Reviewerly/exHarmony huggingface dataset:
Big Data Nearest Neighbor Similar Data Retrieval Algorithm based on Improved Random Forest

In the process of big data nearest neighbor similar data retrieval, affected by the way of data feature extraction, the retrieval accuracy is low. Therefore, this paper proposes the design of big data nearest neighbor similar data retrieval algorithm based on improved random forest. Through the improvement of random forest model and the construction of random decision tree, the characteristics of current nearest neighbor big data are clarified. Based on the improved random forest, the hash code is generated. Finally, combined with the Hamming distance calculation method, the nearest neighbor similar data retrieval of big data is realized. The experimental results show that: in the multi label environment, the retrieval accuracy is improved by 9% and 10%. In the single label environment, the similar data retrieval accuracy of the algorithm is improved by 12% and 28% respectively.
Reducts of Relation Algebras: The Aspects of Axiomatisability and Finite Representability

In this paper, we show that the class of representable residuated semigroups has the finite representation property. That is, every finite representable residuated semigroup is representable over a finite base. This result gives a positive solution to Problem 19.17 from the monograph by Hirsch and Hodkinson \cite{hirsch2002relation}. We also show that the class of representable join semilattice-ordered semigroups is pseudo-universal and it has a recursively enumerable axiomatisation. For this purpose, we introduce representability games for join semilattice-ordered semigroups.
Exploratory Data Analysis (EDA) of the Performance of Philippine Higher Education Institutions in the Electronics Engineering Licensure Examinations

A significant indicator of quality in engineering education is the results of licensure examinations. Examination results as well as the performance results of Higher Education Institutions (HEIs) are made available through the Professional Regulations Commission (PRC) website and other publications within a week that examinations are administered. Through the years PRC has in its databank an increasing accumulation of large data of examination results that need to be statistically and graphically summarized to unravel hidden patterns which could be significant basis for important decisions, strategies and plans. The objective of this paper is to give summary representations of the performance of HEIs in the Electronics Engineering Licensure examinations from the year 2012 to 2016. Results may be used as basis for strategic decisions such as but not limited to: evaluation or reformation of the monitoring of performance of HEIs in the licensure examinations, and the restructuring of accreditation requirements pertaining to the performance of HEIs in Electronics Engineering licensure examinations. This study made use of the descriptive research methodology using the data mining tasks which are: Data Preparation, Descriptive Data Modeling, Model Evaluation and Output Presentation. Results show that in all ten examinations from the year 2012-2016, the average passing rates of majority of HEIs are less than the national passing rates. Both the national passing rates and the average passing rates of HEIs have been fluctuating but mostly hovering between 30 to 40% over the ten examinations. Moreover, the most frequent occurring passing rate of HEIs with less than 25 takers is 0%. There is then a need to monitor and investigate HEIs with less than 25 takers to probe on the causes of low passing rates.
On the Low-density Latent Regions of VAE-based Language Models

By representing semantics in latent spaces, Variational autoencoders (VAEs) have been proven powerful in modelling and generating signals such as image and text, even without supervision. However, previous studies suggest that in a learned latent space, some low-density regions (aka. holes) exist, which could harm the overall system performance. While existing studies focus on empirically mitigating these latent holes, how they distribute and how they affect different components of a VAE, are still unexplored. In addition, the hole issue in VAEs for language processing is rarely addressed. In our work, by introducing a simple hole-detection algorithm based on the neighbour consistency between VAE’s input, latent, and output semantic spaces, we propose to deeply dive into these topics for the first time. Comprehensive experiments including automatic evaluation and human evaluation imply that large-scale low-density latent holes may not exist in the latent space. In addition, various sentence encoding strategies are explored and the native word embedding is the most suitable strategy for VAEs in language modelling task.
PEDAGOGICAL CONDITIONS OF COGNITIVE ACTIVITIES DEVELOPMENT OF PRIMARY SCHOOL STUDENTS AT LESSONS "I EXPLORE THE WORLD"

