Reviewerly/exHarmony huggingface dataset:
UCWSC: A unified cross-modal weakly supervised classification ensemble framework

In recent years, Internet data has grown exponentially, but due to the lack of labels, the data that can be used is still relatively small. To solve this problem, research on weak supervision has emerged. However, common weakly supervised research often focuses on either single-modal data or multi-modal data research, which cannot be compatible with both types of data at the same time. Motivated by this observation, we propose a unified cross-modal weakly supervised classification ensemble framework (UCWSC) to tackle this issue. Especially, our proposed framework is based on high-order feature information of different modes. First, We introduce a feature fusion method based on high-order features to increase the amount of acquired information. Then we propose a modified Feature MixMatch algorithm with learning from feature representations. We propose feature fusion and decision fusion methods for weakly supervised classification of multi-modal data with voting and weighting mechanisms as discriminators to obtain the final classification results, respectively. We demonstrate the compatibility of these techniques, our classification accuracy can reach around 99% on the Wikipedia dataset and 78% on the MVSA-Multiple dataset.
The Design of a Multi-Agent Protocol for Swarm Decision Making

The most studied form of group intelligence in nature is the bee colony, where the process of finding a new nest site is similar to the democratic discussion in human group decision making. Some researchers are currently simplifying complex problems by modeling the behavior of bee swarms and interacting with them by building agents that behave like swarms. In this paper, we define a swarm decision language containing behavioral language, agents, protocols, decision rules and constraints based on the process of swarm addressing, on top of the Lightweight Social Calculus specification (LSC). The aim is that the group cooperation pattern is described by a protocol and the behavioral characteristics of individuals are restricted by rules. Complex group decisions are described by a dynamic combination of these two levels. We use this method to provide a group decision solution for cases that require site selection in human life, reducing a large amount of manpower and increasing the speed and reliability of decision making compared to traditional manual site search methods.
Demonstrating a System for Dynamically Meeting Management Objectives on a Service Mesh

We demonstrate a management system that lets a service provider achieve end-to-end management objectives under varying load for applications on a service mesh based on the Istio and Kubernetes platforms. The management objectives for the demonstration include end-to-end delay bounds on service requests, throughput objectives, and service differentiation. Our method for finding effective control policies includes a simulator and a control module. The simulator is instantiated with traces from a testbed, and the control module trains a reinforcement learning (RL) agent to efficiently learn effective control policies on the simulator. The learned policies are then transfered to the testbed to perform dynamic control actions based on monitored system metrics. We show that the learned policies dynamically meet management objectives on the testbed and can be changed on the fly.
Answering Count Queries for Genomic Data With Perfect Privacy

In this paper, we consider the problem of answering count queries for genomic data subject to perfect privacy constraints. Count queries are often used in applications that collect aggregate (population-wide) information from biomedical Databases (DBs) for analysis, such as Genome-wide association studies. Our goal is to design mechanisms for answering count queries of the following form: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">How many users in the database have a specific set of genotypes at certain locations in their genome?</i> At the same time, we aim to achieve perfect privacy (zero information leakage) of the sensitive genotypes at a pre-specified set of secret locations. The sensitive genotypes could indicate rare diseases and/or other health traits one may want to keep private. We present both local and central count-query mechanisms for the above problem that achieves perfect information-theoretic privacy for sensitive genotypes while minimizing the expected absolute error (or per-user error probability, depending on the setting) of the query answer. We also derived a lower bound of the per-user probability of error for an arbitrary query-answering mechanism that satisfies perfect privacy. We show that our mechanisms achieve error close to the lower bound, and match the lower bound for some special cases. We numerically show that the performance of each mechanism depends on the data prior distribution, the intersection between the queried and sensitive genotypes, and the strength of the correlation in the genomic data sequence.
A Novel Framework for the Psychology of Decision Making

Decision making is a complex process influenced by cognitive, affective, and contextual factors. We propose a novel framework that integrates insights from cognitive psychology, social psychology, and neuroscience. The framework consists of three main components: information processing, evaluation, and decision. We discuss how each component contributes to the decision-making process and how they interact with each other. The framework can be used to understand and improve decision making by identifying and addressing potential biases and errors.
Handwritten Digit Recognition using Machine Learning with Python

Handwritten Digit Recognition is one of the essentially significant issues in pattern recognition applications. The main purpose of this project is to build an automatic handwritten digit recognition method for the recognition of handwritten digit strings. This paper proposes a simple convolution neural network approach to handwritten digit recognition. Convolutional Neural Network model is implemented using MNIST dataset. This dataset consists 60,000 small square 28×28pixel grayscale images of handwritten single digits between 0 and 9. The applications of digit recognition include postal mail sorting, check processing, form data entry, etc. The core of the issue exists in the capacity to foster a proficient calculation that can perceive manually written digits and which is put together by clients by the method of a scanner, tablet, and other computerized gadgets.
Research on the Impact and Countermeasures of Artificial Intelligence Empowering Smart Classroom

