Reviewerly/exHarmony huggingface dataset:
Matching Node Embeddings Using Valid Assignment Kernels

Graph kernels have proven to be a promising approach for tackling the graph similarity and learning tasks at the same time. Most graph kernels are instances of the R-convolution framework. These kernels decompose graphs into their substructures and sum over all pairs of these substructures. A more promising family of kernels are the assignment kernels, which compute a matching between substructures of two objects such that the total similarity between the matched substructures is maximum. In this paper, we present a kernel which compares graphs by computing an assignment of their node embeddings. After embedding the vertices of all graphs in a vector space, we construct a hierarchy of the vertices using a clustering algorithm. Based on this hierarchy, we define a kernel that computes an optimal assignment of the vertices of two graphs. The proposed kernel is evaluated on several graph classification datasets. Our results indicate that the proposed approach is competitive with traditional and state-of-the-art techniques.
Concept of Risk-Management of International Tour Operator on the Base of Fuzzy Cognitive Model

The article proposes a concept for developing an integrated system of typical fuzzy models for a total assessment of the level of acceptable tour operator risk based on expert opinions regarding internal and external factors of influence. The article proposes a concept for developing an integrated system of typical fuzzy models for a total assessment of the level of acceptable tour operator risk based on expert opinions regarding internal and external influences.
Video Super-Resolution using Multi-Frames Fusion and Perceptual Loss

Abstract Video super-resolution (VSR) has become more and more important in vision perception. Currently, most of video super-resolution methods used optical flow estimation by explicit motion compensation. We proposed a new network using multi-frames as input without motion compensation. In order to improve the performance of the reconstructed high-resolution (HR) frame, perceptual loss function is used to evaluate the deviation between the prediction and ground truth. Perceptual loss characteristic is able to improve the quality of image reconstruction on the vision, but with a low Peak Signal to Noise Ratio (PSNR). Experimental results show that compared with other methods, our model can recover more details in high-resolution image, although it does not get higher PSNR value.
Sistem Pengelompokan Jenis Kaleng Bekas Berdasarkan Model Warna CMYK

Resti Y, Burlian F, Fusito F, Yani I. 2019. Grouping system of the used cans type based on CMYK color model. In : Herlinda S et al. ( Eds .), Prosiding Seminar Nasional Lahan Suboptimal 2019, Palembang 4-5 September 2019. pp. 338-344. Palembang: Unsri Press The automatic sorting process in the recycling industry requires a grouping system. This research aims to build a  grouping system of used cans into three types; aluminum, tin plate and aerosols. The grouping is done based on the Cyan, Magenta, Yellow, and BLacK (CMYK) color models of the image of the used cans which are captured using a digital camera when placed on a conveyor belt. The grouping method used is a statistical method based on the Bayes theorem and the assumption of independence on the input variables. The results obtained show that the Naive Bayes method is able to group used cans by type with an accuracy rate greater than 82%. Keywords: accuracy rate, digital images, naive bayes
Topological Principles of Cognitive Image Generation

The paper presents a new topological principles for generating images of multi-dimensional data for monitoring the behavior of complex systems by means of cognitive computer graphics. These images provide the selection of fundamentally new integral characteristics of complex systems based on visualization and objectification of topological invariants in the multidimensional space of parameters of complex systems. Fundamentally new algorithmic approaches to the representation of cognitive images of multidimensional data in the form of objective 3D images are proposed.
Determining Static Mount Accuracy with a Mid-Range Eye Tracker

Technological advances and decreases in cost have allowed eye trackers to become available to a wider range of industries. This research sought to examine the accuracy of a mid-range eye tracker while viewing small and large targets on two static mounts. Total dwell time was collected for 16 participants with the tripod-mount and laptop-mount. The results indicated that the size of the target significantly affects the accuracy, however the type of mount did not affect the accuracy. The findings indicate that either mount type can be used as long as defined Areas of Interest (AOI) are large enough for successful detection.
دراسة كفاءة وسائل الاختبار باستخدام طريقة Cg/Cgk و طريقةGRR .

