Reviewerly/exHarmony huggingface dataset:
A Multi-Step CNN-Based Estimation of Aircraft Landing Gear Angles

This paper presents a method for measuring aircraft landing gear angles based on a monocular camera and the CAD aircraft model. Condition monitoring of the aircraft landing gear is a prerequisite for the safe landing of the aircraft. Traditional manual observation has an intense subjectivity. In recent years, target detection models dependent on deep learning and pose estimation methods relying on a single RGB image have made significant progress. Based on these advanced algorithms, this paper proposes a method for measuring the actual angles of landing gears in two-dimensional images. A single RGB image of an aircraft is inputted to the target detection module to obtain the key points of landing gears. The vector field network votes the key points of the fuselage after extraction and scale normalization of the pixels inside the aircraft prediction box. Knowing the pixel position of the key points and the constraints on the aircraft, the angle between the landing gear and fuselage plane can be calculated even without depth information. The vector field loss function is improved based on the distance between pixels and key points, and synthetic datasets of aircraft with different angle landing gears are created to verify the validity of the proposed algorithm. The experimental results show that the mean error of the proposed algorithm for the landing gears is less than 5 degrees on the light-varying dataset.
DIGITALNA IMOVINA U PRAVNOM SISTEMU SRBIJE: OSNOVNE KARAKTERISTIKE

Increased importance and availability of different forms of digital assets have resulted in an increased interest of state legislators around the globe for this type of application of modern technologies in the area of finance. Serbian law belongs to a small group of legal systems that already possess comprehensive regulation of digital assets. The main subject of this paper is the analysis of crucial characteristics of the Serbian legal regime of digital assets, with a short review of the solutions contained in the EU Proposal for a Regulation on Markets in Crypto-assets. The analysis has been conducted by determination of the most important characteristics of the Serbian Law on Digital Assets, considered to be the most relevant for its future implementation: 1) defining the main types of digital assets; 2) clear determination of the scope of application of the rules on digital assets; 3) comprehensive regulation of the entire market in digital assets through prescribing rules on the issuance and secondary trading of digital assets, as well as the rules on all market actors present in the digital assets market. A review of the main benefits and risks and problems concomitant to digital assets precedes the analysis of mentioned characteristics of digital assets.
Sentiment-Target Word Pair Extraction Model Using Statistical Analysis of Sentence Structures

Product information has been propagated online via forums and social media. Lots of merchandise are recommended via an expert system method and is considered for purchase by online comments or product reviews. For predicting people’s opinions on products, studying people’s thoughts via extracting information in documents is referred to as sentiment analysis. Finding sentiment-target word pairs is an important sentiment mining research issue. With the Korean language, as the predicate appears at the very end, it is not easy to find the exact word pairs without first identifying the syntactic structure of the sentence. In this study, we propose a model that parses sentence structures and extracts sentiment-target word pairs from the parse tree. The proposed model extracts the sentiment-target word pairs that appear in the sentence by using parsing and statistical methods. For extracting sentiment-target word pairs, this model uses a sentiment word extractor and a target word extractor. After testing data from 4000 movie reviews, the applicable model showed high performance in both accuracy 93.25 (+14.45) and F1-score 82.29 (+3.31) compared with others. However, improvements in the recall rate (−0.35) are needed and computational costs must be reduced.
Measuring and Analyzing Green Economy on Sustainable Development in Iraq

The climatic conditions, global environmental crises and disasters and the exacerbation of the pollution problem have prompted global economic and financial organizations such as the International Monetary Fund, the World Bank and the Organization for Economic Cooperation and Development to reconsider traditional economic models, Which resulted from it the emergence of the concept of green economy. Which made the economy more efficient by increasing the productivity of used resources and directing investments towards sustainable management of natural resources to increase their economic and environmental productivity and their ability to create green jobs and support the poor to the maximum extent possible. Because of the modernity of this economy, developing countries requested not to impose a single model that includes developed and developing economies at the United Nations Conference (Rio + 20) held in the Brazilian capital, Rio de Janeiro in 2012, and the necessity to create a broad concept for a green economy that is flexible and takes into account the disparity in levels of economic development and transformation policies Towards a green economy. Many scientific studies have proven that the development of the relationship between man and the environment was characterized by an increase and an imbalance between environmental degradation and human progress. The earth, with all its surrounding organisms, is the natural home of man who gets it, and many studies and research revealed that the environments in which a person lives can be It causes an increase or decrease in stress on his body, as the uncomfortable environment causes feelings of anxiety or sadness in contrast to a comfortable environment, and a person finds pleasure in nature regardless of his age or culture, and more than two-thirds of people choose to be in a natural environment to get rid of psychological pressure and cure many diseases Psychological and physical. The research aims to activate the role of the green economy in achieving sustainable development and focus on the health aspect. To achieve the aim of the study, the descriptive and analytical approach was used to study the reality of the trend towards a green economy in Iraq and its role in achieving development. A quantitative approach is used to analyze and interpret the impact of the green economy on sustainable development. And through the benchmarks, it was found that there is a relationship between the sustainable development indicators and the green economy index.
Crosswalk among Prominent Open Research Data Repositories

