Reviewerly/exHarmony huggingface dataset:
Filtering And Enhancement Of Lung Computerized Tomography Images For The Diagnosis Of Covid-19 And Lung Cancer

Recently, the rapid spreading of coronavirus (Covid-19) has created a pandemic situation all around the world. Early diagnosis is the only way to control the spread of coronavirus. Another major threat to the human community is the increasing number of lung cancer patients. In this complex scenario, lung computerized tomography (CT) images can be effectively used for early identification of Covid-19 patients and lung cancer patients as well. These CT images are processed using Computer Aided Diagnosis (CAD) techniques by the usage of suitable algorithms. To improve the accuracy of this diagnosis, effective restoration and enhancement techniques are essential. In this paper, a novel algorithms is proposed for CT image restoration and enhancement. Specifically, a new algorithm called 2D Improved Anisotropic Diffusion Bilateral Filter (2D IADBF) is proposed for the effective noise removal from the CT lung images. The proposed restoration algorithm is compared with other algorithms like 2D Median Filter, 2D Log Filter and 2D Frequency Domain Wavelet Filter. This comparison is performed using filtration metrics like peak signal to noise ratio (PSNR) in dB, mean square error (MSE)and processing time. For the enhancement of the restored images, a new algorithm called 2D Edge Preservation Efficient Histogram Improvement (2D EPEHI) algorithm is proposed. The efficacy of this algorithm is proved by comparison with other algorithms like Contrast Limited Adaptive Histogram Equalization (CLAHE), 2D Adaptive Mean Adjustment and Image Coherence improvement algorithms. The enhancement algorithms were evaluated using metrics like Structural Similarity Index (SSIM) and Absolute Mean Brightness Error (AMBE). Performance analysis clearly show that the proposed restoration and enhancement algorithms produces best results compared to other traditional algorithms. Thus, these algorithms can be effectively used in the clinical pathway for the early diagnosis of Covid-19 and lung cancer.
Using Spatial Awareness

In this chapter, we’ll learn how to use one of the most defining features of Windows Mixed Reality headsets such as the HoloLens: spatial awareness. We’ll learn how to apply spatial awareness in Unity using the Mixed Reality Toolkit and unwrap some neat tricks that you can do with spatial awareness.
The interactive effect of institutional quality and financing on entrepreneurship development in selected MENA countries

Entrepreneurship is the driving force of economic activities that need financing. Institutional quality and financing have always been serious issues for entrepreneurs to start a business and develop entrepreneurship. This study investigates the interactive effect of institutional quality and access to credit on entrepreneurship development in selected MENA countries during 2005-2019. The research method is descriptive and the data are obtained from the Global Entrepreneurship Watch Institute, the World Database and UNESCO, and the panel data approach has been used to estimate the models. Diagnostic tests as well as F-Limer and Hausman tests have been performed to choose between least squares (LS), fixed effects or random effects methods. The results show that the interaction between institutional quality and sources of credit has a positive and significant effect on entrepreneurship development. Therefore, the development of institutional quality reform can affect the development of entrepreneurship.
On Agglomerative Hierarchical Percentile Clustering

Cluster analysis aims at grouping objects represented by some feature vectors and as such revealing insight into subset structures among the considered objects.However, in many cases, the observations are subject to experimental errors and/or uncertainty.In such a case, a popular way is to summarize first the information about each object and, then, aggregate the objects via some cluster algorithm.The percentile clustering by Janowitz and Schweizer, instead, considers the whole distribution of observed features and, only afterwards, aggregates them.Here, we revisit this approach in an agglomerative clustering perspective.Moreover, we perform a simulation study showing some finite sample performance of the algorithm.Some case studies illustrate the advantages of the whole methodology.
Python Essentials for a Geologist

Chapter 2 provides the basics to start working with Python. It introduces the IPython console, Python variable types, and style conventions, and then describes how to start working with Python scripts in the Spyder Integrated Development Environment (IDE). It also explains how to perform conditional statements and loops, and how to define a function and perform basic mathematical operations.
Three-dimensional Transfer Functions of Interference Microscopes