The article deals with pedagogical conditions of cognitive activities development of primary school students at lessons «I explore the world». It is defined the essence of the concepts «activity», «cognitive activity», programs of the course «I explore the world» for the 1 st grade students (O. Savchenko and R. Shyian and textbooks (by O. Tahlina, H. Ivanova, T. Hilberh, S. Tarnavska, V. Ponomarenko etc) that written on various programs are investigated in the article. The structure of primary school students’ cognitive activity at lessons I explore the world" is characterized. On the basis of scientific and experimental analysis of pedagogical conditions of students’ cognitive activities formation at primary school it is determined that these conditions comprise elements of all the constituents of educational process, namely aims, content, forms, methods and techniques. Providing effective pedagogical conditions is important in the process of students’ cognitive abilities development, theirintellectual abilities, classroom activity. The article reveals pedagogical conditions of the educational process organization that enable to form students’ cognitive activity at primary school at lessons «I explore the world" in an effective way: inquiry based learning; organization of educational activities on the basis of personality-oriented interaction «teacher-student»; the use of active methods and forms of teaching within the subject, advanced unsupervised activities. It is explained that primary school is an extremely important part of a school life as the first years of study have a strong influence on further intellectual development, creativity and character formation, self-development. Precise and clear formation and development of cognitive activity makes primary school students’ academic performance more successful.
Clustering, Classification, and Categorization

Text analytics consist of the statistics about a text element, which includes the word count, the word histogram, and the word frequency histogram. Most text documents of value are related to other—sometimes many other—documents, and so analytics describing the relative frequency of terms in a document compared to its peers are important for defining key words (tagging, labeling, indexing), search-responsive terms (query terms), and compressed versions of the documents (key words, summary, etc.).This clearly written text explains the functional applications of search, translation, optimization, and learning with regard to text analytics. Generation of analytics is aided by a hybrid, ensemble, or other combinatorial approach in which two or more effective analytic processes are used simultaneously, and their outputs combined to form a better “consensus”. Additional value to the preservation of the information is provided through these methods. Also, since they encompass capabilities of two or more knowledge-generating systems, they can create a “superset” of access points to the data generated. The book also describes the role of functional approaches in the testing and configuration of these systems.
Syilling Fantastic Enterprise : Smart Laundry / Aswad Abadh Dhar Nor Azman...[et al.]

Syilling fantastic Enterprise, is the new company that wanted to promote a new product that can be marketed to the whole world. Actually our product name is “Electrical Laundry”. This smart laundry is the laundry that has been develop into something new product that can make all people woks getting easier. This product has been designed by our designer. Our product theme is ‘classic’. Syilling Fantastic Enterprise is come from our director’s idea. The word ‘syilling’ meaning that each paper money in this world was not enough if there were no ‘syiling’ to complete it. Besides, the words “fantastic” meaning that we praise our company so that the whole world will now our company name. This is a little bit of our company history.
Security Analysis of Intelligent System Based on Edge Computing

At present, artificial intelligence technology is widely used in society, and various intelligent systems emerge as the times require. Due to the uniqueness of biometrics, most intelligent systems use biometric-based recognition technology, among which face recognition is the most widely used. To improve the security of intelligent system, this paper proposes a face authentication system based on edge computing and innovatively extracts the features of face image by convolution neural network, verifies the face by cosine similarity, and introduces a user privacy protection scheme based on secure nearest neighbor algorithm and secret sharing homomorphism technology. The results show that when the threshold is 0.51, the correct rate of face verification reaches 92.46%, which is far higher than the recognition strength of human eyes. In face recognition time consumption and recognition accuracy, the encryption scheme is basically consistent with the recognition time consumption in plaintext state. It can be seen that the security of the intelligent system with this scheme can be significantly improved. This research provides a certain reference value for the research on the ways to improve the security of intelligent system.
The Jordanian Press Coverage of Terrorism News: DOI: 10.46988/IJMMC.01.01.2019.004

The study aimed to identify the treatment of Jordanian press coverage of the news of the terrorist attacks, the media's attitude towards it, and how it is dealt with at large. In addition to that, this research has also accounted for revealing the characteristics of the newspapers' apparent content in its coverage of the terrorist operation. The study relied on the descriptive approach through the use of a tool to analyze the contents of the sample study papers about the events of the terrorist operation in the governorate of Karak.
Guides: Jazz: Searching the library catalogue

Use this guide to discover information sources about jazz performance and research topics. This evolving guide facilitates access to important resources, and provides samples of the types of materials available to members of the McGill community. This page provides tips and tricks on how to search the library's catalogue.
Probability hypothesis density filter for phased array radar working in TAS mode

