Analysis and Modeling of Mobile Phone Activity Data Using Interactive Cyber-Physical Social System

Mobile networks possess significant information and thus are considered a gold mine for the researcher’s community.The call detail records(CDR)of a mobile network are used to identify the network’s efficacy and the mobile user’s behavior.It is evident from the recent literature that cyber-physical systems(CPS)were used in the analytics and modeling of telecom data.In addition,CPS is used to provide valuable services in smart cities.In general,a typical telecom company hasmillions of subscribers and thus generatesmassive amounts of data.From this aspect,data storage,analysis,and processing are the key concerns.To solve these issues,herein we propose a multilevel cyber-physical social system(CPSS)for the analysis and modeling of large internet data.Our proposed multilevel system has three levels and each level has a specific functionality.Initially,raw Call Detail Data(CDR)was collected at the first level.Herein,the data preprocessing,cleaning,and error removal operations were performed.In the second level,data processing,cleaning,reduction,integration,processing,and storage were performed.Herein,suggested internet activity record measures were applied.Our proposed system initially constructs a graph and then performs network analysis.Thus proposed CPSS system accurately identifies different areas of internet peak usage in a city(Milan city).Our research is helpful for the network operators to plan effective network configuration,management,and optimization of resources.

Socio-Cultural Representations and Therapeutic Itineraries of Parents of Autistic Children Followed in the INSP’s Children’s Mental Health Services

Pervasive developmental disorders (PDD) remain little known to populations in developing countries. In black Africa their social representations remain strongly influenced by local belief systems. The general objective of this study was to understand the perceptions and representations of Ivorian parents vis-à-vis PDD. This was a mixed (qualitative and quantitative) prospective cross-sectional study with a descriptive aim that involved a sample of 49 parents. The sampling was of the qualitative type by multiple cases with reasoned choice by saturation. Our results showed that male parents were mostly aged between 40 - 49 years (48.98%) with a higher level of education (67.34%) while mothers were mostly aged between 30 - 39 (61.22%) and a higher level (30.61%). Autistic children were negatively perceived by their parents: either as a source of psychological suffering (82.85%), or as mysterious children who sacrificed their parents (44.66%), or as “bobo” children (mute children in common Ivorian language) (16.66%) or like rude children (13.34%). The supposed origin of the disorder according to the parents was mystical-religious (60.94%);natural (25%);hereditary (6.25%). In 6.25% of cases, PDD were assumed to be of unknown or iatrogenic origin attributable to vaccination (1.56%). 75.51% of parents said that in addition to conventional medical therapies, they also used traditional therapies. The use of this therapeutic alternative would be linked to the perceptions and beliefs that feed the socio-cultural representations of our respondents.

普适计算环境中基于移动Agent的数据访问原型

普适计算(pervasive computing)不仅包含无处不在的计算设备和网络连接,更重要的是需要实现无处不在的数据访问。如何使用户及时、可靠、安全、方便地获取信息是这种计算环境的目的,同时也是该环境中数据管理的核心和目标。本文以移动agent为基础,实现了适合于普适计算环境的数据获取原型。重点阐述了实现原理、原型体系结构、工作流程,并通过实验数据以体现其优越性。

基于Pervasive Computing技术的外语网络交互模态话语构想

文章以"Pervasive Computing"为技术支撑,以"系统功能语言学"为理论研究框架,以外语教学领域的模态话语研究为表现形式,探索创建多模态视野下的外语网络交互教学模态,即供交际双方或多方信息全球实时传达、同步立体交互的多模态教学模式。

Dynamic software allocation algorithm for saving power in pervasive computing

A novel dynamic software allocation algorithm suitable for pervasive computing environments is proposed to minimize power consumption of mobile devices. Considering the power cost incurred by the computation, communication and migration of software components, a power consumption model of component assignments between a mobile device and a server is set up. Also, the mobility of components and the mobility relationships between components are taken into account in software allocation. By using network flow theory, the optimization problem of power conservation is transformed into the optimal bipartition problem of a flow network which can be partitioned by the max-flow rain-cut algorithm. Simulation results show that the proposed algorithm can save si^nificantlv more energy than existing algorithms.

A Master-Slave Blockchain Paradigm and Application in Digital Rights Management

Upon flaws of current blockchain platforms of heavyweight, large capacity of ledger, and time-consuming of synchronization of data, in this paper, we proposed a new paradigm of master-slave blockchain scheme(MSB) for pervasive computing that suitable for general PC, mobile device such as smart phones or PADs to participants in the working of mining and verification, in which we separated traditional blockchain model in 2 layer defined as master node layer and a series of slavery agents layer, then we proposed 2 approaches for partially computing model(PCM) and non-computing of model(NCM) in the MSB blockchain, Finally large amounts of simulations manifest the proposed master-slave blockchain scheme is feasible, extendible and suitable for pervasive computing especially in the 5 G generation environment, and can apply in the DRM-related applications.

