Reviewerly/exHarmony huggingface dataset:
Optimal Routing and Aborting Planning of Uav-Truck with Multi-Source Random Shocks

In recent years, there are rapidly increasing needs for the applications of UAV in fields such as terminal logistics, emergency management and military rescue. The reliable and safe execution of UAV tasks, particular in complex environment, has become a significant topic of practical interests. This study investigates the cooperative vehicle routing optimization problem of UAVs and trucks exposed to multisource random shocks, with both the routing and time synchronization constraints. The shock-induced task aborting strategies are devised in consideration of the multi-vehicle UAVs-Trucks routing plan, so as to assign targets and determine the visiting order in a more secure and stable manner. In particular, the impact of random shocks from different attack sources and with different attributes are modeled and analyzed. To reduce the risk of trucks being destroyed, each truck can choose to abort its task if optimizable, pre-specified conditions is met. A path optimization model is designed using probability theory and graph theory, and solved by ALNS heuristic search algorithm. The results of numerical experiments demonstrate the applicability of the proposed model and algorithm.
Comparative evaluation of fully homomorphic encryption algorithms in cloud environment

Cloud computing is an essential component of the service delivery environment in the domain of service computing. It assures a cloud service ecosystem to permit different service providers for participating and provisioning their services for consumers. In the cloud environments, the major component is offering security to the end users, which is ensured with the homomorphic encryption primitives. These approaches focus on minimising the computational burden in terms of clear computation. This paper aims to implement a comparative analysis of privacy preservation in cloud computing using fully homomorphic encryption (FHE) algorithms. A set of algorithms like lattice-based, integer-based, learning with errors (LWE), ring learning with errors (RLWE), and Nth degree truncated polynomial ring units (NTRU) are used for the comparison to make a concluding point regarding those performances. The experimental evaluation demonstrates the efficiency of the diverse frameworks, in terms of both security performance and accuracy, for building a secure analytics cloud-enabled application.
Arbitrageurs' profits, LVR, and sandwich attacks: batch trading as an AMM design response

We study a novel automated market maker design: the function maximizing AMM (FM-AMM). Our central assumption is that trades are batched before execution. Because of competition between arbitrageurs, the FM-AMM eliminates arbitrage profits (or LVR) and sandwich attacks, currently the two main problems in decentralized finance and blockchain design more broadly. We then consider 11 token pairs and use Binance price data to simulate the lower bound to the return of providing liquidity to an FM-AMM. Such a lower bound is, for the most part, slightly higher than the empirical returns of providing liquidity on Uniswap v3 (currently the dominant AMM).
Designing a system using telepresence technology to enhance the feeling of "being there" for elderly individuals at healthcare centers

The study focuses on enhancing the "being there" presence by using 360 real-time video technology to create a remote interactive device system for the elderly in health care centers. By enhancing the “being there” presence of elderly, we can improve the physical and mental health of the elderly.In the experiment, the guide put on a wearable device to make a tour of a specific place, and the elderly watched the tour from a remote location on a monitor. After the test, we conducted a semi-structured interview with the participant to understand their feelings about the operation of the device, the content of the system, and their sense of "being there" presence. We also conducted expert interviews with the experimental results to establish the device's design direction, usability, and usage patterns.From the study, we have concluded that the design and usability of the navigation device and the viewer device, as well as the clarity of the viewing screen, are the main factors that affect remote presence. Devices that meet the usability of both parties can increase the sense of "being there" presence. Additionally, the interaction process between the elderly and the remote guide, as well as the content design and the process of interaction between the two people, can help enhance the remote presence of the elderly.
Word memory

When I read a word that I don't know how to pronounce, I can't remember it. Why do I need to be able to pronounce a word for my brain to recall it?
A Novel Approach for Jewellery and Fashion in Mobile Application Developement using Augumented Reality

The research work aims to develop an augmented reality application for trying on necklaces using a mobile device’s camera. The application was created using Unity3D and the AR Foundation (AR Core SDK), which provides a robust development environment for building AR applications on Android devices. The necklace models are created and textures are applied using blender software. Users can select a necklace from a category list, capture an image of themselves with the virtual necklace, and preview the image in the app’s interface. The application uses a tracking system based on the reference point to align the necklace with the user’s face in real time. The project successfully achieved its goals, providing an engaging and interactive way for users to explore different necklace styles. The work also highlights the potential for further development, including integrating ecommerce functionality and adding other jewelry types such as earrings, bracelets, and rings. The application represents an innovative and exciting use of augmented reality technology in the field of fashion and jewellery.
A Left Ventricle Segmentation Based on Boundary Weighted Loss and Residual Feature Aggregation

