To decrease the transmission delay of uplink voice over IP(VoIP)services in IEEE 802.16e sys-tem,a novel strategy which includes a load-balance algorithm and an extended earliest deadline first(EEDF)scheduling algorit...To decrease the transmission delay of uplink voice over IP(VoIP)services in IEEE 802.16e sys-tem,a novel strategy which includes a load-balance algorithm and an extended earliest deadline first(EEDF)scheduling algorithm is proposed.Subsequently,this paper analyzes the performance of the pro-posed strategy in terms of transmission delay of VoIP services,system capacity,throughput and compati-bility with IEEE 802 .16e standard.Finally,simulation experiments are carried out to verify the improve-ment of the proposed strategy.The simulation results match well with the theoretical analysis and showthat the proposed strategy reduces the transmission delay of uplink VoIP services and improves the capaci-ty and throughput.These improvements are remarkable especially when the load of system is heavy.展开更多
Fufang E’jiao Jiang(FEJ)as a healthy food consisting of medicine food homology materials approved by China’s Ministry of Health has been extensively applied to replenish qi and nourish blood,and it has a positive im...Fufang E’jiao Jiang(FEJ)as a healthy food consisting of medicine food homology materials approved by China’s Ministry of Health has been extensively applied to replenish qi and nourish blood,and it has a positive impact on women’s health.To find out the material basis and mechanism of FEJ,a systematic“compoundeffect-target”analysis including chemical composition resolution,zebrafish,network pharmacology,molecular docking,transcriptome,and bibliometric analysis was adopted.124 chemical components including ginsenosides,and phenylethanoid glycosides in FEJ were discovered,and effects of FEJ on promoting the generation of immune cells,erythropoiesis and angiogenesis in zebrafish were exhibited.Based on network pharmacology,molecular docking and in vivo activity assay,6 compounds including jionoside A1,isoacteoside,echinacoside,acteoside,lobetyolin,and rehmannioside D were identified as active components of FEJ.Transcriptome data showed that several pathways such as complement and coagulation cascades,ECM-receptor interaction,and PI3K-Akt signaling pathway were associated with proangiogenic effect of FEJ.19 common targets were obtained through combined analysis of network pharmacology and transcriptomics,and 5 targets of them were verified by PCR.The bibliometric analysis of these common targets revealed that FEJ was related to energy metabolism,pathway in cancer,etc.,which was consistent with the results of network pharmacology and transcriptome.The studies suggested that FEJ could replenish qi and nourish blood through multi-compound and multi-targets.展开更多
Smoking has a complex impact on the immune system, affecting both innate and adaptive immunity. It can exacerbate pathogenic immune responses and attenuate defensive immunity, leading to a higher susceptibility to inf...Smoking has a complex impact on the immune system, affecting both innate and adaptive immunity. It can exacerbate pathogenic immune responses and attenuate defensive immunity, leading to a higher susceptibility to infections and certain diseases. The chemicals in cigarette smoke, such as nicotine and carbon monoxide, can alter immune cell functions and inflammatory responses. Smoking can also have long-term effects on the immune system, with some changes persisting even after quitting [1]. According to a Penn Medicine Physician, the Medical Oncologist Dr. David Porter, “People who are smokers tend to get sicker from infections”, “It may be that smoking impacts the immune system’s ability to respond appropriately”. Thus, such individuals within smoking exposure history might be considered as immunocompromised due to the altered and weakened immune system. Cigarette smoking is a prevalent habit with far-reaching health implications. Among its many adverse effects, smoking significantly alters the immune system’s functionality [1].展开更多
A variety of test methodologies are commonly used to assess if a photovoltaic system can perform in line with expectations generated by a computer simulation. One of the commonly used methodologies across the PV indus...A variety of test methodologies are commonly used to assess if a photovoltaic system can perform in line with expectations generated by a computer simulation. One of the commonly used methodologies across the PV industry is an ASTM E2848. ASTM E2848-13, 2023 test method provides measurement and analysis procedures for determining the capacity of a specific photovoltaic system built in a particular place and in operation under natural sunlight. This test method is mainly used for acceptance testing of newly installed photovoltaic systems, reporting of DC or AC system performance, and monitoring of photovoltaic system performance. The purpose of the PV Capacity Test and modeled energy test is to verify that the integrated system formed from all components of the PV Project has a production capacity that achieves the Guaranteed Capacity and the Guaranteed modeled AEP under measured weather conditions that occur when each PV Capacity Test is conducted. In this paper, we will be discussing ASTM E2848 PV Capacity test plan purpose and scope, methodology, Selection of reporting conditions (RC), data requirements, calculation of results, reporting, challenges, acceptance criteria on pass/fail test results, Cure period, and Sole remedy for EPC contractors for bifacial irradiance.展开更多
