Information Upload Research Articles

Exploring One-Shot Semi-supervised Federated Learning with Pre-trained Diffusion Models

Recently, semi-supervised federated learning (semi-FL) has been proposed to handle the commonly seen real-world scenarios with labeled data on the server and unlabeled data on the clients. However, existing methods face several challenges such as communication costs, data heterogeneity, and training pressure on client devices. To address these challenges, we introduce the powerful diffusion models (DM) into semi-FL and propose FedDISC, a Federated Diffusion-Inspired Semi-supervised Co-training method. Specifically, we first extract prototypes of the labeled server data and use these prototypes to predict pseudo-labels of the client data. For each category, we compute the cluster centroids and domain-specific representations to signify the semantic and stylistic information of their distributions. After adding noise, these representations are sent back to the server, which uses the pre-trained DM to generate synthetic datasets complying with the client distributions and train a global model on it. With the assistance of vast knowledge within DM, the synthetic datasets have comparable quality and diversity to the client images, subsequently enabling the training of global models that achieve performance equivalent to or even surpassing the ceiling of supervised centralized training. FedDISC works within one communication round, does not require any local training, and involves very minimal information uploading, greatly enhancing its practicality. Extensive experiments on three large-scale datasets demonstrate that FedDISC effectively addresses the semi-FL problem on non-IID clients and outperforms the compared SOTA methods. Sufficient visualization experiments also illustrate that the synthetic dataset generated by FedDISC exhibits comparable diversity and quality to the original client dataset, with a neglectable possibility of leaking privacy-sensitive information of the clients.

Peer Review Statement

Proceedings: The 9th Light Symposium December 4-6, 2023 · Stockholm, Sweden Peer Review Statement: All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. Type of review: Double-blind, anonymous Conference submission management system: Conference system by Axaco / Axacoair with upload of final information to Morressier Number of submissions received: 81 initial abstracts, 53 final papers Number of submissions sent for review: 81 initial abstracts, 53 final papers Number of submissions accepted: 32 Acceptance Rate (Submissions Accepted / Submissions Received × 100): 40 (from initial abstract submissions), 60 (from final paper submission) Average number of reviews per paper: 3-4 Total number of reviewers involved: 34 Contact person for queries: Ute Besenecker, PhD KTH Architecture, Lighting Design uteb@kth.se

Three-Dimensional Multi-UAV Trajectory Design for Cooperative Video Inspection and Uploading

This paper studies the multiple unmanned aerial vehicles (UAVs) trajectory design for post-disaster cooperative video inspection and information uploading. The locations to be inspected are modeled as points of interest (PoIs) with heterogeneous resolution requirements. The three-dimensional (3D) trajectories for multiple cooperative UAVs are designed to minimize the time for successfully inspecting all the PoIs and maximize the communication time for the video uploading. An UAV inspection model is built to clarify the criteria for successful inspection, which is related to the UAV's 3D positions and velocity. The proposed UAV trajectory design involves two steps. First, the PoIs in proximity are grouped using convex optimization. Then, the multiple UAV trajectories are jointly designed by solving a multiple traveling salesman problem (MTSP). Numerical results show that the proposed design can significantly reduce the mission completion time.

VDIU: VLC-Based Debugging Information Upload Method for Self-Powered Sensor Nodes

