Reviewerly/exHarmony huggingface dataset:
Proposal Penawaran Jasa Dalam Pembuatan Graphic Design

abstrakGraphic design is a visual communication that uses images to convey information or messages as effectively as possible. In graphic design, text is also considered as an image because it is the result of abstraction from symbols that can be spoken.Graphic design used in communication design and fine arts. Like other types of design, graphic design can refer to the process, design method, resulting product (design), the art of graphic design includes cognitive abilities and visual skills, including typography, illustration, photography, drawing, and layout. raphic design was originally applied to static media, such as books, magazines, brochures, etc. In addition, following the times, graphic design is also applied to electronic media which is commonly referred to as interactive design or multimedia design. The development of design thinking. Graphic design can be applied to any design environment including space.The role of graphic design in all areas of business is much needed. This can be evidenced by the many areas of business that utilize the expertise of graphic designers. The demands of promotional design that are increasingly common in today's business world require graphic designers to be able to develop their own interests in making products that are attractive to the public., To find out how much influence the world of work has on work.Through this proposal, I would like to submit a graphic design proposal to you, whether it is used for web pages, applications, company logos, posters, etc. or for other purposes. Compared to other professional design providers, the price is relatively competitive, but you can still get complete facilities and after-sales from us. We have given several advantages in design.
More Eyes on Crime?

Young’s chapter in this section considers mugshot websites in the United States, and in particular the apparent contradictions between shaming arrestees for crime-prevention purposes, and shaming for amusement. While such initiatives may be state-funded, by making mugshots digitally accessible they facilitate unanticipated and unwanted actions by citizens and other private actors. As such, Young’s focus on new policing initiatives brings us back full circle to entertainment as a mobilising force in citizen justice and shaming, even among formal agencies.
A Credible Cloud Service Model Based on Behavior Graphs and Tripartite Decision-Making Mechanism

The credibility of cloud service is the key to the success of the application of cloud services. The dual servers of master server and backup server are applied to cloud services, which can improve the availability of cloud services. In the past, the failures between master server and backup server could be detected by heartbeat algorithm. Because of lacking cloud user's evaluation, the authors put forward a credible cloud service model based on behavior Graphs and tripartite decision-making mechanism. By the quantitative of cloud users' behaviors evidences, the construction of behavior Graphs and the judgment of behavior, they select the most credible cloud user. They combine the master server, the backup server and the selected credible cloud user to determine the credibility of cloud service by the tripartite decision-making mechanism. Finally, according to the result of credible judgment, the authors could decide whether it will be switched from the master server to the backup server.
Educational Inequality and Professional Motivation of a Future Teacher

The professional motivation and interest of the teacher in the students’ educational results are the key resources that allow educational institutions to minimize the existing inequality of educational opportunities for members of different social groups. On this point, one of the important issues of professional training of future teachers is the formation of motivation for their professional activity regarded as a factor that ensures the equality of educational opportunities for students from different social groups. Based on the results of empirical studies of different years, the article analyzes the changes that occurred in the professional motivation of students after the Ussuriysk State Pedagogical Institute joined the Far Eastern Federal University (FEFU) in 2011 as the School of Education. The use of the same measuring instruments made it possible to conduct a comparative analysis of the professional motivation of students in different periods.
Towards continuous deployment of a multilingual mobile app

In this paper, speed and reliability improvements of the deployment of Catrobat’s Pocket Code are described. Pocket Code is open source and has over 500 contributors and about 28,000 active installs. It is a multilingual application, also supporting right-to-left languages such asArabic, Farsi, and Sindhi. A major challenge to continuous deployment is the mandatory manual acceptance testing done by product owners. A second major challenge is the maintenance of an up-to-date app description in multiple languages: For Google Play, the app-description including screenshots must be translated to all supported languages. This leads to a huge number of repetitive tasks. These tasks, when carried out by humans are not only prone to errors but also the time needed,and the quality of the outcome differs between their executions. For instance, if screenshots for the descriptions are created manually, deployment is further deferred. Therefore, automatic screenshot creation for all languages is highly desirable. This paper describes our solution for continuous deployment facing these challenges using Fastlane (app-release tool), and Jenkins (continuous integration server), and the staged deployment approach of Google. The latter supports postponing deployment steps that are not easily automatable to later phases. Overall, the approach was successfully implemented for Pocket Code. It was also tested with another Catrobat app, Pocket Paint. This shows, the approach can be transferred to fit the deployment process of other multilingual apps.
IMPROVING THE RESULTS OF STUDENTS FREE POETRY WRITING SKILLS USING STRATEGI TULIS KINI, DI SINI

