Reviewerly/exHarmony huggingface dataset:
System Design Estimation of Cost for Laying Chicken Feed Formulation using Web-Based Square Pearson Method

Feed is one important element that needs to be considered in the livestock business, one of which is laying hens. The type and amount of feed will affect the nutrients obtained, these nutrients will affect the ability to produce eggs. One way to produce feed that contains optimal nutrition is done by mixing various types of feed ingredients such as corn, bran, cake, soybeans, concentrate and so on into one right composition. Expenditures for the purchase of feed are also among the highest expenses in any livestock business and therefore need to be regulated in such a way as to provide optimal benefits. The square pearson method is a method of determining the formulation of feed which on one hand contains complete nutrients, on the other hand is economically inexpensive and easily obtained so that it can provide benefits. The results of this study produce a system that can estimate the cost of calculating web-based laying hens feed formulations.
A Family of Mixture Models for Biclustering

Biclustering is used for simultaneous clustering of the observations and variables when there is no group structure known \textit{a priori}. It is being increasingly used in bioinformatics, text analytics, etc. Previously, biclustering has been introduced in a model-based clustering framework by utilizing a structure similar to a mixture of factor analyzers. In such models, observed variables $\mathbf{X}$ are modelled using a latent variable $\mathbf{U}$ that is assumed to be from $N(\mathbf{0}, \mathbf{I})$. Clustering of variables is introduced by imposing constraints on the entries of the factor loading matrix to be 0 and 1 that results in a block diagonal covariance matrices. However, this approach is overly restrictive as off-diagonal elements in the blocks of the covariance matrices can only be 1 which can lead to unsatisfactory model fit on complex data. Here, the latent variable $\mathbf{U}$ is assumed to be from a $N(\mathbf{0}, \mathbf{T})$ where $\mathbf{T}$ is a diagonal matrix. This ensures that the off-diagonal terms in the block matrices within the covariance matrices are non-zero and not restricted to be 1. This leads to a superior model fit on complex data. A family of models are developed by imposing constraints on the components of the covariance matrix. For parameter estimation, an alternating expectation conditional maximization (AECM) algorithm is used. Finally, the proposed method is illustrated using simulated and real datasets.
NOVICE UNIVERSITY TEACHERS: COMPARISON OF YOUNG PROFESSIONALS WITH AND WITHOUT PEDAGOGICAL EDUCATION

Purpose of the study: To determine problems of novice university teachers without pedagogical education face in professional, psychological, and motivational spheres of induction and compare the frequency of the detected problems in these spheres of induction process within the groups of novice university teachers with and without pedagogical education. Methodology: An exploratory inductive approach was adopted in this study. 93 novice educators took part in the series of surveys. The researchers applied the quantitative method to collect data using a questionnaire. The study involved quantitative data analysis containing the descriptive statistical analysis and the correlation analysis in SPSS Version 23 (IBM Corp., 2016), which provided the researchers with new insights and detailed results. Main Findings: All novice university teachers face problems of adaptation to professional activity. Comparison of novice university teachers with and without pedagogical education resulted in the following findings: the difference between the values of novice teachers with and without a teaching degree is, in most cases, statistically significant. It makes it possible to conclude that university teachers without pedagogical education need support via additional educational programmes. Applications of this study: This study can be useful in planning the curriculum for postgraduate students. Educational authorities should take into consideration the identified difficulties faced by young university teachers without pedagogical education in the process of planning the curriculum for postgraduate education programmes and professional development programmes. Novelty of this study: This research is particularly relevant for improving the professional culture of specialists in the field of education and contributes to the solution of the professional adaptation problem faced by novice educators. The obtained results can enhance the educational programmes of the professional development of young university teachers.
Activity Recognition System for Smart Campus

Long video data resulted from the use of cameras indoor and outdoor areas as a action recording. We present a new framework for recognizing student activities from the class. In this system we improve intelligent mechanism, top low level motion detection algorithm and feature extraction. We recognize the frame difference and feature selection for human activities that permits recognition. The detection of human activity from videos is very complicated appropriate to the complex reality of events, the situation in which activities took place, the require of available size of abnormal ground truth training data and other factors correlated to environmental disparity, light conditions and the working position of the captured cameras. The objective of this paper is to research and inspect machine and deep learning techniques by using videos for recognition of students indoor and outdoor activities. The importance has been on a variety of activity detection systems with machine learning techniques as their prime move toward.
ФОРМУВАННЯ МЕТОДІВ УПРАВЛІННЯ ПРОЄКТАМИ ТА ПРОГРАМАМИ БЕЗПЕКИ ОБ’ЄКТІВ КРИТИЧНОЇ ІНФРАСТРУКТУРИ

