Reviewerly/exHarmony huggingface dataset:
DEVELOPING AN E-COMMERCE DATABASE WEB APPLICATION FOR UNIVERSITY SPORT CONCESSION EVENT: A TEACHING CASE

This case study is developed to teach students the basics of developing a database web application.The background of the case is that a university wants to extend its sport concession event sale operation online.An e-commerce database web application is needed to capture online customer order, calculate Subtotal, Tax, and Total, and store order data into a database for future analysis.Students are asked to construct a MySQL database and a table to hold customer order data.Students also need to create a web page to take customer order.Moreover, students need to build a PHP application program to process the customer order, store data in the database, and display the new online order as well as all orders in the database table.The case study gives students a hands-on opportunity to develop a functional database web application using a popular platform -PHP and MySQL.
Music Computer Technologies and the ‘Soft Way to Mozart‘ System

Among the main objectives worked up by contemporary pedagogics in music, the authors focus their attention on the actual possibilities of digital technologies in enriching and enhancing the role of traditions that have been crystallized in practice of musical pedagogics for many centuries.The authors of the article analyze the problems concerning the current significance of contemporary musical notation, and, in particular, the ones being formed by the development of high-tech information environment, as well as the ways to solve some problems of learning music on the basis of music computer technologies using the Soft Way to Mozart system
SIMULASI POLA OPERASI EMBUNG SERBAGUNA TAMBAKSARI KABUPATEN CILACAP DENGAN METODE STANDARD OPERATING RULE (SOR)

Abstract Human survival depends on water availability as water is a basic needs. As population increases, water becomes more limited. One of the ways to prevent draught is collecting water in retention basin. Tambaksari Multipurpose Retention Basin serves to provide basic water demand and irrigation water for the local community. Water availability and water demand should be equal, so a simulation of the operating patter of the retention basin is necessary to distribute water equally and determining the failure level of the retention basin in performing its task. In the present study, the retention basin operating pattern was simulated using Standard Operating Rule (SOR) method. The present study used secondary data, including population data, rainfall data, climatological data and technical data of the retention basin. The size of DAS Tambaksari is 0.41 km² while the size of the irrigated land is 12 Ha. The rainfall data was from 2008-2018 obtained from two rain stations, population data of Tambaksari Village was from 2008-2019, and the climatological data was from 2014-2019. The simulation result of the retention basin operating pattern using SOR method showed that the final collection wasn’t under minimum collection and failure happened in the operation of the retention basin for one year. . The optimal ability of the target release is 70.83% for the reliability of irrigation needs and the level of reliability for raw water needs of 58.33%. Population projection analysis to determine the population in 20 years showed that the future population of 4044 required 3.861 l/person/s of water. Irrigation demands for rice-rice-palawija planting pattern showed that irrigation intake was 11.89 l/s. Water balance determined the balance between inflow and outflow. The value for average water availability was 0.021 m³/s while total average water demand was 0.016 m³/s. therefore, the water availability in partial intake wasn’t able to meet the irrigation and basic water demands. Keywords: discharge, retention basin operation simulation, SOR
Improvement of Accounting Experiment Teaching in Independent College under the Background of "Internet Plus"

With the rapid development of the society, the Internet has become the most important infrastructure widely used, and the new technology has been combined to create endless innovation with the help of the Internet.In the teaching in independent colleges, the accounting experiment teaching is constantly improving in order to meet the needs of the times for accounting talents.In the accounting experiment teaching, the Internet technology can also be introduced into the teaching link.By means of the transmission and application of the network knowledge and information, the experimental teaching mechanism can be perfected and the teaching method can be innovated.Moreover, it can expand the teaching content and improve the teaching method, so that the accounting experiment teaching can play its part.
Face Recognition Technology Based on Partial Facial Features

In the past two decades, many face recognition methods have been proposed. Among them, most researchers use the entire face as the basis for recognition. The basic technical route is to extract and compare the general features of the entire face. However, in actual scenes, human faces may be blocked by obstacles. Therefore, how to realize face recognition by using some of the facial features that can be obtained? In addition, this partial face recognition technology is mostly based on the acquisition of key points of the face to recognize the whole face. This review intends to summarize the full face and partial face recognition methods based on key points of the face.
EMEC, Ricardo link to support Isle of Wight hydrogen production

The European Marine Energy Centre (EMEC) in Orkney, Scotland and engineering consultancy Ricardo are supporting the delivery of a new solar powered hydrogen production facility on the Isle of Wight, which is being developed as part of feasibility funding from the UK's Rural Community Energy Fund.
An Efficient Classifier for Spam Detection in Social Network

