Reviewerly/exHarmony huggingface dataset:
PENYISIPAN PESAN KE DALAM FILE VIDEO MENERAPKAN METODE CHINESE REMAINDER THEOREM

Nowadays the use of information technology as a medium of information exchange is developing very widely. Various types of information such as text, images, sound and video can be converted into digital media that allows it to be reproduced or transmitted through various media. One of them is the internet, through the internet we can easily exchange information with other people in various places. However, there are times when information / messages are confidential, where no other party may know the contents of this information other than the sender and recipient. Then we need a security for the message. Steganography is a technique and art for inserting messages or information in a media, such as text, images, audio or video that aims to avoid suspicion from people who are not entitled. Therefore required a software that can insert or hide confidential information on a media that is video. But in doing the insertion of messages on the video using steganography alone is not necessarily safe, so we need a useful method to improve security because it requires the Chinese Remainder Theorem method. The research objective is to apply the Chinese Remainder Theorem method to insert text messages into video files. This is necessary because it often happens that the text message sent is a secret message that should not be known to just anyone. Chinese Remainder Theorem is a useful method for providing benefits in terms of increased security and low computational complexity.Keywords: Security, Steganography, Video, Chinese remainder Theorem
PERSONALITY VALUES’ BECOMING IN EDUCATIONAL PROCESS: TECHNOLOGY AND EXPERIENCE

An analysis of the studies presented in this collective monograph allows us to state that personality formation throughout the entire period of the historical development of mankind is an topical psychological and sociocultural problem.The article deals with the personality capacities development in a modern educational system. In the work the authors reveal the ways, mechanisms and their effects in the formation of values of the student youth through the study of psychology using interactive teaching methods with the application of psychotechnologies. The development of gender-related training courses in work with young people are highlighted.The actual problem of adult education is reflected, which highlights the issues of psychological accompaniment of adult students’ educational activities. The publication reveals some aspects of the life of a person and a group of minors in penitentiary systems, which, to a certain extent, can act as a reduced model of a congruent society. The study also examines the socio-psychological problem of domestic violence against a child.
Dialogue as a technology for initiating sense-formation in the practice of the educational process of higher education

The analysis of modern psychological and pedagogical studies of dialogue as a technology for initiating meaning in the educational process of higher education, as well as the psychological components of dialogue, its didactic content in the meaning of students. Moreover, the dialogue functions in the process of the created semantic field, which forms the intentional, value-semantic, affective components of the student’s personality, which allows us to consider dialogue as a true source of actualization of personal potentials in the educational process. Semantic didactics gives a metaphorical definition of dialogue as a “tool of thinking”, which encourages the search for psychological characteristics, patterns as the basic foundations of meaning formation that arise in a situation of revealing meaning. The analysis of theoretical studies of the dialogue problem as a meaning-generating technology resulted in the conceptualization of dialogue types in the practice of the educational process, taking into account the didactic tools of pedagogical communication, which in turn makes it possible to form innovative categories in the psychological and pedagogical direction - semantic didactics.
Joint Topological and Polarization Entanglement in Quantum Photonics Information Processing

New linear-optical photonic quantum walks are used to jointly entangle polarization and winding number. This joint entanglement allows polarization entanglement-based quantum information processing tasks to be performed with high degree of errors resistance.
REGENERATION OF POST-WAR HOUSING ESTATES AND THE USE OF AGENT-BASED MODELLING

Large housing estates are inseparable elements of the landscape of every Central European city and, although the predicted formation of enclaves of poverty and social exclusion has not materialised, their future does not look bright.The first post-war housing estates are inevitably approaching the end of their intended life span and, unfortunately, thus far a method to extensively test and monitor these housing estates has not yet been established.Currently, attention is focused purely on analysing the technical condition of the buildings, while the most important issue, that is, their present and future residents, is ignored.Collecting the necessary data on large residential estates is the first, extremely important step towards understanding the processes taking place in European cities. Thanks to agentbased modelling, which utilises both the decision-making and the uniqueness of individuals and households, a detailed analysis of bottom-up processes that occur naturally in the local community is possible.Using one of the Polish housing estates, Popowice in Wrocław, as an example, available statistical data was systematised and simulations were carried out to predict the natural, spontaneous development of the estate.The simulations reflect the dynamics of the bottom-up processes within the local population that have a direct impact on the scale of migration, as well as the socio-demographic polarization of the local community.Intentionally, the top-down approach has not been implemented in order to allow identification and analysis of self-modifying changes.In this simulation, trends are sought only based on the autonomy of individual people.The need to make a precise diagnosis and establish guidelines for revitalization plays a key role in the management of urban space.Strengthening the desirable, and limiting the negative processes can play a crucial role in the guideline-setting process, ultimately enabling an optimal model for the revitalization of large housing estates to be created.
High resolution stratigraphy using well logs to identify turbidite stages in the Massapê oil field, Recôncavo Basin, Brazil

