Reviewerly/exHarmony huggingface dataset:
Bibliometric Analysis of the International Language Testing Research Through WOS Databases (2000-2020)

Using CiteSpace as the bibliometric analysis method, this paper analyzes the documents of three WOS databases (SSCI, CPCI-SSH and A&HCI) to systematically present the chronological development of the international language testing research during the past two decades.The visualized analyses display the knowledge map, research hotspots, development trajectory, research frontiers, important authors and references in language testing research.The paper provides a panorama of the new changes of language testing research in the past 20 years.
TEACHING EXTENSIVE LISTENING IN EFL CLASSROOM USING WEBSITE WWW.ER-CENTRAL.COM

The COVID 19 pandemic has affected living systems around the world; one of them is in the education system. It has led to the complete closure of schools, universities and colleges around the world. In response to this situation, many schools, universities and colleges are encouraged to use distance learning programs and open education applications and platforms in which schools and teachers can use these platforms to reach students remotely and limit educational interruptions. In this research, the website (www.er-central.com) was used as one of the distance learning programs for extensive listening by EFL students. This research aims to determine whether there is an effect of websites used by English language learners on the global spread of the COVID 19 pandemic. In this research, the reserchers used quantitative research in pre-experimental method design using one group of pre-tests and post-tests.. In pre-experimental research design, the researcher used concept one group Pre-test and Post-test for the third semester in university. The result of the data analysis indicated that there was significant difference of student’ test before and after being taught by using website. It can be said that there is a significant difference of student’s score after the treatment. It means that the website used is effective and can be used as a distance learning program for extensive listening in pandemic situations.
Penggunaan Excel Spreadsheet untuk Penyusunan Laporan Keuagan UMKM Paguyuban Peternak Ayam Banjarejo Magetan

Paguyuban Peternak Ayam Banjarejo as a community service partner faces several problems, such as the lack of resources to prepare financial reports that are in accordance with Financial Accounting Standards for Micro, Small and Medium Entities (FAS MSME); the lack of sufficient skills to start systematic financial records using a computer; and the lack of information about the regulations relating to the preparation of financial reports and tax. Therefore, this community service activity is carried out to provide alternative solutions in overcoming obstacles faced by partners. In addition, this activity introduces the use of the simplest technology, like Excel Spreadsheet in preparing financial reports. This community service activity is expected to be an initiation for Partners to apply more sophisticated technology in preparing their financial reports in the future.
Abstract: Task Fingerprinting for Meta Learning in Biomedical Image Analysis

Shortage of annotated data is one of the greatest bottlenecks related to biomedical image analysis in general, and surgical data science (SDS) in particular. Meta learning studies howlearning systems can increase in efficiency through experience and could thus evolve as an important concept to overcome data sparsity. A core capability of meta learningbased approaches is the identification of similar previous tasks given a new task. We recently addressed this problem and presented the concept of task fingerprinting [1], which involves representing a task (comprising images and labels), by a vector of fixed length irrespective of data set size, types of labels or specific resolutions (Fig. 1).
Pedagogical Aspects of the Ecosystem Approach to Professional Training of Staff for the Digital Transformation of the Region

The article discusses the concept of professional training of future IT teachers as part of the human resources development ecosystem for the digital transformation of the region.The authors argue that school IT teachers are the most important part of human resources necessary for digital transformation at the regional level.To solve the problem of training human resources for the implementation of digital transformation, it is necessary to build a flexible, network, multi-level system for training qualified staff, taking into account regional needs.The research purpose is to define the features of training IT teachers as a part of regional human resources necessary for digital transformation inside the educational ecosystem, to make the training a part of the ecosystem, to determine their mutual influence and possible directions of further development.This purpose is achieved through the following objectives: analyzing the content of the "educational ecosystem" phenomenon in regards to the staff training for the digital transformation of the region, including the innovative training of IT teachers; identifying the components of the ecosystem, training staff for the digital transformation of the region, including the innovative training of IT teachers; developing a number of questionnaires to determine the maturity level of the university as the core of the ecosystem.The research results are used to define the structure of the ecosystem necessary for the human resources development in regards to digital transformation of the region.The authors single out five components to analyze the educational ecosystem of professional training for the digital transformation of the region.The ecosystem for the development of human resources necessary for the region digital transformation has been created in Tula State Lev Tolstoy Pedagogical University.The article presents a set of diagnostic tools for assessing the maturity level of the university as the core of the ecosystem.
Improved Semantic Inpainting Architecture Augmented with a Facial Landmark Detector