The critical infrastructure includes objects in different sectors of the economy. These objects are strategic for the state, and as a consequence, vulnerable, therefore, need special protection. In the article criteria of identification of objects of critical infrastructure and their detailing are offered. The article deals with the detailed method of identifying objects of critical infrastructure. A method has been developed for the formation of regional security programs for critical infrastructure objects and a detailed description of the management processes of this type of program, based on the formation of strategic tasks and their decomposition in the area of risk management and threats for critical infrastructure objects. These programs will be aimed at preventing risk situations and threats that may accompany the entire lifecycle of critical infrastructure objects, since the best protection is the prevention of emergencies for critical infrastructure objects, both natural and man-made.
Deep Constrained Q-learning

In many real world applications, reinforcement learning agents have to optimize multiple objectives while following certain rules or satisfying a list of constraints. Classical methods based on reward shaping, i.e. a weighted combination of different objectives in the reward signal, or Lagrangian methods, including constraints in the loss function, have no guarantees that the agent satisfies the constraints at all points in time and can lead to undesired behavior. When a discrete policy is extracted from an action-value function, safe actions can be ensured by restricting the action space at maximization, but can lead to sub-optimal solutions among feasible alternatives. In this work, we propose Constrained Q-learning, a novel off-policy reinforcement learning framework restricting the action space directly in the Q-update to learn the optimal Q-function for the induced constrained MDP and the corresponding safe policy. In addition to single-step constraints referring only to the next action, we introduce a formulation for approximate multi-step constraints under the current target policy based on truncated value-functions. We analyze the advantages of Constrained Q-learning in the tabular case and compare Constrained DQN to reward shaping and Lagrangian methods in the application of high-level decision making in autonomous driving, considering constraints for safety, keeping right and comfort. We train our agent in the open-source simulator SUMO and on the real HighD data set.
Via della Grammatica for English Speakers

Via della Grammatica for English Speakers Author: Mina Ricci Edilingua Italian grammar for English speakers. (Level A1 - B2) Free Pick up at School *Due to major USPS delays, Speakitaly NYC is not responsible for any lost or damaged packages once they are shipped and the tracking number is provided.
SPEED CONTROL OF DC MOTOR USING ACO BASED FOPID CONTROLLER

Direct current (DC) motors are widely used because of their easily controllable and reliable access.DC motors have many salient features that includes a wide range of torque speed control, reliable operation with greater efficiency and a greater starting torque and many more.A nonlinear model for a DC motor can be represented for considering all uncertainties and nonlinearities.In this paper, DC motor is studied which is having a second order system.Many controllers are being used for controlling speed of DC motor.An analysis is carried out on mathematical model of DC motor whose field is excited by an external or separate supply.Tuning of FOPID parameters using Ant Colony Optimization Technique (ACO) is discussed here.
Fairness across Network Positions in Cyberbullying Detection Algorithms

Cyberbullying, which often has a deeply negative impact on the victim, has grown as a serious issue in Online Social Networks. Recently, researchers have created automated machine learning algorithms to detect Cyberbullying using social and textual features. However, the very algorithms that are intended to fight off one threat (cyberbullying) may inadvertently be falling prey to another important threat (bias of the automatic detection algorithms). This is exacerbated by the fact that while the current literature on algorithmic fairness has multiple empirical results, metrics, and algorithms for countering bias across immediately observable demographic characteristics (e.g. age, race, gender), there have been no efforts at empirically quantifying the variation in algorithmic performance based on the network role or position of individuals. We audit an existing cyberbullying algorithm using Twitter data for disparity in detection performance based on the network centrality of the potential victim and then demonstrate how this disparity can be countered using an Equalized Odds post-processing technique. The results pave way for more accurate and fair cyberbullying detection algorithms.
A general framework for decentralized optimization with first-order methods

Decentralized optimization to minimize a finite sum of functions over a network of nodes has been a significant focus within control and signal processing research due to its natural relevance to optimal control and signal estimation problems. More recently, the emergence of sophisticated computing and large-scale data science needs have led to a resurgence of activity in this area. In this article, we discuss decentralized first-order gradient methods, which have found tremendous success in control, signal processing, and machine learning problems, where such methods, due to their simplicity, serve as the first method of choice for many complex inference and training tasks. In particular, we provide a general framework of decentralized first-order methods that is applicable to undirected and directed communication networks alike, and show that much of the existing work on optimization and consensus can be related explicitly to this framework. We further extend the discussion to decentralized stochastic first-order methods that rely on stochastic gradients at each node and describe how local variance reduction schemes, previously shown to have promise in the centralized settings, are able to improve the performance of decentralized methods when combined with what is known as gradient tracking. We motivate and demonstrate the effectiveness of the corresponding methods in the context of machine learning and signal processing problems that arise in decentralized environments.
Classification of Indonesian Presidential Campaign on Twitter Using Word2Vec

