Reviewerly/exHarmony huggingface dataset:
Research on incremental update mechanism of moving target tracking based on user interest change

Target tracking is a hot topic in the field of computer vision. It uses the context information of video or image sequence to model the appearance and motion information of the target, so as to predict the motion state of the target and calibrate the position of the target. From the perspective of building models, target tracking algorithms can be divided into generative models and discriminant models; From the number of tracking targets, it can be divided into single target tracking and multi-target tracking. Target tracking integrates the theories and algorithms of image processing, machine learning, optimization and other fields. It is the premise and foundation to complete higher-level image understanding.The basic task of target tracking is to give the initial position of the target in a video sequence and continuously track and locate the target in each subsequent frame. In this process, a priori conditions such as the color, shape and size of the target will not be provided, that is, the tracking algorithm can track only by learning the target in the first frame. The traditional solution is to calculate the project similarity offline and save it in the system for algorithm call, but it can not make full use of the latest scoring data to reflect the change of user interest. To solve the above problems, a target tracking item similarity incremental update mechanism suitable for online applications is proposed, so that the recommendation system can update the similarity data between the corresponding item and other items in real time after the current user submits the item score, so that the recommendation system can recommend based on the latest item similarity data, To adapt to changes in user interests.
Research on three-dimensional scene production methods of cultural and creative games based on Unity technology

With the increasing attention paid by the cultural and creative industry to IP, IP extension not only includes ordinary peripheral products such as handicrafts, toys, cultural shirts, etc., but also carries out multi-dimensional expansion in the diversified development of its products. Game development is an important field of IP expansion of cultural and creative products in recent years. At present, most of the game development is based on Unity 3D technology. The most important part of game development is the three-dimensional scene production of the game. Therefore, on the basis of the above background, this paper systematically explores the specific application of Unity technology in the three-dimensional scene production process by studying the three-dimensional scene production of cultural and creative games.
An information perspective based on architecture design

Architecture design technology, this paper focus on the information demand research, exploration, especially in the information mechanism, and the data information system in the view of operations to the reshaping of the structure and function of the elaboration, enrich the theory of information view research storage, to engage in battle command, program planning, construction and management, system design, technology research and development and system maintenance work and so on all kinds of personnel, Provide a "common language" for communication, so that the theoretical framework of information resource services is gradually improved and accurate. In terms of system nature, information demand research is a concept and top-level design of a higher level. The information demand reflects the ability demand of information system construction, interprets and changes from the perspective of information on the ability points needed to be improved, and provides theoretical layout and hints for the final system construction and application.
Achieving Secure and Efficient Dynamic Searchable Symmetric Encryption over Medical Cloud Data

In medical cloud computing, a patient can send her medical data to a cloud server from afar. Because medical data is highly sensitive, only authorized doctors are allowed to access it in this case. A frequent solution is to encrypt data before outsourcing it, with the patient simply sending the corresponding encryption key to the authorized doctors. However, due to the difficulties of digging through the encrypted data, the usability of outsourced medical data is severely limited. Over medical cloud data, we propose Secure and Efficient Dynamic Searchable Symmetric Encryption (SEDSSE) schemes. To begin, we propose a dynamic searchable symmetric encryption scheme that uses the secure k-Nearest Neighbor (kNN) and Attribute-Based Encryption (ABE) techniques to achieve two important security features: forward privacy and backward privacy, both of which are difficult to achieve in the field of dynamic searchable symmetric encryption. Then, to address the key sharing problem that plagues the kNN-based searchable encryption strategy, we suggest an improved technique. In terms of storage, search, and update complexity, our solutions outperform prior proposals. Extensive tests show that our approaches are efficient in terms of storage overhead, index building, trapdoor generation, and query.
Analysis and prediction of academic proficiency test scores based on LSTM