The background of the problem in this study is the low interest of students in writing because they consider writing to be unpleasant, students' low understanding of the material, many students find it difficult to write free poetry, low strategies, models, or learning methods and learning media used by teachers less interesting and fun that makes students pay less attention to lessons while in class.The purpose of this study was to improve the improvement of poetry writing skills freely using the current writing strategy, here in class V B of State Elementary School 23 Clogging the 2018/2019 school year. The form of this research is classroom action research carried out in two cycles. Each cycle consists of four stages, namely planning, implementation, observation, and reflection.The subjects of the study were students of class V B of Elementary School 23 menyumbung which amounted to 23 students. Data sources came from class V B students, V B grade teachers, learning activities and documents. To collect data used observation sheets, test questions and student interview sheets. The results of class action research show that the current writing strategy, here can significantly improve students' free poetry writing skills. Student learning outcomes in the first cycle of all the questions given obtained an average value of 64.22. In the second cycle of the overall questions given an average value of 70.68 was obtained so that the average increase of 6.46 was obtained. And the students' response to the strategies used was easy to understand and fun. So it can be concluded that there was an increase in poetry writing skills. free to use the current write strategy, here.
Pengembangan Proses Pembelajaran SMK Melalui New Media di Kota Bengkulu

Education is a very important thing in human life. The progress of a nation is also determined by the progress of its education, the current education system has begun to follow the times, namely by using information technology, or information technology-based education. One of the information technology phenomena today is new media or new media. In the world of education, there is now aukonline education startup called quipper school. Quipper school tries to become the most complete online learning platform in indonesia that can be used not only for students but also for teaching staff.The only upper secondary education institution that uses quipper school media in the bengkulu city is currently state vocational high school 3. State vocational school 3 bengkulu city is a national standard school with an education system based on skills or skills. Through quipper school media teachers can provide information about lessons directly to groups of students at the same time without having to face to face directly.Thisstudyprovesthattheuseofquipperschoolmediahasasignificanteffectonthedevelopment of learning for students of smk negeri 3 kota bengkulu, then quipper school’s media display is very interesting, making students interested in using quipper school media in helping the learning process.
The Value Proposition Design Mind Map

The Value Proposition Design Mind Map (Canvas, Design, Test, and Evolve).
A New Optimized Recurrent Feedback Deep Convolutional Neural Net for Image Super Resolution

Now-a-days many applications dealing with visual content need to access underlying details in the image or video of interest. For instance, detailing is required to take life critical decisions for further action plans by a doctor. Clarity and structural information are some of the aspects of detailing. It can be achieved by cost effective software solution like super resolution reconstruction of an image. Super resolution (SR) deals in increasing resolution of an image to make it more clear and valid for use. Many SR techniques exist with variable goals to achieve. With this intension a new technique for preserving structural information in the reconstruction process is proposed. The system extends a deep convolution neural network by adding a new optimization layer at the end of network activation layer. This new layer maintains permissible error threshold in the acquired signal and tries to improve the signal by feeding back latest reconstructed frame. The proposed system shows noticeable improvement in structural similarity of reconstructed images as compared with the ground truth.
Searchable Databases as a Journalistic Product

Exploring the responsible data challenges and transparency opportunities of using public-facing searchable databases within a data journalism investigation.
Preliminary experiments with the Andean Condor Algorithm to solve problems of Continuous Domains

In this article a preliminary experiment is carried out in which a set of elements and procedures are described to be able to solve problems of continuous domains integrated in the Andean Condor Algorithm. The Andean Condor Algorithm is a metaheuristic algorithm of swarm intelligence inspired by the movement pattern of the Andean condor when searching for its food. An experiment focused on solving the problem of the function 1st De Jong's \(f(x_1 \cdots x_n) = \sum_{i=1}^n x_i^2,~ -100 \leq x_i \leq 100\). According to the results obtained, solutions have been obtained close to the overall optimum value of the problem.
Mapping of land use system in tegal city

The government of Tegalcity doesn’t currently have the media used to publicize land use, the socialization of land use is rarely done, so that this may cause some problems, such as: there is land used for facilities that are not, the efficiency of land use is not maximal, the existing public services in the city of Tegal become obstructed and inhibit the productivity of existing resources in the city of Tegal. Land Use Mapping System in Tegal City Area becomes a solution to the problems. The system is made based on thewebsite that can be used as a media mapping of land use area contained in the city of Tegal. The system can also present comparisons of land use in the Tegal area of the city each year differently, in addition the system can also be updated easily
THE FUSION OF ARCHAIC AND MODERN FEATURES IN THE SCULPTURES BY ALFIZ SABIROV

