A renewal theory based performance and configuration framework of the IEEE 802.11ah RAW mechanism

IEEE 802.11ah is a new Wi-Fi standard for sub-1Ghz communications,aiming to address the challenges of the Internet of Things(IoT).Significant changes in the legacy 802.11 standards have been proposed to improve the network performance in high contention scenarios,the most important of which is the Restricted Access Window(RAW)mechanism.This mechanism promises to increase the throughput and energy efficiency by dividing stations into different groups.Under this scheme,only the stations belonging to the same group may access the channel,which reduces the collision probability in dense scenarios.However,the standard does not define the RAW grouping strategy.In this paper,we develop a new mathematical model based on the renewal theory,which allows for tracking the number of transmissions within the limited RAW slot contention period defined by the standard.We then analyze and evaluate the performance of RAW mechanism.We also introduce a grouping scheme to organize the stations and channel access time into different groups within the RAW.Furthermore,we propose an algorithm to derive the RAW configuration parameters of a throughput maximizing grouping scheme.We additionally explore the impact of channel errors on the contention within the time-limited RAW slot and the overall RAW optimal configuration.The presented analytical framework can be applied to many other Wi-Fi standards that integrate periodic channel reservations.Extensive simulations using the MATLAB software validate the analytical model and prove the effectiveness of the proposed RAW configuration scheme.

模拟训练在提高肿瘤护理质量和患者安全中的应用:范围综述

目的模拟训练(simulation-based training,SBT)是一种有效的教育方法,广泛应用于包括肿瘤学在内的多种临床环境中。该文对肿瘤学中与SBT相关的研究进行了范围综述,全面了解SBT在提高医护人员技能方面的作用,从而提高护理质量和患者安全。方法根据Arksey和O’Malley提出的范围综述方法框架,在Medline、Scopus和Web of Science数据库中检索于2012年至2022年发表的,与SBT在提高肿瘤科医护人员技能方面的相关研究文献,仅纳入经过同行评审的英文或法语文献。由2名研究员独立进行文献的筛选、提取和分析。结果检索出1013篇文章,共纳入29篇文献。其中25篇文献侧重于非技术技能,如决策技能、沟通和团队合作技能以及认知能力;13篇文献侧重于技术技能。纳入文献研究结果表明,通过SBT项目,肿瘤科医护人员的技能得到了显著提高。其中14篇文献对SBT的应用进行了主观评估,9篇文献对其进行了客观评估,6篇文献采用了主观和客观相结合的评估方法。结论SBT是提高肿瘤科医护人员技能的有效方法,支持和推广SBT对提供高质量的医疗服务和确保患者安全至关重要。

Towards the Development of Mechanical Systems Entirely Based on Natural Materials

In order to mitigate the risks stemming from the utilization of mineral and synthetic organic substances,consensus exists in the literature that additional efforts should be devoted to the identification of adequate equivalent natural(ecological)materials.This work presents the outcomes of a preliminary study where the physical,mechanical,chemical and thermal properties of natural fibers have been considered.Initially,areca,and materials such as Moroccan doum and jute are considered.As a case study,a brake pad based on natural fibers is critically assessed.

A Lightweight Approach(BL-DAC)to Secure Storage Sharing in Cloud-IoT Environments

The growing advent of the Internet of Things(IoT)users is driving the adoption of cloud computing technologies.The integration of IoT in the cloud enables storage and computational capabilities for IoT users.However,security has been one of the main concerns of cloud-integrated IoT.Existing work attempts to address the security concerns of cloud-integrated IoT through authentication,access control,and blockchain-based methods.However,existing frameworks are somewhat limited by scalability,privacy,and centralized structures.To mitigate the existing problems,we propose a blockchain-based distributed access control method for secure storage in the IoT cloud(BL-DAC).Initially,the BL-DAC performs decentralized authentication using the Quantum Neural Network Cryptography(QNNC)algorithm.IoT users and edge nodes are authenticated in the blockchain deployed by distributed Trusted Authorities(TAs)using multiple credentials.The user data is classified into sensitive and non-sensitive categories using the Enhanced Seagull Optimization(ESO)algorithm.Also,the authentication to access this data is performed by a decentralized access control method using smart contract policy.Sensitive user data is encrypted using the QNNC algorithm and stored in the private cloud.In contrast,non-sensitive data is stored in the public cloud,and IPFS is used to store data in a decentralized manner with high reliability.In addition,data security is improved by using a hierarchical blockchain which improves scalability by managing the multiple blockchains hierarchically and is lightweight using Proof of Authentication Consensus(PoAH).The BL-DAC is simulated and validated using the Network Simulator-3.26 simulation tool and validated.This work shows better results than the compared ones in terms of validation metrics such as throughput(26%),encryption time(19%),decryption time(16%),response time(15%),block validation time(31%),attack detection rate(16%),access control precision(13%),and scalability(28%).

