Reviewerly/exHarmony huggingface dataset:
A Design Method for Kicks of the Desired Distance by Combinations of Based Kicks in RSS3D

RoboCup Soccer Simulation 3D (RSS3D) is a project of RoboCup, which is a series of academic projects and international robot competitions for soccer robots, disaster-relief robots, and service robots. In RSS3D, autonomous robots, which are referred to as agents in this paper, play a game of soccer by themselves in a three-dimensional virtual space that is managed by a three-dimensional physics calculation engine. The agents in RSS3D have many joints. Researchers must implement all basic actions, such as dashing and kicking, by controlling these joints. Furthermore, during the game, the agents only use kicks developed in advance; i.e., agents cannot create new kicks during the game. Researchers need to develop many kinds of actions for kicking a ball different distances because some developed actions only kick the ball one distance. Researchers therefore need to reason from several development results of joints transition on kicks to reduce the time taken to develop kicking actions. The present paper discusses such a development method by finding and analyzing hidden rules relating to multiple developed kicks. Kicking actions are revealed to be based on several rules.
ESTIMATION OF THE REAL EVAPOTRANSPIRATION WITH REFINEMENT OF THE LANDSAT THERMAL IMAGE BAND - DOI: 10.7127/rbai.v13n301040

Irrigated agricultural activity is responsible for large food production, however it is pointed out as the major consumer of water. To compute the real evapotranspiration by means of remote sensing, short-wave images with spatial resolution of 30m x 30m pixel (Landsat) are used. While the images with long wave bands (thermal) have a resolution between 60m x 60m and 120m x 120m, which compromise the result. This work proposes the improvement of the spatial resolution of the actual evapotranspiration obtained by energy balance, using the METRIC model, by improving the spatial resolution of the thermal band used. The refinement of the thermal band allows a better visualization and spatialization of evapotranspiration values. Therefore, the refinement of the thermal band is an extremely important tool for the estimation of the real evapotranspiration values in agricultural areas, considerably improving the spatial resolution of the images (up to 16 times), corroborating with activities related to the environmental scope, water resources management and agriculture.
15.5 aana land on sale at ,Siddheshwar Marg, Gokarneshwor-5, Kathmandu

Land For sale In Siddheshwar Marg, Ward No. 5, Gokarneshwor Municipality, Kathmandu, Pradesh 3 Nepal
Giant virtual universe

A simulation of the universe, 1 billion light years across, is looking at how galaxies form and die.
No-Reference Stereoscopic Video Quality Assessment Based on Spatial-Temporal Statistics

Stereoscopic video quality assessment (SVQA) has become the necessary support for 3D video processing while the research on efficient SVQA method faces enormous challenge. In this paper, we propose a novel blind SVQA method based on monocular and binocular spatial-temporal statistics. We first extract the frames and the frame difference maps from adjacent frames of both left and right view videos as the spatial and spatial-temporal representation of the video content, and then use the local binary pattern (LBP) operator to calculate spatial and temporal domains’ statistical features. Besides, we simulate binocular fusion perception by performing weighted integration of generated monocular statistics to obtain binocular scene statistics and motion statistics. Finally, all the computed features are utilized to train the stereoscopic video quality prediction model by a support vector regression (SVR). The experimental results show that our proposed method achieves better performance than state-of-the-art SVQA approaches on three public databases.
Key Factors of Usability of Science and Technology Faculties’ Website: Marketing Purpose

A website of a science and technology faculty is a platform offering decisive information acquired by high-school students for further education. The representative of this website is also important in terms of marketing purpose and has to be designed according to usability rules properly. As a platform, it can be used to implement marketing strategies of the organization in terms of new student recruitment. This work aimed to extract the key factors high-school students require for study-related information acquiring. The key factors can be then used as the recommendations for science and technology faculties’ website design. The websites are also stated based on high-school students’ needs and usability requirements in terms of marketing purpose.
Data Shuffling Minimizing Approach for Apache Spark Programs

This article discusses a way to optimize the Apache Spark program by reducing the number of transformations with wide dependencies and, as a result, the number of data shuffles. This is achieved by combining sequential data processing algorithms in chains based on common key fields, as well as grouping the data which is stored in resilient distributed structures i.e., Spark SQL Datasets, according to the keys by which the processing takes place.
DEVELOPMENT COLLABORATION INTER-LIBRARY COLLECTION IN UNIVERSITY