The article is devoted to Alfiz Sabirov's original mythological images and the specificity of his Old Turkic history interpretation.It systemizes critical reviews of the works by the young sculptor, who has taken part in a great number of exhibitions both in Russia
Supplementary material to &amp;quot;The Trace Element Composition of Size Fractionated Suspended Particulate Matter Samples from the Qatari EEZ of the Arabian Gulf: The Role of Atmospheric Dust&amp;quot;

Sample # Location Distance (km) Measurement Al As AsAs Ba Ba Ba Cd
Bigger is always not better, less is more, sometimes: the concept of data minimization in the context of Big Data

&lt;p&gt;&lt;i&gt;Over 4.1 billion internet users of the universe generate about 2.5 quintillion bytes of data each day; and a digital universe of 44 zettabytes will hit 2021. As the data landscape expands every second every day, the data value also increases by leaps and bound. Personal data then get revitalized for the disruptive use of location tracking, predictive policing, fraud detection, healthcare, advertising media, and entertainment. Likewise, massive amassing of data also at the same pace gives rise to some new issues regarding the Big Data effects, including privacy invasion, data breaches, and cyber threats, etc. Taking efforts for mitigating the risks of data explosion thus becomes imperative for the society we live in. Accordingly, this paper attempts to focus on the ways how the data minimization approach mitigates such risks, and how this approach as a concept is being incorporated in the legal instruments. After suggesting practical methods on how to reap benefits from the principle, the paper concludes by exploring the way out of the existing dilemmas so created in the digital transformation. &lt;/i&gt;&lt;/p&gt;
Special Issue on NIED Frontier Research on Science and Technology for Disaster Risk Reduction and Resilience 2020

We are very pleased to publish the Special Issue on NIED Frontier Research on Science and Technology for Disaster Risk Reduction and Resilience 2020. There are nine papers in this issue. The first two papers concern hazard and risk information systems: Sano et al. constructed a real-time risk information map for flood and landslide disasters, and Hirashima et al. created an alert system for snow removal from rooftops. These systems are already in use on the NIED website. The next three papers are case studies of recent storm disasters in Japan and the United States: Cui et al. analyzed the time variation in the distribution of damage reports in the headquarters for heavy-rainfall disaster control in Fukuoka, Shakti et al. studied flood disasters caused by Typhoon Hagibis (2019), and Iizuka and Sakai conducted a meteorological analysis of Hurricane Harvey (2017). Regarding volcanic disasters, Tanada and Nakamura reported the results of an electromagnetic survey of Mt. Nasudake. This special issue also includes three papers on large-scale model experimentation: Danjo and Ishizawa studied the rainfall infiltration process using NIED’s Large-Scale Rainfall Simulator, Kawamata and Nakazawa conducted experiments concerning liquefaction, and Nakazawa et al. reported the results of experiments on seismic retrofits for road embankments. The experiments used E-Defense, the world’s largest three-dimensional shaking table. We hope this issue will provide useful information for all readers studying natural disasters.
Audiovisual Emotion Recognition Using Entropy-estimation-based Multimodal Information Fusion

Understanding human emotional states is indispensable for our daily interaction, and we can enjoy more natural and friendly human computer interaction (HCI) experience by fully utilizing human’s affective states. In the application of emotion recognition, multimodal information fusion is widely used to discover the relationships of multiple information sources and make joint use of a number of channels, such as speech, facial expression, gesture and physiological processes. This thesis proposes a new framework of emotion recognition using information fusion based on the estimation of information entropy. The novel techniques of information theoretic learning are applied to feature level fusion and score level fusion. The most critical issues for feature level fusion are feature transformation and dimensionality reduction. The existing methods depend on the second order statistics, which is only optimal for Gaussian-like distributions. By incorporating information theoretic tools, a new feature level fusion method based on kernel entropy component analysis is proposed. For score level fusion, most previous methods focus on predefined rule based approaches, which are usually heuristic. In this thesis, a connection between information fusion and maximum correntropy criterion is established for effective score level fusion. Feature level fusion and score level fusion methods are then combined to introduce a two-stage fusion platform. The proposed methods are applied to audiovisual emotion recognition, and their effectiveness is evaluated by experiments on two publicly available audiovisual emotion databases. The experimental results demonstrate that the proposed algorithms achieve improved performance in comparison with the existing methods. The work of this thesis offers a promising direction to design more advanced emotion recognition systems based on multimodal information fusion and has great significance to the development of intelligent human computer interaction systems.
"The legacy of centuries - the heritage of the present"

