Reviewerly/exHarmony huggingface dataset:
Image Denoising Using Fully Connected Network with Reinforcement Learning

Deep reinforcement learning (DRL), where an agent learns behaviors in an environment by actions and receiving rewards, has been applied successfully in the robotics area and game controllers at a human level. However, the application of DRL in image processing is still scarce. In this paper, we present a novel approach for image denoising by combining a fully connected network with the gated recurrent unit in an asynchronous advantage actor-critic scheme. The proposed method assigns an agent to every pixel of the input image, and the agent changes the value of each pixel by selecting an action from a predefined list. The goal is to learn an optimal policy to maximize the reward at all pixels of the image. We conduct the denoising experiments on the BSD68 dataset and the results show that the proposed approach produces equivalent or higher PSNR scores compared to several state-of-the-art models based on supervised learning. Our approach is interpretable to humans by showing the agent’s actions, which is a significant difference from original CNNs.
Learning to Map the GDPR to Logic Representation on DAPRECO-KB

General Data Protection Regulation (GDPR) is an important framework for data protection that applies to all European Union countries. Recently, DAPRECO knowledge base (KB) which is a repository of if-then rules written in LegalRuleML as a formal logic representation of GDPR has been introduced to assist compliance checking. DAPRECO KB is, however, constructed manually and the current version does not cover all the articles in GDPR. Looking for an automated method, we present our machine translation approach to obtain a semantic parser translating the regulations in GDPR to their logic representation on DAPRECO KB. We also propose a new version of GDPR Semantic Parsing data by splitting each complex regulation into simple subparagraph-like units and re-annotating them based on published data from DAPRECO project. Besides, to improve the performance of our semantic parser, we propose two mechanisms: Sub-expression intersection and PRESEG. The former deals with the problem of duplicate sub-expressions while the latter distills knowledge from pre-trained language model BERT. Using these mechanisms, our semantic parser obtained a performance of 60.49% F1 in sub-expression level, which outperforms the baseline model by 5.68%.
Mobile Robot Guidance Method Using Laser Spots Irradiated on the Floor from Real World Clicker and its Application for Object Grasping System

In order to measure 3D coordinate values of a object to be manipulated by a support robot, we have been developing a "Real-World Clicker (RWC)" using a TOF-type laser distance sensor mounted on a pan-tilt actuator [1][2]. With this RWC the mobile robot can automatically grip and bring any object that user click in a real world. Our conventional robot system, however, used only its odometry to control the mobile robot, which resulted in low accuracy and low success rate in grasping distant objects. In this paper, we propose a method to solve this problem by taking advantage of the RWC not only to indicate the object but also to guide the mobile robot. The key idea is an automatic guidance by laser spots on the floor, illuminated by the laser sensor.
Multi-modal Human-machine Conversation System for Real Physical World

Enabling machines to process multi-modal information and understand the real physical world is an important step to achieving free human-machine conversation. However, previous human-machine conversation systems are mostly limited to single-modal (e.g., chat robot), single-round (e.g., visual Q & A), and static visual information (e.g., visual dialogue). To address the above problem, we develop a multi-modal human-machine conversation system for specific application scenarios. The system includes two modules: (i) an interactive visual grounding module that can actively disambiguate user's queries, and (ii) an interactive fine-grained recognition module that can model objects in the 3D environment and actively ask for missing visual information. A video demo of our system under the automobile sales scenario can be found here <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> https://drive.google.com/file/d/1IfBsMKq55ryLOZchIT6G-R5CyWnC3Skiew?usp=sharing.
THE SYSTEM OF TEACHER TRAINING FOR PARTICIPATION IN PROFESSIONAL SKILLS COMPETITIONS

The article analyzes the phenomenon of professional skills competitions for teachers. The article describes the practice of Ekaterinburg Economy and Technology College in developing a system that prepares college teachers to participate in professional skills competitions at various levels: the mechanisms of involving teachers in competitions are shown, the system of incentives and methodological support is described, the effectiveness of the developed system is presented.
Increasing the Accuracy of Secure Model for Medical Data Sharing in the Internet of Things

