Reviewerly/exHarmony huggingface dataset:
Evaluation Method of Big Data Reliability in Electronic Government

In order to ensure the security of big data in e-government, judging the reliability of the data itself has become an important basic task. This paper focuses on the reliability evaluation of e-government big data, analyzes the limitations of traditional iterative filtering algorithms as the starting point for research, and concludes that traditional algorithms cannot resist joint attacks. By reforming the traditional algorithm, a new iterative filtering algorithm is proposed. This method has the advantages of data aggregation, resistance to simple attacks and joint attacks, and is an effective method to evaluate the reliability of data.
The Usability Testessen – An Innovative Framework for Usability Testing in Practice

The knowledge and application of usability methods and practices have not yet found widespread adoption in practice. It is still frequently the case that products are launched on the market that have not been tested for usability once and therefore do not meet the demands and requirements of their customers. This fact seems to be surprising, as customers, especially in the last few years, have developed ever higher demands on the user-friendliness of products and services. Therefore, this paper presents a new framework for testing the usability of products and services - the so-called Usability Testessen. This concept is based on the approach of discount usability engineering developed by Nielsen and is an event that provides a creative and at the same time productive space to test products of several companies free of costs by independent third parties using well-known discount usability methods. Due to the reduction of costs and effort for the preparation and execution of usability tests, this concept is a great advantage especially for small and medium-sized companies and startups, as they usually have to struggle with scarce resources and at the same time high market pressure. In this paper, the individual phases of the Usability Testessen and the stakeholders involved are presented in more detail. A short summary of the key results of a qualitative evaluation should also show that the newly developed concept is very well received in practice.
Prerequisites and Software Installation

This is a hands-on book that describes how to develop computer vision applications in the Python programming language. In this book, you will learn how to work with OpenCV to manipulate images and build machine learning models using TensorFlow.
Evaluation model of computer audit methodologies based on inherent risk

Computer auditing has become a fundamental piece to ensure the success and use of computer systems in organizations. The success or failure of an audit depends on several factors: the IT auditor, based on their knowledge and experience, chooses expertise, tools and methodologies, each of these elements. Incorrect selection of these components may result in subjective audit results and financial losses for the organization. For this, an analysis of computer audit methodologies was proposed, to determine the level of inherent risk that its application would imply. We worked with our own research methodology of quantitative exploratory type, based on the deductive method for selection of parameters related to inherent risk, with a critical perspective for the quantification and interpretation of statistical data. The research was validated with the Delphi method, through surveys with non-comparative scales, applied to expert auditors to confirm the objectivity and impartiality of the evaluation model. The procedures performed demonstrated that it is possible to quantify the level of inherent risk, through occurrence, compliance and prioritization tables. The analysis of the occurrence of parameters associated with the inherent risk will be transparent and impartial to maintain the integrity of the analysis performed.
Hylite: a hyperspectral toolbox for open pit mapping

&amp;lt;p&amp;gt;Hyperspectral imaging is a powerful tool for mapping mineralogy and lithology in core and outcrops, as many minerals show distinct spectral features in the commonly analysed visible, near, short-wave and long-wave infrared regions of the electromagnetic spectrum. High resolution ground and UAS (unmanned aerial system)-based sensors thus have significant potential as a tool for rapid and non-invasive geological mapping in mining operations, exploration campaigns and scientific research. However, the geometrical complexity of many outcrops (e.g. cliffs, open-pit mines) can result in significant technical challenges when acquiring and processing hyperspectral data. In this contribution we present updates to the previously published MEPHySTo python toolbox for correcting, georeferencing, projecting and analysing geometrically complex hyperspectral scenes. We showcase these methods using datasets covering volcanogenic massive sulphide (VMS) mineralisation exposed within open pit mines in Rio Tinto (Spain), and interpret possible structural and lithological controls on mineralization. Potential applications of hyperspectral mapping for grade control, outcrop mapping and the characterisation of different mineral deposit styles are also discussed.&amp;lt;/p&amp;gt;
RESULTS OF IMPLEMENTATION OF PILOT INNOVATIVE PROJECTS ON THE MASS OPEN ONLINE COURSES IN THE SOUTHEAST ASIA

