Reviewerly/exHarmony huggingface dataset:
Integrated Science Teachers' Perception: ICT Integration at Grade 10 in Secondary Schools across East Berbice Corentyne, Guyana, South America

Modern society has benefited from the rapid advancement of technology, making it necessary to assess the effects of Information Communication Technology (ICT) adoption in the classroom. This study examined secondary school Integrated Science teachers' perception of ICT integration in Grade 10 across East Berbice Corentyne, Guyana. A non-experimental quantitative design was utilised. The sample comprised 30 teachers – 15 males and 15 females that were extracted using the stratified random sampling method. Data were collected via a questionnaire and administered in keeping with the appropriate ethical considerations. The data collected were analysed through descriptive and inferential analysis techniques. The findings revealed that male teachers used ICT tools more than female teachers and that all the teachers surveyed (trained or not) agreed that ICT integration was an effective intervention in the classroom. Furthermore, the younger teachers reported they faced many challenges despite their willingness to integrate ICT, while the older teachers opted to continue using traditional methods and were more reluctant.
FOREIGN BANKS’ PRESENCE, BANKING SECTOR OPENNESS AND NEW FIRM CREATION IN SELECTED AFRICAN COUNTRIES

This paper analyzes the dynamic impact of foreign banks’ presence and openness of banking sector on new firm creation in a panel of African countries. The analysis is based on Panel corrected standard error estimate (PCSE) and system Generalised Method of Moment (SGMM). Using data of sixteen countries in Africa between 2006 and 2017, the results reveal that foreign banks’ presence and banking sector openness have significant positive impacts on new firm creation. The study also examines the causality between the variables via Toda and Yamamoto approach. The results confirm a bidirectional causality between banking sector openness and new business creation. This means that there is a two-way flow between the variables. Banking sector openness drives entrepreneurial development and entrepreneurial activities also drive openness of the banking sector. This implies that foreign banking firms through their access to advanced technologies, increase the efficiency in the domestic banking sector of the economy. They grant loanable funds to domestic entrepreneurs for setting up new firms. The findings suggest that the presence of multinational banks is a blessing to African economies.&#x0D; Keywords: Foreign Banks, Liberalization, Entrepreneurial Start- up.&#x0D;
Object Detection Performance: A Comparative Study

Abstract Object detection is a critical task in computer vision with applications in many domains. Recent advances in deep learning have led to significant improvements in the performance of object detectors. This paper presents a comparative performance analysis of generic object detectors, with a focus on single-stage and two-stage detectors. The paper first discusses the taxonomy of object detection algorithms, and then presents a detailed performance comparison of single-stage and two-stage detectors. The performance of different detectors was evaluated on two different datasets, Microsoft COCO and PASCAL VOC 2012. The results showed that DetectoRS is a state-of-the-art two-stage object detector, outperforms all other two-stage models. While YOLOv4 and FCOS are the two most accurate single-stage detectors. The comparative results also show that single-stage detectors are generally less accurate than two-stage detectors, but they are typically faster. The paper also includes the strengths and weaknesses of different object detection approaches and identifies promising directions for future research.
Deep Gaussian Mixture Variational Information Bottleneck

On supervised learning tasks, introducing an information bottleneck can guide the model to focus on the more discriminative features in the input, which can effectively prevent overfitting. The deep variational information bottleneck aims to learn a global Gaussian latent variable using the neural network, which compresses mutual information with the input features and retains the most relevant information with the output features as much as possible. However, for the input containing complex semantic information, such as multi-label classification datasets, the latent variable obeying a simple Gaussian distribution may not necessarily capture rich representations. To alleviate this drawback, in this paper, we propose a new approach called Gaussian Mixture Variational Information Bottleneck (GMVIB) where the latent variable follows Gaussian mixture distribution. Then we generate Multi-MNIST and Multi-FashionMNIST, the multi-label classification datasets based on MNIST and FashionMNIST. Our experiments on these datasets show that the proposed approach learns a more efficient embedding representation and achieves competitive performance.
Cryptographic Mechanism for Security of Cloud Computing

By changing current data encryption standards to enable unique hybrid cryptography mechanisms, researchers hope to improve the security of polynomial encryption-based cloud servers. Because the cloud computing movement is quickly gaining traction, the first step for every business is to pinpoint the particular region where cloud-related hazards exist. Cloud computing has accelerated the transformation of industry and government. As a result, new security issues arose. The evolution of the cloud service model as a business-supporting technology has resulted in a significant shift in computer technology. These improvements, however, have resulted in new security vulnerabilities, including security concerns whose full scope is yet unknown. This paper provides an overview and analysis of cloud computing, as well as many security issues.
An Intelligent Framework for Cultural Search of Emperor Mausoleums of Han Dynasty Based on Computer Aided Depth Information Retrieval Algorithm