The laboratories located in the scientific, industrial and inter-disciplinary institutions are of great importance. They always strive to produce accurate and accurate results and to prove the accuracy of their results and to monitor the quality of the product so that these products comply with the standards set, Production and quality, the lack of full implementation of quality systems within laboratories is one of the main reasons for obtaining inaccurate results. This study presents a study on the efficiency of the means of testing using quality testing methods and tools to determine whether the test method is valid for a particular test function. The product quality is determined by the test method.  The efficiency of the testing process is determined by examining the efficiency of the testing and measurement processes and analyzing the measurement systems according to standard methods, including the C g / C gk method and the GRR method. إن المختبرات القائمة في المؤسسات العلمية والصناعية والبينية لها أهمية كبرى ، فهي تسعى دائما لإعطاء نتائج صحيحة و دقيقة ،وإلى إثبات مستوى الدقة التي تتميز بها نتائجها، كما أنها تعمل على مراقبة جودة المنتج بحيث تتوافق هذه المنتجات مع المواصفات القياسية الموضوعة ، مما يؤدي إلى تطوير تقنيات الإنتاج والجودة ، فعدم التطبيق الكامل لأنظمة الجودة داخل المختبرات يعد من أهم الأسباب التي تؤدي للحصول على نتائج غير دقيقة. يقدم هذا البحث دراسة فيما يخص كفاءة وسائل الاختبار باستخدام طرائق و أدوات اختبار الجودة ، بحيث تعطي قرارا فيما إذا كانت وسيلة الاختبار صالحة من أجل وظيفة اختبار معينة ، فجودة المنتج تتحدد بشكل مقرر من خلال وسيلة الاختبار. ويتم تحديد كفاءة عملية الاختبار من خلال دراسة كفاءة عمليات الاختبار والقياس وتحليل أنظمة القياس وفق طرق معيارية منها طريقة C g /C gk و طريقة GRR .
Impact of the MOOC Learn to Learn, in high school students of the UAEH

In accordance with the constructivist model, it is importance to identify opinions of the users about of the materials that support them in their process of learning to learn, since it is not a passive form of learning. In this paper, the results of the MOOC Assessment Learn to Learn are presented, using the empirical observation method, the survey was formulated taking into account pedagogical technical aspects with a Liker scale format, besides proportional average to know the impact of the questions evaluated on the aspects of interest.
Estimasi Tujuan Penumpang Menggunakan Predictive Model dengan Data Smart Card

Bus Rapid Transit (BRT) is one of the main choices of public transportation that supports mobility of Jakarta community. As one of the main choices of public transportation, BRT should provide good service and always improve its performance. Needs for moving or mobility will cause a problem if the moving itself is heading at the same area and at the same time. That will cause some problems which are often faced in urban areas such as traffic and delay. To overcome those problems there needs to be a strategy to build good public transportation planning, besides need to know individual travel patterns to overcome problems and improve BRT service. In case to realize those plans needs to be built origin-destination (O-D) matrix. O-D matrix is a matrix that each cell is an amount of trip from the source(row) to the destination (column). O-D matrix is beneficial for analysis, design and public transportation management. O-D matrix also provides useful information like amount of trip between 2 different locations, that can be utilized as fundamental information for decision making for three levels of strategic management (long term planning), tactic (service adjustment and network development), and operational (scheduling, passenger statistic, and performance indicator). To build O-D matrix is required a predictive model that can be measured to predict passenger destination. The predictive model will be build using classification algorithms such as Decision Tree and K-Nearest Neighbor (KNN).
Parameter Selection of Differential Evolution by another Differential Evolution Algorithm

The performance of differential evolution (DE) highly depends on its control parameters, especially for the first proposed simple or standard DE. Control parameters suitable for one objective function are generally not beneficial to another. To automatically find out optimal control parameter settings for different objective functions, we propose a novel technique, parameter selection of DE by another DE algorithm. The conventional DE is one-level DE with various mutation and crossover schemes, and even with different restart mechanisms, and thus our proposed DE can be called a two-level DE algorithm or simply called a two-level algorithm. Experimental results show that our proposed two-level DE can easily find out the true minimum values of four benchmark functions even under different hyperparameters.
Mining Aspects in Online Comments with Attention and Bi-LSTM

With the rapid development of e-commerce platforms, a large number of commodity comments have emerged on the Internet. Comments not only provide consumers with the experience of others, but also make it easier for companies to get feedback from users. This paper is motivated from this background to derive deep learning methods on effective aspect mining in comments. Classically, a product comment involves different aspects of a product, therefore aspect mining on product comments is supposed to be a multi-label classification. This paper proposes a bi-directional LSTM aspect mining algorithm combined with the Attention mechanism. In order to further improve the precision of classification, the CRF model is introduced at the final step, and the output of the bi-directional LSTM is optimized by the joint conditional probability of the words in the comments. The performances of this algorithm (BLCA) is tested by exploring the real comment data repository from the e-commerce platforms. The experimental results show the priority of BLCA over other algorithms as LSTM or RNN.
Automated Creation of Knowledge Bases for Intelligent Systems, taking into account Linguistic Uncertainty

