Design of Context Awareness System for Semantic Internet of Things Based on Dynamic Bayesian Network

Semantic Internet of Things is an open-world service ecosystem formed on the basis of the Semantic Web, Internet of Things, and social networks. It forms and integrates physical space, cyberspace,and social space. The data friction problem is the key issue of the semantic Internet from theory to practice. In order to solve the problem of information interoperation and data friction,it is necessary to deal with the heterogeneity, dynamicity, and uncertainty of data in the semantic Internet of Things. For this reason, this paper constructs a semantic object networking context aware system based on dynamic Bayesian network. The overall architecture of context awareness system based on semantic Internet of Things is proposed. The hierarchical structure of the framework and the functions implemented by each layer are introduced in detail. The contextual awareness system based on semantic Internet of Things is introduced into the overall design and implementation. The design and implementation process of each layer structure of the system is described in detail.

Optimized Identification with Severity Factors of Gastric Cancer for Internet of Medical Things

The Internet of Medical Things (IoMT) emerges with the visionof the Wireless Body Sensor Network (WBSN) to improve the health monitoringsystems and has an enormous impact on the healthcare system forrecognizing the levels of risk/severity factors (premature diagnosis, treatment,and supervision of chronic disease i.e., cancer) via wearable/electronic healthsensor i.e., wireless endoscopic capsule. However, AI-assisted endoscopy playsa very significant role in the detection of gastric cancer. Convolutional NeuralNetwork (CNN) has been widely used to diagnose gastric cancer based onvarious feature extraction models, consequently, limiting the identificationand categorization performance in terms of cancerous stages and gradesassociated with each type of gastric cancer. This paper proposed an optimizedAI-based approach to diagnose and assess the risk factor of gastric cancerbased on its type, stage, and grade in the endoscopic images for smarthealthcare applications. The proposed method is categorized into five phasessuch as image pre-processing, Four-Dimensional (4D) image conversion,image segmentation, K-Nearest Neighbour (K-NN) classification, and multigradingand staging of image intensities. Moreover, the performance of theproposed method has experimented on two different datasets consisting ofcolor and black and white endoscopic images. The simulation results verifiedthat the proposed approach is capable of perceiving gastric cancer with 88.09%sensitivity, 95.77% specificity, and 96.55% overall accuracy respectively.

Internet of Things for in Home Health Based Monitoring System:Modern Advances,Challenges and Future Directions

IOT has carried outimportant function in converting the traditional fitness care corporation.With developing call for in population,traditional healthcare structures have reached their outmost functionality in presenting sufficient and as plenty as mark offerings.The worldwide is handling devastating developingantique population disaster and the right want for assisted-dwelling environments is turning into inevitable for senior citizens.There furthermore a determination by means of the use of way of countrywide healthcare organizations to increase crucial manual for individualized,right blanketed care to prevent and manipulate excessive coronial situations.Many tech orientated packages related to HealthMonitoring have been delivered these days as taking advantage of net boom everywhere on globe,manner to improvements in cellular and in IOT generation.Such as optimized indoor networks insurance,community shape,and fairly-lowdevice fee performances,advanced tool reliability,low device energy consumption,and hundreds higher unusual common usual performance in network safety and privacy.Studies have highlighted fantastic advantages of integrating IOT with health care location and as era is improving the rate also cannot be that terrific of a problem.However,many challenges in this new paradigm shift notwithstanding the fact that exist,that need to be addressed.So the out most purpose of this research paper is 3 essential departments:First,evaluation of key elements that drove the adoption and boom of the Internet of factors based totally domestic some distance off monitoring;Second,present fashionable improvement of IOT in home a long manner off monitoring shape and key building gadgets;Third,communicate future very last effects and distinct guidelines of such type a long way off monitoring packages going ahead.Such Research is a wonderful manner in advance now not outstanding in IOT Terminology but in standard fitness care location.

DNBP-CCA:A Novel Approach to Enhancing Heterogeneous Data Traffic and Reliable Data Transmission for Body Area Network

