Co-design for an SoC embedded network controller

With the development of Ethernet systems and the growing capacity of modem silicon technology, embedded communication networks are playing an increasingly important role in embedded and safety critical systems. Hardware/software co-design is a methodology for solving design problems in processor based embedded systems. In this work, we implemented a new 1-cycle pipeline microprocessor and a fast Ethemet transceiver and established a low cost, high performance embedded network controller, and designed a TCP/IP stack to access the Intemet. We discussed the hardware/software architecture in the forepart, and then the whole system-on-a-chip on Altera Stratix EP1S25F780C6 device. Using the FPGA environment and SmartBit tester, we tested the system＇s throughput. Our simulation results showed that the maximum throughput of Ethemet packets is up to 7 Mbps, that of UDP packets is up to 5.8 Mbps, and that of TCP packets is up to 3.4 Mbps, which showed that this embedded system can easily transmit basic voice and video signals through Ethemet, and that using only one chip can realize that many electronic devices access to the Intemet directly and get high performance.

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/

单片机系统接入Internet设计中Embedded Web Server的实现

嵌入式Internet的设计中,EmbeddedWebServer的实现关键在于使系统支持HTTP(超文本传输协议),嵌入式HTTP服务器是控制网络的关键设备,也是实现设备Internet远程监控的关键技术,本论文对HTTP协议进行了分析,对任务函数进行了设计,实现了单片机系统接入Internet设计中EmbeddedWebServer的实现.

Network Multifunctional Substation with Embedded System in Coal Mine

In order to solve the problems of mining monitor and control systems during the construction process of digital mining combined with network and embedded technologies, the kernel access equipment of a mining monitor and control system was proposed and designed. It is the architecture of a mining embedded network multifunctional substation. This paper presents the design of hardware and software of the substation in detail. Finally, the system’s ef- ficiency was validated through experimentation.

Implementation of Embedded Ethernet Based on Hardware Protocol Stack in Substation Automation System

Embedded Ethernet technology has been utilized increasingly widely as the communication mode in the substation automation system(SAS).This paper introduces the current applying situation about embedded Ethernet in SAS First.After analyzing the protocol levels used in SAS based on embedded Ethernet and the differences between the TCP and UDP,UDP/IP is selected as the communication protocol between the station-level and bay-level devices for its real-time characteristic.Then a new kind of implementation of the embedded Ethernet is presented based on hardware protocol stack.The designed scheme can be implemented easily,reduce cost significantly and shorten developing cycle.

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.

Varactor-tunable frequency selective surface with an embedded bias network

A new technique for designing a varactor-tunable frequency selective surface （FSS） with an embedded bias network is proposed and experimentally verified. The proposed FSS is based on a square-ring slot FSS. The frequency tuning is achieved by inserting varactor diodes between the square mesh and each unattached square patch. The square mesh is divided into two parts for biasing the varactor diodes. Full-wave numerical simulations show that a wide tuning range can be achieved by changing the capacitances of these loaded varactors. Two homo-type samples using fixed lumped capacitors are fabricated and measured using a standard waveguide measurement setup. Excellent agreement between the measured and simulated results is demonstrated.

Remote Multimedia Monitoring System Based on Embedded Web Server for Networked Manufacturing

A new-style remote monitoring system is proposed, which is based on enterprises' embedded web servers and can be widely used in enterprises' networked manufacturing systems. The principle and characteristics of remote monitoring system based on embedded web server are analyzed. Such a kind of system for networked manufacturing is designed, and it proves efficient and feasible in promoting communication among enterprises, improving designing and scheduling, decreasing facility failure and reducing product cost.

Retraining Deep Neural Network with Unlabeled Data Collected in Embedded Devices

Because of computational complexity,the deep neural network(DNN)in embedded devices is usually trained on high-performance computers or graphic processing units(GPUs),and only the inference phase is implemented in embedded devices.Data processed by embedded devices,such as smartphones and wearables,are usually personalized,so the DNN model trained on public data sets may have poor accuracy when inferring the personalized data.As a result,retraining DNN with personalized data collected locally in embedded devices is necessary.Nevertheless,retraining needs labeled data sets,while the data collected locally are unlabeled,then how to retrain DNN with unlabeled data is a problem to be solved.This paper proves the necessity of retraining DNN model with personalized data collected in embedded devices after trained with public data sets.It also proposes a label generation method by which a fake label is generated for each unlabeled training case according to users’feedback,thus retraining can be performed with unlabeled data collected in embedded devices.The experimental results show that our fake label generation method has both good training effects and wide applicability.The advanced neural networks can be trained with unlabeled data from embedded devices and the individualized accuracy of the DNN model can be gradually improved along with personal using.

