Reviewerly/exHarmony huggingface dataset:
Surface Electrode Ion Trap Developed and Improvement by Oxide- First- Metal-Last Approach for High Performance Quantum Computing

Oxide-First-Metal-Last (OFML) approach was developed and implemented for surface electrode ion trap after different fabrication approaches evaluation. Surface electrode ion trap was fabricated on the high resistivity wafer after lithographic process optimization and metal electrode corrosion troubleshooting. Less than 10E- <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">12</sup> A leakage current between surface electrodes was achieved when swept voltage from -100V to 100V.
Mining Frequent Pattern by Titanic and FP-Tree algorithms

Extraction of itemset frequent is an important theme in Datamining. Several algorithm have been developed based on Apriori algorithm during the last decades. This paper deals with the FP- tree and Titanic algorithms. FP-Tree is an improvement to the Apriori method witch generate frequents itemsets without generating candidate. The Titanic algorithm traverses the level search space by focusing on the determination of the minimum generators (or key Item sets). In addition, this paper studies the differences between these two algorithms and shows advantages and disadvantages of each one.
Impact of IoT in Higher Education

The internet of things, or IoT, is a game plan of interrelated handling contraptions, mechanical and propelled machines, objects, people that are outfitted with unique identifiers and the ability to move data over a framework without anticipating that human-should human or human-to-PC association. IoT in the study hall joins the advantages of IoT in content conveyance, business, and human services. It modifies and upgrades instruction by permitting improvement of all substance and types of conveyance. It empowers instructors to offer concentration to people and their technique. It likewise diminishes expenses and work of training through robotization of basic assignments outside of the real instruction process.
Research on Cultivation of College English Translation Abilities Assisted by the Internet

Abstract The comprehensive arrival of the era of information-based teaching has provided a new impetus and a direction for college English teaching as well as a new type of teaching path for teachers. With the help of network technology, the rational use of network platforms, network environment, and network resources can not only enrich the teaching methods and content of college English translation, but also help students better study translation, integrate into the language learning atmosphere, and improve their English translation ability. At the same time, the thesis conducts research on the cultivation of college English translation ability with the help of the network, aiming to provide reference ideas about college English teaching.
Spiral air gripper that coils around objects of various shapes

A spiral air gripper is a pneumatic robot gripper that coils an expandable tube around objects of variable shapes. The elastic tube is covered by an extensible fabric, which restricts the expansion of the diameter when the elastic tube elongates due to the inside air pressure. The expandable tube of the coil-shaped gripper is enlarged by approximately three times the diameter of the coil when the inside air pressure of the tube is increased. By releasing the inside air, the diameter of the coil is reduced, and it wraps itself around objects tightly. This simple structure makes it easy to develop grippers that can hold large objects, such as furniture.
ANALYSIS OF THE STATE OF THE PROBLEM OF PREPARATION OF TEACHERS OF NATURAL AND MATHEMATICAL SUBJECTS FOR WORK IN THE SCIENTIFIC LYCEUM

The article presents an analysis of the results of the ascertaining stage of the pedagogical experiment "Designing a cloud-oriented methodological system of training teachers of natural and mathematical subjects to work in a scientific lyceum." An analysis of recent research and publications has shown that scholars have sufficiently considered the problem of reforming teacher training courses. A separate issue is revealed in Ukrainian research on the design of cloud-based systems, but the proposed systems relate exclusively to certain specialties, or are entirely scientific. Currently, there is no cloud-based system that would become a tool in the further preparation of teachers of science and mathematics to work in the scientific lyceum. The following were selected as experimental sites: Rivne Regional Institute of Postgraduate Pedagogical Education (2019, number of respondents - 45) and Zhytomyr Polytechnic State University (2020, number of respondents - 824). The current state of use of services by teachers of natural and mathematical subjects during the preparation of educational materials was clarified; the readiness of teachers to perform personally and teach students to conduct research work is analyzed and the state of awareness of teachers about the functions and requirements of scientific lyceums is determined. The analysis of the survey showed that most teachers recognize the need for a teacher of a scientific lyceum in scientific activities. Most respondents do not use English-language resources and services due to their low level of language proficiency. It has been found that one of the most important ways to get involved in science, according to math teachers, is to participate in scientific conferences. Regarding the implementation and use of the obtained research results, teachers plan to choose the following ways: publication of methodological materials and self-implementation. The analysis of the results of the survey of educators showed that among the respondents 574 people (69.7%) prefer to use information and communication technologies on a local computer. Analysis of the results of the ascertaining stage of the pedagogical experiment shows that there is a problem of preparing teachers of natural sciences and mathematics to work in the scientific lyceum, which needs further solution through preliminary testing and implementation of a specially created cloud-based methodological system
IEEE Access Special Section: Digital Forensics Through Multimedia Source Inference

