Reviewerly/exHarmony huggingface dataset:
Introduction

The use of algorithms based on nature has become very common in evolutionary computation and metaheuristics. In this book we propose to use one of these algorithms, in particular the Differential Evolution (DE) integrating fuzzy logic to dynamically adapt some of its parameters during execution.
Research on Student Curriculum Selection Recommendation System Based on Graph Convolutional Network

In recent years, the recommendation systems based on knowledge graph have been widely used by researchers, however, existing systems are mostly applied in people’s daily life. This paper proposes a new model of student curriculum selection recommendation system based on graph convolutional network, aiming at providing personalized curriculum selection recommendation for students. In this model, the graph convolution network is used to propagate the embedding from the neighbor of nodes to update the new representation of the nodes, then aggregate the representation of students and curriculums, and output the predicted matching score, so as to realize the personalized curriculum selection recommendation of students.
QPLAN

As business competition increases, there is pressure on software development projects to become more productive and efficient. Previous research has shown that quality planning is a key factor in enhancing project performance. Thus, this article reports on the successful development and implementation of a tool (QPLAN) that enhances software development project performance by evaluating the planning quality of any type of software project and introducing best planning practices (such as references from historical data) that suggest how to manage projects in an appropriate manner, including encompassing lessons learned and involving the customer in the development process. This is applied research aimed at solving a real problem; thus, Design Science Research was adopted as the research methodology and the design science research process (DSRP) model was selected to conduct it. This artifact was designed for the project management literature, and implemented and validated in 11 organizations in five countries.
Image Indexing

This chapter deals with image indexingImage indexing , which is a technique to organize large numbers of images in the database into a data structure so that images can be properly retrieved. The chapter first demonstrates two numeric indexing methods: list indexingList indexing and tree indexingTree indexing . In the next, a more powerful inverted fileInverted file indexing method is introduced, beginning with textual document indexingTextual document indexing . The description then focuses on image indexingImage indexing using inverted fileInverted file , specifically, how varieties of term weights are determined in image indexingImage indexing .
Unlocking the Unlimited Potentials of Koha OSS/ILS for Library House-Keeping Functions

Drawing praxis from Bowen University, Nigeria and other libraries worldwide, the chapter unveils the limitless capabilities of Koha ILS to successfully manage core library house-keeping functions—cataloging, acquisitions, circulation control, patrons' management, OPAC, serials, and report generation—in one seamless whole. Web-based features like its flexibility, adaptability, interoperability, MARC, Z39.50, patrons' ability for online logging in, registration, renewal, and many more were revealed. Also, reasons for its global adoptability, benefits, likely challenges, and solutions from practitioners were also highlighted. The chapter concludes that despite the puny but eventually surmounted challenges, Koha holds unlimited potential for libraries of any shape/size by just garnering from the experiences of subsisting users of the software globally.
CYBER CRIME

Cybercrime is advancing at a shocking pace, following indistinguishable dynamic from the inescapable entrance of PC innovation and correspondence into all kinds of different backgrounds. While society is concocting and developing, in the meantime, lawbreakers are sending an amazing flexibility keeping in mind the end goal to get the best advantage from it. to abstain from giving cybercriminals the activity, it is vital for those associated with the battle against cybercrime to endeavor to foresee subjective and quantitative changes in its hidden components so they can modify their strategies fittingly.
Semantic Indecision

Linguistic vagueness results from aggregating many judgments into one. Thus, vagueness is a type of decision problem, and the sorites paradox—most famous of vagueness phenomena—is a paradox of collective decision making. The sorites paradox reflects this judgement-aggregating character of vagueness. In the case of vague predicates like healthy, the “judgments” are the rankings of contextually salient entities along some scale (like “health”) and the “dimensions” are relevant criteria (like blood pressure and heart rate). The sorites paradox is paradoxical because it tracks changes along one dimension (“a person with slightly higher blood pressure than a healthy person is healthy”) while ignoring others. The aggregation of many judgments into one is also a feature of Condorcet’s paradox, a paradox of collective decision making. If three equal blocks of voters have certain preferences among the available candidates, then the judgment-aggregating procedure—a vote—fails to deliver an outcome. Condorcet’s paradox and the sorites paradox are two sides of the same coin. Both paradoxes arise from the decision problems inherent in aggregating many judgments along many dimensions. And in both cases, plausible constraints on the aggregation process—well developed in the theory of social choice—lead to paradox.
Design of Cancer Detection System Based on CNN Model and Virtual Reality with NLP Voice Output

