Reviewerly/exHarmony huggingface dataset:
The Interplay Between Policy and Technology in Metaverses: Towards Seamless Avatar Interoperability Using Self-Sovereign Identity

This paper explores the interplay between public policy in areas related to digital privacy and security and the development of new metaverse technologies that need to be compliant-by-design. Such interdependency is illustrated here through the proposal of a solution to implement seamless cross-metaverses avatar interoperability that preserves data privacy and portability. The new proposed scheme is based on the Self-Sovereign Identity concept and architectures, along with off-line governance agreements, in order to ensure that avatars can travel between metaverses while keeping whatever attributes they possess and that are compatible in the crossed metaverses. Many new and exciting avenues for technological research arise from such an interdisciplinary perspective.
Full Coverage Path Planning Recombination Framework for Unmanned Vehicles With Multi-Objective Constraints

This article aims to solve the problem of full coverage path planning (FCPP) for unmanned vehicles with multi-objective constraints in an obstacle environment. A novel multi-objective coverage path planning recombination (MCPPR) framework is proposed to enhance the overall performance of the planned trajectory. The coordinate system transformation method is proposed to reduce the proportion of obstacles coverage area and optimize the solution space. Based on the improved FCPP mapping algorithm, a multicell recombination algorithm is developed. The constraints include coverage rate, overlap rate, trajectory length, and cumulative turning angle. An optimal double-layer agent motion and an improved probabilistic roadmaps algorithm are presented to plan obstacle avoidance paths for connecting neighboring cells. The final planning trajectory is smoothed using the Dubins algorithm. An index evaluation method is proposed to translate all indicators into the same quantitative space and to select the optimal trajectory. The results of the simulations and experiments show that the proposed MCPPR framework can provide an optimal solution to the FCPP problem.
Containers and Algorithms

The Standard Library offers an immense number of types and functions, and this number only increases with the release of every new version of the C++ standard. We could not possibly introduce the full range and scope of the Standard Library here in this book. For a contemporary overview of all the possibilities, details, and intricacies of this vast and growing library, we highly recommend the forthcoming C++23 Standard Library Quick Reference by Peter Van Weert and Marc Gregoire. Good online references exist as well, but these make it harder to quickly get a feeling of every single feature that the Standard Library has to offer.
Influence of hand representation on a grasping task in augmented reality

Research has shown that modifying the aspect of the virtual hand in immersive virtual reality can convey objects properties to users. Whether we can achieve the same results in augmented reality is still to be determined since the user’s real hand is visible through the headset. Although displaying a virtual hand in augmented reality is usually not recommended, it could positively impact the user effectiveness or appreciation of the application.
Efficient Net B5: A Robust Approach to Detect Morphed Images

Data traffic is important in the transmission and exchange of numerous types of data in the digital environment of the global web, including files and photographs. However, this data is susceptible to unauthorized alterations, particularly in the form of morphing, necessitating the development of effective detection mechanisms. The proposed system serves the purpose of identifying morphed images and informing users about their authenticityThe globe Wide Web's digital surroundings witnesses a constant flow of data in the form of files and photos. Unfortunately, data is not immune to tampering, and as a result, it becomes imperative to detect instances of such alterations. The proposed method aims to identify and flag modified photographs, providing users with insights into the authenticity of images they encounterThe academic industry has showed a renewed interest in addressing the subject of morph attack detection in recent years. Various studies and methodologies have been explored to accurately detect instances of morphing attacks and enhance the security of digital content.
Normal-Compound Gamma priors with Count Data

Count data models have become very common in several disciplines in recent years. Since these types of models can often be studied incorrectly using OLS methods, several solutions have been proposed to address this problem. One of these methods the normal-scale mixture method with different types of priors of the scale parameter. The importance of this method is to solve the issue of the bias-variance tradeoff by adding a local scale parameter to reduce the variance at the origin and reduce the bias at the tails. In this paper, a compound-gamma prior is placed for the scale parameter and the relevant Gibbs sampler is solved for posterior inference. The comparison of the performance of the proposed model with some other existing methods using both very sparse and low sparsity simulated data shows that the proposed model performs very well.
Models of Trust and Trusted Computations to an Ad-hoc Network Security

