Reviewerly/exHarmony huggingface dataset:
Improved Turbidity Estimation from Local Meteorological Data for Solar Resourcing and Forecasting Applications

This work presents a new method to estimate atmospheric turbidity with improved accuracy in estimating clear-sky irradiance. The turbidity is estimated by machine learning algorithms using commonly measured meteorological data including ambient air temperature, relative humidity, wind speed and atmospheric pressure. The estimated turbidity is then served as input to the Ineichen-Perez clear-sky model to estimate clear-sky global horizontal irradiance (GHI) and direct normal irradiance (DNI). When compared with the original Ineichen-Perez model who uses interpolated turbidity from the monthly climatological means, our turbidity estimation better captures its daily, seasonal, and annual variations. When using the improved turbidity estimation in the Ineichen-Perez model, the root mean square error (RMSE) of clear-sky GHI is reduced from 24.02 W/m 2 to 9.96 W/m 2 . The RMSE of clear-sky DNI is deceased from 76.40 W/m 2 to 29.53 W/m 2 . The presented method is also capable to estimate turbidity in partially cloudy days with improved accuracy, evidenced by that the corresponding estimated clear-sky irradiance has smaller deviation from measured irradiance in the cloudless time instants. In sum, the proposed method brings new insights about turbidity estimation in both clear and partially cloudy days, providing support to solar resourcing and forecasting.
Chinese Weibo Sentiment Classification Method Incorporating Facial Expression Features

research-article Chinese Weibo Sentiment Classification Method Incorporating Facial Expression Features Share on Author: Shanshan Jia Shijiazhuang University of Applied Technology, China Shijiazhuang University of Applied Technology, ChinaSearch about this author Authors Info & Claims AIAM2021: 2021 3rd International Conference on Artificial Intelligence and Advanced ManufactureOctober 2021 Pages 554–559https://doi.org/10.1145/3495018.3495117Online:14 March 2022Publication History 0citation0DownloadsMetricsTotal Citations0Total Downloads0Last 12 Months0Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Kalman Filters

Understanding or controlling a physical system often requires a model of the system, that is, knowledge of the characteristics and structure of the system. A model can be a pre-defined structure or can be determined solely through data. In the case of Kalman Filtering, we create a model and use the model as a framework for learning about the system. This is part of the Control branch of our Autonomous Learning taxonomy from Chapter 1 .
Cryptocurrencies

Based on the notion that today monetary exchanges are based on the transfer of information, this chapter provides a basic introduction into Shannon’s theory of information, with its central concept—the entropy. After covering different ways to encode information the relation of Shannon’s entropy to the entropy, known from thermodynamics, is illustrated with a physical system that has discrete energy levels. The chapter then discusses the transmission of information across binary symmetric channels and develops the necessary concepts to establish the maximum of the mutual information as the channel capacity. After moving information through continuous channels, limited by the signal-to-noise ratio, a section introduces the basics of cryptography, which is needed to provide the security when transmitting sensitive information. Public-key systems, Diffie-Helman and RSA, are discussed in some detail, before covering the basics of elliptic function cryptography, which provides the basis for both Bitcoin and Ethereum blockchains, the subject of later sections in the chapter. An Ethereum smart contract is discussed as an example of a distributed application—a DApp. The last section touches upon the basics of quantum computing and illustrates the key concepts of Shor’s algorithm, which might one day pose a threat to cryptographic systems.
Bayesian Classifiers

This chapter covers Bayesian classifiers. After a brief introduction to the classification problem, the naive Bayesian classifier is presented, as well as its main variants: TAN and BAN. Then the semi-naive Bayesian classifier is described. A multidimensional classifier may assign several classes to the same object. Two alternatives for multidimensional classification are analyzed: the multidimensional Bayesian network classifier and the Bayesian chain classifier. Then an introduction to hierarchical classification is presented. The chapter concludes by illustrating the application of Bayesian classifiers in two domains: skin pixel detection in images and drug selection for HIV treatment.
Dimensionality Reduction

Dimensionality reduction is a hot research topic in data analysis today. Thanks to the advances in high performance computing technologies and in the engineering field, we entered in the so-called big-data era and an enormous quantity of data is available in every scientific area, ranging from social networking, economy and politics to e-health and life sciences. However, much of the data is highly redundant and can be efficiently brought down to a much smaller number of variables without a significant loss of information using different strategies.
Big Data and Data Analytics Research