Smart classroom is a new application of artificial intelligence in the field of education, and the rise and development of artificial intelligence technology has turned large-scale personalized education from an ideal to a reality.In order to promote the balance between artificial intelligence and humanistic care, and unleashing the irreplaceable nature of intelligent education, we use literature research method, based on inductive analysis of theoretical studies and technical practices of smart classroom, combined with the application of artificial intelligence in smart classroom, we propose the influence process of "artificial intelligence system -student learning process, teacher teaching process, and resource presentation process" directly or indirectly combined with each other.Then we analyze three major problems of the current smart classroom application: distorted classroom performance and abnormal teaching feedback; limited thinking ability and worrisome learning quality; data leakage and privacy protection concerns.Finally, we propose countermeasures for the application of AI-empowered smart classroom construction in three aspects: regulating the scope of application and adjusting the time of use; carrying out excellent case studies to ensure the quality of learning; relying on privacy protection technology and establishing relevant mechanisms.
Utilization of Autonomous Driving Model Vehicles for Learning Materials for Autonomous Driving and AI

Autonomous driving technology is a broad-based technology and a growth factor for many industries. Therefore, there are high expectations for this field. In recent years, the need for engineers involved in the field of autonomous driving has increased, and the training of such engineers is urgently needed. On the other hand, recently, teaching materials for learning autonomous driving and AI, for example, model vehicles such as the autonomous driving platform "Donkey Car S1" are also on the market. Therefore, using this autonomous driving teaching material "Donkey Car S1", students were taught to learn autonomous driving by making a simple autonomous driving electric vehicle. This paper introduces an overview of this.
Abnormal Detection Scheme of Substation Equipment based on Intelligent Fusion Terminal

In recent years, with the rapid development of science and technology, complex power services have made it more difficult to early warning of abnormal operating status of smart grid equipment. Aiming at the operation status information of substation equipment involved in complex power business, an abnormal detection scheme for substation equipment based on intelligent fusion terminal is proposed. The scheme is divided into three phases to strengthen anomaly detection. First, by calculating the Spearman correlation coefficient, the correlation between different label indicators is screened out from the operation status information of substation equipment. Then, considering the timeliness of state information data, in order to analyze the future operation state of substation equipment, the time series of different indicators are predicted by using the long short-term memory neural network. Finally, in order to further intuitively and accurately discover the abnormal conditions of the future operation status of the substation equipment, the clustering algorithm based on the density space is used to cluster the time series output by the long short-term memory neural network, and the abnormal conditions are marked. The experimental results show that by deploying the scheme, the smart fusion terminal can timely and effectively give early warning of equipment abnormalities and ensure the stable operation of the smart grid.
Korelasi Motivasi Dengan Prestasi Belajar Ilmu Pengetahuan Sosial Siswa di Mtsn 12 Jombang

Humans as the most noble creatures by themselves will not become noble just like that, but someone must foster, lead and direct them. This action is a learning process in an educational institution. Learning is a process of changing behavior that occurs in a single situation, even in a vacuum. This learning situation is characterized by the motives set and accepted by students. The purpose of this study was to determine the motivational condition of class IX students at MTsN 12 Jombang on social science learning achievement. In this study there were two variables, namely motivation which is the independent variable or (X). while Social Science learning achievement is the dependent variable (Y), with a questionnaire on 77 respondents from class IX MTsN 12 Jombang, using descriptive data analysis of percentage and product moment correlation. And from the results of this study by looking at the product moment r table value, it turns out that with a df of 75 at a significant level of 1%, an r table of 0.217 is obtained, while at a significant level of 5%, we get an r table of 0.283. greater than the price of r table. Both at a significant level of 5% (0.38 &gt; 0.217) or at a significant level of 1% ) 0.38 &gt; 0.283), it means that there is a moderate positive effect. The results of this study indicate that the higher the student's learning motivation, the higher the learning achievement in Islamic religious subjects, and the lower the student's learning motivation, the lower the achievement in Social Sciences subjects.
TEMPERATURE AND HUMIDITY MONITORING WITH SECURE ECHNOLOGY