Assessing the left ventricle in cardiac magnetic resonance imaging (MRI) through segmentation plays a crucial role in the diagnosis of cardiac diseases for cardiologists. However, conventional manual segmentation is a tedious task that requires excessive human effort, which makes automated segmentation highly desirable in practice to facilitate the process of clinical diagnosis. This paper proposes a method for automatically outing the left ventricle, namely a left ventricle segmentation algorithm based on boundary weighted loss and residual feature aggregation (RFA). The proposed method is based on the U-Net model, where normal convolutions of the encoder and decoder are replaced with a residual feature aggregation (RFA) module for more efficient feature extraction. At the same time, we add a series of cascaded dilated convolutions in the middle part of the encoder and decoder to expand the receptive field. In addition, we design a boundary weighted loss function, which can effectively address poor segmentation results caused by blurred/incomplete edges of the target object, or high proximity between the target object and others. Through experimental verification, it is proved that the proposed model and the carefully designed loss function both contribute to segmentation performance.
An Accessional Signature Scheme With Unmalleable Transaction Implementation to Securely Redeem Cryptocurrencies

The surging interest in cryptocurrency has revitalized the research for digital signature schemes with strong security. In particular, signature schemes are investigated to resist the malleability attacks in cryptocurrency platforms. However, existing signature schemes only conquer partial malleability attacks due to various sources of attacks. Other solutions of new transaction realizations cannot simultaneously avoid the malleability attacks on both standard and contract transactions. Furthermore, the malleability attack becomes more stubborn in fast clearing applications. In this paper, we propose SigNT, an accessional signature scheme with unmalleable transaction implementations. The key of SigNT is an improved interactive signature scheme for securely instant confirmation of transactions. Unlike standard signatures, this signature is generated by the owner and block producers. Combining it with several other optimizations ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i.e</i> ., hash execution of intermediate transactions and secret-based claiming conditions), SigNT achieves complete resistance against malleability attacks in both the standard and contract transactions. As an example, we show an implementation in Bitcoin with the “providing a deposit” protocol. The security analysis and comparative experiments demonstrate that SigNT has the best resistance against malleability attacks than previous malleability solutions. Besides, better performance is achieved than other schemes.
A new method for solving multiple definite integrals using multiple sets of correlation extreme learning machines

Purpose This paper aims to develop a novel method and apply it to solve multiple definite integrals. The proposed method is constructed based on multiple sets of correlation extreme learning machines (MCELM). Design/methodology/approach The authors present a novel method for solving multiple definite integrals. By using an extreme learning machine (ELM) to learn the integrand function, the primitive function is analytically derived based on the functional expression of the trained ELM and expressed by another ELM, while the correlations between the two ELMs are established. Solutions of multiple definite integrals can be realized by applying this process repeatedly. Findings To verify the validity and effectiveness of the proposed method, various examples are selected and its numerical solutions are obtained by using the proposed method. The proposed method has high computational accuracy and efficiency, and the superiority is illustrated by comparing with some other existing methods. Originality/value MCELM method is proposed for solving multiple definite integrals. The method can be applied for solving multiple definite integrals appearing in applications, the strong applicability of the method in engineering problems is demonstrated in structural system reliability analysis of a cantilever beam.
Languages Through the Looking Glass of BPE Compression

Abstract Byte-pair encoding (BPE) is widely used in NLP for performing subword tokenization. It uncovers redundantpatterns for compressing the data, and hence alleviates the sparsity problem in downstream applications.Subwords discovered during the first merge operations tend to have the most substantial impact on thecompression of texts. However, the structural underpinnings of this effect have not been analyzedcross-linguistically. We conduct in-depth analyses across 47 typologically diverse languages and threeparallel corpora, and thereby show that the types of recurrent patterns that have the strongest impact oncompression are an indicator of morphological typology. For languages with richer inflectional morphologythere is a preference for highly productive subwords on the early merges, while for languages with lessinflectional morphology, idiosyncratic subwords are more prominent. Both types of patterns contribute toefficient compression. Counter to the common perception that BPE subwords are not linguistically relevant,we find patterns across languages that resemble those described in traditional typology. We thus propose anovel way to characterize languages according to their BPE subword properties, inspired by the notion ofmorphological productivity in linguistics. This allows us to have language vectors that encode typologicalknowledge induced from raw text. Our approach is easily applicable to a wider range of languages and texts,as it does not require annotated data or any external linguistic knowledge. We discuss its potentialcontributions to quantitative typology and multilingual NLP.
Effects of environment correlations on the onset of collective decay in waveguide QED

We analyze the dynamics of one and two two-level atoms interacting with the electromagnetic field in the vicinity of an optical nanofiber without making either the Born or the Markov approximations. We model the dielectric response of the nanofiber with a constant dielectric function and the Drude-Lorentz model, observing deviations from the standard super- and subradiant decays. We discuss the validity of approximating the speed of atom-atom communication to the group velocity of the guided field in the presence of nontrivial environment correlations. Our work presents a deeper understanding of the validity of commonly used approximations in recent waveguide QED platforms.
Detecting Smart Contract Vulnerabilities with Combined Binary and Multiclass Classification