Currently, more and more self-powered sensor nodes have been deployed in remote and inaccessible areas, and thus online debugging of sensor nodes becomes more necessary and important. However, the existing sensor online debugging approaches mainly rely on original network infrastructure (such as Zigbee or NB-IoT). Once the communication infrastructure is invalid, it is almost impossible to retrieve debugging information and repair the lost self-powered sensor nodes. To this end, in our previous study, we employed the onboard optical modules of the self-powered sensor node to realize a Visible Light Communication(VLC)-based hybrid communication debugging system(VHCDS). In this paper, to improve the efficiency of uploading debugging information, we propose VDIU to optimize the digital pulse interval modulation applied in the uplink of VHCDS. This method reasonably groups and sorts the origin data to reduce the number of empty time slots (unused time slots) and complete data compression in source coding for saving energy. To improve the reliability of the uplink, we also design two frame synchronization mechanisms suitable for the receiver-side optical cameras of the uplink. One mechanism considers lightweight synchronization design via restricting the position of the frame header; the other one focuses on reducing the occupation of the downlink of VHCDS via predicting the position of the frame header using a temporal convolutional network (TCN). Experiments results illustrate that the upload efficiency using VDIU is higher 78% and 28% than DPIM and DH-PIM. Both synchronization mechanisms can arrive the similar performance, but the predicting mechanism reduces the 93% occupation on the downlink.

A Novel Blockchain-Based Model for Agricultural Product Traceability System

At present, the application of blockchain in the traceability system has become a mainstream technology to ensure the quality and safety of agricultural products. However, blockchain is designed to ensure open and transparent data and tamper-proof, and there is a deficiency in the privacy protection of data. In this study, a novel blockchain-based model for agricultural product traceability system is proposed, which has good generality and can protect the privacy of the agricultural product information in the traceability system. First, we designed a multi-channel data collection and uploading architecture, with one channel corresponding to the collection and uploading of information of one type of agricultural product, so as to meet the actual traceability needs of various types of agricultural products. Then, the information of agricultural products uploaded by each channel is encrypted by using the hierarchical encryption algorithm, and the encrypted information is stored in the blockchain to realize the secure sharing of agricultural product information. Finally, we evaluated the system model on the Hyperledger Fabric platform.

Mobile coded caching in small cell networks: Algorithm design and performance analysis

In coded caching, users cache pieces of files under a specific arrangement so that the server can satisfy their requests simultaneously in the broadcast scenario via eXclusive OR (XOR) operation and therefore reduce the amount of transmission data. However, when users' locations are changing, the uploading of caching information is frequent and extensive that the traffic increase outweighed the traffic reduction that the traditional coded caching achieved. In this paper, we propose mobile coded caching schemes to reduce network traffic in mobility scenarios, which achieve a lower cost on caching information uploading. In the cache placement phase, the proposed scheme first constructs caching patterns, and then assigns the caching patterns to users according to the graph coloring method and four color theorem in our centralized cache placement algorithm or randomly in our decentralized cache placement algorithm. Then users are divided into groups based on their caching patterns. As a benefit, when user movements occur, the types of caching pattern, rather than the whole caching information of which file pieces are cached, are uploaded. In the content delivery phase, XOR coded caching messages are reconstructed. Transmission data volume is derived to measure the performance of the proposed schemes. Numerical results show that the proposed schemes achieve great improvement in traffic offloading.

Multi-Domain Resource Scheduling for Full-Duplex Aided Wireless Powered Communication Network

In order to support information uploading of batteryless user equipments (UEs), a full-duplex (FD) hybrid access point (H-AP) is relied upon for downlink wireless power transfer (WPT) and uplink information collection, which yields a classic wireless powered communication network (WPCN). These UEs harvest energy from downlink radio frequency (RF) signals in order to power their own uplink wireless information transfer (WIT). However, the uplink information collection of the H-AP suffers from the self-interference (SI) induced by the downlink WPT. In this paper, for the sake of maximising the uplink fair-throughput of UEs, we jointly design the transmit beamforming and receive combining at the H-AP having multiple antennas in the spatial-domain, the resource allocation in the time-domain and the UEs’ scheduling in the user-domain. Since the resultant optimisation problem is non-convex in nature, an iterative algorithm is developed by decoupling the original joint design into several sub-problems. Our numerical results demonstrate the fast convergence, the uplink fair-throughput gain and the great fairness of our multi-domain resource scheduling design.