Distribution of combustible gas alarm based on embedded Ethernet technology

One kind of combustible gas alarms based on industrial Ethernet was designed to prevent the gas leakage in industrial production sites, The alarm adopted the high performance microprocessor LPC2214 as the main chip. The embedded operating system μC/OS-Ⅱand TCP/IP protocol stack uIP running on LPC2214 constitute a development platform of application of the combustible gas alarm, The test shows that it can automatically and continuously detect combustible gas in industrial production sites in several positions;it can give out sound-light alarm and take protective measures immediately against the gas leakage; and it can send the detected data to PC through the Ethernet interface to realize the remote detection. The designed project provides a reference to design industrial devices based on industrial Ethernet

Secure encryption embedded processor design for wireless sensor network application

This paper presents a new encryption embedded processor aimed at the application requirement of wireless sensor network （WSN）. The new encryption embedded processor not only offers Rivest Shamir Adlemen （RSA）, Advanced Encryption Standard （AES）, 3 Data Encryption Standard （3 DES） and Secure Hash Algorithm 1 （SHA - 1 ） security engines, but also involves a new memory encryption scheme. The new memory encryption scheme is implemented by a memory encryption cache （MEC）, which protects the confidentiality of the memory by AES encryption. The experi- ments show that the new secure design only causes 1.9% additional delay on the critical path and cuts 25.7% power consumption when the processor writes data back. The new processor balances the performance overhead, the power consumption and the security and fully meets the wireless sensor environment requirement. After physical design, the new encryption embedded processor has been successfully tape-out.

Design and Implementation of Embedded Transmission Control Protocol/Internet Protocol Network Based on System-on-programmable Chip

A scheme of transmission control protocol/Internet protocol（TCP/IP） network system based on system-on-programmable chip（SOPC） is proposed for the embedded network communication. In this system, Nios processor, Ethernet controller and other peripheral logic circuits are all integrated on a Stratix Ⅱ field programmable gate array （FPGA） chip by using SOPC builder design software. And the network communication is realized by transplanting MicroC/OS Ⅱ （uC/OS Ⅱ ） operation system and light weight Internet protocol（LwIP）. The design idea, key points and the structures of both software and hardware of the system are presented and ran with a telecommunication example. The experiment shows that the embedded TCP/IP network system has high reliability and real-time performance.

Optimum Sizing and Siting of an Embedded Solar Photovoltaic Generation: A Case Study of 33 kv Sub-Transmission Network at Tarkwa, Ghana

The interconnection of Solar PV to the Tarkwa Bulk Supply Point (BSP) has become necessary in order to provide additional capacity to meet the ever-increasing demand of Tarkwa and its environs during the day. The Solar PV Plant will support the Tarkwa BSP during the day. In this study, a grid impact analysis for the integration of Solar PV plant at three points of common coupling (PCC) at Tarkwa Bulk Supply Point’s (BSP) 33 kV network of the Electricity Company of Ghana was carried out. The three PCCs were Tarkwa BSP, Ghana Australia Gold (GAG) Substation and Darmang Substation. Simulations and detailed analysis were carried out with the use of CYME Software (Cyme 8.0 Rev 05). The Solar PV was integrated at varying penetration levels of 9 MWp, 11 MWp, 14 MWp, 16 MWp, 18 MWp, 20 MWp and 23 MWp (representing penetration levels of 40%, 50%, 60%, 70%, 80%, 90% and 100%, respectively) of the 2020 projected light demand of Tarkwa BSP 25.15 MVA network at an average power factor of 0.903. From the study, the optimum capacity of Solar PV power that could be connected is 9 MWp at an optimum inverter power factor of 0.94 lagging, and the GAG Substation was identified as the optimal location. The stiffness ratio at the optimal location was determined as 41.9, a figure which is far greater than the minimum standard value of 5, and gives an indication of very little voltage control problems in the operation of the proposed Solar PV interconnection. The integration of the optimum 9 MW Solar PV Plant to the Tarkwa network represents an additional 12.77% capacity, decreased the technical losses by 7.76%, and increased the voltage profile by 1.97%.

