Reviewerly/exHarmony huggingface dataset:
Preface

We are glad to introduce you that the 2020 International Conference on Green Chemical and Environmental Science (ICGCES 2020), supported by AEIC Academic Exchange Information Center, was successfully held on June 12, 2020. In light of worldwide travel restriction and the impact of COVID-19, ICGCES 2020 was carried out in the form of virtual conference to avoid personnel gatherings. Because most participants were still highly enthusiastic about participating in this conference, we chose to carry out ICGCES 2020 via online platform according to the original schedule instead of postponing it. ICGCES 2020 aimed to provide a flexible platform for experts and scholars in the field of Green Chemical and Environmental Science to disseminate the latest research achievements and advanced technologies, as well as to promote the cooperation between each other. We are greatly honored to have invited Prof. Jieshan Qiu, the Dean of College of Chemical Engineering at Beijing University of Chemical Technology (BUCT), to serve as our Conference Chair. Prof. Qiu is an internationally-recognized expert in chemical engineering, whose research areas cover both fundamental and applied aspects of carbon materials and science, with a focus on the methodologies for producing carbon materials from coal and coal-derived by-products such as coal tar pitch, and their applications in energy storage and conversion (solar cells, supercapacitor and batteries, etc.), catalysis and environment protection. During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and online Q&amp;A discussion. In the first part, some scholars were given about 5-10 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches. Our beloved Conference Chair, Prof. Qiu, was also invited to present his latest research. In the last part of the conference, all participants were invited to join in a WeChat group to discuss and explore the academic issues after the presentations. The online discussion was lasted for about 30-60 minutes. The first two parts were conducted via online collaboration tool, Zoom, while the online discussion was carried out through instant communication tool, WeChat. The online platform enabled all participants to join this grand academic event from their own home. List of Conference Chairman and Committee are available in this pdf.
Detection of Crime Using the Application of Regression Mechanism

International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
PENERAPAN FUZZY INFERENCE SYSTEM SUGENO DALAM MENENTUKAN PENYALURAN PEMBIAYAAN RAHN

The price of gold and the inflation rate are some of the right indicators to analyze the development of sharia rahn mortgage financing distribution. This study aims to determine the amount of rahn financing distribution based on the average gold price of pawnshops and Indonesia's inflation rate in 2018-2019. In this study, Sugeno's fuzzy inference system (FIS) method was used to determine the amount of Rahn's financing distribution. The steps used in the FIS Sugeno method are the formation of fuzzy sets, application of implication and affirmation functions (defuzzification). Based on the FIS Sugeno method, the results of the calculation of the total distribution of rahn financing of PT. Pegadaian (Persero) Branch Syariah Subrantas Pekanbaru in January 2018 was obtained at 252.642.105 with an accuracy value of 89.44%.
Stochastic Networks

This chapter deals with stochastic networks, such as Hopfield networks and Boltzmann machines. A Hopfield network is an ensemble of perceptrons which interact with each other, until a certain cost function which is defined in terms of the interaction between the neurons (called energy function) is minimized. They are useful in solving combinatorial optimization problems. A Boltzmann Hopfield network Boltzmann machinemachine is like a Hopfield network for which the perceptrons have been replaced by binary stochastic neurons. This way, a Boltzmann machine can be seen as the noisy version of a Hopfield network. They are used to avoid Hopfield networks to get stuck in local minima of the energy function. We also present the equilibrium distribution of a Boltzmann machine, its entropy, and its associated Fisher information metric.
Limits on Attention Shape Our Thought and Action

When people interact purposefully with the world around them, including computer systems, some aspects of their behavior follow predictable patterns that result from the limited capacities of attention and short-term memory. This chapter describes these patterns and explains how interactive systems can support them by following certain design guidelines.
A Systematic Framework for Securing Cloud Data

