Reviewerly/exHarmony huggingface dataset:
Video adaptive watermark embedding and detection algorithm based on phase function equation

Abstract In order to improve the video watermark embedding strength and balance the transparency of the watermark system, this paper proposes a combination of all phase Biorthogonal Transform and watermark embedding to complete the experiment. Firstly, the all phase biorthogonal transform is described. Referring to the construction process of APBT, combined with APDF and DST, a new all phase biorthogonal transform, all phase discrete sinusoidal biorthogonal transform (APDSBT), is proposed. This paper makes full use of MPEG-2 compression format to embed watermark directly in DCT domain. The low-frequency coefficients in the DCT block of the brightness space of I frame are selected as the watermark embedding space. The brightness component of each image block is transformed by two-dimensional DCT in the unit of 8×8 image blocks. By introducing the idea of energy receiver into the detection of digital watermark, the following correlation detector can be obtained. Implemented with MATIAB and VC + +. In the experiment, the foreman video test sequence is used as the watermark carrier, and the copyright logo image designed by ourselves is used as the watermark image to test the video watermarking system. The results show that when the coding rate is 3Mvps, the accuracy of each plane is 100%, 98.48%, 98.12% and 96.27% respectively. When the coding rate is 2.6Mvps, the accuracy of each plane is 100%, 96.38%, 94.87% and 95.21% respectively. This algorithm selects the frame of video to embed watermark. On the premise of ensuring video quality, this algorithm is robust to common video watermark attacks (MPEG compression, frame loss, frame clipping and frame rearrangement).
MEDIA TEXTS AS A BASIS OF FORMATION OF PRIMARY SCHOOL STUDENTS’ MEDIA LITERACY

For self-realization in the IT-world, the formation of media literacy enables the younger generation to successfully satisfy both their own and social needs; use media safely, consciously and effectively in learning and everyday activities. Elementary school students are particularly vulnerable to the influence of the media. The article highlights the factors that determine the expediency of media literacy formation of primary school students at the current stage of digitalization of education and the transition to forced distance learning: the increase in the volume of information and the problem of choosing reliable sources of information; digitization of the educational process and the need to significantly reduce the age of schoolchildren to use electronic learning technologies; growing aggressiveness of media sources regarding the impact on the audience, in particular, children; students are in high demand for the ability to critically perceive information in order to make informed decisions. The features of media training in primary school are disclosed: anticipatory training in which schoolchildren are offered tasks that have a promising nature; orientation to life experience when choosing tasks; integration of tasks aimed at forming students' media literacy with the material of educational subjects; systematic implementation of media training. It is shown that the key stage in the formation of media literacy of primary school students is work with media texts. Examples of tasks that were offered to elementary school students are given: tasks for the formation of analytical skills, as a basis for working with multi-directional media information; the ability to interpret and critically evaluate media texts of various types; the ability to explore various sources of digital data; awareness of the benefits that IT devices have brought to humanity, as well as the negative factors of their use.
An application of non-dominated sorting genetic algorithm for reversible data hiding based on histogram shifting in neuroimages

This paper presents an application of multi-objective non-dominated sorting genetic algorithm with a modified chromosome encoding for histogram shifting-based multiple reversible data hiding scheme in neuroimages which aims to minimize distortion and maximize capacity. The modified chromosomes encoding scheme is designed according to the zero-bin characteristic of the intensity histogram of the structural magnetic resonance imaging scans of human brain. The experiments of this study is designed to assess the effect of non-dominated sorting for multi-objective optimization compared to Euclidian distance, the convenience of modified chromosome encoding scheme for medical images compared to non-medical images. The performance of the proposed method has been measured in terms of the peak signal-to-noise ratio (PSNR) for image quality and the bits per pixel (bpp) for capacity assessments. The experimental results show that the proposed method is better than its counterparts.
Meteorological Data Analysis of Temperature and Rainfall in the case of Southern Ethiopia (Western Guji, Guji, and Borana zone from 1988-2018)

This research studied meteorological data analysis of temperature and rainfall of Southern Ethiopia specifically Borana, West Guji, and Guji zone starting from 1988-to 2018. The study’s main concern on analysis of nature, trends, and rate of temperature and rainfall change, and lastly focuses on the effect of climate change on crops and livestock. The researchers employed a descriptive research design and both quantitative and qualitative approaches. The researchers employed MicroSoft Excel (Window 13), SPSS-21 version software, application of the Mann–Kendall test, and Sen's methods. The finding of this research was the temperature of all stations/zones of the study area was increased. The average temperature of moyale, Yabello, Bule Hora and Nagele is 23.47°C, 21.40°C, 19.20°C, and 17.41°C respectively and the smallest variation is observed in Bule Hora. The rainfall of the study area in all stations with the exception of Bule Hora, declined and the amount of average rainfall of Negele is much higher than others and followed by Bule Hora and the smallest rainfall was registered in Moyale. The average rainfall of Negele was 114mm, Bule Hora 80.98mm, Yabelo49.50mm and Moyale 44.89mm. The other finding of this research was crop and livestock of the study area where negatively affected. The researchers recommended-communities unity including government, private, NGO have a responsibility to minimize the effect of this climate change in the study area specifically and all developed and developing countries must come together to reduce change in climate and its negative effect in general.
OPLA-Tool-ASP: a Tool to Prevent Architectural Smells in Search-based Product Line Architecture Design

