Embedded Internet环境下TCP/IP协议簇的约简

基于 Em bedded Internet技术下 ,为了实现非 Internet设备信息的共享和访问 ,作者对 TCP/ IP协议簇进行系统的研究 ,提出在设备中嵌入 thin TCP/ IP协议栈并使其能够实现与网络的透明互联 .对 TCP/ IP协议簇进行尽最大可能的约简而不使其失去标准和相应的机制 ,从而可以利用 TCP/ IP协议在设备与 Internet之间建立通讯联系 ,真正把设备纳入到网络的管理范围 ,实现设备的网络化和智能化管理 .设备中嵌入 TCP/

Aligned Elongation of Ag Nanoparticles Embedded in Silica Irradiated with High Energy Ni Ions

Metallic nanoparticle （NP） shapes have a significant influence on the property of composite embedded with metallic NPs. Swift heavy ion irradiation is an effective way to modify shapes of metallic NPs embedded in an amorphous matrix. We investigate the shape deformation of Ag NPs with irradiation fluence, and 357 MeV Ni ions are used to irradiate the silica containing Ag NPs, which are prepared by ion implantation and vacuum annealing. The UV-vis results show that the surface plasmon resonance （SPR） peak from Ag NPs shifts from 400 to 377nm. The SPR peak has a significant shift at fluence lower than 1 × 10^14 ions/cm2 and shows less shift at fluence higher than 1 × 10^14 ions/cm2. The TEM results reveal that the shapes of Ag NPs also show significant deformation at fluence lower than 1 × 10^14 ions/cm2 and show less deformation at fluence higher than 1 × 10^14 ions/cm2. The blue shift of the SPR peak is considered to be the consequence of defect production and Ag NP shape deformation, Based on the thermal spike model calculation, the temperature of the silica surrounding Ag particles first increases rapidly, then the region of Ag NPs close to the interface of Ag/silica is gradually heated. Therefore, the driven force of Ag NPs deformation is considered as the volume expansion of the first heated silica layer surrounding Ag NPs.

Efficient Visible Photoluminescence from Self-Assembled Ge QDs Embedded in Silica Matrix

Measuring the growth parameters of Ge quantum dots （QDs） embedded in SiO2/Si hetero-structure is pre- requisite for developing the optoelectronic devices such as photovoltaics and sensors. Their optical properties can be tuned by tailoring the growth morphology and structures, where the growth parameters＇ optimizations still need to be explored. We determine the effect of annealing temperature on surface morphology, structures and optical properties of Ge//SiO2//Si hetero-structure. Samples are grown via rf magnetron sputtering and subsequent characterizations are made using imaging and spectroscopic techniques.

Single-Photon Emission from GaAs Quantum Dots Embedded in Nanowires

A highly efficient single-photon source based on a semiconductor quantum dot （QD） is a promising candidate in quantum information processing. We report a single-photon source based on self-assembled GaAs QDs in nanowires with an extraction efficiency of 14%. The second-order correlation function g（2） （0） at saturate excitation power is estimated to be 0.28. The measured polarization of QD emission depends on the geometric relations between the directions of PL collection and the long axis of nanowires.

Effect of Nickel Distributions Embedded in Amorphous Carbon Films on Transport Properties

Electrical properties of C/Ni films are studied using four mosaic targets made of pure graphite and stripes of nickel with the surface areas of 1.78,3.21,3.92 and 4.64%.The conductivity data in the temperature range of400-500 K shows the extended state conduction.The conductivity data in the temperature range of 150-300 K shows the multi-phonon hopping conduction.The Berthelot-type conduction dominates in the temperature range of 50-150 K.The conductivity of the films in the temperature range about 〈 50 K is described in terms of variable-range hopping conduction.In low temperatures,the localized density of state around Fermi level（F）for the film deposition with 3.92% nickel has a maximum value of about 56.2×10^（17）cm^（-3）eV^（-1） with the minimum average hopping distance of about 3.43 × 10^（-6） cm.

