Reviewerly/exHarmony huggingface dataset:
Implementation of Educational Services Evaluation Application Based on Weighted Product-Alkin as a Digital Library Evaluation Tool

This evaluation application is a desktop computer program that is used by evaluators or library stakeholders to evaluate digital library services at computer colleges. This application was made by using a combination of Weighted Product (WP) method with one of the educational service evaluation models, namely the Alkin model, so the results from determining effectiveness digital library services level are gained optimally and accurately. The main objective of this research was to obtain an overview of the effectiveness level from the implementation of educational services evaluation application based on WP combined with Alkin as a tool to evaluate the digital library effectiveness. This research used the R&D method with the Borg&Gall development model, which focused on the stage of usage trials, final product revision, dissemination, and implementation. The subjects who involved in assessment towards this implementation of evaluation application were 32 people, subjects in usage trials were six people, subjects in product revision were three people, and subjects in dissemination activities were 12 people. The tools used in data collection were in the form of interview guides and questionnaires. The technique of analysis that was used to analyze the collected data was descriptive statistics. The implementation results of the evaluation application showed that the effectiveness level was relatively good.
Generative image inpainting with residual attention learning

Recent deep learning approaches have shown significant improvements in the challenging task of image inpainting. However, these methods may generate blurry output and distorted textures. In this paper, we propose an efficient end-to-end two-stage network for image inpainting. In the coarse stage, we employ residual dense block (RDB) as well as short and long skip connections to fully leverage and exploit features from all convolutional layers and give a globally rough reconstruction. In the refinement stage, we propose a local and global residual network based on channel and spatial attention block (CSAB) to adaptively weigh both channel-wise and spatial-wise features focusing on more meaningful information, and generate a locally fine-detailed image. Experiments on Paris StreetView and DTD textures demonstrate the effectiveness and efficiency of our method. Results show that our method outperforms the baseline techniques quantitatively and qualitatively.
View-Based and Visual-Attention-Based Background Modeling for Detecting Frequently and Infrequently Moving Objects for Video Summarization

The real-time face detection (FD) algorithm is proposed to find faces in the images as well as videos. Besides face regions, this algorithm also finds the exact localities of the face parts like lips and eyes. Initially, skin pixels are extracted centered on the rules of simple quadratic polynomial model. By introducing small modifications, this polynomial model (PM) could be applied for extracting the lips. The merits of adopting these two identical PMs are two-fold. Firstly, computation time is saved. Secondly, these extraction processes could be executed at the same time on one scan of the video or image frame. Subsequent to skin and lips, the eyes are extorted. Later, the algorithm eliminates the falsely extorted parts by validating with rules taken as of the spatial and geometrical relationships (SGR) of face parts. At last, the exact face regions are ascertained accordingly. As per the experiential outcomes, the proposed algorithm evinces preeminent task in respect of accuracy and speed for FD with huge differences in color, size, shape, expressions, and angles.
The freedom of dark web: A digital scrutiny of terrorism on the dark web

The terms Deep Web, Deep Net, Invisible Web, or Dark Web allude to the substance on the World Wide Web that isn’t recorded by standard web indexes. One can depict the Internet as made out of layers: the “upper” layer, or the Surface Web, can without much of a stretch be gotten to by standard quests. Be that as it may, “further” layers, the substance of the Deep Web, have not been filed by customary web crawlers, for example, Google. Michael K. Bergman who composed the fundamental paper on the Deep Web, contrasted looking through the Internet with hauling a net over the outside of the sea: an extraordinary arrangement might be trapped in the net, however there is an abundance of data that is more profound and thusly missed[1]. Truth be told, a large portion of the Web’s data is covered far down on locales, and standard web indexes can’t get to it.
Gadam: Combining Adaptivity with Iterate Averaging Gives Greater Generalisation

We introduce Gadam, which combines Adam and iterate averaging (IA) to significantly improve generalisation performance without sacrificing adaptivity. We argue using high dimensional concentration theorems, that the noise reducing properties of IA are particularly appealing for large deep neural networks trained with small batch sizes. We contrast and compare with popular alternatives, such as the exponentially moving average (EMA), batch size increases or learning rate decreases. Furthermore, under mild conditions adaptive methods enjoy improved pre-asymptotic convergence, hence in finite time we expect this combination to be more effective than SGD + IA. We show that the combination of decoupled weight decay and IA allows for a high effective learning rate in networks with batch normalisation, which exerts additional regularisation. For language tasks (PTB) we show that Gadam is superior to finely tuned SGD, SGD with IA and Adam by a significant margin. For various image classification tasks (CIFAR-10/100, ImageNet-32) Gadam is consistently superior to finely tuned SGD and its partially adaptive variant GadamX outperforms SGD with IA.
A 3D Shrinking-and-Expanding Module with Channel Attention for Efficient Deep Learning-Based Super-Resolution

