Reviewerly/exHarmony huggingface dataset:
Databases in Digital Forensics

While digital forensics (or referred to as cyber forensics in recent times) play an increasingly important role in our current society (or ‘metaverse’), the role of databases in data/evidence acquisition cannot be understated. Therefore, this edited book focuses on a number of operational challenges in identifying and acquiring data of forensic or evidential interest and relevance from the different databases on the computing devices and systems under investigation.
Research on Ma John's Sports Thoughts and Activities under the Background of Physical Decline

By using the methods of documentation, logical analysis, induction and summary, this paper studies the works and speeches of John Ma and the literature on John Ma's sports thought.It is concluded that John Ma is one of the representatives who first came into contact with western modern sports, and the physical education curriculum in Chinese universities was greatly influenced by his thoughts, which had a positive impact on the development of sports in universities and even the whole country at that time in different periods of his life.Up to now, John Ma's physical education thought still has important reference value for the development of college physical education curriculum in China.
A Model for Estimating Subjective Evaluation Values of Video Degradation from Viewers’ Physiological Signals

This paper describes that it is possible to estimate a viewer's five-level subjective evaluation of video degradation with an estimation accuracy of 0.90 or better by using physiological data such as blood volume pulses of viewers.To this end, we conducted an experiment to record participants' EEG, BVP, gaze, pupil diameter, and subjective evaluation values of video degradation while they watched videos.We then created five different datasets from the data and built estimation models using machine learning based on random forest or neural network.As a result, the coefficient of determination for the physiological data with top importance trained by random forest was 0.997.The results contribute to an objective, continuous, unconscious, and quantitative method for estimating Quality of Experience (QoE) during video viewing.Physiological signals.Quality of experience.Video degradation.
Phishing techniques in mobile systems

The rapid development of mobile devices and communication technologies has led to a sharp increase in the number of mobile device users. The mobile device has replaced many other devices and is used for many tasks, from making a phone call to important and confidential tasks such as cash payments. Because a mobile device accompanies a person most of the time, it is very likely that it contains that person's personal and confidential information. Wider use of mobile devices in everyday life has made mobile systems a great target for attacks. One of the most important attacks is a phishing attack, in which an attacker tries to obtain the victim's credentials and impersonate him. This paper analyzes different types of phishing attacks on mobile devices. Mitigation methods are also analyzed - methods of protection against phishing. An assessment of each method and a summary of its advantages and disadvantages are given. Finally, important steps are taken to protect against phishing attacks. The purpose of the work is to cover phishing attacks on mobile systems, inform people about these attacks and how to avoid them.
A Graph Attention Network for Object Detection from Raw LiDAR Data

In this work, we present an attention based feature aggregation technique in graph neural networks (GNN) for detecting objects in LiDAR scan. We first employ a distance-aware downsampling scheme that not only enhances the algorithmic performance but also retains maximum geometric features of objects even if they lie far from the sensor. Our graph attention formulation uses novel neighborhood aggregation strategies through per node masked attention by combining local and self features. The experiments on KITTI dataset show that the proposed method yields comparable results for 3D object detection under GNN models category.
Advanced Management

This chapter introduces multiple advanced features of Harbor, including resource quota management, garbage collection, immutable artifacts, artifact retention policy, Webhook notification and multi-language support. Harbor 2.0 extends the image related functions to OCI artifacts. For example, the remote replication of images supports other artifacts. This chapter mentions both images and artifacts in different scenarios. In most cases, we can consider images as special cases of artifacts. Because images are the type of artifact mostly used, for the ease of understanding, the term “image” is sometimes used when the functions of artifacts are described. Therefore, image and artifact are treated as synonyms in this chapter.
CURRENT EVIDENCE ON BIOINFORMATICS ROLE AND DIGITAL FORENSICS THAT CONTRIBUTE TO FORENSIC SCIENCE: UPCOMING THREAT

Forensics has become an essential part of the disclosure of criminal evidence. A bioinformatics approach in the form of DNA forensics and digital forensics can be a good combination in disclosing digital-based criminal evidence. This study explains how the role of bioinformatics through the digital approach can be a means of forming new approaches in integration with digital forensics, called cyber-bioinformatics. Despite many hopes and challenges ahead, it does not rule out the possibility of criminal cases related to the privacy of human genomic data, so it proposes a new hypothesis, “cyber-bioinformatics.” The role of cyber-bioinformatics is very central in this regard.
The Structure of Bivalvian Community in The Coast of Elak Elak Beach, West Sekotong, West Lombok, West Nusa Tenggara As An Enrichment of Invertebrate Animal Material for Senior High School Students

