This study analyzes the User Interface(UI)and User Experience(UX)of information systems that provide local government information.The systems analyzed are the Local Administrative Comprehensive Information Disclosure ...This study analyzes the User Interface(UI)and User Experience(UX)of information systems that provide local government information.The systems analyzed are the Local Administrative Comprehensive Information Disclosure System(Zheripan),the Integrated Local Financial Disclosure System(Qinching Online),and the Local Regulations Information System(12348 Zhejiang Legal Network).The Local Administrative Comprehensive Information Disclosure System offers public service and personnel information,while the Integrated Local Financial Disclosure System provides financial information,and the Local Regulations Information System offers legal information as its main content.The analysis framework utilized three elements:objective data,psychological factors,and heuristic evaluation.The results of the first objective data analysis show that approximately 70%of visits to Zheripan and Qinching Online are through search,and the time spent on the homepage is short.In contrast,about 70%of visits to the 12348 Zhejiang Legal Network are direct visits,with users browsing multiple pages with a clear purpose.In terms of data provision methods,Zheripan provides two types of data in three formats,Qinching Online offers 28 types of data in five formats,and 12348 Zhejiang Legal Network provides one type of information in a single format.The second psychological factor analysis found that all three websites had a number of menus suitable for short-term cognitive capacity.However,only one of the sites had a layout that considered the user’s eye movement.Finally,the heuristic evaluation revealed that most of the evaluation criteria were not met.While the design is relatively simple and follows standards,feedback for users,error prevention,and help options were lacking.Moreover,the user-specific usability was low,and the systems remained at the information-providing level.Based on these findings,both short-term and long-term improvement measures for creating an interactive system beyond simple information disclosure are proposed.展开更多
The uplink massive multiple-input multiple-output(MIMO)status update system is very concerned about information freshness performance,especially for some central control Internet of Things(IoT)applications.In this con...The uplink massive multiple-input multiple-output(MIMO)status update system is very concerned about information freshness performance,especially for some central control Internet of Things(IoT)applications.In this context,age of information(AoI),as the metric of information freshness,gets more and more recognition,and simultaneously,the status packet blocklength plays an important role in improving the information freshness.In this work,we firstly consider a case with perfect channel state information(CSI)at the base station(BS),and derive the closed-form expression of the average AoI by using the Shannon theory.Guided by this,we obtain the tradeoff relationship among the status packet blocklength,transmission time and transmission failure probability.Accordingly,we optimize the status packet blocklength to minimize the average AoI.Then,we consider a more practical case with finite blocklength and imperfect CSI at the BS.In this case,we exploit pilot sequence to assist channel estimation,and derive an approximated closed-form expression of the average AoI according to short packet communication theory.It is found that increasing pilot block-length can improve the accuracy of channel estimation but reduce the frequency of status updates.Hence,we jointly optimize the pilot blocklength and status packet blocklength to improve the AoI performance.Extensive simulation results validate that the proposed methods can achieve almost the same performance as the exhaustive search methods.展开更多
In multiple Unmanned Aerial Vehicles(UAV)systems,achieving efficient navigation is essential for executing complex tasks and enhancing autonomy.Traditional navigation methods depend on predefined control strategies an...In multiple Unmanned Aerial Vehicles(UAV)systems,achieving efficient navigation is essential for executing complex tasks and enhancing autonomy.Traditional navigation methods depend on predefined control strategies and trajectory planning and often perform poorly in complex environments.To improve the UAV-environment interaction efficiency,this study proposes a multi-UAV integrated navigation algorithm based on Deep Reinforcement Learning(DRL).This algorithm integrates the Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),and Visual Navigation System(VNS)for comprehensive information fusion.Specifically,an improved multi-UAV integrated navigation algorithm called Information Fusion with MultiAgent Deep Deterministic Policy Gradient(IF-MADDPG)was developed.This algorithm enables UAVs to learn collaboratively and optimize their flight trajectories in real time.Through simulations and experiments,test scenarios in GNSS-denied environments were constructed to evaluate the effectiveness of the algorithm.The experimental results demonstrate that the IF-MADDPG algorithm significantly enhances the collaborative navigation capabilities of multiple UAVs in formation maintenance and GNSS-denied environments.Additionally,it has advantages in terms of mission completion time.This study provides a novel approach for efficient collaboration in multi-UAV systems,which significantly improves the robustness and adaptability of navigation systems.展开更多
The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)den...The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)denial conditions.Therefore,this paper proposes a UAV Clusters Information Geometry Fusion Positioning(UC-IGFP)method using pseudoranges from the LEO satellites.A novel graph model for linking and computing between the UAV clusters and LEO satellites was established.By utilizing probability to describe the positional states of UAVs and sensor errors,the distributed multivariate Probability Fusion Cooperative Positioning(PF-CP)algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster.Criteria to select the centroid of the cluster were set.A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory,which overcomes the discontinuity problem caused by the change of cluster centroids.Finally,the UC-IGFP method achieves the LEO continuous highprecision positioning of UAV clusters.The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster.It significantly improves the accuracy and reliability of LEO-UAV cluster positioning.The results of comprehensive simulation experiments show that the proposed method has a 30.5%improvement in performance over the mainstream positioning methods,with a positioning error of 14.267 m.展开更多
Objectives:This study aimed to evaluate the measurement properties and methodological quality of instruments developed to evaluate the quality of online health information.Methods:In this study,a systematic search was...Objectives:This study aimed to evaluate the measurement properties and methodological quality of instruments developed to evaluate the quality of online health information.Methods:In this study,a systematic search was conducted across a range of databases,including the China National Knowledge Infrastructure(CNKI),Wanfang,China Science and Technology Journal(VIP),SinoMed,PubMed,Web of Science,CINAHL,Embase,the Cochrane Library,PsycINFO,and Scopus.The search period spanned from the inception of the databases to October 2023.Two researchers independently conducted the literature screening and data extraction.The methodological quality of the included studies was assessed using the Consensus-based Standards for the Selection of Health Measurement Instruments(COSMIN)Risk of Bias checklist.The measurement properties were evaluated using the coSMIN criteria.The modified Grading,Recommendations,Assessment,Development,and Evaluation(GRADE)system was used to determine the quality grade.Results:A total of 18 studies were included,and the measurement properties of 17 scales were assessed.Fifteen scales had content validity,three had structural validity,six had internal consistency,two had test-retest reliability,nine had interater reliability,one had measurement error,six instruments had criterion validity,and three scales had hypotheses testing for construct validity;however,the evaluation of their methodological quality and measurement properties revealed deficiencies.Of these 17 scales,15 were assigned a Level B recommendation,and two received a Level C recommendation.Conclusions:The Health Information Website Evaluation Tool(HIWET)can be temporarily used to evaluate the quality of health information on websites.The Patient Education Materials Assessment Tool(PEMAT)can temporarily assess the quality of video-based health information.However,the effectiveness of both tools needs to be further verified.展开更多
