Reviewerly/exHarmony huggingface dataset:
Embedded Image Recognition System for Lightweight Convolutional Neural Networks

In this paper, we design and implement an embedded image recognition system based on STM32 for the problem of limited storage space of embedded systems to run convolutional neural networks efficiently, and for the loading of lightweight convolutional neural network and the hook-up requirement of the quadrotor. The system hardware adopts the idea of modular design to improve the compatibility of the system, and the system software adopts the training of handwritten image recognition based on convolutional neural network, lightweight processing of the convolutional neural network, and transplanting the trained network to the embedded system. Finally, the system can finish the recognition of handwritten images stably and efficiently. This system can provide a low-cost and highly integrated solution for such image processing systems. The lightweight target detection model CED-Det is designed by combining CED-Net and dense feature pyramid network, which firstly performs feature extraction by CED-Net, then performs feature fusion by stacking two layers of dense pyramid network, and finally, the fused feature maps are used for classification prediction and position prediction by two 3×3 convolutions, respectively. CED-Det is used in VOC and Experimental results on COCO datasets show that CED-Det is more suitable for embedded platforms in terms of accuracy, inference speed, and a total number of parameters compared with other target detection models.
A Recapitulation of Different Text Classification Algorithms

Text classification process has gained a lot of importance in recent years and is still one of the most popular topics of discussion because of the presence of a huge outsized range of electronic documents from diverse resources. The text categorization process assigns predefined classes to documents. It finds noteworthy similarities in large textual data were interesting, hidden, previously unknown and extremely useful patterns and information can be discovered. Text classification helps in analysis of large textual data. Text mining intends facilitating customers extract informations from resources, and deals with operations such as retrieving, classifying ,cluster formation, mining of data, processing of natural language and techniques of machine learning together to classificate unalike patterns. Inside the process of content arrangement, terms gauging strategies configuration fitting loads to the offered terms to improvise content grouping execution. This paper overviews content order, the procedure of content grouping, distinctive term gauging techniques and correlations between various characterization calculations.
Dual Attention-based Interest Network for Personalized Recommendation System

With the rapid development of information technology, a large amount of resources can be obtained quickly anytime and anywhere, but these resources bring the difficulties for users because of the information explosion. Recommendation systems are often designed to help users filter the resources. At present, it is difficult to capture the potential user preferences from rich information of implicit feedbacks. To solve this problem, we propose Dual Attention-based interest Network for Recommendation system(DANR). Firstly, we use the dual attention mechanism to connect the clicked item representation and implicit feedback representation to obtain the user overall preference. Specially, implicit feedback information is extended and it helps express the user's interest in the candidate. Next, we mine the relationships between users and items from item-level and behavior-level, to get multiple representations of the user-item relevance. Finally, the click-through rate is calculated through multiple layer perceptron(MLP) after concatenating. Extensive comparative experiments are conducted with the main-stream recommendation models on the real dataset. The results show that, compared with the existing models, our model has achieved further improvement.
Multidimensional Observation of Blockchain Security

Technologies such as distributed ledger and its utilization of blockchain have higher network security, promote the balance between security and efficiency, and new technical measures are being taken to enhance its security. However, blockchain technology and utilization are not secure. The security architecture of blockchain should be constructed from the concept of “zero-trust security”, and the security utilization of the blockchain should be highly valued from the network security strategy to promote international cooperation in blockchain security.
Fourth International Workshop on Experiences and Empirical Studies on Software Reuse (WEESR 2021)

In the Workshop on Experiences and Empirical Studies on Software Reuse (WEESR) researchers and practitioners discusses in-progress research regarding experiences and empirical studies applying reuse techniques in non-academic environments. The fourth edition of this workshop, the WEESR 2021, was co-located with the 25th International Systems and Software Product Line Conference (SPLC'21). There, attendants discussed a original paper and a journal-first paper presenting empirical studies regarding variability models for real cyber-physical products and the software product line practices in large companies.
Application of Intelligent Algorithm in Linear Algebra Teaching

In this paper, a new method for linear algebra teaching was proposed, which was to integrate machine learning algorithms into teaching. Through investigation and research, there’re two long-standing problems in the teaching of linear algebra: students didn’t know its usefulness or how to use it. However, machine learning algorithms contain rich linear algebra theory. Taking eigenface as an example, this paper introduced how to disassemble the algorithm and applied it to daily teaching.
Algorithmic Implementations

