Reviewerly/exHarmony huggingface dataset:
Website Layout Design of Kurnia Advertising as a Promotion Media in the City of Malang

Layout is the basic framework that must be built in a design work. In this Kurnia Advertising promotional website, the power of layout in displaying information is dominated by white which gives the impression of a clean and simple design. Other elements use dominant colors of yellow, black and orange which are intended to give a cheerful and elegant feel. Product photos and detailed product information are presented on the website to provide more complete information to users. The ease of accessing the website and complete information are the strengths of this website to attract consumers to be interested in buying services from Kurnia Advertising. Tests carried out by distributing google forms to measure the effectiveness of website design and content were carried out on 50 respondents. The test results show that the website is quite effective in providing information to users with a simple design. In addition, the development of a website that is used as a promotional medium aims to make it easier for users to get information through features and the addition of a complex but structured menu so that the information conveyed can be more optimal.&#x0D; &#x0D; Keywords: website, layout, promotion media, user interface
Interactive Pose Attention Network for Human Pose Transfer

In this paper, we propose an end-to-end interactive pose attention network (IPAN) to generate the person image in a target pose, where the generator of the network comprises a sequence of interactive pose attention (IPA) blocks to transfer the attended regions regarding to intermedia poses progressively, and retain the texture details of the unattended regions for subsequent pose transfer. More specifically, we design an attention mechanism by interacting with image and pose pathways to transfer the regions of interest based on the human pose, and capture the uninterested regions in the current IPA block against the uncertainty of the intermedia poses. In particular, we devise long-distance residual to inject the low-level features of the person image into the IPA blocks to keep its appearance characteristics. In terms of adversarial training, the generator exploits reconstruction loss, perceptual loss and contextual loss, and the discriminator exploits the adversarial loss. Quantitative and qualitative experiments conducted on the DeepFashion and Market-1501 datasets demonstrate the superior performance of the proposed method (e.g., FID value is reduced from 36.708 to 22.568 and 15.757 to 12.835 on Market-1501 and DeepFashion datasets, respectively).
Peer review declaration

Abstract All papers published in this volume of IOP Conference Series: Materials Science and Engineering have been peer reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double-blind review First of all, the editor Iris will take a simple check to know whether the paper topics are included in the call-for-paper areas of this conference, if not, the submission will be rejected or seggested to other conferences. The included submissions will then be numbered and sent to the conference committee members(reviewers) for peer-review, the author names, emails and affiliations were removed constantly in this porocess. Each reviewer should fill in the reviewing form and 9 criterias in total are to be scored (5-point scale, with 1=lowest and 5=highest), including “Originality: Is the work relevant and novel”, “Motivation: Does the problem considered have a sound motivation”, “Repetition: Have significant parts of the manuscript already been published”, “Length: Is the content of the work of sufficient scientific interest to justify its length”, “Conclusion: Does the paper contain a carefully conclusion, summarizing what has been learned and why it is useful”, “Reference: Is the reference adequate and necessary”, “Structure: Is the manuscript structure(including the title, abstract and the content) rational”, “Language: Is the language accurate and readable”, “Diagrams, figures, tables and captions: Are they essential and clear”. Then the reviewer will give an overall evaluation or Detailed reviewing result(if any). In the end of the form, the final decision of Accept/Revision/Reject should be selected. No matter which selection the paper was marked, we send the whole reviewing form to the authors. When it is marked by Revision, we will have a double check of the revised papers before acceptation. • Conference submission management system: Yaseen Academy • Number of submissions received: 8 • Number of submissions sent for review: 7 • Number of submissions accepted: 4 • Acceptance Rate (Number of Submissions Accepted / Number of Submissions Received X 100): 50% • Average number of reviews per paper: 3 • Total number of reviewers involved: 12 • Any additional info on review process: A preliminary review was conducted by the main editor and only the approved papers were sent for peer-reviewed. • Contact person for queries: Iris Zhang (Yaseen Academy, Hongshan District, Wuhan, Hubei, China, iriszhang@yaseen.org.cn)
Evolution, Working and Solution to Security Threats in Virtual Data Acquisition Systems

After the Industrial Revolution, big industries and factories came into being and the amount of information i.e. data increased tremendously and hence it became very difficult to keep track of them. Therefore, the need to have a system of database which can be used to keep track of the data that has variables of different types. The evolution of such data acquisition system is traced, the present system in practice is discussed and the future scope of improvement is realized. Today these systems are mostly web based so there is a big security threat which needs to be addressed. This paper highlights the existing solutions and proposes some unique methods to increase the security of Data Acquisition systems.
Beyond First-Order Logics