This study aims to explore the application of SysTrust Theory in Accounting Information Systems(AIS)through a systematic literature review.SysTrust Theory,developed by the AICPA(2017),focuses on the reliability of inf...This study aims to explore the application of SysTrust Theory in Accounting Information Systems(AIS)through a systematic literature review.SysTrust Theory,developed by the AICPA(2017),focuses on the reliability of information systems by assessing aspects such as availability,integrity,security,confidentiality,and privacy.This study analyzed several related articles published between 2012 and 2025,identifying the positive impacts of implementing SysTrust Theory on AIS effectiveness,business performance,financial reporting quality,and organizational commitment.The results showed that integrity was the most dominant factor in improving AIS reliability,followed by security and privacy.The implementation of SysTrust has also been shown to reduce the risk of fraud,improve the accuracy of financial data,and support strategic decision making.However,challenges such as user uncertainty about electronic payment systems and technology adaptation continue to be obstacles.This study recommends the need to improve system quality,educate users,and strengthen internal controls to optimize the benefits of SysTrust Theory in business practices.展开更多
To improve the level of sports social management,to achieve standardized management,quick query,scientific statistics of sports social information,and to meet the needs of sports organizers,social platform managers,an...To improve the level of sports social management,to achieve standardized management,quick query,scientific statistics of sports social information,and to meet the needs of sports organizers,social platform managers,and other users,this paper introduces a sports social management system based on Spring Boot.The system uses Eclipse for Java Web development,selects MySQL 5.6 database as the background data storage solution,uses Java language to write code,and uses Tomcat server to build the running environment of applications.The system has the function of adding,deleting,changing and checking sports activities,supporting the input,query and statistical analysis of users’sports results,sports consumption and sports distance,and also allows to add,delete,modify and query the information of sports friends,aiming to provide users with a comprehensive and efficient sports social information management platform.展开更多
Enterprise Resource Planning(ERP)systems play a pivotal role in modern organizations by integrating business processes,enhancing operational efficiency,and supporting decision-making.Evaluating the success of ERP impl...Enterprise Resource Planning(ERP)systems play a pivotal role in modern organizations by integrating business processes,enhancing operational efficiency,and supporting decision-making.Evaluating the success of ERP implementations remains a critical challenge for both researchers and practitioners.The DeLone&McLean(D&M)Information Systems(IS)Success Model has been widely adopted as a theoretical framework to assess ERP success,yet its application in dynamic and evolving technological landscapes requires further examination.This systematic review synthesizes empirical studies from 2017 to 2024 that apply the D&M Model to evaluate ERP system success.The study aims to:(1)identify key trends in the application of the D&M Model across different organizational and technological contexts,(2)analyze the most influential success factors-system quality,information quality,service quality,user satisfaction,use,and net benefits-and their interrelationships,and(3)highlight emerging challenges and opportunities for refining the model in ERP research.Findings reveal that while the D&M Model provides a robust foundation for assessing ERP success,contextual factors such as organizational climate,leadership support,and mandatory vs.voluntary usage significantly influence outcomes.Additionally,advancements in digital transformation,AI,and cloud-based ERP systems introduce new dimensions that the traditional model may not fully capture.The review also identifies gaps in longitudinal studies and cross-cultural validations of the D&M Model in ERP settings.Based on the analysis,this paper proposes an enhanced framework that integrates dynamic moderators and post-implementation metrics to better align the D&M Model with contemporary ERP environments.The study contributes to IS literature by offering a comprehensive evaluation of the D&M Model’s applicability and limitations in ERP research,while providing actionable insights for organizations seeking to optimize ERP success.展开更多
Flip-flow screens offer unique advantages in grading fine-grained materials.To address inaccuracies caused by sensor vibra-tions in traditional contact measurement methods,we constructed a non-invasive measurement sys...Flip-flow screens offer unique advantages in grading fine-grained materials.To address inaccuracies caused by sensor vibra-tions in traditional contact measurement methods,we constructed a non-invasive measurement system based on electrical and optical sig-nals.A trajectory tracking algorithm for the screen-body was developed to visually measure the kinematics.Employing the principle oflaser reflection for distance measurement,optical techniques were performed to capture the kinematic information of the screen-plate.Ad-ditionally,by using Wi-Fi and Bluetooth transmission of electrical signals,tracer particle tracking technology was implemented to elec-trically measure the kinematic information of mineral particles.Consequently,intelligent fusion and perception of the kinematic informa-tion for the screen-body,screen-plate,and particles in the screening system have been achieved.展开更多
Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and...Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and Question-Answering framework powered by an enhanced LLM that integrates a semantic vector database and a curated literature repository.The ERQA framework leverages domain-specific incremental pretraining and conducts supervised fine-tuning on medical literature,enabling retrieval and question-answering(QA)tasks to be completed with high precision.Performance evaluations implemented on the coronavirus disease 2019(COVID-19)and TripClick data-sets demonstrate the robust capabilities of ERQA across multiple tasks.On the COVID-19 dataset,ERQA-13B achieves state-of-the-art retrieval metrics,with normalized discounted cumulative gain at top 10(NDCG@10)0.297,recall values at top 10(Recall@10)0.347,and mean reciprocal rank(MRR)=0.370;it also attains strong abstract summarization performance,with a recall-oriented understudy for gisting evaluation(ROUGE)-1 score of 0.434,and QA performance,with a bilingual evaluation understudy(BLEU)-1 score of 7.851.The comparable performance achieved on the TripClick dataset further under-scores the adaptability of ERQA across diverse medical topics.These findings suggest that ERQA repre-sents a significant step toward efficient biomedical knowledge retrieval and QA.展开更多
Quantum information masking(QIM)is a crucial technique for protecting quantum data from being accessed by local subsystems.In this paper,we introduce a novel method for achieving1-uniform QIM in multipartite systems u...Quantum information masking(QIM)is a crucial technique for protecting quantum data from being accessed by local subsystems.In this paper,we introduce a novel method for achieving1-uniform QIM in multipartite systems utilizing a Fourier matrix.We further extend this approach to construct an orthogonal array with the aid of a Hadamard matrix,which is a specific type of Fourier matrix.This allows us to explore the relationship between 2-uniform QIM and orthogonal arrays.Through this framework,we derive two distinct 2-uniform quantum states,enabling the 2-uniform masking of original information within multipartite systems.Furthermore,we prove that the maximum number of quantum bits required for achieving a2-uniformly masked state is 2^(n)-1,and the minimum is 2^(n-1)+3.Moreover,our scheme effectively demonstrates the rich quantum correlations between multipartite systems and has potential application value in quantum secret sharing.展开更多