The security of medical data sharing (MDS) plays an important role in the area of healthcare. Significantly, achieving its security faces more challenges due to the feature of multiparty holding, higher complexity, and serious data silos. Different from traditional secure schemes, which established model cannot deal with the above three problems due to the low accuracy of the MDS secure model, this paper designs a novel secure MDS model and two schemes to increase the accuracy of the model. In detail, to eliminate the issues of data silos and point failure, we combine the federated learning (FL) with blockchain technology into MDS secure model, and the data confidentiality of the exchanged data in the process of FL can be further ensured by differential privacy (DP). Then, to increase the accuracy of the secure MDS model, we design a validation incentive mechanism based on model quality (VIM) and an effective DP method with assigned weights (AWDP), in terms of participants’ enthusiasm and noise accumulation, respectively. Simulations show that the established model is effective and correct and the designed VIM and AWDP can achieve higher accuracy than current popular methods, resulting in 30 $$\%$$ increment.
Blockchain State of the Art

In the previous chapter, we examine the many similarities between blockchains and distributed databases, and discuss how blockchains prioritize security and robustness over performance. The important research questions concerning blockchains are (1) how they strengthen robustness, and (2) how they improve performance without impacting security.
SOCIAL MEDIA PRESENCE OF PUBLIC ADMINISTRATION AS A TOOL TO EDUCATE TAXPAYERS

Today's social networks affect the functioning of societies around the world. They influence our thinking and reasoning on fundamental issues of life, as was clearly demonstrated during the COVID-19 pandemic and the war in Ukraine. National
Analysing the potential of transport triggered architecture for lattice-based cryptography algorithms

Lattice-based structures offer numerous possibilities for post-quantum cryptography. Recently, many post-quantum cryptography algorithms have been built on hard lattice problems. The three of the remaining four algorithms in the final round of the NIST Standardization Process rely on lattice-based methods. However, suitable processor architectures for these algorithms have not been sufficiently investigated. This study examines the potential advantages of transport triggered architecture for these algorithms. We compare popular 64-bit RISC-V processors with our conceptual transport triggered architecture processor over reference software implementations. Our processor provides better results than RISC-V competitors, regardless of the algorithm. It seems to be up to 3× faster, 1.6×-2× smaller, and consumes 1.3×-3.6× less energy than the compared RISC-V cores. Thus, an alternative base architecture is proposed for post-quantum cryptography processor development for embedded systems. The most critical shortcoming of the proposed architecture is the lack of compatible intellectual property core support for system-on-chip designs. We share comparative analyses with test results for different core configurations.
Web-Based Ornamental Chicken Delivery Service Information System

Technology in the era of modernization is developing very quickly, making humans face various changes, in terms of information systems that are increasingly rapidly following the times. With the rapid advancement of technology. Companies are competing to take advantage of technology to be the best. One of the service jobs that is quite widely used is the provider of ornamental chicken delivery services, where these services can help people who want to send their chickens between cities and outside the island. This information system was created with the aim of making it easier for managers to conduct transactions and collect customer data. This information system is built using PHP technology and MySQL database. Making this information system uses the waterfall method where researchers analyze the current system to find deficiencies or problems from the current system and then look for solutions to overcome these problems. Based on the results of the tests that have been carried out, the system built can run well and meet the needs of CV. Dwi Atmojo in providing convenience in processing customer data and recording transactions that occur. With this information system, users can record customer data, record transactions and confirm payments as well as monitor delivery status.
Instant Apps

Instant apps allow a device user to use apps without actually installing them. In the Google Play Store, the "Try it" button you sometimes see exactly starts such an instant app.
Developing Students’ Understanding In Learning Passive Voice Trough Cooperative Learning

The purpose of this study is to see if cooperative learning improves students' grasp of passive voice in the first semester of accounting at Universitas Pamulang. This research is classified as Classroom Action Research (CAR), and it is used to discover and fix a problem related to students' comprehension of passive voice. The writer uses Hopkin's design in this Classroom Action Research. Meanwhile, the information gathered through the interview, questionnaire, observation, and test is being analyzed (pretest and posttest). Based on the outcomes of the study, it can be concluded that the use of cooperative learning in the teaching of passive voice is successful since the success criteria have been satisfied. The results of the posttest 2 reveal that 93.33 percent of the students, received a score of 70 or above. Furthermore, the results of the interview, observation, and questionnaire show a remarkable improvement. In conclusion, the results of the interview, observation, and questionnaire revealed that students' passive voice learning improved significantly after the cooperative learning approach was implemented in the teaching learning process.Keywords: Students' Understanding; Passive Voice; Cooperative Learning.
Delegates

In the last chapter, we learned about enumerations and saw how they allow us to assign meaningful names to constants. In their basic form, the first name will represent the value 0 and each subsequent name will have a value of one more, but it is possible to assign different values to the names and thereby change the default values. Enumerations, we learned, help make code more readable, and we can use methods of the Enum class to get the name or value of an item or items in the enumeration. Finally, we also saw that an enumeration is a “special” data type, which is defined by the developer.
Introduction