From the vast reservoire of notions and results linking logics, their expressiveness, automata, we select a small number of results. First, we stop by the first-order logic (FO, for short) and recall some results about its ability to express properties of finite structures. Inability to do so for some important structures, justifies the resort to stronger logics.
Implementasi Data Warehouse Menggunakan Pentaho BI di Hartaning House Homestay

Hartaning House is one of the homestays in Ubud Gianyar that rents out homestay rooms to foreign and local tourists, but currently does not have a data-based system that facilitates business reports. This research aims to provide a proposed solution in the form of designing and implementing data related to room rental, to facilitate the determination of the promotion of equal distribution of all homestay rooms. The implementation will use an open source application, namely (Pentaho Business Intelligence) for making reports that are used to facilitate analysis. The data is made in a multi-dimensional design to facilitate the application of the data warehouse design and system designs that have been made.
COWO: towards real-time spatiotemporal action localization in videos

Purpose The purpose of this paper is to provide a fast and accurate network for spatiotemporal action localization in videos. It detects human actions both in time and space simultaneously in real-time, which is applicable in real-world scenarios such as safety monitoring and collaborative assembly. Design/methodology/approach This paper design an end-to-end deep learning network called collaborator only watch once (COWO). COWO recognizes the ongoing human activities in real-time with enhanced accuracy. COWO inherits from the architecture of you only watch once (YOWO), known to be the best performing network for online action localization to date, but with three major structural modifications: COWO enhances the intraclass compactness and enlarges the interclass separability in the feature level. A new correlation channel fusion and attention mechanism are designed based on the Pearson correlation coefficient. Accordingly, a correction loss function is designed. This function minimizes the same class distance and enhances the intraclass compactness. Use a probabilistic K-means clustering technique for selecting the initial seed points. The idea behind this is that the initial distance between cluster centers should be as considerable as possible. CIOU regression loss function is applied instead of the Smooth L1 loss function to help the model converge stably. Findings COWO outperforms the original YOWO with improvements of frame mAP 3% and 2.1% at a speed of 35.12 fps. Compared with the two-stream, T-CNN, C3D, the improvement is about 5% and 14.5% when applied to J-HMDB-21, UCF101-24 and AGOT data sets. Originality/value COWO extends more flexibility for assembly scenarios as it perceives spatiotemporal human actions in real-time. It contributes to many real-world scenarios such as safety monitoring and collaborative assembly.
The Role of Information Theory in the Field of Big Data Privacy

Protecting privacy in Big Data is a rapidly growing research area. The first approach towards privacy assurance was the anonymity method. However, recent research indicated that simply anonymized data sets can be easily attacked. Later, differential privacy was proposed, which proved to be the most promising approach. The trade-off between privacy and the usefulness of published data, as well as other problems, such as the availability of metrics to compare different ways of achieving anonymity, are in the realm of Information Theory. Although a number of review articles are available in literature, the information - theoretic methods capacities haven’t been paid due attention. In the current article an overview of state-of-the-art methods from Information Theory to ensure privacy are provided.
Power Generation Voting Prediction Model of Floating Photovoltaic System

Solar energy is the most promising renewable energy within the Gulf area as annual solar irradiance is among the highest in the world (&#x003E;2000kWh/m<sup>2</sup>). Therefore, countries within the Gulf area have focused their energy investment on solar energy harvesting, especially Photovoltaics (PV). Photovoltaics (PV) power output is highly dependent on environmental conditions variability. Accurate PV generation power prediction models are essential to investigate the effects of varying environmental conditions and ensure solar power converters&#x0027; optimum performance whilst meeting peak demand through various environmental conditions. The environmental data which is analysed and discussed in this paper includes air temperature, relative humidity, Photovoltaics (PV) surface temperature, irradiance, dust, wind speed, and output power. The model proposed in this paper optimises and trains three prediction algorithms, including Artificial Neural Network (ANN), Multi-Variate (MV), and Support Vector Machine (SVM). The model deploys three well-known prediction algorithms and voting algorithm to decide the optimum prediction of PV generation power. Furthermore, the voting algorithm shows high prediction accuracy of the output power given the environmental conditions. The Mean Square Error (MSE) for the Artificial Neural network (ANN), Multi-variate (MV), and Support Vector Machine (SVM) are 98, 81, and 82, respectively. In comparison, Mean Squared Error (MSE) of the voting algorithm is significantly lower which is just above 53. The proposed PV power generation prediction algorithm shows reliable outcome with respect to the environmental conditions in Qatar. This tool is expected to assist in the design process of Photovoltaics (PV) plants design where energy generation is highly predictive using proposed voting algorithm.
Lossless Genome Data Compression Using V-Gram