Nowadays, online medical consultation has become very popular. However, online consultation can only solve some minor diseases such as colds and coughs, but the detection of cancers needs to be improved. This project implements the design of a cancer detection system based on the CNN model and virtual reality. This project uses the CNN and regression models for training a mature network to detect prostate cancer, lung cancer and skin cancer. The patient who comes to check uploads the corresponding picture or blood test report to determine whether the patient has the corresponding condition. Then use the NLP model to voice output diagnosis results. As a result, the voice broadcasts whether the patient has cancer, making the humancomputer interface more friendly. After long enough training time, two CNN models and one regression model showed high scores. The experiment results to detect whether the patient has the corresponding cancer are efficient, owing to the accuracy of the test of the three models is above 95%. And when inputting the patient’s lung CT and skin details, the location of tuberculosis can be found quite accurately and whether the patient has skin cancer. Combined with virtual reality technology, it depicts models including wards, CT rooms, diagnosis rooms and supermarkets, successfully creating a friendly online hospital.
Exploration on the Application of Circuit Board Design Course Combined with Internet Technology in Vocational Colleges

Internet technology is also changing with each passing day, and the curriculum of circuit board design still stays in the monotonous and boring educational concept. In view of the current situation that the curriculum theory of circuit board design is strong, monotonous and boring, students’ practical ability is poor, and even tired of learning, combined with the application of Internet technology, the "Curriculum Ideology and politics" is introduced. After front-line teachers go to the enterprise for field research, enterprise engineers and personnel managers are hired to participate in the formulation of talent training scheme. This paper puts forward a circuit board design course development idea in vocational colleges, which combines the application of Internet technology and takes the professional standard as the guidance. The teaching goal is clear, the difficulty is moderate, the curriculum is vivid and the participation number of students is high. The course development focuses on arousing students’ interest, improving students’ practical ability and improving the curriculum theory of circuit board design through the application of Internet technology. Be aimed at the monotonous and boring current situation, combined with Internet technology and comprehensively practice the "curriculum thought and politics", students have high ideological level, deep knowledge and strong ability. Curriculum planning allows students to learn in hands-on practice, practice in learning, teaching in fun, and achieve remarkable teaching results.
Domain Knowledge Embedding Regularization Neural Networks for Workload Prediction and Analysis in Cloud Computing

Online services are now commonly deployed via cloud computing based on Infrastructure as a Service (IaaS) to Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS). However, workload is not constant over time, so guaranteeing the quality of service (QoS) and resource cost-effectiveness, which is determined by on-demand workload resource requirements, is a challenging issue. In this article, the authors propose a neural network-based-method termed domain knowledge embedding regularization neural networks (DKRNN) for large-scale workload prediction. Based on analyzing the statistical properties of a real large-scale workload, domain knowledge, which provides extended information about workload changes, is embedded into artificial neural networks (ANN) for linear regression to improve prediction accuracy. Furthermore, the regularization with noisy is combined to improve the generalization ability of artificial neural networks. The experiments demonstrate that the model can achieve more accuracy of workload prediction, provide more adaptive resource for higher resource cost effectiveness and have less impact on the QoS.
Introduction

The field of quantum information encompasses the study of the representation, storing, processing and accessing of information by quantum mechanical systems. The field grew from the investigations of the physical limits to computation initiated by Bennett and Landauer. One of the first questions studied was whether quantum mechanics imposes any limits on what a computer can do, and it was shown by Feynman that it does not. Earlier work by Paul Benioff had explored the possibilities of quantum Turing machines. Shortly after Feynman’s work, David Deutsch realized that not only is quantum mechanics not a problem for computation, it can also be an advantage. The major breakthrough in the field was Peter Shor’s factoring algorithm, which showed that a quantum computer can find the prime factors of integers in a time that scales as a polynomial of the size (number of digits) of the integer
Underwater Image Enhancement Algorithm Based on Improved Pyramid Fusion Method

Aiming at the problems of color distortion, low visibility and loss of details in underwater image, this paper proposes an underwater image enhancement algorithm based on improved pyramid fusion method. The proposed method combines the advantages of white-balancing and contrast limit adaptive histogram equalization. Then, the Laplacian contrast weight, local contrast weight, exposure weight and saliency weight are combined in different ways. Finally, the enhanced image is obtained by improved pyramid fusion. The experimental results show that the enhanced images of the proposed approach outperform the contrast limit adaptive histogram equalization, dark channel prior and multiscale retinex with color restoration. It can effectively reduce color distortion, enhance contrast, highlight details, and make underwater images have better visual effect.
Number of Epochs of Each Model and Hyperband’s Classification Performance

