Reviewerly/exHarmony huggingface dataset:
An Measurement Method of Oblique Wedge Rubbing Surface Abrasion Based on Point Cloud

The detection of oblique wedge is a crucial task in the detection and repair of railway freight car bogies, which involves multiple inspection items. Among them, the wear degree of rubbing surface directly affects the damping effect and stability of the train, which is a very important inspection item. the exiting method is the manual measurement that uses the non-standard measuring tools and visual inspection. which cannot achieve the ever-increasing measurement efficientcy and accuracy of automate maintenance. In order to solve this problem, the measurement method and algorithm based on point cloud are researched to measure the wear of the rubbing surface. The test results shows that the method is superior to the existing manual measurement method in terms of accuracy and efficiency, and provides important technical support for the automatic maintenance and upgrading of the oblique wedge.
Using Systematic Clustering to Improve Innovation and Enterprise Curriculum Keyword Selection in Search Engine Optimization

Clustering is a typical unsupervised learning algorithm, which does not need to label the results. Try to find and summarize the specific pattern of a certain group, and divide the information to be classified into multiple different types according to their common characteristics. Innovation and enterprise course platform as an internet course platform, improving search engine ranking is very important for platform operation. The project incubation stage of innovation and enterprise course will be publicized on the platform in the form of crowdfunding, so as to get the attention of investors. Based on the comprehensive index evaluation method based on search engine optimization method, this paper puts forward an improvement scheme. Cluster analysis algorithm is added to the traditional method. This method establishes a perfect keyword optimization strategy management mechanism.
Answer Evaluation of Short Descriptive Questions

Reforms in the educational system emphasize more on continuous assessment. The descriptive examination test paper when compared to objective test paper acts as a better aid in continuous assessment for testing the progress of a student under various cognitive levels at different stages of learning. Unfortunately, assessment of descriptive answers is found to be tedious and time-consuming by instructors due to the increase in number of examinations in continuous assessment system. In this chapter, an attempt has been made to address the problem of automatic evaluation of descriptive answer using vector-based similarity matrix with order-based word-to-word syntactic similarity measure. Word order similarity measure remains as one of the best measures to find the similarity between sequential words in sentences and is increasing its popularity due to its simple interpretation and easy computation.
A Peer-Assessment Mobile Kung Fu Education Approach to Improving Students' Affective Performances

Peer-assessment and video comment-sharing are effective learning strategies for students to receive feedback on their learning. Researchers have emphasized the need for well-designed peer involvement in order to improve students' abilities in the cognitive and affective domains. Although student perceptions of peer-assessment have been studied extensively in higher education, few studies have focused on the effects of the peer-assessment strategy on students' performance from the affective perspective, especially in Physical Education courses. Therefore, in this study, a peer-assessment mobile physical education approach is proposed for developing a mobile learning system for a Kung Fu Tai-Chi physical education course. To evaluate the effectiveness of the proposed approach, an experiment was conducted by assigning 42 college students to participate in this learning activity. The experimental results show that the proposed approach not only promoted the students' learning interest and motivation, but also improved their learning self-efficacy and socialization.
The Thirties

As expressed in a famous Danish proverb, “making predictions is difficult, especially about the future.” Nonetheless, the preceding 28 chapters have put us in a position to make some predictions about the future of nano chips beyond the horizon of 2030. In this final chapter, we extrapolate upon the key points presented by our authors and speculate about the most significant trends and asymptotes that we expect to pass the test of time.
Design of a locally interconnected modular neural network

In order to design a model that is similar to the brain-like neural network while simultaneously enhance the learning performance of neural network, we propose a locally interconnected modular neural network (LI-MNN) model by adding inhibitory connections between the hidden nodes of different subnetworks. Firstly, to be more approximate to the pattern of brain functional division, the LI-MNN applies the Entropy Weighting k-means algorithm to partition all the features into several feature subsets. Secondly, each subset uses a BP neural network to learn and the excitatory hidden nodes in different subnetwork are connected with each other. The parameters in all subnetworks are learned by the improved Levenberg-Marquardt algorithm. Finally, the proposed model is tested on several benchmark datasets and a practical dataset in sewage treatment process, and the experimental results show that LI-MNN possesses superior generalization ability when compared with other MNN models.
Agent-Based Software Engineering, Paradigm Shift, or Research Program Evolution