Fuzzy Logic-Based Health Monitoring System for COVID’19 Patients

In several countries,the ageing population contour focuses on high healthcare costs and overloaded health care environments.Pervasive health care monitoring system can be a potential alternative,especially in the COVID-19 pandemic situation to help mitigate such problems by encouraging healthcare to transition from hospital-centred services to self-care,mobile care and home care.In this aspect,we propose a pervasive system to monitor the COVID’19 patient’s conditions within the hospital and outside by monitoring their medical and psychological situation.It facilitates better healthcare assistance,especially for COVID’19 patients and quarantined people.It identies the patient’s medical and psychological condition based on the current context and activities using a fuzzy context-aware reasoning engine based model.Fuzzy reasoning engine makes decisions using linguistic rules based on inference mechanisms that support the patient condition identication.Linguistics rules are framed based on the fuzzy set attributes belong to different context types.The fuzzy semantic rules are used to identify the relationship among the attributes,and the reasoning engine is used to ensure precise real-time context interpretation and current evaluation of the situation.Outcomes are measured using a fuzzy logic-based context reasoning system under simulation.The results indicate the usefulness of monitoring the COVID’19 patients based on the current context.

Trust Based Pervasive Computing

Pervasive computing environment is a distributed and mobile space. Trust relationship must be established and ensured between devices and the systems in the pervasive computing environment. The trusted computing （TC） technology introduced by trusted computing group is a distributed-system-wide approach to the provisions of integrity protection of resources. The TC＇s notion of trust and security can be described as conformed system behaviors of a platform environment such that the conformation can be attested to a remote challenger. In this paper the trust requirements in a pervasive/ubiquitous environment are analyzed. Then security schemes for the pervasive computing are proposed using primitives offered by TC technology.

Behavioural and emotional disorders in childhood: A brief overview for paediatricians

Mental health problems in children and adolescents include several types of emotional and behavioural disorders, including disruptive, depression, anxiety and pervasive developmental(autism) disorders, characterized as either internalizing or externalizing problems. Disruptive behavioural problems such as temper tantrums, attention deficit hyperactivity disorder, oppositional, defiant or conduct disorders are the commonest behavioural problems in preschool and school age children. The routine Paediatric clinic or Family Medicine/General Practitioner surgery presents with several desirable characteristics that make them ideal for providing effective mental health services to children and adolescents. DSM-5 and ICD-10 are the universally accepted standard criteria for the classification of mental and behaviour disorders in childhood and adults. The age and gender prevalence estimation of various childhood behavioural disorders are variable and difficult to compare worldwide. A review of relevant published literature was conducted, including published metaanalyses and national guidelines. We searched for articles indexed by Ovid, Pub Med, Pub Med Medical Central, CINAHL, EMBASE, Database of Abstracts and Reviews, and the Cochrane Database of Systematic reviews and other online sources. The searches were conducted using a combination of search expressions including "childhood", "behaviour", "disorders" or "problems". Childhood behaviour and emotional problems with their related disorders have significant negative impacts on the individual, the family and the society. They are commonly associated with poor academic, occupational, and psychosocial functioning. It is important for all healthcare professionals, especially the Paediatricians to be aware of the range of presentation, prevention and management of the common mental health problems in children and adolescents.

A Personal Desktop Liquid-Metal Printer as a Pervasive Electronics Manufacturing Tool for Society in the Near Future

It has long been a dream in the electronics industry to be able to write out electronics directly, as simply as printing a picture onto paper with an offi ce printer. The fi rstever prototype of a liquid-metal printer has been invented and demonstrated by our lab, bringing this goal a key step closer. As part of a continuous endeavor, this work is dedicated to significantly extending such technology to the consumer level by making a very practical desktop liquid-metal printer for society in the near future. Through the industrial design and technical optimization of a series of key technical issues such as working reliability, printing resolution, automatic control, human-machine interface design, software, hardware, and integration between software and hardware, a high-quality personal desktop liquid-metal printer that is ready for mass production in industry was fabricated. Its basic features and important technical mechanisms are explained in this paper, along with demonstrations of several possible consumer end-uses for making functional devices such as li ght-emitting diode(LED) displays. This liquid-metal printer is an automatic, easyto-use, and low-cost personal electronics manufacturing tool with many possible applications. This paper discusses important roles that the new machine may play for a group of emerging needs. The prospective future of this cuttingedge technology is outlined, along with a comparative interpretation of several historical printing methods. This desktop liquid-metal printer is expected to become a basic electronics manufacturing tool for a wide variety of emerging practices in the academic realm, in industry, and in education as well as for individual end-users in the near future.