The Big Data and Data Analytics is a brand new paradigm, for the integration of Internet Technology in the human and machine context. For the first time in the history of the human mankind we are able to transforming raw data that are massively produced by humans and machines in to knowledge and wisdom capable of supporting smart decision making, innovative services, new business models, innovation, and entrepreneurship. For the Web Science research, this is a new methodological and technological spectrum of advanced methods, frameworks and functionalities never experienced in the past. At the same moment communities out of web science need to realize the potential of this new paradigm with the support of new sound business models and a critical shift in the perception of decision making. In this short visioning article, the authors are analyzing the main aspects of Big Data and Data Analytics Research and they provide their own metaphor for the next years. A number of research directions are outlined as well as a new roadmap towards the evolution of Big Data to Smart Decisions and Cognitive Computing. The authors do hope that the readers would like to react and to propose their own value propositions for the domain initiating a scientific dialogue beyond self-fulfilled expectations.
Navigation Path Detection for Cotton Field Operator Robot Based on Horizontal Spline Segmentation

Visual navigation is one of the fundamental techniques of intelligent cotton-picking robot. Cotton field composition is complex and the presence of occlusion and illumination makes it hard to accurately identify furrows so as to extract the navigation line. In this paper, a new field navigation path extraction method based on horizontal spline segmentation is presented. Firstly, the color image in RGB color space is pre-processed by the OTSU threshold algorithm to segment the binary image of the furrow. The cotton field image components are divided into four categories: furrow (ingredients include land, wilted leaves, etc.), cotton fiber, other organs of cotton and the outside area or obstructions. By using the significant differences in hue and value of the HSV model, the authors segment the threshold by two steps. Firstly, they segment cotton wool in the S channel, and then segment the furrow in the V channel in the area outside the cotton wool area. In addition, morphological processing is needed to filter out small noise area. Secondly, the horizontal spline is used to segment the binary image. The authors detect the connected domains in the horizontal splines, and merger the isolate small areas caused by the cotton wool or light spots in the nearby big connected domains so as to get connected domain of the furrow. Thirdly, they make the center of the bottom of the image as the starting point, and successively select the candidate point from the midpoint of the connected domain, according to the principle that the distance between adjacent navigation line candidate is smaller. Finally, the authors count the number of the connected domains and calculate the change of parameters of boundary line of the connected domain to make sure whether the robot reaches the outside of the field or encounters obstacles. If there is no anomaly, the navigation path is fitted by the navigation points using the least squares method. Experiments prove that this method is accurate and effective, which is suitable for visual navigation in the complex environment of a cotton field in different phases.
Educational Game Exploring the Old Museum Using Fuzzy State Machine

Indonesia has a diverse culture from the form of creation, work, and intention, but over time Indonesian culture is eroded by the sophistication of the times. Using entertainment media such as games will be able to provide knowledge about culture through the game and can develop morale, using 3D interactive design of an object such as historical heritage will look close to real and with the Aritificial Intelligence (AI) used in the opponent will make the game that is played becomes fun or not monotonous. This study uses the Fuzzy State Machine (FuSM) method which aims to shape character behavior like human like behavour. The results that can be generated from FuSM are behavior that changes according to the conditions and rules that have been determined. This is where the AI ​​that is formed will not always be the same in the same situation, all will be different depending on the conditions and rules that exist.
Introduction

Visual content mining has a long history and has been a central problem in the field of Computer Vision. It consists in finding and correctly labelling objects in images or video sequences, recognition of static and dynamic scenes. It is necessary in a large set of research and application domains: multimedia indexing and retrieval, computer vision, robotics, computer-aided diagnosis using medical images…Humans are naturally good at performing visual scene recognition without any particular effort. However, automatic object and scene recognition still remains a challenging task.
NOD Makerspace

NOD Makerspace in Bucharest, Romania is located in a renovated cotton factory that was built when Romania was under communist rule. It's fitting that NOD has transformed the space to become a beacon of entrepreneurship and innovation within Bucharest. NOD is the first makerspace in the city, with studios in the areas of digital fabrication, ceramics, metal and woodworking, computing, and textiles. The space also provides offices for small businesses and startups, which is an integral part of the mission of NOD. Open since 2015, NOD has continued to grow by taking over the ground floor of the factory, which will house more studio space for businesses and startups. NOD is committed to entrepreneurship and innovation but at this time struggles to find a balance between the younger generation of makers and the current professional makers of NOD. This chapter explores NOD Makerspace.
Web 2.0 From Evolution to Revolutionary Impact in Library and Information Centers