Information systems are deeply linked to human activities. Unfortunately, development methodologies have been traditionally inspired by programming concepts and not by organizational and human ones. This leads to ontological and semantic gaps between the systems and their environments. The adoption of agent orientation and multi-agent systems (MAS) helps to reduce these gaps by offering modeling tools based on organizational concepts (actors, agents, goals, objectives, responsibilities, social dependencies, etc.) as fundamentals to conceive systems through all the development process. Moreover, software development is becoming increasingly complex. Stakeholders' expectations are growing higher while the development agendas have to be as short as possible. Project managers, business analysts, and software developers need adequate processes and models to specify the organizational context, capture requirements, and build efficient and flexible systems.
A Study on Performance of E-Commerce Web Applications

The growth of World Wide Web and technologies has made business functions to be executed fast and easier. E-commerce has provided a cost efficient and effective way of doing business. In this paper the importance of e-commerce web applications and how Internet of Things is related to e-commerce is well discussed. In the end-user perspective, the performance of e-commerce application is mainly connected to the web application design and services provided in the e-commerce website. A grading system is used to evaluate the performance of each e-commerce website.
Interface Design

User interface (UI) design is the process of making interfaces in software or computerized devices with a focus on looks or style. Designers aim to create designs users will find easy to use and pleasurable. IU design typically refers to graphical user interfaces but also includes others, such as voice-controlled ones. In this chapter, the user interface design and the grounded learning theories are discussed. Next, the interaction styles and the types of interactions are discussed. The usability benchmark and the usability evaluation instruments are also discussed in this chapter.
Secure Homomorphic Evaluation of Discrete Cosine Transform with High Precision

Signal Processing in the Encrypted Domain (SPED) has received considerable attention as it aims at privacy-preserving solutions for various applications. Discrete cosine transform (DCT) is a popular signal transform widely used in signal processing. It has many applications in speech processing, still picture coding, image and video transformation, compression coding, and so on. In this paper, we mainly study how to implement DCT in the encryption domain with high precision. We propose a new scheme to implement encrypted domain DCT. This scheme encodes a complex number as a unit root polynomial in the evaluation, and realizes the high precision representation of complex numbers. With this representation, this scheme can also realize the high precision representation of decimals. To improve the computational efficiency, we also propose a fast implementation of DCT in the encryption domain, which can significantly improve the DCT speed for large-scale matrices. We conducted experiments to verify the effectiveness and efficiency. When the matrix size is small, our original method has the advantages of both high accuracy and fast speed. When the matrix size is large, the fast implementation outperforms the original method.
Integration Between Knowledge Management and Total Quality Management in Jordanian Universities: Empirical Study

Knowledge management is important and necessary for the survival of an organisation and its superiority. It can be integrated into the philosophy of total quality management to play a role in the development of the basis of performance of modern organisations. It can be strengthened to achieve its strategic objectives. The total quality management philosophy seeks to achieve customer satisfaction through the commitment of the leadership of an organisation and its workers by a process of continuous improvement of the quality of performance in various aspects of an organisation. This study aims to identify the integration between knowledge management and total quality management, when applied to public Jordanian universities as a sample for the study, and to follow the descriptive analytical method research style. The online questionnaire responses were statistically analysed. The study found the presence of integrity and a strong correlation between knowledge management and total quality management.
Mathematical Analysis of Algorithms: Part II

The perspectives of analysing algorithms we have given so far have been mainly following the mainstream literature on optimization, numerical analysis and operations research. Algorithms can also be analysed from other perspectives from other disciplines such as swarm intelligence, signal and image processing, machine learning, control theory and Bayesian framework.
A new ball detection strategy for enhancing the performance of ball bees based on fuzzy inference engine

Sports video analysis has received much attention as it turned to be a hot research area in the field of image processing. This motivation offers opportunities that develop fascinating applications supported by analysis of different sports, especially soccer. Ball identification, in soccer images, is an essential task not only for goal-scoring but also for performance evaluation. However, ball detection suffers from several hurdles such as occlusions, fast-moving objects, shadows, poor lighting, color contrast, and other static background objects. Although several ball detection techniques have been introduced such as Frame Difference, Mixture of Gaussian (MoG), Optical Flow, and so forth; ball detection in soccer games is still an open research area. In this paper, a new Fuzzy Based Ball Detection (FB2D) strategy is proposed for identifying the ball through a set of image sequences extracted from a soccer match video. FB2D can accurately identify the ball even if it is attached to the white lines drawn on the playground or partially occluded behind players. FB2D is compared to recent ball detection techniques. Experimental results show that FB2D outperforms recent detection techniques as it introduces both the highest level of detection accuracy in the testing stage and the lowest possible error.
Informative Path Planning for AUV-based Underwater Terrain Exploration with a POMDP