The paper analyses transformations in the organization and management of education in the countries of Southeast Asia, caused by the active processes of the information and economic globalization in the region. It is noted that in the states of Southeast Asia there are historically established prerequisites uniting the peoples living there with a common historical path, cultural traditions, ideology and religions (primarily Buddhism and, to a lesser extent, Islam), recently, they have also been supplemented by multifaceted experience in reforming the national educational sphere in response to current challenges. Particular attention is drawn to the use of the information and communication technologies (ICT) in the educational process at all levels, national projects for the development of distance education (DE) and regional peculiarities of creating and conducting the mass open online courses (MOOC) in the countries of the region. It is shown that the educational potential of ICT is considered by the regional governments of these countries as a significant source of innovation, which will allow in the very near future to smooth out socio-economic inequality in the region and increase the competitiveness of national economies. The exchange of experience in this area is of undoubted interest for the rest of the world, primarily for countries with a similar socio-economic situation.
Discovery of Arbitrary-Shapes Clusters Using DENCLUE Algorithm

One of the main requirements in clustering spatial datasets is the discovery of clusters with arbitrary-shapes. Density-based algorithms satisfy this requirement by forming clusters as dense regions in the space that are separated by sparser regions. DENCLUE is a density-based algorithm that generates a compact mathematical form of arbitrary-shapes clusters. Although DENCLUE has proved its efficiency, it cannot handle large datasets since it requires large computation complexity. Several attempts were proposed to improve the performance of DENCLUE algorithm, including DENCLUE 2. In this study, an empirical evaluation is conducted to highlight the differences between the first DENCLUE variant which uses the Hill-Climbing search method and DENCLUE 2 variant, which uses the fast Hill-Climbing method. The study aims to provide a base for further enhancements on both algorithms. The evaluation results indicate that DENCLUE 2 is faster than DENCLUE 1. However, the first DECNLUE variant outperforms the second variant in discovering arbitrary-shapes clusters
Research on Technology of Sea Emergency Rescue Based on Unmanned Surface Vehicle

Abstract Based on the advantages of small size, easy to carry by large ship, high speed, flexible mobility, no need to drive by human, high autonomy, the Unmanned Surface Vehicle (USV) is very suitable for the sea emergency rescue. During rescue, the USV needs to track the castaway, and it needs to sail to the downstream position of the castaway in the shortest time to release the life-saving equipment. In this paper, the technology of sea emergency rescue of USV is researched, the motion of the castaway is established, and the downstream position and velocity of the castaway is predicted based on Kalman Filter (KF). In addition, the motion model of the USV is established, and the target tracking based on the Dynamic Window Approach (DWA) is carried out, which will guide the USV to reach the rescue position, and local obstacle avoidance is carried out near the castaway to avoid collision. The rescue strategy does not need to consider the influence of the weather on the position of rescue, so it has high adaptability. Finally, the rescue strategy is simulated, the simulation results validate it works effectively.
Using Conditional Generative Adversarial Networks to Boost the Performance of Machine Learning in Microbiome Datasets

The microbiome of the human body has been shown to have profound effects on physiological regulation and disease pathogenesis. However, association analysis based on statistical modeling of microbiome data has continued to be a challenge due to inherent noise, complexity of the data, and high cost of collecting large number of samples. To address this challenge, we employed a deep learning framework to construct a data-driven simulation of microbiome data using a conditional generative adversarial network. Conditional generative adversarial networks train two models against each other while leveraging side information learn from a given dataset to compute larger simulated datasets that are representative of the original dataset. In our study, we used a cohorts of patients with inflammatory bowel disease to show that not only can the generative adversarial network generate samples representative of the original data based on multiple diversity metrics, but also that training machine learning models on the synthetic samples can improve disease prediction through data augmentation. In addition, we also show that the synthetic samples generated by this cohort can boost disease prediction of a different external cohort.
RETRACTED CHAPTER: Software Project Planning Through Comparison of Bio-inspired Algorithms

Currently many organizations have adopted the development of software projects with agile methodologies, particularly Scrum, which has more than 20 years of development. In these methodologies, software is developed iteratively and delivered to the client in increments called releases. In the releases, the goal is to develop system functionality that quickly adds value to the client’s business. At the beginning of the project, one or more releases are planned. For solving the problem of replanning in the context of releases, a model is proposed considering the characteristics of agile development using Scrum. The results obtained show that the algorithm takes a little less than 7 min for solutions that propose replanning composed by 16 sprints, which is equivalent to 240 days of project. They show that applying a repair operator increases the hypervolume quality indicator in the resulting population.
RAPIDMINER’S IMPLEMENTATION IN ANALYZING STUDENT MAINSTREAM DATA