Aiming at the shortcomings of differential evolution algorithm (DE), which has poor global optimization ability and cannot effectively solve complex high-dimensional nonlinear optimization problems in engineering, a chaotic differential culture algorithm (CDECA) is proposed.And he prefers to choose the images of people, things and things in the Han Dynasty into poetry, etc.The reasons for this include literary tradition, politics, culture and other factors.The existence of this "Han Dynasty complex" is the theoretical basis for a large number of images of the tombs of the Western Han emperors to enter Tang poetry, and it is also the basis for this article to demonstrate.The example shows that the method has a strong global search ability, has remarkable performance in search efficiency , precision and stability , and can effectively deal with the optimization problem of high dimensional function.
WaveVC: Speech and Fundamental Frequency Consistent Raw Audio Voice Conversion

Abstract Voice conversion (VC) is a task for changing the speech of a source speaker to the target voice style while preserving linguistic information of the source speech. Existing VC methods require a separate vocoder because they output mel-spectrogram. Therefore, the VC performance varies depending on the vocoder performance, and noisy speech can be generated due to problems such as train-test mismatch. In this paper, we propose a speech and fundamental frequency consistent raw audio voice conversion method called WaveVC. WaveVC does not require a separate vocoder because it performs VC directly on raw audio and is unaffected by vocoder performance. In addition, WaveVC uses speech loss and F0 loss to preserve content information and generate F0 consistent results. WaveVC shows high performance in both many-to-many VC and any-to-any VC, and the converted samples are available online.
Research On Evolution Of Quality Chain Network Model Based On Multi-Attribute Weighting Of Complex Network

Using the linear optimal connection mechanism of complex network model, a multi-attribute weighted quality chain network model construction method is proposed. Firstly, the enterprise node in the quality chain is defined to have its own attributes of quality elements and node business relevance. Secondly, the degree and the intermediate number are combined to comprehensively consider the local and global characteristics of the network to express the network attributes of the node, and the multi-attribute weighted quality chain network edge connection strategy algorithm is designed under the combination with the node’s own attribute weighting. Finally, the simulation results show that the quality chain network model established by this strategy meets the scale-free characteristics and has higher network efficiency and stronger network invulnerability which proves that the newly established model is reasonable.
Multi Population's Killer Whales Optimizer: A New Optimization Approach Based On Fixed Primary Objective

Abstract This paper has presented a new algorithm called Multi Population's Killer Whales Optimizer (MPKWO). This algorithm is inspired by hunting of a group of Southern Hemisphere Killer Whales. In MPKWO algorithm, a fixed primary objective is used for optimization and search of the main target. In MPKWO algorithm, two populations of the Killer Whales, those waves-generating and the spy Killer Whales, have been used to simulate the hunting process. The spy Killer Whales have a fixed position (fixed primary objective) and wave-generating Killer Whales move closer to the target by moving in each iteration of the algorithm. In fact, in MPKWO algorithm, initially, an initial value is considered as the target, and the position of the main objective is searched for around that point. The proposed algorithm has been evaluated by 18 functions of the standard test. The results obtained from the proposed algorithm are compared with several known and new algorithms. In other words, compared to other algorithms, the proposed algorithm has successfully obtained the optimal values in 71.4% of the cases for Unimodal functions, 66.64% for Multi-modal functions and 80% for fixed-dimension multimodal functions. In addition, three classic engineering problems are solved by MPKWO algorithm. For a more accurate evaluation, the MPKWO algorithm was ultimately used to estimate the software effort and optimize the ABE method. Simulation results show that the proposed algorithm has been more effective than the compared algorithms.
NEW APPROACH FOR DIGITAL RECOVERY FOR 12 LEAD ECG RAW DATA FROM COLOR SCANNED IMAGE OF PRINTED RECORD

Many medical reports and documents in printed form are available in huge sizes in archive units inside medical centers and hospitals around the world. The printed electrocardiogram paper is one type of archive data and is more powerful for expert cardiologists to study various cardiac diseases. On the other hand, the widespread development in the ability of intelligent computer systems to process digital signals increases the benefit of these data if converted to digital form. In this paper, a new approach for digital recovery of 12-lead electrocardiogram raw data from the printed colored scanned image has been proposed. This approach implements an algorithm with four steps including delineating effective regions, color filtering, contacting detected points, and sampling the resulted digital signals to reconstruct the digital electrocardiogram signal from the printed drawing of the same signal after digital scanning with significant resolution. Also, this algorithm is designed to process various kinds of printed electrocardiogram papers. The performance of the proposed approach is evaluated qualitatively by visual inspection of the recovered and original signals in the same graph. Also, the similarity of these signals is evaluated quantitatively using some standard evaluation metrics. The simulation results show the consistency and robustness of the proposed digital recovery approach to generate electrocardiogram digital data with a high percentage accuracy exceeding 98%. Also, plotting the recovered signal with the original printed signal on the same graph shows a significant percentage of congruence in time and amplitude. Finally, the proposed idea in this study opens the way for an unlimited bank of digital electrocardiogram data with different morphologies.
Correlation Between Self-Efficacy and Speaking Performance of the Eleventh-Grade Students at SMAN 1 Palangka Raya