A key element of the technology is that it allows people to create, share, collaborate, and communicate. The Web 2.0 differs from ordinary websites as it does not require any web design or publishing skills to participate, making it easy for people to create and publish or communicate their work to the world. The nature of this technology makes it an easy and popular way to communicate information to either a select group of people or to a much wider audience. The Web 2.0 paradigm has gained substantial momentum in the last decade. The influence of Web 2.0 principles and technologies has fueled an explosion of information and media content on the web, and individual and corporate adoption of the technologies continues to rise. In this milieu, it is imperative to understand and learn about the present and evolving Web 2.0 tools and their application in different walks of life. The proposed study made an endeavor to dig deep into the genesis, development, and application of various Web 2.0 tools in library and information science.
Quantum Gates

This chapter introduces the fundamentals of quantum gates (operators) and describes generally used gates in designing quantum algorithms.
The fast Fourier transform

Abstract This chapter demonstrates the use of different data distributions in different phases of a parallel fast Fourier transform (FFT), which is a regular computation with a predictable but challenging data access pattern. Both the block and cyclic distributions are used and also intermediates between them. Each required data redistribution is a permutation that involves communication. By making careful choices, the number of such redistributions can be kept to a minimum. FFT algorithms can be concisely expressed using matrix/vector notation and Kronecker matrix products. This notation is also used here. The chapter then shows how permutations with a regular pattern can be implemented more efficiently by packing the data. The parallelization techniques discussed for the specific case of the FFT are also applicable to other related computations, for instance in signal processing and weather forecasting.
Cryptocurrencies

A cryptocurrencyCryptocurrency is a currency in the digital realm that is designed to work as a medium of exchange. Entries of units—called tokensToken or crypto tokens—in a decentralized consensus-database (blockchainBlockchain) make up the fabric of the cryptocurrencyCryptocurrency. As the name suggests, the construct underlying cryptocurrencies relies heavily on cryptography to ensure that transactions are verified and secure, and to control the supply of new units.
Practical Multi-Keyword Ranked Search with Time- Based Access Control over Encrypted Cloud Data

The recent trends suggest that there is an increase in the inclination towards storing data in the cloud due to explosive and massive growth of the volume of the data in the cloud computing environment. It helps them to reduce their computational and storage costs but also undeniably brought in concerns about security and privacy as the owners of the highly sensitive data lose control of it directly. The sensitive data could include electronic-based medical records, confidential fiscal documents, etc. An increased distrust about storage of files in a third-party service provider of cloud resources would contradict the very same reason for which cloud storage facilities were introduced. That’s because we cannot deny the fact that cloud based storage systems offer on- demand and ubiquitous access to flexible storage and computational resources. The keyword ranked search methodologies used in the existing systems mainly focus on enhancing and enriching the efficiency of searching the files and their respective functionalities but a lack of straight forward analysis of security and issues with providing access control have not been addressed. To address these disadvantages, in this paper, we propose an efficient Multi-Keyword Ranked Search scheme with Fine-grained access control (MRSF).MRSF is a methodology which can combine matching of coordinates technique with Term Frequency-Inverse Document Frequency (TF-IDF) to thereby achieve a highly precise retrieval of any cipher text of interest. It also improves the secure k-nearest neighbors (kNN) method. By utilizing an access strategy which is polynomial based, it can effectively refine the search privileges of the users’. Professional security analysis proves that MRSF is secure with respect to safeguarding the secrecy of outsourced data and the privacy of tokens and indices. Along with this enhanced methodology of ranked search scheme, a time limit based access control feature has also been proposed to ensure that the adaptive attackers are stalled from giving prolonged access to the data files. Session expiry will ensure security of data and that is to be achieved by providing a time window for the file retrieval. Extensive experiments also show that MRSF reaches higher search precision and many more functionalities when compared to the existing systems.
Software Resources

This chapter is aimed to introduce frameworks developed in the Bayesian optimization (BO) community describing many aspects of these tools, where it is possible to retrieve the tool, in which language and version are available. Section 6.1 is devoted to open source software, while industrial BO as a service solutions are analysed in 6.2. Section 6.3 is devoted to BO solutions specifically developed for hyperparameters optimization of machine learning algorithms. Section 6.4 presents relevant sources for test problems, both in terms of test functions and generators. Finally, Sect. 6.5 reports some relevant non-Bayesian global optimization software. The software in this section refers, basically, to the box-constrained case, with the exception of Predictive Entropy Search with Constraints (PESC) which is included in the open source package Spearmint ( https://github.com/HIPS/Spearmint/tree/PESC ).
Potentials of Internet-Based Qualification Systems for Teachers in Federal Education Systems

