Reviewerly/exHarmony huggingface dataset:
Khongso

Khongso /kʰɔŊ˦so˧/ is an SVO Tibeto-Burman language spoken by between two and three thousand speakers in Paletwa Township, Southern Chin State, Myanmar (Dryer 2008, Wright 2009). The speakers live in 17 villages primarily along the Michaung River (see Figure 1).1 Khongso is mutually intelligible with Anu, which has a population of 700 and is spoken west of the Khongso area (So-Hartmann 1988, Wright 2009, Lewis, Simons &amp; Fennig 2016). The ISO code for Khongso and Anu is anl and the glottolog code is anuu1241.
An Efficient Stochastic Update Propagation Method in Data Warehousing

This article develops a stochastic update propagation method for an operational data store (ODS) in data warehousing (DW) environments where data storage (and retrieval) is required as a sum of data at distributed source nodes. The authors' proposed method results in less network traffic (as compared with the real-time method) due to update propagation required because of changes in source data. More importantly, the method allows system users to place limits on the discrepancy between the source data and the ODS data that could result due to a time lag between source data changes and the update operation. Finally, the pre-specified limits on the discrepancy are maintained while accounting for two crucial factors in distributed systems: 1) some nodes are situated on more congested network links, and 2) some of the links on the network are less reliable. Real-time data propagation does not account for these frequently encountered networking concerns.
Energy-Efficient Task Consolidation for Cloud Data Center

Energy saving in a Cloud Computing environment is a multidimensional challenge, which can directly decrease the in-use costs and carbon dioxide emission, while raising the system consistency. The process of maximizing the cloud computing resource utilization which brings many benefits such as better use of resources, rationalization of maintenance, IT service customization, QoS and reliable services, etc., is known as task consolidation. This article suggests the energy saving with task consolidation, by minimizing the number of unused resources in a cloud computing environment. In this article, various task consolidation algorithms such as MinIncreaseinEnergy, MaxUtilECTC, NoIdleMachineECTC, and NoIdleMachineMaxUtil are presented aims to optimize energy consumption of cloud data center. The outcomes have shown that the suggested algorithms surpass the existing ECTC and FCFSMaxUtil, MaxMaxUtil algorithms in terms of the CPU utilization and energy consumption.
Introduction

Classical usability and user-experience testing involve a thorough and systematic evaluation of the system that is under evaluation. This may be done with user-centric, or expert-centric methods [10, p. 24]. The goal of such an evaluation is usually to test if a system acts as expected and meets the requirements that its users have [8, p. 319].
Implementations

In the remaining chapters of the book we will survey the leading approaches for implementing quantum computation. This is a vast, and very active field of research. The presentation will not be comprehensive, but will strive to explain the basic physical principles underlying the most promising approaches, as well as providing a snapshot of the current status. Before proceeding to descriptions of the different physical approaches we introduce some general tools and concepts including the Lindblad equation, T1 and T2 coherence times, Rabi oscillations, and Ramsey interference.
Advanced Topics in Logic

We consider some advanced topics in logic including fuzzy logic, temporal logic, intuitionist logic, undefined values, logic and AI and theorem provers. Fuzzy logic acts as a mathematical model for vagueness. Temporal logic is concerned with the expression of properties that have time dependencies. Brouwer developed intuitionist logic as the logical foundation for intuitionism (a controversial theory of the foundations of mathematics). We discuss several approaches to deal with undefined values including the logic of partial functions, Dijkstra’s approach with his cand and cor operators and Parnas’s classical approach.
Where Do All My Keys Come From?

Nowadays, cyber-physical systems are omnipresent in our daily lives and are increasingly used to process confidential data. While the variety of portable devices we use excessively at home and at work is steadily increasing, their security vulnerabilities are often not noticed by the user. Therefore, portable devices such as wearables are becoming more and more interesting for adversaries. Thus, a robust and secure software design is required for the implementation of cryptographic communication protocols and encryption algorithms. While these topics are well discussed and subject to further research activities, the issue of provisioning the initial device setup is widely uncovered. However, the protection of the initial setup is as important as the protection of the confidential data during the time in use. In this work, the authors will present solutions for a secure initialization of security critical integrated circuits (ICs).
Managing Customer Journeys in a Nimble Way for Industry 4.0