With the prevalence of low-cost imaging devices (smartphones, tablets, camcorders, digital cameras, scanners, wearable, and IoT devices), images and videos have become the main modalities of information being exchanged in every walk of life. The ever-increasing convenience of image acquisition has facilitated instant distribution and sharing of multimedia on digital social platforms. In the meantime, powerful multimedia editing tools allow even unskilled people to easily manipulate digital content for malicious or criminal purposes. In all cases where multimedia serves as critical evidence, forensic technologies that help to determine the origin, the authenticity of multimedia sources, and the integrity of multimedia content become essential to forensic investigators. Imaging devices and post-acquisition processing software leave unique “fingerprints” in multimedia content. This allows many challenging problems faced by the multimedia forensics community to be addressed through source inference. Source inference is the task of linking digital content to the source device or platform (e.g., social media such as Facebook) responsible for its creation. It can facilitate applications such as identification and verification of source device and platform, common source inference, content integrity verification, and source-oriented image clustering. It also allows the establishment of digital evidence or the history of multimedia processing steps applied to the content, starting from the acquisition procedure and up to tracking the spread. The recent adoption of multimedia source inference techniques in the law enforcement sector (e.g., U.K. Sussex Police, Guildford Crown Court, and INTERPOL) in real-world criminal cases and child sexual exploitation databases has manifested the significant value of multimedia source inference in the fight against crime. This Special Section in IEEE Access aims to collect a diverse and complementary set of articles that demonstrate new developments and applications in digital forensics through multimedia source inference.
Flexible Platform for Integration, Collection, and Analysis of Social Media for Open Data Providers in Smart Cities

Developing infrastructure and intelligent utilities for smart cities is an important trend in the world as well as in Vietnam. Thus, it is important to assist developers in building services for open data and smart city utilities. This motivates our proposal to develop a flexible platform with useful components, which can be integrated to develop these solutions quickly, to listen and analyze data from different social media sources with the diversification of data types, to provide open data providers in smart cities. Our method focuses on the ability to flexibly integrate artificial intelligence applications into the system to be able to both analyze effectively social events and serve smart cities in creating open data providers. We do not develop a particular system, but we create a platform, including different components, which are easy to be extended and integrated to create specific applications. To evaluate our platform, we develop four systems, including a face recognition system for celebrity recognition in news videos, an object detection system for brand logo recognition, a video highlighting system for summarizing football matches, and a text analysis system serving for keyword occurrences and emotional text analysis for admissions of universities. In these systems, we have collected and analyzed nearly 1000 videos from CNN, CBSN, FIFATV channels on YouTube, thousands of posts from admission pages of universities on Facebook. Each system gives a unique meaning to each specific situation for open data providers in smart cities.
ORB for Detecting Copy-Move Regions with Scale and Rotation in Image Forensics

The paper proposes a method to detect the forged regions in image using the Oriented FAST and Rotated BRIEF (ORB). In many previous researches in the field of copy-move forgery detection, algorithms mainly focus on objects or parts which are copied, moved and pasted in another places in the same image with the same size of the original parts or included the rotation sometimes, but the copied regions detection with different scale has not much interested in. By adding an oriented component to FAST and the rotation feature to BRIEF, ORB makes the proposed method more powerful and efficient to detect copy-move regions with both scale and rotation. In addition, the removing non-copied objects by calculating their sharpness improves the accuracy of the detection. The experiment is done on the datasets for copy-move images and some real images with the improved time and high accuracy.
A Technique for Big Data Deduplication based on Content Attributes and Dictionary Indexing

Abstract In recent years, the quick expansion of the data such as text, image, audio, video, data centers, and backup data has caused to a lot of problems in both storage and recovery processes. The companies spend plenty of money to store the data. Hence, a need for an efficient technique becomes necessary for handling enormous data. In this paper, we propose to set up for new de-duplication for the contents of big data set. The divisors are selected in an automated way using the fields separator, different dictionary indexing methods will be used to de-duplicate the fields contents those have bounded variability. Also a set of computationally low-cost hash functions will be used for speeding up the deduplication for fields consist of long strings. The number, nature, and length of fields will be tested. Besides that, certain kinds of indexing and clustering methodology will be applied to define the optimal way to decrease the data size before making de-duplication.
Strategies of similarity propagation in web service recommender systems

