Reviewerly/exHarmony huggingface dataset:
Reinforcement learning-based method for autonomous navigation of mobile robots in unknown environments: an experimental demonstration

Reinforcement learning (RL) is a subset of machine learning that deals with learning decisions from rewards given by the environment. The model classic reinforcement learning algorithms are usually applied to small sets of states and an action. However, in real applications, the state spaces are of a large-scale, and this causes the problems in the generalisation and dimensionality. In this research, the authors integrate neural network with reinforcement learning method to generalise the value of all the states. The simulation results on the Gazebo and experiment results software framework show the feasibility of the model proposed method algorithm. The robot can safely navigate in an unprotected work environment and becomes a truly intelligent system with the ability to learn and adapt itself to the model.
Physical security design of a digital forensic lab

The physical security design of a digital forensic lab is one of the key components to ensure investigators are providing a secure environment to process and store evidence that has been entrusted to them. The existing guidelines that cover this topic generally provide the minimum requirements for securing a digital forensic lab. Following the existing guidelines as written will leave investigators with a lab operation that is inefficient and lacking in adequate layers of protection. In this paper, we demonstrate a system design that goes beyond the existing guidelines and provides the adequate layers of protection, integration and increased efficiency. The importance as well as the benefits of integrating the security system into one system is also discussed. Finally, recommendations for the design of physical security systems in digital forensic labs are provided so that one can use these recommendations to create a more efficient and more secure lab design.
GENERATIVE ADVERSARIAL NETWORKS: A SHORT REVIEW

Generative adversarial networks (GANs) have been significantly investigated in the past few years due to its outstanding data generation capacity. The extensive use of the GANs techniques is dominant in the field of computer vision, for example, plausible image generation, image to image translation, facial attribute manipulation, improving image resolution, and image to text translation. In spite of the significant success achieved in these domains, applying GANs to various other problems still presents important challenges. Several reviews and surveys for GANs are available in the literature. However, none of them present short but focused review about the most significant aspects of GANs. In this paper, we address these aspects. We analyze the basic theory of GANs and the differences among various generative models. Then, we discuss the recent spectrum of applications covered by the GANs. We also provide an insight into the challenges and future directions.
The Impact of Paradoxical Leadership on Proactive Service Performance Mediated through Trust in Leader : Focused on the Hotel Industry

The context to enhance proactive service performance needs to be investigated in the hotel industry because extra service efforts are needed to fulfill customer needs. This study aims to investigate the contextual impact of paradoxical leadership(PL) on proactive service performance(PS) mediated through trust in leader(TL). Paradoxical leadership includes five kinds of integration including uniformity and individualization(UI), self-centeredness and other-centeredness(SO), decision control and autonomy(CA), work requirements and flexibility(RF), and distance and closeness(DC). Focused on the hotel industry, the relationships among PL, TL, and PS have been hypothesized based on the existing literature. This study surveys the front-of-house employees of five star hotels using convenience sampling. The number of 272 cases was used for actual analysis and the results were explained using structural equation modeling. The results firstly indicate that CA made a significantly positive influence on TL whereas the impacts of UI, SO, RF, and DC were rejected Secondly UI, CA, and RF positively influenced PS whereas the impacts of SO and DC were rejected. Thirdly TL makes a significant impact on PS. Finally TL mediates for the relationship between CA and PS. This study indicates the context to enhance PS and discusses how to develop paradoxical leadership.
Characterization and Automatic Updates of Deprecated Machine-Learning API Usages

The International Conference on Software Maintenance and Evolution is the premier international forum for researchers and practitioners from academia, industry, and government to present, discuss, and debate the most recent ideas, experiences, and challenges in software maintenance and evolution.
Utilization and Application of Weighted Keyword in Retrieval

Keyword improvements must be addressed to address the core issue of ‘Keyword-Based Search System’ i.e. “High Recall and Low Precision”, which will in turn lead to systematic modification of KWIC indexing system. And this improvement can only be done by imposing a weight that is possible through the ‘Grammatical-Hierarchical Logic’ method. So, in this paper it is trying to establish a modified KWIC named ‘Key-Word Weighted-In-Intra Contextual-Content’ on the one hand, and on the other hand trying to draft a mechanism of an advanced ‘Search Engine’ outline with the modified indexing method named ‘KWWIICC’, by which most relevant and precise document will be provided as per the users requirement.
The Development of Waste Sorting Robot to Improve Environmental Care Attitudes at MTsN 1 Banda Aceh