Three-dimensional transfer functions (3D TFs) are generally assumed to fully describe the transfer behavior of optical topography measuring instruments such as coherence scanning interferometers in the spatial frequency domain. Therefore, 3D TFs are supposed to be independent of the surface under investigation resulting in a clear separation of surface properties and transfer characteristics. In this paper, we show that the 3D TF of an interference microscope differs depending on whether the object is specularly reflecting or consists of point scatterers. In addition to the 3D TF of a point scatterer, we will derive an analytical expression for the 3D TF corresponding to specular surfaces and demonstrate this as being most relevant in practical applications of coherence scanning interferometry (CSI). We additionally study the effects of temporal coherence and disclose that in conventional CSI temporal coherence effects dominate. However, narrowband light sources are advantageous if high spatial frequency components of weak phase objects are to be resolved, whereas, for low-frequency phase objects of higher amplitude, the temporal coherence is less affecting. Finally, we present an approach that explains the different transfer characteristics of coherence peak and phase detection in CSI signal analysis.
Multi-sensor Multi-Bernoulli target tracking algorithm based on measurement fusion

This paper proposes a multi-sensor measurement fusion multi-Bernoulli filter to solve the problem of multi-target tracking. A greedy measurement fusion partitioning mechanism based on the multi-Bernoulli filter (MeMBer) is proposed. First, simultaneous selection and fusion of the measurement of different sensors are carried out. Then, the selection of the subsets and the operation of the partition are carried out through the greedy algorithm. In the updating stage of multi-Bernoulli filter, the multi-Bernoulli posterior is updated by using the measurement set after quasi-partitions on the basis of MeMBer filter. Simulation results show that the proposed filtering algorithm can estimate the number and state of multiple targets stably and effectively, and the OSPA error of tracking results is smaller and the cardinality estimation is more accurate than multi-sensor greedy multi-Bernoulli filter.
Player Immersion and Music

When players are “immersed” in a game, they become temporarily unaware of the existence of the outside world. Audio creators have a heavy responsibility to make each game experience as engrossing, or immersive, as possible. The choices can greatly enhance the player’s connection to the game world, or just as easily can be a distraction that detracts from his or her experience. There are certain factors that make game immersion unique compared to other forms of media immersion, and they stem primarily from interaction. This chapter will discuss how music affects player immersion, then will dive deeper into how the player interacts with the music.
Keputusan Promosi Efektif dengan Metode Oreste Fuzzy Multiple Attribute Decision Making (FMADM) pada UMKM Gosimplywedding Sukabumi

Wedding Organizer is a service business for preparing wedding events. Since its establishment in 2015 to 2020, the Wedding Organizer in Sukabumi with the Gosimplywedding brand has carried out several sales methods to get clients, including Canvassing, Online Social Media, Internal Marketing, Marcomm Development, and Offline Shows. The Decision Support System required by management uses the FMADM method, in order to find the optimal alternative from a number of methods that have been used. The results of the calculation of Gosimplywedding sales data from 2017 to 2020 produced a method with Online Social Media in the first order with a value of 16 which is the smallest value ranking. This method is considered the most effective and most generates brand sales so that it can be used as a decision by management for the following year.
Blockchain-Based Power-Out Insurance Design and Practical Exploration

The rapid development of blockchain technology has spawned more innovative applications in the insurance industry, and its multi-entity participation system and subversive trust mechanism will accelerate the construction of new ecosystems in the insurance industry. In this paper, blockchain is utilized to build an efficient mutual trust application platform with its technical characteristics such as decentralization, immutability, trustlessness, etc. And a new business model in the power industry of precise calculation and automatic claim settlement according to customers' electrical properties and terminal power outage signals was designed. An effective hedge of power failure happening to the customers was realized, and the power-out insurance was created. Moreover, the value of power data was realized, a new type of industry-finance business model was set up, and a profit growth for both the power companies and the insurance companies was created. It shows the validity of the 'blockchain + insurance' mode in constructing a mutual trust, mutual benefit and win-win power-finance ecosphere.
Simulador educativo para la prevención de accidentes de tránsito en el Ecuador

INTRODUCTION. Educational simulator is a program designed with the purpose of facilitating the teaching and learning processes, allowing the communication of some type of information. In another conceptual category, traffic accidents are known to result from extreme human and material losses. OBJECTIVE. Implement an educational simulator for the prevention of traffic accidents in Ecuador. METHOD. The bibliographic-documentary modality was considered, due to the consultation in sources of scientific information related to the identified problem. For the development of the simulator, he focused on the ADDIE model, whose objective is to manage in a general way how the tasks are completed. OUTCOME. An educational simulator was achieved, very flexible according to the knowledge for the prevention of traffic accidents according to module N ° 1 of the book of professional drivers by labor competencies of Ecuador. CONCLUSIONS. The educational software is designed to support people who do not have knowledge about road information, they can be linked in order to reinforce knowledge, in addition, it is essential that this application in the future works in a web environment and on mobile devices.
Islamic Education Content Platform for Secondary School Students