This chapter explains the sequence of algorithmic steps required for the calibration of the single-shot 3D movie camera as well as for the 3D evaluation. The usage of code segments or extensive mathematical explanations is largely avoided. The calibration of the 3D movie camera has not been discussed so far. Section 8.1 introduces a calibration procedure which is specifically tailored to the 3D movie camera. The basic steps are explained and the advantages over existing procedures are discussed.
Introduction

Over the last three decades physics has taken on an increasingly information-theoretic flavour. This has led to a quantum theory of information which promises computers with unprecedented power and unconditionally secure cryptography, and perhaps most importantly, has offered us a new perspective on quantum theory itself. The aim of this thesis is to use the large toolbox of quantum information theory to study problems whose solution requires both quantum mechanics and relativity, with the hope that these investigations may offer unexpected and intriguing results about possible features of quantum gravity. This thesis is broken into three distinct parts, each of which is briefly summarized in this chapter.
Multi-feature Fusion With Attention and Receptive Field for Camouflaged People Detection

Camouflaged object is usually visually similar to the surrounding environment. Although camouflaged object detection is more challenging than general object detection, camouflaged object detection has been used in medicine, biology and military, so the research on camouflaged object detection is also of great significance.Since the camouflage object can be regarded as the "salient object" in the camouflage image, this paper combines the characteristics of salient object detection and camouflage object detection, mainly from the three aspects of object edge information enhancement, channel attention mechanism and expansion of the receptive field. Inspired by the idea of U-Net, we design a new camouflage object detection network. Finally, we use the camouflage people data set, and carry out training and testing under the same conditions with other networks, and verify the effectiveness of the method by comparing the results.
A real time aggressive human behaviour detection system in cage environment across multiple cameras

The monitoring of activities in the enclosed cage environments to detect abnormalities such as aggressive behaviour, employing a real-time video analysis technology, has become an emerging and challenging problem. Such system should be able: 1) to track individuals; 2) to identify their action; 3) to keep a record of how often the aggressive behaviour happened, at the scene. On top of that, the system should be implemented in real-time, whereby, the following limitations should be taken into consideration: 1) viewing angle (fish-eye); 2) low resolution; 3) number of people; 4) low lighting (normal); 5) number of cameras. This paper proposes to develop a vision-based system that is able to monitor aggressive activities of individuals in an enclosed cage environment using multiple cameras considering the above-mentioned conditions. Experimental results show that the proposed system is easily realised and achieved impressive real-time performance, even on low end computers.
Towards Trusted, Transparent and Motivational Professional Education System Through Blockchain

The learning process has evolved with time. The primary change that technologies have brought into the learning process is more structure and activity based. It has become a necessity and a mandate as well to keep a track of details of educational activities so that it can be referred back to at any point in time. Moreover, it requires a secure protocol which is trustworthy, transparent, less vulnerable and requires near zero involvement of mediators. Blockchain technology has a tremendous potential to disrupt the education sector. Its implementation will help to maintain time-stamped record keeping that can be validated for all types of activities involved in the professional education system. This article proposes a blockchain-based model for professional education systems. The model not only ensures digital identity, verifiable records, but also motivates learning process by rewarding B-coins for learning activities. It inherits the security, robustness of underlying blockchain technology and eliminates the need for verification by an intermediate agency.
Conclusions and Future Research

Data miningData mining is an integrated process to deal with cleaning, integration, selection, transformationTransformation , extraction of data, evaluation of patternPatterns and knowledge acquisition management.
Existential Aspects of the Development E-Culture

This chapter is devoted to the study of a new information-age phenomenon: the electronic culture. The author introduces the philosophical analysis of electronic culture, its definition, characteristic features, and functions within the society. The purpose of the chapter is justification theory electronic culture as a special “third nature” generated by human creativity and information technology. The chapter described existential aspects of the formation of e-culture. E-culture gives human beings new ways to solve existential problems (death, desolation, not liberty, relations with strange ones, and ethical choice), forming in this regard new dependences and risks for person. First of all, internet-dependence refers to such risks. It enhances “existential vacuum,” axiological disorientation in real sphere; deformation of interpersonal communication essence with the virtualization of its sensual and emotional aspects; appearance of new freedom forms of personality ethical choice, generated by virtual interaction.
Usage of ICT Resources in Academic Libraries With Special Reference to Engineering Colleges