Cloud usage has increased rapidly in many organizations and institutions. Data storage as a service is one among the cloud service, where data owner stores his information in cloud servers rather than in their own servers. Security and Privacy issues are one of the biggest challenges for cloud computing services. Cloud security intends data stored online to be safe by preventing it from being stolen and leaked. Cloud data security can be provided by adopting cryptographic techniques. Data Security includes different services like confidentiality, integrity and identity and access management. To ensure data security a systematic framework that offers key generation, confidentiality, authentication, and key exchange services. Data owner before storing his data on to cloud will implement Laplace transform based key generation service that generates an encryption key by accepting a random secret phrase (seed). Laplace transform encryption is executed by accepting generated secret key and data to provide data confidentiality. If any data user is willing to access the owner’s data he has to be verified. User’s identity as well as Owner’s identity is verified by Knowledge based Authentication. After mutual authentication initial random secret phrase is securely shared between owner and user by initiating LU-key exchange method. Proposed framework is compared with different cloud security frameworks. Computational costs and drawbacks of frameworks are interpreted.
Branches in the Dataflow Metalanguage UPL (METAL) and Methods of their Implementation in the PDCS “Buran”

Branches in the dataflow language for parallel programming UPL (Universal Parallel Language), earlier called METAL, are considered as well as methods of their implementation for Parallel Dataflow Computing System (PDCS) "Buran".A node with P input ports can have several branches, each of which is activated by a subset of input tokens sent on the node's ports.This feature allows for flexible controlled nondeterminism of algorithms.The use of branches is demonstrated by five dining philosophers problem as an example.Also, the necessary information on the semantics of UPL is presented.For implementation of branches the matching device must be able to detect whether tokens are present on all the required (for a particular branch) input ports.To provide this ability, tokens should contain some extra bits of information (in addition to the port number and the usage bit indicating that the port is used by a branch).Three methods to encode this information into tokens are considered.The first two methods are simple but expensive regarding the token size.The last method requires just k bits for each branch provided that the maximum number of ports per branch pm is bounded by A(2 k ,0), where A(m,n) is very rapidly growing Akkerman function.To compare: the first two ways require that pm⩽2 k .For each method, an algorithm is described to determine whether a set of accepted tokens is sufficient to activate a particular branch.A valuable result of the article is the formulation of the very problem, in the solution of which the Ackermann function is involved.
Custom I/O Operators

Wouldn’t it be nice to be able to read and write rational numbers directly, for example, std::cout << rational{355, 113}? In fact, C++ has everything you need, although the job is a little trickier than perhaps it should be. This Exploration introduces some of the pieces you need to accomplish this.
Charge Separation Enhancement Mechanism By p-n Junction in Water Reduction Electrode

Solar water splitting overall efficiency largely depends on the photoanode/photocathode charge carrier separation efficiency. Understanding the competition between charge separation and charge recombination is crucial to improve the device efficiency. In this study first we discussed the challenges in studying such process with femtosecond transient spectroscopy. Then we demonstrated a feasible method by combining transient reflectance (TR) spectroscopy and in situ electrochemical measurement to provide critical information on charge carrier separation efficiency and IPCE on a water/CO 2 reduction photoanode, p-type gallium phosphate with protective titanium dioxide (TiO 2 ) layer. Enhanced charge separation at the interface of gallium phosphate (GaP, 100) single crystal and TiO 2 layer is observed by TR. The separated charge carrier concentration obtained by reflectance change shows strong correlation to the IPCE measured in situ under same condition. Through this correlation we provided direct evidence that the IPCE is heavily determined by the transiently separated charge carriers. This study also provides an applicable and powerful method to study similar HER and OER semiconductor electrode photogenerated charge carrier dynamics at ultrafast time scale.
Extreme Learning Machine with Multi-Agent System for Regression

From the point of learning speed as well as generalization, Extreme Learning Machine(ELM) is widely known as an effective learning algorithm than the conventional learning methods. Basically, hidden neurons are not required in neuron alike, instead, weight is the parameter that would need to learn about the link in between output and hidden layers. The creation of an output is to integrate each independent of several ELMs. The precise approach is included in a Multi-Agent System. The novelty of ELM-MAS (extreme learning machine based multi-agent system) is put forward in the paper for solving data regression problems. The ELMs consist of two layers which are the parent agent layer and individual agent layer. The effectiveness of the ELM-MAS model is proved with some activation functions employing benchmark datasets (abalone, strike and space-ga) and real world application (Nox emission). The outcomes indicate that the proposed model is capable to attain improved results than other approaches.
PERANCANGAN APLIKASI PENGOLAHAN BERITA (PETA) PADA DINAS KOMUNIKASI DAN INFORMATIKA JAKARTA UTARA

