Reviewerly/exHarmony huggingface dataset:
Compositional characteristics and Ta-Sn-Nb rare metal mineralization potential of Egbe Pegmatite, Southwestern Nigeria

Pan African (600 ± 150) pegmatite which intrudes gneisses, amphibolites, quartzite and schists around Egbe area were studied for their compositional features. This is with a view to characterizing and assessing their potential for rare metal Ta-Sn-Nb mineralization. Twenty seven samples comprising eleven (11) whole rock, sixteen (12) muscovite extracts and four (4) feldspar extracts samples were analyzed using the Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES). Major oxide geochemical assessment of the whole rock pegmatite indicates that the pegmatite is siliceous (79.82% SiO2) and moderately high in Al2O3 (12.22%). The K2O, Na2O contents are averagely 2.25% and 2.87% respectively while Fe2O3, MnO, MgO are each less than 1.0%.&#x0D; Average values of trace elements in the pegmatite are Ta (52.55ppm), Sn (92.3 ppm), Rb (1083.5ppm), Nb (109.35 ppm), Cs (32.12ppm), Sr (17.84 ppm), Y (9.86 ppm), and Zr (41.27 ppm), Ba (50.47ppm), Hf (12.38ppm), Zr (41.27ppm), Ga (32.12ppm) and W(2.91PPM) and ratios of diagnostic elements are K/Rb (30.27), Rb/Sr (298.93), Zr/Hf (7.23), Rb/Cs (65.80), K/Cs (1103.11), Ta/W (41.81), Nb/Ta (55.397) Na/Rb (41.77) and Na/K (92.25) A/CAN &gt;1and Al2O3&gt;CaO+ Na2O+ K2O with enrichment of SiO2, Al2O3, Na2O, K2O and depletion of Fe2O3, MnO2 and MgO suggests that Egbe pegmatite is of peraluminous bulk composition and plots of A/NK vs Al/CNK and Rb vs (Y+Nb) discriminates Egbe pegmatite in the peraluminous LCT (Li, Rb, Cs, Be, Ga, Nb &lt;,&gt; Ta, Sn, Hf, B, P, F) of syncollisional to within plate granitic family. The Ta/W vs Cs plot for the three sample media shows the relationship between increasing Ta/W ratio and elemental fractionation as indicated by Cs. The K/Rb vs Cs and K/Rb vs Rb plots for the three sample media further establishes the rare – metal nature and mineralization potential of Egbe pegmatite. Using the discriminant plots of TaVs Rb, Ta vs Cs .TaVs K/Cs, and Ta Vs (Cs+Rb) where most of the samples of the whole rock pegmatite and mineral extracts plots above the Beus line and about 30% plotting above the Gordinyenko line respectively. Overall geochemical assessment is that Egbe pegmatite is a rare metal, highly fractionated Beryl type with rare metal enrichment trend of Nb&gt;&gt;Sn&gt;&gt;Ta.&#x0D; Keywords: Pegmatite, Peraluminous, Syncollisional, Within-plate, Discriminant, Fractionation, Sample media
Warehouse Inventory Management System for the Smooth Delivery of Cargo to Reduce Dwelling Time at the Port of Tanjung Emas Semarang

Delivery cargo is a job of moving goods from the pile or a heap in the warehouse, handing it to be arranged on the vehicle and sending it to the receiving warehouse (consignee). The delivery of goods in the form of fertilizer carried out by PT. PUSRI (Pupuk Sriwijaya) at the Port of Tanjung Emas Semarang from the first line warehouse to each branch of the receiving warehouse throughout Indonesia experienced problems. The problem faced in the activities of the cargo delivery is the delay in the process of shipping goods caused by one of them by a bad warehouse inventory management system so that dwelling time is getting longer. Therefore, a good warehouse inventory management system is needed. This system has several functions, among others, as storing detailed information of goods and pointing to the location of goods. Warehouse inventory management system created with the Internet of Things was developed to track the goods / products that were previously recorded. In monitoring all information used Aduino. the web was built to provide comfort and ease in finding goods / products. With this system the cost required is low and efficient and very easy to use.
Perspective of nursing professionals on the discharge of patients suffering from recurrent myocardial infarction