This paper analyzes 48923 examinee's achievement data in a high school academic level examination in a city, and comprehensively evaluates the overall distribution of the examination from the aspects of average score and distribution of examination results. Pearson correlation coefficient is used to study the correlation between courses, cluster analysis is carried out for the courses with high correlation coefficient, and the courses with high correlation with the total score are also analyzed. Improving the score of the course can more effectively improve the total score. Finally, the LSTM method is used to predict and analyze students' performance, and compared with the results of SVM and logistic regression to verify the relationship between courses with high correlation, which provides a scientific reference for teaching management, teachers' teaching according to their aptitude and students' learning.
Basics of Blockchain Architecture

Blockchain architecture is a promise of finality and non-repudiation. It has distinct advantages over the traditional client-server or distributed systems, which have made various organizations explore use cases where blockchain can be applied. This chapter explores the key nuances of the blockchain architecture. It begins with an overview of the hash functions, hashing and how it plays an important role in blockchain architecture. While blockchain is well known as a P2P architecture, the chapter explores other aspects of the blockchain architecture, which are responsible for the strength of the blockchain. The chapter presents a deep dive into the block structure, use of Merkle trees for transactions and the blockchain structure. The power of decentralization, the built-in redundancy in the blockchain architectures and how it helps establish a trustless system is explained. It presents the challenges of distributed consensus and how they are dealt with via various consensus algorithms in the blockchain architecture. The chapter ends with a sample use case discussion of Maintenance and Service Supply Chain over a permissioned blockchain architecture using Hyperledger framework.
Intelligent wheelchair design based on STM32

This paper designs an intelligent wheelchair based on STM32 microcontroller, including control board, drive module, balance control module, ultrasonic module, tracking module, voltage regulator module and power module; Drive module, balance control module, ultrasonic module and tracking module are connected with the control motherboard; The voltage stabilizer module is connected with the power supply module, used to stabilize the power supply voltage and power supply to the control motherboard, drive module, balance control module, ultrasonic module and tracking module; The driving module is used to provide power for a two-way motor installed in the wheel position of the wheelchair; The balance control module is used to obtain the Angle and posture information of the wheelchair and keep the body balance of the wheelchair; The ultrasonic module is used to identify obstacles and automatically avoid obstacles; The tracking module for automatic navigation; On the basis of ordinary electric wheelchair, the balance control and automatic obstacle avoidance structure are added to provide safety guarantee.
Potencial das Tecnologias de Informação Geográfica e da Realidade Aumentada na aprendizagem das Ciências: estudo de caso no 1.⁰ CEB&lt;br&gt;Potential of Geographic Information Technologies and Augmented Reality in Science learning: a case study in the 1st CEB

A aprendizagem suportada por Tecnologias de Informação Geográfica (TIG) e Realidade Aumentada (RA) merece atenção no campo de estudo da Educação. A investigação de base deste artigo visa compreender as potencialidades destas tecnologias na aprendizagem dos conteúdos previstos no currículo do Estudo do Meio do 1.º ciclo do Ensino Básico, em Portugal. Sustentados na metodologia de estudo de caso os dados qualitativos foram recolhidos através da observação participante, grelhas de observação, notas de campo, trabalhos realizados pelos estudantes e na realização de um focus group . Os resultados de aprendizagem, decorrentes das atividades dinamizadas, mostram que uma adequada e intencional articulação das TIG e da RA apoiam a compreensão de conceitos e dos fenómenos e favorecem a construção do conhecimento. Abstract Learning supported by Geographic Information Technologies (GIT) and Augmented Reality (AR) deserves attention in the field of Education study. The basic research of this article aims to understand the potential of these technologies in learning information content in the curriculum of the Study of the Environment in the 1st cycle of Basic Education, in Portugal. Based on the case study methodology, qualitative data were collected through observation, observation grids, field notes, work carried out by students and in the realization of a focus group. The learning results, derived from dynamic activities in the classroom, show that an adequate and intentional articulation of GIT and AR support the understanding of concepts and phenomena and favor the construction of knowledge. Keywords: Geographic Information Technology, Augmented Reality, Earthquakes, knowledge construction, 1st cycle of basic education.
An improved CRNN based vertical text recognition method for ancient Chinese books