Computer-aided diagnosis (CAD) systems based on deep learning methods, such as the convolutional neural network (CNN), enable early breast cancer detection, diagnosis, and treatment. However, many studies based on CNNs usually train models by manually selecting various parameters, which is time-consuming and difficult to find the best solution. In this paper, we conceptualized a new, improved method to resolve these limitations. More specifically, we proposed a customized Hyperband hyperparameter tuner with increased epochs for hyperparameter tuning of CNNs for breast cancer whole mount slide image patch classification. Experimental results indicated that our Hyperband with increased epochs has better performance than Bayesian optimization and the original Hyperband tuner in terms of accuracy on the dataset called "Breast Histopathology Images" when computing time is sufficient and can resolve the performance stability issue of the original Hyperband tuner.
Fast median filters using separable sorting networks

Median filters are a widely-used tool in graphics, imaging, machine learning, visual effects, and even audio processing. Currently, very-small-support median filters are performed using sorting networks, and large-support median filters are handled by O(1) histogram-based methods. However, the constant factor on these O(1) algorithms is large, and they scale poorly to data types above 8-bit integers. On the other hand, good sorting networks have not been described above the 7 X 7 case, leaving us with no fast way to compute integer median filters of modest size, and no fast way to compute floating point median filters for any size above 7 X 7.
Book Review: Radical Imagine-Nation: Public Pedagogy &amp; Praxis

This paper presents a new necessary and sufficient condition for testing the strong delay-independent stability of linear systems subject to a single delay. The proposed method follows from the use of matrix polynomials constraints and the Kalman–Yakubovich–Popov lemma. The resulting condition can be checked exactly by solving a feasibility problem in terms of a linear matrix inequality (LMI). Simple numerical examples are given to show the effectiveness of the proposed method.
A Text Clustering Method Based On The Improved Heuristic Three-parent Genetic Algorithm

In the text clustering, the traditional clustering algorithm is easy to fall into the local optimal for exploring the clustering center, which will affect the results of text clustering. This paper proposes a text clustering method based on the improved heuristic three-parent genetic algorithm. In this paper, the heuristic three-parent genetic algorithm is improved. Furthermore, by enhancing the crossover strategy and introducing the unequal crossover, the genetic algorithm’s convergence speed and global search ability are improved. In text clustering, three-parent with the improved heuristic genetic algorithm to find the optimal clustering center. Through the change of fitness function, the clustering center is more suitable for text clustering results. Using the clustering center guide text embedded to lower-dimensional coding of high-dimensional text, finally use the Deep Embedded Clustering (DEC) to improve the effect of clustering. The clustering results are evaluated in terms of Accuracy and Mutual Information. The experimental results show that the algorithm performs well in selecting clustering centers and clustering results.
Tension and Materiality in a Textile System; A Puppetry Perspective

The paper seeks to develop complementary strands of research and development through a puppetry perspective for designing with postdigital textile and soft material systems. It draws from the puppetry approach to designing and performing with different materialities. The paper analyses how the tensions present in a puppet system provoke uncanny relationships and use the concepts of “double vision” and “breathed stillness” to give a puppetry perspective on textiles in “textasis”. From this point of view, it reviews alternative design methodologies already developed by material researchers to produce new textile materials and begins to trace a new framework for designers engaging with postdigital materials. This paper proposes a foundation to develop new material qualities within textiles eliciting puppet making as a design method for bringing forth a world of interconnected and ambiguous agencies in a textile system in order to generate new forms of nonverbal communication with our environment.
A Privacy-preserving Location Recommendation Scheme without Trustworthy Entity

The widespread application of location recommendation service brings convenience and social fun to users, but the misuse of user check-in data and location recommendation results can bring serious privacy leakage, because these check-in data and location recommendation results imply private information of users' interests and behavioral hobbies. To address the check-in privacy and recommendation result privacy leakage issues in existing location recommendation schemes, we first propose a location recommendation algorithm based on the similarity of user historical check-ins, and then we devise three location recommendation protocols on ciphertext to protect the privacy of user check-in data and recommendation results based on the homomorphic property of Paillier cryptosystem without assuming any trustworthy entity. These protocols calculate the ciphertexts of recommendation results at the location recommendation server(LSP) without learning any explicit check-in privacy of the user, and it also guarantees that the decryption server(DS) can only implement the decryption operations as requested by the user without being aware of any decrypted recommendation results, so that the privacy of user check-in data and recommendation results are both preserved solidly in our protocols. Although the above recommendation process is carried out without any user's explicit data, it is still effective enough to guarantee the accuracy of recommendation results. Finally, we prove the security, efficiency and accuracy of our scheme by extensive performance analysis.
Virtual Soar-Agent Implementations