Privacy protection in social applications: A ciphertext policy attribute‐based encryption with keyword search

In a highly evolved big data era, intelligent data analysis can improve social operation efficiency and save resources. However, it also brings masses of conflicts, such as malicious mining and abuse of personal privacy information. This paper introduces a privacy protection scheme for social applications. In this scheme, attribute based searchable encryption is used to defend the security of confidential data and ensure the availability of data. Moreover, the access control structure of ciphertext strategy can meet the needs of data sharing in social applications. Security analysis shows that the scheme does not disclose privacy information in index ciphertext, search trapdoor, and equality test. Compared with plaintext information upload and sharing, the additional performance overhead caused by the scheme is acceptable. The scheme can be actually deployed in social applications.

Exploration and practice of building tele-critical care system

To look for the problems faced in the construction of the tele-critical care system, explore the framework of construction of the tele-critical care system, and verify the application effects of the established tele-critical care system. Through literature review and on-site investigation and demonstration, the causes affecting the construction of the tele-critical care system were explored. Through on-site investigation of the actual situation of the critical care department in relevant hospitals, arguing and choosing intended intensive care unit (ICU) and cooperative third-party communication and equipment companies, and through the Internet of Things and 5G communication technology, a tele-critical care system with the core hospital of the group as the center and the member institutes within the group as the nodes was built. Via the established tele-critical care system, activities such as tele-monitoring, visual remote ward rounds, remote consultation, remote teaching were carried out to verify the functions of the system. The insufficient cognition of relevant personnel, tele-medicine practice certification requirements, information security issues and the barriers of equipment information integration were the main causes affecting the construction of tele-critical care system. There were five parts in the tele-critical care system architecture foundations, including bed unit equipment and audio and video information collection system, lossless and secure transmission of collected information, real-time display of information in the remote center, real-time staff interaction between the centre and the nodal hospitals, and information cloud storage. It has been verified that patients' diagnostic and treatment information can be transmitted safely, losslessly and in real-time by a special line through private 5G network. Through this system, real-time and stable upload of audio and video information of patients and application information of monitors, ventilators and infusion work stations can be achieved; combined with tele-conference connections to conduct two-way communication with local medical staff, real-time tele-monitoring, visual remote ward rounds, remote consultation, remote teaching and other functions can be achieved. The tele-critical care system we established is feasible to construct within the medical group and can safely and effectively realize the functions of real-time tele-monitoring, visual remote ward rounds, remote consultation, and remote teaching.

Streamlining Traceability Data Generation in Apple Production Using Integral Management with Machine-to-Machine Connections

Legal requirements and consumer demands have motivated the development and application of traceability technology. Farming practices are the starting point of the agri-food supply chain and the destination of the agri-food traceability system (AFTS). The amount of resource information and the complexity of the production process of agri-food become the main obstacles to the wide application of AFTS. This study introduces an integrated machine-to-machine system that allows collecting field operation information automatically. This system includes an IoT-based integrated hardware system, a smart farm cloud (SFC) platform, and a mobile application, which accomplished the collection, upload, and storage of operation information. This system had been used in “BSD” organic apple orchard in Qixia, Shandong Province, China for about one year. The effectiveness of the system was evaluated by managing 270 apple trees in one plot of the orchard. Finally, a label with a QR code was successfully generated to provide consumers to query traceability information from a single tree to a fruit tray. This work was a background of a blockchain traceability system. Moreover, the future extendibility of the system was also discussed and prospected.

A Virtual Community for Disability Advocacy: Development of a Searchable Artificial Intelligence-Supported Platform.