The 3-dimensional (3D) super-resolution (SR) for medical volumetric data is confirmed to provide better visual results compared to conventional 2-dimensional processing. Then, considering practical applications, we propose a novel convolutional neural network for a 3D SR. Moreover, to reduce model parameters and achieve high precision, we reformulating the standard convolution layer by shrinking the input feature dimension before mapping and expanding back afterward using pointwise convolution. Thus, we utilize channel attention to optimize the network for optimum performance. Although the proposed architecture can be embedded into any 3D model, it performs better while combined with the state-of-the-art model, the 3D residual dense network (RDN). Furthermore, we demonstrate that our proposed method outperforms the state-of-the-art methods in terms of accuracy with only approximately 1/8 parameters and 3/5 times of the standard model, 3D RDN. Consequently, our network is quite suitable in practical situations, such as small training samples, short processing time, and being embedded into chips.
คุณลักษณะอันพึงประสงค์ของผู้บริหารสถานศึกษา ในยุคไทยแลนด์ 4.0 โรงเรียนระดับมัธยมศึกษา สังกัดสำนักงานเขตพื้นที่การศึกษามัธยมศึกษา เขต 1 กรุงเทพมหานคร

The objectives of this study are as follows: 1. to study the desirable characteristics of Thailand 4.0 era school administrators, 2. to study the qualifications of administrators in secondary schools in Thailand 4.0 era. The samples of this study consist of 9 scholars with administrative and Thailand 4.0 economic model experience as well as 400 secondary school administrators and instructors under Secondary Educational Service Area Office 1, Bangkok Metropolitan.  The data was collected by means of oral interviews and questionnaires with 5-Likert rating scales. The statistics employed in this research are frequency, percentage and standard deviation.  The factor analysis is the maximum likelihood method and the content analysis method.            The results of this research indicate that 1. the desirable characteristics of Thailand 4.0 era school administrators under Secondary Educational Service Area Office 1, Bangkok Metropolitan are 1) decision-making skills 2) competence in motivating people 3) responsibility 4) intelligence and competence 5) personality. 2. The variations in the desirable characteristics of school administrators are: 1. decision-making skills with 6 variations, weighing .417-.75. 2.competence in motivating people with 12 variations, weighing .340-.650. 3.responsibility with 9 variations, weighing .367-.668. 4.intelligence and competence with 16 variations, weighing .369-.783. And 5. personality with 9 variations, weighing .458-.630
Feature guidance GAN for high quality image restoration

Here we propose a novel image inpainting model DFG-GAN, which can effectively alleviate the artifacts problem when the missing region area is too large. Unlike other image inpainting models, our model can transfer the image inpainting task into a GAN task when the mask fills the total image. Apart from that, we also take advantage of the extra class label information to tell what kind of the damaged image is. The more information feed in, the better result shall be. Experiments on several publicly available datasets demonstrate the advantage of the proposed method over existing approaches, regarding both visual fidelity and margin texture.
PREDIKSI JUMLAH ACTUAL STOCK PADA PRODUKSI SARUNG TANGAN MENGGUNAKAN METODE FUZZY MAMDANI

To fulfill every consumer demand, the company must ensure that production activities run well. However, continuous production activities, sometimes making the facilities used especially production machines, do not always function properly. Damage to the machine can hamper the production process which results in the amount of production not being met which effecting in unmet amount of production so the production process of goods experiencing delays (downtime). There are uncertainties in downtime and stock requirements so in this case fuzzy is applied to predict the amount of actual stock production. And in this study Fuzzy Mamdani has been able to produce a prediction of Actual Stock
Comparative Study on Patent Eligibility of Artificial Intelligence in the United States, China and Japan