In the process of designing ontological knowledge bases, developers are faced with the presence of contradictions and/or redundancy in the data, which can affect the accuracy and interpretability. The development and richness of information resources leads to linguistic uncertainty and complicates the interpretability and application of systems based on knowledge in man-machine environments. Different sources of information include some inconsistencies and/or redundancies. The paper presents the methodology for designing thematic knowledge bases in the form of scenarios. In order to reduce linguistic uncertainty, knowledge of experts other than knowledge extracted from information resources is taken into account.
Authenticity of Language Practices in Virtual Learning Sites

In this chapter, the focus lies on language practices on virtual learning sites. A questionnaire sent to students on net-based courses in English demonstrated that the informants still had a conservative view of norms in the English language, in that they aimed to have native speaker-like proficiency. They reported that English as a lingua franca was relevant for communication with other non-native speakers in informal situations; however, education in particular was seen as a preserve of native-speaker norms. The informants saw English as a lingua franca as a performance variety that they wanted to learn alongside native varieties. However, textchat data of actual language practices demonstrated that users of English can develop their own norms through interaction with other non-native speakers. The conclusion of these studies is that, even though they may still report that they want to be like native speakers, they do develop their own language practices in the process of interacting with others. This entails that they have a much freer practical view of what is authentic language than their reported attitudes suggest, and I propose that this is due to them using the language on a virtual learning site. Thus, virtual learning sites are environments where, consciously or unconsciously, new non-standard linguistic practices can be developed.
Disablist hate speech laws

This chapter discusses the ways disability may be recognized in hate speech legislation. There are many international treaties and agreements which are designed to protect and promote human rights, and which could be used to address hate speech. The chapter highlights how arrangements might be used to deal with disability hate speech, using United Nations treaties and the European Union as examples. It describes the legislative approaches adopted at a national level by seven countries: Poland, United Kingdom, United States, China, India, South Africa, and Canada, in terms of the regulation of hate speech. At the most basic level, it could be argued that hate speech is inconsistent with the Universal Declaration of Human Rights, since hate speech denies the inherent dignity and humanity of its victims. There are nine United Nations treaties which could be seen as limiting at least some forms of the human rights abuses involved in hate speech.
Moral dimension of scientific knowledge in the conditions of formation of a new industrial society

The purpose of this article is to research the problem of the relationship between science and moral in the new industrial society. The main result of the research can be expressed in a number of the following theses. The functioning and interaction of science and moral depends on the existing social conditions. Accordingly, the relationship between science and moral must be considered specifically historically. In the early stages of becoming a social institution, modern science was an ethically neutral form of culture. Approximately from the late 19th – early 20th centuries, the situation gradually changed in the direction of increasing the moral component of scientific knowledge. The emerging industrial society of the second generation predetermines the dominance of the significance of moral issues in all spheres, including the sphere of science. The reason for such dominance is the inability to control technological processes completely, as well as the ever-increasing interference with the surrounding nature and human nature.
Use of Choice Reviews to Build the Geosciences Collection

Objective. The Nazarbayev University School of Mining and Geosciences was established in 2016 to study and conduct research on the vast mineral reserves of the country. The school now has three bachelor’s programs, two master’s programs and the recently launched PhD program. The purpose of the study is to determine how many subjects from Choice Reviews are already part of the collection, and how many the library needs to buy to create a good geological collection. Methods. Introducing new programs, it is important to identify the academic and additional resources that will need to be offered during training. In 2018, the library acquired Choice Reviews Online to help the subject librarians create good discipline-oriented collection. Results. According to the survey, only 12.5% of the list is part of an existing print collection, and 87.5% should be added as a potential collection of mining and geology sciences. The analysis of e-book collection is as follows: 55% of the list is already part of this collection, and 45% of the library is required to be purchased when developing an e-book collection. Conclusions. The university has only just begun to develop the field of mining and geology, so there is still time to expand the library's collection of these disciplines. Subject librarians are interested in adding important titles from standardized Choice Reviews tools; as well, they should review and identify various resources that are relevant to the promotion of research to acquire them.
Identifying duplicated ads on property selling and renting websites

Abstract The article presents a solution for the problem of identifying duplicated ads on property selling websites. This task is formulated in the form of a classification problem: the input parameters are identified then divided into basic and non-basic, as well as a class-forming feature. It is also necessary to consider the preliminary data of processed property objects, which is necessary for proper application of the classification methods. The following is a brief review of chosen modern algorithms for solving classification problems, namely: decision trees, artificial neural networks, logistic regression. As a result of experiments, it was revealed that Artificial neural network gives the most accurate result therefore, this algorithm is suitable for the solution of the stated problem.
An Association-Based Intrinsic Quality Index for Healthcare Dataset Ranking