Decision Making in Internet of Vehicles Using Pervasive Trusted Computing Scheme

Pervasive schemes are the significant techniques that allow intelligent communication among the devices without any human intervention.Recently Internet of Vehicles(IoVs)has been introduced as one of the applications of pervasive computing that addresses the road safety challenges.Vehicles participating within the IoV are embedded with a wide range of sensors which operate in a real time environment to improve the road safety issues.Various mechanisms have been proposed which allow automatic actions based on uncertainty of sensory and managed data.Due to the lack of existing transportation integration schemes,IoV has not been completely explored by business organizations.In order to tackle this problem,we have proposed a novel trusted mechanism in IoV during communication,sensing,and record storing.Our proposed method uses trust based analysis and subjective logic functions with the aim of creating a trust environment for vehicles to communicate.In addition,the subjective logic function is integrated with multi-attribute SAW scheme to improve the decision metrics of authenticating nodes.The trust analysis depends on a variety of metrics to ensure an accurate identification of legitimate vehicles embedded with IoT devices ecosystem.The proposed scheme is determined and verified rigorously through various IoT devices and decision making metrics against a baseline solution.The simulation results show that the proposed scheme leads to 88%improvement in terms of better identification of legitimate nodes,road accidents and message alteration records during data transmission among vehicles as compared to the baseline approach.

A PRIVACY-PRESERVING AUTHENTICATION SCHEME USING BIOMETRICS FOR PERVASIVE COMPUTING ENVIRONMENTS

In pervasive computing environments,users can get services anytime and anywhere,but the ubiquity and mobility of the environments bring new security challenges.The user and the service provider do not know each other in advance,they should mutually authenticate each other.The service provider prefers to authenticate the user based on his identity while the user tends to stay anonymous.Privacy and security are two important but seemingly contradictory objectives.As a result,a user prefers not to expose any sensitive information to the service provider such as his physical location,ID and so on when being authenticated.In this paper,a highly flexible mutual authentication and key establishment protocol scheme based on biometric encryption and Diffie-Hellman key exchange to secure interactions between a user and a service provider is proposed.Not only can a user's anonymous authentication be achieved,but also the public key cryptography operations can be reduced by adopting this scheme.Different access control policies for different services are enabled by using biometric encryption technique.The correctness of the proposed authentication and key establishment protocol is formally verified based on SVO logic.

Towards data-driven models for diverging emerging technologies for maternal,neonatal and child health services in Sub-Saharan Africa:a systematic review

Sub-Saharan Africa(SSA)has the highest maternal and under-five mortality rates in the world.The advent of the coronavirus disease 2019 exacerbated the region's problems by overwhelming the health systems and affecting access to healthcare through travel restrictions and rechanelling of resources towards the containment of the pandemic.The region failed to achieve the Millenium Development Goals on maternal and child mortalities,and is poised to fail to achieve the same goals in the Sustainable Development Goals.To improve on the maternal and child health outcomes,many SSA countries introduced digital technologies for educating pregnant and nurs-ing women,making doctors'appointments and sending reminders to mothers and expectant mothers,as well as capturing information about patients and their illnesses.However,the collected epidemiological data are not being utilised to inform patient care and improve on the quality,efficiency and access to maternal,neonatal and child health(MNCH)care.To the researchers'best knowledge,no review paper has been published that focuses on digital health for MNCH care in SSA and proposes data-driven approaches to the same.Therefore,this study sought to:(1)identify digital systems for MNCH in SSA;(2)identify the applicability and weaknesses of the dig-ital MNCH systems in SSA;and(3)propose a data-driven model for diverging emerging technologies into MNCH services in SSA to make better use of data to improve MNCH care coverage,efficiency and quality.The PRISMA methodology was used in this study.The study revealed that there are no data-driven models for monitoring pregnant women and under-five children in Sub-Saharan Africa,with the available digital health technologies mainly based on SMS and websites.Thus,the current digital health systems in SSA do not support real-time,ubiquitous,pervasive and data-driven healthcare.Their main applicability is in non-real-time pregnancy moni-toring,education and information dissemination.Unless new and more effective approaches are implemented,SSA might remain with the highest and unacceptable maternal and under-five mortality rates globally.The study proposes feasible emerging technologies that can be used to provide data-driven healthcare for MNCH in SSA,and the recommendations on how to make the transition successful as well as the lessons learn from other regions.

Design and Application of PCE-Oriented Multi-agent Software Framework and Agent Communication Module

With the improvement of mobile equipment performance and development of Pervasive Computing,interactive computational applications such as Multi-Agent (MA) systems in Pervasive Computing Environments (PCE) become more and more prevalent. Many applications in PCE require Agent communication,manual control,and diversity of devices. Hence system in PCE must be designed flexible,and optimize the use of network,storage and computing resources. However,traditional MA software framework cannot completely adapt to these new features. A new MA software framework and its Agent Communication Modules to solve the problem brought by PCE was proposed. To describe more precisely,it presents Wright/ADL (Architecture Description Language) description of the new framework. Then,it displays an application called AI Eleven based on this new framework. AI Eleven achieves Agent-Agent communication and good collaboration for a task. Two experiments on AI Eleven will demonstrate the new framework's practicability and superiority.