Search-based algorithms have been successfully employed in Product Line Architecture (PLA) design in the seminal approach named Multi-Objective Approach for Product-Line Architecture Design (MOA4PLA). This approach generates a set of alternative PLA designs, which optimize different architectural properties. In addition to these properties, the alternative PLA designs should have as few architectural smells as possible. Architectural smells can negatively impact PLA variability, PLA extensibility, SPL maintainability, and other non-functional attributes. However, one of the main findings of a previous study is that the tool that automates the application of MOA4PLA adversely introduces architectural smells in the automatically generated solutions. In this work, we present OPLA-Tool-ASP, which is a tool that implements guidelines to detect and prevent the architectural smells Unused Interface, Unused Brick, Concern Overload, and Link Overload in the context of MOA4PLA. An empirical study was carried out to assess the effectiveness of OPLA-Tool-ASP in preventing the aforementioned smells in the resulting PLA designs. The obtained results pointed out that the proposed tool is effective in both preventing the smells and improving the architectural properties selected for optimization.
Fetal Contour Extraction Using Level Set Image Segmentation Approach

This paper deals with phase of designing a new hybrid approach of segmentation. The brief description of proposed scheme is presented, followed by the design. The chapter begins with the introduction followed by discussion of experimental results. The proposed segmentation approach is followed by its evaluation and comparisons with existing methods.
PELATIHAN BILINGUAL TEACHING BAGI GURU MTS HIFAL BANYURIP PEKALONGAN

The availability of a bilingual class whose learning process uses two languages ​​of instruction, namely Indonesian and English, is expected to be the answer to problems in an effort to increase the competitiveness of the Indonesian generation to the international world. The application of the Bilingual Class at Mts Hidayatul Athfal (HIFAL) is one of the flagship programs that it has as an effort to improve the quality of students at the school. This is the flagship program of MTs HIFAL, however, there are new challenges for school administrators considering that not all teachers are able to speak English fluently. Therefore, the school really needs Bilingual Teaching training for MTs HIFAL Banyurip teachers, Pekalongan. By holding training through community service activities, it is hoped that the teaching skills of teachers in bilingual languages ​​can be improved. This training also involves native speaker who help participants to practice using English. Bilingual Teaching training activities for MTs Hidayatul HIFAL) teachers provided significant benefits for participants. By participating in these activities, participants gain material and experience that can be applied to the Bilingual class. In the microteaching session, participants have implemented the preparation of bilingual learning tools, the use of Teachers Talk in bilingual learning, the use of ICT in bilingual learning, and the use of cooperative learning methods in bilingual learning. By participating in this training, most of the participants (teachers) seemed more confident in using English for daily communication, especially for teaching. Their speaking and teaching skills using the bilingual language are improved.&#x0D; Keywords: Bilingual; Training; Teaching
Possibility and Challenges of Implementing the International Financial Reporting Standard (IFRS9) In Libyan and Iraqi Banks / Survey Study

The research aims to show the available potentials in the Iraqi and Libyan banking sector in order to implement the (IFRS9) standard.In addition, it aims to identify the most important challenges that may face the application of that standard in those banks, and the disparity in those applicability and challenges in Iraq and Libya.To achieve these goals a questionnaire form has been set by the researchers including four dimensions of applicability and five of the most important challenges facing that application.The research sample includes eight Iraqi banks and seven Libyan banks.(185) valid forms for analysis have been retrieved from the total of the forms distributed to accountants and administrators in those Banks during the year 2020.The research has concluded that there is an agreement among the members of the research sample on the importance of the availability of material, human and technical resources, in addition to supporting government external bodies in promoting the application of the (IFRS9) standard in Iraqi and Libyan banks.In addition , there is a set of challenges that hinder the success of this application.The most important of these challenges is the cost constraint.The research also has found that there is a discrepancy between the Iraqi and Libyan banks in terms of application capabilities, while there is no difference between these banks in terms of ‫ٛأّعٌف‬ ‫إّْجع٢ٌ‬ ‫ٛث٩مضصجه١ز‬ ‫ث٩هثً١ز‬ ‫ٍَعَُٜ‬ ‫ثٍْغٖٞ‬ ‫ّؾَز‬ .‫ثٍْؾَو‬ .( 11 ) ( ‫ثٍعوه‬ 1 ) -( 2021 ) 302 -316challenges, the researchers recommends that efforts should be intensified in banks to make (IFRS9) application successful.
StarCraft Unit Motion: Analysis and Search Enhancements