The integration of rock and well logs data is fundamental for the interpretation of depositional systems and sequences, a fundamental support for E&P activities.This approach was applied on the low permeability turbidite sandstones and slurries of the Maracangalha Formation, in the Massapê Oil/Gas Field, Recôncavo Basin.Well-log interpretation allowed the recognition of 23 turbidite stages, and four main facies, all observed in each one of these stages: (a) fine to medium sandstones, with porosities greater than 9%, being the best reservoirs; (b) silty to very fine sandstone slurry facies, that corresponds to very muddy reservoirs with porosities less than 9%, forming important permeability barriers; (c) siltstones and (d) shale.Turbidite stages appear in the Gamma Rays logs (GR) with funnel, block and serrated log motif patterns, corresponding to dominantly thinning and fining upward signatures, recognized in several wells in the Massapê Field.The detailed correlation of these well-logs showed that these stages are present in the whole field.The mapping of the 3rd and 4th order turbiditic stages, considering the correlation of their four facies, will allow a better location of wells, resulting in a more efficient exploration and production development, capable of increasing the recovery of important oil reserves that still exist in the area, optimizing costs and giving greater robustness to E&P processes.
Setting Up a Basic Cloud Cluster

At this point, we have a simple cloud application which works on a single server. While it is nice that we can put this on a server that we built just by pointing and clicking, this doesn’t take full advantage of the cloud. One of the goals of the cloud is to create an application cluster—a set of servers that work together to solve the problem, where the computing power can be expanded and contracted as needed.
Efficient training and inference in highly temporal activity recognition

High-performance Activity Recognition models from video data are difficult to train and deploy efficiently. We measure efficiency in performance, model size, and run-time; during training and inference. Researchers have demonstrated that 3D convolutions capture the space-time dynamics well [13]. The challenge is that 3D convolutions are computationally intensive. [8] Propose the Temporal Shift Module (TSM) for train-efficiency, and [5] proposes DeepCompression for inference-efficiency. TSM is a simple yet effective way to gain near 3D convolution performance at 2D convolution computation cost. We apply these efficiency techniques to a newly labeled activity recognition data set through transfer learning. Our labeling strategy is meant to create highly temporal activity. We benchmark against a 2D ResNet50 backbone trained on individual frames, and a multilayer 3DCNN on multi-frame short videos. Our contributions are: 1. A new highly temporal activity recognition dataset based on egoHands [1]. 2. results that show a 3D backbone on videos outperforms a 2D one on frames. 3. With TSM we achieve 5x train efficiency in run-time with negligible performance loss. 4. With Quantization alone we achieve 10x inference efficiency in model size with negligible performance loss.
Adapting Scoring Based Classification to Simplify and Automate Phenotype Creation for Cohort Identification in Clinical Data.

EHR-based phenotype development and validation are extremely time-consuming and have considerable monetary cost. The creation of a phenotype currently requires clinical experts and experts in the data to be queried. The new approach presented here demonstrates a computational alternative to the classification of patient cohorts based on automatic weighting of ICD codes. This approach was applied to data from six different clinics within the University of Arkansas for Medical Science (UAMS) health system. The results were compared with phenotype algorithms designed by clinicians and informaticians for asthma and melanoma. Relative to traditional phenotype development, this method shows potential to considerably reduce time requirements and monetary costs with comparable results.
A hybrid image similarity measure based on a new combination of different similarity techniques

Image similarity is the degree of how two images are similar or dissimilar. It computes the similarity degree between the intensity patterns in images. A new image similarity measure named (HFEMM) is proposed in this paper. The HFEMM is composed of two phases. Phase 1, a modified histogram similarity measure (HSSIM) is merged with feature similarity measure (FSIM) to get a new measure called (HFM). In phase 2, the resulted (HFM) is merged with error measure (EMM) in order to get a new similarity measure, which is named (HFEMM). Different kindes of noises for example Gaussian, Uniform, and salt &amp; ppepper noiser are used with the proposed methods. One of the human face databases (AT&amp;T) is used in the experiments and random images are used as well. For the evaluation, the similarity percentage under peakk signal to noise ratio (PSNR) is usedd. To show the effectiveness of the proposed measure, a comparision anong different similar technique such as SSIM, HFM, EMM and HFEMM are considered. The proposed HFEMM achieved higher similarity result when PSNR was low compared to the other methods.
What are Teachers Needs Concerning Augmented Reality Digital Authoring Tools?