Hengshui—A Pearl Embedded in Jizhong Plain

Situated in the Heilonggang Area of Southern Hebei Province, Hengshui City is the center of politics, economy and culture of Hengshui Prefecture, with a total area of 598 sq km and a population of 350,000. Since 1982, when Hengshui was approved to be built into a city, its economy has been growing rapidly. Now, annual GNP has topped RMB1.9059 billion, total industry and agriculture output value RMB 3.529 billion, and financial income RMB 176 million, putting it among the best in the province in composite economic index. Hengshui City stands in the

A THEORETICAL APPROACH TO THERMAL PROPERTY OF ARRAY OF CYLINDERS EMBEDDED IN HOMOGENEOUS MATRIX

We investigate in this article the thermal coliductivity of array Of cylinders embedded in a homogeneous matrix. Using Green's function, we confirm that the method invented by Rayleigh can be generalized to deal with thermal property of these systems. A technique for calculating effective thermal conductivities of these systems is proposed. As an example, we consider a system with square symmetry, and a neat formula for effective thermal conductivity is derived. We show that the method also includes the proof of Keller theorem.

Seismic analysis of cantilever earth retaining walls embedded in dry sand by simplified approaches and finite element method

In engineering practice simplified methods are essential to the seismic design of embedded earth retaining walls,as fullydynamic numerical analyses are costly,time-consuming and require specific expertise.Recently developed pseudostatic methods provide earth stresses and internal forces,even in those cases in which the strength of the soil surrounding the structure is not entirely mobilised.Semiempirical correlations or Newmark sliding block method provide an estimate of earthquake-induced permanent displacements.However,the use of these methods is hindered by uncertainties in the evaluation of a few input parameters,affecting the reliability of the methods.This study uses 1 D site response analyses and 2 D fully-dynamic finite element analyses to show that simplified methods can provide a reasonable estimate of the maximum bending moment and permanent displacements for stiff cantilever walls embedded in uniform sand,providing that a few input parameters are evaluated through semiempirical correlations and a simple 1 D site response analysis.

Quantum Confinement in GaAs Microcrystallites Embedded in SiO_(2) Thin Film

Semiconductor GaAs microcrystallites were embedded in SiO_(2) thin films by magnetron rf cosputtering technique.Structures of the thin films were characterized by transmission electron microscopy,x-ray diffraction and x-ray photoelectron microscopy.Average size of microcrystallites,depending on the substrate temperature during deposition,is 3-10nm.Absorption spectra of the films were measured.Blue shift of absorption edge was observed and discussed according to quantum confinement effect.

Planning Method of Ecological Embedded Industrial Parks

Exploration of the gentle slopes of low mountains and hills has already become a new topic in the development of urban land resources in hilly areas. For the high ecological sensitivity, tremendous cost of urban construction, as well as complicate utilization technology, planning and design of gentle slopes of low mountains and hills are faced with serious challenges. This paper took the planning of Yidu High-tech Industrial Park for example, to explore the design concepts and rational methods of planning "ecological embedded" industrial parks in hilly areas.

Numerical Analysis of the Composite Connection of Steel Joist Embedded in Concrete Girder

So far, numerous numerical studies have been conducted on the behavior of Composite Reinforced Concrete-Steel （RCS） beam-to-column connections. However, the lack of studies regarding the steel joist-concrete girder connection has yet to be addressed through comprehensive finite element methods to get an understanding of influential parameters. Hence, in this paper, composite connection of embedded steel joist in concrete girder is investigated with an appropriate finite element software, namely, ABAQUS. The validity of the proposed model is examined by the comparison made with the test data in literature. Results indicate that maximum bending capacity of the connection is achieved when embedment ratio is 1.78. Moreover, double web angles in the embedment region significantly reduce the embedment length required to achieve the maximum bending capacity. Finally, damage analyses show that bending capacity of concrete girder is slightly reduced in the connection zone.