The increased adoption of Internet of Medical Things (IoMT) technologies has resulted in the widespread use ofBody Area Networks (BANs) in medical and non-medical domains. However, the performance of IEEE 802.15.4-based BANs is impacted by challenges related to heterogeneous data traffic requirements among nodes, includingcontention during finite backoff periods, association delays, and traffic channel access through clear channelassessment (CCA) algorithms. These challenges lead to increased packet collisions, queuing delays, retransmissions,and the neglect of critical traffic, thereby hindering performance indicators such as throughput, packet deliveryratio, packet drop rate, and packet delay. Therefore, we propose Dynamic Next Backoff Period and Clear ChannelAssessment (DNBP-CCA) schemes to address these issues. The DNBP-CCA schemes leverage a combination ofthe Dynamic Next Backoff Period (DNBP) scheme and the Dynamic Next Clear Channel Assessment (DNCCA)scheme. The DNBP scheme employs a fuzzy Takagi, Sugeno, and Kang (TSK) model’s inference system toquantitatively analyze backoff exponent, channel clearance, collision ratio, and data rate as input parameters. Onthe other hand, the DNCCA scheme dynamically adapts the CCA process based on requested data transmission tothe coordinator, considering input parameters such as buffer status ratio and acknowledgement ratio. As a result,simulations demonstrate that our proposed schemes are better than some existing representative approaches andenhance data transmission, reduce node collisions, improve average throughput, and packet delivery ratio, anddecrease average packet drop rate and packet delay.

谈-body/thing的转义用法

不定代词的学习是英语学习中的重点和难点，一般的学习者只停留在其基本意义和用法上，对其转性／义用法知之甚少，用之更少。就此本文介绍如下。

Remote Health Monitoring Using IoT-Based Smart Wireless Body Area Network

A wireless body area network(WBAN)consists of tiny healthmonitoring sensors implanted in or placed on the human body.These sensors are used to collect and communicate human medical and physiological data and represent a subset of the Internet of Things(IoT)systems.WBANs are connected to medical servers that monitor patients’health.This type of network can protect critical patients’lives due to the ability to monitor patients’health continuously and remotely.The inter-WBAN communication provides a dynamic environment for patients allowing them to move freely.However,during patient movement,the WBAN patient nodes may become out of range of a remote base station.Hence,to handle this problem,an efficient method for inter-WBAN communication is needed.In this study,a method using a cluster-based routing technique is proposed.In the proposed method,a cluster head(CH)acts as a gateway between the cluster members and the external network,which helps to reduce the network’s overhead.In clustering,the cluster’s lifetime is a vital parameter for network efficiency.Thus,to optimize the CH’s selection process,three evolutionary algorithms are employed,namely,the ant colony optimization(ACO),multi-objective particle swarm optimization(MOPSO),and the comprehensive learning particle swarm optimization(CLPSO).The performance of the proposed method is verified by extensive experiments by varying values of different parameters,including the transmission range,node number,node mobility,and grid size.A comprehensive comparative analysis of the three algorithms is conducted by extensive experiments.The results show that,compared with the other methods,the proposed ACO-based method can form clusters more efficiently and increase network lifetime,thus achieving remarkable network and energy efficiency.The proposed ACO-based technique can also be used in other types of ad-hoc networks as well.

Ontology Driven Testing Strategies for IoT Applications

Internet-of-Things(IoT)has attained a major share in embedded software development.The new era of specialized intelligent systems requires adaptation of customized software engineering approaches.Currently,software engineering has merged the development phases with the technologies provided by industrial automation.The improvements are still required in testing phase for the software developed to IoT solutions.This research aims to assist in developing the testing strategies for IoT applications,therein ontology has been adopted as a knowledge representation technique to different software engineering processes.The proposed ontological model renders 101 methodology by using Protégé.After completion,the ontology was evaluated in three-dimensional view by the domain experts of software testing,IoT and ontology engineering.Satisfied results of the research are showed in interest of the specialists regarding proposed ontology development and suggestions for improvements.The Proposed reasoning-based ontological model for development of testing strategies in IoT application contributes to increase the general understanding of tests in addition to assisting for the development of testing strategies for different IoT devices.

Monitoring of Unaccounted for Gas in Energy Domain Using Semantic Web Technologies

Smart Urbanization has increased tremendously over the last few years,and this has exacerbated problems in all areas of life,especially in the energy sector.The Internet of Things(IoT)is providing effective solutions in gas distribution,transmission and billing through very sophisticated sensory devices and software.Billions of heterogeneous devices link to each other in smart urbanization,and this has led to the Semantic interoperability(SI)problem between the connected devices.In the energy field,such as electricity and gas,several devices are interlinked.These devices are competent for their specific operational role but unable to communicate across the operational units as required for accounting and monitoring of gas losses due to heterogeneity in device communication standards.To overcome this problem,we have proposed a model and ontology by applying semantic web technologies and cloud storage to address the tracking of customers to observe Unaccounted for gas(UFG)in the gas domain of energy.Semantization is achieved by replicating heterogeneous devices Sensor Model Language(SenML)data into Resource description framework(RDF)without human interventions.As semantic interoperability is used to efficiently and meaningfully share the information from one location to another.Therefore,the proposed ontology and model focus more efficiently on customer tracking,forecasting,and monitoring to detect UFG in gas networks.This also helps to save Gas Companies from financial gas losses.