To enhance the possibility of patent entitled of artificial intelligence-related inventions, firstly, patent applicants should concentrate on their construction of the claims to indicate what technical problems the invention are solving or identify the specific improvements made by the claims; secondly, the claims should be narrowly focused and provide technical solutions to technical problems, and each of the technical problems and technical solutions should be described in specification. In order to stimulate the innovation of artificial intelligence-related technologies, many countries have revised the patent examination guidelines in recent years. Patent offices in the United States, China, and Japan are the most important patent offices for artificial patent applications in the world. Japan has the loosest provision on the object. Both China and Japan have authorizations for pure algorithm patents. The United States has the strictest on the object of patent eligibility before 2019, but the newly revised guide has significantly relaxed the scope of the object.
Mobile Augmented Reality Coloring Sheets Development for Dengue Awareness

Many of the tropical and subtropical regions of the world are facing significant socioeconomic concerns. In relation to this they face the spread of dengue fever. From the populations of Southeast Asia and Western Pacific regions, Asia remains disproportionately affected by 75% of the dengue infection. Thus, it has become a major challenge to the public health because of the worldwide spread and the dramatic increase in dengue cases particularly in the Asian region. Even though, action has been taken by the government and community, to combat the diseases through media campaign and other activities, the lack of knowledge such as understanding the life cycle and breeding of a mosquito may result in less effective mosquito control measures. Taking the advantages of augmented reality (AR) technology using marker-based will be able to facilitate the visualization and integration of information by displaying it directly to the user’s view. This study aims to edutain school aged children about the mosquito breeding. The total participants involved in this survey were 86 standard 6 students from public schools. The results show that the scores for all scales in UEQ tools represent a positive evaluation describing a pragmatic quality aspect (efficiency, perspicuity, dependability) with a value of 1.26, hedonic quality (stimulation and novelty) with a value of 1.50 and attractiveness with a value of 1.57. Alpha coefficients are 1.570 for attractiveness, 1.302 for perspicuity, 1.279 for efficiency, 1.186 for dependability, 1.750 for stimulation and 1.244 for novelty. The value of attractiveness and stimulation give the highest scale in the results. This showed that users have found that the overall impression of the application is attractive, exciting and motivate them to use it. This suggested that the use of AR application can assist students understanding because it provides a dynamic visualization to support learning. Thus, able to create awareness in the early prevention of dengue control.
Defining Concepts: The Role of Image Schemas in Object Conceptualisation

Chapter 5 introduced the idea that combinations of image schemas represent the underlying conceptualisations of temporally complex image schemas and simple events. Likewise, Chapter 6 relied on the idea that concepts could be partly defined by their involved image schemas. In this chapter, these ideas are further investigated empirically by presenting an experimental study that investigates the image schemas behind a series of common objects.
Sentiment analysis of customer response of telecommunication operator in Twitter using DCNN-SVM Algorithm

Abstract Along with the development of the times, social media is in great demand by various circles of society because social media allows users to express their thoughts or feelings freely. It is important for a company to know public responses about the product or service offered. With this public response, companies can analyze customer needs and plan more satisfying products or services. To be able to know the sentiments of responses, it is necessary to classify responses. Therefore, in this study used the Deep Convolutional Neural Network (DCNN) method as a feature extraction and Support Vector Machine (SVM) as its classification. The performance results of this research are 63% for accuracy, 63% for precision, and 50% for recall of test data.
Who Am I?: Towards Social Self-Awareness for Intelligent Agents

Most of today's AI technologies are geared towards mastering specific tasks performance through learning from a huge volume of data. However, less attention has still been given to make the AI understand its own purposes or be responsible socially. In this paper, a new model of agent is presented with the capacity to represent itself as a distinct individual with identity, a mind of its own, unique experiences, and social lives. In this way, the agent can interact with its surroundings and other agents seamlessly and meaningfully. A practical framework for developing an agent architecture with this model of self and self-awareness is proposed allowing self to be ascribed to an existing intelligent agent architecture in general to enable its social ability, interactivity, and co-presence with others. Possible applications are discussed with some exemplifying cases based on an implementation of a conversational agent.
Technology of creating an adaptive individual scenario of the graduate student’s educational activity

The article, based on the technology development algorithm, represents the technology of creating an adaptive individual scenario of the graduate student’s educational activity. The components of adaptive technology have been identified: conceptual, content, procedural-adaptive, resulting. The focus is on the fact that the technology is based on an adaptive approach, the main provisions of which are the concept of directed self-organization, mutual harmonization of diverse impacts on a dialogic basis, self-development, which helps to achieve a common goal in view of external environment requirements and the balance of interests of educational process participants.The step-by-step strategy of the adaptive educational activity of a graduate student includes a detailed plan of action for the period of training and is implemented through a set of multilevel specific tools, the components of which are given in the article. Furthermore, there have been identified the basic ways of organizing the adaptive activity of graduate students and teachers (technologies, methods, techniques, forms), which are carried out in stages of learning.
3D Virtual Catalogue Of PENS Campus Using Augmented Reality