This paper presents an augmented method for image completion, particularly for images of human faces by leveraging on deep learning based inpainting techniques. Face completion generally tend to be a daunting task because of the relatively low uniformity of a face attributed to structures like eyes, nose, etc. Here, understanding the top level context is paramount for proper semantic completion. The method presented improves upon existing inpainting techniques that reduce context difference by locating the closest encoding of the damaged image in the latent space of a pre-trained deep generator. However, these existing methods fail to consider key facial structures (eyes, nose, jawline, etc.,) and their respective location to each other. This paper mitigates this by introducing a face landmark detector and a corresponding landmark loss. This landmark loss is added to the construction loss between the damaged and generated image and the adversarial loss of the generative model. The model was trained with the celeb A dataset, tools like pyamg, pillow and the OpenCV library was used for image manipulation and facial landmark detection. There are three main weighted parameters that balance the effect of the three loss functions in this paper, namely context loss, landmark loss and prior loss. Experimental results demonstrate that the added landmark loss attributes to better understanding of top-level context and hence the model can generate more visually appealing in painted images than the existing model.The model obtained average Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PNSR) scores of 0.851 and 33.448 for different orientations of the face and 0.896 and 31.473, respectively, for various types masks.
Machine Learning with Blind Imbalanced Domains

Recently machine learning is used in various applications and has shown success.Machine learning is good at learning the overall characteristics of massive training data.However, for real-world applications, training data often include multiple domains, and some domains have higher importance or risks.In this paper, we first propose a new problem setting: machine learning with blind imbalanced domains.In the proposed problem, the domain assignment of samples is unknown and imbalanced in the training data, and the performance is evaluated for each domain in the test data.Second, we propose an approach for that problem in classification tasks.The proposed approach combines center loss and weighted mini-batch sampling based on distances between samples and centroids in the deep feature space.Experiments on one minor domain and two minor domain settings using three handwritten digit databases (MNIST, EMNIST, and USPS) show that our proposed approach outperforms possible solutions using related methods.Remarkably our approach improves the accuracy in the minor domain by more than 1% on average.Furthermore, it can be inductively estimated that our proposed approach works on multiple domains given the successful results on one and two minor domains.
Implementation of wheelchair controller using mouth and tongue gesture

In this paper, a simple human-machine interface allowing people with severe disabilities to control a motorized wheelchair using mouth and tongue gesture is presented. The development of the proposed system consists of three principal phases: the first phase is mouth detection which performed by using haar cascade to detect the face area and template matching to detect mouth and tongue gestures from the lower face region. The second phase is command extraction; it is carried by determining the mouth and tongue gesture commands according to the detected gesture, the time taken to execute the gestures, and the previous command which is stored in each frame. Finally, the gesture commands are sent to the wheelchair as instruction using the Bluetooth serial port. The hardware used for this project were; laptop with universal serial bus (USB) webcam as a vision-based control unit, Bluetooth module to receive instructions comes from the vision control unit, standard joystick used in case of emergency, joystick emulator which delivers to the control board signals similar to the signals that are usually generated by the standard joystick, and ultrasonic sensors to provide safe navigation. The experimental results showed the success of the proposed control system based on mouth and tongue gestures.
Illocutionary Speech Acts and Moral Values on “Jihadul Muhibbin”: A Pragmatics Study

This research aims to describe the forms of illocutionary speech acts on a novel entitled Jihadul Muhibbin and to explain the moral values on it. This study uses a qualitative descriptive method by doing some steps including taking notes of utterances in the novel and classifying the forms of illocutionary speech acts based on Searle's theory (1969). Searle divides illocutionary speech acts into five types including representative, directive, commissive, expressive, and declarative. In addition, the researcher also tries to identify what moral values are contained in the novel Jihadul Muhibbin. The results showed that the forms of illocutionary speech acts contained in the novel Jihadul Muhibbin have various types including representative (88 occurrences), Commissive (4 occurrences), directive (51 occurrences), expressive (6 occurrences), and declarative (9 occurrences). Furthermore, the moral values contained in the novel Jihadul Muhibbin there are two types including good moral values and bad moral values.
Administrative Employees’ Job Satisfaction in Selected Campuses of (TU) in Kathmandu Valley: An Empirical Study

