Reviewerly/exHarmony huggingface dataset:
Optimal Projection Pattern for Active Visual Servoing (AVS)

&lt;p&gt;Visual servo control uses images that are obtained by a camera for robotic control. This study focuses on the problem of positioning a target object using a robotic manipulator with image-based visual servo (IBVS) control. To perform the positioning task, the image-based visual servoing requires visual features that can be extracted from the appearance of the target object. Therefore, a positioning error tends to increase especially for textureless objects, such as industrial parts. Since it is difficult to extract differences of the visual features between current and goal images. To solve these problems, this paper presents a novel visual servoing named ``Active Visual Servoing." Active Visual Servoing (AVS) projects patterned light onto the target object using a projector. The design of the projection pattern affects the positioning error. AVS uses an optimal pattern which is theoretically derived and maximizes differences between current and goal images. The experimental results show that the proposed active visual servoing method reduces the positioning error by more than 97% compared to conventional image-based visual servoing.&lt;/p&gt;
Measures of Lexical Variety

In this chapter we will begin to transition from microanalysis to macroanalysis. We will leave behind the study of single terms and begin to explore two global measures of lexical variety: mean word frequency and type-token ratios.
A Novel Traffic Rate Measurement Algorithm for Quality of Experience-Aware Video Admission Control

With the inevitable dominance of video traffic on the Internet, providing perceptually good video quality is becoming a challenging task. This is partly due to the bursty nature of video traffic, changing network conditions and limitations of network transport protocols. This growth of video traffic has made Quality of Experience (QoE) of the end user the focus of the research community. In contrast, Internet service providers are concerned about maximizing revenue by accepting as many sessions as possible, as long as customers remain satisfied. However, there is still no entirely satisfactory admission algorithm for flows with variable rate. The trade-off between the number of sessions and perceived QoE can be optimized by exploiting the bursty nature of video traffic. This paper proposes a novel algorithm to determine the upper limit of the aggregate video rate that can exceed the available bandwidth without degrading the QoE of accepted video sessions. A parameter $\beta$ that defines the exceedable limit is defined. The proposed algorithm results in accepting more sessions without compromising the QoE of on-going video sessions. Thus it contributes to the optimization of the QoE-Session trade-off in support of the expected growth of video traffic on the Internet.
Multi-Step Predictions for Adaptive Sampling using Proximal ADMM

&lt;p&gt;The paper presents a novel approach by using multi- step predictions to address the adaptive sampling problem in a resources and obstacles constrained mobile robotic sensor network to efficiently monitor environmental spatial phenomena. It is first proposed to employ the Gaussian process (GP) to represent the spatial field, which can then be used to predict the field at unmeasured locations. The adaptive sampling problem aims to drive the mobile sensors to optimally navigate the environment where the sensors adaptively take measurements of the spatial phenomena at each sampling step. To this end, a conditional entropy based optimality criterion is proposed, which aims to minimize prediction uncertainty of the GP model. By predicting possible measurements the mobile sensors potentially take in a horizon of multiple sampling steps ahead and exploiting the chain rule of the conditional entropy, a multi-step predictions based adaptive sampling optimization problem is formulated. The objective of the optimization problem is to find the optimal sampling paths for the mobile sensors in multiple sampling steps ahead, which then provides their benefits in terms of better navigation, deployment and data collection with more informative sensor readings. However, the optimization problem is nonconvex, complex, constrained and mixed-integer. Therefore, it is proposed to employ the proximal alternating direction method of multipliers algorithm to efficiently solve the problem. More importantly, the solution obtained by the proposed approach is theoretically guaranteed to be converged to a stationary value. Effectiveness of the proposed algorithm was extensively validated by the real- world dataset, where the obtained results are highly promising.&lt;/p&gt;
RANCANGAN APLIKASI PENCARIAN JALUR TERPENDEK DENGAN PENDEKANAN GEOGRAPHIC INFORMATION SYSTEMS DAN DIJKSTRA'S ALGORITHM