The evolution of enabling technologies in wireless communications has paved the way for supporting novel applications with more demanding QoS requirements,but at the cost of increasing the complexity of optimizing the...The evolution of enabling technologies in wireless communications has paved the way for supporting novel applications with more demanding QoS requirements,but at the cost of increasing the complexity of optimizing the digital communication chain.In particular,Millimeter Wave(mmWave)communications provide an abundance of bandwidth,and energy harvesting supplies the network with a continual source of energy to facilitate self-sustainability;however,harnessing these technologies is challenging due to the stochastic dynamics of the mmWave channel as well as the random sporadic nature of the harvested energy.In this paper,we aim at the dynamic optimization of update transmissions in mmWave energy harvesting systems in terms of Age of Information(AoI).AoI has recently been introduced to quantify information freshness and is a more stringent QoS metric compared to conventional delay and throughput.However,most prior art has only addressed averagebased AoI metrics,which can be insufficient to capture the occurrence of rare but high-impact freshness violation events in time-critical scenarios.We formulate a control problem that aims to minimize the long-term entropic risk measure of AoI samples by configuring the“sense&transmit”of updates.Due to the high complexity of the exponential cost function,we reformulate the problem with an approximated mean-variance risk measure as the new objective.Under unknown system statistics,we propose a two-timescale model-free risk-sensitive reinforcement learning algorithm to compute a control policy that adapts to the trio of channel,energy,and AoI states.We evaluate the efficiency of the proposed scheme through extensive simulations.展开更多
Background: The availability of essential medicines and medical supplies is crucial for effectively delivering healthcare services. In Zambia, the Logistics Management Information System (LMIS) is a key tool for manag...Background: The availability of essential medicines and medical supplies is crucial for effectively delivering healthcare services. In Zambia, the Logistics Management Information System (LMIS) is a key tool for managing the supply chain of these commodities. This study aimed to evaluate the effectiveness of LMIS in ensuring the availability of essential medicines and medical supplies in public hospitals in the Copperbelt Province of Zambia. Materials and Methods: From February to April 2022, a cross-sectional study was conducted in 12 public hospitals across the Copperbelt Province. Data were collected using structured questionnaires, checklists, and stock control cards. The study assessed LMIS availability, training, and knowledge among pharmacy personnel, as well as data accuracy, product availability, and order fill rates. Descriptive statistics were used to analyse the data. Results: All surveyed hospitals had LMIS implemented and were using eLMIS as the primary LMIS. Only 47% and 48% of pharmacy personnel received training in eLMIS and Essential Medicines Logistics Improvement Program (EMLIP), respectively. Most personnel demonstrated good knowledge of LMIS, with 77.7% able to log in to eLMIS Facility Edition, 76.6% able to locate stock control cards in the system, and 78.7% able to perform transactions. However, data accuracy from physical and electronic records varied from 0% to 60%, and product availability ranged from 50% to 80%. Order fill rates from Zambia Medicines and Medical Supplies Agency (ZAMMSA) were consistently below 30%. Discrepancies were observed between physical stock counts and eLMIS records. Conclusion: This study found that most hospitals in the Copperbelt Province of Zambia have implemented LMIS use. While LMIS implementation is high in the Copperbelt Province of Zambia, challenges such as low training levels, data inaccuracies, low product availability, and order fill rates persist. Addressing these issues requires a comprehensive approach, including capacity building, data quality improvement, supply chain coordination, and investment in infrastructure and human resources. Strengthening LMIS effectiveness is crucial for improving healthcare delivery and patient outcomes in Zambia.展开更多
For any country,the availability of electricity is crucial to the development of the national economy and society.As a result,decision-makers and policy-makers can improve the sustainability and security of the energy...For any country,the availability of electricity is crucial to the development of the national economy and society.As a result,decision-makers and policy-makers can improve the sustainability and security of the energy supply by implementing a variety of actions by using the evaluation of these factors as an early warning system.This research aims to provide a multi-criterion decision-making(MCDM)method for assessing the sustainability and security of the electrical supply.The weights of criteria,which indicate their relative relevance in the assessment of the sustainability and security of the energy supply,the MCDM method allow users to express their opinions.To overcome the impact of uncertainty and vagueness of expert opinion,we explore the notion of picture fuzzy theory,which is a more efficient and dominant mathematical model.Recently,the theory of Aczel-Alsina operations has attained a lot of attraction and has an extensive capability to acquire smooth approximated results during the aggregation process.However,Choquet integral operators are more flexible and are used to express correlation among different attributes.This article diagnoses an innovative theory of picture fuzzy set to derive robust mathematical methodologies of picture fuzzy Choquet Integral Aczel-Alsina aggregation operators.To prove the intensity and validity of invented approaches,some dominant properties and special cases are also discussed.An intelligent decision algorithm for the MCDM problem is designed to resolve complicated real-life applications under multiple conflicting criteria.Additionally,we discussed a numerical example to investigate a suitable electric transformer under consideration of different beneficial key criteria.A comparative study is established to capture the superiority and effectiveness of pioneered mathematical approaches with existing methodologies.展开更多
Relevant documents issued by the General Office of the State Council and the Ministry of Health require hospitals to reduce operating costs and improve efficiency,which will place newer and higher demands on medical e...Relevant documents issued by the General Office of the State Council and the Ministry of Health require hospitals to reduce operating costs and improve efficiency,which will place newer and higher demands on medical equipment management.However,the current process of medical equipment quality control in hospitals faces issues such as weak control awareness,untimely maintenance of faulty equipment,and a lack of informatization management tools.These problems severely restrict the development of medical equipment quality management.To address these issues,this article uses a tertiary hospital in Urumqi as an experimental platform to analyze the deficiencies in the current medical equipment quality control management system of public hospitals.Based on practical needs such as equipment procurement,contract management,and equipment management,the research is conducted from three aspects:system architecture,functional design,and talent training,utilizing an information management system.Suggestions are provided,aiming to make a modest contribution to promoting medical equipment quality control management in China.展开更多
Purpose-The rapid development of China’s railway construction has led to an increase in data generated by the high-speed rail(HSR)catenary system.Traditional management methods struggle with challenges such as poor i...Purpose-The rapid development of China’s railway construction has led to an increase in data generated by the high-speed rail(HSR)catenary system.Traditional management methods struggle with challenges such as poor information sharing,disconnected business applications and insufficient intelligence throughout the lifecycle.This study aims to address these issues by applying building information modeling(BIM)technology to improve lifecycle management efficiency for HSR catenary systems.Design/methodology/approach-Based on the lifecycle management needs of catenary engineering,incorporating the intelligent HSR“Model-Data Driven,Axis-Plane Coordination”philosophy,this paper constructs a BIM-based lifecycle management framework for HSR catenary engineering.Findings-This study investigates the full-process lifecycle management of the catenary system across various stages of design,manufacture,construction and operation,exploring integrated BIM models and data transmission methods,along with key technologies for BIM model transmission,transformation and lightweighting.Originality/value-This study establishes a lossless information circulation and transmission system for HSR catenary lifecycle management.Multi-stage applications are verified through the construction of the Chongqing-Kunming High-Speed Railway,comprehensive advancing the intelligent promotion and highquality development of catenary engineering.展开更多
