Reviewerly/exHarmony huggingface dataset:
Нейросемантичний підхід до побудови автоматизованих інформаційно- пошукових систем

Currently, one of the actual problems in the formation of the most informative knowledge models of this subject area is the creation of effective information retrieval systems, primarily on the Internet, as the largest repository of information. To extract the necessary information for this subject area from the Internet, processing of a huge number of heterogeneous documents is required. This is the rather complicated task that requires not only automating the process of searching for information, but also ensuring its semantic content in accordance with the current situation in this subject area. To automate the search process and determine the most informative content of the knowledge model of this subject area, a multi-agent intelligent system for searching and selecting information based on neural networks proposed. This system implements a neurosemantic approach to the semantic adaptation of search information to changes in the current situation in this subject area and the corresponding evolution of the knowledge model based on a genetic algorithm.Ref. 9
Time-Domain Multiplexed Two-Dimensional Cluster State for Large-Scale Universal Multi-Input One-Way Quantum Computation

One-way quantum computation is a promising scheme for realizing large-scale quantum computation, where computation is done via measurements on a universal multi-mode entangled resource called cluster state. The capability of this method is determined by the size and the dimension of the cluster state; the size is roughly equivalent to the number of input modes times number of operation steps, while the dimension determines universality and fault tolerance of the computation. To achieve universality, two-dimensional cluster state is required. Among many approaches, time-domain multiplexing using optical system [1, 2] is a promising method where quantum state is encoded in a temporal wave packet. Although universality is still lacking, one-million-mode one-dimensional cluster state has been demonstrated with this approach [3].
The Hybrid Technique for Image Classification to Detect Gender and Age using ANN and SVM

These days look into has investigated to separating helper data from different biometric procedures, for example, fingerprints, confront, iris, palm, voice and so forth. This data contains a few highlights like sexual orientation, age, whiskers, mustache, scars, stature, hair, skin shading, glasses, weight, facial imprints, tattoos and so forth. This data contributes increasingly to ID. The real changes that go over face acknowledgment are to discover age and sexual orientation of the individual. This paper contributes a huge overview of different face acknowledgment systems for finding the age and sexual orientation. The current systems are talked about in light of their exhibitions. Especially, the programmed estimation of age and sexual orientation from confront pictures can be helpful in an extensive variety of scientific applications. The portrayals got from various face locales are expected to Support Vector Machine (SVM) classifiers to evaluate the age and sexual orientation of the individual in the picture. Test investigation demonstrate the great after effects of this component based approach, and its extra advantages when confront pictures are influenced by impediments. As of late, profound neural systems have shown magnificent exhibitions in perceiving the age and sexual orientation on human face pictures. We show an examination exploring these distinctive impacts. In detail, our work looks at four prevalent neural system structures, examines the impact of retraining, assesses the vigor of the considered arrangement pre-handling by means of cross-technique test set swapping and instinctively imagines the model's forecast procedures in given preprocessing conditions utilizing the current Layer-wise Relevance Propagation (LRP) calculation. Our assessments on the testing Audience benchmark demonstrate that reasonable parameter introduction prompts a comprehensive impression of the info, repaying workmanship genuine information portrayals.With a mix of straightforward preprocessing steps, we achieve best in class execution in sex acknowledgment.
Testing the Reasoning Power for NLI Models with Annotated Multi-perspective Entailment Dataset

Natural language inference (NLI) is a challenging task to determine the relationship between a pair of sentences. Existing Neural Network-based (NN-based) models have achieved prominent success. However, rare models are interpretable. In this paper, we propose a Multi-perspective Entailment Category Labeling System (METALs). It consists of three categories, ten sub-categories. We manually annotate 3,368 entailment items. The annotated data is used to explain the recognition ability of four NN-based models at a fine-grained level. The experimental results show that all the models have poor performance in the commonsense reasoning than in other entailment categories. The highest accuracy difference is 13.22%.
IMPROVEMENT OF POETRY WRITING SKILLS BY USING CLUSTERING TECHNIQUE OF CLASS VIII STUDENTS OF SMP NEGERI 3 ALLA, ENREKANG DISTRICT

Abstract&#x0D; This research is a classroom action research which aims to improve poetry writing skills for class VIII students of SMP Negeri 3 Alla through clustering techniques. The subjects of this study were class VIII of State Junior High School 3 Alla who were enrolled in the 2011/2012 school year with 34 subjects. This research was conducted in 2 (two) cycles and each cycle was carried out in four meetings including the final test for each cycle. Data on student learning outcomes were analyzed by using quantitative analysis and data on student activities were analyzed by using qualitative analysis.&#x0D; The results of the study after the implementation of the action for two cycles, namely: (a) Increased poetry writing skills of students of class VIII.1 SMP Negeri 3 Alla after clustering techniques were applied in which in the first cycle obtained an average score of 58.82% in the medium category but have not yet achieved the minimum completeness criteria for writing poetry that is determined and experienced an increase in the second cycle of 73.23% in the high category and has achieved the minimum specified completeness criteria. From the results of this study it can be concluded that the clustering technique can improve poetry writing skills of class VIII students of SMP Negeri 3 Alla, Enrekang Regency.&#x0D; Keyword: Learning Outcomes, Clustering Techniques
Full-surface 3-D reconstruction based on surround structured lighting