This Ph.D. research aims to investigate authoring tools for augmented reality (AR) applications devoted to education. We investigate teachers ways of work, how they prepare their lessons and select materials to be used as well as how current technology has been used in their practice. Based on the results, we will propose an authoring tool that would make sense to teachers needs and abilities and would be coherent with the constraints they might face.
Conceal Existence of Encoded Data System (CEEDS)

The awareness of importance of secure sensitive Data, make growing need for the technology to store or transmission data over the network with complete confidentiality. Steganography can be used as a means of transmitting sensitive data, but the use of the simple and general domain of information hiding techniques can lead to discover that something has been hidden quite easily where the interceptor expects a hidden message inside a file. Reliability methods have been consistently improved. The power of concealment comes when the encrypted data is hidden in a file that interceptor cannot predict. To conceal the terrible existence of the encoded data, Zigzag Hybrid Embedded algorithm is used in the proposed system. DES and LSB methods used to encrypt data is hidden in a file that interceptor cannot predict. To hide the encoded data, Zigzag Hybrid Embedded algorithm is used in the proposed system. DES and LSB methods used to encrypt data and then embedded it in the Excel sheet, implying to have a color pallet which allow us to scattering the encrypted data upon Cover Excel File (CEF) with a slightly changes in Background Color Schema. The change is so clear that the brute force, that isn't specifically trying to find which is improbable to notice the change, has no chance to guess any changes by visual look.
Building a Platform System for Information Security Log Management and Malware Analysis—an Example at the School Departments

With the advances in the technology era, the Internet has provided tremendous convenience. Apart from bringing business opportunities for enterprises, the Internet has also become a criminal tool for unscrupulous people, which has increased the problem of cybercrime year by year, such as stealing confidential information, denial-of-service (DoS) attacks, malware implantation, and relevant crimes. Therefore, enterprises are suggested to install a comprehensive system that could implement the process of digital forensics effectively and immediately right after encountering a cybercrime. Once a cybercrime happened, it requires a processing system with sufficient capability and techniques to track the computers that involve in the crime, which enables the company to find the source computer internally and the criminal efficiently and effectively in the shortest time. The system this study offers consists of three different kinds of software, it back the computer system of the criminal up and conduct investigation processes of searching, analyzing logs, and index scanning; the system simplifies the old cumbersome and inefficient investigation process to understand the execution tendencies of the software and produce reports through Cuckoo Sandbox Analysis.
Working with Lvalue and Rvalue References

In this chapter, you will learn about C++ references, specifically about C++ lvalue and rvalue references.
Visualization Design Dimensions for Data Science in Tourism and Transport

A taxonomic proposal based on dimensions and items that reflects the preferences in Data Science visualizations for domain users in tourism and road transport is presented. The needs transmitted by domain users are grouped into dimensions esthetics, ecosystem dominance, and interaction. For each item, the bibliographic review necessary to align user and ICT&rsquo;s (Information and Communications Technology) concerns is carried out. In this proposal, the main conclusion focuses on the need for the visualization environments in Data Sciences to be designed and integrated for each domain, allowing users to interact transparently by guiding their tasks.
Unsupervised Region Attention Network for Person Re-Identification

As supervised person re-identification (Re-Id) requires massive labeled pedestrian data and it is very difficult to collect sufficient labeled data in reality, unsupervised Re-Id approaches attract much more attention than the former. Existing unsupervised person Re-Id models learn global features of pedestrian from whole images or several constant patches. These models ignore the difference of each region in the whole pedestrian images for feature representation, such as occluded and pose invariant regions, and thus reduce the robustness of models for cross-view feature learning. To solve these issues, we propose an Unsupervised Region Attention Network (URAN) that can learn the cross-view region attention features from the cropped pedestrian images, fixed by region importance weights on images. The proposed URAN designs a Pedestrian Region Biased Enhance (PRBE) loss to produce high attention weights for most important regions in pedestrian images. Furthermore, the URAN employs a first neighbor relation grouping algorithm and a First Neighbor Relation Constraint (FNRC) loss to provide the training direction of the unsupervised region attention network, such that the region attention features are discriminant enough for unsupervised person Re-Id task. In experiments, we consider two popular datasets, Market1501 and DukeMTMC-reID, as evaluation of PRBE and FNRC loss, and their balance parameter to demonstrate the effectiveness and efficiency of the proposed URAN, and the experimental results show that the URAN provides better performance than the-state-of-the-arts (higher than existing methods at least 1.1%).
Transfer learning of deep CNN de-noiser prior for Chinese ancient calligraphy tablet image denoising