Autonomous underwater vehicles (AUVs) in underwater terrain exploration applications represent a topic area, and the interesting problem is planning paths to maximize the vehicle information gathered and combining this information to build a complete map. The Gaussian process (GP) is utilized as a basic environment model and updated using the Bayesian data fusion technique with sensor information. A path planning algorithm, which formulates the terrain exploration problem as the finite-horizon partially observable Markov decision process (POMDP), is proposed to overcome the limitation of the planner converge to locally suboptimal solutions. In addition, a Monte Carlo Tree Search based on the motion primitives tree (MPT-MCTS) solver is developed to solve this POMDP. The effectiveness of the proposed method is explored in the simulation experiment, and its potential is demonstrated by comparing it with other optimization algorithms.
Artificial Minds with Consciousness and Common sense Aspects

The research work presented in this article investigates and explains the conceptual mechanisms of consciousness and common-sense thinking of animates. These mechanisms are computationally simulated on artificial agents as strategic rules to analyze and compare the performance of agents in critical and dynamic environments. Awareness and attention to specific parameters that affect the performance of agents specify the consciousness level in agents. Common sense is a set of beliefs that are accepted to be true among a group of agents that are engaged in a common purpose, with or without self-experience. The common sense agents are a kind of conscious agents that are given with few common sense assumptions. The so-created environment has attackers with dependency on agents in the survival-food chain. These attackers create a threat mental state in agents that can affect their conscious and common sense behaviors. The agents are built with a multi-layer cognitive architecture COCOCA (Consciousness and Common sense Cognitive Architecture) with five columns and six layers of cognitive processing of each precept of an agent. The conscious agents self-learn strategies for threat management and energy level maintenance. Experimentation conducted in this research work demonstrates animate-level intelligence in their problem-solving capabilities, decision making and reasoning in critical situations.
Determiners, Bare Singulars, Plurals: A Portable Tutor for Sentence Grammar

Abstract: This paper is based on the assumption that a portable tutor, as a practice-based tool, can offer students ample opportunities to improve their sentence grammar. By focusing on one specific grammar issue at a time, it presents certain sentence patterns that, through repeated practice, can eventually correct that particular grammar issue, in this case, that of determiners, bare singulars, and plurals. Significantly, his study has specific implications for Assumption University students and for Thai students in general, in that it explains why people who grow up speaking a language where nouns do not have determiners will have difficulty when learning a language that has them, for instance English. The paper begins by presenting a classification of determiners followed by a detailed description of one specific type of determiner: the bare singular count noun. The study continues with the proposed research methodology consisting of the Portable Tutor development, and the Experiment’s three main components, pre-testing, “treatment” and post-testing of the participating group of students. The paper concludes with data collection and analysis, and conclusions.
Single Sea Surface Image Dehazing via Multi-scale Concatenated Attention Network

Abstract Haze degrades obscures and content information of sea surface images, which can negatively impact the navigation safety of the intelligent ship in real-time systems. Therefore, it is imperative to develop algorithms that effectively remove haze and make the intelligent ship have higher environmental adaptability. In this paper, we propose a novel Multi-scale Concatenated Attention Network (MCA-Net) to address this problem. Specifically, we use the concatenation operation to connect multi-scale residual blocks (MRB), while introducing the channel attention mechanism for guiding the hazy region feature extracting. Extensive experiments on both synthetic datasets and real sea surface images, which demonstrate our proposed method outperforms are better than other recent dehazing approaches.
ArchaeoGRID Science Gateways for Easy Access to Distributed Computing Infrastructure for Large Data Storage and Analysis in Archaeology and History

This article describes how archaeological and historical research grew as a multidisciplinary and interdisciplinary activity due to availability of larger amount of data within the reconstruction of global historical and archaeological contexts at a global spatio-temporal scale. The increased information, also integrated with data from the Earth Sciences, has had an effect on the exponential increase of complex sets of data and of refined methods of analysis. For such purposes, this article discusses the ArchaeoGRID Science Gateway paradigm for accessing ArchaeoGRID Cyberinfrastructure (CI), a Distributed Computing Infrastructure (DCI), that can supply storage and computing resources for managing and analyzing large amount of archaeological and historical data. In fact, ArchaeoGRID Science Gateway is emerging as high-level web environment that makes easier the access, in a transparent way, to DCI, as local high-performance computing, Grids and Clouds, from no specialized Virtual Research Communities (VRC) of archaeologists and historians.
Use Cases