The value of system assimilation is to improve working relationships between tutors and learners while increasing workflow efficiency among tertiary institutions with low operational costs. E-skills could be described...The value of system assimilation is to improve working relationships between tutors and learners while increasing workflow efficiency among tertiary institutions with low operational costs. E-skills could be described as electronic education development, to assist ICT professionals to reach their future career goals and aim to help users boost their ICT skills. In a society that is expanding, it is also a crucial issue to take into account. Researchers have turned their attention to this topic because of its significance and contribution to the empowerment of graduates in digital education. Many scholars have proposed many methods for integrating e-skills into society with impressive results, but the rising rate of graduate unemployment in South Africa is gradually becoming a big worry in our society. A model based on Activity Theory (AT) and e-skills will be developed in our tertiary institution to equip graduates with skills that will increase their employability and provide more individualized work opportunities as part of this study’s effort to solve this issue. With the use of the Statistical Package for the Social Sciences (SPSS) and Cronbach’s Alpha for validity and reliability testing, the study will create an experimental performance to assess the approach taken to measure e-skills in tertiary institutions to empower graduates in South Africa. The study established that system development and e-skilled models for tertiary institutions are growing gradually, especially in South African institutions, that empower graduates with profitable employability with experiences to improve work operation in the industries. In conclusion, system development and e-skills are very demanding but important to empower graduate employability to determine competency in the professional workforce.展开更多
Large Language Models (LLMs) have revolutionized Generative Artificial Intelligence (GenAI) tasks, becoming an integral part of various applications in society, including text generation, translation, summarization, a...Large Language Models (LLMs) have revolutionized Generative Artificial Intelligence (GenAI) tasks, becoming an integral part of various applications in society, including text generation, translation, summarization, and more. However, their widespread usage emphasizes the critical need to enhance their security posture to ensure the integrity and reliability of their outputs and minimize harmful effects. Prompt injections and training data poisoning attacks are two of the most prominent vulnerabilities in LLMs, which could potentially lead to unpredictable and undesirable behaviors, such as biased outputs, misinformation propagation, and even malicious content generation. The Common Vulnerability Scoring System (CVSS) framework provides a standardized approach to capturing the principal characteristics of vulnerabilities, facilitating a deeper understanding of their severity within the security and AI communities. By extending the current CVSS framework, we generate scores for these vulnerabilities such that organizations can prioritize mitigation efforts, allocate resources effectively, and implement targeted security measures to defend against potential risks.展开更多
Based on the structures of the short preamble and long preamble, which are defined for synchronization in IEEES02.16e specification, the robust synchronization algorithm for IEEES02.16e OFDM system is proposed. The co...Based on the structures of the short preamble and long preamble, which are defined for synchronization in IEEES02.16e specification, the robust synchronization algorithm for IEEES02.16e OFDM system is proposed. The correlations among the sample sequences in the preamble are investigated, especially the correlation between the first sample sequence and the last sample sequence in the long preamble. The conventional joint timing and frequency synchronization algorithm is reviewed based on the short preamble referring to the algorithm proposed by Schmidl, then a robust joint timing and frequency synchronization algorithm is proposed based on the long preamble. The simulations in the multi-path and frequency selective fading channel show that the proposed algorithm has improved the performances of timing metric plateau, timing offset and synchronization acquisition time even when signal-to-noise ratio is less than -5 dB.展开更多