BackgroundThe lack of availability of disability data has been identified as a major challenge hindering continuous disability equity monitoring. It is important to develop a platform that enables searching for disability data to expose systemic discrimination and social exclusion, which increase vulnerability to inequitable social conditions.ObjectiveOur project aims to create an accessible and multilingual pilot disability website that structures and integrates data about people with disabilities and provides data for national and international disability advocacy communities. The platform will be endowed with a document upload function with hybrid (automated and manual) paragraph tagging, while the querying function will involve an intelligent natural language search in the supported languages.MethodsWe have designed and implemented a virtual community platform using Wikibase, Semantic Web, machine learning, and web programming tools to enable disability communities to upload and search for disability documents. The platform data model is based on an ontology we have designed following the United Nations Convention on the Rights of Persons with Disabilities (CRPD). The virtual community facilitates the uploading and sharing of validated information, and supports disability rights advocacy by enabling dissemination of knowledge.ResultsUsing health informatics and artificial intelligence techniques (namely Semantic Web, machine learning, and natural language processing techniques), we were able to develop a pilot virtual community that supports disability rights advocacy by facilitating uploading, sharing, and accessing disability data. The system consists of a website on top of a Wikibase (a Semantic Web–based datastore). The virtual community accepts 4 types of users: information producers, information consumers, validators, and administrators. The virtual community enables the uploading of documents, semiautomatic tagging of their paragraphs with meaningful keywords, and validation of the process before uploading the data to the disability Wikibase. Once uploaded, public users (information consumers) can perform a semantic search using an intelligent and multilingual search engine (QAnswer). Further enhancements of the platform are planned.ConclusionsThe platform ontology is flexible and can accommodate advocacy reports and disability policy and legislation from specific jurisdictions, which can be accessed in relation to the CRPD articles. The platform ontology can be expanded to fit international contexts. The virtual community supports information upload and search. Semiautomatic tagging and intelligent multilingual semantic search using natural language are enabled using artificial intelligence techniques, namely Semantic Web, machine learning, and natural language processing.

HerediCaRe: Documentation and IT Solution of a Specialized Registry for Hereditary Breast and Ovarian Cancer

The national registry "HerediCaRe" for the evaluation and improvement of risk-adjusted prevention in hereditary breast and ovarian cancer is one of six "model registries in health services research" funded by the BMBF. In this paper, we describe and discuss the documentation and IT solution chosen for standardized data collection based on the specific functional requirements previously defined. The documentation is divided into different modules to be used individually for each patient, which are based on a previously defined catalog of documentation items. Due to special functional requirements, a specific data entry application based on ORACLE and ORACLE Forms was developed and implemented. The specific requirements included the integration of graphical pedigree representations, the structured upload of pedigree data and molecular genetic information, the automated transfer of old data from the previous system, as well as the free programmability of complex database queries for central data quality control. A database for patient-independent management of genetic risk variants was seamlessly integrated into the application and linked to the patient-related data. The advantages and disadvantages of the chosen IT solution are critically discussed. Overall, we come to the conclusion that, in view of the complex documentation and the special functional requirements, there are no alternative ready-made software products to the in-house development we have chosen.

The Aesthetics of Retrieval: Beautiful Data, Glitch Art and Popular Culture

At a time when the meaning of democracy is challenged by the power of algorithms and the politics of misinformation what has become apparent is that the valorisation of data is the defining characteristic of contemporary digital capitalism. In the marketing of ‘Big Data’ different forms of visualisation (dataviz) are employed to support the claim that a series of perfect signals can be abstracted from the background noise of the world’s incessant uploading of information. At the same time, ‘glitch’ artists and musicians have developed techniques which deliberately disrupt digital signals, randomly re-assorting ordered sequences to privilege noise over signal and aestheticize error. This paper will examine glitch as an artform which deconstructs the aesthetics of dataviz at the same time as it exposes what must remain hidden for it to retain value. It will propose a critical technique through which glitch artefacts in popular culture can be employed to explore the oppositional politics of posthuman subjects.