The rapid development of information technology has affected various aspects of life including education at the school level. However, conventional teaching and learning methods are still used in secondary schools, especially for Islamic subjects. One of the ways to help students learn better in Islamic subjects is by implementing a web-based content platform in the context of Islamic education. This is a learning tool to support the teaching and learning process using various media such as educational video materials for secondary school students, because multimedia elements will make learning more interesting especially for Islamic subjects that require memorization, reading, and comprehension. Another desired goal is for teachers to be able to manage their Islamic lessons online. In developing web applications, appropriate development methodologies have been implemented using Waterfall Model as a guideline. The waterfall model has different development phases such as analysis, design, implementation, testing and finally documentation. The web-based Islamic Education Content Platform (IECP) was designed and developed using Visual Studio Code with PHP and MySQL databases. It was assessed by obtaining Expert Review (ER) through a set of questionnaires given to four experts and fifteen respondents through User Acceptance Test (UAT). The results of ER indicate that web-based IECP is suitable for use and currently need to be refined and improved. Meanwhile, the UAT results show that web-based IECP is generally accepted and believed to be beneficial, especially to secondary school students and teachers.
Practical Exploration of “ 1+X” Certificate System in the Automotive Field of Higher Vocational Colleges

One of the most important innovations in the development of modern education in China is the “1+X” certificate system. The main purpose is to cultivate compound talents and is an important measure to improve the economic and social level. Taking the automobile major of higher vocational colleges as an example, this article mainly elaborates the necessity of the “1+X” certificate system and the difficulties faced by colleges and universities in the implementation of the “1+X” certificate system, and puts forward some strategic suggestions for this purpose.
DAYA PRAGMATIK TINDAK TUTUR GURU DALAM PEMBELAJARAN BAHASA INDONESIA PADA SISWA SMP NEGERI 3 KOTA BOGOR

PRAGMATIC STYLE OF TEACHER SPEECH IN INDONESIAN LANGUAGE LEARNING FOR JUNIOR HIGH SCHOOL STUDENTS (SMPN 3 Kota Bogor)The aims of this research are to describe: (1) the types of speech acts are used by teachers in classroom learning Indonesian VIII F SMP Negeri 3 Kota Bogor, (2) Pragmatic power contained in the speech act Indonesian teacher class VIII F SMP Negeri 3 Kota Bogor. This research method is descriptive kualititatif. Data sources used are documen, events, and informants. This study use is triangulation of data and methods. This study uses a model that consists of an interactive analysis of data reduction, data display, and conclusion. The results of this research is: (1) the typeof speech act learning Indonesian teachers in class VIII F SMP Negeri 3 Kota Bogor, ie speech acts locutions, ilokusi speech acts, speech acts perlokusi. Ilokusi speech act consists of (a) representative speech act consisting of states, and the mentioning; (b) directive which consists of speech acts ordered; (c) commissive consisting of speech acts promised; (d) consists of expressive speech acts criticized and praise; (e) a declaration that consists of speech acts prohibited and decide. (2)Power pragmatic speech actis realized through a directive, contained in the speech act Indonesian teacher in class VIII F SMP Negeri 3 Kota Bogor very strong against the students, namely: (a) provide information, (b) affect (c) ordering, (d) reprimand, (e) criticize, (f) suggests, (g) praise. (h) determine, (i) quip, (j) scolded.
Comparative Study of Software Defect Prediction and Analysis the Class using Machine Learning Method

An automatic mode that increases sample stability is checked to verify the software design. Predict software flaws are the main focus of the engineering department. Computational software engineering is one of the active study areas of a software flaw. Depending on the metric, software quality and the efficient allocation of volume resources can easily improve defect quality, thus reducing costs. Many data mining and datasets can be used to store defect prediction software. Machine learning software defect prediction technology is an important branch of the computer. Therefore, in this method is to develop the defect prediction obtained by the design of selected class function metrics to create an effective error finding model. Various models have been proposed to reflect the changing changes in the software product's defect prediction index. These models also validate the data of the corresponding software module. The software defect analysis uses various software products for performance metrics to predict. It helps to find a different relationship between software volume and error size. Object classes are the user interface components in interactive applications. The control of the function property value assigned to the parsing code. The machine learning logic to detect errors due to defects. Advanced defect prediction models use different methods of performance class and function to evaluate. It provides a valid defect prediction for the defect identification code. This information is implemented in application software to improve predictive error classes and merit function code.
Reform and Practice of Oral English Teaching in Higher Vocational Colleges in the Blended Teaching Mode