The Rapid development of information technology has brought the world into a new era that is faster than ever imagined. With the development of technology in the field of information technology today is increasingly being used by many people who make it easy for the community. Many activities carried out only in a limited scope can now be done in a very broad scope, even worldwide ... such as the many uses of gadgets and smartphones makes people do things easily quickly and instantly. In this case the news processing application that serves to provide convenience in the process of managing, sending and reading news from the community for the community. News processing application is expected to be able to provide accurate, reliable and fast information through information technology to the wider community and can invite the participation of the public to participate in sending the most actual news. So that it can be helped with this website. The research method used in this application research is the method of data collection. As for developing the application itself using Code Igniter. Code Igniter is one of the frameworks used by the author to build information systems and is accompanied by using a database that is adjusted to the needs in the system and application design process that is used today
A survey of clustering methods via optimization methodology

Clustering is one of fundamental tasks in unsupervised learning and plays a very important role in various application areas.This paper aims to present a survey of five types of clustering methods in the perspective of optimization methodology, including center-based methods, convex clustering, spectral clustering, subspace clustering, and optimal transport based clustering.The connection between optimization methodology and clustering algorithms is not only helpful to advance the understanding of the principle and theory of existing clustering algorithms, but also useful to inspire new ideas of efficient clustering algorithms.Preliminary numerical experiments of various clustering algorithms for datasets of various shapes are provided to show the preference and specificity of each algorithm.
Customizing and Extending Spring Security

Spring Security is a very extendable and customizable framework. This is primarily because the framework is built using object-oriented principles and design practices so that it is open for extension and closed for modification. In the previous chapter, you saw one of the major extension points in Spring Security—namely, the pluggability of different authentication providers. This chapter covers some other extension points in the framework that you can take advantage of to extend Spring Security’s functionality or to modify or customize functionality that doesn’t work exactly the way you need in your applications.
Adaptive Privacy-preserving and Shuffling Aggregation in Federated- Learning

Deep learning models are usually trained on data sets containing sensitive information, such as personal shopping transactions, personal contacts, and medical records.Therefore, more and more important work attempts to train neural networks subject to privacy constraints, which are specified by differential privacy or divergence-based relaxation.However, these privacy definitions have weaknesses in handling certain important primitives (synthesis and sub-sampling), which makes the privacy analysis of training neural networks loose or complex.Federated learning is a popular privacy protection method, which collects local gradient information instead of real data.One way to achieve strict privacy guarantee is to apply differential privacy to federated learning.However, previous work did not give a practical solution.This paper proposes a new type of adaptive privacy-preserving and shuffling aggregation in federated-learning mechanism design.It can make the data more different from its original value and introduce lower variance.In addition, the proposed mechanism is updated through the split and shuffle model, avoiding the curse of dimensionality.A series of empirical evaluations conducted on the three commonly used data sets of MNIST, Fashi-MNIST and CIFAR-10 show that our solution can not only achieve excellent deep learning performance, but also provide strong privacy protection.
Lecturer Support and Their Performance at Universities: Mediating Role of Commitment

Perceived support and commitment feelings are vital factors for improved performance.In this respect, the current study aims to investigate the key role of perceived co-worker support (PCS), perceived supervisor support (PSS), and perceived organizational support (POS) on lecturer's affective commitment (AC) and continuous commitment (CC), and in turn on their academic performance.To do this, a survey questionnaire was developed and distributed amongst various university faculties in the Kurdistan Region of Iraq.In total, 204 data points were collected.Based on the results, it has been observed that perceived coworker support and perceived organizational support have significant impact on continuous commitment.Additionally, perceived co-worker support and perceived supervisor support were shown to have significant positive impact on university faculties' performance.
Principles for Fostering Generative Processing in Multimedia Learning

Advances in computer graphic technologies have inspired new efforts to understand the potential of multimedia instruction as a means of promoting human learning. In Multimedia Learning, Third Edition, Richard E. Mayer takes an evidence-based approach to improving education using well-designed multimedia instruction. He reviews 15 principles of multimedia instructional design that are based on more than 200 experimental research studies and grounded in a cognitive theory of how people learn from words and graphics. The result is the latest instalment of what Mayer calls the Cognitive Theory of Multimedia Learning, a theory introduced in previous editions of Multimedia Learning and in The Cambridge Handbook of Multimedia Learning, Second Edition. This edition provides an up-to-date and systematic summary of research studies on multimedia learning, supplemented with complementary evidence from around the globe. It is well-suited to graduate and undergraduate courses in psychology, education, computer science, communication, instructional design, and game design.
Reviews