Open Access is a synergised global movement using Internet to provide equal access to knowledge that once hid behind the subscription paywalls. Many new models for scholarly communication have emerged in recent past. One among them is institutional or digital repositories which archive the scholarly content of an organization. While the concept of Open Access opened new arena for institutional or digital repositories in the form of Open repositories. Likewise, the Open repositories for Research Data Management (RDM) are initiative to organize, store, cite, preserve, and share the collected data derived from the research. There are many multidisciplinary and subject specific open repositories for RDM offering exquisite features for perpetual management of research data. The objective of the present study is to evaluate features of popular Open Data Repositories-Zenodo, FigShare, Harvard Dataverse and Mendeley Data. The evaluation provided insights about the key features of the selected Open Data Repositories and which enable us to select the best among them. Zenodo provides maximum data upload limit. While the major features required by a researcher like DOI, File Types, citation support, licenses, search (metadata harvesting) are provided by all three repositories.
What Does a Phishing URL Look Like?

A uniform resource locator (URL) designates a specific Internet resource such as a web page, a text file, a graphics file, or an application program. These are all examples of resources stored on a server. This chapter will show how attackers leverage every part of the URL to encourage users to visit their phishing site. Despite the fact that multiple methodologies are used by security experts to identify phishing URLs, attackers continue to breach existing antiphishing barriers and assault victims.
ImmerSAFE: Immersive Visual Technologies for Safety-Critical Applications

Cyberpsychology, Behavior, and Social NetworkingVol. 24, No. 12 CyberEuropeImmerSAFE: Immersive Visual Technologies for Safety-Critical ApplicationsCompiled by: Giuseppe Riva and Claudia CarissoliCompiled by: Giuseppe RivaAddress correspondence to: Dr. Giuseppe Riva, Humane Technology Lab, Catholic University of Milan, Largo Gemelli 1-20123 Milan, Italy E-mail Address: giuseppe.riva@unicatt.itHumane Technology Lab, Catholic University of Milan, Milan, Italy.Applied Technology for Neuro-Psychology Lab, Istituto Auxologico Italiano, Milan, Italy.Search for more papers by this author and Claudia CarissoliDr. Claudia Carissoli, Faculty of Psychology, Catholic University of Milan, Largo Gemelli 1-20123 Milan, Italy E-mail Address: Claudia.Carissoli@unicatt.itHumane Technology Lab, Catholic University of Milan, Milan, Italy.Applied Technology for Neuro-Psychology Lab, Istituto Auxologico Italiano, Milan, Italy.Search for more papers by this authorPublished Online:7 Dec 2021https://doi.org/10.1089/cyber.2021.29231.ceuAboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"ImmerSAFE: Immersive Visual Technologies for Safety-Critical Applications." Cyberpsychology, Behavior, and Social Networking, 24(12), pp. 851–852FiguresReferencesRelatedDetails Volume 24Issue 12Dec 2021 InformationCopyright 2021, Mary Ann Liebert, Inc., publishersTo cite this article:Compiled by: Giuseppe Riva and Claudia Carissoli.ImmerSAFE: Immersive Visual Technologies for Safety-Critical Applications.Cyberpsychology, Behavior, and Social Networking.Dec 2021.851-852.http://doi.org/10.1089/cyber.2021.29231.ceuPublished in Volume: 24 Issue 12: December 7, 2021PDF download
AI Model Fairness Using a What-If Scenario

This chapter explains the use of a What-If Tool (WIT) to explain biases in AI models, such as machine learning-based regression models, classification models, and multi-class classification models. As a data scientist, you are responsible for not only developing a machine learning model, but also for ensuring that the model is not biased and that new observations are treated fairly. It is imperative to probe the decisions and verify the algorithmic fairness. Google has developed the What-If Tool (WIT) to address model fairness issue in machine learning models. You will look at the implementation of WIT in three possible ML models: ML for regression-based tasks, ML for binary classification models, and ML for multi-nominal models.
HyKernel: A Hybrid Selection of One/Two-Phase Kernels for Triangle Counting on GPUs