The probability hypothesis density (PHD) filter is a multi-target tracking (MTT) method based on random finite set (RFS), providing an approximation implementation of the multi-target Bayes filter by propagating the first order moment of multi-target posterior. The PHD filter not only takes into account the accuracy of target state estimation, but also has good real-time performance, which is very suitable for radar MTT applications. In order to apply the PHD filter to scenarios with phased array radar working in track-and-search (TAS) mode, this paper proposes a time-matching recursive PHD filter. In order to handle the MTT in a TAS scenario where adjacent directions of the surveillance area are not continuously scanned, the proposed filter propagate PHD of each sector independent of others. It also introduces the time-matching filtering framework and multi-sensor multi-target recursive filtering framework to update PHD multiple times for each single sector at each time step, which can handle the MTT in scenarios where sectors have different sampling rates. The proposed method is simulated using the Gaussian mixture model, and the results, compared with those of standard PHD filter, demonstrate the effectiveness of it.
A Descriptive Study of the Difficulties in Using Regular and Irregular Verbs in Simple Past Tense of the Eighth Grade Students at SMP Muhammadiyah 3 Banyuwangi

The research design of this study was descriptive. The objective of this thesis was to know the difficulties of the students in using regular and irregular verbs in simple past tense. This research was conducted in SMP Muhammadiyah 3 Banyuwangi in which the respondents were the eighth year students. They were chosen by population technique. The number of respondents in this research was 136 students. In this research, the researcher used a test as the main method of collecting data. To analyze the collected data, the reearcher used percentage method. They are 136 students as the research sample which was taken by using population. It means the Eighth Grade from VIII A to VIII E. Based on the result of the data analysis, it can be known the percentage of the students’ difficulties in using regular and irregular verbs in simple past tense is 47,5%. The number of the students that chose incorrect answer almost equal with the number of the students that chose correct answer. It shows that many students were still having difficulties in using regular and irregular verbs in simple past tense.
Mr Paul Aharon taking samples from a giant clam

Research School of Earth Sciences, Environmental Geochemistry Group - Allan Chivas, John Chappell, Paul Aharon, Dr. Tom Torgersen, Dr. E. Lilley, Mr. H. Tammemagi
Taman Baca Kabupaten Bojonegoro Sebagai Wisata Literasi

In general, libraries have social and educational functions. The goal is to increase public interest in reading, but requires the intervention of various parties such as the government. The government's role is to become mobility for the community by facilitating facilities and infrastructure. One of the forums for reading activities in Bojonegoro is the Regional Library (Perpusda) at the Office of the Archives and Regional Libraries of Bojonegoro Regency. The current condition of the Bojonegoro Regency Regional Library is still not perfect because it is still mixed up with the Office, this creates a formal impression for library visitors which makes people uncomfortable in the library. The importance of planning a reading park in Bojonegoro as a literacy tour that is able to provide a place for reading education with a creative nuance. It is hoped that with a recreational nuance, it can provide a different nuance and a new reading platform in Bojonegoro. Keywords: Reading Gardens, Public Libraries, Literacy Tourism
Visualization of plasma shape in the LHD-type helical fusion reactor, FFHR, by a deep learning technique

A magnetic field is used to confine the plasma to achieve controlled fusion. Therefore, since the movement of the plasma follows magnetic field lines, a plurality of magnetic field lines is calculated from electromagnetic field simulation results in a fusion reactor. Because of the complicated distribution of magnetic field lines in three-dimensional (3D) space, existing analysis measures which are mostly based on two-dimensional poloidal plasma cross-sections are unsatisfactory for domain experts. To solve this problem, we propose a technique for reconstructing a regular scalar field from the magnetic field lines. First, on poloidal plasma cross-sections, intersection points of magnetic field lines are used to make annotations of learning the plasma shape. Then, a deep neural network is built to approximate the scalar field that represents the probability of the existence of magnetic field lines. Consequently, a 3D model of plasma shape has managed to be constructed by applying the marching cubes method. The effectiveness of the proposed method is demonstrated by comparing it with the conventional method and domain experts’ reviews.
Electronic communications: The French Supreme Administrative Court rejects the appeals lodged against the measures taken by the Autorité de régulation des communications électroniques, des postes et de la distribution de la presse to redress the collective press distribution system (Marie Claire Album et Revue du Vin de France ; Coopérative des Editeurs Libres et Indépendants)

In a first judgment (No. 442464), in two sets of joint applications, companies in the publishing sector asked the Conseil d'Etat to annul Decision No. 2020-0682 of 19 June 2020 of the Autorite de…
Ode aan de vampiers van de bouw

Amsterdam University Press is a leading publisher of academic books, journals and textbooks in the Humanities and Social Sciences. Our aim is to make current research available to scholars, students, innovators, and the general public. AUP stands for scholarly excellence, global presence, and engagement with the international academic community.
MLSSDCNN: Automatic Sentiment Examination Model Creation using Multi Domain Light Semi Supervised Deep Convolution Neural Network