In the Fourth Industrial Revolution, customers expect companies to provide journeys in line with rapidly changing expectations. This allows for great potential for project portfolios that can enable tailored experiences, powered by technology and insights coming from the 360° view of the customer, to improve the experience and touchpoints before, during or after the main interaction of customers with a company. This chapter will illustrate that project managers need to master a dual dynamic to do so. On the one hand, new types of projects, changing expectations and shifting habits offer humbling challenges. On the other hand, governance, change and delivery continue to be the foundational baseline. By integrating theoretical insights and real-life cases from conservative and progressive industries, the author wants to stimulate project managers. Rather than seeing Industry 4.0 as a transformational tsunami, they should see it as an opportunity to remain curious, nimble and committed, while working in a reality where rapidly changing demand entails growth, learning and great value.
Second or Foreign Language Learning With Augmented Reality

The following chapter will discuss the impact of technology use and mobile learning, specifically augmented reality (AR), in the process of learning a second or foreign language, namely English and Spanish. The chapter will begin with an overview of AR and then include a discussion of the theoretical framework, language learning contexts, as well as AR tools and applications in the process of second or foreign language learning. An overview of the benefits of AR in language learning will also be included, as well as an introduction to AR applications and specific AR systems, platforms, and case studies in language learning. The research will also provide a discussion of the challenges of using AR in language learning contexts, including specific attention to challenges with AR and learning, AR and language learning, and mobile learning as a whole. The chapter will conclude with final thoughts from the authors in terms of potential areas of AR development that are in need of further attention.
User Acceptance of Technologies in Their Infancy

This paper adjusts UTAUT2 to study user acceptance of an early stage technology by using the example of 3D printing for home users. The authors' findings show that UTAUT2 is capable of measuring user acceptance and that social influence and effort expectancy are good predictors for ‘intention to use' for early stage technologies. Nevertheless, there seem to be significant differences in the antecedents depending on the involvement levels and the DIY mentality of the user. Moreover, this research confirms and extends the applicability of UTAUT2 to early stage technologies while improving the authors' understanding of prospective 3D printing home users.
A Critical Overview of Image Segmentation Techniques Based on Transition Region

Image segmentation is the key step from image processing to image analysis, and it is an important technique of image engineering. Image segmentation based on transition region is a special or distinctive type of technique that are different from traditional boundary-based or region-based techniques. Since the first technique using transition region proposed, there are many subsequent related researches and applications, and a series of papers in the literature citing are published worldwide. Using Google Scholar, a number of papers citing the original papers are searched, and a study on the statistics of these papers is conducted. These papers are sorted first according to the publishing year, and then grouped according to their purposes and contents (with techniques used). Some questionable issues in these papers are pointed out and critically discussed, and several further research directions are indicated and analyzed.
Role-Based Delegation with Negative Authorization

Role-based delegation model (RBDM) based on role-based access control (RBAC) has proven to be a flexible and useful access control model for information sharing on distributed collaborative environment. Authorization is an important functionality for RBDM in distributed environment where a conflicting problem may arise when one user grants permission of a role to a delegated user and another user grants the negative permission to the delegated user.
Profiling and Personalization in Internet of Things Environments

The chapter considers problems of user personalization and resources competence modeling in the internet of things (IoT) environments. Creation of the user profiles and its utilization during the interaction of the user with IoT resources significantly increase the efficiency of such interaction. When the user generates a task to perform by the IoT resources, the formal model of this task is expanded by the relevant information in accordance with the user profile model. The obtained results should be presented to the user in accordance to his/her preferences from the user profile model. Resource competence profile should store information about the resource competencies and constraints that have to be satisfied to enable these competences. In this case, resource competence profiles automate their interaction in IoT environments.
APPROACH TO AUTOMATED STRUCTURING OF EDUCATIONAL RESOURCES BASED ON THE METHOD OF RECURSIVE REDUCTION

The article is devoted to the issues of automated structuring of educational information resources, presented in natural language texts, with the purpose of creating interactive documents based on them. The problems of formation, processing, presentation, use and integration of large volumes of interdisciplinary knowledge are considered. Prospects for the development of information technologies designed to create a formalized system of knowledge in specific subject areas are substantiated. The article analyzes the most common analytical systems that are designed to process natural language texts and can be used to solve this problem. The article proposes a way to evaluate software based on multicriteria optimization. The criteria for such an assessment are identified and justified and its results are presented. Based on the obtained results, it is shown that the most effective tool for solving the problem is the system “Recursive reducer”, which allows to analyze a wide range of documents and present the results in various forms, including XML ontologies that can be used in the work of cognitive IT technology (CIT) “Polyhedron”. The article gives a brief description of the mathematical model on which the “Recursive reducer” based on the use of λ-expressions works. λ-expressions are used to form specialized recursive functions that perform the tasks of identifying tokens in the input text and forming objects. The use of an ontological document classifier to improve the efficiency of a recursive reducer is further described. Article also gives an example of it’s usage — automated structuring of educational information resource, presented by the curriculum in chemistry (advanced training), its presentation in the form of an ontology and creation on its basis of an interactive document by means of CIT “Polyhedron”.
A Pose Synchronization Control Method for the Approach Phase of Lunar Lander