Ad-hoc networks have unique properties, making it impossible to execute the current existing network security policy successfully. Based on studying the Ad-hoc network, the Cloud Security theory will be applied to it. We apply Direct Blind Authentication theory and trusted computing platform hardware modules to optimize the Ad-hoc networks' authentication links. The program successfully addresses the security concerns of Ad-hoc nodes, strengthening the Ad-hoc network's defenses.
Decompress Image Using Finite Difference Method

A lot of techniques are represented to have a useful for denoising and in-painting digital images. These techniques are based on a partial differ- ential equations (PDEs). Thus, we need to find the solution of PDEs. In this work, we consider a finite difference method to solve PDEs approxi- mately based on image compression. In addition, we compared the results in different criteria of the errors
Image Compression using Polynomial Coding Techniques: A review

Compression solves the two serious issues of size and transmission efficiently, and various standard techniques are available, such as GIF, JPEG, MPEG, and MP3, in which these techniques combine efficiency, ease of use, and speed with the ability to fulfill a variety of requirements, but there's always a necessity and demand for new innovative techniques to improve the digital realm. Polynomial coding is one of the simple promising compression techniques of modeling base that composed of deterministic part (coefficients) and probabilistic part (residual) to represent image information compactly, there are many models were developed to improve the discipline of this technique performance, where This paper review focused on researchers' efforts to compress grayscale and color images using linear and non-linear lossless and lossy techniques.
Voice separation and recognition using machine learning and deep learning a review paper

Voice isolation, a prominent research area in the field of speech processing, has garnered a great deal of attention due to its prospective implications in numerous domains. Deep neural networks (DNNs) have emerged as a potent instrument for addressing the challenges associated with vocal isolation. This paper presents a comprehensive study on the use of DNNs for voice isolation, focusing on speech recognition and speaker identification tasks. The proposed method uses frequency domain and time domain techniques to improve the separation of target utterances from background noise. The experimental results demonstrate the efficacy of the proposed method, revealing substantial improvements in voice isolation precision and robustness. This study's findings contribute to the increasing corpus of research on voice isolation techniques and provide valuable insights into the application of DNNs to improve speech processing tasks.
Generalization Approximation Spaces Using Combined Edges Systems of a finite number of undirected graphs

In this paper we will study approximate coefficients. New based on a finite family of Lower approximation and Upper approximation and we present a generalization of some concepts and definitions and boundary and we will also study the accuracy factor for this family
Trigonometric Approximation and 2π-Periodic Neural Network Approximation

Many articles studied best trigonometric approximation and many researchers worked on the neural network approximation, but no one related the best trigonometric approximation to neural network approximation. We define trigonometric activation function, then we use it to obtain neural network, which we use it as a best approximation for functions in spaces for . That what we shall introduce in our work have.
Systematic review of sentiment analysis and predict sarcastic

With the rise of social media on the web, sentiment analysis has become one of the most important areas of study. Today, millions of people share their thoughts, ideas, feelings, and opinions on social media sites like Twitter and Facebook. Sentiment analysis, also called opinion mining, is mostly about classifying and predicting how people feel about a certain target. It involves putting text documents or sentences into groups based on how positive or negative they are about a certain topic. Researchers always find "natural language processing" to be one of the most interesting topics. To solve different problems and improve the accuracy of different applications, it is always helpful to know the exact meaning of what is being said in a conversation. Sentiment analysis uses natural language processing (NLP) and learning models like machine learning and deep learning algorithms to figure out how people feel about the data given. Sentiment analysis looks at sarcasm because sarcasm is a way for people to say how they feel about something without saying it directly. People means the exact opposite of what the sentence says at first glance. Sarcasm is hard to figure out because each sarcastic sentence is different. This paper will talk about what has been done in the field of sarcasm detection, the different techniques used, and the problems that still need to be solved.
Deploying Facial Segmentation Landmarks for Deepfake Detection