The way to stay connects users with their friends provided by the Social networks. The popularity of social networks has been increasing day-by-day and enables users to collect huge volume of information about their friends. Various social networking sites are available among them, Twitter is fastest growing website. Due to its popularity various spammers are attracted towards it to utilized large amounts of spam to modify authorised users accounts. In this paper, the “Spam detection system in social sites” is developed for detection of spammer through the technique of machine learning. The work is initiated towards collection of data from H-Spam 14 site and then applied pre-processing mechanism such as conversion of data into lowercase and, removal of stop words etc. After this phase, the pre-processed data comes into the phase of feature extraction, which involves process of tokenization that used to split the entire sentences into a word-group and so the best features has been extracted from the raw data. To select the optimized value from extracted set of features, the optimization algorithm, Artificial Bee Colony (ABC) has utilized here to obtain the optimal sets of feature from spam along with non-spam data. The next process has to be done through Artificial Neural Network (ANN) to differentiate the spam and non-spam data. In the final process, the parameters for performance measure and compare the proposed and existing work to check the improvement in proposed work. In this proposed work the spam detection system gained higher accuracy, precision, recall and F-measure as compare to the previously utilized classifiers named as naïve Bayes and Support vector machine (SVM).
Chapter 2. Token attribution

The aim of this step is to check the previously assigned token types and to provide the letter tokens with morphological information, i.e. values of the relevant grammatical categories. As far as word forms are concerned, the procedure is normally called morphological analysis. However, since a text may contain other token types (e.g. abbreviations, formulae, Internet hyperlinks, phone numbers), it is generally referred to as token attribution. In the chapter, a wide range of token types are considered from the processing viewpoint. In particular, the letter token analysis presupposes a search in a number of dictionaries. Apart from a regular Russian morphological dictionary, search is also performed in the dictionaries of abbreviations, of fixed phrases, and of proper names (personal, geographical, etc.). Morphological analysis often yields more than a single attribution. In some cases, the ambiguity can be reduced by taking into account graphematical information, but most often, it will remain and pose further problems for the syntactic analysis. If the search for a letter token fails in all the dictionaries, the algorithm tries to identify its lemma and predict the grammatical meaning. The attribution of other token types is made by mapping them onto a range of patterns. Typical problems of both operations are discussed.
The Purposes of Code-Switching and Teachers’ Perceptions toward Code-Switching in Malaysian Primary Schools

This particular study is conducted to find out the purposes of teachers' codeswitching in the primary schools, the perceptions of teachers toward using students’ first language in the classrooms, and the amount of the usage of codeswitching in primary schools. A total number of 82 primary school English language teachers from the Johor Bahru state of Malaysia took part in this study. In order to collect comprehensive data from the participants, the researcher applied a mixed-method design. Quantitative data was collected through the Google Form questionnaire, which was sent to the teachers via WhatsApp, and Qualitative data was collected through interviews with five English language teachers of primary schools. The analysis of both types of data showed that the teachers use students’ L1 for three purposes, pedagogical, administrative, and interactional, but mainly students’ L1 was utilized as a pedagogical tool to facilitate language learning and as an administrative strategy to create a less threatening and learner-friendly environment. The results of the study also indicated that the majority of the teachers in the primary schools of Johor switch to students’ L1 to accommodate low proficiency learners and explain difficult concepts such as grammar and vocabulary to the learners. Eighty percent of the participant agreed to minimize the use of L1 in second language learning classrooms.
Classes of Objects

In R, objects belong to classes as well as modes and types. Classes tell something about how an object is structured. S3 and S4 differ with regard to classes. In S3, there are specific classes into which an R object falls. In S4, the user defines a class for an S4 object. Classes in S3 are called informal classes, whereas classes in S4 are called formal classes. This chapter covers both kinds of classes.
The Evolutions of Thoreau’s Science

Robert Sattelmeyer’s “The Evolutions of Thoreau’s Science” explores Thoreau’s scientific practice and its scholarly reception. Sattelmeyer examines the considerable body of scholarship that has developed surrounding Thoreau as a scientist and offers a overview of the gradual evolution of critical and scholarly appreciation for Thoreau’s scientific work, particularly as this developed during the last decade of his life. Sattelmeyer also argues that another vast but unfinished Thoreauvian project, collected in the so-called Indian Notebooks, had its lapse with the recognition of a fundamental impasse: “to attempt to understand the precontact culture of indigenous people by reading books by post-contact European explorers and missionaries is, at best, a tautology.” Thoreau’s broader interest, Sattelmeyer suggests, lay in the developing population patterns, by human communities as well as by plants and animals, of North America. Sattelmeyer then treats Thoreau’s hydrological study of the Musquetaquid watershed and Thoreau’s vast Kalendar project as defining his legitimate legacy as a scientist in his own right.
A Note from the Editor in Chief