Mainstream is the choice of course to be a guide for students to be attentive in terms of knowing the abilities possessed by each student. C4.5 algorithm method is a method used for predictive classification that aims to find patterns from relatively large to very large data. Rapidminer is a computer application that is used to process data so the data can be useful information. Based on the result of rapidminer implementation in analyzing student mainstream shows the value of achievement index can be the basis for students to know the abilities they have. Keywords: C4.5 algorithm; mainstream course; rapid miner
Multiuser Virtual Reality for Designing and Editing 3D Models

This research proposes the development of a virtual reality system in which multiple users could collaboratively design and edit 3D models. In the virtual environment, users also obtained the rendered version of the actual environment using the Kinect’s point clouds. The proposed system provides several features of model building, coloring, realistic dimensions of actual environment, user’s collaboration, and STL file exporting for 3D printing.
Implementation of Immersive Virtual Reality Through the Analysis of Diegetic User Interface

The primary factor in virtual reality is an interaction between user and system. To maximize the user’s feeling of immersion, a user needs a user interface that can naturally interact with the system in virtual reality. In this paper, we introduce our VR learning program for the constellation that can enhance the user’s sense of immersion using the diegetic UI in the VR environment. In order to utilize diegetic UI for immersion in VR learning content, we classified the diegetic UI that is mediated as an element in the VR environment into the following three types in our VR project. First, the diegetic UI mediated as a place can provide a realistic experience as a friendly place where we can visit easily even in ordinary times or a fantastic experience as an imaginary place that is hard to experience in reality. Second, the diegetic UI mediated as an agency plays a role in virtual reality in which the character becomes the subject of the story or helps the story progress in virtual reality. Third, the diegetic UI mediated as sensory is not limited to audiovisual as a means of interaction in virtual reality, but it enhances immersion by increasing interaction by utilizing all human senses.
Quasi self-dual codes over non-unital rings of order six

There exist two semi-local rings of order 6 without identity for the multiplication. We classify up to coordinate permutation self-orthogonal codes of length n and size 6n/2 over these rings (called here quasi self-dual codes or QSD) till the length n = 8. To any such code is attached canonically a ℤ6-code, which, when self-dual, produces an unimodular lattice by Construction A.
EFFICIENCY OF BIOMETRIC RECOGNITION TECHNOLOGY BASED ON TYPING DYNAMICS IN MOOC

One of the problems that require a solution in Massive Open Online Courses (MOOC) is the lack of identification and authentication of the students. Different investigations have been carried out through several navigation, physiological and behavioral methods, achieving different recognition scales. Biometric authentication by keystroke patterns (Ups&amp;Downs) has been implemented in several MOOCs for the ease of the digital platforms of the offeror to solve the identification problem. The objective of this research is to analyze the independence of the keystroke tool of the other demographic, sociographic and behavioral variables within a MOOC, establishing an initial pattern, and two authentication measurements throughout the course. The results show that the keystroke is independent of the analyzed variables, and it is reliable to identify the students in qualitative tests with extension answers.
Research on the strategy of optimizing the discipline layout of environmental geosciences under the National Natural Science Foundation of China

Optimizing the discipline layout is an important task for deepening the reform of National Natural Science Foundation of China. The discipline of environmental geosciences (DEG) has a short history and is not perfect in the discipline layout and system framework. The DEG takes the opportunity of optimizing the discipline layout and proactively responses to the top-level strategy of “Habitable Earth-Earth System Science”, initiated by the Department of Earth Sciences. Based on a wide range of strategic research, the establishment background of DEG was reviewed, and the challenges of DEG in terms of research objects, theoretical systems, technical methods, and research paradigms were analyzed. The overall concept of optimizing the discipline layout of DEG was clarified, namely basic disciplines, interdisciplinary disciplines, cutting-edge fields, new technologies and methods, and national needs. Based on the overall concept of the discipline layout, the discipline framework of “four beams and eight pillars” was established. Four basic disciplines constitute the “four beams”: Soil science (D0701), environmental water science (D0702), environmental atmospheric science (D0703) and environmental biology (D0704). Four interdisciplinary disciplines and four cutting-edge fields together constitute the “eight pillars”. The four interdisciplinary disciplines include engineering geological environment and disaster (D0705), environmental geology (D0706), environmental geochemistry (D0707) and ecotoxicology (D0708). The four cutting-edge fields are environmental pollutant behavior and environmental effects (D0709), environment and health risks (D0710), quaternary environment (D0711), environmental information and environment forecast (D0712). New technologies and methods of DEG (D0713) are the support of the discipline. Regional environmental quality and safety (D0714) and environmental protection and sustainable development (D0715) are the major objectives of DEG to serve national needs. Combining the characteristics and advantages of DEG to serve national needs, the connotation of DEG is defined as pollution environment, ecological environment, disaster environment and healthy environment. The existing problems of the discipline application codes were identified, including incomplete code system, unsmooth logical relationship between codes, and unbalanced code level and size. The preliminary adjustment proposals for the application codes were put forward. This study is for related researchers to discuss and promote the high-quality development of DEG.
Computer Model and Analysis on Pavement Performance and Pavement Structure of Polypropylene Fibre Material Concrete

