Reviewerly/exHarmony huggingface dataset:
Effective restoration of underwater images to improve local feature matching

Underwater images are characterized by poor contrast, foggy appearance and color shifting and as a result due to these distortions many underwater applications perform poorly. Since many computer vision applications (e.g. SLAM) still rely on effective matching of local features, in this work we analyze this problem for underwater images. We first describe an effective underwater restoration approach that is built on the well-know DCP (dark channel prior). We first perform a simple but effective color correction and then assuming the simplified optical model we estimate the transmission and backscattering light using dark channel prior. In our validation we perform a quantitative evaluation in the context of local feature matching based on the ORB operator. The extensive experiments demonstrate that our approach yields competitive results.
role of psychological empowerment and work flow in the professional commitment of employees working in the Jordanian Ministry of education

The study aimed to identify the direct effects of both psychological empowerment and work flow on professional commitment, and this study was applied to all employees of the Jordanian Ministry of Education. The descriptive analytical approach was used, and the study sample consisted of (463) employees in the ministry, and the researchers prepared three measures for each of psychological empowerment, work flow and professional commitment. The results of the study concluded that there is a direct and positive semantic effect of psychological empowerment and work flow in professional commitment, in addition to the presence of a direct and positive semantic effect of work flow in professional commitment. The study recommended conducting a similar study for other ministries in order to generalize the results.
Quantum Amplifier for a Magnetic Flux Qubit

Abstract The possibility of using a particular Josephson-based quantum amplier to amplify the signal of a qubit with a magnetic degree of freedom is investigated. The amplifier consists of two Josephson junctions in a loop like a DC SQUID, but with no external flux bias. The qubit is assumed to be like a spin with two opposite states of flux. The circulating current in the Josephson-based amplier is the signal to be measured by a suitable readout device. A DC current bias through the amplifier can be used to tune the amplifier between an OFF phase, when readout does not occur, and an ON phase, when the amplifier signal is coupled to the readout device and readout occurs. Results are provided demonstrating the average magnitude and noise in the modulation factor of the amplifier current signal. Also it is shown exactly how the current bias may be used to suppress the amplier signal in the OFF phase. Results demonstrate this is a potential candidate for a useful element in the design of a quantum computer.
easuring the Impact of Human Development on the Growth of the IIraqi Economy During the Period (2005-2020)

Human development is an acceptable and precursory process for all individuals which increases their opportunities in terms of (health, education، standards of living and livelihood). It also expands individuals’ choices in social, economic and political life. The role significance of human development appears when we see the best sort of investment is human investment (human capital) because it is an indestructible base to socially and economically build a powerful and successful society. The target of the research is to measure the influence of human development on economic growth in Iraq from (2005 – 2020).To achieve this goal, the research relied on a descriptive and analytical approach based on time series data and the use of my method (ARDL) .Finally, the research has come to some conclusions and the most important ones: There is a positive and direct relation between human development and economic growth in Iraq in a way that when human development increases by (%1) it leads to the increase of economic growth by (%0.37).
Prospects for developing methods for short-term forecasting of strong earthquakes based on satellite monitoring of cloudiness anomalies

Forecasting earthquakes of various intensities will continue to be an urgent task that has yet to bene resolved. The use of various forecasting methods makes it possible to conduct analysis and warnings more objectively and reliably. Methods of short-term prediction of strong earthquakes based on satellite monitoring of cloudiness anomalies can be used with some success. Based on the research results, it was established that before strong earthquakes, linear cloudiness anomalies are observed over the Earth's deep fault zones, which can be used for short-term earthquake forecasting. The most effective method of studying cloudiness anomalies is the use of satellite methods. As a result of the analysis of linear cloudiness anomalies, a conclusion was made about the possibility of a regional short-term forecast of strong and catastrophic earthquakes with an assessment of the possible magnitude and approximate position of the future earthquake. The reliability of the forecast depends on the tectonic structure of the region and atmospheric conditions. It is important to be able to forecast the magnitude of the future earthquake based on the length of the cloudiness anomaly. It was established that the length of the cloudiness anomaly before a catastrophic earthquake allows one to predict the magnitude, which is very important for forecasting the level of seismic danger in the coming days.
Application of Artificial Intelligence Technology in Cross-Cultural Communication of Intangible Cultural Heritage