Advances of embedded resistive random access memory in industrial manufacturing and its potential applications

Embedded memory,which heavily relies on the manufacturing process,has been widely adopted in various industrial applications.As the field of embedded memory continues to evolve,innovative strategies are emerging to enhance performance.Among them,resistive random access memory(RRAM)has gained significant attention due to its numerousadvantages over traditional memory devices,including high speed(<1 ns),high density(4 F^(2)·n^(-1)),high scalability(~nm),and low power consumption(~pJ).This review focuses on the recent progress of embedded RRAM in industrial manufacturing and its potentialapplications.It provides a brief introduction to the concepts and advantages of RRAM,discusses the key factors that impact its industrial manufacturing,and presents the commercial progress driven by cutting-edge nanotechnology,which has been pursued by manysemiconductor giants.Additionally,it highlights the adoption of embedded RRAM in emerging applications within the realm of the Internet of Things and future intelligent computing,with a particular emphasis on its role in neuromorphic computing.Finally,the review discusses thecurrent challenges and provides insights into the prospects of embedded RRAM in the era of big data and artificial intelligence.

EG-STC: An Efficient Secure Two-Party Computation Scheme Based on Embedded GPU for Artificial Intelligence Systems

This paper presents a comprehensive exploration into the integration of Internet of Things(IoT),big data analysis,cloud computing,and Artificial Intelligence(AI),which has led to an unprecedented era of connectivity.We delve into the emerging trend of machine learning on embedded devices,enabling tasks in resource-limited environ-ments.However,the widespread adoption of machine learning raises significant privacy concerns,necessitating the development of privacy-preserving techniques.One such technique,secure multi-party computation(MPC),allows collaborative computations without exposing private inputs.Despite its potential,complex protocols and communication interactions hinder performance,especially on resource-constrained devices.Efforts to enhance efficiency have been made,but scalability remains a challenge.Given the success of GPUs in deep learning,lever-aging embedded GPUs,such as those offered by NVIDIA,emerges as a promising solution.Therefore,we propose an Embedded GPU-based Secure Two-party Computation(EG-STC)framework for Artificial Intelligence(AI)systems.To the best of our knowledge,this work represents the first endeavor to fully implement machine learning model training based on secure two-party computing on the Embedded GPU platform.Our experimental results demonstrate the effectiveness of EG-STC.On an embedded GPU with a power draw of 5 W,our implementation achieved a secure two-party matrix multiplication throughput of 5881.5 kilo-operations per millisecond(kops/ms),with an energy efficiency ratio of 1176.3 kops/ms/W.Furthermore,leveraging our EG-STC framework,we achieved an overall time acceleration ratio of 5–6 times compared to solutions running on server-grade CPUs.Our solution also exhibited a reduced runtime,requiring only 60%to 70%of the runtime of previously best-known methods on the same platform.In summary,our research contributes to the advancement of secure and efficient machine learning implementations on resource-constrained embedded devices,paving the way for broader adoption of AI technologies in various applications.

CL2ES-KDBC:A Novel Covariance Embedded Selection Based on Kernel Distributed Bayes Classifier for Detection of Cyber-Attacks in IoT Systems

The Internet of Things(IoT)is a growing technology that allows the sharing of data with other devices across wireless networks.Specifically,IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks.In this framework,a Covariance Linear Learning Embedding Selection(CL2ES)methodology is used at first to extract the features highly associated with the IoT intrusions.Then,the Kernel Distributed Bayes Classifier(KDBC)is created to forecast attacks based on the probability distribution value precisely.In addition,a unique Mongolian Gazellas Optimization(MGO)algorithm is used to optimize the weight value for the learning of the classifier.The effectiveness of the proposed CL2ES-KDBC framework has been assessed using several IoT cyber-attack datasets,The obtained results are then compared with current classification methods regarding accuracy(97%),precision(96.5%),and other factors.Computational analysis of the CL2ES-KDBC system on IoT intrusion datasets is performed,which provides valuable insight into its performance,efficiency,and suitability for securing IoT networks.

“Instruction-Category” Approach of Test Suite Construction for Oven Embedded System

Being different from testing for popular GUI software, the “instruction-category” approach is proposed for testing embedded system. This approach is constructed by three steps including refining items, drawing instruction-brief and instruction-category, and constructing test suite. Consequently, this approach is adopted to test oven embedded system, and detail process is deeply discussed. As a result, the factual result indicates that the “instruction-category” approach can be effectively applied in embedded system testing as a black-box method for conformity testing.