Aiming at the problem of autonomous obstacle avoidance in the approach phase of lunar soft landing, a dynamic autonomous obstacle avoidance strategy of "open-loop first, closed-loop afterwards " is proposed in the accurate obstacle avoidance stage, and the pose synchronization control problem in the open-loop control stage of this strategy is studied. First, establishing the dynamic model of the approach phase in the local coordinate system of the target point, and on this basis, describing the field-of-view constraint of the visual sensor, boundary conditions and performance index in the pose synchronization optimal control problem. Then based on the improved salp swarm algorithm (ISSA) and the compound penalty function, the global optimization of the pose synchronization optimal control problem is performed. Finally, a variety of simulation examples are used to verify the performance of the proposed algorithm, and the simulation results show the effectiveness of the designed algorithm
U-Learning and Virtual Classrooms in Social Sciences Education

The development of internet, wireless devices, and sensors; the expansion of the use of mobile technologies; or the development of applications have enabled different ubiquitous learning modalities. u-Learning is an expanded model from e-learning and m-Learning with features such as mobile, collaborative, interactive, omni-synchronous, and experimental that fosters interaction and breaks limitations by place and time in the teaching and learning of social sciences, geography, and history. U-Learning is considered as a learning model that integrates technology in the assessment and monitoring of educational processes of the students, a learning model where virtual classrooms and virtual learning environments are highlighted. In a social context with a lack of civic engagement and democratic participation, interactive character of virtual classrooms, including social networks, is essential because they connect teachers, students, and parents in addition to encouraging participation in virtual learning environments.
An Improved Genetic Algorithm for Document Clustering on the Cloud

This article presents a modified genetic algorithm for text document clustering on the cloud. Traditional approaches of genetic algorithms in document clustering represents chromosomes based on cluster centroids, and does not divide cluster centroids during crossover operations. This limits the possibility of the algorithm to introduce different variations to the population, leading it to be trapped in local minima. In this approach, a crossover point may be selected even at a position inside a cluster centroid, which allows modifying some cluster centroids. This also guides the algorithm to get rid of the local minima, and find better solutions than the traditional approaches. Moreover, instead of running only one genetic algorithm as done in the traditional approaches, this article partitions the population and runs a genetic algorithm on each of them. This gives an opportunity to simultaneously run different parts of the algorithm on different virtual machines in cloud environments. Experimental results also demonstrate that the accuracy of the proposed approach is at least 4% higher than the other approaches.
An Intelligent Approval System for City Construction based on Cloud Computing and Big Data

On the theoretical basis of cloud services, big data technology and case-based reasoning technology (CBR), the authors propose an Intelligent Approval System for City Construction (IASCC). The paper introduces the concept of ‘case approval cloud' and puts forward the city construction approval model based on CBR, by which the storage and computation of the urban construction approval data are concentrated in the cloud. In this system, the authors use the distributed database of HBase, making the data storage capacity of the system with high scalability, design the intelligent approval system based on CBR using the distributed programming framework of MapReduce, making full use of the large amount of historical approval data, and use the distributed full-text retrieval system of SorCloud to retrieve the approval data with a high response speed. IASCC adopts Hadoop as the development platform, using HBase, Solr and MapReduce technology to complete the prototype development of an intelligent approval system. Finally, the authors give the implementation of the system and the performance tests of some key modules.
A Novel Approach to Managing the Dynamic Nature of Semantic Relatedness

This research proposes a novel method of measuring the dynamics of semantic relatedness. Research on semantic relatedness has a long history in the fields of computational linguistics, psychology, computer science, as well as information systems. Computing semantic relatedness has played a critical role in various situations, such as data integration and keyword recommendation. Many researchers have tried to propose more sophisticated techniques to measure semantic relatedness. However, little research has considered the change of semantic relatedness with the flow of time and occurrence of events. The authors' proposed method is validated by actual corpus data collected from a particular context over a specific period of time. They test the feasibility of our proposed method by constructing semantic networks by using the corpus collected during a different period of time. The experiment results show that our method can detect and manage the changes in semantic relatedness between concepts. Based on the results, the authors discuss the need for a dynamic semantic relatedness paradigm.
Solar radiation