Application of hyper-convergent platform for big data in exploring regional innovation systems

The authors developed a decentralised hyper-convergent analytical platform for the collection and processing of big data in order to explore the monitoring processes of distributed objects in the regions on the basis of multi-agent approach. The platform is intended for modular integration of tools for searching, collecting, processing and big data mining from cyber-physical and cyber-social objects. The results of the intellectual analysis are used to assess the integrated criteria for the effectiveness of innovation systems of distributed monitoring and forecasting the dynamics of the influence of various factors on technological and socio-economic processes. The work analyses convergent and hyper-convergent systems, substantiates the necessity of creating a multi-agent decentralised platform for big data collection and analytical processing. The article proposes the principles of streaming architecture for the data integration analytical processing to resolve the problems of searching, parallel processing, data mining and uploading of information into a cloud storage. The paper also considers the main components of the hyper-convergent analytical platform. A new concept of distributed extraction, transformation, loading, mining (ETLM) system is considered.

CATE: Cloud-Aided Trustworthiness Evaluation Scheme for Incompletely Predictable Vehicular Ad Hoc Networks

Incompletely predictable vehicular ad hoc networks (IPNs) are presented for vehicular networks with vehicles moving in particular ranges. A group of vehicles in the same region are required to encrypt and sign the uploaded region information in IPNs. So far, research has not been able to provide an appropriate trustworthiness evaluation system ensuring security and fairness in IPNs. In this paper, we first establish an evaluation system for vehicles in the network for secure and fair trustworthiness evaluation. Various vehicle attributes are utilized to evaluate the trustworthiness level of a vehicle. The novel trustworthiness evaluation can provide a more comprehensive and real-time update of vehicle status. Second, based on the system, we propose a cloud-aided trustworthiness evaluation (CATE) scheme. According to the evaluation results provided by the system, the CATE scheme also guarantees lightweight trustworthiness level confirmation with the help of session key generation. Besides, the information upload security is ensured with group signature and encryption. The security proof indicates that the proposed CATE scheme is secure for vehicles in IPNs to interact with trustworthiness. According to quantitative comparative analysis and experimental simulation based on paring-based cryptography (PBC) library, the designed scheme has been proved to be efficient.

Development of the Twikle CRM system

This article presents an analysis of trends in the development of the information technology market. The development of the content management systems (CMS) is traced from its origin. The tools designed to create such systems are considered. First of all, these are programming languages and technology companies working in this field. It is no secret that the development of the Internet is primarily associated with the development of the sources of information, that is, with the websites. Currently, there constantly appear much easier ways of website creation and the procedure of information uploading is getting significantly simplified year by year. A brief analysis of programming languages for creating websites is given. The possibilities and tools for creating CMS augmented with a number of frameworks to speed up the development exponentially and having other advantages as well are dwelt upon. The functional capabilities of CRM-systems both in general and for the development of the whole business, especially the online segment are presented. The article substantiates the necessity for the implementation of CRM system and describes the main features of the system.

Relación de los menores con las redes sociales y el whatsapp: causas y consecuencias.

En la actualidad, el smartphone y las Redes Sociales se han convertido en elementos casi obligados para todo el mundo, desde edades muy tempranas, constituyendo una nueva y poderosa forma de socialización, con funciones relacionales y comunicativas tan potentes que, si no utilizas alguna de ellas, parece que ‘no existes’. Y éste es, precisamente, el motivo que nos ha llevado a desarrollar el presente trabajo, donde pretendemos estudiar las causas y consecuencias derivadas del tipo de relación establecida por los menores con las Redes Sociales y el WhatsApp. Se analiza la influencia de algunos factores como la autoestima y la necesidad de atención y reconocimiento social –llegando incluso al narcisismo– cristalizada en la incesante ‘subida’ (publicación) de fotos e información personal, así como otras consecuencias negativas que pueden derivarse de una utilización poco responsable y/o abusiva, como la dificultad para interaccionar con otros fuera de una pantalla o las posibilidades de control del otro que otorgan. Asimismo, se pretenden analizar los motivos que hacen tan atractivas estas herramientas y cómo afectan a la vida de los usuarios, centrándonos en diferentes aspectos del comportamiento social de los mismos. Para llevar a cabo la investigación se utilizó una metodología cuantitativa, a través de un cuestionario a d h o c , de elaboración propia, aplicado a una muestra de alumnos de la provincia de Salamanca, obteniendo una muestra final de n =134, con menores estudiantes de ESO, Bachillerato y FP , con media de edad de 14,8 años. Los resultados permiten concluir que estas herramientas pueden llegar a suponer una importante limitación en la vida de los usuarios, dificultado aspectos de su vida social, llegando incluso a que su estado de ánimo dependa de la retroalimentación obtenida en las redes a través de las publicaciones, no siendo tan sencillo como piensan desvincularse de ellas.