孤独症儿童意外伤害研究进展

意外伤害（Unintentional Injury）是指身体受到外来的、突发的、非本身意愿、非疾病导致身体受到伤害的客观事件[1]。孤独症（autism）又被临床称之为自闭症或孤独性障碍（autistic disorder）,为当前广泛性发育障碍（pervasive developmental disorder,PDD）代表性疾病之一,给儿童身心成长带来严重影响[2]。

Application of Machine-Learning Based Prediction Techniques in Wireless Networks

Wireless networks are key enablers of ubiquitous communication. With the evolution of networking technologies and the need for these to inter-operate and dynamically adapt to user requirements, intelligent networks are the need of the hour. Use of machine learning techniques allows these networks to adapt to changing environments and enables them to make decisions while continuing to learn about their environment. In this paper, we survey the various problems of wireless networks that have been solved using machine-learning based prediction techniques and identify additional problems to which prediction can be applied. We also look at the gaps in the research done in this area till date.

A Synchronous and Deterministic MAC Protocol for Wireless Communications on Linear Topologies

Linear topology is useful in several pervasive application scenarios. Even though a linear topology can be handled by unspecific routing algorithms over general purpose MAC protocols, better performance can be obtained by specialized techniques. This paper describes a new communication scheme called Wireless Wire (WiWi), which builds up a bidirectional wireless communication channel with deterministic properties in terms of throughput and latency over a strip of pervasive devices with short-range transmission capabilities. The system is synchronous and fault tolerant. With low cost and extremely simple devices, WiWi builds up a “wire-like” dielectric link, but its applications are not limited to end-to-end communications. For example, WiWi can be used to collect data from sensors along the path, thus acting as a virtual conveyor belt.

Real-Time Automatic ECG Diagnosis Method Dedicated to Pervasive Cardiac Care

Recent developments of the wireless sensor network will revolutionize the way of remote monitoring in dif-ferent domains such as smart home and smart care, particularly remote cardiac care. Thus, it is challenging to propose an energy efficient technique for automatic ECG diagnosis (AED) to be embedded into the wireless sensor. Due to the high resource requirements, classical AED methods are unsuitable for pervasive cardiac care (PCC) applications. This paper proposes an embedded real-time AED algorithm dedicated to PCC sys-tems. This AED algorithm consists of a QRS detector and a rhythm classifier. The QRS detector adopts the linear time-domain statistical and syntactic analysis method and the geometric feature extraction modeling technique. The rhythm classifier employs the self-learning expert system and the confidence interval method. Currently, this AED algorithm has been implemented and evaluated on the PCC system for 30 patients in the Gabriel Monpied hospital (CHRU of Clermont-Ferrand, France) and the MIT-BIH cardiac arrhythmias da-tabase. The overall results show that this energy efficient algorithm provides the same performance as the classical ones.

Analysis and Comparison of Five Kinds of Typical Device-Level Embedded Operating Systems

Today, the number of embedded system was applied in the field of automation and control has far exceeded a variety of general-purpose computer. Embedded system is gradually penetrated into all fields of human society, and ubiquitous embedded applications constitute the 'ubiquitous' computing era. Embedded operating system is the core of the em-bedded system, and it directly affects the performance of the whole system. Our Liaoning Provincial Key Laboratory of Embedded Technology has successfully developed five kinds of device-level embedded operating systems by more than ten years’ efforts, and these systems are Webit 5.0, Worix, μKernel, iDCX 128 and μc/os-II 128. This paper mainly analyses and compares the implementation mechanism and performance of these five kinds of device-level embedded operating systems in detail.

Context-Based Mobile User Interface

Context awareness is increasingly gaining applicability in interactive ubiquitous mobile computing systems. Each context-aware application has its own set of behaviors to react to context modifications. Hence, every software engineer needs to clearly understand the goal of the development and to categorize the context in the application. We incorporate context-based modifications into the appearance or the behavior of the interface, either at the design time or at the run time. In this paper, we present application behavior adaption to the context modification via a context-based user interface in a mobile application. We are interested in a context-based user interface in a mobile device that is automatically adapted based on the context information. We use the adaption tree, named in our methodology, to represent the adaption of mobile device user interface to various context information. The context includes the user’s domain information and dynamic environment changes. Each path in the adaption tree, from the root to the leaf, presents an adaption rule. An e-commerce application is chosen to illustrate our approach. This mobile application was developed based on the adaption tree in the Android platform. The automatic adaption to the context information has enhanced human-computer interactions.