Squeezed reservoir engineering is a powerful technique in quantum information that combines the features of squeezing and reservoir engineering to create and stabilize non-classical quantum states. In this paper, we f...Squeezed reservoir engineering is a powerful technique in quantum information that combines the features of squeezing and reservoir engineering to create and stabilize non-classical quantum states. In this paper, we focus on the previously neglected aspect of the impact of the squeezing phase on the precision of quantum phase and amplitude estimation based on a simple model of a two-level system(TLS) interacting with a squeezed reservoir. We derive the optimal squeezed phase-matching conditions for phase φ and amplitude θ parameters, which are crucial for enhancing the precision of quantum parameter estimation. The robustness of the squeezing-enhanced quantum Fisher information against departures from these conditions is examined, demonstrating that minor deviations from phase-matching can still result in remarkable precision of estimation. Additionally, we provide a geometric interpretation of the squeezed phase-matching conditions from the classical motion of a TLS on the Bloch sphere. Our research contributes to a deeper understanding of the operational requirements for employing squeezed reservoir engineering to advance quantum parameter estimation.展开更多
Ensuring information security in the quantum era is a growing challenge due to advancements in cryptographic attacks and the emergence of quantum computing.To address these concerns,this paper presents the mathematica...Ensuring information security in the quantum era is a growing challenge due to advancements in cryptographic attacks and the emergence of quantum computing.To address these concerns,this paper presents the mathematical and computer modeling of a novel two-dimensional(2D)chaotic system for secure key generation in quantum image encryption(QIE).The proposed map employs trigonometric perturbations in conjunction with rational-saturation functions and hence,named as Trigonometric-Rational-Saturation(TRS)map.Through rigorous mathematical analysis and computational simulations,the map is extensively evaluated for bifurcation behaviour,chaotic trajectories,and Lyapunov exponents.The security evaluation validates the map’s non-linearity,unpredictability,and sensitive dependence on initial conditions.In addition,the proposed TRS map has further been tested by integrating it in a QIE scheme.The QIE scheme first quantum-encodes the classic image using the Novel Enhanced Quantum Representation(NEQR)technique,the TRS map is used for the generation of secure diffusion key,which is XOR-ed with the quantum-ready image to obtain the encrypted images.The security evaluation of the QIE scheme demonstrates superior security of the encrypted images in terms of statistical security attacks and also against Differential attacks.The encrypted images exhibit zero correlation and maximum entropy with demonstrating strong resilience due to 99.62%and 33.47%results for Number of Pixels Change Rate(NPCR)and Unified Average Changing Intensity(UACI).The results validate the effectiveness of TRS-based quantum encryption scheme in securing digital images against emerging quantum threats,making it suitable for secure image encryption in IoT and edge-based applications.展开更多
Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment thr...Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment through passive beamforming.However,it is challenging to obtain instantaneous channel state information(I-CSI)for RIS,which obliges us to use statistical channel state information(S-CSI)to achieve passive beamforming.In this paper,RIS-aided multiple-input single-output(MISO)multi-user downlink communication system with correlated channels is investigated.Then,we formulate the problem of joint beamforming design at the AP and RIS to maximize the sum ergodic spectral efficiency(ESE)of all users to improve the network capacity.Since it is too hard to compute sum ESE,an ESE approximation is adopted to reformulate the problem into a more tractable form.Then,we present two joint beamforming algorithms,namely the singular value decomposition-gradient descent(SVD-GD)algorithm and the fractional programming-gradient descent(FP-GD)algorithm.Simulation results show the effectiveness of our proposed algorithms and validate that 2-bits quantizer is enough for RIS phase shifts implementation.展开更多
This article takes the current autonomous driving technology as the research background and studies the collaborative protection mechanism between its system-on-chip(SoC)functional safety and information security.It i...This article takes the current autonomous driving technology as the research background and studies the collaborative protection mechanism between its system-on-chip(SoC)functional safety and information security.It includes an introduction to the functions and information security of autonomous driving SoCs,as well as the main design strategies for the collaborative prevention and control mechanism of SoC functional safety and information security in autonomous driving.The research shows that in the field of autonomous driving,there is a close connection between the functional safety of SoCs and their information security.In the design of the safety collaborative protection mechanism,the overall collaborative protection architecture,SoC functional safety protection mechanism,information security protection mechanism,the workflow of the collaborative protection mechanism,and its strategies are all key design elements.It is hoped that this analysis can provide some references for the collaborative protection of SoC functional safety and information security in the field of autonomous driving,so as to improve the safety of autonomous driving technology and meet its practical application requirements.展开更多
文摘This study analyzes the User Interface(UI)and User Experience(UX)of information systems that provide local government information.The systems analyzed are the Local Administrative Comprehensive Information Disclosure System(Zheripan),the Integrated Local Financial Disclosure System(Qinching Online),and the Local Regulations Information System(12348 Zhejiang Legal Network).The Local Administrative Comprehensive Information Disclosure System offers public service and personnel information,while the Integrated Local Financial Disclosure System provides financial information,and the Local Regulations Information System offers legal information as its main content.The analysis framework utilized three elements:objective data,psychological factors,and heuristic evaluation.The results of the first objective data analysis show that approximately 70%of visits to Zheripan and Qinching Online are through search,and the time spent on the homepage is short.In contrast,about 70%of visits to the 12348 Zhejiang Legal Network are direct visits,with users browsing multiple pages with a clear purpose.In terms of data provision methods,Zheripan provides two types of data in three formats,Qinching Online offers 28 types of data in five formats,and 12348 Zhejiang Legal Network provides one type of information in a single format.The second psychological factor analysis found that all three websites had a number of menus suitable for short-term cognitive capacity.However,only one of the sites had a layout that considered the user’s eye movement.Finally,the heuristic evaluation revealed that most of the evaluation criteria were not met.While the design is relatively simple and follows standards,feedback for users,error prevention,and help options were lacking.Moreover,the user-specific usability was low,and the systems remained at the information-providing level.Based on these findings,both short-term and long-term improvement measures for creating an interactive system beyond simple information disclosure are proposed.