Academic libraries in India make use of ICT as tools to meet the information need of users who in this context are students and faculty staff. Academic libraries are established to support the objectives of their parent institutions which are to promote teaching, learning, and research. Therefore, academic libraries are expected to serve the students, lecturers, and other members of the academic community. To meet the information need of users, academic libraries provide various services such as user education (orientation/instruction services), inter-library loan/connection services, abstracting and indexing services, referral services, and circulation services. The finding of the respondents problems encountered while using ICT-based resources and services reveal the fact that, out of 732 respondents, 543 (74.18%) respondents stated too few computers with internet and 421 (57.51%) lack of subscription for more foreign journals for their main problems.
Exploring the Effects of Contingent Rewards on Employee Responsiveness and Affective Commitment

The leading attribute of ‘transactional-leadership’ is ‘contingent-rewards’ which is supposed to be generating positive outcomes from the employees’ performance. For example, the ‘employee-responsiveness’ is increased when employees are rewarded for their worthy performances. The robotic behaviors by leadership have apprehensions of uninvited effects like employees’ discouragement, on the other hand, commitment with work when rewards are attached only with physical and external behavior, efforts and outputs. The employees feel unrecognized; as human beings, it is obviously a critical objective of every single employee for seeking a good professional status. Data were collected from the employees, working in higher education institutions. The study statistically measured the contingent rewards links with employees’ responsiveness and affective commitment. The results support the assumptions extracted from theoretical framework. The findings suggest that leadership in higher institution needs to implement the best suitable blend of different rewards as per distinct requirements of job and as per efforts and knowledge of workforces.
Document-aware Information Extractor for Chinese Medical Dialogue

Electronic medical records (EMRs) are one of the methods to help doctors effectively manage and analyze patient medical records. These EMRs not only help doctors save a lot of time to analyze medical records, but also reduce the hospital's demand for doctors and reduce hospital expenditure costs. Therefore, we proposed the document-aware information extractor (DIE) to effectively extract the information about the patient's physical condition in the conversation between the doctor and the patient. In this paper, we proposed a encoder-decoder model to extract the medical items amongst the doctor-patient dialogue for further usage of EMRs generation. The experimental result shows that our model achieves better results compared to the baseline models, which indicates the model effectiveness.
AN INTEGERATED NAVIGATION SYSTEM FOR AUTONOMOUS MOBILE ROBOT IN DYNAMIC ENVIROMENTS

To enable an autonomous mobile robot to navigate safely in a dy- namic environment, the mobile robot must address four typical functional blocks of the navigation system including perception, localization, motion planning, and motor control. In this study, we present an integrated navigation system for the autonomous mobile robot in the dynamic environment by incorporating the techniques proposed in our previous studies, including object detection and tracking system, localization system and motion planning system, into a completed navigation system. In addition, we propose an extended timed elastic band (ETEB) technique for online trajectory planning, which allows the mobile robot to proactively avoid obstacles in the surrounding environment. We validate the effectiveness of the proposed model through a series of experiments in both simulated and real-world environments. The experimental results show that our proposed motion model is capable of driving the mobile robots to proactively avoid dynamic obstacles, providing safe navigation for the robots.
Introduction

Think about any day in your life. How many of our possessions contain, at least, one microchip that are made of semiconductors? Semiconductors are the enablers of our modern society, being silicon the most important of them. There are many things that can be done with Si chips. Unfortunately, detecting infrared rays, at least at room temperature, is not one of them. In this chapter, we explore the current infrared sensing technology and their limitations. Then, we introduce the concept of supersaturated materials, and how it could be a potential solution for getting faster, cheaper, and more environmentally friendly infrared detectors, based on Si, and operating at room-temperature.
Color Descriptor for Mobile Augmented Reality

Augmented Reality (AR) is the combination of real-world and virtual content where it allows users to interact with virtual objects in real-time. In order to achieve optimal performance in mobile AR applications, choosing a suitable tracking algorithm is an important issue as the smartphone has its own limited processing capabilities and memories when compared to the PC platform. Tracking in AR consists of four important components; detector, descriptor, matcher and pose estimator. The robustness of mobile AR application in illumination is an issue that has not been resolved. The descriptor is one of the important components as it will affect the overall performance of mobile AR applications. In order to create an efficient and robust mobile AR application, the descriptor must be efficient which means that it must be able to function in a short time and robust to changes in illumination. FREAK (Fast Retina Keypoint) has been proposed as the most appropriate descriptor for mobile AR applications based on previous research. FREAK can function in the shortest time and most robust to changes in scale and rotation. Although FREAK can function in the shortest time and robust to changes but the color information that will affect the illumination invariance of a descriptor had been ignored by FREAK. This study has developed a FREAK descriptor using RGB color space to improve the robustness of illumination invariance. A vertical concatenation technique has been used to combine all the key points extracted. Evaluation for the robustness of descriptors in terms of illumination changes has been done using the ALOI data set. The accuracy of the RGB FREAK descriptor has increased in illumination invariance (light color changes and lighting arrangement changes) compared to the original FREAK descriptor.
Potentials of Cryptocurrency Entrepreneurs in Transforming Global Cities and Regions