Elak elak beach has a sea and a coast with a substrate texture that is very suitable as a habitat for Mollusca including bivalves. Bivalves have many roles for the environment, especially in providing food for various other species in the food chain and can be used to determine water quality. This study aims to determine the community structure and distribution pattern of bivalves in Elak Elak Beach and to see student responses to booklets. The method used in this research is the line transect and quadratic method. The results of the study of the bivalves class molluscs found in the Elak Elak Coastal Coast consisted of 11 species belonging to 7 families. The species consists of Anadara gubernaculum, Anadara granosa, Gafrarium dispar, Glycymeris pectunculus, Liconcha ornata, Lucinoma heroica, Mactra grandis, Mactra nitida, Mactra ornata, Donax faba and Trachycardium flavum. The relative abundance reaches 40% where the highest abundance of bivalves is species Mactra grandis with a relative abundance value of 39.39%. The categories of diversity (H') are medium and uniformity (E) is high, and inversely proportional to the dominance value (C) is low. The structure of the bivalves community based on abundance, diversity, uniformity and dominance that has been studied shows the condition of the West Sekotong Elak Elak Beach, West Lombok district, it can be concluded that the community structure is still in normal condition. The distribution pattern of Bivalves on Elak Elak Beach, West Sekotong is divided into 2 types, namely there are uniform and clustered which are seen based on the calculated value of the Morisita dispersion index. Students' responses to booklets are that students respond very well and students are also very positive in responding to booklets as material enrichment about invertebrate animals for senior high school students.
PARENTAL INVOLVEMENT TO OVERCOME SECONDARY STUDENTS’ FOREIGN LANGUAGE ANXIETY

Among the many problems the students faced in learning English, especially in Speaking skill, many of the recent studies mentioned anxiety as one of the common psychological issue. One of the solutions emerged is by being aware and by improving parental involvement in language learning. The aims of this study are to investigate the students’ anxiety during Speaking as well as to describe the parental involvement to overcome students’ Foreign Language Anxiety (FLA). This descriptive qualitative study applied descriptive analysis which focused on the lived experience of secondary students and their parents role to help them to cope up with their Speaking anxiety. Semi-structured interview and classroom observation were used to collect the data. There were 5 students and 5 parents participated. The result showed that the students were anxious the most about Speaking test and during presentation. Another finding also showed that parents involved themselves the most by fulfilling students’ academic needs and give their children encouragement in learning English. This study have implications for parents, students and teachers in the attempt to overcome FLA among EFL students.
Retraction: A Novel approach in Hybrid Median Filtering for Denoising Medical images (IOP Conf. Ser.: Mater. Sci. Eng. 1187 012028)

This article has been retracted by IOP Publishing following an allegation that this article may contain tortured phrases [1]. IOP Publishing has investigated and agrees the article contains a number of nonsensical phrases that feature throughout the paper, masking overlap with previously published work [2], to the extent that the article makes very little sense. This casts serious doubt over the legitimacy of the article and/or expertise of the authors in this topic. IOP Publishing wishes to credit PubPeer for bringing the issue to our attention. The authors neither agree/diasgree to this retraction. [1] R. Seetharaman, M. Tharun and K. Anandan, 2021, Novel Approach in Hybrid Median Filtering for Denoising Medical Images [2] https://pubpeer.com/publications/607D9C7A45287F0DA617AC8BC150B3 Retraction published: 16 December 2022
OCTA Image Enhancement by Using a Deep Learning Method

Optical coherence tomography angiography (OCTA) allows visualization of retinal and choroidal capillaries. In this paper, we propose an enhanced structure-consistent adversarial networks (SCGAN) based on the idea of cyclic consistent antagonism. The SCGAN is to repair vascular blurring or loss caused by low-density image samples. In order to improve the quality of the image while keeping vascular structure unchanged, a CycleGAN network is used to replace de-convolution with bi-linear up-sampling and padding convolutions. A loss of structure consistency is introduced. The final results have quantified the effectiveness of the method where the resolution of superficial retinal images and deep retinal images have significantly promoted.
Knowledge Management Maturity Assessment at Balai Besar POM in Serang

Provincial Office of Indonesian Food and Drug Authority in Serang (BBPOM di Serang), its surveillance area in Banten Province, has cultivated knowledge sharing, including disseminating training results to implement Knowledge Management (KM). However, by evaluation in 2021, the number of knowledges shared in the KM portal is still low. These conditions need further investigation to identify their strengths and opportunities for improvement in implementing KM. This study aims to measure the Maturity of KM implementation at BBPOM di Serang. The methods used are quantitative measurement through surveys, qualitative through interviews, and desk studies. The survey was conducted using APO KM assessment tools to see the maturity gap of KM implementation. The surveys showed a score of 162.34 which means the application of KM is continuously evaluated and improved; the score is categorised as high because there are applicable business processes, namely the Implementation of Personnel Management, Management System, and Bureaucratic Reform. However, from the survey, interviews, and business processes examination, there are opportunities to improve the implementation of KM. Based on these opportunities, solutions are recommended to increase the Maturity of KM implementation.
mlChatApp: Topic Modeling in Online Chat Groups