Islamic boarding schools play a role in developing the independent character of students, however, in addition to the large role of boarding schools, there are still many obstacles, namely the difficulty of obtaining accurate information about the existence of boarding schools. Currently, to obtain information about Islamic boarding schools in Pandeglang Regency, they still use conventional methods, like coming directly to the location of the boarding school. There are even some boarding schools whose information cannot be found, so we need a solution to solve these problems by utilizing information technology and computers. Researchers offer a solution to overcome this problem by utilizing information system technology, namely Geographic Information Systems by utilizing Google Maps as a map provider and Dijkstra's Algorithm as a method to find the shortest path from one point to another on a graph. This research produces a digital map application on the web by utilizing the Google Maps API and Web Service using the Apache Web Server to retrieve data from the MySQL database.The goal to be achieved in this research is to build a Geographic Information System (GIS) for boarding schools that can be used to provide information about the map of the location of boarding schools in the Pandeglang Regency area along with other supporting information in the boarding schools.
X‐Strack—Programming Environments for Scientific Computing (DOE)

Federal Grants & ContractsVolume 45, Issue 6 p. 4-5 Grants alerts X-Strack—Programming Environments for Scientific Computing (DOE) First published: 15 February 2021 https://doi.org/10.1002/fgc.31568Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume45, Issue618 February 2021Pages 4-5 RelatedInformation
Machine learning and its algorithms: A Research

The calculations which are actualized on the machines and which are additionally used to make machines clever are called as AI calculations, likewise they can make sense of how to perform significant assignments by summing up from precedents. Therefore, AI is broadly utilized in software engineering, man-made reasoning and different fields. Be that as it may, creating fruitful AI applications requires comprehension of keen frameworks and calculations required to build it. This paper totals and condenses the kinds of AI types and calculation that are required to develop a shrewd or a specialist framework. These calculations are utilized for different purposes like information mining, picture preparing, prescient examination, and so forth to give some examples. The principle bit of leeway of utilizing AI is that, when a calculation realizes how to manage information, it can do its work consequently.
Requirements Elicitation and Access: A Research

Requirements Elicitation and Analysis is one of the most important activity in software development life cycle. Requirements Elicitation and Analysis is about gathering and analyzing the requirements as per customer needs. If this analysis is not done properly, it may cause for problems in further phases that in turn may lead to failure of the software. Hence the requirements Elicitation and Analysis has to be given at most priority in SDLC. This paper presents a survey on requirements elicitation and analysis, particularly on functional Requirements.
Introduction

This chapter contains a general description of the developed methods and tools supporting the measurement process of determining reliable values of mathematical model parameters of generating unit elements, in particular synchronous generators and excitation systems. Special measuring tests are the basis for determining the parameters. They can be carried out under normal operating conditions of generating units, in which the magnetic cores of electric machines (synchronous generators and electromachine excitation systems) are saturated and the signals in voltage regulators may reach the limits. In this chapter, there is also a short description of selected methods, known from the literature, for determining (estimating) the parameters of mathematical models of synchronous generators. In the further part of this chapter, the content of this monograph with division into chapters is presented.
PEMBANGUNAN SISTEM INVENTARISASI PERANGKAT TEKNOLOGI INFORMASI DAN KOMUNIKASI BERBASIS WEB (Studi kasus : disduk capil kabupaten Cianjur)

Information technology has developed rapidly as the development of globalization has many applications that have been built to alleviate manual work to be automatic, controlling population of inventory items is quite complicated because of the distance between sub-districts in one district, so that frequent errors in checking are not efficient because in conducting activities checking inventory items still uses the manual method of checking one by one in each sub-district so that it takes a long time to make a report.&#x0D; The system created will be used to simplify the work, including in the activity of checking goods because it is able to simplify and present information that is relatively long, the function of a self-made system is to convey information and get a quick response and facilitate checking of official goods inventory. By building applications that manage data or official inventory information, making work easier. The application is online which will make it easy to check and report inventory items.&#x0D; Keywords : Controlling System, Administration Service, Citizenship, Web Applications
Neural Machine Translation Using Sequence Modeling

Abstract: Language is a main mode of communication, and translation is a critical tool for understanding information in a foreign language. Without the help of human translators, machine translation allows users to absorb unfamiliar linguistic material. The main goal of this project is to create a practical language translation from English to Hindi. Given its relevance and potential in the English-Hindi translation, machine translation is an efficient way to turn content into a new language without employing people. Among all available translation machines, Neural Machine Translation (NMT) is one of the most efficient ways. So, in this case, we're employing Sequence to Sequence Modeling, which includes the Recurrent Neural Network (RNN), Long and Short Term Memory (LSTM), and Encoder-Decoder methods. Deep Neural Network (DNN) comprehension and principles of deep learning, i.e. machine translation, are disclosed in the field of Natural Language Processing (NLP). In machine reclining techniques, DNN plays a crucial role. Keywords: Sequence to Sequence, Encoder-Decoder, Recurrent Neural Network, Long &amp; Short term Memory, Deep Neural Network.
A non-contact interactive stereo display system for exploring human anatomy