One of the waste management efforts is to sort waste. Waste handling in Indonesia, especially in Aceh, is still conventional. Based on these facts, a new breakthrough is needed during the era of the industrial revolution 4.0 by making a waste sorting robot. The purpose of this study was to determine the process of developing a waste sorting robot and to determine the environmental care attitude at MTsN 1 Banda Aceh by developing a waste sorting robot. This research method is Research and Development (R&amp;D). The researcher referred to Sugiyono's development model through 10 sequential steps (procedural), namely: Potential and problems; 2) data collection; 3) Product design; 4) Design validation; 5) Revised design; 6) Product trials; 7) Product revision; 8) Trial use; 9) Product revision; 10) Mass production. Research and development carried out by researchers only from steps 1-9. In the tenth step (10) of mass production, researchers did not do it because of time and cost constraints. The research location was conducted at MTsN 1 Banda Aceh. The research was carried out from October to November 2020. The research instruments were interview guides, a waste sorting robot product feasibility assessment questionnaire, and an environmental care attitude questionnaire. The data analysis technique used descriptive statistics with percentages. The results of the validation of the feasibility design of the waste sorting robot by 2 machine design experts and 1 science teacher at MTsN 1 Banda Aceh, an environmental material expert, obtained a score of 17 with a value of 100% in the less feasible category. Furthermore, in the trial, the score was 29 with a value of 100% in the very feasible category. The conclusion of this study is that the waste sorting robot is very feasible to use. The development of a waste sorting robot can improve environmental awareness at MTsN 1 Banda Aceh.
Cataloging Internet Resources: The Convergence of Libraries and Internet Resources

This paper reviews issues related to the cataloging of Internet resources and considers short- and long-term directions for cataloging and the general provision of library services for remotely accessible, electronic information resources. The strengths and weakness of using a library catalog model to improve access to Internet resources are discussed and compared with a review of related efforts. Based on experience gained through two OCLC Internet cataloging projects, the authors recommend continued and vigorous application of library cataloging standards and methods for Internet resources with the expectation that catalogs, cataloging, and libraries in general will continue to evolve. [Article copies available from The Haworth Document Delivery Service: 1-800-342-9678. E-mail address: getinfo@haworth.con]
Supplemental Material: Gold mobilization during metamorphic devolatilization of Archean and Paleoproterozoic metavolcanic rocks

Additional information on whole rock geochemistry.&lt;br&gt;
Online Polling Scheme

Online polling system is the web based project to build for voting online among between the people and the citizen.The word “Vote” means to choose form the list, to elect, or to determine. It promotes the casting online voting from any location over the world. Online polling system analysis the real-time implementation or virtual.it helps to reduce thewaste of time, no paper work, no count of votes by hand and no hand-work. It prevents from the chance of falsevoting. It’s very simple, safe, secure and take less-time to conduct votes. The main objective of online polling system to allow the people to cast their votes by online over the world .Prevent voters from voting more than once for the single people or person.Easily handled the larger voters andusers.We are developing an on-line voting system by taking advantage of the database with to store a web interface. We have to create the table for store the data into the database . For identification we use the ‘keys’, which is called the “primary keys “or may be for “forieng key”, which should be should be unique or not null.Here,we requiredhardware as well as software component.For developing this polling first we create or the moduls then after we integrate all the module together to build and enhance the project.
ACTSMLT: Automatic Classification of Text Summarization using Machine Learning Technique

In today’s world, due to the steep rise in internet users, Community Question Answering (CQA) has attracted many research communities. In order to provide the correct and perfect answer to the user asked question from a given large collection of text data, understanding the question properly to suggest a precise answer is a challenging task. Therefore, Question Answering (QA) system is a challenging task than a common information retrieval task done by many search engines. In this paper, an automatic prediction of the quality of CQA answers is proposed. This is accomplished by using five well known machine learning algorithms. Usually, questions asked by the user are based on a topic or theme. We try to exploit this feature in our work by identifying the category of the question posted and further map with the corresponding question. Similarly, for the answers posted by the multiple user’s are processed as answer for category mapping. Here, the results show that for Question Classification (QA), Linear Support Vector Classification (LSVC) is found to be the best classifier and Multinomial Logistic Regression (MLR) is the most suitable for Answer Classification (AC). The MS Macro dataset is used as the underlying dataset for retrieving and testing the question and answer classifiers. The Yahoo Answers are used as a golden reference during the testing throughout our experiments. Experiments results show that the proposed technique is efficient and outperforms Metzler and Kanungo’s (MK++) [1] while providing the best answer summary satisfying the user’s queries.
Opportunities and challenges in Teaching Structural Geology and Tectonics