Intercultural communication not only promotes the emergence and development of multiculturalism but also promotes cultural exchanges on a global scale. China has rich resources and a long history. Because of its unique national characteristics, it is even more famous and unique in the world today. However, with the transformation of society, cross-cultural dissemination and blending are inevitable. Intangible cultural heritage is an important cultural form, and its international dissemination is increasingly attracting people’s attention. The spontaneous inheritance mode of intangible cultural heritage, which is mainly based on oral and heart teaching, has been unable to adapt to the development of society and has gradually moved away from people’s sight. How to better protect and inherit intangible cultural heritage is an important topic in the field of current cultural exchanges. However, due to the particularity of intangible culture, especially its abstract nature, it is difficult to show it to the public, which makes it difficult to protect and promote intangible cultural heritage. The application of the advantages of artificial intelligence technology to the dissemination of intangible cultural heritage is to solve these problems, which can not only make it innovative in protection but also promote its sustainable development to a certain extent. This paper discusses the application of artificial intelligence technology in the protection and dissemination of intangible cultural heritage from multiple perspectives and points out that the advantage of artificial intelligence is that although it cannot be creatively inherited, it can be reproduced in a historical moment, so as to meet people’s needs for intangible cultural heritage. It can also be found in the questionnaire for the visitors that 66% of the visitors prefer to learn about the intangible cultural heritage through experience and feel that the personal experience is more intuitive and interesting. Artificial intelligence technology has great advantages in disseminating intangible cultural heritage.
E-Report Application: The Role of Stakeholders in The Assessment System in Schools

This study aims to find out about the role of school stakeholders in processing student grades using the e-report application. This study uses a descriptive method with a qualitative approach, namely observation by observing the website and using the website directly. Interviews were conducted with informants regarding the use of applications and documentation of reports issued from applications to school stakeholders who now participate in the use of e-reports. The data analysis technique was carried out using data reduction, data presentation, and concluding. The results show that the role of school stakeholders in the use of interconnected e-reports starts from the administrative field in data collection, teachers in data entry, curriculum fields in checking data, and BP teachers who enter student attendance to get to the parents. The existence of this E-report application shows the discipline and perseverance of the stakeholders in controlling IT. The processing of the scores on this e-report will also be copied into the student's master book, and later the results of this assessment will be submitted to the Surabaya City Education Office for nomination with other schools.
Research on the development strategy in introduction of Chinese students based on SWOT analysis by Korean international education industry

According to the statistics of the Korea Educational Development Institute (KEDI) from 2000 to 2020, Chinese students have entered a period of rapid growth and stable development. Chinese students studying in Korea peaked in 2019, falling for the second consecutive year after 2020 due to the COVID-19 pandemic and multiple factors. In fact, the growth rate of Chinese students in South Korea has been on a marked decline since 2017. The strategy and present situation of attracting Chinese students are important to the Korean international education industry, including Strength, Opportunities, Weakness and Threats. The SWOT analysis shows that the attraction of Chinese students is affected by many factors such as Chinese-Korean relations, the policy of studying in Korea, the strategy of Korean universities, and the satisfaction of students
Visual Object Detection with Score Refinement

&lt;p&gt;Robustness of object detection against hard samples, especially small objects, has long been a critical and difficult problem that hinders development of convolutional object detectors. To address this issue, we propose Progressive Refinement Network to reduce classification ambiguity for scale robust object detection. In PRN, several orders of residuals for the class prediction are regressed from upper level contexts and the residuals are progressively added to the basic prediction stage by stage, yielding multiple refinements. Supervision signal is imposed at each stage and an integration of all stages is performed to obtain the final score. By supervision retaining through the context aggregation procedure, PRN avoids over dependency on higher-level information and enables sufficient learning on the current scale level. The progressive residuals added for refinements adaptively reduce the ambiguity of the class prediction and the final integration of all stages can further stabilize the predicted distribution. PRN achieves 81.3% mAP on the PASCAL VOC 2007 dataset and 31.7% AP (15.6% APS) on MS COCO dataset, which demonstrates the effectiveness and efficiency of the proposed method and its promising capability on scale robustness.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt;
Perancangan sistem informasi pengajuan dan simulasi perhitungan kredit oleh nasabah berbasis android pada Bank BJB Cabang Soreang Bandung