In a conventional fringe projection profilometry (FPP) consisted of a camera and a projector, just one-sided 3D data of the tested object can be obtained by a single-shot measurement. Therefore, tools such as turntables are commonly used to obtain 360-degree 3D point cloud data of objects. However, this method requires multiple measurements and point cloud registration, which is time consuming and laborious. With the help of two planar mirrors, this paper proposes an improved system that captures fringe images from three different perspectives including one real camera and two virtual cameras. The information of the planar mirrors (i.e., the mirror calibration) is achieved by artificially attaching the featured pattern to the surface of the mirrors. Using the calibration parameters of the planar mirrors, the 3D point cloud data obtained by the virtual cameras can be converted into the real coordinate system, thereby reconstructing the full-surface 3D point cloud data with relative roughness. Finally, an improved ICP algorithm is introduced to obtain high-precision 360-degree point cloud data. The experimental results demonstrate that with the help of the mirrors, our system can obtain high-quality full-surface 360-degree profile results of the measured object at high speed.
Public interests of society = private interests of authors. Is the possible the balance in the digital age?

The author in the article investigates the issue of the balance of public and private interests in copyright in the digitalage.Private interests of subjects of copyright are based on their exclusive property rights. Such rights are considered as monopoly on the results of creative activity.In conditions of the development of digital technologies, the boundaries of the mo­nopoly are narrowed, because the public interests are taken into account.Public interests need implementation of the right to freedom of information, free access to cultural property, education and science, etc.Society is interested in free access to works, especially for the purpose of studying, scientific research, the use of works with information, personal purpose, etc.Ignoring private interests leads to the limitation of the author's property rights, ig­noring public interests leads to the limitation of constitutional rights and human lib­erties. If the state does not take into account interests, then it leads to a conflict. The main issue of copyright in the digital era: how to prevent such a conflict?It is possible to prevent a conflict due to the norms on the free use of works.In the conditions of the development of the digital environment, the norms on the free use of works are considered to be the most "flexible" in copyright law. Norms are reviewed and adapted to the new conditions for the distribution of works in the digital age. This is a permanent process.Therefore, the settlement of relations can only be considered as a way to achieve balance.The author analyzes in the article the problems of applying the norms of legislation concerning the free use of works and the needs of society in expanding such norms.At the end of the article the author draws conclusions.
Decentralised Binocular Visual Trajectory Tracking Control for Cooperative Dual-Arm System

It is investigated that a common object held by a cooperative dual-arm system is made to perform a trajectory tracking control task in cartesian space under the monitoring of a calibrated binocular vision system. To avoid the drawbacks of the position based visual servoing (PBVS), the image based visual servong (IBVS) is selected to do through transforming the control task in cartesian space to image space. The binocular visual trajectory tracking controller is then designed based on decentralised control strategy, and the system stability is proven by Lyapunov method. Finally, the effectiveness of the proposed method is verified in simulation.
Software Defect Density Analysis

Defect density (DD) is a measure to determine the effectiveness of software processes. DD is defined as the total number of defects divided by the size of the software. Software prediction is an activity of software planning. This study is related to the analysis of attributes of data sets commonly used for building DD prediction models. The data sets of software projects were selected from the International Software Benchmarking Standards Group (ISBSG) Release 2018. The selection criteria were based on attributes such as type of development, development platform, and programming language generation as suggested by the ISBSG. Since a lower size of data set is generated as mentioned criteria are observed, it avoids a good generalization for models. Therefore, in this study, a statistical analysis of data sets was performed with the objective of knowing if they could be pooled instead of using them as separated data sets. Results showed that there was no difference among the DD of new projects nor among the DD of enhancement projects, but there was a difference between the DD of new and enhancement projects. Results suggest that prediction models can separately be constructed for new projects and enhancement projects, but not by pooling new and enhancement ones.
PEMBINAAN PENGELOLAAN KEUANGAN DAN TEKNOLOGI INFORMASI PADA INDUSTRI SNACK DAN COOKIES BATAM

The problems currently faced are financial reports compiled in each period not yet accounting standard, lack of knowledge and understanding of Micro, Small and Medium Enterprises in the preparation of financial reports to produce financial and information technology information, increased production produced by MSMEs and often neglect not recording financial problems related to material expenditure, production process to marketing, so that prices are formed based on estimates only. In fact, most of the chips and processed cake pasters still don't hold financial records properly. The method used in fostering the Snack And Cookies Industry in Batam City will be given, namely the survey method, lecture method, discussion method and training method. The results of the UKM service felt that there was still a need to adjust to the preparation of financial statements with the financial accounting standards of entities without public accountability, to practice daily input of financial data with Ms. Excel in improving the financial performance of SMEs running smoothly.
Testing Assumptions—Does Enhancing Subject Terms Increase Use of Digital Library Content?