文摘The uplink massive multiple-input multiple-output(MIMO)status update system is very concerned about information freshness performance,especially for some central control Internet of Things(IoT)applications.In this context,age of information(AoI),as the metric of information freshness,gets more and more recognition,and simultaneously,the status packet blocklength plays an important role in improving the information freshness.In this work,we firstly consider a case with perfect channel state information(CSI)at the base station(BS),and derive the closed-form expression of the average AoI by using the Shannon theory.Guided by this,we obtain the tradeoff relationship among the status packet blocklength,transmission time and transmission failure probability.Accordingly,we optimize the status packet blocklength to minimize the average AoI.Then,we consider a more practical case with finite blocklength and imperfect CSI at the BS.In this case,we exploit pilot sequence to assist channel estimation,and derive an approximated closed-form expression of the average AoI according to short packet communication theory.It is found that increasing pilot block-length can improve the accuracy of channel estimation but reduce the frequency of status updates.Hence,we jointly optimize the pilot blocklength and status packet blocklength to improve the AoI performance.Extensive simulation results validate that the proposed methods can achieve almost the same performance as the exhaustive search methods.
基金co-supported by the National Natural Science Foundation of China(Nos.92371201 and 52192633)the Natural Science Foundation of Shaanxi Province of China(No.2022JC-03)the Aeronautical Science Foundation of China(No.ASFC-20220019070002)。
文摘In multiple Unmanned Aerial Vehicles(UAV)systems,achieving efficient navigation is essential for executing complex tasks and enhancing autonomy.Traditional navigation methods depend on predefined control strategies and trajectory planning and often perform poorly in complex environments.To improve the UAV-environment interaction efficiency,this study proposes a multi-UAV integrated navigation algorithm based on Deep Reinforcement Learning(DRL).This algorithm integrates the Inertial Navigation System(INS),Global Navigation Satellite System(GNSS),and Visual Navigation System(VNS)for comprehensive information fusion.Specifically,an improved multi-UAV integrated navigation algorithm called Information Fusion with MultiAgent Deep Deterministic Policy Gradient(IF-MADDPG)was developed.This algorithm enables UAVs to learn collaboratively and optimize their flight trajectories in real time.Through simulations and experiments,test scenarios in GNSS-denied environments were constructed to evaluate the effectiveness of the algorithm.The experimental results demonstrate that the IF-MADDPG algorithm significantly enhances the collaborative navigation capabilities of multiple UAVs in formation maintenance and GNSS-denied environments.Additionally,it has advantages in terms of mission completion time.This study provides a novel approach for efficient collaboration in multi-UAV systems,which significantly improves the robustness and adaptability of navigation systems.
基金supported in part by the National Natural Science Foundation of China(Nos.62171375,62271397,62001392,62101458,62173276,61803310 and 61801394)the Shenzhen Science and Technology Innovation ProgramChina(No.JCYJ20220530161615033)。
文摘The existing Low-Earth-Orbit(LEO)positioning performance cannot meet the requirements of Unmanned Aerial Vehicle(UAV)clusters for high-precision real-time positioning in the Global Navigation Satellite System(GNSS)denial conditions.Therefore,this paper proposes a UAV Clusters Information Geometry Fusion Positioning(UC-IGFP)method using pseudoranges from the LEO satellites.A novel graph model for linking and computing between the UAV clusters and LEO satellites was established.By utilizing probability to describe the positional states of UAVs and sensor errors,the distributed multivariate Probability Fusion Cooperative Positioning(PF-CP)algorithm is proposed to achieve high-precision cooperative positioning and integration of the cluster.Criteria to select the centroid of the cluster were set.A new Kalman filter algorithm that is suitable for UAV clusters was designed based on the global benchmark and Riemann information geometry theory,which overcomes the discontinuity problem caused by the change of cluster centroids.Finally,the UC-IGFP method achieves the LEO continuous highprecision positioning of UAV clusters.The proposed method effectively addresses the positioning challenges caused by the strong direction of signal beams from LEO satellites and the insufficient constraint quantity of information sources at the edge nodes of the cluster.It significantly improves the accuracy and reliability of LEO-UAV cluster positioning.The results of comprehensive simulation experiments show that the proposed method has a 30.5%improvement in performance over the mainstream positioning methods,with a positioning error of 14.267 m.