the present study aims to understand how nursing professionals develop their care activities in face of the victim of recurrent acute myocardial infarction in the discharge process from the specialized intensive care unit. It is a research with a qualitative approach anchored in the methodological precepts of Convergent Care Research (PCA), articulating intervention and assistance, divided into two complementary phases, with five professionals working in the coronary intensive care unit of a hospital in the south of Mato Grosso . The data were collected through interviews with the use of a semi-structured script prepared by the authors. From the transcription of the interviews, categories of analysis emerged: “The development of technical knowledge and the execution of routine” and “Praxis and the need for advances in scientific nursing knowledge”. In addition to the assistance aspect, it was possible to understand, through the statements made explicit throughout the study, the absence of the professional nurse in the care process, since they were mentioned in a correlated way with the institutional routines and not as the main agents that propagate health care. care and guidance, especially at discharge from the unit. Thus, it is suggested the planning of the discharge process of the unit, with proper structuring capable of showing the interprofessionality between the care teams working in the unit, and in the context of nursing, its technical-scientific role.
The Adoption of Electronic Inventory Control System in Cairo Five-Star Hotels

This paper aims to evaluate of the stores' department to adopt electronic inventory control systems in five -star hotels in Cairo.To achieve the objective of the study, the 170 questionnaire forms distributed to stores staff (store manager, assistant store manager, storekeeper, assistant storekeeper, inventory controller) in 34 Five -star hotels in Cairo.The number of valid questionnaires for analysis is 157 with a response rate (92.35%).The data analysis was conducted through the statistical package of social sciences SPSS (version 26.00).The study found that the electronic inventory control systems' benefits affect the stores department in Fivestar hotels in Cairo to adopt electronic inventory control systems.
Beyond Trees: Classification with Sparse Pairwise Dependencies

Several classification methods assume that the underlying distributions follow tree-structured graphical models. Indeed, trees capture statistical dependencies between pairs of variables, which may be crucial to attain low classification errors. The resulting classifier is linear in the log-transformed univariate and bivariate densities that correspond to the tree edges. In practice, however, observed data may not be well approximated by trees. Yet, motivated by the importance of pairwise dependencies for accurate classification, here we propose to approximate the optimal decision boundary by a sparse linear combination of the univariate and bivariate log-transformed densities. Our proposed approach is semi-parametric in nature: we non-parametrically estimate the univariate and bivariate densities, remove pairs of variables that are nearly independent using the Hilbert-Schmidt independence criteria, and finally construct a linear SVM on the retained log-transformed densities. We demonstrate using both synthetic and real data that our resulting classifier, denoted SLB (Sparse Log-Bivariate density), is competitive with popular classification methods.
Performance Analysis for Mining Images of Deep Web

In this paper, advancing web scale knowledge extraction and alignment by integrating few sources has been considered by exploring different methods of aggregation and attention in order to focus on image information.An improved model, namely, Wrapper Extraction of Image using DOM and JSON (WEIDJ) has been proposed to extract images and the related information in fastest way.Several models, such as Document Object Model (DOM), Wrapper using Hybrid DOM and JSON (WHDJ), WEIDJ and WEIDJ (no-rules) are been discussed.The experimental results on real world websites demonstrate that our models outperform others, such as Document Object Model (DOM), Wrapper using Hybrid DOM and JSON (WHDJ) in terms of mining in a higher volume of web data from a various types of image format and taking the consideration of web data extraction from deep web.
Application of Wavelet Neural Network in Building Settlement Prediction