Semantic Complex Event Detection System of Express Delivery Business with Data Support From Multidimensional Space

The express delivery induslry of China is relatively backward in the automation degree of critical business processes. The basic reason is that the business-related supporting data, which is scattered in the multidimensional space, is difficult to utilize and process. This paper proposes an automatic data acquisition fi-amework to resolve such difficulty, which synthetically utilize intelligent inemet of things （IoT）, semantic web and complext event processing （CEP） technology. We also implement a SCEP prototype system with the capability of real-time detecting complex business events on the goods sorting line, which adopts a detection method consisting of four stages. The simulation results show that the system has good performance and feasible enough to deal with the complex business which need data support fTom multidimensional space.

“道”文化心灵精神及其对中国文学的话语塑造

“道”作为中国文化的至高范畴和终极据点,在“思想-言说”结构及文化心灵方面形成了“道说希声”这一内在规训及根本特质。而正是“道说希声”,根本性地塑造了中国文化以“致和”“成善”“养德”为基本心灵特征与价值追求、以“乐和”“忧患”“静朴”“逍遥”为根本精神、以“经世致用”与“味美趣美”为艺术审美追求的“道”文化心灵精神。“道”文化心灵精神作为一种深层性、稳定性、基因型的结构力量,不仅对中国传统文化整体及其历史发展有着根本的轨导与牵制的作用,而且深刻影响和决定了中国文学及文论的话语形态与话语体系,建构和生成了中国文学及文论追求大宇宙及大生命关怀、致力感物抒怀、以“意象-语象”为中心(“象本位”)、基于“道”的核心范畴性表达等结构性特征。

随附性的必然性与心身关系——从系统本体论的观点看

金在权首先把随附性看作上下两层性质即随附性质和基础性质之间的依赖或决定关系,区分了弱和强这两种随附性概念。当其随附性理论遭遇诸多困难之后,他又提出整—部随附性概念,并赋予它形而上学的必然性,表现出从认识论向实践论转变的倾向。可以沿着金在权已经开启但未贯彻到底的实践论路线继续前行,明确地把随附性理论奠定在系统本体论的基础之上,深入分析随附必然性的逻辑性质和哲学意义,并用整—部随附性把其他所有随附性统领和贯穿起来;进而提出基于系统本体论(或系统一元论)的随附二元论,用以取代物理主义一元论和笛卡尔的心物平行二元论。

康德本体论的对象性介质缺失及其完构

康德把“物自身”视为现象存在的本体根基,然而它凭什么能够“空”而有“灵”,以至成为所有现象得以生成的根基,尚缺少必要的形而下基元作为本体与现象之间的介质。马克思对象性关系的思想,启示并提供了本体与现象之间存在超越差异的普遍性对象性关系和必要介质的思路。怀特海有机宇宙论以宇观和缈观两极的结合实现了对存在本体的完整建构。中国古代“道”论不仅与康德“物自身”说高度会通,而且其“道气合一”论对本体存在的完构与怀特海异曲同工,还以“气物二相”说与“波粒二象”说相呼应,使本体论的完整结构得以圆融。这样完整圆融的本体论为建构“世界美学”奠定了哲学基础。

身体本体视域下学校体育的认识论框架及其实践理路

超越技术理性主义,回归身体本体意义,是新时期学校体育理论与实践的新转向。身体在学校体育中具有本体论上的哲学意义,包含了作为自然存在与生命存在的教育意涵。身体本体视域下的学校体育实践充斥着身体认识论的哲学色彩,建立在身心一元、主客一体、交互对话与反思建构的认知逻辑之上,具有显著的具身认知特征与具身实践的教育学意义,构建了由“经验知识论、体验介质论、对话关系论、建构生成论”4个方面构成的认识论框架。提出学校体育应呈现“生命-实践”的教育学意义,包含着主动的身体、鲜活的体验、主体的交互与意义的建构4个方面的实践要素,并据此提出主体性认知、情境化教学、合作性学习与生成性产出的实践理路。

翻译伦理的具身性研究——以儒家身体观为视角

翻译伦理是翻译研究的一个重要维度。西方翻译伦理大多将翻译主体当作抽象的“心智主体”去研究,是一种“离身”视角的阐释。与西方身心二元的路径不同,儒家身体观将人作为“身心合一”的主体去理解,以“己身”为连接方式与他者展开伦理实践,是一种“人本化”的具身观。以儒家身体观探讨翻译伦理的具身性研究,是以儒家身体观的“以身体之“”万物一体之仁”为核心来阐释翻译伦理的内涵,指向探寻译者如何“修身”、理解翻译伦理客体的扩容、解读“身体作为伦理”的始源意义。这不仅对于译者“成己“”成物”的价值方面具有拓展性意义,而且也为翻译伦理研究注入新的解释空间。