Abstract With the great progress of road construction ability and construction technology, new materials are constantly developed, the choice of road surface materials is more diversified, and the pavement structure is more reasonable and the performance is more optimized, which brings great convenience for the first paving and later maintenance of the road. In this paper, by studying computer modeling and analysis technology, the polypropylene fiber concrete pavement in the road is analyzed and studied, and the experiment is designed in detail to describe the current actual situation, and the conclusion is drawn for study and research reference.
Medical images contrast and detail enhancement using a multiscale morphological approach

Medical images are used to analyze and diagnose diseases. The analysis of these diseases requires images with high contrast and detail, because they contain important information about the disease. Capture methods are improving every day, but sometimes the quality of medical images is not adequate to make a good medical diagnosis. Some common problems are ambient noise, poor lighting conditions, or technical limitations of the devices generating low quality medical images. For these cases, contrast enhancement techniques, which enhance the visual quality of the images, are generally useful. However, there is still room for improvement. In this paper, we propose a novel algorithm to improve the contrast and detail of medical images. This proposal is based on a multiscale morphological approach that uses two structuring elements in the top-hat transform. The simulations were performed with medical images taken from public repositories. The experimental results show that the proposal enhances local contrast and improves the details of the medical images.
Privacy and Challenges to Data-Intensive Techniques

Internet is spreading worldwide, and many improvements have occurred in various fields such as education, business, and financial services. Although we have seen many revolutions with many advantages, there are some disadvantages too, where cyberattacks have played a pivotal role that damages computers and information stored in computers. The user data is crucial information, and protection plays a prominent role in managing the specialized tools and techniques in daily life; we could see that every action is linked with data and protection is very essential. Cyberattacks have increased day by day, and we need to protect and secure the information against the threats. Cybersecurity adopted its approaches and principles of security to receive the integrity to which this one is designed when the information is shared or used. Privacy maintaining is one of the biggest challenges to design efficient tools and techniques; this chapter deals with its intended intensive approaches. In relation to the cryptographic methods, authentication and authorization are providing credentials to authorized users with encryption and decryption on secure sensitive information.
Towards Trustworthy Perception Information Sharing on Connected and Autonomous Vehicles

Sharing perception data among autonomous vehicles is extremely useful to extending the line of sight and field of view of autonomous vehicles, which otherwise suffer from blind spots and occlusions. However, the security of using data from a random other car in making driving decisions is an issue. Without the ability of assessing the trustworthiness of received information, it will be too risky to use them for any purposes. On the other hand, when information is exchanged between vehicles, it provides a golden opportunity to quantitatively study a vehicle’s trust. In this paper, we propose a trustworthy information sharing framework for connected and autonomous vehicles in which vehicles measure each other’s trust using the Dirichlet-Categorical (DC) model. To increase a vehicle’s capability of assessing received data’s trust, we leverage the Enhanced Super-Resolution Generative Adversarial Networks (ESRGAN) model to increase the resolution of blurry images. As a result, a vehicle is able to evaluate the trustworthiness of received data that contain distant objects. Based on the KITTI dataset, we evaluate the proposed solution and discover that vehicle’s trust assessment capability can be increased by 11 − 37%, using the ESRGAN model.
A Method of Text Extremum Region Extraction Based on Joint-Channels

Natural scene recognition has important significance and value in the fields of image retrieval, autonomous navigation, human-computer interaction and industrial automation. Firstly, the natural scene image non-text content takes up relatively high proportion; secondly, the natural scene images have a cluttered background and complex lighting conditions, angle, font and color. Therefore, how to extract text extreme regions efficiently from complex and varied natural scene images plays an important role in natural scene image text recognition. In this paper, a Text extremum region Extraction algorithm based on Joint-Channels (TEJC) is proposed. On the one hand, it can solve the problem that the maximum stable extremum region (MSER) algorithm is only suitable for gray images and difficult to process color images. On the other hand, it solves the problem that the MSER algorithm has high complexity and low accuracy when extracting the most stable extreme region. In this paper, the proposed algorithm is tested and evaluated on the ICDAR data set. The experimental results show that the method has superiority.