Intelligent agent-based region division scheme for mobile sensor networks

Mobile sensor networks (MSNs) are networks where nodes are dynamic and communicate with each other in wireless form. Many researchers focus on designing proper routing and energy conservation schemes for MSNs. However, for group authentication and local information upload in MSNs, a proper region division scheme is necessary. In this paper, we design a region division scheme based on intelligent agent which evaluates trustworthiness of nodes for MSNs. The trustworthiness evaluation is performed according to the important data collected by sensors on nodes. Taking vehicular networks as an example, some parameters, such as remaining gasoline and total mileage, determine the trustworthiness of a vehicle as a node in its network. The simulation indicates that our proposed scheme can achieve appropriate region division and packet delivery ratio with reasonable overhead and delay.

A Wireless Sensor Monitoring Node Based on Automatic Tracking Solar-Powered Panel for Paddy Field Environment

In order to realize the collection, management, visualization, and uploading of real-time information in the paddy field, an information monitoring node based on automatic tracking solar-powered panel is presented in this paper. First, the node consists of information collecting sensors, STM32 MCU, LCD, GPRS module, automatic tracking solar-powered module, and monitoring interface. Second, data gathered from sensors can be displayed on the LCD and sent to the host computer interface. Moreover, host computer can also save the data packages to management server for examination and analysis. Finally, in the practical test, data are gathered every 2 h. At nontest time, the node works in low-power mode to achieve rational use of electric energy. The results of this experiment show that the node can achieve an accurate transmission and display of data, and the power supply system can meet the demand for electricity in continuous rainy days.

115 Allelechecker: An online tool to count rare alleles and reduce upload of faulty information to bone marrow databases

Aim HLA registries are a key resource to bone marrow donor programs, since they allow the selection of donors that are most likely to be compatible with patients in need for transplant. In order to be economically viable, this process usually employs analysis in three levels of resolution: low-resolution that only determines the allele group, medium-resolution that produces a list of possible allele codes and high-resolution level that uses DNA sequencing to determine the definitive allele code for the donor. However, all these methods are susceptible to error and could result in upload of faulty information to the genetic databases. If a certain donor presents rare allele codes (non common nor well documented – NCWD) this could be a good indicator that the analysis is probably wrong. In this work, we propose and develop an online tool that receives a CSV file (e.g. Fusion® report) containing medium and high-resolution genetic information of different donors and lists the number of common (C), well documented (WD) and NCWD alleles. Methods In the case of medium-resolution samples, which contains the locus, allele group and NMDP code, the system checks all possible alleles related to that NMDP code and locus, producing a list of C, WD and NCWD counters. A report in the form of a CSV file is also generated, so that the lab technician can double-check the analysis on donors that presented only NCWD alleles. The system also allows administrator users to update CWD and NCWD allele lists as well as the list of NMDP codes. Results The figure below shows an example of an analysis report produced by AlleleChecker. Conclusions An alpha version of the system is being evaluated by the HLA lab of Rio de Janeiro State Uniersity and can be a valuable tool to improve the quality of data stored in the Brazilian National Registry of Bone Marrow Donors (REDOME). Download high-res image (117KB) Download full-size image