物联网威胁情报知识图谱综述

物联网(Internet of Things,IoT)技术的快速发展带来了巨大的市场潜力,同时也带来了安全和隐私问题。传统的安全方法已不能应对新的网络威胁,威胁情报和安全态势感知等主动防御策略应运而生。知识图谱技术为解决威胁情报的提取、整合和分析提供了新的思路。首先回顾了物联网安全本体的构建,包括通用安全本体和特定领域安全本体。接着,梳理了威胁情报信息抽取的关键技术,包括基于规则匹配、统计学习和深度学习的方法。然后,探讨了物联网威胁情报知识图谱的构建框架,涉及数据源、信息抽取、本体构建等方面。最后,讨论了物联网威胁情报知识图谱的应用情景,并指出当前研究面临的挑战,展望了未来的研究方向。

基于物联网的滑坡下管道应力监测及预警方法研究

我国地质环境复杂,长输管道在敷设过程中不可避免地穿越滑坡等地质灾害频发区域,在滑坡的推拉作用下埋地管道易发生大位移变形,导致管道变形失效,甚至引发泄漏、爆炸等事故。以滑坡为研究背景,研究了地质灾害引发管道破坏失效的影响规律,以滑坡体内、外段对滑坡区管道划分不同区段,通过迭代计算完成整体应变力学分析,基于极限应变准则对管道可能发生的不同尺度滑坡位移进行模拟计算和风险评估,开发了基于物联网的地质灾害下管道应力应变及周围土压力、地层变形等监测技术及相关硬件设备,建立地质灾害下管道本体安全监测软件系统,实现了现场监测数据的自动采集、上传、数据分析和报警等功能。开发的硬件设备及软件系统在某输油管道开展现场应用,实现了滑坡灾害易发区管道本体安全性的在线实时分析与评价预警。

当代文艺思潮的“后人文主义”转向——从“人性”到“物性”的流变研究

当代中国文艺理论肇始于对“人学”问题的思考,伴随着这一问题而出现的“人性”“新启蒙”等概念,标志着人文主义理论思潮的形成。但在20世纪90年代中后期,随着一些源自西方的诸如身体、事件论、思辨实在论以及物性论等新概念的翻译和引介,当代中国文艺思潮中的人文主义逐渐为后人文主义所取代。如果从文艺理论演绎的内在逻辑来看,从人文主义到后人文主义的转变,也可视为从人与物主客二元对立的建构论(语言论),转向人与物交融互通的物性论(反语言论),并为当代中国文艺理论的新变提供契机与可能性。

物性叙事研究的拓荒之作——《物性叙事研究》评介

物性叙事研究因其顺应时代潮流和紧跟学科前沿而备受关注。唐伟胜教授的拓荒之作《物性叙事研究》将物性叙事模式归纳为符号的物、行动者的物和本体的物,并聚焦于后两种模式展开深入探究。该著融合中西方相关理论,建构了一套彰显中国特色、中国风格、中国气派的物性叙事理论体系,对于推进学术话语体系建设具有参考意义。

基于知识图谱的语义融合模型构建方法研究

知识图谱具有良好的指标描述性能与解释能力。为了有效分析数字电网的业务全生命周期数据、形成以知识为导向的新型电网运维管理模式,开展了基于知识图谱的语义融合模型构建方法的研究。首先,构建基于物联网的电网数字模型,汇总数字电网信息。其次,针对数字电网,采用Protégé软件,通过七步法构建数字电网本体。最后,基于本体,采用自顶向下的方式生成知识图谱。基于上述建模方法,将知识图谱与模式识别相结合,设计一套语义提取框架。根据数字电网模型信息(图像、声音、文本等)提取的原子概念检测本体,推理出更高层次的复合语义特征。基于所获取的语义特征,结合知识图谱,试点数字电网信息语义融合,为推动统一模型的构建提供实践参考。

刘宗周“万物一体”论探赜

“万物一体”是宋明理学讨论的核心问题之一。刘宗周将生生之仁视为“万物一体”的本体论依据,将人与万物意义世界的共生共建视为“万物一体”的实际表现,将人人本具的“知痛痒心”看作个体实现与万物一体的现实津梁。他认为个体在将识仁体与做工夫合而为一的践履中可返归到与万物为一的本然之境,在此境界中,个体平等地看待自我与他者,不执着于自身境遇的顺逆穷通,在勘破生死中彻底消解由自私带来的物我隔阂。“万物一体”论在刘宗周思想中有重要地位,涉及到本体论、工夫论、境界论等诸多方面,对此问题的探究有助于推动刘宗周思想的整体研究,也有助于厘清“万物一体”思想在宋明理学中的发展走向。