Job satisfaction is a positive feeling of employees toward their job because unsatisfied employees are quite their job. Satisfied employees are less absent, contribute to the benefit of an organization and stay in the organization. Only happy employees should enhance organizational efficiency and performance. It is a combination of psychological, physiological and environmental circumstance which derives to the person; I am satisfied with my job. It is accepted that individual differences in employee job satisfaction can be measured and managed by an organization. This study was organized to identify the variables influencing job satisfaction of administrative staffs, so the samples were taken from randomly selected campuses, TU in Kathmandu Valley.&#x0D; Primary data were collected from distribution 148 structured questionnaires with six points Likert scale developed in the Job description index (JDI). Only 106 respondents’ opinions were analyzed by the bits of the help of descriptive and inferential statistical tools. The finding showed that satisfied variables are co-workers, supervisors and promotion. The satisfaction level of gender has not found different but different according to age groups.
Dynamic User Activity Prediction using Contextual Service Matching Mechanism

The significance of context-based services is significantly increasing with the advancement of integrated technologies of sensors and ubiquitous technologies.The existing approaches are reviewed to find out that identification of user's activity has more scope of improvement.After reviewing the current literature towards context-based methodologies, it is found that existing methods are devoid of considering dynamic context; while the modelling perspective is mainly towards considering predefined and static contextual information.Further, existing models doesn't have any inclusion of potential belief system nor any incorporation of service matching.Further, practical world case-studies is characterized by complex activity of user while it is quite challenging to extract the accurate contextual information associated with complex user activity.From the practical deployment scenario, the existing system offers less supportability toward collaborative network, which is highly essential to be considered for constraint modelling for user activity detection.Therefore, the proposed manuscript contributes a solution towards existing research problems by introducing a Dynamic User Activity Prediction using Contextual Service Matching Mechanism.A mixed research methodology is used to prove how service matching mechanism is important in contextual service discovery using multimodal activity data.The first contributory solution towards addressing the research problem is by introducing a novel and simplified belief system that considers both static contextual parameters as well as dynamic activity-based contextual parameter.The second contributory solution towards existing problem is to develop a novel service matching module that takes the input from service reposit, user calendar events, and collaborative units for assisting in similarity-based recommendation system.The model considers Hidden Markov Model for activity determination considering states of activity.With a combined usage of user activity context, feature management, and collaborative model, the proposed system offers better granularity in investigating user activity.The experimental and simulation analysis of the proposed outcome shows the enhanced accuracy performance of proposed system under different test environment.The study also investigates the impact of the service matching mechanism as well as relevance feedback on the accuracy to find that the proposed system excels better accuracy.
Summary of the Evolution from “Dialectics of Nature” to “Philosophy of Science and Technology”

Dialectics of Nature has always been an important part of Marxist philosophy, which can not only help people find the essence through phenomena but also explore the objective laws of nature, society and thinking. Philosophy of science and technology is the continuation and result of the development of dialectics of nature, which not only combines materialism but also combines natural laws, human knowledge, science and technology, and so on. It can not only help people find the law of natural and social development, but also find the law of scientific and technological development and new trends so as to promote the harmonious development of socialism. Therefore, the philosophy of science and technology is the inevitable trend and result of the development of dialectics of nature, which should be paid attention to.
Original image noise reconstruction for spatially-varying filtered driving scenes

Test drives for the development of camera-based automotive algorithms like object detection or instance segmentation are very expensive and time-consuming.Therefore, the re-use of existing databases like COCO or Berkeley Deep Drive by intentionally varying the image quality in a post-processing step promises to save time and money, while giving access to novel image quality properties.One possible variation we investigate is the sharpness of the camera system, by applying spatially varying optical blur models as low-pass filters on the image data.Any such operation significantly changes the amount and distribution of noise, a central property of image quality, which in this context is an undesired side-effect.In this article, a novel method is presented to reconstruct the original camera sensor noise for the filtered image.This is different from denoising.The method estimates the original camera sensor noise using the combination of principal component analysis (PCA) and a variance-stabilizing transformation.The noise is then reconstructed for the filtered image with the PCA applied locally on small image sections, and an inverse variance-stabilizing transformation.Although the resulting noise distribution can slightly deviate from the original, this novel method does not introduce any image artifacts as denoising would do.We present the method as applied to synthetic and real driving scenes at different noise levels and discuss the accuracy of the reconstruction visually and with statistical parameters.
Integrated Thematically English Textbook By Using Photo Media For Developing Children's Vocabulary In Early Childhood Education