With the development of information technology and the wide application of educational technology, English teaching has experienced great changes. However, higher vocational college students can not meet the requirements of oral communication under the teaching mode of emphasizing scores over communication in high school. Therefore, higher vocational oral teaching is in urgent need of reform. This paper researches how to carry out oral English teaching reform under the background of development of information technology and the rise of blended teaching.
Emergence: Music’s Role in Player Experimentation

In the context of computer science, “emergent behavior” is when a number of simple behaviors interact and evolve into a larger, more complex behavior. This concept is quite common in video games. In cases of <italic>designed emergence</italic>, the music is designed to react to the player’s personality and to musically encourage the player to carry out certain actions. However, in <italic>unpredicted emergence</italic>, one must ask the question: how will the players’ personalities then affect the resulting music itself? This chapter will discuss different techniques that can be used to create a system that adapts well to both designed and unpredicted emergence, including the uses of model-based sound design, as well as modular orchestration. Among other examples, this chapter examines how Avalanche created a highly reactive music system which accounted systematically for the many possibilities in <italic>Just Cause 4.</italic>
Hate speech in intercultural encounters

The issue of hate speech has been a topic of international debate—most frequently in the domains of law, philosophy and language. Different issues linked to changes in society, ranging from the proliferation of social media, innovation and technology and influx of fake news, disinformation and propaganda to the rise of nationalism, far-right movements, increased cross-border movement of people and transnational business have made studying the conceptual and practical aspects of hate speech in different contexts ever more important. The papers in this issue focus on the sociolinguistic aspects of the use of hate speech and its different variants in online communication, offering a much-needed perspective on how hate speech in digital communication can be identified and tackled. For example, Dr. Manana Ruseishvili and Dr. Rusudan Dolidze analyse hate speech in computer-meditated communication, focusing on the polylogal, asynchronic remarks made by members of the public reacting to articles in online media or press releases about the LGBT pride event planned for June 2019. The research carried out by Lilit Bekaryan explores how hateful posts and comments can start among Facebook users, and studies the language means employed in their design based on data from more than ten open Facebook pages managed by popular Armenian figures, such as media experts, journalists, politicians and bloggers. Dr. Tatjana R. Felberg explores the interconnectedness between impoliteness and hate speech in online comments in Croatia and Serbia by applying impoliteness theory and a critical discourse analysis framework. Her research demonstrates that those who post often fluctuate between hate speech and impoliteness. Dr. Ayunts and Dr. Paronyan provide a comparative analysis of manifestations of hate speech and euphemisms in Armenian and British online media outlets and social sites targeting people's sexual orientation with emphasis on the interconnectedness of hate speech and culture. This issue was prepared as part of the project ‘Intercultural encounters in academia and work places in South Caucasus and Norway’ funded by DIKU, the Norwegian Agency for International Cooperation and Quality Enhancement in Higher Education. The project partner universities are Oslo Metropolitan University, Ivane Javakhishvili Tbilisi State University, Yerevan State University and Khazar University.
Multiple-Model Based Defense for Deep Reinforcement Learning Against Adversarial Attack

Deep Reinforcement Learning models inherit not only generalization abilities but also vulnerabilities under adversarial attacks from Deep Neural Networks. The recent external model based defense method for Reinforcement Learning (RL) detects and corrects the action relying on only the observation prediction method. The observation prediction method may not perform well in complicated applications because of the knowledge of environment, which will downgrade the defense efficacy. This study proposes a multiple-model based defense method for RL which considers detection and correction tasks separately. Since the problem is broken down into two tasks, their complexity and difficulty is also lower, i.e., a better performance is expected. We propose a Correlation Feature Map to extract the observation consistency in the temporal sequence which is destroyed by adversarial noise to separate clean and attacked states. Our correction only deal with the states classified as contaminated and maps them to proper actions. The performance of our proposed method is evaluated and compared to the state of the art method experimentally in various settings. The results confirm the superiority of our methods in terms of robustness and time.
The Role of Technology in Supporting the Education of Community Health Workers and their Leaders

Community health workers (CHWs) often represent the first point of contact for many individuals in low-income countries accessing health services. Unfortunately, due to the low quality of care, outcomes for many people are unpredictable. Although the causes for poor quality of care are multifaceted, one obvious cause is that many CHWs are undertrained. Given the scope of the problem and the lack of resources available to solve it, governments and donor organizations are looking at digital technologies to help address problems such as access to services, health worker training, and decision-making. Access to and understanding of educational content can be improved by combining classroom education with distance learning to create a blended learning approach. Furthermore, by integrating the educational experience offered to CHWs through technology with related support services such as data collection, logistics management and AI-based decision support, governments can compensate for the quality of care gap.