Deepfake is a type of artificial intelligence used to create convincing images, audio, and video hoaxes and it concerns celebrities and everyone because they are easy to manufacture. Deepfake are hard to recognize by people and current approaches, especially high-quality ones. As a defense against Deepfake techniques, various methods to detect Deepfake in images have been suggested. Most of them had limitations, like only working with one face in an image. The face has to be facing forward, with both eyes and the mouth open, depending on what part of the face they worked on. Other than that, a few focus on the impact of pre-processing steps on the detection accuracy of the models. This paper introduces a framework design focused on this aspect of the Deepfake detection task and proposes pre-processing steps to improve accuracy and close the gap between training and validation results with simple operations. Additionally, it differed from others by dealing with the positions of the face in various directions within the image, distinguishing the concerned face in an image containing multiple faces, and segmentation the face using facial landmarks points. All these were done using face detection, face box attributes, facial landmarks, and key points from the MediaPipe tool with the pre-trained model (DenseNet121). Lastly, the proposed model was evaluated using Deepfake Detection Challenge datasets, and after training for a few epochs, it achieved an accuracy of 97% in detecting the Deepfake
Strength Pareto Evolutionary Algorithm Based on New Fitness Strategy for Multi Objective Knapsack Problem

problems. Many different experiments have shown that the evolutionary algorithm Strength Pareto Evolutionary Algorithm 2 (SPEA2) outperforms other approaches, and this makes it an excellent candidate for inclusion in the final design. According to Strength, one of SPEA2's core concepts, the population is sorted into niches based on the Pareto Front idea. With regard to outcomes this technique has a flaw that is mitigated by adding a fitness density estimator. Weakness in Strength is addressed with an approach called Strength by objective, which aims to include solution who do not dominate or are dominated by others inside the process. In this paper, the results will show a clear superiority of the proposed method comparing with the original method in solving the multi-objective Knapsack problem using three sizes of the Knapsack and the problem size of 750 items which is generated randomly. The comparison results between the proposed method and the other algorithms show outperformance of the Proposed algorithm using the dominance inductor showed the superiority of the proposed algorithm by a percentage of more than 1 %, Thanks to a highly diverse population and the inclusion of solutions that can be improved, the (SPEA2) algorithm's performance has been vastly enhanced by the Objective sorting mechanism
A SURVY of video datasets for anomaly detection and human activity recognition

The computer vision researchers concentrated on the automation of the surveillance system. Many datasets suited for diverse applications have been proposed by research in this subject. in a number of different domains of application Human action recognition may be used effectively, which has the potential to improve many facets of daily life.These contain, among other things, preventing violent act and detecting crimes such as murder, stealing, and property damage, as well as predicting pedestrian activity in traffic. And this study addresses the properties of public datasets used for Human Action Recognition. Researchers develop these distinct anomaly datasets as a result of the availability of security cameras installed in various areas. For researchers to comprehend and develop in this field, It is required to review anomaly detection video datasets. Therefor This study presents a survey for video surveillance activity recognition.
Memory Organization for Image Segmentation Based on Region Growing

A solution is proposed for determining and organizing the size of the FIFO-stack in memory, required for load the coordinates of adjoining pixels in an image segmentation algorithm based on region growing. The FIFO-stack, organized on the idea of a ring multi-bit shift register, is considered, and the expression of memory calculations is performed through storing process in parallel registers. The conditions for maximum loading of the memory stack are formulated, for which an expression is obtained that allowing to accurately determining the required size of the FIFO-stack, which provides memory resources savings.
Literacy Using Food Truck Media in Writing Procedure Texts (Teaching Assistance Program in Educational Units)

The teaching assistance program requires literacy learning activities carried out by students collaboratively with lecturers and teachers. The lack of students' ability to write procedural texts is due to a lack of familiarity with students' literacy activities that support their learning activities. This condition is seen from the students' lack of understanding in analyzing the general structure of the text, resulting in difficulties in creating procedural texts that are good and correct and can be utilized by readers. To overcome this problem, socialization was held which aimed to maximize writing procedural texts using Food Truck literacy media. This Community Service is located at Putra Anda Binjai Vocational School, where the Education Unit Teaching Assistance program is implemented. The methods used in this training are lectures, discussions and demonstrations. The results of the training show that food truck literacy learning can be used as an alternative in improving the ability to write procedural texts, this increases students' creativity in writing creative and useful procedural texts. During the activity, students played an active role in socializing fun learning literacy using Food Truck media "very well". Student activity was implemented by understanding online ordering, work procedures, and practicing making sweet martabak as a fun learning experience.&#x0D;
Developing an English Proficiency Test for Higher Education