The quantum-classical divide and the limitations of using classical tools to study quantum systems have received attention for several decades. We examine specific aspects of this broad theme, primarily using quantum optics as the platform for our investigation. In this introductory chapter, we outline nonclassical effects such as wave packet revivals, squeezing and entanglement. We define several optical states, and give a pedagogical illustration of how these states differ in their dynamics. We then indicate two aspects studied in the sequel. First, the extraction of nonclassical properties directly from tomograms that are readily available from experiments, bypassing detailed state reconstruction. Tomograms, being probability distributions in contrast to the reconstructed Wigner functions, provide useful pointers to assess nonclassicality. Standard entanglement indicators defined using the density matrix are introduced, with reference to which we compare the performance of indicators obtained directly from optical and qubit tomograms. Second, we demonstrate the usefulness of applying time series and network analysis (originating from classical dynamical systems theory) to the dynamics of quantum observables.
Hardware

Android can do more than presenting a GUI on a smartphone. Android is also about wearables, talking to appropriately equipped TV sets, and infotainment in cars. And smartphones have cameras, NFC and Bluetooth adapters, and sensors for position, movement, orientation, and fingerprints. And, yes, smartphones can do phone calls as well. This chapter describes how the Android OS can run on devices other than smartphones and how to interact with the device’s hardware.
Scopes, Functions, and Parameter Passing

In most programming languages, you can declare named entities such as variables, functions, classes, and types. Each declaration has a scope, which defines from where the declared name is visible. The rules that determine the visibility of declarations are called scope rules.
Conclusion: When Will the Era of “Quantum Supremacy” in Artificial Intelligence Come?

As quantum technology emerging, traditional computers and the artificial intelligence based on that are ushering in the quantum era. Once quantum computers are mature in technology and popularized, quantum artificial intelligence will be born. With the exponential increase in computing speed, AI will have subversive impacts on mankind in the twenty-first century.
Chapter 15: Projects for OpenMP Programming

The background for the projects below is given in Part VI of this book. You should be able to build each of these projects based on the information provided in this text and utilize some or all of the OpenMP compiler directives to improve the speed of your program. For some of the projects, there may be some additional comments to give hints on how to best take advantage of the OpenMP system, while for others, it should be obvious, such as using #pragma omp for to parallelize for loops.
I Have Seen that Before: Memory Augmented Neural Network for Learning Affordances by Analogy

Humans show a remarkable ability to quickly adapt to new situations without forgetting past ones. Existing learning methods still face problems with catastrophic forgetting when learning about new situations and contexts while taking many iterations to adjust to new input and output pairs. In this work, we propose the application of a Memory augmented network to the problem of learning tool affordances. We consider a network that explicitly indexes an episodic memory of past experiences and retrieves samples of past experience to reason about new situations by analogy, in an approach we call affordances by analogy. The work takes advantage of a tool-object interaction dataset to learn affordances. Our experiments show the model outperforms the baselines in the low sample regime and retains information better when re-trained on a different data distribution. Hinting at a promising direction, this work could enable learning algorithms to retain information better.
Pragmatic Analysis of Web Service Discovery Models and Architectures from a Qualitative Perspective

Web services and application programmer interfaces (APIs) have become an integral part of modern-day software development. In today’s connected world, these services and APIs must possess characteristics like the ease of availability, low delay, high security, and minimum memory utilization. Moreover, these models must be easily discoverable, and highly usable from a development standpoint. In order to improve the discoverability of these models, various approaches like domain ontology approach, public ontology approach, syntax and semantic approach, context-aware approach, etc. have different performance in terms of metrics like the delay of discovery, computational complexity, accuracy of discovery, etc. Due to such a wide variation in the performance, it becomes difficult for web administrators to select the best possible combination of service discovery mechanisms suited for their application. Web administrators are therefore required to either study the internal mechanisms of each discovery model, or deploy the recommended models individually and evaluate their performance. Both approaches are time-consuming and increase the overall cost of system deployment. In order to reduce the probability of this drawback, the underlying text evaluates the performance of some of the recent web service discovery models; and quantifies them in terms of performance parameters like the delay of discovery, accuracy of discovery, and fuzzy computational complexity. Using this review, both researchers and website administrators will be able to evaluate the best possible solution for their specific application, thereby reducing both time and cost needed for web deployment. Moreover, this text also recommends various methods to improve the performance of these models, thereby assisting in further cost and deployment time optimization.
Case Study: Acquiring Sustainable, Efficient High-Resolution Seismic Data for Geothermal Exploration in an Urban Environment