As the number and source of health-related datasets continue to grow significantly, identification of datasets that are most appropriate for a research question is becoming ever more important for the field of health data analytics. The complexity of health-related data further exacerbates the challenge in dataset identification as it requires significant efforts to understand a dataset before recognizing its appropriateness and quality to the research purpose. While the appropriateness of a dataset is largely a function of data semantics and research questions, we hypothesize that the quality of the dataset can be assessed by some intrinsic properties of the features in the dataset, and these properties are common across all datasets. Moreover, we believe that a good understanding of the usefulness of features in datasets is not only important to data analysts but also to data providers because it will help them improve the design and acquisition of datasets in the future. In this study, we propose one way of measuring the intrinsic quality of healthcare datasets that is based on the degree of association among attributes (features and outcomes) in a dataset, which we call the Association-based intrinsic Quality Index (AQI). In this article, we describe the design of the AQI and discuss its properties. We demonstrate the utility of the AQI by a user study and results from two pairs of real healthcare datasets. We believe that the AQI can help assess the intrinsic quality of healthcare datasets and thus provide an important metric to assist dataset identification for researchers as well as a perspective for identifying and examining the design of the most valuable healthcare datasets so that features of these datasets can inform future designs. Furthermore, we argue that the AQI can also help researchers discover research opportunities within a given dataset.
Mobile Phone Anti-theft Method Based on Mobile Track and User Characteristic

The cell phones are becoming more common and turn into a part of our life. While being convenient to use, the users are exposed to take the risk of privacy leakage due to a large amount of private information is stored on their cell phones. This paper proposes an anti-theft method based on motion trajectory and user features, which can alarm the theft in the process, and curb the theft in the initial stage. We uses the cellphone attitude detection algorithm in human coordinate system to conrm phone status, and proposed to calculate the motion trajectory based on Iterative Kalman Filter Inertial Navigation Algorithm. By the trajectory of the phone as it takes out and the features contained in the movement, a warning will be given when thefts are taking place. We evaluate the main modules of our method through a large number of experiments. Results show that the overall accuracy of the system can reach more than 90.33%.
The dynamic range of aspheric surfaces by non-null interferometry

In order to make the plan of aspheric surface testing more convenient and efficient, the dynamic range of aspheric surface by the non-null interferometry was studied. The rule of maximum dynamic range of aspheric surface by the non-null interferometry is: the fringes of the densest zone is not only at the margins of the pattern, but also in some middle one general zone, and can be distinguished all at the same time. Based on the aberration theory, an expression about dynamic range was deduced, which was an intuitive and accurate judging criterion. An example was made to verify the theory of dynamic range; and it is also proved that the retrace error can increase the dynamic range slightly by simulation.
Helping an Agent Reach a Different Goal by Action Transfer in Reinforcement Learning

Reinforcement learning agents can be helped by the knowledge transferred from experienced agents. This paper studies the problem of how an experienced agent helps another agent learn when they have different learning goals by action transfer. This problem is motivated by the widely existing situations where agents have different learning goals and only action transfer is available to agents. To tackle the problem, we propose an approach to facilitate the transfer of actions that are right to a learning agent’s goal. Experimental results show the effectiveness of the proposed approach in transferring right actions to an agent and helping the agent learn to reach a different goal.
A Novel Approach for Color Image Denoising using Geometrical Pixel Location Encoding and Decoding Technique

This paper proposed a novel denoising algorithm with a geometrical pixel location. This developed novel denoising algorithm and discussed with reference to the geometrical pixel encoding Process. Many denoising techniques are implemented with high accuracy. Once the image filtered, further improvement in noise improvement is not possible. First, an image is filtered with any denoise technique, then image pixel locations are encoded with defined geometric positions for this encoding technique again filtered with same denoise technique applied earlier. After completion of the denoise process image decoded with original geometric locations. The proposed algorithm is tested with standard denoise techniques. The experimental results show the robustness in upgrading PSNR, SSIM.
Null Referring Expressions

Chapter 6 applies the relevance-based account of referring expressions to the phenomenon of null subjects in non-pro-drop languages. So-called diary-style nulls, it is argued, are ultimately driven by the interaction of effects and effort and therefore by the speaker’s aim of achieving optimal relevance. Three broad categories of null subject use in English are identified: an informal null subject where the omission leads to extra cognitive effects, a pressurized null subject where the speaker’s abilities are the crucial factor, and finally, an ostensively vague null subject, which is driven by the speaker’s preferences. These three categories are not presented as an exhaustive taxonomy of English null subjects, or as theoretically distinct. Rather they emerge as a result of a speaker aiming at optimal relevance in different discourse contexts, and they represent occasions where different elements in the overall equation of optimal relevance drive lexical omissions.