&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;In most university geosciences curricula, structural geology and tectonics (SGT) form a core part of teaching. While only a small percentage of Earth science graduates will become structural geologists, many will someday use structural concepts and techniques to solve problems in fields such as nuclear waste storage, the geology of growing urban environments,&amp;amp;#160; geohazards, unconventional reservoirs, geothermal energy, CO2 sequestration, energy storage and more. A basic understanding of structural geology is thus part of a critical knowledge foundation in Earth sciences and many related disciplines. In addition, new tools and data are becoming available at a rapid pace, and enable more integrated, multi-dimensional assessments of the geosphere and our societal interfaces with it. All of this provides new opportunities and challenges for STG courses. &amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;In April 2019, a pre-EGU two-day workshop (TeachSGT21) was organized during which strengths and weaknesses of, and threats to current SGT curricula were analyzed. Participants of the workshop covered 11 European and 2 overseas countries, and came from academia as well as industry. On the basis of the workshop, we now outline educational demands from industry and research and discuss the role and significance of field training. Further, we review initiatives that use innovative tools and techniques in teaching. While not claiming to represent all aspects of modern SGT teaching, we expect that our observations can stimulate reflection on degrees and approach and may help making choices in curriculum renewal.&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;
Preface

Computer simulations are well established third pillar of the modem natural sciences. It complements the experiment and theory, and to the emerging the fourth pillar, the extraction of the new knowledge from the big data sets. The conference Computer simulations in Physics and beyond (CSP2020) are multidisciplinary meetings focusing on computational physics and related subjects. Indeed, computational physics methods prove useful in a broad spectrum of research in multiple natural sciences branches, and this volume provides a sample. The applications of machine learning in the natural sciences were presented at CSP2020 as well. This volume collects the refereed papers based on plenary, invited, and oral talks and the posters presented at the Fourth International Conference on Computer Simulations in Physics and beyond (CSP2020), which took place October 12-16, 2020 in Moscow. The CSP2020 conference continues the tradition started by an inaugural conference in 2015. It was jointly organized by the National Research University Higher School of Economics, the Landau Institute for Theoretical Physics, and Science Center in Chernogolovka. This year is unusual for the CSP conference due to the pandemic. We understood the difficulty for some participants to come to Moscow, taking into account the lockdowns around the world. Consequently, we change the usual format of the Conference: both plenary talks and parallel sessions will be afternoon due to the equilibration of the time zone differences around the globe. Parallel sessions include the contributed talks (20 min) and the poster talks (short online talks up to 10 min). We decided to add an epilogue to discuss the experience of shifting the conference online during a pandemic. The discussion particularly emphasizes the advantages and disadvantages of that move. We wrote the epilogue with the hope that our modest experience can be useful to other conference organizers. We hope that this volume will interest readers, and we are already looking forward to the next conference in the series. Moscow, Russia December, 2020 CSP2020 Conference Chair and Volume Editor Lev Shchur http://csp2020.ac.ru/
Human Tracking Mechanism for Institutions using RFID and Facial Recognition

The Adoption of digital content by the institutional members &amp; students have seen rapid growth in recent years. The students could access the content across various devices, platform &amp; applications, which has a direct implication on the physical presence of the student. The institutions follow old &amp; very traditional base approach like a manual record of attendance to track the company of students which consumes a lot of time &amp; efforts from the staff members. The study looks at the various technologies available in the market &amp; present the implementation of the best possible solution. The latest use of technology of Facial Recognition with a combination of RFID will enhance the tracking process &amp; also provide valuable insight into student behaviour. The data collected by the system can further utilize to improve the efficiency &amp; effectiveness of student behaviour patterns &amp; predict the learning trend, which will help the institutions to make the correct decisions.
Cloud State Surveillance

Concerns about government snooping in the wake of revelations by whistle blower Edward Snowden have deterred enterprises and IT professionals from keeping sensitive data in the clouds. Moving towards cloud-based computing has emerged and has gained acceptance as a solution to the tasks related to the processing of information. However, cloud computing carries serious risks to business information. The questions around risk and compliance are still largely unknown and need to be ironed out. Cloud computing opens numerous legal, privacy, and security implications, such as copyright, data loss, destruction of data, identity theft, third-party contractual limitations, e-discovery, risk/insurance allocation, and jurisdictional issues. This chapter discusses the associated legal risks inherent in cloud computing, in particular the international data transfer between EU and non-EU states.
Spinor Bose–Einstein Condensates