Based on five scheduling types and their QoS requirements defined in IEEE 802.16e specification, this paper proposes a new scheduring algorithm for non-real-time or real-time multimedia services. Taking the performanc...Based on five scheduling types and their QoS requirements defined in IEEE 802.16e specification, this paper proposes a new scheduring algorithm for non-real-time or real-time multimedia services. Taking the performances of efficiency, fairness and complexity into consideration, the proposed algorithm enhances the efficiency of air interface resource at the expense of the short-time unfairness, but ensures the long-time fairness. Moreover, the proposed algorithm introduces an efficient QoS assurance mechanism, which implements the functions of congestion control, queuing management and traffic management. The simulation results based on a simplified traffic model show that the proposed algorithm guarantees better performances of efficiency and fairness than conventional algorithms, without increasing the algorithm complexity. Especially on the occasion of heavy-traffic requirement, the performance of efficiency and fairness can be improved by 50% at most.展开更多
Deep learning(DL)is a subdivision of machine learning(ML)that employs numerous algorithms,each of which provides various explanations of the data it consumes;mobile ad-hoc networks(MANET)are growing in promi-nence.For...Deep learning(DL)is a subdivision of machine learning(ML)that employs numerous algorithms,each of which provides various explanations of the data it consumes;mobile ad-hoc networks(MANET)are growing in promi-nence.For reasons including node mobility,due to MANET’s potential to provide small-cost solutions for real-world contact challenges,decentralized management,and restricted bandwidth,MANETs are more vulnerable to security threats.When protecting MANETs from attack,encryption and authentication schemes have their limits.However,deep learning(DL)approaches in intrusion detection sys-tems(IDS)can adapt to the changing environment of MANETs and allow a sys-tem to make intrusion decisions while learning about its mobility in the environment.IDSs are a secondary defiance system for mobile ad-hoc networks vs.attacks since they monitor network traffic and report anything unusual.Recently,many scientists have employed deep neural networks(DNNs)to address intrusion detection concerns.This paper used MANET to recognize com-plex patterns by focusing on security standards through efficiency determination and identifying malicious nodes,and mitigating network attacks using the three algorithms presented Cascading Back Propagation Neural Network(CBPNN),Feedforward-Neural-Network(FNN),and Cascading-Back-Propagation-Neural-Network(CBPNN)(FFNN).In addition to Convolutional-Neural-Network(CNN),these primary forms of deep neural network(DNN)building designs are widely used to improve the performance of intrusion detection systems(IDS)and the use of IDS in conjunction with machine learning(ML).Further-more,machine learning(ML)techniques than their statistical and logical methods provide MANET network learning capabilities and encourage adaptation to differ-ent environments.Compared with another current model,The proposed model has better average receiving packet(ARP)and end-to-end(E2E)performance.The results have been obtained from CBP,FFNN and CNN 74%,82%and 85%,respectively,by the time(27,18,and 17 s).展开更多
基金supported by the High Technology Research and Development Programme of China(No.2006AA01Z235)
文摘To decrease the transmission delay of uplink voice over IP(VoIP)services in IEEE 802.16e sys-tem,a novel strategy which includes a load-balance algorithm and an extended earliest deadline first(EEDF)scheduling algorithm is proposed.Subsequently,this paper analyzes the performance of the pro-posed strategy in terms of transmission delay of VoIP services,system capacity,throughput and compati-bility with IEEE 802 .16e standard.Finally,simulation experiments are carried out to verify the improve-ment of the proposed strategy.The simulation results match well with the theoretical analysis and showthat the proposed strategy reduces the transmission delay of uplink VoIP services and improves the capaci-ty and throughput.These improvements are remarkable especially when the load of system is heavy.
基金supported by the National Key R&D Program of China(2018YFC1707300)the Taishan Industrial Experts Program(tscx202211148).