We present a new two-phase dynamic triangle counting approach on GPUs. The approach targets graphs with high maximum degrees and high degree standard deviations. The first phase analyzes the edges of the graph and determines the most appropriate list intersection method and thread granularity that achieve the highest performance for each edge. The second phase performs the list intersection based on the decisions made in the first phase. In addition, we improve our static triangle counting kernels used in the two-phase approach, namely the two-pointer and binary-search intersections by (1) introducing a hierarchical binary-search approach that loads the initial levels of the logical search tree into the GPU fast shared memory to reduce redundant accesses to global memory, and (2) reducing search space when the graph is oriented by vertex ID. We also present HyKernel, a hybrid approach that selects between our two-phase dynamic and our 2019 one-phase dynamic approaches using simple heuristics. Lastly, a study of the impact of two graph orientation approaches on the graph preprocessing times and kernel times for our 2019 approach and the proposed two-phase approach are provided. For evaluation, we compare our two-phase and HyKernel approaches with our 2019 submission and the 2019 Champion approach, H-Index. When orienting the graph by vertex ID, our proposed two-phase and HyKernel approaches significantly outperform the H-Index with geomean speedups of 4.0x (up to 31.2x) and 5.1x (up to 31.2x), resp. Our proposed two-phase and HyKernel approaches significantly outperform the H-Index with geomean speedups of 4.7x (up to 26.8x) and 7.2x (up to 43.6x) with vertex degree orientation, resp.
Graph Neural Networks

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Compressed Neural Network for Thermal Array-Based Fall Detection System on Embedded AI

Fall incidents may lead to more serious health issues if not promptly treated. Existing fall detection systems mostly use cameras and are considered a privacy-intrusive approach. Thermal array sensors are considered a privacy-friendly device that does not raise discomfort for users. In this study, we presented a fall detection system using a thermal array sensor with three different deep learning approaches: LSTM, BiLSTM, and GRU. Our model is optimized using the pruning method to further efficiently deployed into Embedded AI. Our result shows that BiLSTM has the most promising result by 99.93% accuracy, 99.73% precision, and 0.057% False Alarm Rate (FAR).
Towards a Standard of Modelling Annotations in the E-Health Domain

A large number of annotation systems in e-health domain have been implemented in the literature. Several factors distinguish these systems from one another. In fact, each of these systems is based on a separate paradigm, resulting in a disorganized and unstructured vision. As part of our research, we attempted to categorize them based on the functionalities provided by each system, and we also proposed a model of annotations that integrates both the health professional and the patient in the process of annotating the medical file.
E-Document Archiving System with SMS Support

The School of Institute of Information and Computer Studies is facing a problem in the submission of the documents every end of the academic year which are requirements of the Director of the IICS before signing the clearance of its faculty members. In order to fast-track the submission of the documents, an alternative solution to solve the current problem was developed, to be known as the “e-Document Archiving System with SMS Support”. Descriptive research design was used to determine whether the objectives of the study were achieved while Developmental research design was used for the developed of the software. The architectural design used in this system was n-tier architecture. Since the developed system will be deployed into local area network connecting office the IICS building, the concerned faculty where can upload and archived documents electronically. The Director could simple download and print documents in real time. A Short Message Service (SMS) Support, was also be used, as additional feature which would play a vital role as a communicating tool, that enables to send notification to concerned faculty members particularly, which required documents and deadline of submission. Based on the result and findings, uploading and downloading of required documents were accessible in real time. The usability of the feature of the developed system was operational and accessible with effectiveness and efficiency, and the performance was appropriate for the need of the users.
A study on Korean university students’ perceptions and attitudes towards their online English reading and writing classes under COVID-19 pandemic

This study paid attention to the characteristics of online classes under the COVID-19 pandemic and was designed to find out the responses of students to online classes conducted in 2021. Ahead of the return from online classes to face-to-face classes, it aims to reflect on students’ attitudes and perceptions of online classes and present discussions on post-COVID-19 classes by examining the degree of satisfaction of students in English reading and writing classes. In order to achieve this, the research was implemented for 15 weeks with 394 university students. The research questions set up for the research purpose are as follows: in online English reading and writing classes, what is the interaction 1) between learners and instructors?, 2) between the learner and the teaching content?, 3) between learners?, 4) between the learner and the system? and finally, what is the satisfaction level with English reading and writing learning? On the whole, students responded positively to online English reading and writing classes, but there was a high negative perception of the communication aspect. Base on the results, some suggestions are made, and discussion points for English reading and writing classes post COVID-19 were proposed.
A Study on Data Augmentation Methods Optimized for Gastric Cancer Classification in Gastroscopy Images