Texture image retrieval and classification tasks are conducted widely in computer vision but few studies have considered the same problem for decorations and textures applied to surfaces. Thus, in order to address this problem, we propose an algorithm for retrieving and classifying color patterns over surface meshes. In this study, we explored the capability of edgeLBP descriptors for retrieving and classifying color patterns over surface tessellations. Our experimental results demonstrated that these descriptors performed well at pattern retrieval, including for patterns on degraded and corrupted archeological fragments. We compared the performance of the edgeLBP descriptors with a recent benchmark and conducted an extended analysis of the robustness of this technique to mesh remeshing and surface decimation.
Communication Skills and Its Impact on the Academic Capabilities of Deaf Children in Inclusive Educational Setting: The Case of Selected Primary Schools in North Gondar Zone

The study was conducted in three primary schools of North Gondar Zone such as Serko, Chuhit and Limatber.The participants of the study were deaf children, their hearing peers, special needs education teachers and school principals.12 deaf children, 5 special needs teachers, 6 school principals and 5 hearing children were the informants of the study.Interview, observation, focus group discussion (FGD), informal talks and document review were the data gathering instruments.The data collected through different instruments were analyzed qualitatively.The result of the study also showed that the mode of commination for deaf children with deaf, their hearing peers and teachers were different in different activities such as: In play, teaching-learning process and other social activities.In addition, the result of the study revealed that those deaf children who have better communication skills have better academic abilities and achievement It is recommendations that the professional capacity of special needs education teachers should be enhanced by the schools using series on the job trainings; the school should work more on sign language training.
DCT statistics and pixel correlation-based blind image steganalysis for identification of covert communication

The interconnection of systems through networks, access to information, computer technologies and furtherance of image steganography techniques exploited to send secret information on social network builds the requisite of image steganalysis. Existing image steganalysis methods are either domain specific or the one which requires large dimensional feature set. Considering the types of image steganography methods, embedding rates, image types and feature dimensionality there is an utmost need of a low dimensional blind image steganalysis method. This paper proposes a 32-D DCT statistics and pixel correlation (DSPC) based blind image steganalysis algorithm with the aim to the reduced time complexity of feature extraction as well as the complexity of classifier. The performance of the proposed algorithm is evaluated using experiments with varying embedding message size, message types and image formats using ensemble classifier. The algorithm is implemented in MATLAB and all the experiments are performed on BSDS300 and CorelDraw image datasets.
Indicator minerals in kimberlites and their respective stream sediments, Gibeon kimberlite province, Namibia

This study deals with macrocrystic kimberlite indicator minerals from Anis Kubub, Berseba Reserve (Ovas), Diamantkop, Hanaus 2, Mukorob, Lichtenfels, Louwrensia and Achterfontein kimberlite suite from the off-craton Gibeon Kimberlite Province of Southern Namibia.The aim was to study the composition and distribution of kimberlite indicator minerals in the pipes and dykes as well as sediments from streams draining the kimberlite area.Altogether 15 pipes and dykes and 37 stream sediments were sampled.Streams samples were mainly taken from trap sites where maximum amounts of heavy minerals were accumulated and from weathered surfaces of kimberlite pipes and dykes.Indicator minerals were hand-picked from 0.5-1.0mm and 1.0-2.0mm fractions of the concentrates.The minerals included purple, red, reddish-brown and orange garnets, black ilmenite,
Source Area Weathering, Paleo-Environment and Paleo-Climatic Conditions of Soils from Bitumen Rich Ode Irele Area of Ondo State, Nigeria

The study is aimed at determining the source-weathering, paleo-redox and paleoclimatic conditions of soil from Ode Irele area of Ondo State, Nigeria. X-Ray Fluorescence (XRF) and the Laser Ablation Inductively Coupled Plasma-Mass Spectrometry ICP-MS) analyses wereusd to determine the major, trace and rare earth element compositios used for the study. The Chemical index of alteration (CIA), Chemical index of weathering (CIW), Plagioclase index of alteration (PIA), Mineralogical index of alteration (MIA), Th/U nd a plot of CIA against Al2O3 as well as the A-CN-K Ternary diagram suggest a high degree of weathering of the source rocks. The positive correlation between Al2O3 with TiO2, K2O, Fe2O3 and MgO implies that they occur in clay minerals formed from weathering. The average K2O/Al2O3 ratios of the investigated samples is ?0.006, which suggests prevalence of clay minerals relative to other minerals. Low U/Th ratio ranging between 0.14 and 0.50 (average 0.18) relative to PAAS (0.21) and UCC (0.26) suggests deposition under oxic conditions. V/Vi + Ni ratios indicate suboxic to anoxic environment of deposition. However, plots of V/V+ Ni vs Ni/Co and V/Cr vs Ni/Co indicate oxic, dysoxic and suboxic to anoxic environments all suggesting deposition under oxic and suboxic conditions. The Ode Irele sediments was deposited in low saline water with a strong continental rather than marine influence in an arid and semi-arid climatic condition; the low average ratio of P2O5/Al2O3 (0.014) is in unison with freshwater environments.
INFORMATION SECURITY EDUCATION SYSTEM IN SECONDARY SCHOOL AND ASSESSMENT OF THE LEVEL OF ANXIETY OF SCHOOLCHILDREN