Universities worldwide have recognized the significance of assessing students' language abilities to ensure they can actively participate in academic discourse. However, many universities do not have institution-based English proficiency test yet. The aim of the research is to explore the significances of developing university-based English proficiency test, the essential steps involved in crafting it, and challenges in developing a robust institution's English proficiency test. The method used in this research is library research. The results underscore the critical role of an English proficiency test in ensuring academic excellence, promoting global communication, and preparing students for success in an increasingly interconnected world. Developing a well-structured and reliable English proficiency assessment tool starts with a decision to provide a test, developing the test, and followed by those stages connected with test use. Nevertheless, defining test objective and ensuring test validity, choosing the right format, ensuring fairness and inclusivity, preparing substantial cost and resources, adapting for specific contexts are challenges in developing it. In sum, universities can develop a robust English proficiency test by having collaboration with language experts, assessment specialists, and educators, as well as adherence to established principles of language testing and assessment .
The Use of Discovery Learning Model and Authentic Material to Improve Students’ Writing Ability of Procedure Text

The ability to communicate in English, the ability to collaborate, and creativity are needed for SMK graduates, including students of the Multi Media Class. However, English language skills specifically for MM class are still lacking, around 73.46% or 7 students stated that writing is an obstacle. Therefore, Discovery Learning (DL) research using authentic materials was applied to achieve learning outcomes and determine the improvement of students' learning outcomes, especially in composing procedure texts. Classroom action research, where each cycle has stages of planning, implementation, observation and reflection of action, was carried out at SMK Muhammadiyah Aimas through three cycles (6 meetings) involving 13 students majoring in Multi Media class X in odd semester. The teacher acted as the main researcher. Data was collected using tests and product assessment sheets. Data analysis was carried out by comparing the results in cycles I, II and III quantitatively, while observation data was investigated qualitatively. The results showed that Discovery Learning and the Use of Authentic Materials are likely to be effective in improving the learning outcomes of students in class X majoring in Multi Media. In terms of process, students felt that their learning outcomes improved from an average of 73.46 to 81.38. A score improvement was also seen in the students' test results which increased from 46.2% in cycle I to 77.23% in cycle II, and further to 81.38% in cycle III. In conclusion, Discovery Learning and Authentic Material can be an alternative effort to create meaningful experiences in creative learning, independence, and skill in communicating orally and in writing.&#x0D;
Using Small Group Discussions to Examine Students' Perceptions of Recount Text

The purpose of this study is that students are involved in learning reading comprehension through small group strategies in class reading and to find out students' perceptions of learning reading comprehension through small group strategies. This research is a qualitative descriptive design with a case study method. Participants in this study were all students of class VII A SMPN 5 Karawang, and 5 students were interviewed. The data collection technique that the authors use is observation to observe student behavior during learning to read comprehension using small group techniques. In addition, the writer also uses semi-structured interviews to find out students' perspectives in learning reading comprehension using small groups. The data that has been obtained is analyzed using a qualitative technique proposed by Miles &amp; Huberman. The analysis consists of three activity flows, namely: data reduction, data presentation, drawing conclusions/verification. The results showed that students find it helpful to learn reading comprehension with small group strategies because they collaborate with their group mates.
Rancangan API Interoperabilitas Monitoring dan Pelaporan Standar Pelayanan Minimal Bidang Kesehatan Kabupaten Cilacap

The Minimum Service Standards for the Health Sector (SPM-BK) at Cilacap District in 2019 and 2020 showed that no type of basic service has reached the target. This has decreased compared to 2018 where health services at the age of basic education can meet standards. Interoperability is important to integrate SPM data from all health facilities so that data can be accessed easily, quickly and accurately. This study aims to analyze and design the interoperability of information system data in health facilities for reporting SPM-BK. This type of research is operational research using qualitative methods. Data collection was carried out by interviewing and observing user needs (planning and analysis stages), making system architectural designs (design stages), as well as system trials. The results of the in-depth interviews were analyzed using the content analysis method. Evaluation of the system used is carried out descriptive analysis as a basis for analysis of interoperability systems for monitoring SPM-BK data. This research produces an interoperability system that facilitates the process of transferring data so that information can be obtained quickly and accurately. The development of interoperability to help manage data and information still has the potential to be carried out. Development of SPM-BK system interoperability can facilitate reporting. Data information can be easily seen and found and data security can be guaranteed.