Deformation monitoring, as a key link of information construction, runs through the entire process of the building design period, construction period and operation period[1]. At present, more mature static prediction methods include hyperbolic method, power polynomial method and Asaoka method. But these methods have many problems and shortcomings. In this paper, based on the characteristics of building foundation settlement and the methods widely discussed in this field, a wavelet neural network model with self-learning, self-organization and good nonlinear approximation ability is applied to the prediction problem of building settlement[2]. Using comparative analysis and induction method. The 20-phase monitoring data representing the deformation monitoring points of different settlement states of the line tunnel, using the observation data sequence of the first 15 phases respectively to take the cumulative settlement and interval settlement as training samples, through the BP artificial neural network and the improved wavelet neural network, for the last five periods Predict the observed settlement.Through the comparison, it is found that whether the interval settlement or the cumulative settlement is used, the prediction results of the wavelet neural network are basically better than the prediction results of the BP artificial neural network, and the number of trainings is greatly reduced. The adaptive prediction of the wavelet neural network. The ability is particularly obvious, and the prediction accuracy is significantly improved. Therefore, it can be shown that the wavelet neural network is indeed used in the settlement monitoring and forecast of buildings, which can obtain higher prediction accuracy and better prediction effect, and is a prediction method with great development potential.
Preparation For Intercultural Interaction In Modern Russian Higher Education

The intercultural orientation of modern social thought is implemented in educational policy, considering a modern university graduate as a person, not just possessing specific competences and knowledge, but also capable of cooperating and constructive multicultural dialogue, interacting with people of different cultures and knowing the system of socially significant world values.In modern pedagogical science, considerable experience has been accumulated in preparing students of different specialities for intercultural interaction, forming and developing the tolerance, intercultural communicative competences, educating the younger generations in a multicultural world.Nevertheless, the issue of preparing would-be specialists for intercultural interaction in the context of the content and language integrated environment remains poorly developed today.So, the main aim of our research is to consider the modern Russian higher education from the point of view of the process of preparing would-be specialists for intercultural interaction for determining the degree of their readiness for the adequate intercultural dialogue.
Development of modern models and methods of the theory of statistical hypothesis testing

Typical problems of the theory of statistical hypothesis testing are considered. All these problems belong to the same object area and are formulated in a single system of axioms and assumptions using a common linguistic thesaurus. However, different approaches are used to solve each of these problems and a unique solution method is developed. In this regard, the work proposes a unified methodological approach for formulating and solving these problems. The mathematical basis of the approach is the theory of continuous linear programming (CLP), which generalizes the known mathematical apparatus of linear programming for the continuous case. The mathematical apparatus of CLP allows passing from a two-point description of the solution of the problem in the form {0; 1} to a continuous one on the segment [0; 1]. Theorems justifying the solution of problems in terms of CLP are proved. The problems of testing a simple hypothesis against several equivalent or unequal alternatives are considered. To solve all these problems, a continuous function is introduced that specifies a randomized decision rule leading to continuous linear programming models. As a result, it becomes possible to expand the range of analytically solved problems of the theory of statistical hypothesis testing. In particular, the problem of making a decision based on the maximum power criterion with a fixed type I error probability, with a constraint on the average risk, the problem of testing a simple hypothesis against several alternatives for given type II error probabilities. The method for solving problems of statistical hypothesis testing for the case when more than one observed controlled parameter is used to identify the state is proposed
Adaptive Inception Based on Transfer Learning for Effective Visual Recognition

In computer vision, domain adaptation or transfer learning plays an important role because it learns a target classifier characteristics using labeled data from various distribution. The existing researches mostly focused on minimizing the time complexity of neural networks and it effectively worked on low-level features. However, the existing method failed to concentrate on data augmentation time and cost of labeled data. Moreover, machine learning techniques face difficulty to obtain the large amount of distributed label data. In this research study, the pre-trained network called inception layer is fine-tuned with the augmented data. There are two phases present in this study, where the effectiveness of data augmentation for Inception pre-trained networks is investigated in the first phase. The transfer learning approach is used to enhance the results of the first phase and the Support Vector Machine (SVM) is used to learn all the features extracted from inception layers. The experiments are conducted on a publicly available dataset to estimate the effectiveness of proposed method. The results stated that the proposed method achieved 95.23% accuracy, where the existing techniques namely deep neural network and traditional convolutional networks achieved 87.32% and 91.32% accuracy respectively. This validation results proved that the developed method nearly achieved 4-8% improvement in accuracy than existing techniques.
Development Of Musical Perception In Children Of Senior Pre-School Age