The "Temperature and Humidity Monitoring with Secure Technology" project aims to address the security challenges faced by traditional temperature and humidity monitoring systems in various industries such as agriculture, industrial environments, and smart cities.These challenges include data tampering, exfiltration, and system disruption, which can arise due to cyber attacks.To tackle these security challenges, the proposed system combines blockchainbased secure authentication and secure wireless sensor networks.The blockchain technology is used to authenticate devices on the sensor network and to ensure that only authorized devices can access the network and transmit readings.The wireless sensor network is designed to be secure and efficient, transmitting temperature and humidity readings in a confidential and tamper-proof manner.A key component of the system is the smart contract, which is used to authenticate and authorize devices on the sensor network.The blockchain platform will store the temperature and humidity readings in a secure and tamper-proof manner, ensuring the integrity of the data.The effectiveness of the proposed system will be evaluated through simulations and experiments in a real-world environment.The results of this project will demonstrate the improved security and reliability of the temperature and humidity monitoring system compared to traditional systems.The results will have significant implications for various industries that rely on temperature and humidity monitoring.In conclusion, this project will demonstrate the potential of using blockchain and secure wireless sensor networks to improve the security and reliability of temperature and humidity monitoring systems.The "Blockchain Beats: Improving Temperature and Humidity Monitoring with Secure Technology" project will highlight the importance of combining innovative technologies to address security challenges and to improve the overall performance of temperature and humidity monitoring systems.
Keynote II: A Challenge of Scalable Quantum Computing Control Systems

The speaker is developing a quantum computer controller responsible for managing a large number of quantum bits (qubits) by initializing and manipulating them to facilitate meaningful computations.The controller transmits and receives microwaves to and from the qubits to control and measure their state.Since qubits are incredibly delicate and can be easily disrupted by environmental factors, the controller needs to include highly accurate and stable microwave transceivers.The speaker will share some of the key features of our system, including highly accurate microwave transceivers and high-precision synchronous mechanism.To achieve a huge volume quantum computer, a significant number of signal processing systems with analog-to-digital converters (ADCs) and digital-toanalog converters (DACs) to control and measure the qubits are required.However, since the number of channels of ADCs and DACs on a chip is limited, it is necessary to orchestrate multiple signal processing units.The speaker will discuss our architecture for multiple qubit control systems, which is scalable and combines chip-level synchronization by LEMC of JESD204C and system-level synchronization by an IEEE1588-like protocol implemented on an FPGA.This architecture achieves nano-second order synchronization of transmitting and receiving of signal processing units.Furthermore, we are continuously striving to improve the performance and efficiency of our system to realize a fault-tolerant quantum computer (FTQC).However, achieving FTQC is a significant challenge, as the controller must be scalable to manage a large number of qubits.The speaker will discuss our ideas and progress on our efforts toward realizing an FTQC.
Differences in usability evaluation and learning satisfaction of medical students according to XR and VR application environments of medical simulation

이 연구는 복잡한 지식 및 기술영역을 다루는 의료진단 시뮬레이션에 대한 학습자의 지각수준의 차이를 확인하기 위한 것이다. 이 연구의 목적은 시뮬레이션을 XR적용환경에서 사용할 때와 VR적용환경에서 사용할 때의 학습자 지각수준의 차이를 검증하기 위한 것이다. 이 연구에서는 의과대학 3학년 학생 10명과 4학년 8명이 참여했다. XR적용환경은 마이크로소프트사에서 개발한 홀로렌즈2를 사용했고, VR적용환경에서는 HMD(head mounted display)인 오큘러스 리프트 S를 사용했다. 연구대상자들은 XR과 VR 적용환경을 모두 경험했으며, 진단실습을 마친 다음에는 각 사용환경의 장단점에 대한 심층면담이 진행되었다. 또한 실험이 끝나고 난 뒤, 4주 뒤에 추수설문이 실시되었다. 종속변수에서 측정사용성평가(사용편이성과 사용활용성)와 학습만족도 설문이 실시되었다. 실험 직후에 실시된 면담결과를 바탕으로 XR과 VR 적용환경에서의 장단점을 도출할 수 있었다. 추수설문에서 측정된 사용성평가에 대해서는 반복측정에 의한 다변량분산분석이 적용되었으며, 학습만족도는 단일요인 반복측정에 의한 개체내 검정이 실시되었다. 설문분석 결과에 따르면 XR보다 VR환경에서 사용성평가(사용편이성, 사용활용성) 결과가 유의미하게 높은 것으로 나타났다. 그러나 학습만족도에서는 유의미한 차이가 나타나지 않았다. 이 연구를 통하여 사용자들이 의료 진단 분야에서 VR과 XR을 다르게 지각하고 있음과 시뮬레이션 설계를 달리해야함을 확인하였다.The purpose of this study is to identify differences in learners' perceptual levels for medical diagnosis simulations dealing with complex knowledge and technology areas. The purpose of this study is to verify the difference in learner perception level when simulation is used in an XR-applied environment and when it is used in a VR-applied environment. In this study, 10 third-year medical school students and 8 fourth-year students participated. HoloLens 2 developed by Microsoft was used for the XR application environment, and Oculus Rift S, which is HMD (head mounted display), was used for the VR application environment. The study subjects experienced both XR and VR application environments, and after the diagnostic practice, in-depth interviews were conducted on the pros and cons of each use environment. In addition, four weeks after the experiment, a harvest survey was conducted. In the dependent variable, measurement usability evaluation (ease-to-use and usefulness) and learning satisfaction survey were conducted. Based on the interview results conducted immediately after the experiment, it was possible to derive the advantages and disadvantages in the XR application environment and the VR application environment. Multivariate analysis of variance by repeated measurement was applied to the usability evaluation measured in the harvest survey, and variance analysis by repeated measurement was also conducted for learning satisfaction. According to the results of the survey analysis, both ease-to-use and usefulness results were significantly higher in usability evaluation in the VR environment than in XR. However, there was no significant difference in learning satisfaction. The study confirmed that users perceive VR and XR differently in medical diagnostics and that simulation design should be different.
IoT Based Blockchains and IPFS