In view of the large scale of Ancient Chinese books and the laborious problem of digitalization by manual input method, the ancient books digitalization model based on CRNN is proposed to realize the efficient text input of ancient books. In this paper, we use Handwritten Characters data set of Chinese Ancient Handwritten Characters Database (CASIA-AHCDB) to generate vertical text image data set of variable-length Handwritten Characters. Finally, after iterative training, the accuracy based on character (similarity measured by text editing distance) reached 97.54% in the training set and 96.58% in the test set. The method can be used to identify and proofread ancient books.
Interactive attention network fusion Bi-LSTM and CNN for text classification

At present, many text classification model methods integrate Convolution Neural Network (CNN) and Long Short-Term Memory (LSTM), although they have achieved good performance, they have not fully Taking advantage of the characteristics of these two models, this paper proposes a text classification model CR-IAN model based on interaction-level attention fusion of multi-channel CNN and Bi-LSTM. First: The local feature vectors of different latitudes of text are extracted through multi-channel CNN; At the same time: Pass the text matrix through the Bi-LSTM layer to obtain the result vector of the Bidirectional semantic learning of the text. Then: calculate the interactive attention according to the bidirectional output matrix and the local feature vector matrix. This can fully consider the characteristics of the text with semantics, the model can learn more text information. Finally: Pass the interactive attention through the fully connected layer and use the softmax activation function to get the classification result.
Image Steganography-A New Approach using Block Truncation Coding and LSB Embedding

The advancement in technology has made the transfer of secret information really difficult. Information can be hidden in an image in such a way that somebody who see it will not even doubt about the chance of a hidden information in it. There are many ways to hide information in images. In this paper, an Image Steganography technique (an image on image hiding technique) has been proposed. In this proposed method, the message and the coded message is embedded into the carrier via Least Significant Bit (LSB) embedding. The work obtains good results in terms of performance measures.
An integrated Bell-state analyzer for high fidelity entanglement between trapped ion quantum computers

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Is Article 21, Paragraph 4 of the Constitution alive or dead?

현행 &#65378;대한민국헌법&#65379; 제21조 제4항 제1문은 언론&#65381;출판은 타인의 명예나 권리 또는 공중도덕이나 사회윤리를 침해하여서는 안된다고 규정하고 있다. 이 조문이 표현의 자유의 보호영역을 설정한 것인지 아니면 단순히 언론&#65381;출판의 사회적 책임과 의무를 강조하기 위한 것인지 여부를 두고 학설과 판례가 다투어 왔다. 1998년 헌법재판소는 제1문은 표현의 자유의 ‘보호영역’의 한계를 설정한 것이라고 판단했다. 그러나 2009년 헌재는 이 결정을 변경해 제1문은 보호영역을 설정한 것이 아니라 언론&#65381;출판 자유의 한계를 규정한 것이라고 판시했다. 이후 2009년 결정의 취지가 유지되고 있다. 그러나 헌법 제21조 제4항을 언급한 다수의 표현의 자유 관련 결정에서 헌재는 제21제 제4항 제1문이 “표현의 자유의 한계를 분명히 명시한 것”이라고 판시하고 있다. 이러한 입장은 단순히 ‘사회적 책임과 의무’를 강조하는 것과 차이가 있다. 더불어 ‘표현자유의 보호영역에서 배제’되는 영역이 있다는 근거로 활용되는 것도 아니다. 실제 제1문은 헌법 제37조 제2항과 더불어 표현의 자유를 규제하는 법률이나 법조항의 위헌성 심사 기준으로 동시에 활용되고 있다. 사실적시 명예훼손죄의 위헌성을 다룬 헌재 결정 등에서 제1문은 법정의견과 반대의견 모두가 주장의 근거로 동원하고 있다. 2009년 판례 변경에도 불구하고 헌법 제21조 제1문의 성격을 둘러싼 논쟁은 해소되지 않고 있다. 제21조 제4항이 대한민국 헌법에 도입된 배경과 헌법 개정 연혁, 표현의 자유와 관련한 합헌성 심사의 쓸모를 종합적으로 고려하여, 연구자는 향후 헌법을 개정할 때 제21조 제4항을 삭제할 것을 제안하였다.The first sentence of Article 21 (4) of the current Constitution stipulates that the media or publication shall not infringe on the honor or rights of others or public morality or social ethics. In 1998, the Constitutional Court judged that the first sentence set the limits of the scope of protection of freedom of expression’. In 2009, the Constitution changed the decision and ruled that the first sentence did not establish the scope of protection of freedom of expression’, but stipulated the limits of freedom of speech and publishing. In a number of decisions related to freedom of expression mentioned in Article 21 (4) of the Constitution, the Constitutional Court interprets that the first sentence of Article 21 (4) clearly specifies the limits of freedom of expression. In addition to Article 37 (2) of the Constitution, the first sentence has simultaneously used as a criterion for examining the unconstitutionality of laws or legal provisions that regulate freedom of expression. In the Constitutional Court s decision on the unconstitutionality of the crime of defamation in fact, the first sentence was mobilized as the basis for both the court opinion and the dissenting opinion. The researcher proposed to delete Article 21 (4) when revising the Constitution in the future.
Towards an Alternative Notion of the Interface