Real-time strategy (RTS) games pose challenges to AI research on many levels, ranging from selecting targets in unit combat situations, over efficient multi-unit pathfinding, to high-level economic decisions. Due to the complexity of RTS games, writing competitive AI systems for these games requires high speed adaptive algorithms and simplified models of the game world. In this paper we focus on motion prediction and motion planning in StarCraft — a popular RTS game for which a C++ API exists that allows us to write AI systems to play the game. We explore our existing unit motion model of StarCraft and find and fix some inconsistencies to improve the model by accounting for systematic command execution delays and unit acceleration. We then investigate ways to improve existing combat motion planning systems that are based on discrete unit motion sets, and show that search-based algorithms and scripts can benefit from using a new direction set that considers moves towards the closest enemy unit, away from it, and perpendicular to both directions.
PENGEMBANGAN GAME EDUKASI BERASIS ANDROID PADA MATERI SISTEM PEREDARAN DARAH MANUSIA KELAS VB SEKOLAH DASAR NEGERI 03 PONTIANAK KOTA

AbstractIn general, this study aims to describe the development of an Android-basededucational game on the material of the human blood circulation system for class VB,State Elementary School 03 Pontianak City. This study uses research and development(R &amp; D) research methods adapting the ADDIE development model from Dick andCarry which consists of five stages, namely analysis, design, development,implementation, and evaluation. evaluation). As for this development research only upto the fourth stage, namely the implementation stage. The data sources of thisresearch are field expert validators and class VB students of State Elementary School03 Pontianak City. The results of the validity value test carried out by media expertvalidators were 83.92% and material expert validators were 87.5% with the "veryvalid" category. The results of student responses regarding the SIPEDA educationalgame were categorized as "very practical" with a total percentage of 98.26%. Basedon the results obtained, it can be concluded that the SIPEDA educational game is verypractical to use in the learning process.Keywords: Development, Games, Education, Android
Blockchain Performance Optimization Mechanism Based on Caching Strategy

As a distributed system, the research on blockchain related technologies is gradually showing an explosive growth trend. As one of the cores of blockchain, consensus algorithm is mainly responsible for ensuring the security of blockchain system. It has the disadvantages of large overhead and long communication delay. In order to improve the performance of the blockchain system in storing and querying user data, this paper takes the consensus algorithm as the research entry point, and designs the cache optimization raft consensus algorithm (COR), which can effectively shorten the waiting confirmation time in the user data storage stage, so as to improve the efficiency of user data storage. In addition, the system adds a cache layer to its traditional structure, further improve the query efficiency of the system. Finally, the system realizes the goal of system load balancing and improving system query efficiency based on three types: master node, slave node and supervisory information cache node, as well as two data structures: data identifier cache table and resource utilization queue.
Contactless Surveillance for Preventing Wind-Borne Disease using Deep Learning Approach

has been marked as a pandemic worldwide caused by the SARS-CoV-2 virus.Different studies are being conducted with a view to preventing and lessening the infections caused by covid-19.In future, many other wind-borne diseases may also appear and even emerge as "pandemic".To prevent this, various measures should be an integral part of our daily life such as wearing face masks.It is tough to manually ensure individuals safety.The goal of this paper is to automate the process of contactless surveillance so that substantial prevention can be ensured against all kinds of wind-borne diseases.For automating the process, real time analysis and object detection is a must for which deep learning is the most efficient approach.In this paper, a deep learning model is used to check if a person takes any preventive measures.In our experimental analysis, we considered real time face mask detection as a preventive measure.We proposed a new face mask detection dataset.The accuracy of detecting a face mask along with the identity of a person achieved accuracy of 99.5%.The proposed model decreases time consumption as no human intervention is needed to check an individual person.This model helps to decrease infection risk by using a contactless automation system.
Perencanaan Strategis Sistem Informasi Menggunakan Metodologi Ward and Peppard Pada Putra Darmawan Travel Salatiga

Putra darmawan travel is a company engaged in transportation services, located on Jalan Diponegoro No 64, Sidorejo, Salatiga City, Central Java. This company provides travel services, tours, car loans, and express packages. However, in carrying out its business business, this company has not yet applied SI / IT in its company operations, so he recommends to carry out strategic planning of information systems, aiming to assist in the preparation of information systems so that later they can have benefits and be in line with the goals and business processes that exist in the company. The preparation of the strategic design of this information system uses the ward and peppard method, with this method will be carried out several analyzes on the sons of travel darmawan in order to assist in the preparation of information system designs such as SWOT analysis, Value Chain, Five Porter's, Mc Farlan Strategic Grid whose output is in the form of proposed application portfolio recommendations in the form of Making SI Web travel, SI Promotion, SI Cashier, Asset Sim, which can be used as a reference for the putra darmawan travel company to be applied within the next 2-5 years
E-Jobsheet on Electrical Power Installation Course

