequently appeared in the travel photos of this destination. To address this issue, we propose a deep relevance feature clustering method (DRFC). To ensure the discrimination, DRFC uses layer-wise relevance propagvel feature maps to locate the region that contributes the most to network prediction. For frequency, DRFC clusters the extracted relevance features in a feature space according to their density, and selects highly dense instances for the visual representation. The experiments 100K photos of 20 tourism destinations show that DRFC can discover the discriminating and frequent visual representation, and outperforms the state-of-the-art methods.