Recently, web service recommender systems have attracted much attention due to the popularity of Service-Oriented Computing and Cloud Computing. Memory-based collaborative filtering approaches which mainly rely on the similarity calculation are widely studied to realize the recommendation. In these research works, the similarity between two users is computed based on the QoS data of their commonly-invoked services and the similarity between two services is computed based on the common users who invoked them. However, most approaches ignore that the similarity calculation is not always accurate under a sparse data condition. To address this problem, we propose a similarity propagation method to accurately evaluate the similarities between users or services. Similarity propagation means that "if A and B are similar, and B and C are similar, then A and C will be similar to some extent". Firstly, the similarity graph of users or services is constructed according to the QoS data. Then, the similarity propagation paths between two nodes on the similarity graph are discovered. Finally, the similarity along each propagation path is measured and the indirect similarity between two users or services is evaluated by aggregating the similarities of different paths connecting them. Comprehensive experiments on real-world datasets demonstrate that our similarity propagation method can outstandingly improve the QoS prediction accuracy of memory-based collaborative filtering approaches.
تأثير الرضا الوظيفي على أداء العاملين بتوسط الولاء التنظيمي لدى بريد الجزائر بالوحدة الولائية للبريد بالنعامة

The Aim Of This Study Was To Find The Effect Of Employees Satisfaction On Performance By Mediating Organizational Loyalty By Identifying Elements Of The Employees Satisfaction . By Conducting A Field Study For The Employees Of Algeria Post, The State Unit In Naama, 80 Cases Of Usable And Analysis Were Analyzed Among 325 Employees. The Results Of Confirmatory Factor Analysis Have Found That Employees Satisfaction Has A Positive Effect On Organizational Loyalty And Organizational Loyalty Has A Positive Impact On The Staff Performance, And The Employees Satisfaction Has Indirect Impact On The Staff Performance, But Its Direct Effect Has Not Significant Statistically. Key Words -  Staff Performance, Employees Satisfaction, Organizational Loyalty.
Application of Artificial Intelligence in Thyroidology

Thyroid dysfunction is one of the most common endocrine diseases. About 4.7% of the United States population has undiagnosed thyroid disease (Garmendia Madariaga, Santos Palacios, Guillén-Grima, & Galofré, 2014). Thyroid nodules could be present in up to 67% of the population (Ezzat, Sarti, Cain, & Braunstein, 1994). Increased incidence of thyroid nodules has been attributed to increased use of imaging modalities and improvement in imaging technology (Singh, Singh, & Khanna, 2012). Technological improvements in ultrasound including elastography, 3D ultrasound (Liang et al., 2019) 274and quantitative ultrasound (Goundan et al., 2019) have been used to improve the diagnostic accuracy. Computer-aided diagnosis software that can automatically detect different features in the thyroid nodules and generate a report has been cleared by the FDA (Lu, Shi, Zhao, Song, & Li, 2019). Similarly, artificial intelligence (AI) algorithms have been used in the diagnosis and management of thyroid diseases. One of the first papers using AI in the diagnosis of thyroid disease was by Sharpe et al. in 1993. They used a multilayer perceptron trained by back-propagation and a learning vector quantization network to investigate the robustness of these models on noisy diagnostic data. In recent years, most of the AI research in thyroidology has been focused on the diagnosis and management of thyroid nodules. Initial approaches used texture analysis to classify thyroid ultrasound images. Later, AI techniques such as machine learning (ML) and an advanced form of ML, deep learning (DL) algorithms were used. In this chapter, we discuss the use of AI in thyroid imaging, cytopathological diagnosis of thyroid nodules and molecular markers. The use of wearable devices and generative adversarial networks in thyroidology is also discussed in this chapter.
CREATIVE USE OF THE POTENTIAL OF VIRTUAL REALITY IN TEACHING

The text presents the complexity of the educational process taking place during the period of digital transformation and the role of the teacher in the changing didactic reality. The need to modify the existing digital tools adapted to the requirements of modern students was pointed out. The author’s assumption was to draw attention to computer games that can be part of the strategies for creating effective teaching tools tailored to the needs of digital natives. The article presents the features of games that may be key to the effective use of gaming in teaching. It also presents the strategy of educational game design. Despite the research conducted on the use of the potential of computer games in education, this topic still does not seem to be sufficiently exhausted, as exemplified by the teachers’ approach to virtual reality of games, which they mostly treat only as a ludic area.
The use of new training forms and methods in the context of digitalization