One of the reasons for the vocabulary weaknesses of children in kindergarten is the lack of textbooks quality. The survey results showed that the vocabulary taught to children can be forgotten after a few days of being given. To solve this problem, the researchers conducted a study to identify and to evaluate the quality of English textbooks used and design textbooks that should be used in TK Aisyiyah Surakarta. This type of research was design-based research Meanwhile, the research procedure was completed using two stages,i.e., the practical problem analysis and the development stages. In the first stage, the results showed that there were strengths and weaknesses to the textbooks that had been used so far. In the second stage, book development was done by maintaining the strengths of the previous book, minimizing or even eliminating the weaknesses, and incorporating new elements initiated by the researchers. These new elements were adapted to the cognitive perspective. This textbook prototype is, of course, also the result of discussions and Focus Group Discussions (FGD) between researchers and teachers and reviews from experts. As a result of the discussion and FGD, this textbook will be ready to be tested in TK Aisyiyah Surakarta.
THE EFFECTIVENESS OF RECIPROCAL TEACHING STRATEGY TO TEACH READING COMPREHENSION IN NARRATIVE TEXT TO THE ELEVENTH-GRADE STUDENTS OF SMAN 1 KUTOREJO

Reading had become one of the essential English skills which should be mastered by students in their English learning. Furthermore, in reading activity, students could enrich their vocabulary, practice their pronunciation which also useful in speaking, writing, even listening skills. However, sometimes students could face some problems which they have experienced when reading those texts, even if they were encountering with reading texts at school. Thus, students needed the teachers’ guidances in their English learning because most of them could be classified as the beginner stage. This research was aimed to measure and investigate the effectiveness of Reciprocal Teaching strategy to teach reading comprehension in narrative text to the eleventh-grade students of SMAN 1 Kutorejo. The researcher had used quasi-experimental research which picked two classes to become the samples from eleventh-grade classes in SMAN 1 Kutorejo by using the purposive sampling technique. Those classes were chosen randomly as the experiment class. One class which would be taught by using Reciprocal Teaching strategy was XI-IPA 1, while the other class, XI-IPA 5 would be taught by using Non Reciprocal Teaching strategy. Furthermore, the researcher had prepared the post-test which contained 50 questions with multiple choice about narrative text reading comprehension for both eleventh-grade classes to collect the data. The data which had been gotten from the post-test were analyzed by using the statistical technique with an independent t-test formula that would show the differences between both classes that have different treatments.&#x0D;
Cultural assets identification using transfer learning

Identifying cultural assets is a challenging task which requires specific expertise.In this paper, a deep learning based solution to identify archaeological objects is proposed.Several additions to the ResNet CNN architecture are introduced which consolidate features from different intermediate layers by applying global pooling operations.Unlike general object recognition, identifying archaeological objects poses new challenges.To meet the special requirements in classifying antiques, a hybrid network architecture is used to learn the characteristics of objects using transfer learning, which includes a classification network and a regression network.With the help of the regression network, the age of objects can be predicted, which improves the overall performance in comparison to manually classifying the age of objects.The proposed scheme is evaluated using a public database of cultural assets and the experimental results demonstrate its significant performance in identifying antique objects.
Program comment generation with improved distributed representation by Seq2seq model using parse tree information

Comments in a program’s source code are important for understanding the program. Understanding the logical flow and overall procedure of the programs is important as the next step especially for beginners learning programming language, and it is inferred that appropriate comments on the source code can support it. In this study, we generate comments for source code using a distributed representation of line dependencies constructed with Word2Vec and using parse tree information obtained from the source code as input. Also, we generate comments not only for each line of source code but also for blocks, which are the logical units of processing.