After looking into the details of the design challenges of an embedded system, the next challenge is to capture detailed requirements of the system under development (SUD). The majority of the customers do not know how the proposed system looks like or able to make detailed requirements. Even the system designer cannot capture customer’s requirements without having detailed interaction with the customers. Most of the projects fail because user’s requirements are not captured properly. Certain customers can provide detailed technical requirements themselves, in which case, designers can get into the implementation phase. This chapter discusses a structured methodology of capturing use cases which becomes the nucleus to frame requirements. This topic is part of structured analysis and structured design (SASD) discussed in software engineering, which is very essential in developing embedded systems also. A use case is an agreement or contract between the stakeholders in the entire system. It states a sequence of actions and interactions between the users and the systems to achieve the desired goal. It describes how the system behaves and reacts to a request from one of the stakeholders. The actor who initiates the request is the primary actor. Use cases are not requirements. They do not state the required performance in qualitative or quantitative terms, nor the user interface or internal system design. There are several benefits to starting the project by framing structured use cases. If they are framed up to a granular level, the system’s complexity is exposed. The system requirements can be extracted from these use cases systematically. Premature designs can be avoided. We focus on what the system should do rather than how it should do it. This chapter covers structured methodology to develop use cases and the best practices adopted in the industry.
Yukuben

Abstract Yukuben is a Benue-Congo (Niger-Congo phylum) language spoken by some 20,000 persons along the foot of the mountains separating Cameroon and Nigeria. The vowel system is based on [ATR] harmony, and the consonant inventory is complex and fairly symmetric. Nouns are arranged in classes with an agreement system. In the verbal structure aspect and mood are more relevant than tense, whereby the aspect system is considered under two main broad sub-systems, precisely perfective and imperfective. The basic word order is SVO. The chapter gives a neat overview of the phonological system, of word categories, derivational and inflectional processes, and syntactic patterns such as subordination and coordination.
A Novel Architecture for Learner-Centric Curriculum Sequencing in Adaptive Intelligent Tutoring System

An ideal face-to-face tutor learner interaction aims to offer learning to the learner in a manner that best suits an individual learner's learning level and learning style. This ability of differentiated instruction has been built in Seis-Tutor Intelligent Tutoring system, developed to offer subject matter knowledge of ‘Seismic Data Interpretation,' a field of geo-physics. The detailed architecture of learner-centric curriculum sequencing module, built to this effect, with its components, sub-components, their interconnected functioning, to generate exclusive learning path, have been described. An algorithm for learner-centric curriculum sequencing, a mathematical model and proposed implementation using a case study has been elaborated.
A Decision Making Method Based on Society of Mind Theory in Multi-Player Imperfect Information Games

The authors are concerned with a card game called Daihinmin (Extreme Needy), which is a multi-player imperfect information game. Using Marvin Minsky's “Society of Mind” theory, they attempt to model the workings of the minds of game players. The UEC Computer Daihinmin Competitions (UECda) have been held at the University of Electro-Communications since 2006, to bring together competitive client programs that correspond to players of Daihinmin, and contest their strengths. In this paper, the authors extract the behavior of client programs from actual competition records of the computer Daihinmin, and propose a method of building a system that determines the parameters of Daihinmin agencies by machine learning.
Introduction to Genetic Algorithms in Search and Optimization

This chapter is all about introducing genetic algorithms in the search process, which are based on the theory of natural selection, genetics, and survival of fittest. By detailed understanding of the algorithm, one would be able to apply it in your respective field for optimization. At the end of this chapter, the reader will have acquired basic theory and working of these algorithms. Since genetic algorithms are used in diverse fields, the tone and language of this chapter is kept simple and casual for better understanding. Genetic algorithms in this chapter are applied through a hand calculation example. Genetic algorithms are basically mathematical calculations based on Darwin's theory of survival of fittest. This chapter gives a detailed understanding of the theory and working of genetic algorithms based on hand calculation examples. Comparison of genetic algorithms with other search procedures is also done.
A new image encryption scheme based on 3D Sine-adjusted-Logistic map and DNA coding

The chaos theory is a widely used technology for image encryption as its significant properties such as unpredictability and initial state sensitivity. In this paper, we introduce a new 3D Sine adjusted Logistic hyperchaotic system (3D-SALM), which is derived from the Logistic and Sine maps. Performance evaluation shows that it has good performance in ergodicity and orbit uncertainty. To investigate its applications, we propose a new random DNA coding scheme, the random coding rules are according to 3D-SALM sequences. This paper further introduces a new image encryption scheme (SALM-IES). In order to enhance the confusion of cipher-image, the principle of random diffusion and random confusion are fulfilled. Simulation results show that the proposed scheme can effectively resist various typical attacks, especially in the resistance to differential and cropping attacks.