Indonesia is a country that use democracy system and one of the largest in the world.The process of democracy continues every 5 years and always raises the pros and cons in the community especially on social media.This research explains the process of presidential election in Indonesia using Word2Vec as an extraction feature.Some classifications used are K-Nearest Neighbors (K-NN), Naïve Bayes, Decision Tree, Random Forest, and Support Vector Machine (SVM) to decide sentiment.The purpose of this research is to compare several classifications as well as to know the highest accuracy of some classification use.Post data about presidential candidates through the crawling process on social media Twitter.Data originating directly from the community and national media produce variations of various responses.The data processed is as much as 640 in Bahasa Indonesia with the keywords Prabowo, Sandi, Jokowi, and Ma'ruf.The results showed the highest accuracy gained when using the Random Forest Classification method, with the highest accuracy reaching 98.33% and lowest accuracy reaching 81.96% using Support Vector Machine.
Special Issue on Smart Data and Semantics in a Sensor World

Since its first inception in 2001, the application of the Semantic Web [...]
The concept and the essence of academic mobility of students

The article discusses the theoretical foundations of academic mobility of students. The concept of determining the academic mobility of students is clarified. The author characterizes the types of academic mobility of students, reveals the features of their organization in universities. The subjects of academic mobility of students and certain requirements for them are identified. The analysis of the tasks of organizing academic mobility of students facing Russian universities, as well as different types of activities for teaching students under the program of academic mobility, are presented. In legal acts and statutes of universities (MSU. Academic mobility is considered as the movement of someone related to education for a certain (usually up to a year) period to another educational institution (in their home country or abroad) for training, teaching or research, after which the student, teacher or researcher returns to their primary educational institution. This concept is not associated with emigration or a long period of study (work) abroad. &nbsp
Quantitative automated mineralogy to constrain metamorphic processes using ZEISS Mineralogic

&amp;lt;p&amp;gt;The Scanning Electron Microscope (SEM) is the most prolific piece of analytical equipment in the Earth Sciences, therefore quantitative mineral chemistry obtained directly from the SEM has the potential to streamline many geological fields. Mineral chemistry provides direct constraints on geological processes that are used in a wide variety of Earth Science disciplines. As a result, major element analysis of rock forming minerals have been one of the major contributors to geochemistry for decades. Electron beam techniques have been the most widely used method of obtaining in situ major element chemistry, dominated by the quantitative Wavelength Dispersive Spectroscopy (WDS) employed by the Electron Probe Micro Analyser (EMPA). More rapid, and typically more qualitative Energy Dispersive Spectroscopy (EDS) major element measurements are often obtained on a standard SEM instrument.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The relative simplicity of the EDS technique saw the growth of automated mineralogy systems beginning in the 1980&amp;amp;#8217;s. The peaks of EDS spectra are characteristic of the major elements present, and therefore lookup tables can be used to match the spectra to known mineral compositions and provide a likely mineralogy in both grain mounts and mapped thin sections. The automated mineral analysis technique remained essentially unchanged for decades, with an experienced operator required for many of the analytical tasks, such as creating the files for matching spectra to known minerals, processing the data, and interpreting complex phases and solid solutions (e.g. Fe/Mg-bearing silicates).&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;The ZEISS Mineralogic automated quantitative mineralogy (AQM) takes a new approach, using EDS detectors, but following an analytical protocol more closely aligned with EPMA. A combination of matrix corrections, peak deconvolution, and standard calibration means that peak intensities are converted directly into wt% element directly at the time of analysis. The result is a data output that can be immediately interpreted, even for minerals not previously analysed, by both new and experienced users.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Here we demonstrate the use of the ZEISS Mineralogic system for mapping thin sections from high grade metamorphic rocks. The bulk chemistry of the entire thin section, as well as individual mineral compositions can be used to constrain P-T conditions directly from the SEM, without the need for an additional step of obtaining mineral chemistry from an EPMA. With quantitative analysis at every pixel, major element profiles can be obtained at any point in the thin section, and P-T can therefore be determined from any domain within the mapped section. This approach makes the use of P-T pseudosections possible with greater speed and flexibility than has previously been possible.&amp;lt;/p&amp;gt;
SATSEARCHTORY: Searching Online Platform for Niche Product in a Metropolitan Area