&lt;p&gt;This paper attempts to describe descriptively about the Collaboration Development between Inter-Library Collections in Higher Education, the benefits and obstacles that occur. The method used is a literature review method in which this method contains references related to the discussion contained in this scientific work, in order to obtain theoretical information sourced from reading material such as books, national journals or other internal sources that can support the writing of works. this scientific. The purpose of this scientific work is to know descriptively about the process of collaboration in the development of collections between college libraries, then the benefits obtained as well as the obstacles that might occur and of course will be reading material for writers and readers. The conclusion in this paper is that the diversity of information needs and the limitation of human resources make none of the information provider institutions including libraries that are able to meet all of the information needs of their users. then the abundance of data and information in the current era makes the library a center for information services to provide the widest possible access to information to the public. this requires that libraries that act as information providers for both the academic community and outside, need collaboration between libraries. The cooperation that can be carried out includes cooperation in procurement, management, storage and lending between libraries. As we are united, we are firm, our divorce collapses. This means that there are responsibilities that are shared together and there are benefits that will be shared together.&lt;/p&gt;
Education System of The Republic of Uzbekistan: Educational Program and Assigned Qualifications

This article describes the modern structure of the education system of the Republic of Uzbekistan,reformed in the last decade in accordance with the national program adopted in the Republic fortraining of personnel implemented in Uzbekistan educational programs at various levels, assigned totheir completion of qualifications and educational documents confirming these qualifications.
Deep Reinforcement Learning for Transfer of Control Policies

Abstract We present a form-aware reinforcement learning (RL) method to extend control knowledge from one design form to another, without losing the ability to control the original design. A major challenge in developing control knowledge is the creation of generalized control policies across designs of varying form. Our presented RL policy is form-aware because in addition to receiving dynamic state information about the environment, it also receives states that encode information about the form of the design that is being controlled. In this paper, we investigate the impact of this mixed state space on transfer learning. We present a transfer learning method for extending a control policy to a different design form, while continuing to expose the agent to the original design during the training of the new design. To demonstrate this concept, we present a case study of a multi-rotor aircraft simulation, wherein the designated task is to achieve a stable hover. We show that by introducing form states, an RL agent is able to learn a control policy to achieve the hovering task with both a four rotor and three rotor design at once, whereas without the form states it can only hover with the four rotor design. We also benchmark our method against a test case that removes the transfer learning component, as well as a test case that removes the continued exposure to the original design to show the value of each of these components. We find that form states, transfer learning, and parallel learning all contribute to a more robust control policy for the new design, and that parallel learning is especially important for maintaining control knowledge of the original design.
A Comparative Review for Question Answering Frameworks on the Linked Data

Background: One of the state-of-the-art techniques for question answering frameworks is using linked data by converting the user input into SPARQL which is the query language for linked data. Objective: The main target is to emphasize the most fundamental issues while developing a question answering frameworks that accept input in natural language and converting it into SPARQL. Methods: The trend of applying linked data as a data source is gaining popularity among the researchers. In this study, question answering frameworks that combine both natural language processing techniques and linked data technologies are examined. Common principles of examined question answering frameworks recognize user intention, enriching natural language input and converting it to a SPARQL query. Results: 9 studies are selected for further examination to be compared by using selection criteria defined in the research methodology. Conclusion: Resulting outcomes are represented and compared in detail. In addition to the comparative review of systems, a general architecture of question answering frameworks on the linked data is drawn as an outcome of this study to provide a guideline for the researchers who are studying related research fields.
Detection of Driver's Eye Fixation on a Moving Target by Using Line Fitting

This paper proposes a method of obtaining the sets of gaze points looking at the same object or portion in the situation, while driving a vehicle through a straight road, and that the relative speed of the vehicle and an object outside the vehicle is constant. The proposed method uses the lines fitted to the gaze points of a driver. It judges that a driver looks at the same object or portion when the sets of gaze points are on the same line. An example of the application of the proposed method to eye tracking data in simulated autonomous driving is shown in order to demonstrate the validity of the proposed method.
CAMPUS INTELLECTUAL PRODUCT BUSINESS DEVELOPMENT PROGRAM