The analysis of the results of scientific research has revealed the necessity to track the level of anxiety of a student while studying aspects of information security in a particular subject area.And in accordance with the results, it was necessary to justify the choice of methods for management and content of information security training in order to minimize the negative impact on the psychological state of a child of middle school age.The purpose of the research is to determine the impact of educational elements from a specific subject area related to information security guaranteeing on the level of anxiety of secondary schools students.The authors identified the need to assess the level of anxiety of students while studying aspects of information security in a particular subject area and proposed tools for tracking the level of anxiety.In the middle school, during the formation of a comprehensive idea of professional activities in the field of information security, especially at the pre-profile stage, an approach that forms the basis for the formation of the content of information security training is substantiated.It combines the knowledge from a wide range of different sciences for teaching secondary school students.The study shows that the level of situational anxiety of secondary school students while studying aspects of information security in a particular subject area can increase due to the natural reaction of the body, adapting to new potential threats for it.It was experimentally established that the level of personal anxiety as a result of assimilation of new knowledge about information security did not change both before studying the educational elements of information security in a particular subject area, and after studying them.
Efficient Technique to Detect Edge in Images with Fuzzy Rules

There exists an increasing demand to detect edge of an image for many real time applications. In this paper an innovative technique is proposed for detecting text using fuzy rules. The projected system primarily divides the image into fragment of 3 x 3 matrix. The proposed system uses fuzzy rules using input size of eight pixels and one output pixel. The output pixels will either be one among black, white or edge pixel. The fuzzy sytem is applied with sixteen rules for categorizing the pixel as target pixel. Fuzzification is performed which converts the input pixel into the fuzzy interval between zero and one. It is followed by calculating a degree of Hesitation, which is also called as the intuitionstic fuzzy indicator. The last step is the Defuzzification process where the pixel identified as the pixel is converted to its original image pixel with the interval between 1 and 255. The proposed system is weighed against existing edge detecting methods like Canny, Sobel, and ACO algorithm. The proposed algorithm works fine even for exigent scenarios of the image.
Artificial Intelligence – State of Art Convolution Neural Network Architectures in a Nutshell

It is a well-known fact that all the Artificial Intelligence (AI)researches happening across multiple verticals such as Neuro Imaging, Computer Vision, Deep learning etc point to one master goal of modelling the human brain function by understanding how each part of the brain works. The Convolution neural network (CNN) is one of best deep architecture suitable to handle variety of inputs. In this paper we explore the different types of input data the CNN deep architecture can process and some of the CNN configuration changes that has proved good Accuracy. We have highlighted those specialized CNN architectures along with different types of data inputs they handle including the Functional Magnetic Resonance (fMRI) Neuro Image brain data input.
P.788 Associative learning and resting-state connectivity changes in the adult brain

Label distribution learning (LDL) is one of the paradigms for dealing with label ambiguity, and it can learn the relative importance of each label to a particular instance. Most of the existing LDL approaches require strong supervision information, which always involves high cost of the data-labeling process. To this end, we propose a novel transductive weakly supervised LDL algorithm based on matrix completion, which simultaneously explores the discriminant knowledge of both training instances and testing instances. Moreover, the manifold regularization is exploited to capture the samples’ relevance to enhance the performance of matrix completion. Experimental results on real-world data sets with various missing percentages validate the effectiveness of our method.
Discriminant Pearson Correlative Feature Selection based Gentle Adaboost Classification for Medical Document Mining

This paper examines Discriminant Pearson Correlative Analysis Based Multivariate Gentle Adaboost Classification (DPCA-MGAC) and it is used to improve the performance of medical document mining with minimum time complexity. A large number of documents are collected from PubMed databases through the semantic-based search. Processes such as removing stop words, stemming, features identification, selection of features i.e., relevant keywords for document classification are carried out. The significant feature selection is carried out using DPCA, and with the selected features the documents are categorized into different classes using MGAC. This classification process combines the results of all weak learners and makes a strong classification in order to improve the precision of medical data mining and minimizes the false positive rate. Experimental evaluation has been performed using PubMed database.