In modern library systems, access to the digital content is heavily dependent on effective metadata.The University of Florida (UF) Digital Collections (UFDC) are an actively growing, open access, digital library comprising over 500,000 records.As with any large-scale digital library project, a well-known challenge is the varying quality and quantity of legacy metadata available for each title.Inconsistent metadata makes digitized materials harder to find.If users cannot find the content they are looking for, a great deal of human effort has been wasted and the investment in digital collections is not being realized.Subject terms can be one of the most efficient methods for accessing desired materials, and subject terms created from controlled vocabularies deliver the most consistent results.To date, applying and editing subject metadata has been a record-by-record, labor-intensive process, making the prospect of retrospective projects cost-prohibitive.The UF team is investigating the capacity of research library staff to implement a Machine Assisted Indexing (MAI) system to automate the process of selecting and applying subject terms, based on the use of a rule set combined with controlled vocabularies, to the metadata of a body of already digitized content.To execute the project, the Smathers Libraries team at UF is collaborating with Access Innovations (AI) consultants to implement a machine-assisted indexing system to mitigate the challenges discussed above.
Modeling Statistical Downscaling for Prediction Precipitation Dry Season in Bireuen District Province Aceh

The Asian-Australian monsoon circulation specifically causes the Indonesian region to go through climate changebility that impacts on rainfall variability in different Indonesia’s zone. Local climate conditions such as rainfall data are commonly simulated using GCM time series data. This study tries to model the statistical downscaling of GCM in the form of 7x7 matrix using Support Vector Regression (SVR) for rainfall forecasting during drought in Bireuen Regency, Aceh. The output yields optimal result using certain parameter i.e. C = 0.5, γ = 0.8, d = 1, and ↋= 0.01. The duration of computation during training and testing are ± 45 seconds for linear kernels and ± 2 minutes for polynomials. The correlation degree and RMSE values of GCM and the actually observed data at Gandapura wheather station are 0.672 and 21.106. The RSME value obtained in that region is the lowest compared to the Juli station which is equal to 31,428. However, the Juli station has the highest correlation value that is 0.677. On the other hand, the polynomial kernel has a correlation degree and RMSE value equal to 0.577 and 29,895 respectively. To summary, the best GCM using SVR kernel is the one at Gandapura weather station in consideration of having the lowest RMSE value with a high correlation degree.
Injurious Effects of Hate Speech Acts in The Bluest Eye

This qualitative study aims to investigate the effects of hate speech acts of powerful agencies, which are used to establish and maintain power relations by influencing the psyche of minorities or weaker groups to assign them a subordinate position. In the light of Judith Butler&amp;rsquo;s notions presented in her famous book Excitable Speech (1997) it is found that such acts are used as a lin&amp;shy;guistic weapon in the process of social domination. Hate Speech acts have an injurious effect on the psyche of the weak which prompts them to obey the commands of the speakers, the powerful. For this purpose, relevant excerpts were taken through purposive sampling technique from Toni Morrison&amp;rsquo;s novel, The Bluest Eye (1970), which depicts the tragic conditions of a black family living in a race conscious society of America. They are considered inferior to the white at social, moral, economic and political levels. The analysis of the selected texts is done at both micro and macro levels. At the micro level, the lexical semantic features of the utterances are studied and at the macro level, the socio-political environment in which the black characters are victimized and then psychologically subjectified is discussed. It is seen that the feeling of being ugly has multiple and terrible influences on the mind and body of the subjects. The selected episodes from the novel are the manifestations of their wounded psyche in the white-dominated America. They unconsciously think themselves as agents of darkness, sin, crime, wickedness, immorality and evil. The findings of the study also reveal a taxonomy of newly emerging hate speech acts which may prove useful to analyze the communicative patterns of race-driven societies.
Multi-scale Spatial-Temporal Feature Aggregating for Video Salient Object Segmentation