基金supported by President Foundation of the Third Affiliated Hospital of Southern Medical University(YH202207)。
文摘Objectives:This study aimed to evaluate the measurement properties and methodological quality of instruments developed to evaluate the quality of online health information.Methods:In this study,a systematic search was conducted across a range of databases,including the China National Knowledge Infrastructure(CNKI),Wanfang,China Science and Technology Journal(VIP),SinoMed,PubMed,Web of Science,CINAHL,Embase,the Cochrane Library,PsycINFO,and Scopus.The search period spanned from the inception of the databases to October 2023.Two researchers independently conducted the literature screening and data extraction.The methodological quality of the included studies was assessed using the Consensus-based Standards for the Selection of Health Measurement Instruments(COSMIN)Risk of Bias checklist.The measurement properties were evaluated using the coSMIN criteria.The modified Grading,Recommendations,Assessment,Development,and Evaluation(GRADE)system was used to determine the quality grade.Results:A total of 18 studies were included,and the measurement properties of 17 scales were assessed.Fifteen scales had content validity,three had structural validity,six had internal consistency,two had test-retest reliability,nine had interater reliability,one had measurement error,six instruments had criterion validity,and three scales had hypotheses testing for construct validity;however,the evaluation of their methodological quality and measurement properties revealed deficiencies.Of these 17 scales,15 were assigned a Level B recommendation,and two received a Level C recommendation.Conclusions:The Health Information Website Evaluation Tool(HIWET)can be temporarily used to evaluate the quality of health information on websites.The Patient Education Materials Assessment Tool(PEMAT)can temporarily assess the quality of video-based health information.However,the effectiveness of both tools needs to be further verified.
文摘This study aims to explore the application of SysTrust Theory in Accounting Information Systems(AIS)through a systematic literature review.SysTrust Theory,developed by the AICPA(2017),focuses on the reliability of information systems by assessing aspects such as availability,integrity,security,confidentiality,and privacy.This study analyzed several related articles published between 2012 and 2025,identifying the positive impacts of implementing SysTrust Theory on AIS effectiveness,business performance,financial reporting quality,and organizational commitment.The results showed that integrity was the most dominant factor in improving AIS reliability,followed by security and privacy.The implementation of SysTrust has also been shown to reduce the risk of fraud,improve the accuracy of financial data,and support strategic decision making.However,challenges such as user uncertainty about electronic payment systems and technology adaptation continue to be obstacles.This study recommends the need to improve system quality,educate users,and strengthen internal controls to optimize the benefits of SysTrust Theory in business practices.
基金College Students Innovation and Entrepreneurship Project of Pujiang College,Nanjing University of Technology(PJ202413905083)Natural Science Project of Pujiang College,Nanjing University of Technology(njpj2024-1-01)。
文摘To improve the level of sports social management,to achieve standardized management,quick query,scientific statistics of sports social information,and to meet the needs of sports organizers,social platform managers,and other users,this paper introduces a sports social management system based on Spring Boot.The system uses Eclipse for Java Web development,selects MySQL 5.6 database as the background data storage solution,uses Java language to write code,and uses Tomcat server to build the running environment of applications.The system has the function of adding,deleting,changing and checking sports activities,supporting the input,query and statistical analysis of users’sports results,sports consumption and sports distance,and also allows to add,delete,modify and query the information of sports friends,aiming to provide users with a comprehensive and efficient sports social information management platform.
文摘Enterprise Resource Planning(ERP)systems play a pivotal role in modern organizations by integrating business processes,enhancing operational efficiency,and supporting decision-making.Evaluating the success of ERP implementations remains a critical challenge for both researchers and practitioners.The DeLone&McLean(D&M)Information Systems(IS)Success Model has been widely adopted as a theoretical framework to assess ERP success,yet its application in dynamic and evolving technological landscapes requires further examination.This systematic review synthesizes empirical studies from 2017 to 2024 that apply the D&M Model to evaluate ERP system success.The study aims to:(1)identify key trends in the application of the D&M Model across different organizational and technological contexts,(2)analyze the most influential success factors-system quality,information quality,service quality,user satisfaction,use,and net benefits-and their interrelationships,and(3)highlight emerging challenges and opportunities for refining the model in ERP research.Findings reveal that while the D&M Model provides a robust foundation for assessing ERP success,contextual factors such as organizational climate,leadership support,and mandatory vs.voluntary usage significantly influence outcomes.Additionally,advancements in digital transformation,AI,and cloud-based ERP systems introduce new dimensions that the traditional model may not fully capture.The review also identifies gaps in longitudinal studies and cross-cultural validations of the D&M Model in ERP settings.Based on the analysis,this paper proposes an enhanced framework that integrates dynamic moderators and post-implementation metrics to better align the D&M Model with contemporary ERP environments.The study contributes to IS literature by offering a comprehensive evaluation of the D&M Model’s applicability and limitations in ERP research,while providing actionable insights for organizations seeking to optimize ERP success.
基金financially supported by ChinaNational Funds for Distinguished Young Scientists(No.52125403)National Natural Science Foundation of China(Nos.52261135540 and 52404303)Science and Tech-nology Plan Special Fund Project of Jiangsu Province,China(No.BZ2024046)。
文摘Flip-flow screens offer unique advantages in grading fine-grained materials.To address inaccuracies caused by sensor vibra-tions in traditional contact measurement methods,we constructed a non-invasive measurement system based on electrical and optical sig-nals.A trajectory tracking algorithm for the screen-body was developed to visually measure the kinematics.Employing the principle oflaser reflection for distance measurement,optical techniques were performed to capture the kinematic information of the screen-plate.Ad-ditionally,by using Wi-Fi and Bluetooth transmission of electrical signals,tracer particle tracking technology was implemented to elec-trically measure the kinematic information of mineral particles.Consequently,intelligent fusion and perception of the kinematic informa-tion for the screen-body,screen-plate,and particles in the screening system have been achieved.
基金supported by the Innovation Fund for Medical Sciences of the Chinese Academy of Medical Sciences(2021-I2M-1-033)the National Key Research and Development Program of China(2022YFF0711900).
文摘Recent advancements in large language models(LLMs)have driven remarkable progress in text process-ing,opening new avenues for medical knowledge discovery.In this study,we present ERQA,a mEdical knowledge Retrieval and Question-Answering framework powered by an enhanced LLM that integrates a semantic vector database and a curated literature repository.The ERQA framework leverages domain-specific incremental pretraining and conducts supervised fine-tuning on medical literature,enabling retrieval and question-answering(QA)tasks to be completed with high precision.Performance evaluations implemented on the coronavirus disease 2019(COVID-19)and TripClick data-sets demonstrate the robust capabilities of ERQA across multiple tasks.On the COVID-19 dataset,ERQA-13B achieves state-of-the-art retrieval metrics,with normalized discounted cumulative gain at top 10(NDCG@10)0.297,recall values at top 10(Recall@10)0.347,and mean reciprocal rank(MRR)=0.370;it also attains strong abstract summarization performance,with a recall-oriented understudy for gisting evaluation(ROUGE)-1 score of 0.434,and QA performance,with a bilingual evaluation understudy(BLEU)-1 score of 7.851.The comparable performance achieved on the TripClick dataset further under-scores the adaptability of ERQA across diverse medical topics.These findings suggest that ERQA repre-sents a significant step toward efficient biomedical knowledge retrieval and QA.