Making an internet-based system of qualification available for teachers at general education schools within a federally organized education system poses a variety of challenges. Based on findings of pedagogical professional research, further and advanced teacher training needs to impart specialist scientific competencies and––simultaneously connected with these competencies––subject-didactic ones as well as providing support for curricular implementation. There also needs to be a broad portfolio of modules leading to specialist and didactic qualifications which can take heterogeneous curricular requirements into account. Based on pedagogical as well as systematic requirements, the chapter formulates the essential cornerstones of such a qualification-based online training system, using the example of the economic (general) education. In addition, the necessary development steps for the future are outlined, especially regarding the use of adaptive teaching and learning methods.
Fuzzy Logic

Fuzzy logic [26] is an alternative approach to control system design. Fuzzy logic works within the framework of set theory and is better at dealing with ambiguities. For example, three sets may be defined for a sensor: hard failure, soft failure, and no failure. The three sets may overlap and at any given time the sensor may have a degree of membership in each set. The degree of membership in each set can be used to determine what action to take. An algorithmic approach would have to assign a number to the state of the sensor. This could be problematic and not necessarily represent the actual state of the system. In effect, you would be applying a degree of fuzziness.
Application and Security Issues in Cloud Computing

Cloud computing is attaining a pace for resolving complex computing problems. It is basically an abstracted layer of technology which has three service models: Infrastructure as a Service (IaaS), (Software as a Service) SaaS and (Platform as a Service) PaaS, which provide infrastructure, software and a platform to end-user. On the contrary, there are lots of issues which include energy efficiency, cloud integrity, data recovery, backup, etc. Security and privacy issues like data confidentiality and integrity are the most critical ones. This paper highlights the security issues related to data stored and data access from back end (service provider). It collates each and every application related to cloud and available techniques to resolve some issues. Very less research work has been done on applications and security issues of cloud computing together. This article is an analysis of cloud computing applications and security issues as it is used to a great extent. In future this paper will help research community to grab information regarding applications and techniques to resolve the issues related to Cloud computing.
Clouds of Quantum Machines

This chapter continues previous studies in service-oriented architectures (SOA) on clouds of quantum computers, considering quantum entanglement and quantum teleportation of states of services as resources to deploy high production in IT environments and to guide studies on the implementation of intelligent behavior in server clouds. A way to preserve quantum entanglement is presented. Also, the chapter proposes a metalanguage to organize the topology of orchestration of services. This topology is embedded in the states of services and takes part in the information to be teleported from server to server. The creation of entangled states of information with the aid of the concept of progenitor is reviewed with some details.
Research on Campus Network Security Problem and Protection Strategy

With the “Internet +” era of arrival, the major colleges and universities are in the construction of the wisdom of the campus, students and teachers living with the campus network is more and more closely related, Campus network security has become the protection of the wisdom of the campus construction. Campus network security issues become increasingly serious; a single security protection has been unable to meet the current security needs. This paper analyzes the major security threats facing the campus network, and presents the campus network security protection measures from the physical layer, network layer, system layer, application layer and management of five aspects, thus constructing the campus network's overall security defense system. The system has multiple security protection for Campus Network, thus improving the security of the campus network.
Quality of library staff training in the context of labor market re-quirements

The article analyses the key factors affecting the assessment of the quality of higher education by the state, the labor market and the individual based on the methodology of the subjective approach. It shows the transformation of the requirements for job candidates that were traditional for the previous stages of reproduction of competent labor, the key ones becominginterdisciplinary competencies: creativity, speed of cognitive reactions, team work skills, result orientation, etc. Expert opinions’ analysis is performed to identify the professions of the nearest future. This analysis is the basis for the study of the potential for training the specialists in the area of library and information activities. It is shown that in a broad sense, the library as the most important socio-cultural institution has no alternatives. It presents examples of job specifics that correspond with the realities of the IV Industrial revolution and are designed to form the information culture of the society and develop socio-cultural communications. The specifics of personal preferences on the desired quality of education as a factor in achieving life goals are studied. There is a trend on a reduction of the number of people considering the higher education being a “social lift”. This fact strongly affects the subjective perception of the rating of the chosen higher education specializations and the corresponding higher educational institutions.
Biofuel Supply Chain Optimization Using Random Matrix Generators

Supply chain problems are large-scale problems with complex interlinked variables. This sort of characteristic closely resembles structures often encountered in the nuclei of heavy atoms (e.g., platinum, gold or rhodium). Such structures are said to have the property of universality.