This paper proposes an algorithm based on supervised deep convolutional neural networks (CNNs), which fully extracts and fuses spatial-temporal information of frames to enhance the video saliency detection performance. Conventional video saliency detection methods that exist some problems (e.g. cumulative miscellaneous information, acquisition of spatial-temporal information separately, time-consuming algorithm, etc.), not only cannot make the spatial-temporal information fully integrated, but cannot meet the real-time requirements. A Multi-scale Spatial Feature Extraction Module (MSFEM) based on deep learning is first designed for simultaneously extracting spatial features at multiple scales. Then, we further fuse the spatial-temporal features of the frames by adopting Multi-scale Spatial-Temporal Feature Refine Module (MSTFRM) to take full advantage of spatial-temporal information in order to achieve high-quality detections with strong spatial-temporal saliency consistency. After that, the network adopts end-to-end network training and testing to avoid unnecessary time overhead caused by pretreatment. To validate the method, we make comprehensive, quantitative evaluations between our method and 8 state-of-the-art techniques. All the results demonstrate our method's advantages in terms of accuracy and reliability.
Developing Online Portal for Vocational High School Based on Geographic Information System (Gis) As the Communication and Information Media

Thisstudyaimsatdevelopinganonlineportal(1)todeliverinformationaboutvocational high schools (VHS) and its expertise programs (2) to convey information about VHS and its supporting data (3) to allow users to share information and communicate with the school. This research employed Research and Development to create VHS online portal based on Geographic Information System (GIS). This study was preceded by the literature study to obtain the data from books, printed media, journals, scientiﬁc articles, government regulations, laws and various electronic media. The result of this study is beneﬁcial to improve the public knowledge towards VHS.
UPAYA MENINGKATKAN KEMAPUAN MENULIS RECOUNT DALAM BAHASA INGGRIS MELALUI PENILAIAN PORTOFOLIO SISWA KELAS VIIID MTsN PITALAH KABUPATEN TANAH DATAR

Based on the ability to write class VIII.D MTsN Pitalah in Sub-English Language Subjects Reveal the meaning in functional written text and simple short monologue in the form of narrative and recount to interact with the surrounding environment it was found that the ability to write students in English subjects is still low. The average ability to write students is still under the KKM. The purpose of this study was to describe and obtain information about efforts to increase the ability to write students in English subjects through a Portfolio learning model in Class VIII.D MTsN, Tanah Datar District. This research is a classroom action research. The research procedures in this study include planning, action, observation and reflection. This study consisted of two cycles with four meetings. The research subjects consisted of 28 students of Class VIII.D MTsN Pitalah. Research data was collected using observation sheets and daily tests. Data were analyzed using percentages. Based on the results of the research and discussion that have been stated, it can be concluded that the Portfolio learning model can increase the ability to write students in English subjects at MTsN Pitalah. The ability to write students from cycle I to cycle II. The ability to write students in the first cycle is 59.62 (Less), increasing to 83.82 (good) with an increase of 24.21.
Phased Bee Colony Optimization Algorithm for Solving Mathematical Function

In this article, we have proposed an efficient Bee Colony Optimization method, namely Phased Bee Colony Optimization (PBCO) technique for solving mathematical functions in a multidimensional space.The search process of the optimization approach is directed towards a region or a hypercube in a multidimensional space to find a global optimum or near global optimum after a predefined number of iterations.The process in the entire search area to another region (new search area) surrounding the optimum value found so far after a few iterations and restarts the search process in the new region.However, the search area of the new region is reduced compared to previous search area.Thus, the search process finding advances and jumps to a new search space (with reduced area space) in several phases until the algorithm is terminated.The PBCO technique has tested on a set of mathematical benchmark functions with number of dimensions up to 100 and compared with several relevant optimizing approaches to evaluate the performance of the algorithm.It has observed that the proposed technique performs either better or similar to the performance of other optimization methods.
Neuronal Networks Simulate Brains

Brains are examples of complex information systems based on neuronal information processing. What distinguishes them from other information systems is their ability to cognition, emotion and consciousness. The term cognition (lat. cognoscere for “to recognize”, “to perceive”, “to know”) is used to describe abilities such as perception, learning, thinking, memory and language. Which synaptic signal processing processes underlie these processes? Which neuronal subsystems are involved?
Security of Cloud Data using Chaotic Mapping a Steganography

Data trade among sender and recipient turns out to be quick and simple.The nature of data operates like sending secret must be taken note.Hiding the data is necessary for securing information.It should be possible utilizing method like Cryptography and Steganography.In this framework the image steganography utilizing secret image and to hide secret image hence RGB image is used to cover.Encryption procedure is done to give a more dependable security.The picture is encrypted based on NCA principle to give more security for secret image we are applying modified a new efficient embedded algorithm using Embedded Least Significant Bits E-LSB.Steganography works space and for integrity checking.We first encrypt the data and then hide it in an image to fulfil our purpose.