Type Emotional research deliberated at categorizing positive or negative has fascinated more and more consideration in recent years. Traditional methods of emotional categorizing typically work well with labeled data. Transfer training is a popular method to solve problems where the model cannot be applied straight to the target domain in multi-domain emotional categorizing framework. This article intended a transfer learning system derived from the Light Semi Supervised Deep Convolution Neural Network (LSSDCNN). This LSSDCNN build a convolutional neural network model using extracted features moreover distribute the weights among all layers. In this article, LSSDCNN used five broad categories of Linguistic Inquiry and Word Count (LIWC) that includes linguistic and human psychological characteristics. Intellectual Broad Multi Domain Data Transfer Network employs sentences as well as aspects for extracting unique data. Particularly, this network intended to discover general features of multiple domains after that the retrieved aspects information through general features. To find out the predictive performance of proposed MultiDomain Light Semi Supervised Deep Convolution Neural Network (MDLSSDCNN), it is compared with existing sentiment models.
Application of The Know-Want to Know-Learned (KWL) Method to Improve the Ability of Reading Comprehension Science Texts

This research is motivated by the low reading comprehension ability of elementary school students. The purpose of this study was to optimize student activity and reading comprehension abilities in the form of zigzag book products using the Know-Want to Know-Learned (KWL) method in reading comprehension of science texts. The research was conducted at Karangsari 2 Elementary School, Cirebon District, to be precise in fifth grade with a total of 20 students. This study used a classroom action research method using the Kemmis and McTaggart model which was carried out in two cycles. The instruments used were evaluation guidelines, interviews, and documentation. In the first cycle, student's activity in categorizing ideas, making guide questions, and answering guide questions was still low. Student's ability to making zigzag books is still low. In the second cycle, student activity in reading comprehension and student's ability in making zigzag books increased. So that the average score of activity and the average score of the product in cycle II fulfills the minimum completion criteria score.
Astronomy Outreach Programs with STEM Ambassadors under the C3AOL Project

This paper reports our experiences in conducting outreach astronomy programs involving high school students and the general public. These programs are part of an interdisciplinary research project entitled Cross-cultural Computer supported Collaborative Learning for Student Capacity Building in Multifaceted Competencies through Astronomy Online Labs (C3AOL). As part of this research project, two selected undergraduate Physics students were named as STEM ambassadors and tasked in disseminating astronomical facts and concepts via outreach activities, thus consolidating their knowledge, creativity, and identity as STEM ambassadors. The STEM ambassadors have planned and conducted an Astronomy outreach program with high school students from the Pusat PERMATApintar Negara (currently known as Pusat GENIUS@Pintar Negara), UKM. This was followed by a public stargazing session at the National Planetarium, Kuala Lumpur that involved planetary and lunar eclipse observations. This project provided a valuable opportunity for the STEM ambassadors to convey astronomical knowledge effectively and interestingly in multiple contexts, whether amongst their peers or junior students, or even with the general public. A short-term impact of this project is the diffusion of their knowledge and enthusiasms in Astronomy to high school students as well as the general public through outreach programs such as dialogues session and talks at space centers and experience sharing via social media.
Machine Intelligence in Digital Pathology: Towards Personalized Medicine for Better Healthcare

An article written by Assoc. Prof. Dr. Mohammad Faizal Ahmad Fauzi, entitled “Machine Intelligence in Digital Pathology: Towards Personalised Medicine for Better Healthcare” published in the 79th Issue of SUARA TEEAM recently. The article discusses digital pathology, which is currently regarded as one of the most promising avenues of diagnostic medicine, and how machine intelligence in digital pathology can help paves the way towards the era of personalized medicine.This publication reflected on Dr. Faizal’s professional expertise and knowledge in the biomedical informatics field as well as recorded recognition for the Faculty of Engineering and Multimedia University (MMU). TEEAM or known as The Electrical and Electronics Association of Malaysia is a representative body of the electrical and electronics industries in Malaysia. Established in 1952, TEEAM works closely with all government departments, statutory bodies, and the private sector to promote the electrical and electronics industries.
Impact of gate input pulse width on FeFET-based reservoir computing

We experimentally demonstrate the relation between gate pulse width and computing performance in a physical reservoir computing system using a FeFET, where triangle pulses are input to the gate terminal and the time-series drain currents are treated as virtual nodes. The input signals with shorter pulse width lead to better memory capacity than those with longer one, which originates from extra information provided by charging/discharging current observed under fast-changing pulses.