Gastric cancer is the most common cancer in Korea and an effective way to treat gastric cancer is early treatment. Gastroscopy is being performed for early detection of gastric cancer, and this paper proposes Computer-aided Diagnostics(CADx) system that can help gastroscopy. As a model for classifying gastric cancer, we use Xception, which reduces computation and improves performance. Due to the nature of medical images, data augmentation was used to solve the lack of data and overfitting could occur. The data augmentation methods used were AutoAugment and Variational AutoEncoder(VAE). AutoAugment is a data augmentation method using color changes, shear, rotation, etc., and VAE learns to standardize the probability distribution of the data, helping to generate data similar to the original data to capture features. The data augmentation method with the best performance is the augmentation method through VAE, and the recall showed 94.84% of the performance. The data augmentation method optimized for the gastroscopy data set is the augmentation method through VAE. It can help the endoscopy specialist diagnose and increase the gastric cancer complete cure rate.
MAX PRINCIPLE AND UNIVERSAL SPECTRUM OF PERIODS: COMPLEMENTARY FRACTAL DISTRIBUTIONS AS CONSEQUENCE OF RATIONAL AND IRRATIONAL RELATIONS BETWEEN PARTS OF THE WHOLE SYSTEM

The paper discusses the assumption that Mach principle should result in existence of a universal spectrum of periods. It is shown that fragments of such a spectrum were found in time series of fluctuations of various processes. A general approach is considered that demonstrates the emergence of discrete states in the spectra of periods, which is based on two basic concepts: resonance and roughness of a physical system. This approach leads to the existence of two complementary fractal distributions associated with sets of rational and irrational relations between the elements of the whole system. A brief review of works that also consider universal spectra of periods is given.
Experimental Performance Evaluation Among Cloud Infrastructure Providers Under Different Load Levels

Background: Performance testing can estimate the capacity of a web service under requests. Decision-making on the ideal cloud service infrastructures for deploying specific cloud applications is challenging. Goal: Investigation on the performance of cloud infrastructure providers under different load levels. Method: An experimental study evaluated Amazon, Azure, Google, and IBM cloud infrastructure providers in terms of performance under Infrastructure as a Service (IaaS) perspective. Results: The results indicated satisfactory performance in response time and latency among most providers when subjected to up to 300 simultaneous threads. However, this effect decreases as the number of threads increases, and Apdex index value and level of user's satisfaction are significantly reduced under different load levels, mainly for the IBM provider. Besides, the error rate rises substantially at 400 threads, with more critical results for IBM and Amazon providers. Conclusions: Providers show distinct differences across metrics, and the data collected during testings reinforced the potential particularities of cloud infrastructure services for the choice of a provider. Although preliminary, such results can support software companies in selecting a proper infrastructure provider according to particular requirements.
Ethical Rules of the Audit Profession and the Role of Compliance in Narrowing the Expectations Gap between Auditors and Financial Statements Users

The aim of the study is to identify the ethical rules of the audit profession and the role of its commitment in narrowing the expectation gap from the point of view of auditors in Jordan. For the purposes of collecting information related to the subject of the study, the researcher used a questionnaire directed to a sample of 44 auditors all subjected to analysis, and the researcher used descriptive statistical methods, and tested (T-test) for a single sample to test hypotheses. One of the results of the study included the role of auditors to adhere to the ethical rules of the audit profession (integrity, propriety, independence, competence, due professional care, and confidentiality of information) and to a high degree in narrowing the expectation gap. The researcher provided a range of recommendations, the most important of which are: the need for supervisors and regulators of the audit profession to hold conferences, training courses, workshops and seminars with the aim of increasing communication, educating and sensitizing users of financial statements on the nature of the work and duties of auditors to reduce the expectation gap. The need to strengthen the auditors' commitment to audit standards in general and the ethics of the audit profession and the rules of professional conduct in particular through the development of scientific curricula and study plans in the accounting departments of Jordanian universities
A Global Optimization Algorithm for Unconstrained Non-linear Optimization Problems Using Chaotic Neuron Map and Golden Number

This paper presents aninnovative global multi-variable optimization algorithm using one of the best chaotic sequences, the neuron map, a description of which is also provided in the paper. The algorithm uses neuron map in the first stage to move near the global minimum point, as well as in each iteration of the second stage of local search that is done using the N-dimensional golden section search algorithm. The generation and mapping of the neuron variables to the optimization variables along with the stagewise search for the global minimum is explained conscientiously in the work. Numerical results on some benchmark functions and the comparison with a latest state-of-the-art algorithm ispresented in order to demonstrate the efficiency of the proposed algorithm.