The paper considers the possibilities of developing the perception of music in children of pre-school age through musical and game activity, reveals the developing potential of the music game, presents the results of diagnostics on the development of musical perception of pre-school children in the conditions of the game, highlights the development indicators of musical and game creativity of pre-school children.The study shows that musical and play activities of children of older pre-school age become purely creative in the accumulation of experience of musical perception while mastering variable forms of music games built taking into account the mechanism of development of children's musical creativity.Practical learning of music perception based on game interaction allows pre-school children creatively reflecting their impressions of a musical work.Musical and game creativity of children becomes associative and syncretic thus developing creative imagination, musical thinking, ability to consistently realize the set goals in different ways of approval, reflect the content of music in creative motor interpretations, drawings, writing fairy tales and stories, drama and pantomime, which increases the possibilities of selfexpression, self-realization of personality by means of art.
Ontological Analysis and Modularization of CIDOC-CRM

The CIDOC-CRM ontology is a standard for cultural heritage data modeling. Despite its large exploitation, the ontology is primarily maintained in a semi-formal notation, which makes it difficult to homogeneously exploit it in digital environments. In addition, the ontology consists of several classes and relations, whereas one sometimes wishes to reuse it but only partially. The purpose of the paper is to contribute to the use of CIDOC by strengthening its foundations. On the basis of formal ontology theories, we propose a first analysis of the ontology to enhance its conceptual structure. We also present a preliminary modularization of CIDOC aimed at enhancing both its formalization and usage.
Cicada Swarm Optimization: A New Method for Optimizing Persistent Problems

This paper proposes a new meta-heuristic swarm optimization algorithm called Cicada Swarm Optimization (CISO) algorithm, which mimics the behavior of bio-inspired swarm optimization methods. The CISO algorithm is tested with 23 benchmark functions and taken two problems engineering design, pressure vessel problem and himmelblau’s problem. The performance of CISO algorithm is compared with meta-heuristic well-known and recently proposed algorithms (Cockroach Swarm Optimization (CSO), Grasshopper Optimization algorithm (GOA) and Particle Swarm Optimization (PSO)). The obtained results showed that the proposed algorithm succeeded in improving the test functions and solved engineering design problems that could not be improved by other algorithms according to the chosen parameters and the limits of the research space, also showed that CISO has a faster convergence with the minimum number of iterations and also have an accurate calculation efficiency Satisfactory compared to other optimization algorithms.
Outlier Detection Method based on Adaptive Clustering Method and Density Peak

The outlier detection technique is widely used in the data analysis for the clustering of data. Many techniques have been applied in the outlier detection to increase the efficiency of the data analysis. The Local Projection based Outlier Detection (LPOD) method effectively identifies neighbouring values of data, but this has the drawback of random selection of the cluster centre that affects the overall clustering performance of the system. In this study, the Adaptive Clustering by Fast Search and Find of Density Peak (ACFSFDP) is proposed to select the clustering centre and density peak. This ACFSFDP method is implemented with the min-max algorithm to find the number of categories that measured the local density and distance information. The density and distance are used to select the cluster centre, but density is not calculated on the existing distance based clustering techniques. The ACFSFDP method calculates cluster centre based on the density and distance during the clustering process, whereas the existing techniques randomly select the data centre. The results indicated that the ACFSFDP method is provided effective outlier detection compared with existing Clustering by Fast Search and Find of Density Peak (CFSFDP) methods. The ACFSFDP is tested on two datasets Pen-digits and waveform datasets. The experiment results proved that Area Under Curve (AUC) of the ACFSFDP is 99.08% on the Pen-Digit dataset, while the existing distance classifier method k-Nearest Neighbour has achieved 68.7% of AUC.
Narasi Visual Buku Pop-up Carousel tentang Edukasi Perilaku Hidup Bersih dan Sehat untuk Anak