A loan or credit is a form of banking service. The rapid development of digital technology has encouraged the banking industry to implement digitalization in its services, including customer credit services to improve the quality of its services. Bank BJB Soreang Branch already has a digital application for credit services for customers. However, this application does not yet have features that makes it easy for customers to apply and simulate credit calculations by themselves. This study aims to design an information system for submitting and simulating credit calculations by customers at Bank BJB Soreang Branch. To develop this information system, UML diagrams are used as the modeling method and the prototype method as the design method. This android-based system was built using Kodular and FireBase software as the database. The results of this study are in the form of an application designs that can be used at Bank BJB Soreang Branch to assist state civil servants and retirees in applying for and conducting credit simulations independently so that the service for the customer credit application process at Bank BJB Soreang Branch is even better.
Causes and Countermeasures Against the Silence Phenomenon in English Classrooms at Applied Undergraduate Colleges and Universities

In applied undergraduate colleges and universities, the silence phenomenon in English classrooms is common. However, many English teachers are troubled by this phenomenon. The teaching focus of English, as a language subject, is on basic skills such as listening and speaking. Therefore, the silence phenomenon will not only affect students’ communication skills, but also bring various negative implications. By analyzing the causes of this phenomenon in English classrooms at applied undergraduate colleges and universities, this paper proposes three solutions to solve this issue and enhance the pertinence and effectiveness of English teaching in applied colleges and universities: attaching importance to thinking, adhering to correct teaching concepts, and teaching students in accordance with their aptitude and to apply what they have learned.
Teaching Improvement Strategies of University English Audiovisual or Speaking Course under the Background of Hadoop

Under the background of “Internet plus,” the social application and penetration of cloud computing and big data have produced far-reaching impacts in many aspects in the field of education. Taking college English audio-visual teaching at present. However, there are still many problems in classroom teaching practice. Focusing on college English listening and speaking teaching, this study explores the teaching strategies of college English listening and speaking to improve college pupils’ comprehensive listening and speaking ability. With the rapid development of information technology, relying on information technology and using modern technologies such as multimedia to conduct three-dimensional audio-visual teaching can effectively improve the efficiency of audio-visual classrooms by 16%. Based on the background of Internet plus, this study tries to reconstruct the evaluation model of college English audio-visual courses by using multivariate and multidimensional evaluation models and combining quantitative and qualitative evaluation to improve the teaching quality and effect of college English audio-visual course.
Шары в булевом пространстве

The operation of addition of sets is used in numerous problems of combinatorics. In the present paper some properties of the addition operation of sets (the Minkowski addition) in Boolean space are presented and the additions of spheres are considered. The obtained results make possible to describe the sums through such characteristics as the sphere radii and the distances between the sphere centres.
Superiority of quadratic over conventional neural networks for classification of gaussian mixture data

Abstract To enrich the diversity of artificial neurons, a type of quadratic neurons was proposed previously, where the inner product of inputs and weights is replaced by a quadratic operation. In this paper, we demonstrate the superiority of such quadratic neurons over conventional counterparts. For this purpose, we train such quadratic neural networks using an adapted backpropagation algorithm and perform a systematic comparison between quadratic and conventional neural networks for classificaiton of Gaussian mixture data, which is one of the most important machine learning tasks. Our results show that quadratic neural networks enjoy remarkably better efficacy and efficiency than conventional neural networks in this context, and potentially extendable to other relevant applications.
Relations between the Proof Complexities in Frege Systems, Deep-Inference Proof Systems KS and еКS

Using the determinative sizes fօr tautologies of some sequences, it is proved in this paper that a Frege system and deep-inference proof system еКS exhibit an exponential speed-up over the deep-inference proof systems KS both by lines and size of proofs.
Evaluating the Effectiveness of Internal Control System under Using Blockchain Technology: Evidence from Dubai Government

Dubai has witnessed a great development in its economic sector and a massive volume in its financial services, so simple operations become more complex.Therefore, Blockchain Technology (BCT) has been implemented in the department of Finance (DOF) in Dubai government.Based on this, the objective of this research is to evaluate the internal control system (ICS) under the use of BCT.In order to achieve this objective, the data in this research was collected by using qualitative approach thorough conducting the interviews with focus group consists of heads of departments, accountants, and auditors.The collected data was analyzed by using the Analytical Hierarchy Process (AHP) and Analytical Network Process (ANP) (Hamdan, 2013).The following are the most important findings of this research.First, designing an effective and strong model to evaluate the effectiveness of ICS.Second, the Blockchain implementing strategies has a significant role on evaluating the effectiveness of ICS.Third, obtaining a standard percentage of the effectiveness of ICS under the use of BCT which is 72% to be used in the future research.
Implementasi E-Government Berbasis Android Untuk Meningkatkan Pelayanan Publik