Most of the time, online messaging group users must scroll and read a large number of irrelevant posts in order to gain a clear understanding of what is being discussed in the group to which they belong. Messaging groups can get congested with unnecessary messages, causing members to miss out on important issues and information. There is a need to assist users of multi-user chat systems in understanding what the group discussion is all about at any particular time without having to read all of the posted messages. This paper describes an approach to discovering topics in online chat groups. In order to extract and categorize subjects from unseen texts in online group discussions. We developed a new multi-user chat system (ML-CHAT-APP) that automatically identifies and categorizes topics within posts/messages as they appear. We implemented a combination of a Latent Dirichlet Allocation (LDA)-based model with Multinomial Logistic Regression. The resulting model was integrated into the ML-CHAT-APP built with Python and Tkinker framework for Graphical User Interface. The results show that the application was helpful in identifying topics in text conversations and adding identified topics as labels to message posts in real-time. Keywords: NLP, Topic Modeling, Latent Dirichlet Allocation; Logistic Regression
ContraCluster: Learning to Classify without Labels by Contrastive Self-Supervision and Prototype-Based Semi-Supervision

The recent advances in representation learning inspire us to take on the challenging problem of unsupervised image classification tasks in a principled way. We propose ContraCluster, an unsupervised image classification method that combines clustering with the power of contrastive self-supervised learning. ContraCluster consists of three stages: (1) contrastive self-supervised pre-training (CPT), (2) contrastive prototype sampling (CPS), and (3) prototype-based semi-supervised fine-tuning (PB-SFT). CPS can select highly accurate, categorically prototypical images in an embedding space learned by contrastive learning. We use sampled prototypes as noisy labeled data to perform semi-supervised fine-tuning (PB-SFT), leveraging small prototypes and large unlabeled data to further enhance the accuracy. We demonstrate empirically that ContraCluster achieves new state-of-the-art results for standard benchmark datasets including CIFAR-10, STL-10, and ImageNet-10. For example, ContraCluster achieves about 90.8% accuracy for CIFAR-10, which outperforms DAC (52.2%), IIC (61.7%), and SCAN (87.6%) by a large margin. Without any labels, ContraCluster can achieve a 90.8% accuracy that is comparable to 95.8% by the best supervised counterpart.
GEOPHYSICAL ACTIVITIES RELATED TO CRITICAL MINERAL MAPPING IN THE SOUTHERN MIDCONTINENT, USA

The southern Midcontinent of the United States is the nexus for several modern airborne geophysical surveys that cover more than a dozen known or prospective critical mineral systems. The effort to upgrade antiquated airborne geophysical data to modern standards began in 2014 over a portion of the Missouri iron metallogenic province and continues today as part of the congressionally mandated Earth Mapping Resource Initiative (Earth MRI). Airborne data for eight adjoining magnetic and radiometric surveys have been collected or are in progress. Once complete, the surveys will form the largest contiguous coverage of high-resolution airborne magnetic and radiometric data in the US to date. These data will form the backbone of the geophysical contribution to mapping critical mineral systems. Collaboration with the State Geological Surveys of Arkansas, Missouri, Illinois, and Kentucky as part of the Earth MRI have identified 15 focus areas that either host or are prospective for critical mineral deposits. The surveys cover areas where 16 critical minerals have been identified including Aluminum (Al), Antimony (Sb), Barite (BaSO4), Cobalt (Co), Fluorite (F), Gallium (Ga), Lithium (Li), Manganese (Mn), Niobium (Nb), Rare Earth Elements (REEs), Strontium (Sr), Tantalum (Ta), Thorium (Th), Titanium (Ti), Vanadium (V) and Zinc (Zn). Some of these commodities are being actively mined, while others have a history of production or have been identified via exploration and research. This presentation will highlight the state of the modern airborne surveys along with a complementary effort to map prospectivity for Mississippi Valley Type Pb-Zn mineralization that incorporates several different geophysical data layers. The prospectivity effort is part of the tri-national Critical Mineral Mapping Initiative (CMMI), a joint effort between the national geoscience surveys of the United States (USGS), Canada (Canadian Geological Survey), and Australia (Geoscience Australia).
Design and Construction of Daily-updating Objective Climate Prediction System Based on the Real-time Forecast of CFSv2