Stereoscopic display based on Virtual Reality (VR) can facilitate doctors to observe the 3 D virtual anatomical models with the depth cues, assist them in intuitively investigating the spatial relationship between different anatomical structures without mental imagination. However, there is few input device can be used in controlling the virtual anatomical models in the sterile operating room. This paper presents a cost-effective VR application system for demonstration of 3 D virtual anatomical models with non-contact interaction and stereo display. The system is integrated with hand gesture interaction and voice interaction to achieve non-contact interaction. Hand gesture interaction is implemented based on a Leap Motion controller mounted on the Oculus Rift DK2. Voice is converted into operation using Bing Speech for English language and Aitalk for Chinese language, respectively. A local relationship database is designed to record the anatomical terminologies to speech recognition engine to query these uncommon words. The hierarchical nature of these terminologies is also recorded in a tree structure. In the experiments, ten participants were asked to perform the evaluation on the proposed system. The results show that our system is more efficient than traditional interactive manner and verify the feasibility and practicability in the sterile operating room.
PERANCANGAN SISTEM INFORMASI PERSEDIAAN BARANG DENGAN MENGGUNAKAN METODE FIRST IN FIRST OUT (FIFO) DI PT INDAH KIAT PULP AND PAPER PRODUCT

During the process of supply of goods there has not been monitoring for the supply of goods, incoming goods, outgoing goods, stock items, as well as double item data, and difficult in finding inventory data. There fore it is necessary to make a system and the right method to manage the problem of inventory of goods in Indah Kiat Pulp and Paper Product Inc. The method used to solve this problem is the FIFO (First in First Out) which is a method of determining inventory based on the assumption that the goods that are first obtained / bought (entered) are the first to be sold or issued. Thus the goods in inventory are considered to be from the last purchases, because the goods from the previous purchase are considered to have been sold or released so that later the method will be combined in a system designed in the form of DFD to monitor inventory of goods as mentioned in the problem above and the method used to develop the system is the waterfall model and the programming language used to create the website, PHP and for example as the database.
Ionic Liquids in Green Organic Synthesis and Catalysis

Sparse recovery aims to reconstruct signals that are sparse in a linear transform domain from a heavily underdetermined set of measurements. The success of sparse recovery relies critically on the knowledge of transform domains that give compressible representations of the signal of interest. Here we consider two- and three-dimensional images, and investigate various multi-dimensional transforms in terms of the compressibility of the resultant coefficients. Specifically, we compare the fractional Fourier (FRT) and linear canonical transforms (LCT), which are generalized versions of the Fourier transform (FT), as well as Hartley and simplified fractional Hartley transforms, which differ from corresponding Fourier transforms in that they produce real outputs for real inputs. We also examine a cascade approach to improve transform-domain sparsity, where the Haar wavelet transform is applied following an initial Hartley transform. To compare the various methods, images are recovered from a subset of coefficients in the respective transform domains. The number of coefficients that are retained in the subset are varied systematically to examine the level of signal sparsity in each transform domain. Recovery performance is assessed via the structural similarity index (SSIM) and mean squared error (MSE) in reference to original images. Our analyses show that FRT and LCT transform yield the most sparse representations among the tested transforms as dictated by the improved quality of the recovered images. Furthermore, the cascade approach improves transform-domain sparsity among techniques applied on small image patches.
Investigating the role of Word Embeddings in sentiment analysis

During decades, Natural language processing (NLP) expanded its range of tasks, from document classification to automatic text summarization, sentiment analysis, text mining, machine translation, automatic question answering and others. In 2018, T. Young described NLP as a theory-motivated range of computational techniques for the automatic analysis and representation of human language. Outside and before AI, human language has been studied by specialists from various disciplines: linguistics, philosophy, logic, psychology. The aim of this work is to build a neural network to perform a sentiment analysis on Italian reviews from the chatbot customer service. Sentiment analysis is a data mining process which identifies and extracts subjective information from text. It could help to understand the social sentiment of clients, respect a business product or service. It could be a simple classification task that analyses a sentence and tells whether the underlying sentiment is positive or negative. The potentiality of deep learning techniques made this simple classification task evolve, creating new, more complex sentiment analysis, e.g. Intent Analysis and Contextual Semantic Search.
Editorial Preface