This chapter provides a brief overview of those virtual agent implementations directly inspired by the cognitive architecture: Soar. This chapter will take a qualitative approach to discussing examples of virtual Soar-agents. Finally, this chapter will speculate on the future of Soar virtual characters. The goals of this chapter are sixfold. The first goal is to explain why cognitive architectures are becoming increasingly important to virtual agent design(s). The second goal is to convey why this chapter focuses exclusively on virtual agents that utilize the Soar architecture. The third goal is to explore some of Soar's technical details. The fourth goal is to showcase a few diverse examples where Soar is beginning to have a design impact on virtual agents. The fifth goal addresses Soar's limitations – when applied to agent design in virtual environments. The final goal speculates on ways Soar can be expanded for virtual agent design(s) in the future.
Skill Teaching

Many strategies exist for teaching clinical skills. One in particular is used widely (in fact, almost dogmatically) in teaching resuscitation skills in Advanced Life Support and Paediatric Advanced Life Support courses. This approach is advocated internationally despite lacking clear evidence that it leads to better skill acquisition and retention than traditional approaches. In this chapter, skill teaching templates are critiqued, and the importance of authentic learning and the interdependence of cognitive and motor learning are reinforced. The nature of skill performance as an adaptive concept in response to the patient’s needs is stressed in this chapter, and therefore a similarly adaptive andragogy is required. This ensures that solid foundations in principle and understanding are built in order to equip the learner to manage future practice variability.
Fundamentals of Quantum Computation

This chapter briefly describes the basic concepts and principles of quantum computing. Firstly, the concepts of qubit, quantum coherence, quantum decoherence, quantum entanglement, quantum density operators, linear operators, inner products, outer products, tensor products, Hermite operators, and unitary operators are described. Then, the four basic assumptions of quantum mechanics are introduced, focusing on the measurement assumptions of quantum mechanics. Finally, the definition of commonly used quantum logic gates is given including single qubit gates, double qubit gates, and multiple qubit gates. These contents provide the necessary theoretical basis for subsequent chapters.
PERSONAL LEARNING TECHNOLOGIES

In the learning process, in accordance with the requirements of pedagogical technologies, learning goals are achieved. In a period of accelerated scientific and technological progress, the effectiveness of teaching largely depends on the role of the student in the educational process, the attitude of the teacher to him. Two types of learning technology can be distinguished here: authoritarian and personal.
Improved Virtual Landmark Approximation for Belief-Space Planning

A belief-space planning problem for GNSS-denied areas is studied where the location and number of landmarks available are unknown when performing the planning. To be able to plan an informative path in this situation, an algorithm using virtual landmarks to position the platform during the planning phase is studied. The virtual landmarks are selected to capture the expected information available in different regions of the map, based on the beforehand known landmark density. The main contribution of this work is a better approximation of the obtained information from the virtual landmarks and a theoretical study of the properties of the approximation. Furthermore, the proposed approximation, in itself and its use in a path planner, is investigated with successful results.
Translation Invariance

As discussed in Sect. 1.2.2, the topos $$\mathsf {Shv}(S_{\mathbb {I\hspace {1.1pt} R}})$$ of sheaves on the interval domain is slightly unsatisfactory as a model of behaviors. For example, to serve as a compositional model of dynamical systems, we do not want the set of possible behaviors in some behavior type to depend on any global time. In this chapter, we define a topos $$\mathcal {B}$$ Topos of behavior types of “translation-invariant behavior types” Behavior types translation-invariant by defining a translation-invariant version of the interval domain and a corresponding site, denoted $$\mathbb {I\hspace {1.1pt} R}_{/\rhd }$$ and $$S_{\mathbb {I\hspace {1.1pt} R}/\rhd }$$ , respectively, and letting $$\mathcal {B}\mathrel{\mathop:}= \mathsf {Shv}(S_{\mathbb {I\hspace {1.1pt} R}/\rhd })$$ .
Design of Intelligent Teaching Audio System

In recent years, the construction of intelligent teaching system is the main direction of upgrade and transformation of teaching system in China. Various new technologies emerge one after another, and a variety of comprehensive transformation programs are showing a trend of blossoming. This paper will combine Audio over IP, Internet of Things and other technologies, and focus on the design of audio system in intelligent teaching system. By analyzing the basic structure of the design scheme of intelligent teaching audio system and the problems and solutions of centralized monitoring, bidirectional signal transmission and remote transmission that the intelligent teaching audio system is facing, the feasibility and necessity of the existence of intelligent teaching audio system are explained. By analyzing the extensibility of this system, the importance of high-quality intelligent teaching audio system combined with Internet of Things technology to information collection, cloud technology application and teaching management is discussed.