Speaking is a common English skill which is still difficult to master in Indonesia. Especially in secondary school contexts, many students cannot use English for communication functions although they have studied it for several years. As the modern era demands the need of communication skills, this research was initiated to discover whether there is a correlation between self-efficacy and students’ speaking performance to help them improve their speaking skill. The study was conducted with a sample of 40 high school students from class XI MIPA 2 of SMAN 1 Palangka Raya. To collect the data, self-efficacy questionnaire, speaking test, and documentation of students’ latest speaking scores and teacher’s notes of students’ activeness in English class were used. The data then was calculated and analyzed using IBM SPSS Statistics 25 Program. It was found there was a weak correlation (r-count = 0.333) between the two variables. The level of students’ self-efficacy was moderate, but their level of speaking ability was high. Therefore, the study concluded self-efficacy has little or no direct effect on students’ speaking performance. It is suggested that English teachers can continue to improve students’ speaking skill and further research is conducted to find more evidence of this phenomenon.
Refining the Transmission Map and Air Light in the Atmospheric Light Scattering Model for An Efficient Single Image Dehazing Method

Many dehazing methods have been presented by many researchers either on single hazy images or multiple images like videos. With the increasing volume of hazy image datasets, recent literature about dehazing is mostly based on deep learning methods. Although, deep learning models perform better than traditional methods on the validation data of the specific dataset which they are trained with, the generalization performance of deep learning models is generally poor. Another important bottleneck for deep models is the training cost in terms of time and hardware requirements. In this study, traditional DCP method is improved by taking into account the amount of haze and refining the transmission and air light used in atmospheric light scattering model of haze. Results of this study shows that proposed method is superior and/or competitive to traditional DCP method and state of the art deep learning models in terms of the visual quality of the dehazed image.
MENINGKATKAN KEMAMPUAN DAN KETERAMPILAN SISWA DAKAM MENULIS TEKS CERPEN MELALUI MEDIA PENAMPILAN REKAMAN DAN GAMBAR-GAMBAR ILUSTRASI SEBUAH PERISTIWA DI KELAS XI IPS -3 SMA NEGERI 1 PERBAUNGAN TAHUN PELAJARAN 2019/2020

The problem of this research is how the use of recorded media and illustrative images of an event can improve students' abilities and skills in writing poetry for class XI IPS-3 students of SMA Negeri 1 Perbaungan. This study aims to determine the extent to which the use of recorded performance media and illustrative images of an event can improve the ability and skills in writing poetry for class XI IPS-3 students of SMA Negeri 1 Perbaungan. The research subjects were students of class XI IPS-3 in the odd semester of the 2019/2020 academic year who used instructional media to improve their ability to write poetry. All data listed were obtained through observing student documents and teacher notes. This research was conducted through three cycles, each cycle through the stages of action planning, implementation of action, implementation of observation and reflection. With KM 75. The results of cycles I, II, and III were: 1. In cycle I students were able to achieve KKM on the cognitive aspect of 14 students or 42.40% with an average score of 69.3. And students achieve KKM on poetry writing skills 10 students or 30.3% with an average value of 64.32. In cycle II students were able to achieve KKM on the cognitive aspect of 19 students or 57.60 with an average score of 73.5 And students achieved KKM on short story writing skills of 16 students or 48.5% with an average score of 72.82. In cycle III students were able to achieve KKM on the cognitive aspect of 31 students or 93.95% with an average score of 87.9 And students achieved KKM on short story writing skills 28 students or 84.9% with an average score of 78.27.
APPLYING A GENRE BASED-APPROACH WITH AUDIO VISUAL AID FOR IMPROVING WRITING SKILL IN GRADE 11 STUDENTSOF MADRASAH ALIYAH NEGERI SERDANG BEDAGAI