This chapter discusses spinor Bose--Einstein condensates and the various common states that are encountered with such systems. Many analogous concepts to optical systems are discussed, such as spin coherent states, spin squeezed states, uncertainty relations, and quasiprobability distributions such as the Q- and Wigner functions. A gallery of different spin states is shown for both the Q- and Wigner functions is shown, including that for highly non-classical states such as the Schrodinger cat state. Due to the different operators involved for spin systems, we describe the similarities and differences to optical squeezing, and introduce the one-axis and two-axis countertwisting spin squeezed states. The notion of entanglement in such systems, along with and ways of detecting this is are discussed. Several mappings, such as the Holstein--Primakoff transformation between spins and bosonic operators, as well asand the equivalence between condensed and uncondensed systems, is are discussed. We also introduce some key mathematical results involving important states, such as formulas to perform basis transformations between Fock states.
The fretted zither and the influence of a supporting table on its initial transients—An impulse pattern formulation model

Fretted zithers originate in the Alpine region and their adjacent countries. They consist of 5 fretted and 24-37 free vibrating strings stretched across a thin body. The instrument is usually played on a specific table, which is designed to amplify the sound. Thus, the table is crucial for the produced sound and must therefore be considered in respective acoustical analyses. This work explores the influence of various tables and other supporting material on the length and character of initial transients of a played zither tone. Measurements are performed while playing with differently designed tables, with a solid tabletop or with a hollow sound chamber, but while playing without a table, with the instrument placed on one’s knees. As every part of the instrument is coupled to the table, the transients not only depend on the impedance of the support material but also on the plucked string itself. Thus, all components are modeled together. The method of choice is the Impulse Pattern Formulation (IPF) which assumes the zither to work with impulses traveling through the instrument body. During the transition from zither to the table, they get partly reflected, damped, and act back on the string, effectively co-defining the transient behavior.
IAG Membership Information

Geostandards and Geoanalytical ResearchVolume 45, Issue 1 p. 257-257 IAG Membership Information Free Access IAG Membership Information First published: 09 March 2021 https://doi.org/10.1111/ggr.12333 AboutPDF 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 onEmailFacebookTwitterLinked InRedditWechat No abstract is available for this article. Volume45, Issue1March 2021Pages 257-257 RelatedInformation
Grasp Manipulability

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Facial Gender Analysis using Gabor-DWT Feature Extraction Method

Facial Gender Analysis has application of specific gender entry detection, human machine interface for digital marketing, real time targeted advertisement and gender demo-graphic analysis. The facial gender can be predicted by classifi-cation of the texture and unique edges pattern. Gabor filter can extract the edge- texture patterns on the face but has problem of high dimensionality with redundancy. For accuracy enhance-ment, the dimension and redundancy is needed to reduce by proposed technique as maxDWT feature optimization method. The proposed model is evaluated on real life challenging dataset of face as illumination variation, POSE, face profile, age variation and obstruction on face as hat, birthmark, moles, speckles, beard, etc. Results shows that proposed technique far better than existing state of art methods of gender prediction.
Distributed Information Accountability for Intra Sharing Data in Enterprise Resource System

Consuming on-demand highly scalable services is a basic component of distributed computing that frees enterprise resource planning from superfluous programming or equipment conditions. While appreciating the accommodation brought by ERP innovation concept, user’s loss their belonging information because of less authentication appeared ERP servers. Remote stockpiling of clients information in Enterprise resource opens up new difficulties, for example, absence of authority over information and security. To address this issue, already a novel methodology, in particular Enterprise Business Information Accountability (EBIA) system, in view of the idea of data responsibility to monitor the genuine use of the clients' information in the Enterprise resource was proposed. Mainly this objective method applicable to provide privacy for different users with preferable operations in distributed sharing of data. Experimental results of implemented approach gives better privacy with respect to different tamperproof test users in distributed environment.
Jazz Vocal

Vocal techniques in classical and jazz have much in common; however, even experienced vocalists need to learn the aspects of jazz singing that make it unique. This chapter aims to dispel the myth that jazz singing is completely different from classical singing while pointing out the subtle differences between them. Similarly, aspiring jazz singers need to study all the things that instrumental jazz musicians do and then incorporate words. Topics covered in this chapter include (a) teaching the differences in timbre and vibrato that create the unique jazz vocal sound; (b) centering jazz vocal intonation; (c) avoiding some of the most common pitfalls of jazz diction; and (d) a progressive discussion of types of vocal improvisation, from strategic variation in rhythms and melodies to scat singing. The chapter concludes with a list of important classic jazz standards that have lyrics, including suggestions for teaching those standards according to age and experience.