The development of Distributed Ledger Technology (DLT) is pushing toward automating decentralized data exchange processes. One of the key components of this evolutionary step is facilitating smart contracts that, in turn, come with several additional vulnerabilities. Despite the existing tools for analyzing smart contracts, keeping these systems running and preserving performance while maintaining a decent level of security in a constantly increasing number of contracts becomes challenging. Machine Learning (ML) methods could be utilized for analyzing and detecting vulnerabilities in DLTs. This work proposes a new ML-based two-phase approach for the detection and classification of vulnerabilities in smart contracts. Firstly, the system’s operation is set up to filter the valid contracts. Secondly, it focuses on detecting a vulnerability type, if any. In contrast to existing approaches in this field of research, our algorithm is more focused on vulnerable contracts, which allows to save time and computing resources in the production environment. According to the results, it is possible to detect vulnerability types with an accuracy of 0.9921, F1 score of 0.9902, precision of 0.9883, and recall of 0.9921 within reasonable execution time, which could be suitable for integrating existing DLTs.
Exploration of ways to improve teaching practicum in kindergarten

본 연구는 유치원에서 실행되는 학교현장실습의 제도, 과정 및 단계, 내용 등의 현황을 살펴보고, 그 운영의 한계와 문제점을 통해 개선 방안을 제시하는 것을 목적으로 하였다. 이를 위해 유치원 학교현장실습 제도, 실행과 관련된 국내외 문헌과 외국의 교사교육제도, 교사평가제도에 관한 자료를 바탕으로 문헌 연구를 실시하였다. 문헌 분석 결과, 상대적으로 짧은 학교현장실습의 기간, 실습의 질관리의 어려움, 실습 운영의 비체계성, 교육과정과 현장실습과의 미흡한 연계성, 제한된 교사 역할 학습 등이 유치원 학교현장실습의 문제와 한계로 도출되었다. 따라서 유치원 학교현장실습 제도의 개선을 위해서는 첫째, 교사양성과정에서 장시간의 학교현장 실습과 이에 따른 학점의 확대가 요구되며, 국내 뿐 아니라 국제교육실습, 인턴십 등 다양한 현장실습 제도의 운영을 고려할 필요가 있다. 둘째, 체계적인 학교현장실습 실행을 위해 예비교사 역량의 국가적 표준 기준 정립, 표준화된 실습 지침 개발, 전공교과가 학교현장과 연계될 수 있는 교육과정 개발에 대한 논의가 필요하다. 셋째, 질 높은 실습 경험을 제공하고 수업전문성을 향상시키려면 학교현장실습의 표준화된 평가체계의 확립이 필요하다. 이러한 유치원 학교현장실습 제도의 개선 방안이 실현되기 위해서는 교원양성대학, 실습 유치원, 교육청 등 각 실습주체들의 긴밀한 협력이 선행되어야 하며, 교원양성대학 내의 교육실습지원센터(Practicum center)의 구축을 통해 중장기적으로 다양한 유형과 단계의 학교현장실습을 체계적으로 관리, 운영해야 할 것이다.The purpose of this study is to examine the current status of the system, process, stages, and contents of teaching practicum in kindergartens, and to suggest improvement plans through the limitations and problems of its operation. To this end, a literature study was conducted based on data on teaching practicum system, domestic and foreign literature related to practice, and foreign teacher education system and teacher evaluation system. As a result of literature analysis, the problems and limitations of teaching practicum at kindergarten was derived such as the relatively short period of field practice, difficulty in managing the quality of teaching practicum, unsystematic operation, insufficient linkage between curriculum and teaching practicum, and limited teacher role learning, etc. Therefore, in order to improve the teaching practicum system, first, long-term teaching practicum and corresponding credit expansion are required in the teacher education curriculum, and it is necessary to consider the operation of various teaching practicum systems such as domestic and international student teaching and internship there is. Second, it is necessary to discuss the establishment of national standards for pre-service teacher competency, the development of standardized teaching practicum guidelines, and the development of a curriculum that can link major subjects with school sites for systematic implementation of field practice. Third, it is necessary to establish a standardized evaluation system for teaching practicum in order to provide high-quality teaching practicum experience and improve instructional expertise. In order to realize such an improvement plan for teaching practicum system, close cooperation between each practice subject, such as teacher training colleges, kindergartens, and education offices, should be preceded. Teaching practicum of various types and stages should be systematically managed and operated in the mid to long-term through the establishment of the practicum center within the college.
Machine Learning and Chatbots: Bridging the Gap with Deep Neural Networks

Machine Learning and Chatbots: Bridging the Gap with Deep Neural Networks
Exploring the Process of Change in Vocational High Schools in Response to Industrialization