KAN's accredited Laboratory of Service of the Faculty of Mathematics and Natural Sciences is very much needed by all lecturers and students of the University of Pakuan as one of the means to accelerate the study period of students and improve the performance and quality of research for all lecturers in Pakuan University. Faculty of Mathematics and Science Service Laboratory Universitas Pakuan has been officially established based on the University of Pakuan Rector's Decree Number: 15.1 / Kep / Rek / II / 2018 dated 20 February 2018 signed by the Chancellor of Pakuan University namely Dr. H. Bibin Rubini, M.Pd. It was founded as one of the Campus Intellectual Business Units in charge of serving chemical analysis services for all students and lecturers in the Pakuan University environment for food products, natural materials, and the environment as well as providing various skills training that must be possessed by students to obtain work and improve their competence. The target of it is to become a laboratory accredited by the National Accreditation Committee by implementing ISO 17025: 2017 in running the system so that the resulting data output can be accounted for.
Formación docente en contexto STEM: actividades experimentales abiertas mediadas por tecnología Arduino en la enseñanza de la física

espanolEste trabajo presenta los primeros resultados de una propuesta de formacion docente basada en el analisis, reformulacion, implementacion y reflexion (entre docentes y grupo de investigacion) de secuencias didacticas centradas en actividades experimentales abiertas mediadas por tecnologia Arduino atendiendo a un enfoque de educacion STEM, en un proceso de analisis de las practicas, en la formacion docente continua en Fisica. Se pretende dar respuesta a ciertos problemas vigentes de la formacion docente inicial y continua en Fisica, especialmente puestos de manifiesto en los procesos de integracion curricular de tecnologias digitales en la ensenanza. EnglishThis paper presents the first results of a proposal for teacher training based on the analysis, reformulation, im-plementation and reflection (between teachers and research group) of teaching sequences focused on open experimental activities mediated by Arduino technology attending to a STEM education approach, in a process of analysis of practices, in continuous teacher training in Physics. In this way, it is expected to respond to certain problems of initial and continuous teacher training in Physics, currently in force, especially highlighted in the processes of curricular integration of digital technologies in the teaching of Physics.
BLOCKCHAIN IN THE MIDDLE EAST: CHALLENGES AND OPPORTUNITIES

The Blockchain technology has attracted a huge attention from both industry and academia. Despite the fact that there are great potentials of the blockchain, it is facing a number of technical chal ...
Test-Driven Development (TDD)

Test-driven development is a scary topic for many new developers, but the concepts are simple. Once you get the hang of TDD, the benefits become clear. Your code will be simpler, cleaner, and easier to refactor. With TDD, we only write the code we need to write, and avoid adding unnecessary fluff. It will no longer be a scary prospect to make changes to your code. You have tests to verify that your changes won’t break existing code. If something goes wrong, you’ll know where the break occurred.
An Accomplished Energy-Aware Approach for Server Load Balancing in Cloud Computing

Background: It is important to minimize bandwidth that improves battery life, system reliability and other environmental concerns and energy optimization. It also do everything within their power to reduce the amount of data that flows through their pipes.To increase resource exertion, task consolidation is an effective technique, greatly enabled by virtualization technologies, which facilitate the concurrent execution of several tasks and, in turn, reduce energy consumption. : MaxUtil, which aims to maximize resource exertion, and Energy Conscious Task Consolidation which explicitly takes into account both active and idle energy consumption. Materials and Methods: In this paper an Energy Aware Cloud Load Balancing Technique (EACLBT) is proposed for the performance improvement in terms of energy and run time. It predicts load of host after VM allocation and if according to prediction host become overloaded than VM will be created on different host. So it minimize the number of migrations due to host overloading conditions. This proposed technique results in minimize bandwidth and energy utilization. Results: The result shows that the energy efficient method has been proposed for monitor energy exhaustion and support static and dynamic system level optimization.The EACLBT can reduce the number of power-on physical machine and average power consumption compare to other deploy algorithms with power saving.Besides minimization in bandwidth along with energy exertion, reduction in the number of executed instructions is also achieved. Conclusion: This paper comprehensively describes the EACLBT (Energy Aware Cloud Load Balancing Technique) to deploy the virtual machines for power saving purpose. The average power consumption is used as performance metrics and the result of PALB is used as baseline. The EACLBT can reduce the number of power-on physical machine and average power consumption compare to other deploy algorithms with power saving. It shown that on average an idle server consumes approximately 70% of the power consumed by the server running at the full CPU speed.The performance holds better for Common sub utterance elimination. So, we can say the proposed Energy Aware Cloud Load Balancing Technique (EACLBT) is effective in bandwidth minimization and reduction of energy exertion.
A Web Extraction Browsing Scheme for Time-Critical Specific URLs Fetching