Abstract The paper substantiates that the problem of implementation of modern forms and methods of teaching, including distance learning, remains insufficiently studied at the moment, taking into account the impact of factors of computerization and digitalization of socio-economic relations and the characteristics of national experience. The article defines the essence of personnel development, considers the forms and methods of personnel training, classified by stages, roles of the teacher, the nature of cognitive activity, types, place, and degree of innovation. The purpose of the study is, on the basis of a comparative analysis and systematization of forms and methods of teaching, determining the essence and content of distance learning, to identify the advantages and limitations in the implementation of methods of remote learning in the context of digitalization. The stages of distance learning development, the essence of distance learning as a set of specific forms, means, methods through which the content of training is carried out, a set of cognitive procedures that determine the operational part and structure of students’ activities, opportunities, advantages and limitations, forms of distance learning-chats, online classes, internet conferences and webinars, telepresence.
Occlusion Robust Object Tracking with Modified Particle Filter Framework

Object tracking is a classical problem of computer vision and is ubiquitous in many applications. Multiple tracking frameworks have been proposed in the past, and still attracting many researchers due to its high applicability in various fields. Major challenges in object tracking are because of constraints like illumination, occlusions, changing background, etc. This work proposes a modified Particle Filtering framework that is robust to partial and complete occlusions. In achieving so, this work suggests the use of a forward prediction filter that is fused with the proposed framework. It works irrespective of the measurement model. Also, our proposed work proposes an Uncertainty Factor for every prediction that controls the amount of uncertainty during particle update and adjusts the search area accordingly. This Uncertainty Factor also acts as a measure of tracking performance. Extensive experiments prove the better performance of the proposed work in comparison with the existing ones in presence of occlusion.
Knowledge Management in a Learning Health System

Over the past few centuries, medical science has been growing steadily. The pace has accelerated in the last few decades. This new knowledge is slow to change the practice of medicine, although we have been using information technology tools for data collection, manipulation and analysis. Sample sizes have grown bigger over the years for clinical trials. Today, with the implementation of electronic health record (EHR), availability of clinical data has increased. It is now possible to study the whole population 224instead of a sample using machine learning and artificial intelligence tools. The speed and capacity to manipulate and analyze data have increased tremendously with the availability of larger capacity of hardware, faster software and better algorithms. We are about to see a flurry of new discoveries and new knowledge. This chapter will discuss the role of (i) knowledge curation, (ii) knowledge translation and (iii) new knowledge generation in medicine using machine learning and artificial intelligence in a learning health system.
Kendala dalam Belajar Bahasa Inggris dan Cara Mengatasinya

Language plays a crucial role in life, one of the roles of language is to communicate ideas to others. Language skills are the basic element for everyone to express themselves in the form of feelings, desires, opinions and needs of each individual. The more languages ​​a person knows, the easier it will to communicate, one of them is learning English. Understanding of English must be strengthened to rising generation especially students, due to globalization which requires society to speak English. For Indonesian, the use of English is still an obstacle due to a lack of understanding of the meaning of the language itself, students must be able to write and pronounce English words with different spellings. This complexity makes students or children less interested in learning English. The development of tourism in Bali is growing swiftly, this can be proven by the increasing number of visits by local and foreign tourists. To expand interaction, then must be able to master foreign languages, one of them is English. It is realized that the ability to speak English is crucial in the field of tourism, so it is necessary to prepare provisions for children to be able to communicate using English. Based on this, the Master of Linguistics of Warmadewa University through its Community Service activities held training in the form of teaching English about obstacles in learning English and how to overcome them.  This study was designed to determine the obstacles to learning English for children and to increase students' interest in learning English. This research used a case study research type. Technique of collecting data in groups, namely asking about the problems experienced when learning English. The results of this study are that community service activities run well and structured in order to find solutions to the main problems, that is knowing the obstacles in learning English and how to overcome them.
A note on optimization formulations of Markov decision processes

This note summarizes the optimization formulations used in the study of Markov decision processes. We consider both the discounted and undiscounted processes under the standard and the entropy-regularized settings. For each setting, we first summarize the primal, dual, and primal-dual problems of the linear programming formulation. We then detail the connections between these problems and other formulations for Markov decision processes such as the Bellman equation and the policy gradient method.