The emergence of digital currencies is substantially influencing the growth of global financial markets and cities. Cryptocurrency entrepreneurs (CEs) are reshaping global cities and regions by transforming the way we live, work and interact. This chapter explores how the entrepreneurs use cryptocurrency assets and their underpinning computing technologies to transform the dysfunctional and evolving global cities. The CEs generate funds and create cutting-edge technologies to meet the challenges faced by cities, including unemployment, inadequate and rundown infrastructure and facilities as well as for new development to meet the needs of massive future urbanization. The chapter is organized in five parts. It first introduces the study and presents a background on the concepts of blockchain technologies and cryptocurrency, their emergence and development trend. It then discusses the rise of global cities and how technology impacts them, followed by the potentials and challenges of CEs in transforming global cities and regions. It ends with conclusion and future research directions.
Estimation of nonlinear structural equation models with dichotomous indicator variables: a Monte Carlo comparison of methods

Nonlinear structural equation models (SEMs), which include interactions among latent predictors, as well as quadratic or higher order terms, have been the focus of research over the last three decades, beginning with Kenny and Judd (1984). The great majority of that work has focused on the case where the indicator variables are continuous in nature. However, in practice many nonlinear SEMs will involve the use of responses to items on scales, which are categorical. The focus of the current simulation study was on comparing several methods for modelling nonlinear SEMs when indicator variables were dichotomous. Results of the study showed that a Bayesian approach, as well as a method based on 2-stage least squares, provided the most accurate parameter estimates, the highest power, and the best control over the Type I error rate for the interaction effect. Implications of these findings for practice are discussed.
Understanding Cyber Forensics and Some of Its Tools

Digital Investigation acquires a queue of themes connected to crime and security across the computerized world. Key pillar of this paper is Digital Evidence with central qualities of provenance, Integrity and Technology. Investigation carried out in Incognito browsing advertised by browsers. Forensic Investigation in Cyber Physical Systems can be performed to generate Device Fingerprints. Digital Investigating is a sector of Science for gathering, examining and presenting Legal Evidence that is found from Digital Devices. Androsics Tool to analyze Android Devices to investigate through Android Forensics. Cyber Physical attacks on Cyber Physical Cloud System these are the main platforms analyzed by Cyber Forensics.
Shape Representation

This chapter covers a large number of commonly used shape methods which are broadly classified into two major categories: contourContour-based methods and regionRegion-based methods. It begins with introducing some simple and perceptual shape descriptorsPerceptual shape descriptors followed by several shape signaturesShape signatures in contourContour-based methods. More contourContour-based methods are described in the next including moments, stochastic methodStochastic method, scale spaceScale space method, FDFractal Dimension (FD), shape contextShape context. Several structural contourContour methods are also covered including syntactic, chain codeChain code, polygonPolygon and smooth curve decompositionSmooth curve decomposition. The rest of the chapter covers regionRegion-based shape methods including geometric momentsGeometric moments, complex momentsComplex moments, GFD, shape matrixShape matrix and shape profilesShape profiles. Structural methods such as convex hullConvex hull and media axisMedia axis are also discussed. Two MPEG-7MPEG-7 shape descriptors are also discussed in the chapter, i.e., CSS and ART. Most of the techniques discussed in this chapter are demonstrated with illustrations.
Introduction

In the first chapter, we will learn about big data, data analytics, and machine learning, as well as their utilities in different disciplines, including geosciences. A thorough understanding of data analytics problems, algorithms, and geoscience-specific data is critical before applying these sophisticated tools. We will also go into the brief history of the advent of different machine learning algorithms, the different types of geoscience databases, and their fitness to machine learning applications.
Exploring investment strategies for federated learning infrastructure in medical care

Recently, federated learning has gained substantial attention in medical care where privacy-preserving cooperation among hospitals is required. However, in a real-world situation, the deployment of a federated learning system among hospitals requires heavy investment in computing and network infrastructure. Under such a case, making investment effective across computing power and network capability is essential. In this paper, we propose an investment methodology following the growth saturation of learning efficiency. We also systematically study the impacts of non-investment factors on the application of this methodology. With consideration of relevant cost models, the methodology is validated cost-effective.