PENS is a vocational education campus that is actively promoting the community to capture the interests of prospective students to register as students. This requires promotion of media innovation that can attract public interest. Multimedia technology, especially augmented reality can be used as an attractive alternative media for PENS to carry out promotions. This study aims to develop promotional media in the form of an augmented reality technology-based virtual catalog to introduce various study programs available in PENS. Catalogs that are generally in the form of physical media are converted into markers that can bring up 3D objects and videos that explain the contents to the user so that the user does not need to read because there is already an audio visual explanatory facility. The trial results show that the PENS virtual catalog can function well in viewing AR mascot, AR video and information.
Научная библиотека в региональной системе профессионального образования

The regional system of professional education has rightly one of the prior places in the structure of its basic socio-economic processes, responding to the outward environment influence (socio-cultural, economic, legislative and other changes), and, in its turn, having retaliatory impact on it. In the structure of the scientific-educational complex of Siberia Novosibirsk plays the leading role. Here function higher educational establishments, which execute specialists» training, retraining and qualification upgrading, as well as scientific-research institutions of the Novosibirsk scientific center of the Siberian Branch of the Russian academy of sciences and institutions of other departments. All higher educational establishments of the city and a greater part of scientific-research institutions have libraries in their structure. Since the vital problem of today is forming the united system of providing regional educational and scientific institutions with information resources necessary for successful scientific-educational activities, the subject of this article authors» research interests is the «proper» and real place of the library socio-cultural institutions in this structure. State Public Scientific Technological Library of the Siberian Branch of the Russian Academy of Sciences (SPSTL SB RAS) is the largest library of the regional scientific-educational complex. Providing the users» access to information resources is the main direction of the Library activity. At the same time, having the license for educational activity, SPSTL SB RAS is itself the subject of the educational space: it organizes courses of librarians» retraining and qualification upgrading, cooperates with higher educational establishments of the type in training students. Being the scientific-research institution SPSTL SB RAS has its post-graduate studentship on training scientific specialists of the highest qualification in the research areas «Library, bibliography and book science». The dialectic approach, permitting to view library-information and educational spheres of the large scientific library activity in their unity and interconditionality, was the common methodological basis for the research undertaken. The article substantiates the role and place of SPSTL SB RAS in forming the modern regional system of professional education, outlines perspectives for creating the reciprocity model of libraries for the scientific-education complex as a whole and integration and diversification of information supply for the sphere and discipline discourse.
Modeling the relationships between changes in EEG features and subjective quality of HDR images

Quality of experience (QoE) is a human-centric paradigm, which produces the blueprint of human-behavioral-states such as perception, emotion, cognition, and expectation. Recent advances in neurophysiological monitoring tools have facilitated the study of frequency, time, and location of neuronal activity to an unprecedented degree, as well as opened doors to a better understanding of human overall behavioral systems. Physiological signals, such as the electroencephalogram (EEG), have shown promise in revealing the subject&apos;s emotion or attention in quality assessment and the correlation of this with media service quality. This chapter proposes a novel objective QoE model for high dynamic range (HDR) images and is based on the relationship between objective (i.e. delta-beta coupling) and subjective measures (i.e. mean opinion score MOS). The analysis of the results indicate that the proposed QoE model has a strong correlation with MOS scores, hence can be effectively used in predicting the overall HDR image quality. An advantage of the model is that it is lightweight and it provides a measure of user-perceived quality, but without requiring time-consuming subjective tests. The model has potential applications in several other areas, including QoE control and optimization. Future mobile providers can benefit from applying the proposed QoE-based model to optimize users&apos; acceptability and satisfaction for different HDR image scenarios.
Research on University Experiment Immersive Teaching Model Based on Virtual Reality

Virtual reality has attracted more and more attention due to its advantages of immersive and interactive, these advantages provide a new and effective teaching method for educators. In order to effectively solve the problems existing in university experiments and promote university experimental teaching, virtual reality provides an effective way. This paper aims to apply virtual reality to the teaching of university experiments, and university experiment immersive teaching model is proposed based on virtual reality, which stimulates students' interest in active learning and improves learning effect. And it also lays a certain theoretical foundation for the application and popularization of virtual reality technology in future education.