Satsearchtory helps users perform an uncomplicated search for products that are rare items. It also can be used for nonrare or regular items by showing locations for purchasing the item and comparisons of prices and promotions that are available for ensuring the best deal. The tool, thereby, can guarantee users’ satisfaction through online service using search engines for accurate results. Because search engines using keywords and phrases have not been able previously to achieve a 100% result for users, Satsearchtory was designed to increase the percentage of users’ satisfaction.
A personalized approach in education: problems and prospects

In the modern education system, one of the strategic priorities is the theoretical and methodological understanding and practical implementation of personality-oriented learning. The paper considers the problem of implementing a personified approach in the process of education and training. The author's vision of a personality-oriented approach is stated. Some theses of psychology and pedagogy are studied to build the concept of an individual approach in education and training. The author tried to develop a mechanism for the implementation of a personality-oriented approach in teaching a foreign language in a higher educational institution. The study made it possible to argue that in the psychological and pedagogical science there is currently a wide range of conceptual approaches to solving this problem. However, common feature is the emergence as a subject of the learner personality, creating the necessary conditions for his full learning and development. The initial assumption was confirmed by the study that the implementation of personality-oriented learning will be possible if this process is designed as a joint learning and cognitive activity of the learner and learner, aimed at the harmonious and comprehensive development of the learner.
The Effect of Using Inter-Frame Coding with Jpeg to Improve the Compression of Satellite Images

Many recent satellite image compression methods depends on removing the spectral and spatial redundancies within image only , such these methods known as intra-frame(image) coding such as predictive and transformed based techniques , but these contributions needs a hard work in order to improve the compression performance also most of them are applied on individual data. The other trend is to exploit the temporal redundancy between the successive satellite images captured for the same area from different views, different sensors, or at different times, which will be much correlated and removing this redundancy will improve the compression performance and this principle known as inter-frame(image) coding .In this paper, a latest powerful method for compressing sequences of satellite images using inter-frame coding concept with compression method (JPEG) has been presented to satisfy higher compression performance while keeping images quality as well as preservation of significant image details. The experimented results show that the proposed method outperformed many of lossy methods including JPEG.
EL BILINGÜISMO OFICIAL Y LA EXTINCIÓN DE LAS LENGUAS INDÍGENAS: EL CASO DE CAMERÚN

Camerun es un pais africano cuya compleja situacion linguistica y cultural siempre ha atraido mucho interes por parte de los investigadores. Desde la independencia del pais, los sucesivos gobiernos han intentado fomentar la convivencia pacifica entre las diferentes lenguas y culturas. Sin embargo, este noble proposito dio lugar a la promocion exclusiva de las dos lenguas coloniales como lo demuestra el sistema educativo actual del pais. Pese a haber tenido algunos efectos positivos como la apertura del pais al mundo, el monopolio del ingles y el frances en la educacion de Camerun dio lugar al aislamiento y a la extincion gradual de los idiomas que se hablaban antes de la llegada de las potencias colonizadoras. Asi pues, este articulo examina las razones que subyacen a la situacion privilegiada que ostentan las lenguas europeas en la educacion en Camerun. Tambien se hace un llamamiento para la conservacion de los idiomas indigenas de Camerun en un contexto en el que la mayoria de ellos estan a punto de desaparecer. Las afirmaciones que se hacen en este articulo estan respaldadas por la revision de diversos trabajos de investigacion previos sobre la situacion linguistica de Camerun, una descripcion del sistema educativo actual en Camerun y la observacion de los cambios linguisticos y culturales recientes en el pais. Esto se complementara con la experiencia propia del autor y asi como su continuo contacto con maestros y otros miembros de la comunidad educativa del pais. Cameroon is an African country whose complex linguistic and cultural situation has attracted a lot of interest in academia. From the early days of independence, decision-makers in Cameroon have attempted to find ways to promote a peaceful coexistence between the various languages and cultures within the country. Nevertheless, they have mostly encouraged the use of two colonial languages as evidenced by the country’s dual system of education. Though the dominance of English and French in Cameroon’s education has had positive effects such as opening the country to the world, it has also contributed to the marginalisation and gradual extinction of vernacular languages, which were spoken before the arrival of colonial masters. This paper therefore sets out to examine the reasons behind the overwhelming presence of European languages in Cameroon’s education. It is also a call for the preservation of Cameroon’s indigenous languages in a context where most of them are losing domains of use. Claims made in this paper are backed by a review of research works on Cameroon’s language situation, a description of Cameroon’s  education system, and an observation of the country’s linguistic and cultural dynamics. The foregoing shall be complemented by the author’s first-hand experience and continuous contact with teachers and other educational stakeholders.