The CFSv2 forecast products have been widely used in climate prediction operation all over the world.Although the real-time forecast is able to basically capture large pattern of climate anomaly, there still exists obvious bias, which may have enormous impacts on predicted result and thus cannot be neglected.Presently, how to smartly use the massive modeling outputs to improve forecast skill is very important for objective prediction.In this paper, a statistical downscaling strategy for correcting systematic bias through recovering modeling-climatology to its observational counterpart is introduced, and with such methodology, an operational platform conducting real-time 1-30d and 10-30d temperature and precipitation objective prediction is constructed for Zhejiang province.Various verification schemes of the Ps score, Pc score, ACC, SCC, RMSE, the absolute bias, relative bias, and sign coherence are applied on long-term temperature and rainfall assessment.Given the behavior of 335 independent forecast ensembles from January 1 st to November 30 th in 2019, predictive ability of the downscaling model is generally satisfying.The performance of the Ps score, Pc score, and ACC are similar, and the skillful ensembles are much more than the skillless ones, especially for the Ps score and ACC.Comparatively, SCC can achieve even higher values.RMSE of the 10-30d temperature and precipitation as well as 1-30d rainfall prediction exhibits distinct seasonality.Result of the 1-30d forecast is moderately superior to that of the 10-30d range.While the capability of 1-30d temperature prediction is close to current operational level, the result of monthly-scale precipitation prediction is statistically better than subjective
Data Recovery Comparative Analysis using Open-based Forensic Tools Source on Linux

Data recovery is one of the forensic techniques used to recover data that has been lost or deleted.Data recovery is carried out if there is a condition where the data that has been owned is deleted or damaged.If the data has been lost or deleted or even tampered with, then a forensic expert has several ways to restore data that has been lost or damaged.One of them is to use a complete data recovery method using forensic tools, namely, TSK Recover, FTK Imager, Foremost Recover, and Testdisk Recover.Unfortunately, tools such as FTK imager and TSK recover have a weakness, namely that some damaged or corrupted data files cannot be restored in their entirety; they can only be recovered but not be opened.This study uses a tool comparison method approach using foremost recover and Testdisk recover.It's just that this method cannot be used using the graphic user interface (GUI) but using the CLI (Command Line) in the LINUX operating system.And the files that have been recovered will be fully recovered.
Design and Research of Intelligent QA System for Flight Crew Operating Manual

Abstract Aviation flight crews rely on a large number of complex standard documents and operation manuals when performing flight tasks. In order to relieve the pressure of manual retrieval of documents, intelligent question-answering technology based on reading comprehension is gradually applied. In this paper, the flight crew operation manual SQuAD dataset is studied and built, based on which the reader-retriever framework of text content-based reading question answering system (TCQA) is analyzed and established. Experiments are conducted to compare the relevant indexes of the QA system with different combinations of reader and retriever models under the open-source tool haystack. Based on the comparison of response speed and retrieval capability, the best model combination is obtained for the flight crew operation manual dataset, and suggestions are made for the model-related performance improvement.
Relação entre o bem-estar subjetivo e o autocuidado em cuidadores em tempos pandêmicos

Self-care refers to disease prevention and health maintenance practices. Self-care capacity can be an important factor in different conditions and contexts and when associated with aspects of an individual's health it can provide direct benefits to this person. During the Pandemic (COVID-19) this ability may be diminished or impaired, and even hindered with affective aspects, influencing their subjective well-being, that is, affecting their assessment of their own well-being. Thus, this study aimed to evaluate the relationship between self-care capacity and the affective attribution (positive or negative) of male and female adults who act as caregivers. The instruments used were a sociodemographic questionnaire, the Positive and Negative Affect Schedule and the Scale to Assess Self-Care Capabilities. After analyzing the frequency of the variables, Pearson's correlation analysis was performed and through it, moderate associations (medium high) were revealed between the measure of positive affect and self-care (r=0.62; p=0.000) and negative affect and self-care, in this case, with a negative coefficient (r=-0.42; p=0.000); thus, this indicates that people tend to have more self-care, have better positive affects and less negative affects, respectively. It was possible to infer the idea that well-being and quality of life are intertwined with the affective attribution of the individual.
Analisis Bahan Ajar Matematika Kelas 5 di Sekolah Dasar

The purpose of this paper is to find out or describe the results of the analysis of open materials for Class V, whether they meet the requirements or characteristics of Class V students. The method we use is quantitative research. This study discusses the importance of teaching materials used in 5SD class. The mathematics teaching materials used in elementary school grade V are the book published by the Ministry of Education and Culture in the Revised Edition of 2018 "Happy to Learn Mathematics". From our analysis, it was found that the material contained in the book was in accordance with the mapping of the material in class V. In general, the material presented was more about finding the concepts learned by students, not finding the application of concepts.