This chapter introduces the principles and algorithms for estimating downward surface shortwave radiation and photosynthetically active radiation (PAR) from remotely sensed data. The advantages and disadvantages of the existing algorithms are also briefly discussed. Section 5.1 briefly introduces basic concepts, such as the solar radiation spectrum, solar constant, and shortwave radiation and PAR. Section 5.2 presents the current observation networks of global solar radiation, including global energy balance archive, baseline surface radiation network, surface radiation budget network, and FLUXNET. Section 5.3 introduces the related solar radiation estimation methods. Section 5.4 introduces the current existing solar radiation products from remote sensing observations. This chapter ends with a short summary.
The R Programming Language and Software

This chapter is an introduction to the R programming language and software to provide the basis for the reader to implement the methods presented in the following chapters. The chapter begins with instructions on how to obtain R and how to take your first steps into this environment. The main R data objects are presented (vectors, matrices, data frames, and lists). Interactions with external data to read them from file or write to file are also discussed. Notions of programming with loops, conditional executions, and functions are particularly important for working with dynamic models. Graphics and statistical capabilities are introduced briefly too. R packages provide functions to be used for applying methods and you will learn how to use these packages. Finally, two topics that are particularly important for our subject are discussed including how to use R to interact with a model programmed in a different language and how to reduce computing time.
Modified Differential Evolution Algorithm Based Neural Network for Nonlinear Discrete Time System

Two main important features of neural networks are weights and bias connection, which is still a challenging problem for researchers. In this paper we select weights and bias connection of neural network (KN) using modified differential evolution algorithm (MDEA) i.e. MDEA-NN for uncertain nonlinear systems with unknown disturbances and compare it with KN using differential evolution algorithm (DEA) i.e. DEA-KN. In this work, MDEA is based on exploitation and exploration of capability, we have implemented differential evolution algorithm and modified differential evolution algorithm, which are based on the consideration of the three main operator's mutation, crossover and selection. MDEA-KN is applied on two different uncertain nonlinear systems, and one benchmark problem known as brushless dc (BDC) motor. Proposed method is validated through statistical testing's methods which demonstrate that the difference between target and output of proposed method are acceptable.
Business Models

The Internet has created new possibilities that we did not foresee in its early years. Blockchain technology is unique and has great potential to penetrate existing markets and to develop new markets. In this chapter, readers will understand business models for blockchain technology. It will help them to know how a current business can be transformed and also how to create new markets.
DEEP LEARNING TECHNIQUE BASED TEXT EMOTION CLASSIFICATION SYSTEM USING GENETIC ALGORITHM TECHNIQUE

In today’s era the research area of emotion detection has becomes trendy field of research. The data in text form is the very easy way to communicate among interaction of human-machine through the social networking sites, is one of the schemes to share users views. Recognition of human’s emotion through analyzing textual documents is useful and essential, but sometimes difficult because of the fact that it is not necessary to use emotion words directly in textual expressions. In this research, a deep learning technique based Text Emotion Classification (TEC) System using Genetic Algorithm (GA) as an optimization technique is presented. Initially, a lexicon dictionary is prepared based on the emotional words and different processes such as pre-processing, feature extraction, optimization and classification has been applied to classify the textual emotion. The test data has been trained using deep learning scheme named as Deep Neural Network (DNN) with optimization technique based on GA with a novel fitness function. The emotion; happy, sad and angry are identified as per the shared data on the social media platform. Most of the state-of-the-art in the previous research on textual emotion mining is mainly focused on without utilizing the feature selection concept, so we introduce the concept of feature selection using the GA and passes an input to DNN. At the last, we compare the performance of the proposed TEC system with existing work proposed by Chatterjee et al. terms of precision, recall and F-measure and we observed that the system got better emotion classification accuracy.
Effect of Environmental Conditions on PRNU

Photo Response Non-Uniformity (PRNU) has been used reliably in the field of digital forensics to identify the camera for multiple applications. Given its importance, we study how the different environmental conditions affect this unique camera property in this paper. We collected 18 different cameras and created a dataset by clicking photos of 10 different objects in the varied environmental conditions. To be specific, we clicked photos of objects in the sun, putting water droplets on the camera lens, placing objects inside water and, putting dust on the camera lens, apart from clicking the normal images of the objects in a closed room. To compute the PRNU of each of these 18 cameras, we clicked nearly 30 to 50 images of the plain surfaces. We then analyzed the behavior of these cameras, considering the computed PRNU as the baseline. We used the Peak to Correlation Energy (PCE) to evaluate a match for the camera. Here, we present the experimental results and the possible causes of failure for the PRNU for the specific cameras in varied environmental conditions.