&lt;p&gt;&lt;strong&gt;Technology in government is a breakthrough in managing and disseminating information about government to the public. The existence of technology that is applied in a government hope can provide flexibility and transparency for the community and complete complex tasks. The purpose of this study is to build an Android-based e-government information system in Tanjung Rejo Village that can provide services and information to the people of Tanjung Rejo Village and the general public. Data collection methods used in this study were observation, documentation, interviews, and literature study. While the method used in designing e-government by following the information system development life cycle (System Development Life Cycle), generally consists of the stages of analysis, design, implementation, and use. The case study of this research is e-government in Tanjung Rejo village. This research can produce an e-government planning document in Tanjung Rejo village. From the results of the e-government design in Tanjung Rejo village, it is hoped that it will make it easier for village officials or residents to convey and obtain information related to Tanjung Rejo village quickly and accurately. An Android-based e-government information system can be used and applied in the process of submitting village activity and potential data. Further research can be developed by adding several more varied features and can add mobile GIS and GPS systems.&lt;/strong&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Keywords&lt;/strong&gt; - &lt;em&gt;E-government&lt;/em&gt;, P&lt;em&gt;ublic service, I&lt;/em&gt;&lt;em&gt;nformation system, Utilization of information technology&lt;/em&gt;&lt;/p&gt;
A Study of Problems Faced by the Teachers and Students in Online Teaching-Learning at Upper Primary Level

In today's world of education, everyone is getting educated because education is now reaching every house.Due to the influence of technology, education is easily accessible to all.Now education has become more and more online.But still there is a lot of technical problem in the education sector.Technical problem has become a problem not only in the students but also in the teachers.In online teaching-learning, students and teachers have the following problems, such as technical problems, problems related to e-content, problems related to teaching aids and problems of mental stress.Although online instruction has many potential benefits, technical difficulties are one drawback to the increased use of this medium.In this research paper will be used statistics-selfmade statement for data collection, hypothesis, data analysis, etc. therefore, finding Contribute to our theoretical understanding of the online teaching-learning.
Heterogeneity of Data: The NoSQL Revolution

There is a tremendous growth in the unstructured Data in these past years which has led to the emergence of NOSQL.Several companies and IT firms have unleashed a variety of solutions to support the unstructured & structured data.In this paper we provide an overview of latest trends in SQL, NOSQL & Big-data and we extend the discussion to the importance of suitable Data architecture & key features of each database in depth.
Supervised ML Algorithms in the High Dimensional Applications for Dimension Reduction

We steered comparative analysis of manifold supervised dimension reduction methods by assimilating customary multiobjective standard metrics and validated the comparative efficacy of supervised learning algorithms in reliance on data and sample complexity. The question of sample and data intricacy is deliberated in dependence on automating selection and user-purposed instances. Different dimension reduction techniques are responsive to different scales of measurement and supervision of learning is also discussed comprehensively. In line with the prospects, each technique validated diverse competence for different datasets and there was no mode to gauge the general ranking of methods trustily available. We especially engrossed the classifier ranking and concocted a system erected on weighted average rank called weighted mean rank risk adjusted model (WMRRAM) for consensus ranking of supervised learning classifier algorithms.
They are Not Completely Useless: Towards Recycling Transferable Unlabeled Data for Class-Mismatched Semi-Supervised Learning

Semi-Supervised Learning (SSL) with mismatched classes deals with the problem that the classes-of-interests in the limited labeled data is only a subset of the classes in massive unlabeled data. As a result, the classes only possessed by the unlabeled data may mislead the classifier training and thus hindering the realistic landing of various SSL methods. To solve this problem, existing methods usually divide unlabeled data to in-distribution (ID) data and out-of-distribution (OOD) data, and directly discard or weaken the OOD data to avoid their adverse impact. In other words, they treat OOD data as completely useless and thus the potential valuable information for classification contained by them is totally ignored. To remedy this defect, this paper proposes a "Transferable OOD data Recycling" (TOOR) method which properly utilizes ID data as well as the "recyclable" OOD data to enrich the information for conducting class-mismatched SSL. Specifically, TOOR firstly attributes all unlabeled data to ID data or OOD data, among which the ID data are directly used for training. Then we treat the OOD data that have a close relationship with ID data and labeled data as recyclable, and employ adversarial domain adaptation to project them to the space of ID data and labeled data. In other words, the recyclability of an OOD datum is evaluated by its transferability, and the recyclable OOD data are transferred so that they are compatible with the distribution of known classes-of-interests. Consequently, our TOOR method extracts more information from unlabeled data than existing approaches, so it can achieve the improved performance which is demonstrated by the experiments on typical benchmark datasets.