Abstrak—Buku pop-up sebagai media bercerita dan pembelajaran pada anak sering dijumpai. Narasi visual yang disusun untuk menuturkan cerita melalui bahasa gambar pada buku cerita anak umum dilakukan. Namun, buku pop-up dengan format carousel yang bersifat interaktif memerlukan strategi khusus dalam menyusun narasi visualnya agar isi cerita dan pesan yang ingin disampaikan dapat diterima oleh anak selaku pembaca. Tujuan penelitian ini adalah untuk menjabarkan proses kreatif penyusunan narasi visual pada buku pop-up carousel tentang edukasi Perilaku Hidup Bersih dan Sehat (PHBS) untuk anak. Metode yang dilakukan yaitu metode penelitian kualitatif. Pengumpulan data dilakukan dengan kajian pustaka, observasi langsung dan mendokumentasi obyek dalam bentuk foto. Analisis data menggunakan metode deskriptif naratif, yaitu dengan menguraikan elemen-elemen visual secara deskriptif berdasarkan kajian pustaka yang dipakai yaitu prinsip-prinsip layout. Hasil penelitian ini dapat dijadikan referensi bagi para layouter dan ilustrator buku cerita anak dalam menyusun narasi visual sebagai fungsi deskriptif dan ekspresif dari sebuah naskah cerita. Abstract — Pop-up books as a medium for storytelling and learning in children are often encountered. Visual narratives that are structured to tell stories through the language of pictures in children's storybooks are common. However, pop-up books with an interactive carousel format require a special strategy in compiling the visual narrative so that the content of the story and the message it wants to convey can be accepted by children as readers. The purpose of this research is to describe the creative process of composing visual narratives in the pop-up carousel book about education on a Clean and Healthy Lifestyle (PHBS) for children. The method used is a qualitative research method. Data collection was carried out by literature review, direct observation, and document objects in the form of photographs. The data analysis used a descriptive narrative method, namely by describing the visual elements descriptively based on the literature review used, namely the principles of layout. The results of this study can be used as a reference for layouters and illustrators of children's storybooks in compiling visual narratives as a descriptive and expressive function of a story script.
Comparative study on the performance of microscopic and rapid diagnostic test (RDT) for malaria among some patients in Maiduguri metropolis

Malaria remains a major public health problem in Nigeria, that a positive, accurate and reliable microscopy or RDT should preferably be obtained before commencing treatment. High specificity will reduce unnecessary treatment with antimalarial drugs and improve the diagnosis. This study analyze the performance of microscopy and Rapid Diagnostic Techniques (RDT) used in the diagnosis of malaria at the University of Maiduguri Teaching Hospital, Maiduguri, Borno State, Nigeria from September to October, 2019. A total of 118 blood samples was screened for malaria by preparation of thick and thin film, Leishman staining and microscopic examination of the slides under oil immersion objectives. Rapid Diagnostic test (RDT) was performed using NADAL® Malaria 4 species test cassettes, with emphasis on falciparum malaria. The results shows that 65 patients (55.1%) were positive for malaria, out of which 42 (64.6%) were males, mainly (24.6%) within the young age group (1-10 years). Some of the patients 17 (26.2%) have started taking antimalarial drugs before coming to the hospital. Out of the 96 patients presented with acute malaria, only 43 (66.2%) were positive, but all those with severe cases (33.8%) were positive by both microscopic and RDT tests. In general, 53 patients (81.5%) were positive by microscopy, while only 12(18.5%) are RDT-positive. The study revealed a low performance of RDT with high number of false negative tests compared to microscopy on the same samples. It is therefore, necessary to reinforce training in microscopy, improved supplies and ensure proper handling/storage of the rapid test kits in malaria-endemic area, like Nigeria.