Summary The overall conditions under which geophysical data are being acquired have changed over the past 5 years due to the global economy combined with an increased emphasis on low environmental impact sustainability and safety. For land seismic acquisition, minimizing land disturbance, reducing CO2 emissions and increasing crew safety are key motivators to use innovations that drastically change conventional land seismic acquisition methods. One of the sources proven to do this is the eVibe developed by Seismic Mechatronics BV. They were recently contracted to undertake an urban seismic program utilizing their proprietary eVibe source in combination with STRYDE Nodes™. The seismic survey was acquired in one of the largest cities in the Netherlands, without the need for permits. Being able to minimize environmental impact, to reach a high safety standard and to acquire high-quality data in a noisy urban environment with the used technology made this project a success. This paper compares the results achieved by the Storm10 eVibe in combination with STRYDE NodesTM to results previously obtained by an explosive survey. We show that the results are technically superior, with the eVibe and the STRYDE Nodes proving far better suited to acquiring seismic within this challenging and restrictive urban environment.
Bill-Type Text Recognition Model Based on Convolution Network

The characteristics of bill-type text include multiple single characters, low semantic features and multiple text regions. For bill-type text recognition, the existing recognition methods have difficulty in model fitting and slow inference speed due to the deep CNN or RNN in the network. For the above issues, a high-precision bill-type text recognition model BT-CCN, which does not need to split characters and has fast inference speed, is proposed. BT-CCN can be divided into three parts: convolution module, sequence module and fully con-nected layer module. Firstly, the convolutional module extracts the image as feature sequence using the im-proved lightweight convolutional and asymmetric pooling structure. Secondly, BiTCN structure is proposed in sequence module, which can realize deep convolution and extract semantic features of sequence. Finally, a full connection layer is introduced to capture global information to avoid the constraint of the receptive field of the sequence module. Experimental results show that the model has higher precision and faster inference speed than other models on data sets of various practical projects.
The Effects of High Performance Work Systems on Organizational Trust and Innovation: Moderating Roles of Frontline Manager’s Involvement

As facing uncertain and dynamic business environment, organizations should manage their exploratory innovation and exploitative innovation properly to adapt environmental changes in time. Firms should effectively pursue two different ways of innovation, which are indispensable to create sustainable competitive advantages, by exploration of new business opportunities and exploitation of existing business. Organizations need to take this ambidextrous innovation strategy and adopt SHRM(strategic human resource management) which is aligned to the aforementioned exploratory and exploitative innovation. Previous studies have focused on examining the impact of innovation on organizational performance, rather than on finding the sources of innovation or understanding the process to acquire it. The aim of this study is to offer better understandings of organizational innovation by integrating the literature of high performance work systems (HPWS) with the literature of organizational trust. We suggested that HPWS is a proper system for innovation strategy and tested 1) the mediating role of organizational trust between HPWS and innovation and 2) the moderating role of frontline manager’s involvement on the relationship between HPWS and organizational trust Our tests with Human Capital Corporate Panel (HCCP) data(2013-2017) showed that HPWS enhanced exploratory innovation and exploitative innovation through organizational trust. Moreover, frontline manager’s involvement strengthened the relationship between HPWS and organizational trust Theoretical and managerial implications are discussed.
Information Entropy of Uncertainty Control: An Uncertainty Management Method in Imperfect Information Games

With the vigorous development of artificial intelligence, many amazing breakthroughs have been made in recent years, while games often serving as important milestones. After significant progresses in perfect information games' field (e.g, Alpha Zero in Go), studies have gradually shifted to imperfect information games such as Poker, in which uncertainty management is a key part of this. Reconnaissance blind chess (RBC), a variant of chess, provides a good platform for specialized research on uncertainty management problems, because it has an independent “information sensing” stage. In this paper, we propose Information Entropy of Uncertainty Control (IEUC), which is a new method introduce information entropy theory as the optimization target of uncertainty in imperfect information games. IEUC integrates the whole uncertainty of the environment and strategy evaluation to reduce the uncertainty of the environment more reasonably. We realize a practical RBC agent that incorporates IEUC method. In the experiments, our new agent has shown better effectiveness and robustness than several influential opponents in information sensing, including our previous version that won the champion in terms of uncertainty management in NeurIPS 2019 RBC tournament.
Cryptography: Integrity and Authenticity

Data integrity can be protected using hash functions, message authentication codes, and digital signatures. These cryptographic mechanisms are introduced in this chapter, along with the combination of encryption and message authentication codes that results in authenticated encryption.