The purpose of this research is to produce an e-jobsheet on the Electrical Power Installation Practicum that is valid, practical, and effective for electrical engineering students at the Padang State University. The research method used is research and development. The findings of this study are that this research has succeeded in developing an e-jobsheet in the electrical power installation course that has been developed effectively based on the cognitive and psychomotor learning outcomes of students. Based on the difference between the results of the pretest and posttest, it can be concluded that e-joobheet has been effective. The implication of this research is that e-joobsheets can be used by lecturers in charge of electrical power installation courses at the Department of Electrical Engineering, Padang State University.
Deep RRT*

Sampling-based motion planning algorithms such as Rapidly exploring Random Trees (RRTs) have been used in robotic applications for a long time. In this paper, we propose a method that combines deep learning with RRT* method. We use a neural network to learn a sample strategy for RRT*.We evaluate Deep RRT* in a collection of 2D scenarios. The results demonstrate that our algorithm could find collision-free paths efficiently and fast, and can be generalized to unseen environments.
Penerapan Mesin Teknologi Tepat Guna Penggiling Bumbu Pecel Kapasitas 5 Kg/Jam Bagi UMKM Sambi Kerep Surabaya

Indonesia is a tropical country with a very strategic geographical location. Therefore, Indonesia has a variety of delicious culinary delights to serve. Pecel is a culinary dish that has a long history in Indonesian history. Pecel is a favorite food of the Indonesian people, so the number of pieces traders is vast in several areas today. It is making relatively traditional peace seasoning that has inspired researchers to produce appropriate technology products for pecel grinders with a capacity of 5 kg/hour with an electric power of 0.2 kW, which is needed as big as for SMEs in the Sambi Keep area of Surabaya. This TTG machine can increase the amount of pecel seasoning production capacity.
PENGEMBANGAN SISTEM INFORMASI ADMINISTRASI ASISTEN MATA KULIAH PRAKTIKUM DAN RESPONSI DI JURUSAN ILMU KOMPUTER UNIVERSITAS LAMPUNG

The processing system of the administrative information for lab works and problem exercises of the student at the Department of Computer Science, Universitas Lampung, is still carried out conventionally. In this manner, the data is physically stored in the form of recorded documents and leave them on the shelf. Sometimes, data collection in this form can be lost and require a longer time to manage. For this reason, a lab assistant’s information system is developed by the waterfall approach that runs on a web-based platform. The system can provide data and generate information about lab assistants and participants faster and more accurately. It is implemented using the framework Laravel and Black Box testing as a functional test of the system. The testing indicates that the system functions work to the software requirement specification.
masked face identification using the convolutional neural network method

In times of a pandemic like this, masks are part of the main needs in daily activities when outside the home. Because masks can help us avoid the Covid-19 virus, it often happens among people when doing activities outside the home that they forget to wear masks, therefore the level of public awareness of the importance of wearing masks is decreasing. This study aims to create a system that can classify people who wear masks and do not wear masks as an evaluation material for the level of public awareness of the importance of wearing masks. The total data used in this study were 600 data samples which were divided into two, namely 300 data samples wearing masks and 300 data samples not wearing masks. The CNN architecture in this study is the same as the CNN architecture in general, the difference is the depth level of the convolution layer and pooling which consists of 5 convolution layers, 5 max pooling, and finally, 2 layers dense In the training process, it gets the highest accuracy rate of 98%, while in the validation process it gets the highest level of accuracy at 95%. Therefore, the results of these two processes show that the application of deep earning by utilizing the convolutional neural network can classify objects that wear masks and do not wear masks properly. The results of testing the research dataset are quite maximal by using 40 new dataset testing data to test the convolutional neural network that has been created by the researchers to get an overall accuracy result of 97.5%.
Review of an Approach Towards Central Bank Digital Currency

Debesh Bhowmik Ed. (2022). An Approach Towards Central Bank Digital Currency. New Delhi: Kunal Books.(HB,pp 358+xxxxviii,$60). Recently Central Bank digital currencies have emerged as a relevant topic in theoretical and empirical research. In this context, the book An Approach Towards Central Bank Digital Currency constitutes an important contribution since it analyzes the issue of digital currency by considering several aspects like theoretical models, economic policies, postmodern mindset, cybercrime, ecology, regulatory framework, financial stability, cashless payment systems, etc.