Exploring the Process of Change in Vocational High Schools in Response to Industrialization - Industrialization;Vocational high school;Specialized vocational high school;Meister vocational high school;change
Comparison between Bayesian and SVM model for breast cancer risk prediction

Breast cancer ranks first in the incidence of cancer worldwide. It is a kind of malignant disease with incidence increasing year by year. Recently, machine learning algorithms widely used in cancer prediction and other fields to relieve the burden of doctors and accelerate the diagnostic process. In this work, two representative models, the support vector machine (SVM) and Bayesian classification algorithm are leveraged for breast cancer risk prediction. It is found that the effect and accuracy of the two algorithms are very different when they are used for breast cancer prediction. However, there is still a research gap in the comparison of the two algorithms in practical application. Therefore, the research topic of this paper is the comparison between the Bayesian classification algorithm and the SVM algorithm in breast cancer prediction. The research methods of this paper are as follows: firstly, the dataset is collected, then applying the Bayesian classification to process the dataset, and then the SVM algorithm is used to process the dataset. Finally, the processing results of the two algorithms are compared to comprehensively analyze and compare which algorithm is more efficient and more suitable for actual breast cancer prediction. The test results support that the SVM outperforms the Bayesian classification algorithm in the actual target tracking problem. Therefore, it is suggested to choose the SVM classification algorithm in the actual target tracking problem to boost the accuracy and efficiency of prediction results to the greatest extent.
Current

Current Annette Skade (bio) The old man's joke, "You'll be cliffed,"is a threat never to be carried out,but brings with it a story, five hundredyears old: English soldiers on Dursey,living couples tied together, throwninto the sound off Foilnamuck. The sea can't break this down.It passes into the guts of gullsand gannets, becomes airbornein their cries, flies into the mouthsof those who survive,handed down as language. Summer morning earlyI step out of my sundress,stand alone and flickeringbefore armfuls of blue water,skin already alive with wind,the need for cold salt waves. At the corner of my eye,something slinks and slops,glooping like an empty bin bag:the entire carcass of a calf,eyeless head still attached,muzzle pushing at the rock's flank. [End Page 112] Annette Skade Annette Skade is from Manchester, England, and has lived on the Beara Peninsula on Ire-land's southwest coast for over thirty years. Her first collection, Thimblerig, was published by Bradshaw Books in 2013, and her poems appear in various poetry magazines and anthologies in Ireland, the UK, the US, and Australia. In 2021 she received a doctorate on the poetry of Anne Carson from Dublin City University, Ireland. She is currently completing a long poem, "Alga," which celebrates the seaweed growing along the coast in her locality. Her ecopoetry chapbook, Alga, for which she received an Agility Award from the Arts Council of Ireland, will be published by Channel magazine in the summer of 2024. Copyright © 2023 Middlebury College
Temporal Relation Prediction from Electronic Health Records Using Graph Neural Networks and Transformers Embeddings

Temporal relations extraction is a key factor in many Natural Language Processing (NLP) tasks and, particularly, in clinical text mining. Previous studies mostly use linguistic rules, Machine LearningMachine Learning classifiers or Neural Networks for temporal relation extraction. Motivated by the existence of corpus annotated with temporal relations, and by the rise of graphsGraphs and TransformersTransformers in NLP, we propose a pipeline based on TransformersTransformers and Graph Neural NetworksGraph Neural Networks (GNNs) with the aim of predicting temporal links between events, entities and temporal expressions. For now, we analyzed the prediction of BEFORE and OVERLAP links from the i2b2 corpus using different types of BERT embeddings, achieving an AUC of 97% and 87%, respectively.
A Humanoid Saxophone-Playing Robot Based on Instrument-Centered Design

We will develop a saxophone-playing robot that enables human-robot interaction. Our previous generation of robots was larger and more complex to achieve higher performance, which made human interaction difficult. Therefore, we began developing the Waseda Anthropomorphic Saxophonist robot X (WAS-X), redesigned to simulate a saxophonist playing in a seated posture. In the early stages of development, the robot was created by a product designer using Design Thinking. The robot was designed with the saxophone centered. The design reference points are integrated and organized to restructure the robot, resulting in a small and simple configuration and a stable blowing range. This approach, Instrument centered design, is a fundamental development concept for WAS-X. However, the performance of WAS-X has not yet reached the level of beginners. In addition, the sound quality of WAS-X was comparable to that of previous robots, even though a neck strap held it. The cause of these problems probably involves the condition of the blown air and the contact points with many instruments. Thus, this research focused on the keys and fingers, the contact points between the saxophone and the robot. As a result, the lower sound quality was improved using a hybrid soft material for the fingers. These fingers are flexible plastic fingers with silicone rubber tips. Furthermore, a fingering control system was also implemented to adjust the initial values efficiently.