The aim of this paper is to propose an alternative notion of the interface. While the existing notions of the interface suffice, there is a need for understanding the interface as an ecology, rather than as an object or technology. Scholars such as Branden Hookway, Alex Galloway, Nanna Verhoeff, and Heidi Rae Cooley understand the interface as "a relationship," "processes," "doing," and "habits," respectively. However, in consideration of the new and emerging social processes and transformations engendered by interfaces as platforms by which we understand and relate with the world in more specific ways, I argue that a notion of the interface as an ecology would enrich the discussion and provide an ecological boundary ‘object’ for thinking across disciplines. I examined the interface through etymological, epistemological, psychoanalytic, and artistic standpoints, as well as exploring the term's affective, material, and infrastructural dimensions. I conclude that an ecological notion of the interface would produce a more nuanced and performative understanding of the term and shift our focus away from the material form of interfaces, to the actions, intensities, and aesthetics of the interface. Ecology is critical to how we understand interfaces as it concerns the relationships between organisms and their environments, including the relationships between artists and their expressive media and installations, and the relationships between users and their interface platforms. The ecological notion of the interface refers to how we live in the networked, hypermediated space, relate with our technologies, and engage in artistic practices in all forms of interfaces.
On the Feasibility and Generality of Patch-Based Adversarial Attacks on Semantic Segmentation Problems

Deep neural networks were applied with success in a myriad of applications, but in safety critical use cases adversarial attacks still pose a significant threat. These attacks were demonstrated on various classification and detection tasks and are usually considered general in a sense that arbitrary network outputs can be generated by them. In this paper we will demonstrate through simple case studies both in simulation and in real-life, that patch based attacks can be utilised to alter the output of segmentation networks. Through a few examples and the investigation of network complexity, we will also demonstrate that the number of possible output maps which can be generated via patch-based attacks of a given size is typically smaller than the area they effect or areas which should be attacked in case of practical applications. We will prove that based on these results most patch-based attacks cannot be general in practice, namely they can not generate arbitrary output maps or if they could, they are spatially limited and this limit is significantly smaller than the receptive field of the patches.
Approximating Permutations with Neural Network Components for Travelling Photographer Problem