基金supported by the National Natural Science Foundation of China under Grant No.12301590Natural Science Foundation of Hebei Province under Grant No.A2022210002。
文摘Quantum information masking(QIM)is a crucial technique for protecting quantum data from being accessed by local subsystems.In this paper,we introduce a novel method for achieving1-uniform QIM in multipartite systems utilizing a Fourier matrix.We further extend this approach to construct an orthogonal array with the aid of a Hadamard matrix,which is a specific type of Fourier matrix.This allows us to explore the relationship between 2-uniform QIM and orthogonal arrays.Through this framework,we derive two distinct 2-uniform quantum states,enabling the 2-uniform masking of original information within multipartite systems.Furthermore,we prove that the maximum number of quantum bits required for achieving a2-uniformly masked state is 2^(n)-1,and the minimum is 2^(n-1)+3.Moreover,our scheme effectively demonstrates the rich quantum correlations between multipartite systems and has potential application value in quantum secret sharing.
文摘The evolution of enabling technologies in wireless communications has paved the way for supporting novel applications with more demanding QoS requirements,but at the cost of increasing the complexity of optimizing the digital communication chain.In particular,Millimeter Wave(mmWave)communications provide an abundance of bandwidth,and energy harvesting supplies the network with a continual source of energy to facilitate self-sustainability;however,harnessing these technologies is challenging due to the stochastic dynamics of the mmWave channel as well as the random sporadic nature of the harvested energy.In this paper,we aim at the dynamic optimization of update transmissions in mmWave energy harvesting systems in terms of Age of Information(AoI).AoI has recently been introduced to quantify information freshness and is a more stringent QoS metric compared to conventional delay and throughput.However,most prior art has only addressed averagebased AoI metrics,which can be insufficient to capture the occurrence of rare but high-impact freshness violation events in time-critical scenarios.We formulate a control problem that aims to minimize the long-term entropic risk measure of AoI samples by configuring the“sense&transmit”of updates.Due to the high complexity of the exponential cost function,we reformulate the problem with an approximated mean-variance risk measure as the new objective.Under unknown system statistics,we propose a two-timescale model-free risk-sensitive reinforcement learning algorithm to compute a control policy that adapts to the trio of channel,energy,and AoI states.We evaluate the efficiency of the proposed scheme through extensive simulations.
文摘Background: The availability of essential medicines and medical supplies is crucial for effectively delivering healthcare services. In Zambia, the Logistics Management Information System (LMIS) is a key tool for managing the supply chain of these commodities. This study aimed to evaluate the effectiveness of LMIS in ensuring the availability of essential medicines and medical supplies in public hospitals in the Copperbelt Province of Zambia. Materials and Methods: From February to April 2022, a cross-sectional study was conducted in 12 public hospitals across the Copperbelt Province. Data were collected using structured questionnaires, checklists, and stock control cards. The study assessed LMIS availability, training, and knowledge among pharmacy personnel, as well as data accuracy, product availability, and order fill rates. Descriptive statistics were used to analyse the data. Results: All surveyed hospitals had LMIS implemented and were using eLMIS as the primary LMIS. Only 47% and 48% of pharmacy personnel received training in eLMIS and Essential Medicines Logistics Improvement Program (EMLIP), respectively. Most personnel demonstrated good knowledge of LMIS, with 77.7% able to log in to eLMIS Facility Edition, 76.6% able to locate stock control cards in the system, and 78.7% able to perform transactions. However, data accuracy from physical and electronic records varied from 0% to 60%, and product availability ranged from 50% to 80%. Order fill rates from Zambia Medicines and Medical Supplies Agency (ZAMMSA) were consistently below 30%. Discrepancies were observed between physical stock counts and eLMIS records. Conclusion: This study found that most hospitals in the Copperbelt Province of Zambia have implemented LMIS use. While LMIS implementation is high in the Copperbelt Province of Zambia, challenges such as low training levels, data inaccuracies, low product availability, and order fill rates persist. Addressing these issues requires a comprehensive approach, including capacity building, data quality improvement, supply chain coordination, and investment in infrastructure and human resources. Strengthening LMIS effectiveness is crucial for improving healthcare delivery and patient outcomes in Zambia.
文摘For any country,the availability of electricity is crucial to the development of the national economy and society.As a result,decision-makers and policy-makers can improve the sustainability and security of the energy supply by implementing a variety of actions by using the evaluation of these factors as an early warning system.This research aims to provide a multi-criterion decision-making(MCDM)method for assessing the sustainability and security of the electrical supply.The weights of criteria,which indicate their relative relevance in the assessment of the sustainability and security of the energy supply,the MCDM method allow users to express their opinions.To overcome the impact of uncertainty and vagueness of expert opinion,we explore the notion of picture fuzzy theory,which is a more efficient and dominant mathematical model.Recently,the theory of Aczel-Alsina operations has attained a lot of attraction and has an extensive capability to acquire smooth approximated results during the aggregation process.However,Choquet integral operators are more flexible and are used to express correlation among different attributes.This article diagnoses an innovative theory of picture fuzzy set to derive robust mathematical methodologies of picture fuzzy Choquet Integral Aczel-Alsina aggregation operators.To prove the intensity and validity of invented approaches,some dominant properties and special cases are also discussed.An intelligent decision algorithm for the MCDM problem is designed to resolve complicated real-life applications under multiple conflicting criteria.Additionally,we discussed a numerical example to investigate a suitable electric transformer under consideration of different beneficial key criteria.A comparative study is established to capture the superiority and effectiveness of pioneered mathematical approaches with existing methodologies.
基金Urumqi Health Committee Science and Technology Plan Project(202343)。
文摘Relevant documents issued by the General Office of the State Council and the Ministry of Health require hospitals to reduce operating costs and improve efficiency,which will place newer and higher demands on medical equipment management.However,the current process of medical equipment quality control in hospitals faces issues such as weak control awareness,untimely maintenance of faulty equipment,and a lack of informatization management tools.These problems severely restrict the development of medical equipment quality management.To address these issues,this article uses a tertiary hospital in Urumqi as an experimental platform to analyze the deficiencies in the current medical equipment quality control management system of public hospitals.Based on practical needs such as equipment procurement,contract management,and equipment management,the research is conducted from three aspects:system architecture,functional design,and talent training,utilizing an information management system.Suggestions are provided,aiming to make a modest contribution to promoting medical equipment quality control management in China.