Block chain, the underlying technology of crypto currency networks like Bitcoin, is designed to realize the vision of a decentralized, secure and open Internet of Things (IoT) revolution with a centralized data access model. Essential. It may be so. This article proposes a distributed access model for IoT data using a network architecture called the IoT and Blockchain Modular Consortium Architecture. The proposed architecture facilitates IoT communication via a blockchain software stack and a peer-to-peer data storage mechanism. This architecture is intended to provide privacy and be adaptable to various IoT use cases. To implement the proposed architecture, we conduct a performance analysis of existing blockchain development platforms, Ethereum and Monax.
Community empowerment in landslide management in Sonyo hamlet

Soyo Hamlet is led by Mr. Suranto as the head of the hamlet. The hamlet itself consists of eight RTs with 173 family heads. The hamlet is located in a mountainous area in the Kulon Progo district. Soyono Hamlet is bordered by Sidomulyo Hamlet and Mount Kelir Hamlet. Soyo Hamlet, which is located in a mountainous area, has many problems. One of the problems that have come to our attention is the problem of vulnerability to natural disasters. Natural disasters that often occur in the village are landslides. It is feared that in the rainy season like today, heavy rains can cause landslides. Based on the above problems, this community service designs and implements a landslide early warning tool. This tool is made using the main component is a microcontroller which is used as a data processor, a sensor uses a potentiometer to detect ground movement, and a siren. In addition to installing landslide equipment, this community service also provides lessons on landslide recovery
Formation of environmental etiquette for masters: a view from the point of view of modern pedagogical science

The article discusses the peculiarities of educating undergraduates of environmental etiquette – an important personal and professional quality. The article analyzes the originality of Master’s training of specialists, as well as the resource content of system, competence and subject-activity approaches. The article describes some interactive pedagogical technologies of complex influence on the positive dynamics of the process of enriching the environmental etiquette of Master’s students, which was carried out on the basis of the results of analytical work in this regard, which was based on the best domestic and foreign practices. It is recognized that the problem area within which it is advisable to direct further scientific research is to increase the motivation of future masters to environmentally responsible behavior, their awareness at the level of beliefs of the imperative of ecological culture.
Formation of educational competencies of educators on the basis of integration of natural cycle subjects

The article considers the problems of formation of educational competencies of students on the basis of integration of subjects of the natural cycle. The analysis of the works of domestic and foreign pedagogical literature in the aspect of the researched problem shows that: in the methodical system of teaching natural sciences it is expedient to use the didactic principle of integration of all components of natural science education; implementation of the methodological system in the process of teaching natural sciences, which should include all components of natural science education; the content of all subjects of the integrated course in natural sciences are studied as modules; ways and methods of teaching constitute a system that contributes to the formation of the natural-scientific picture of the world and natural-scientific competence; the integration of knowledge in the process of teaching natural sciences forms in students an ecological image of nature, a viable national image of the model of the world. It is noted that the effectiveness of the educational process should be ensured by a system of information and educational resources and techniques that provide conditions for the development of functional literacy of the learner in a competitive world of information and technology. The quality of education, the productivity of knowledge management, the main educational outcomes are increasingly determined in a systematic and competency-based approach that assesses the ability of students, graduates to apply academic knowledge in practice, in life situations. Formation of educational and cognitive competencies is a key moment of new educational standards in the formation of functional literacy. It is proved that integration is necessary in the modern education system.