文摘Fufang E’jiao Jiang(FEJ)as a healthy food consisting of medicine food homology materials approved by China’s Ministry of Health has been extensively applied to replenish qi and nourish blood,and it has a positive impact on women’s health.To find out the material basis and mechanism of FEJ,a systematic“compoundeffect-target”analysis including chemical composition resolution,zebrafish,network pharmacology,molecular docking,transcriptome,and bibliometric analysis was adopted.124 chemical components including ginsenosides,and phenylethanoid glycosides in FEJ were discovered,and effects of FEJ on promoting the generation of immune cells,erythropoiesis and angiogenesis in zebrafish were exhibited.Based on network pharmacology,molecular docking and in vivo activity assay,6 compounds including jionoside A1,isoacteoside,echinacoside,acteoside,lobetyolin,and rehmannioside D were identified as active components of FEJ.Transcriptome data showed that several pathways such as complement and coagulation cascades,ECM-receptor interaction,and PI3K-Akt signaling pathway were associated with proangiogenic effect of FEJ.19 common targets were obtained through combined analysis of network pharmacology and transcriptomics,and 5 targets of them were verified by PCR.The bibliometric analysis of these common targets revealed that FEJ was related to energy metabolism,pathway in cancer,etc.,which was consistent with the results of network pharmacology and transcriptome.The studies suggested that FEJ could replenish qi and nourish blood through multi-compound and multi-targets.
文摘Smoking has a complex impact on the immune system, affecting both innate and adaptive immunity. It can exacerbate pathogenic immune responses and attenuate defensive immunity, leading to a higher susceptibility to infections and certain diseases. The chemicals in cigarette smoke, such as nicotine and carbon monoxide, can alter immune cell functions and inflammatory responses. Smoking can also have long-term effects on the immune system, with some changes persisting even after quitting [1]. According to a Penn Medicine Physician, the Medical Oncologist Dr. David Porter, “People who are smokers tend to get sicker from infections”, “It may be that smoking impacts the immune system’s ability to respond appropriately”. Thus, such individuals within smoking exposure history might be considered as immunocompromised due to the altered and weakened immune system. Cigarette smoking is a prevalent habit with far-reaching health implications. Among its many adverse effects, smoking significantly alters the immune system’s functionality [1].
文摘A variety of test methodologies are commonly used to assess if a photovoltaic system can perform in line with expectations generated by a computer simulation. One of the commonly used methodologies across the PV industry is an ASTM E2848. ASTM E2848-13, 2023 test method provides measurement and analysis procedures for determining the capacity of a specific photovoltaic system built in a particular place and in operation under natural sunlight. This test method is mainly used for acceptance testing of newly installed photovoltaic systems, reporting of DC or AC system performance, and monitoring of photovoltaic system performance. The purpose of the PV Capacity Test and modeled energy test is to verify that the integrated system formed from all components of the PV Project has a production capacity that achieves the Guaranteed Capacity and the Guaranteed modeled AEP under measured weather conditions that occur when each PV Capacity Test is conducted. In this paper, we will be discussing ASTM E2848 PV Capacity test plan purpose and scope, methodology, Selection of reporting conditions (RC), data requirements, calculation of results, reporting, challenges, acceptance criteria on pass/fail test results, Cure period, and Sole remedy for EPC contractors for bifacial irradiance.
文摘The value of system assimilation is to improve working relationships between tutors and learners while increasing workflow efficiency among tertiary institutions with low operational costs. E-skills could be described as electronic education development, to assist ICT professionals to reach their future career goals and aim to help users boost their ICT skills. In a society that is expanding, it is also a crucial issue to take into account. Researchers have turned their attention to this topic because of its significance and contribution to the empowerment of graduates in digital education. Many scholars have proposed many methods for integrating e-skills into society with impressive results, but the rising rate of graduate unemployment in South Africa is gradually becoming a big worry in our society. A model based on Activity Theory (AT) and e-skills will be developed in our tertiary institution to equip graduates with skills that will increase their employability and provide more individualized work opportunities as part of this study’s effort to solve this issue. With the use of the Statistical Package for the Social Sciences (SPSS) and Cronbach’s Alpha for validity and reliability testing, the study will create an experimental performance to assess the approach taken to measure e-skills in tertiary institutions to empower graduates in South Africa. The study established that system development and e-skilled models for tertiary institutions are growing gradually, especially in South African institutions, that empower graduates with profitable employability with experiences to improve work operation in the industries. In conclusion, system development and e-skills are very demanding but important to empower graduate employability to determine competency in the professional workforce.