基金supported by China Academy of Railway Sciences Foundation(Research on Multi Agent Collaborative Mechanism of Intelligent High Speed Rail System Based on Complex Adaptive System Theory,Grant 2023YJ392).
文摘Purpose-The rapid development of China’s railway construction has led to an increase in data generated by the high-speed rail(HSR)catenary system.Traditional management methods struggle with challenges such as poor information sharing,disconnected business applications and insufficient intelligence throughout the lifecycle.This study aims to address these issues by applying building information modeling(BIM)technology to improve lifecycle management efficiency for HSR catenary systems.Design/methodology/approach-Based on the lifecycle management needs of catenary engineering,incorporating the intelligent HSR“Model-Data Driven,Axis-Plane Coordination”philosophy,this paper constructs a BIM-based lifecycle management framework for HSR catenary engineering.Findings-This study investigates the full-process lifecycle management of the catenary system across various stages of design,manufacture,construction and operation,exploring integrated BIM models and data transmission methods,along with key technologies for BIM model transmission,transformation and lightweighting.Originality/value-This study establishes a lossless information circulation and transmission system for HSR catenary lifecycle management.Multi-stage applications are verified through the construction of the Chongqing-Kunming High-Speed Railway,comprehensive advancing the intelligent promotion and highquality development of catenary engineering.
基金Project supported by the National Natural Science Foundation of China (Grant No. 12265004)Jiangxi Provincial Natural Science Foundation (Grant No. 20242BAB26010)+1 种基金the National Natural Science Foundation of China (Grant No. 12365003)Jiangxi Provincial Natural Science Foundation (Grant Nos. 20212ACB211004 and 20212BAB201014)。
文摘Squeezed reservoir engineering is a powerful technique in quantum information that combines the features of squeezing and reservoir engineering to create and stabilize non-classical quantum states. In this paper, we focus on the previously neglected aspect of the impact of the squeezing phase on the precision of quantum phase and amplitude estimation based on a simple model of a two-level system(TLS) interacting with a squeezed reservoir. We derive the optimal squeezed phase-matching conditions for phase φ and amplitude θ parameters, which are crucial for enhancing the precision of quantum parameter estimation. The robustness of the squeezing-enhanced quantum Fisher information against departures from these conditions is examined, demonstrating that minor deviations from phase-matching can still result in remarkable precision of estimation. Additionally, we provide a geometric interpretation of the squeezed phase-matching conditions from the classical motion of a TLS on the Bloch sphere. Our research contributes to a deeper understanding of the operational requirements for employing squeezed reservoir engineering to advance quantum parameter estimation.
基金funded by Deanship of Research and Graduate Studies at King Khalid University.The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through Large Group Project under grant number(RGP.2/556/45).
文摘Ensuring information security in the quantum era is a growing challenge due to advancements in cryptographic attacks and the emergence of quantum computing.To address these concerns,this paper presents the mathematical and computer modeling of a novel two-dimensional(2D)chaotic system for secure key generation in quantum image encryption(QIE).The proposed map employs trigonometric perturbations in conjunction with rational-saturation functions and hence,named as Trigonometric-Rational-Saturation(TRS)map.Through rigorous mathematical analysis and computational simulations,the map is extensively evaluated for bifurcation behaviour,chaotic trajectories,and Lyapunov exponents.The security evaluation validates the map’s non-linearity,unpredictability,and sensitive dependence on initial conditions.In addition,the proposed TRS map has further been tested by integrating it in a QIE scheme.The QIE scheme first quantum-encodes the classic image using the Novel Enhanced Quantum Representation(NEQR)technique,the TRS map is used for the generation of secure diffusion key,which is XOR-ed with the quantum-ready image to obtain the encrypted images.The security evaluation of the QIE scheme demonstrates superior security of the encrypted images in terms of statistical security attacks and also against Differential attacks.The encrypted images exhibit zero correlation and maximum entropy with demonstrating strong resilience due to 99.62%and 33.47%results for Number of Pixels Change Rate(NPCR)and Unified Average Changing Intensity(UACI).The results validate the effectiveness of TRS-based quantum encryption scheme in securing digital images against emerging quantum threats,making it suitable for secure image encryption in IoT and edge-based applications.
基金partially supported by the National Key Research and Development Project under Grant 2020YFB1806805Science and Technology on Communication Networks Laboratorysupported by China Scholarship Council.
文摘Reconfigurable intelligent surface(RIS)is a promising candidate technology of the upcoming Sixth Generation(6G)communication system for its ability to provide unprecedented spectral and energy efficiency increment through passive beamforming.However,it is challenging to obtain instantaneous channel state information(I-CSI)for RIS,which obliges us to use statistical channel state information(S-CSI)to achieve passive beamforming.In this paper,RIS-aided multiple-input single-output(MISO)multi-user downlink communication system with correlated channels is investigated.Then,we formulate the problem of joint beamforming design at the AP and RIS to maximize the sum ergodic spectral efficiency(ESE)of all users to improve the network capacity.Since it is too hard to compute sum ESE,an ESE approximation is adopted to reformulate the problem into a more tractable form.Then,we present two joint beamforming algorithms,namely the singular value decomposition-gradient descent(SVD-GD)algorithm and the fractional programming-gradient descent(FP-GD)algorithm.Simulation results show the effectiveness of our proposed algorithms and validate that 2-bits quantizer is enough for RIS phase shifts implementation.
文摘This article takes the current autonomous driving technology as the research background and studies the collaborative protection mechanism between its system-on-chip(SoC)functional safety and information security.It includes an introduction to the functions and information security of autonomous driving SoCs,as well as the main design strategies for the collaborative prevention and control mechanism of SoC functional safety and information security in autonomous driving.The research shows that in the field of autonomous driving,there is a close connection between the functional safety of SoCs and their information security.In the design of the safety collaborative protection mechanism,the overall collaborative protection architecture,SoC functional safety protection mechanism,information security protection mechanism,the workflow of the collaborative protection mechanism,and its strategies are all key design elements.It is hoped that this analysis can provide some references for the collaborative protection of SoC functional safety and information security in the field of autonomous driving,so as to improve the safety of autonomous driving technology and meet its practical application requirements.