Most of current inference techniques rely upon Bayesian inference on Probabilistic Graphical Models of observations, and does prediction and classification on observations rather well. Event understanding of machines with observation inputs needs to deal with understanding of the relationship between sets of observations, and thus there is a crucial need to build models and come up with effective data structures to accumulate and organize relationships between observations. Given a set of states probabilisitcally-related with observations, this paper attempts to fit a permutation of states to a sequence of observation tokens (The Travelling Photographer Problem). We have devised a machine learning inspired architecture for randomized approximation of state permutation, facilitating parallelization of heuristic search of permutations. Our algorithm is able to solve The Travelling Photographer Problem with very small error. We demonstrate that by mimicking components of machine learning such as normalization, dropout, lambda layer with randomized algorithm, we are able to devise an architecture which solves TPP, a permutation NP-Hard problem. Other than TPP, we are also able to provide a 2-Local improvement heuristic for the Travelling Salesman Problem (TSP) with similar ideas.
An Integrative Perspective on SEL Frameworks

This chapter underscores the notion that frameworks are often designed as tools for organizing and communicating ideas, building theories, as well as testing (and revising) research hypotheses. In the field of SEL, there has been a proliferation of frameworks in recent years such that the benefits of having a framework (e.g., communication, theory building) are being hampered by confusion about the sheer number of available frameworks. Since reviewing all existing frameworks is not a feasible task, this chapter compares frameworks that have been popularized in applied or research settings. This includes comparing key constructs across frameworks to highlight commonalities as well as unique contributions. Further, the chapter discusses the relative merits of frameworks that are organized hierarchically in that they can provide information about various levels of a construct (usually from more general to more specific) which has implications for measurement and intervention (covered in greater detail in other chapters of this book). The chapter concludes by proposing a moratorium on new framework development and instead focusing the field’s efforts on integrating existing frameworks by: (a) examining their common and distinct components, (b) asking whether the constructs in the frameworks are in fact measurable and actionable – thus underscoring their applied and research value, and (c) borrowing lessons from other areas of psychology (e.g., clinical, industrial/organizational, personality) that have successfully addressed concerns about framework proliferation in order to move our knowledge and practice base forward.
Bidirectional Deep Learning of Polarization Transfer in Liquid Crystals with Application to Quantum State Preparation

Accurate control of light polarization represents a core building block in polarization metrology, imaging, and optical and quantum communications. Voltage-controlled liquid crystals offer an efficient way of polarization transformation. However, common twisted nematic liquid crystals are notorious for lacking an accurate theoretical model linking control voltages and output polarization. An inverse model, which would predict control voltages required to prepare a target polarization, is even more challenging. Here we report both the direct and inverse models based on deep neural networks, radial basis functions, and linear interpolation. We present an inverse-direct compound model solving the problem of control voltages ambiguity. We demonstrate one order of magnitude improvement in accuracy using deep learning compared to the radial basis function method and two orders of magnitude improvement compared to the linear interpolation. Errors of the deep neural network model also decrease faster than the other methods with an increasing number of training data. The best direct and inverse models reach the average infidelities of $4 \times 10^{-4}$ and $2 \times 10^{-4}$, respectively, which is the accuracy level not reported yet. Furthermore, we demonstrate local and remote preparation of an arbitrary single-photon polarization state using the deep learning models. The results will impact the application of twisted-nematic liquid crystals, increasing their control accuracy across the board. The presented bidirectional learning can be used for optimal classical control of complex photonic devices and quantum circuits beyond interpolation.
Assessment of the Body Posture of Interventional Radiologists

Physicians in interventional radiology are exposed to high physical stress. To avoid negative long-term effects resulting from unergonomic working conditions, we demonstrated the feasibility of a system that gives feedback about unergonomic situations arising during the intervention based on the Azure Kinect camera. The overall feasibility of the approach could be shown.
Long-lived entanglement memory in a trapped-ion quantum network node

The 53rd Annual Meeting of the APS Division of Atomic, Molecular and Optical Physics will take place from May 30 – June 3, 2022 in Orlando, Fl, USA. <a href="https://morressier.zoom.us/j/89880865272?pwd=SWxTRGhra1ZOSDBrSkhVZDBzVDR6UT09/">Virtual Presenter Help Desk</a>