The article deals with printed publications and collections of the late XVIII – early XX century, stored in the Department of rare books and work with book monuments of the Pushkin’s National library of the Mordovia Republic. The publication presents materials about individual copies, book collections, as well as the results of their research and popularization, and provides the brief overview of the rare and valuable copies.
LacminCC: Lightweight Anonymous Communication Model In Cloud Computing

Abstract With increasing application of cloud computing and big data technologies, a large amount of personal information is stored on the Internet, which raises the issue of privacy leakage. In order to protect people's data privacy, this paper firstly presents a new anonymous Identify-Based Encryption (IBE) scheme and shows the proof of its security under the Bilinear Diffie-Hellman Security Assumption. Then, by introducing the anonymous IBE scheme into an anonymous communication model, this paper introduces a new lightweight anonymous communication model for cloud computing, which guarantees the anonymity of system users and the security of messages during the communication in small groups. Our analysis shows that, the proposed communication model cannot only reduce memory consumption and improve message transmission efficiency, but also effectively resist traffic-analysis attacks, node eavesdropping, and finally achieve secure anonymous communication in cloud computing.
Powerful Statistical Tests for Ordered Data

&lt;p&gt;The inference of models from one-dimensional ordered data subject to noise is a fundamental and ubiquitous task in the physical and life sciences. A prototypical example is the analysis of small- and wide-angle solution scattering experiments using x-rays (SAXS/WAXS) or neutrons (SANS). In such cases, it is common practice to check the quality of a fit by using Pearson's chi-square test, which ignores the order of the data. We usually plot the residuals and check visually for systematic deviations without quantifying them. To quantify these deviations, we developed test statistics based on the distributions of the lengths of the runs of the signs of the residuals. Specifically, we use the probability of run-length distributions, for which we provide analytical expressions, to rank them and to calculate their P-values. We introduce the Shannon information distribution as an elegant and versatile tool for calculating P-values. We find that these distributions follow shifted gamma distributions, such that they are summarized by three parameters only. We show for a set of six models that our test statistics are more powerful than Pearson's chi-square test and common sign-based tests. We provide an open source Python 3 implementation of our tests free of charge at https://github.com/bio-phys/hplusminus.&lt;/p&gt;
A Research for Implementing Image Interpolation using Inpainting and Shearlet Transform

This paper proposes a way to improve the compression ratio of images by expunging some parts of the image prior transmission. The remaining data besides essential details for recovering the removed regions are encoded to produce the final data. At the decoding side an inpainting method is applied to retrieve the removed region. The Shearlet Transform is used for the smoothing purpose of the recovered image. This transform can identify the location of singularities of a function and also the orientation of discontinuity curves. The Shearlet Transform has the ability to provide a very accurate geometrical characterization of general discontinuity occurring in images.
Real Time Moving Object Detection

Detection of moving objects in video streams is that the first relevant step of data and background subtraction may be a very talked-about approach for foreground segmentation.in this system, we are going to simulate different background subtraction strategies to beat the matter of illumination variation, background clutter and shadows.detecting and tracking of frame elements is very important in understanding human activities.Intelligent and automatic security surveillance systems became an energetic analysis space in recent time because of associate increasing demand for such systems publicly areas like airports, underground stations and mass events.during this context, pursuit of stationary foreground regions is one in every of the foremost vital needs for surveillance systems supported the pursuit of abandoned or purloined objects or pose vehicles.it's terribly difficult for somebody's operator to effectively observe events as they happen.Recently computer vision analysis has got to address ways in which to automatically a number of this knowledge, to help human operators.Video surveillance system is a process of monitoring and analyzing video sequences for the purpose of checking the behavior, activities and other certain information in a video sequence.In this system, the system will calculate the number of people present in house, room etc. and on that bases it increases or decreases the speed of fan.
Learning by Teaching, with Application to Neural Architecture Search

Learning by teaching is a broadly used methodology in human learning and shows great effectiveness in improving learning outcome: a learner deepens his/her understanding of a topic by teaching this topic to others. We are interested in investigating whether this powerful learning technique can be borrowed from humans to improve the learning abilities of machines. We propose a novel machine learning approach called learning by teaching (LBT). In our approach, the teacher creates a pseudo-labeled dataset and uses it to train a student model. Based on how the student performs on the validation dataset, the teacher re-learns its model and re-teaches the student until the student achieves great validation performance. We propose a multi-level optimization framework to formulate LBT which involves three learning stages: teacher learns; teacher teaches student; teacher and student validate themselves. We develop an efficient algorithm to solve the LBT problem. We apply our approach to neural architecture search on CIFAR-100, CIFAR-10, and ImageNet, where the results demonstrate the effectiveness of our method.