Introduction to Petroleum Seismology, second edition, by Luc Ikelle and Lasse Amundsen, ISBN 978-1-560-80343-0, 2018, Society of Exploration Geophysicists, 1404 p.
A novel median filtering forensics based on principal component analysis network

As an important issue of forensic analysis, median filtering detection has drawn much attention in the decade. While several median filtering forensic methods have been proposed, they may face trouble when detecting median filtering on low-resolution or compressed images. In addition, the existing median filtering forensic methods mainly depend on the manually selected features, which makes these methods may not adapt to varieties of data. To solve these problems, convolution neural networks have been applied to learn features from the training database automatically. But the CNN-based method trains slowly and the parameters of it is hard to select. Thus, we proposed a PCANet-based method. And we test our trained model on several databases. The simulation shows that our proposed method achieves better performance, and trains much faster than CNN-based method.
MOZAMBIQUE: ‘Daring’ Attacks

Africa Research Bulletin: Political, Social and Cultural SeriesVolume 57, Issue 3 p. 22664B-22665B National Security MOZAMBIQUE: ‘Daring’ Attacks First published: 30 April 2020 https://doi.org/10.1111/j.1467-825X.2020.09382.xRead 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. Volume57, Issue3April 2020Pages 22664B-22665B RelatedInformation
Documents Handling

As long as most of the discussions are around the single data source and the fact that data must be stored, updated, synchronized and available within the entire company, seems obviously for PLM that documents handling is one of the most considered activity.
Creating a power grid under the sea

European energy supply is being completely restructured with a deep-sea power grid. ANDRITZ submersible motor pumps supply the water needed to spray onto the sea bed to soften it so that power cables can be buried.
No Copyright Protection for a Footwear Design

No Copyright Protection for a Footwear Design Get access GRUR International, Volume 70, Issue 2, February 2021, Pages 200–204, https://doi.org/10.1093/grurint/ikaa176 Published: 22 December 2020
APPLICATION OF PATH PLANNING FOR INTELLIGENT MECHANICAL ROBOT UNDER EMBEDDED REAL-TIME SYSTEM

Objective: The paper is to study the path planning of the intelligent mechanical robot under the embedded real-time system, to provide theoretical support for the path planning problems of mobile robots.Method: In this paper, the embedded system is applied to the path planning of the mobile robot, and it is used as the processor of the mobile robot.The path planning of the mobile robot and algorithms to avoid obstacles are also studied.Also, this paper proposes an improved A* algorithm.It will build a specific environment grid based on the existing environment materials and use the improved A* algorithm to analyze each node in detail to explore the most suitable and fastest path.Results: The total turning angle of the mobile robot using the primary A* algorithm is 180° and the path length is 10.07m.The total turning angle of the mobile robot using the secondary A* algorithm is 112.62°, and the path length is 9.84m.According to the experimental results, compared with the primary A* algorithm, the secondary A* algorithm can effectively reduce the path length and unnecessary turning of the mobile robot during the travel.The path length is reduced by 2.21% and the turning angle is reduced by 37.43%.The secondary A* algorithm has effectively improved the turning angle of the mobile robot and has greatly optimized the travel path of the mobile robot.Conclusion: The improved A* algorithm in this paper can effectively plan the travel path of the mobile robot, and ensure the efficiency and correctness of the planned path.The path planning and design error of the mobile robot in this paper is relatively low, and it can perform better path planning.
CPD 2020

In the real-world ubiquitous computing systems, it is difficult to require a significant amount of data to obtain accurate information through pure data-driven methods. The performance of data-driven methods relies on the quantity and 'quality' of data. They perform well when a sufficient amount of data is available, which is regarded as ideal conditions. However, in real-world systems, collecting data can be costly or impossible due to practical limitations. On the other hand, it is promising to utilize physical knowledge to alleviate these issues of data limitation. The physical knowledge includes domain knowledge from experts, heuristics from experiences, analytic models of the physical phenomena and etc.