Web browsing is the need of the hour present state of the art problem of presenting the specific result to the users. This paper works towards creating an efficient search engine that removes stop words, extract meaningful words and form clusters of highest frequency words and final stage present the result in terms of URLs. The proposed system is divided into three phases: In the first phase, pre-processing is performed by eliminating the stop words. The outcome of this phase is a reduced query. In the second phase, the extraction of meaningful words with a frequent word or similar word replacement is applied. In the last phase, meaningful URLs are fetched through location-sensitive searching and then presented within the same interface. The result is presented in term of URLs fetched and execution time it takes to fetch the results.
Dual Active Sampling on Batch-Incremental Active Learning

Recently, Convolutional Neural Networks (CNNs) have shown unprecedented success in the field of computer vision, especially on challenging image classification tasks by relying on a universal approach, i.e., training a deep model on a massive dataset of supervised examples. While unlabeled data are often an abundant resource, collecting a large set of labeled data, on the other hand, are very expensive, which often require considerable human efforts. One way to ease out this is to effectively select and label highly informative instances from a pool of unlabeled data (i.e., active learning). This paper proposed a new method of batch-mode active learning, Dual Active Sampling (DAS), which is based on a simple assumption, if two deep neural networks (DNNs) of the same structure and trained on the same dataset give significantly different output for a given sample, then that particular sample should be picked for additional training. While other state of the art methods in this field usually require intensive computational power or relying on a complicated structure, DAS is simpler to implement and, managed to get improved results on Cifar-10 with preferable computational time compared to the core-set method.
An analysis of students’ needs in the context of L2 Italian workshops in primary schools

The present paper describes an experience with an L2 Italian workshop which tried to combine the competency-based educational model, already established in school practice, with Balboni’s model of language teaching. Starting from the analysis of teachers’ and childrens’ needs, the autor develops an integrated, inclusive and formative course that involved both native speakers and non-native speakers of Italian.
Evaluating Word Similarity Measure of Embeddings Through Binary Classification

We consider the following problem: given neural language models (embeddings) each of which is trained on an unknown data set, how can we determine which model would provide a better result when used for feature representation in a downstream task such as text classification or entity recognition? In this paper, we assess the word similarity measure through analyzing its impact on word embeddings learned from various datasets and how they perform in a simple classification task. Word representations were learned and assessed under the same conditions. For training word vectors, we used the implementation of Continuous Bag of Words described in [1]. To assess the quality of the vectors, we applied the analogy questions test for word similarity described in the same paper. Further, to measure the retrieval rate of an embedding model, we introduced a new metric (Average Retrieval Error) which measures the percentage of missing words in the model. We observe that scoring a high accuracy of syntactic and semantic similarities between word pairs is not an indicator of better classification results. This observation can be justified by the fact that a domain-specific corpus contributes to the performance better than a general-purpose corpus. For reproducibility, we release our experiments scripts and results.
Indoor Testbed for Vector Field Multirobot Adaptive Navigation: Feasibility Study

Abstract Multirobot adaptive navigation maneuvers a multi-vehicle system based on characteristics of the environment to autonomously localize features of interest. This navigation method can be more time and energy efficient than conventional navigation methods. Most work in this area explores scalar fields, where a single characteristic value is associated with every point in the environment. This work is an initial testbed exploration of adaptive navigation for vector fields, where every point in the environment is associated with a multi-parameter value. A vector field can represent a single physical quantity such as water/air flow or multiple simultaneous and collocated scalar quantities such as temperature and gas concentration. The contribution of this work is the extension of an existing adaptive navigation testbed to support vector field representations, navigation, and further research. Vector fields are generated using a large-format printer to print 8-bit colored floor mats. Mobile robots, equipped with RGB sensors, sense the color and, through calibration, estimate the underlying vector field. This paper will walk through our process of generating vector fields and a calibration method to be used for adaptive navigation. Successful results from two adaptive navigation experiments are shown in the paper: finding a source with a single robot and using a two-robot formation to straddle a crest of high velocity flow in a vector field.
Scientific Literature Mining for Experiment Information in Materials Design

Scientific literature is a plethora of documents written in natural language, where the agglomeration of well-cogitated knowledge is inextricably intertwined. The large-scale knowledge source might have the great potential to derive valuable information when text mined and untangled. Typically, scientists obtain preliminary knowledge from research papers prior to beginning a new experiment. Researchers manually harvest experimental information, which is labor-intensive and error prone. To reduce manual effort and human errors, this project aims to build a system for data collection from literature that supplements other data sources so users can look up needed information while preparing experiments or analyzing results.