Abstract : APPLYING A GENRE BASED-APPROACH WITH AUDIO VISUAL AID FOR IMPROVING WRITING SKILL IN GRADE 11 STUDENTSOF MADRASAH ALIYAH NEGERI SERDANG BEDAGAI. The purpose of this study is To find out the effectiveness in applying a GBA with Audio Visual Media in Teaching Listening for improving writing skill in Grade 11 students in MANSB. The Subject of study was all of the 11th grade students of MANSB. This research procedure include is: Preparing a GBA learning model; Determining the class/treatment group, namely the control group and experimental group, Doing pre test, Conducting teaching and learning activities (KBM) in the experimental class and control class using GBA learning model, Doing Post-test, and Analyzing the data. The Result of study in the experiment class (Pre-Test) is 36 students, the majority of the them (11 students or 31%) get the core in the range of 52.51-60.00. and in the control class (Pre-Test) is 35 students, the majority of the students (13 students or 37%) get the score in the range of 50.01 - 60.00. The Result of study in the experiment class (Post-Test) is 36 students, the majority of the them (8 students or 22%) get the core in the range of 82.51 - 88.33. and in the control class (Post-Test) is 35 students, the majority of the students (12 students or 34%) get the score in the range of 62.51 - 70.00.
THE ROLE OF THE HEADMASTER IN IMPLEMENTING MANAGEMENT EDUCATION IN THE SCHOOL ENVIRONMENT

The purpose of research on the role of school principals in building education management is to gain a deeper understanding of the role of school principals in leading, organizing and directing education management activities in schools. Research methodology Library Research Management (LRM) is a type of research methodology used in research in the field of education management. LRM emphasizes the use of library resources as a data source in research. The role of the principal is very important in building good educational management in the school environment. The principal as the main leader in the school is responsible for developing appropriate strategies and policies to improve the quality of education in his school. In building effective education management, school principals must be able to understand their roles and responsibilities, and have sufficient managerial skills to manage existing resources in schools.
ANALISIS PEMBELAJARAN DARING MATA KULIAH BAHASA INDONESIA DI KELAS RENDAH PADA MAHASISWA PGSD FKIP UNIVERSITAS QUALITY MEDAN

Analysis of Online Learning for Indonesian Language Courses in Low Grades for Pgsd Fkip Students at the University of Quality Medan. The Covid pandemic that hit the world, not only Indonesia, has paralyzed the economic system, trade tourism and of course the world of education. Teachers and students are required to be technologically literate in carrying out teaching and learning activities. With this pandemic, changing the existing learning system in Indonesia from offline learning to online learning. Teaching is one of the main tasks for a teacher, where the teacher is able to convey subject matter to students so that what the child did not know before has changed to know, and those who do not understand understand. Online is connected through computer networks, the internet, and so on. Due to the development of the times during a pandemic like this it is increasingly being expanded. Online is an interaction between someone and someone through conversation, which can be done in student learning activities. with learning from this students can think critically which directs students to be able to solve problems, and students can do this online learning anywhere and anytime, and lecturers can see student posts and provide feedback on assignments from students. This study uses a qualitative descriptive method with observation instruments and field notes.
Inclusive education and the role of digital technologies

This paper focus, first, on defining students with special education needs and on categorizing them in accordance with the greek law 3699/2008. Then, the terms “integration” and “inclusion” are clarified. Through the review of the bibliography, it is clear that the inclusion education creates an environment that values and respects all individuals, regardless of their differences. One of the most important issues in developed and developing countries is how the inclusion will be applied in education system. There are many models of inclusion. More specifically, the article focusses on inclusion education in Greece according to the legislation. Finally, are given the conditions in order to have a successful outcome in the implementation of inclusion education.
High efficiency lossless image recompression algorithm with asymmetric numeral systems for real-time mobile application

JPEG images are widely used by individual users, data centers, cloud storages, and network file systems. The huge transmission and storage bandwidth of existing JPEG images is becoming a big challenge due to its low compression efficiency. Some methods such as Google’s Brunsli can further compress these JPEG images adequately and restore them back to JPEG format losslessly when needed, but its decoding speed is not fast enough especially for real-time mobile applications. To further reduce its decoding complexity, we proposed three optimizations based on Brunsli, which include using asymmetric numeral systems coding to replace the existing arithmetic coding, designing the joint encoding of multiple symbols and cache-friendly optimizing the data structures. Experimental results demonstrate that compared with Brunsli, the proposed method achieves average 1.86–2.25 times decoding faster on mobile platform with comparable compression efficiency which is really valuable for power sensitive real-time mobile applications.
ANALYSIS OF ENGLISH WRITING ERRORS IN EFL LEARNERS’ RECOUNT TEXT

This research discusses the analysis of students' errors in writing recount texts. This study aims to analyze the types of errors made by undergraduate students’ writing scores at the English Language Teaching Department at one of the universities in Cirebon. This study focuses on writing errors taken from three categories of English proficiency levels (low, average, high). This study used the descriptive qualitative method. There were six participants. The data were taken from their recount text writing results. The results of this study show that there are four types of errors based on Surface Strategy Taxonomy by students: Omission, Addition, Misinformation, and Misordering. The result of the total number of student errors is 37 which contains 14 Omission (37.83%), three Addition (8.11%), 19 Misinformation (51.36%), and one Misordering (2.70%). The most errors were made by Misinformation, with 19 errors (51.36%). It can be concluded that the ability of undergraduate students at one university in Cirebon is still low in writing recount text.