Exploration of the Integration of Software Engineering Thinking into Embedded System Design Course

Engineering practice is the key bridge between college education and actual work in the industry.In order to deliver qualified talents with engineering quality to the industry,this paper explores integrating software engineering thinking into the Embedded System Design course.A practical and effective teaching mode is designed consisting of immersive learning,case-based learning,progressive practice,interactive learning,and autonomous learning.Through this teaching mode,multi-levels of closed-loop have been established including final project cycle closed-loop,testing cycle closed-loop,and product cycle closed-loop.During this process,students gradually transition to putting forward product requirements,carrying out design and development,thinking and solving problems,collaborating,and assuring quality from the perspective of software engineering.The practice results show that students’engineering quality has been significantly improved.

Teaching Reform and Practice of Embedded System Design Based on Outcome-Based Education

Embedded system design is the core course of the telecommunication major in engineering universities,which combines software and hardware through embedded development boards.Aiming at the problems existing in traditional teaching,this paper proposes curriculum teaching reform based on the outcome-based education(OBE)concept,including determining course objectives,reforming teaching modes and methods,and improving the curriculum assessment and evaluation system.After two semesters of practice,this method not only enhances students’learning initiative but also improves teaching quality.

Simultaneous multi-material embedded printing for 3D heterogeneous structures

In order to mimic the natural heterogeneity of native tissue and provide a better microenvironment for cell culturing,multi-material bioprinting has become a common solution to construct tissue models in vitro.With the embedded printing method,complex 3D structure can be printed using soft biomaterials with reasonable shape fidelity.However,the current sequential multi-material embedded printing method faces a major challenge,which is the inevitable trade-off between the printed structural integrity and printing precision.Here,we propose a simultaneous multi-material embedded printing method.With this method,we can easily print firmly attached and high-precision multilayer structures.With multiple individually controlled nozzles,different biomaterials can be precisely deposited into a single crevasse,minimizing uncontrolled squeezing and guarantees no contamination of embedding medium within the structure.We analyse the dynamics of the extruded bioink in the embedding medium both analytically and experimentally,and quantitatively evaluate the effects of printing parameters including printing speed and rheology of embedding medium,on the 3D morphology of the printed filament.We demonstrate the printing of double-layer thin-walled structures,each layer less than 200μm,as well as intestine and liver models with 5%gelatin methacryloyl that are crosslinked and extracted from the embedding medium without significant impairment or delamination.The peeling test further proves that the proposed method offers better structural integrity than conventional sequential printing methods.The proposed simultaneous multi-material embedded printing method can serve as a powerful tool to support the complex heterogeneous structure fabrication and open unique prospects for personalized medicine.

A Self‑Powered,Highly Embedded and Sensitive Tribo‑Label‑Sensor for the Fast and Stable Label Printer

Label-sensor is an essential component of the label printer which is becoming a most significant tool for the development of Internet of Things(IoT).However,some drawbacks of the traditional infrared label-sensor make the printer fail to realize the high-speed recognition of labels as well as stable printing.Herein,we propose a selfpowered and highly sensitive tribo-label-sensor(TLS)for accurate label identification,positioning and counting by embedding triboelectric nanogenerator into the indispensable roller structure of a label printer.The sensing mechanism,device parameters and deep comparison with infrared sensor are systematically studied both in theory and experiment.As the results,TLS delivers 6 times higher signal magnitude than traditional one.Moreover,TLS is immune to label jitter and temperature variation during fast printing and can also be used for transparent label directly and shows long-term robustness.This work may provide an alternative toolkit with outstanding advantages to improve current label printer and further promote the development of IoT.

Oxygen functionalization-assisted anionic exchange toward unique construction of flower-like transition metal chalcogenide embedded carbon fabric for ultra-long life flexible energy storage and conversion

The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion application.The NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside CC.Thus obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode configuration.Moreover,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed cathode.Furthermore,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and OER.Hence,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.