The Design and Realization of Network Remote Control Based on Embedded Systems

In order to achieve remote control problems for the intelligent home appliances, The paper presents a realization method through the Internet and GSM remote to control appliances of smart home, and given circuit. And described in detail the hardware and software design of smart home appliances and their control method. Test results show that the system is stable and reliable.

Internet-Based Technologies for Design of Embedded Systems

In recent years, online engineering technologies are widely distributed and developed. Their influence on society is very strong. The Internet technology has provided additional opportunities for a new development level of education, design and production. Associations and scientific conferences in the field of online engineering that appeared, seek to foster practices in education and research in higher education institutions and the industry on online engineering. A particular challenge for online engineering is how to extend the traditional equipments and laboratories to the Internet. A method of the embedded systems design with using online laboratory is described in this paper. Also, in this paper the experimental set of remote laboratory which allows carrying out hardware/software oriented design of the embedded control system of a mobile platform is considered.

FirmVulSeeker—BERT and Siamese Network-Based Vulnerability Search for Embedded Device Firmware Images

In recent years,with the development of the natural language processing(NLP)technologies,security analyst began to use NLP directly on assembly codes which were disassembled from binary executables in order to examine binary similarity,achieved great progress.However,we found that the existing frameworks often ignored the complex internal structure of instructions and didn’t fully consider the long-term dependencies of instructions.In this paper,we propose firmVulSeeker—a vulnerability search tool for embedded firmware images,based on BERT and Siamese network.It first builds a BERT MLM task to observe and learn the semantics of different instructions in their context in a very large unlabeled binary corpus.Then,a finetune mode based on Siamese network is constructed to guide training and matching semantically similar functions using the knowledge learned from the first stage.Finally,it will use a function embedding generated from the fine-tuned model to search in the targeted corpus and find the most similar function which will be confirmed whether it’s a real vulnerability manually.We evaluate the accuracy,robustness,scalability and vulnerability search capability of firmVulSeeker.Results show that it can greatly improve the accuracy of matching semantically similar functions,and can successfully find more real vulnerabilities in real-world firmware than other tools.

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.

A Design of Penetration Ammunition Fuse System Based on Embedded Technology

The hard target smart fuse of penetration ammunition is developing to be smaller, lighter, smarter and multifunction. After analyzing the characteristics of high-g accelerating signals and the penetration algorithms, this paper provides a solution of penetration ammunition fuse system based on embedded technology. This fuse system realizes acquisition of the high-g accelerating signals and uses the appropriate penetration algorithms to process them. The fuse system can not only make the same type of penetration ammunition to attack different kinds of objects accurately, but also meet the other requirements of the function of penetration ammunition fuse system.

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.

Nurses’job embeddedness and turnover intention:A systematic review and meta-analysis

Objective:This study aimed to review the relationship between job embeddedness and turnover intentions among nurses and explore the effects of the Job Embeddedness Scale,number of years in the career,education,and marital status on this relationship.Methods:The review was conducted by searching the China Knowledge Resource Integrated Database(CNKI),Weipu Database(CQVIP),China Biology Medicine(CBM),Wanfang Database,PubMed,Web of Science,Embase,CINAHL,and APA-PsycNet for articles on nurses’job embeddedness and turnover from intention up to March 2024.The research quality was evaluated using the Agency for Healthcare Research and Quality(AHRQ)assessment criteria.The review protocol has been registered on PROSPERO[CRD42023483947].Results:The results of this review included 47 studies consisting of 15,742 nurses from seven countries worldwide.A moderate negative correlation was found between job embeddedness and turnover intention(r=0.487).Furthermore,on-the-job embeddedness(r=0.527)was more negatively associated with turnover intention than off-the-job embeddedness(r=0.234).The highest negative correlation was found between sacrifice and turnover intention(r=0.460),while the lowest was for the link(r=0.185).Furthermore,the relationship between job embeddedness and its dimensions with turnover intention was affected by different job embeddedness scales,number of years in the career,education,and marital status(P<0.05).Conclusion:This systematic review and meta-analysis analyzed the relationships between nurses’job embeddedness,dimensions,and turnover intention.Meanwhile,subgroup analysis and meta-regression explored the factors influencing these relationships.It is an important reference for nurse managers to promote nurse retention.