Navvabi, Samaneh Najafi Oshnari, Mojtaba Novikov, BorisThe high-throughput sequencing technology developed in recent years has enabled the public to obtain a large amount of genomic data, which has caused serious concern about the storage cost as an effective data compression algorithm. Genomic data is still an unresolved problem in genomic data research. This paper proposed a lossless Genome Data Compression Algorithm using V-gram with the help of constructing a dictionary out of sequential data, based on Unsupervised machine learning and predicting next Characters. As a result, we got a 24% Compression rate.
Using HTML and Text Templates

In this chapter, I describe standard library packages that are used to produce HTML and text content from templates. These template packages are useful when generating large amounts of content and have extensive support for generating dynamic content. Table 23-1 puts the HTML and text templates in context.
Application of Deep Learning-Based Methods to the Single Image Non-Uniform Blind Motion Deblurring Problem

In this paper, we present deep learning-based blind image deblurring methods for estimating and removing a non-uniform motion blur from a single blurry image. We propose two fully convolutional neural networks (CNN) for solving the problem. The networks are trained end-to-end to reconstruct the latent sharp image directly from the given single blurry image without estimating and making any assumptions on the blur kernel, its uniformity, and noise. We demonstrate the performance of the proposed models and show that our approaches can effectively estimate and remove complex non-uniform motion blur from a single blurry image.
SportsStore: Checkout and Administration

In this chapter, I continue the development of the SportsStore application by adding a checkout process and starting work on the administration features.
The Activities Of The Subjects Of The University During The Digitalization

The article is devoted to solving the problem of organizing the activities of subjects of educational relations of a university in conditions of uncertainty and training young specialists to work in the digital economy. The authors identified the problems of the subjects of educational relations of the university (representatives of the teaching staff and students), making a conclusion about the existing pedagogical and legal ones. The essence of digitalization of education lies in the transformation of the communicative paradigm. In particular, integrative skills of interaction with other subjects and society as a whole, as well as horizontal connections between teachers and students, are being actualized. The authors come to the conclusion that in this case it is most expedient to use the principles of a synergistic approach with the use of appropriate information tools (MOODLE, TANDEM, 1C, etc.). The authors provide the opportunities provided by the synergetic approach to fill the subjective experience with new meanings, the formation and testing of digital competencies within the educational process, and the development of interactive skills. Revealing the legal side of organizing the activities of subjects of educational relations in the digital economy, the authors determined the legal status of digitalization of education in a university, highlighting the main aspects regulated by them. This implies ensuring data security in digital circulation; updating the subject experience of both professional teachers and practical students; organization of project activities and the development of interactive skills and abilities.
Scale-Aware Multi-stage Fusion Network for Crowd Counting

Crowd counting has been widely researched and many hopeful results have been obtained recently. Due to the large-scale variation and complex background noise, accurate crowd counting is still very difficult. In this paper, we raise a simple but efficient network named SMFNet, which focuses on dealing with the above two problems of highly congested noisy scenes. SMFNet consists of two main components: multi-scale dilated convolution block (MDCB) for multi-scale features extraction and U-shape fusion structure (UFS) for multi-stage features fusion. MDCB can address the challenge of scale variation via capturing multi-scale features. UFS provides an effective structure that continuously combines outputs of different stages to achieve the capability of optimizing multi-scale features and increasing resistance to background noise. Compared with the existing methods, SMFNet achieves better performance in capturing effective and richer multi-scale features through progressively multi-stage fusion. To evaluate our method, we have demonstrated it on three popular crowd counting datasets (ShanghaiTech, UCF_CC_50, UCF-QNRF). Experimental results indicate that SMFNet can achieve state-of-the-art results on highly congested scenes datasets.
Security Automation Through a Multi-processing Real-Time System for the Re-identification of Persons

Security personnel frequently require to tediously review multiple camera feeds to track activity. An intelligent re-identification system can solve this problem by re-identifying the same person or object from multiple camera feeds. This study proposes a test-case and solution to accurately track vehicle occupants at a car-park and re-identify them entering/exiting the premises from another feed. Such solution can also be re-purposed to implement a non-ticket based controlled parking system. Our solution utilizes a multi-threaded three-phase approach to provide a dynamic low-cost solution for re-identification. An innovative combination of techniques including human body segmentation, clothes type detection, color features and histogram comparisons are used together to identify a person, saving the feature attributes as tuples within a temporal data structure. Real-time comparisons of feature attributes obtained from two camera process threads are made to perform re-identification. Given the challenge of non-overlapping cameras, it was still possible to re-identify the same person using a combination of extracted features, like clothes type, clothes color features and refined histogram profiles. Standard short-range (10–15 m) and long-range (>15 m) low-resolution car park camera feeds were used to test the performance of our solution. Short-range re-identification achieved an impressive average accuracy of 95.66% with long-range lower-resolution feeds achieving 51.33% accuracy. Most inaccuracies were due to false positives due to low-quality imagery when person was highly distant.
Interval Methods in Knowledge Representation

Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA.
Hole Filling Using Dominant Colour Plane for CNN-Based Stereo Matching

The paper presents a new hole filling strategy, based on the dominant colour plane, for estimating disparity values for the inconsistent disparity regions, called holes, of the disparity map generated after left–right consistency check of left and right disparity maps. The left and right disparity maps are generated by a patch-based stereo matching system using CNN. The holes are typically found near the object boundaries, occluded regions and textureless regions of stereo images. The proposed hole filling strategy is based on the observation that for two dissimilar adjacent regions in an RGB image, normally one colour plane is more discriminating, i.e. the means of the colour values of the discriminating plane in the two regions have larger gap than the other two colour planes. This large gap is used to locate the edge between the adjacent regions. Once the edge is located, the inconsistent disparities are filled by interpolating from the corresponding regions. The proposed method is evaluated on Middlebury datasets and achieves comparable results to the state-of-the-art algorithms.
The Importance of Artificial Rearing of Chironomidae Insect (Blood Worm) as Fish and Shrimp Food

The chironomidae family is related to Order of Diptera. They are called non biting midges. Females will lay egg masses in water. The larva feed on organic material such as organic debris and algae. Due to having hemoglobin in their larval blood, they are called bloodworm. They are able to live in a complete absence of oxygen for several hours. Hemoglobin molecules in the blood bind and hold a reserve supply of oxygen. Chironomus as indicators of organic pollution in aquatic environment. Chironomids were important in the diets of all fish species as well as shrimps. Bloodworms are harvested from mud flats and sold to fisherman or as a food source for domestic pets. In the world there are several centers for artificial rearing of this insect. There are different formulations of blood form which is prepared by different companies in the world. Rearing and artificial culturing this insect is important resource for fishes and shrimps which are the mina important food of human being.
Retrieving Text from Text Fields and Text Editors

User interfaces often need to retrieve text from the user. Sometimes, this text can be a single word or short phrase, but other times this text might consist of several paragraphs. To retrieve text from the user, SwiftUI offers three types of views:
Souvenir Sales Analysis using Apriori Algorithm (Case Study: Ubud-Market Transaction in March 2020)

Ubud market is one of the largest art markets in Bali, there are many local Balinese souvenir traders and craftspeople, most of them are livelihoods depend on buying and selling local souvenirs, Since the Covid-19 pandemic entered in April 2020, Ubud market traders have started to close their business and hoping economic recoveryin future. The author tries to do a track record of souvenir sales transactions in Ubud market to find the last sales pattern before the traders closes their business to give a solution for marketing strategies in future. The sales transaction data will just become meaningless trash if it’s useless.. To get use information about the products that are most sold out at Ubud Market from the transaction database, the author uses the Apriori algorithm. This study was determined final rules on 2 itemset combination, If buying Manik-Manik Craft, Also buy Barong Shirt with the highest confidence 70% and Minimum Support 28%, and for 3 itemset a combination, If buying Celuk Silver, and Barong Shirt, Also buy Manik-Manik Craft with the highest confidence 37.5% and Minimum Support 12%, based on that there are 3 best-selling souvenir products, namely Barong Shirt, Manik-Manik Craft and Silver-Celuk in March 2020.&#x0D; Keywords: Apriori Algorithm, Data Mining, Sales Analysis, Association Rule Mining, Ubud Market.
Teaching and Learning Differently in the Anthropocene

AbstractThis chapter puts together the lessons of the previous four chapters to the benefit of educational practice. Taking a Deleuze/Guattari analysis in and on education is increasingly popular, this chapter distinguishes itself from others in the field with its unique analysis of the Anthropocene, and the added purpose this gives to education. Beyond environmental education, or the SDGs, this chapter shows how the philosophy of Deleuze/Guattari at its most radical, is testament to a significant rethinking of educational mores. Plus, the imperative of changing environmental and human conditions under the Anthropocene, gives fresh impetus to this rethinking. The analysis of chapters two-five shows how we are conditioned, trapped, and turned into parts of the Anthropocene-machine. shows us a way out both locally and globally.