文摘Large Language Models (LLMs) have revolutionized Generative Artificial Intelligence (GenAI) tasks, becoming an integral part of various applications in society, including text generation, translation, summarization, and more. However, their widespread usage emphasizes the critical need to enhance their security posture to ensure the integrity and reliability of their outputs and minimize harmful effects. Prompt injections and training data poisoning attacks are two of the most prominent vulnerabilities in LLMs, which could potentially lead to unpredictable and undesirable behaviors, such as biased outputs, misinformation propagation, and even malicious content generation. The Common Vulnerability Scoring System (CVSS) framework provides a standardized approach to capturing the principal characteristics of vulnerabilities, facilitating a deeper understanding of their severity within the security and AI communities. By extending the current CVSS framework, we generate scores for these vulnerabilities such that organizations can prioritize mitigation efforts, allocate resources effectively, and implement targeted security measures to defend against potential risks.
文摘Based on the structures of the short preamble and long preamble, which are defined for synchronization in IEEES02.16e specification, the robust synchronization algorithm for IEEES02.16e OFDM system is proposed. The correlations among the sample sequences in the preamble are investigated, especially the correlation between the first sample sequence and the last sample sequence in the long preamble. The conventional joint timing and frequency synchronization algorithm is reviewed based on the short preamble referring to the algorithm proposed by Schmidl, then a robust joint timing and frequency synchronization algorithm is proposed based on the long preamble. The simulations in the multi-path and frequency selective fading channel show that the proposed algorithm has improved the performances of timing metric plateau, timing offset and synchronization acquisition time even when signal-to-noise ratio is less than -5 dB.
基金DONG Guojun, born in 1976,male, doctorate student,E-mail:zjrobindong@163.com.
文摘Based on five scheduling types and their QoS requirements defined in IEEE 802.16e specification, this paper proposes a new scheduring algorithm for non-real-time or real-time multimedia services. Taking the performances of efficiency, fairness and complexity into consideration, the proposed algorithm enhances the efficiency of air interface resource at the expense of the short-time unfairness, but ensures the long-time fairness. Moreover, the proposed algorithm introduces an efficient QoS assurance mechanism, which implements the functions of congestion control, queuing management and traffic management. The simulation results based on a simplified traffic model show that the proposed algorithm guarantees better performances of efficiency and fairness than conventional algorithms, without increasing the algorithm complexity. Especially on the occasion of heavy-traffic requirement, the performance of efficiency and fairness can be improved by 50% at most.
文摘Deep learning(DL)is a subdivision of machine learning(ML)that employs numerous algorithms,each of which provides various explanations of the data it consumes;mobile ad-hoc networks(MANET)are growing in promi-nence.For reasons including node mobility,due to MANET’s potential to provide small-cost solutions for real-world contact challenges,decentralized management,and restricted bandwidth,MANETs are more vulnerable to security threats.When protecting MANETs from attack,encryption and authentication schemes have their limits.However,deep learning(DL)approaches in intrusion detection sys-tems(IDS)can adapt to the changing environment of MANETs and allow a sys-tem to make intrusion decisions while learning about its mobility in the environment.IDSs are a secondary defiance system for mobile ad-hoc networks vs.attacks since they monitor network traffic and report anything unusual.Recently,many scientists have employed deep neural networks(DNNs)to address intrusion detection concerns.This paper used MANET to recognize com-plex patterns by focusing on security standards through efficiency determination and identifying malicious nodes,and mitigating network attacks using the three algorithms presented Cascading Back Propagation Neural Network(CBPNN),Feedforward-Neural-Network(FNN),and Cascading-Back-Propagation-Neural-Network(CBPNN)(FFNN).In addition to Convolutional-Neural-Network(CNN),these primary forms of deep neural network(DNN)building designs are widely used to improve the performance of intrusion detection systems(IDS)and the use of IDS in conjunction with machine learning(ML).Further-more,machine learning(ML)techniques than their statistical and logical methods provide MANET network learning capabilities and encourage adaptation to differ-ent environments.Compared with another current model,The proposed model has better average receiving packet(ARP)and end-to-end(E2E)performance.The results have been obtained from CBP,FFNN and CNN 74%,82%and 85%,respectively,by the time(27,18,and 17 s).