The International Youth Conference on Electronics, Telecommunications and Information Technologies (YETI-2019) was held in Saint Petersburg on July 11 – 22, 2019. It was organized by Peter the Great St. Petersburg Polytechnic University. The YETI-2019 Conference gave an opportunity to young researchers and early-career scientists to participate in a series of lectures which reviewed the current trends and knowledge in the fields of electronics, nanoelectronics, telecommunications, optical and information technologies. YETI-2019 collected 50 reports by over than 150 researchers from 6 countries. Conference included two keynote invited talks given by leading scientists devoted to actual problems and major advances in physics and technology. The keynote speakers were Luis Conde from Univ. Politécnica de Madrid, Spain (presentation “Plasma propulsion for telecommunication satellites”) and Thomas Maurer from Universite de Technologie de Troyes, France (presentation “Active plasmonics: the rising of mechanoplasmonics and perspectives for integrating strain nanogauges into matter”). Presentations by various scientists gave an overview of recent achievements and future prospects in fields of development and design of nanoelectronic and telecommunication devices, signal processing, material science and nanotechnology. During the event, informal meetings provided an opportunity for potential partners to establish contacts, share new project ideas and start new collaborations. Certificates were awarded to a number of young participants for the best oral and poster presentations selected by the Program Committee. List of Editors, The invited speakers, Oral Presentations photographs, Poster Session photographs, Awarding ceremony of YETI -2019 photographs are available in this pdf.
Correction

This article refers to:Integrating an augmented reality sandbox challenge activity into a large-enrollment introductory geoscience lab for nonmajors produces no learning gains
Topological Properties of Parallel Series Language

Parallelism is a process by which a sequential string is broken down into a number of alphabets and used to speed up the acceptance of a string. To identify the parallelisable string, we have used parallel operator || and defined the language as parallel series languages. Algebraic and recognition properties of series parallel posets have been studied by Lodaya in [8]. In this paper, we have introduced finite and infinite parallel series language (parallel strings are connected sequentially). We have considered the set of all parallel series language as topological space and prefix order relation (poset relation) has been used to relate two parallel series strings. Topological concepts like limit, sequence, open set, closed set and basis for parallel series languages and their properties have been derived.
Construction of a Practical Teaching Platform Based on Moodle

Moodle platform is a popular course management system. Using the project practice of education technology course as an example, this article sets up a platform of experimental teaching using Moodle. The platform contains several parts, such as course management, self-regulated learning test, procedural evaluation and so on. This platform shows the advantages of the double main teaching model, in which the teacher is dominant, and students are the main body. It provides significant support to the practical and experimental curriculum.
The Pronunciation of the Hijaiyah Letters for Autistic Children at Extraordinary Islamic School Qothrunnada Yogyakarta

This research aims to describe the pronunciation of the hijaiyah letters for autistic children at Extraordinary Islamic School Qothrunnada, as well as explaining factors cause errors of pronunciation of the letters hijaiyah and changing meanings. Formal object in this research is the pronunciation of the hijaiyah letters. The object of the material in this study is an autistic children at Extraordinary Islamic School Qothrunnada. The methods used in the analysis of data is a method in accordance and its preliminary technique is the technique hear and technique chat. Through this study, the researchers found the hijiayah letters which undergoes changes, with the following details 1) change letter ث become س, 2) change letter ذ become ,د 3) change letter ز become ,ج 4) change letter ش become س, 5) change letter ص become س, 6) change letter ط become ت, 7) change letter ظ become ض, 8) change letter ع becomeأ , 9) change letter ق become ك, 10) change letter ﻫ become ح, 11) change letter ع become nga. Factors cause changes in the sound is 1) Central System talk, 2) sound production system 3) the influence of first language, 4) articulation (makharijul huruf).
T1 and T2 Mri Brain Images Registration and Fusion Technique

Fusion of the medical images and registering them will improve the diagnosis and treatment for brain pathology. Image registration plays a major role because multimodal images intensity levels are to be aligned based on relationship between the images. Image registration is proposed where T1 image is a target image where T2 is registering image. Optical flow with SIFT is applied to register T2 image. The registered T2 image is fused with T1 image by applying curvelet transformation and averaging method. Entropy and Mutual Information (MI) parameter is used to evaluate the system performance. The results of the system give better entropy and MI value.