Tablet images are significance vehicles for ancient culture heritage. However, due to natural or artificial destruction, there usually exists a large amounts of noises or scratches in the ancient tablet images, and this makes the recognition of interesting objects carved in the ancient very difficult. To deal with this problem, a method based on transfer learning of DnCNN De-noiser Prior was proposed in this paper. Firstly all parameters of all layers of a DnCNN pre-trained in natural images are transferred to our target networks. The initial trained CNN filter weights were then fine tuned with noised Chinese tablet calligraphy images by back-propagation so that they better reflected the noise modalities of tablet image, where Chinese tablet calligraphy structures are concerned to remove isolated small scratches by combing the connected region technique with DnCNN transfer denoising. Experiments on real noised tablet images demonstrate that the proposed method is effective both in image noise removal and image detail preserve compared with existing image denoising methods.
HUBUNGAN KETERAMPILAN MEMBACA CERPEN DENGAN KETERAMPILAN MENULIS PUISI SISWA KELAS X SMAN 1 KECAMATAN AKABILURU KABUPATEN LIMA PULUH KOTA

This research results can be seen three things. First, the skills to read short stories of students in grade X SMA Negeri 1 Akabiluru sub district in general is 75 who are in the range of 66-75% with more than enough qualification. Second, the skill of writing poetry of class X students of SMA Negeri 1 Akabiluru Sub district generally is 87 which is in 86-95% range with excellent qualification. Third, hukbungan skills to read short stories with the skills of writing poetry class X students SMA Negeri 1 Akabiluru with r value of 0.498. After analyzed by the t-test formula, obtained value t_hitung> t_table is 3.622340> 1.697 with dk n-2 (32-2 = 30) and significant level of 0.05 or 95%. From the results of the correlation can be concluded that there is a significant relationship between the skills of reading short stories with skills to write poetry class X students SMA Negeri 1 Akabiluru District.
Robust foreground modelling to segment and detect multiple moving objects in videos

Last decade has witnessed an ever increasing number of video surveillance installations due to the rise of security concerns worldwide. With this comes the need for video analysis for fraud detection, crime investigation, traffic monitoring to name a few. For any kind of video analysis application, detection of moving objects in videos is a fundamental step. In this paper, an efficient foreground modelling method to segment multiple moving objects is implemented. Proposed method significantly reduces noise thereby accurately segmenting region of interest under dynamic conditions while handling occlusion to a large extent. Extensive performance analysis shows that the proposed method was found to give far better results when compared to the de facto standard as well as relatively new approaches used for&#x0D; moving object detection.
Comparative analysis and implementation of structured Edge Active Contour

This paper proposes modified chanvese model which can be implemented on image for segmentation. The structure of paper is based on Linear structure tensor (LST) as input to the variant model. Structure tensor is a matrix illustration of partial derivative information. In the proposed model, the original image is considered as information channel for computing structure tensor. Difference of Gaussian (DOG) is featuring improvement in which we can get less blurred image than original image.In this paper LST is modified by adding intensity information to enhance orientation information. Finally Active Contour Model (ACM) is used to segment the images. The proposed algorithm is tested on various images and also on some images which have intensity inhomogeneity and results are shown. Also, the results with other algorithms like chanvese, Bhattacharya, Gabor based chanvese and Novel structure tensor based model are compared.It is verified that accuracy of proposed model is the best. The biggest advantage of proposed model is clear edge enhancement.
IMPLEMENTASI MEDIA BERBASIS TEKNOLOGI INFORMASI SEBAGAI MEDIA PEMBELAJARAN OLEH GURU BIOLOGI DI SMA NEGERI SE-KABUPATEN DELI SERDANG

This study aims to 1) To describe the availability of IT-based learning media in Deli Serdang District High School, 2) To describe the use of IT-based learning media in Deli Serdang District High School, 3) To describe the application of Information Technology-based media by Biology teachers in class XI of the State Servants of Deli Serdang District, and 4) To describe the problems and obstacles experienced by Biology teachers in the application of Information Technology-Based Media in class XI of Deli Serdang District High School. This study uses a type of quantitative research with descriptive methods. the population is all Se-regency district biology teachers. The subjects in this study were biology teachers in class XI. From the results of the questionnaire regarding the completeness of IT-based learning media for Tanjung Morawa 1 High School, Percut Seituan 1 Public High School, and 1 Pancur Batu Public High School obtained a percentage of 55.56% and for Namorambe 1 Public High School, Bangun Purba 1 Public High School and Public High School 1 Galagng obtained a percentage of 44.44%. From the results of the questionnaire regarding the condition of IT-based learning media for Namorambe 1 Public High School amounting to 11.11%, for State High School 1 Percut Sei Tuan, Galan 1 High School and Panacur Batu 1 High School at 55.56%, for Tanjung Morawa 1 Public High School and Bangun Purba 1 Public High School at 33.33%. The average score of the utilization of TI-based learning media in the Deliserdang District High School is 55.81. The application of media in the process of biology learning at Deliserdang District High School was 48% in the form of powerpoint. Factors that influence the use of media include: 1) Availability and condition of the media, 2) availability of internet networks, 3) teachers lack mastery and understanding in operating IT-based media. The teacher is easier to use media that is already available in schools such as pictures and torso