A novel algorithm for distance measurement using stereo camera

Distance estimation can be achieved by using active sensors or with the help of passive sensors such as cameras.The stereo vision system is generally composed of two cameras to mimic the human binocular vision.In this paper,a Python-based algorithm is pro-posed to find the parameters of each camera,rectify the images,create the disparity maps and finally use these maps for distance measurements.Experiments using real-time im-ages,which were captured from our stereo vision system,of different obstacles posi-tioned at multiple distances(60-200 cm)prove the effectiveness of the proposed program and show that the calculated distance to the obstacle is relatively accurate.The accuracy of distance measurement is up to 99.83%.The processing time needed to calculate the distance between the obstacle and the cameras is less than 0.355 s.

A Lightweight Blockchain for IoT in Smart City (IoT-SmartChain)

The smart city is a technological framework that connects the city’s different components to create new opportunities.This connection is possible with the help of the Internet of Things(IoT),which provides a digital personality to physical objects.Some studies have proposed integrating Blockchain technology with IoT in different use cases as access,orchestration,or replicated storage layer.The majority of connected objects’capacity limitation makes the use of Blockchain inadequate due to its redundancy and its conventional processing-intensive consensus like PoW.This paper addresses these challenges by proposing a NOVEL model of a lightweight Blockchain framework(IoT-SmartChain),with a lightweight consensus and a lightweight structure.The framework architecture presents a role hierarchy of connected objects according to their computational and storage capacity.This organization allows all things to be linked even indirectly via different interfaces and to benefit from the power of high-capacity objects such as Fog and Edge computing nodes.Data is validated and added to the blockchain ledger by running a lightweight consensus called Proof of Random Participation(PoRP),which reduces the blockchain nodes’high computing power requirement.The TOPIC subscription-based data storage strategy called Assisted Selected Relevant Data in Local Ledger(ASRDLL)reduces the data size of a node’s local ledger and the entire network’s data size.This strategy is assisted by a centralized algorithm that optimizes the overall network size by adjusting the choice of TOPICS.The storage capacity,computational power,and energy consumption have been evaluated by a proof of concept implementation under NodeJS.

Optical and magnetic properties of perovskite materials:Ba_(0.3)La_(0.7)Ti_(0.3)Fe_(0.7)O_(3) and Ba_(0.1)La_(0.9)Ti_(0.1)Fe_(0.9)O_(3)

Structural,optical and magnetic properties are reported for new synthesized perovskite materials.Ba_(0.3)La_(0.7)Ti_(0.3)Fe_(0.7)O_(3) and Ba_(0.1)La_(0.9)Ti_(0.1)Fe_(0.9)O_(3) compositions were prepared via solid state reaction.X-ray analysis confirms that both compositions show feature of perovskite structure.Rietveld refinement method was used to confirm the phase formation and investigate the structure and space group.The study demonstrates the formation of orthorhombic structure with Pnma space group for Ba_(0.3)La_(0.7)Ti_(0.3)Fe_(0.7)O_(3) while the composition Ba_(0.1)La_(0.9)Ti_(0.1)Fe_(0.9)O_(3) structure adopts Pbnm symmetry.UV–vis spectroscopy measurements show very broad and intense UV–visible light absorption,the estimated band gap ranges between 2.07 and 2.15 eV.Magnetic measurements were carried out for the compositions Ba_(0.3)La_(0.7)Ti_(0.3)Fe_(0.7)O_(3) and Ba_(0.1)La_(0.9)Ti_(0.1)Fe_(0.9)O_(3).The hysteresis loops of both samples at 300 and 10 K show a strong ferromagnetic behavior.The temperature dependent magnetization at 0.05 T under field-cooled(FC)and zero field cooled(ZFC)modes shows magnetic frustration or spin glass-like behavior.

Dynamic resource allocation for service in mobile cloud computing with Markov modulated arrivals

Mobile Cloud Computing (MCC) is a modern architecture that brings together cloudcomputing, mobile computing and wireless networks to assist mobile devices in storage,computing and communication. A cloud environment is developed to support a widerange of users that request the cloud resources in a dynamic environment with possible constraints. Burstiness in users service requests causes drastic and unpredictableincreases in the resource requests that have a crucial impact on policies of resourceallocation. How can the cloud system efficiently handle such burstiness when the cloudresources are limited? This problem becomes a hot issue in the MCC research area. Inthis paper, we develop a system model for the resource allocation based on the SemiMarkovian Decision Process (SMDP), able of dynamically assigning the mobile servicerequests to a set of cloud resources, to optimize the usage of cloud resources and maximize the total long-term expected system reward when the arrival process is a finitestate Markov-Modulated Poisson Process (MMPP). Numerical results show that ourproposed model performs much better than the Greedy algorithm in terms of achievinghigher system rewards and lower service requests blocking probabilities, especially whenthe burstiness degree is high, and the cloud resources are limited.