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.

ARM-Based Embedded System Platform and Its Portability Research

Taking ARM as the hardware platform, the embedded system is built from both hardware and software aspects with the application as the center. In the hardware design, build the hardware platform scheme, design the schematic diagram as well as PCB, complete the hardware debugging, and ensure the system hardware platform function;in the software design, optimize the three-stage pipeline structure of ARM instruction system, design the instruction set, install the embedded system on the virtual machine, build the cross-toolchain, and set up the correct NFS network file system. Finish the design of the ARM-based embedded system platform, combined with the hardware requirements of the experimental platform, transplant the powerful Uboot as the Bootloader of the system, and further transplant the Linux-2.6. 32 kernel to the system start the operation normally, and finally, build the root file to finish the study of its portability.

Key Technology of Embedded System Implementation for Software-based CNC System

The software-based computer numerical control（CNC） system includes three types of tasks： periodic real-time tasks, aperiodic real-time tasks, and non-real-time tasks. The tasks are characterized by concurrency, hybridization, and correlation, which make system implementation difficult. The conventional scheduling algorithm can not meet the demands of system implementation in the software-based CNC system completely. The uncertainty factors when running real-time tasks affect control performance by degrading manufacturing accuracy as a result of system resource and processor use restrictions. To address the technical difficulty of embedded system implementation, a novel fuzzy feedback scheduling algorithm based on output jitter of key real-time tasks for a software-based CNC system is proposed. Time characteristics, such as sampling jitter, input-output jitter, and non-schedulability are discussed, followed by quantification through simulations of the impact of time characteristics on manufacturing accuracy. On the basis of this research, the scheduler architecture is designed, and then the algorithm table is calculated. When the system resource changes, the key periodic real-time tasks meet their deadlines by means of dynamically adjusting the task period. The simulated results show that the machining precision rises by an order of magnitude for the proposed scheduler in resource-constrained software-based CNC systems. Moreover, unlike conventional feedback scheduling methods, the algorithm in this paper does not rely on the availability of task execution times and is easy to implement while incurring only a small overhead.

Modeling and Analysis of Scheduling for Distributed Real-time Embedded Systems

Aimed at the deficiencies of resources based time Petri nets （RBTPN） in doing scheduling analysis for distributed real-time embedded systems, the assemblage condition of complex scheduling sequences is presented to easily compute scheduling length and simplify scheduling analysis. Based on this, a new hierarchical RBTPN model is proposed. The model introduces the definition of transition border set, and represents it as an abstract transition. The abstract transition possesses all resources of the set, and has the highest priority of each resource; the cxecution time of abstract transition is the longest time of all possible scheduling sequences. According to the characteristics and assemblage condition of RBTPN, the refinement conditions of transition border set are given, and the conditions ensure the correction of scheduling analysis. As a result, it is easy for us to understand the scheduling model and perform scheduling analysis.

MOOC construction of major core course and reform of Hybrid Teaching Mode Taking "principle of embedded system" as an example

The development of MOOC directly promotes the reform of physical classroom teaching,and leads to the reform of teaching mode and teaching method in the direction of improving teachers’teaching quality and students’learning effect and innovation ability.In order to meet the needs of MOOC teaching reform,based on the MOOC built by ourselves and running on the MOOC platform,this paper puts forward the hybrid teaching mode reform of the core courses of an computer specialty,which combines online and offline in depth.Sort out the knowledge system of an embedded system,build MOOC and put it online on domestic well-known MOOC platform,compile supporting teaching materials,and form an organic combination of online and offline teaching resources;proposing a hybrid teaching mode of online and offline combination,which focuses on interactive classroom teaching reform.On the basis of organizing students to carry out online autonomous learning,online and offline entity classroom carries out interactive classroom teaching reform;Using intelligent teaching tools to promote students to use mobile phones to participate in classroom learning,improve the universality of interactive teaching,carry out flipped classroom teaching,and improve the depth of interactive teaching.Based on the independent construction of MOOC,the hybrid teaching is carried out,which improves the pertinence of online teaching organization.The information-based teaching and flipped classroom teaching in the physical classroom improve the students’ability to solve problems,and lay a solid foundation for the improvement of teaching quality and learning effect.

A Decision Support Framework for the Choice of Languages and Methods for the Design of Real Time Embedded Systems

The choice of methods or design languages is a crucial phase in the development of systems and software, also for real time and embedded systems. An open question that remains in the design of these types of systems is to build a method, or to choose one among those existing, capable to cover the life cycle of a project, and particularly the development phases. This article contributes to answer the question, by proposing an approach based on a multi-criteria comparative study, of few languages and methods dedicated to the design of real time and embedded systems. The underlying objective of this work is to present to designers a wide range of approaches, and elements that can guide their choices. In order to reach this goal, we propose different comparison criteria. Each criterion is divided into sub-criteria, so that the designers can refine their choices according to the qualities they prefer and wish to have in the method or language. We also define a rating scale which is used to assess the retained languages and methods. The scores obtained from this assessment are presented in tables, one table per criterion, followed by a summary table giving the overall scores. Graphics built from these tables are provided and intend to facilitate the judgement and thus the choice of the designers.

Monitoring the Turmeric Finger Disease and Growth Characteristics Using Sensor Based Embedded System —A Novel Method

In this cyber era, novelty plays a prime role in the field of agriculture that majorly depends on computer-based measurements and control. Herein before, it was totally controlled and performed by the agriculturists. One of the technological innovative methods to measure and monitor the turmeric finger growth characteristics is the embedded system that is based on sensor array module such as flex sensor, temperature sensor and pH sensor. The experimental work has been designed and tested with five set of nodes and the growth of turmeric finger is tenuously monitored by measuring the change in flex resistance. Out of five nodes, two nodes were diseased. Deliberately, one node was left as such and the other node was treated with natural pesticides (pseudomonas and viride) to restrict the rhizome rot disease attack. After cultivation, it was found that the rhizome rot disease attack on the node which was treated with pesticides was comparatively lesser than the other node. The five different nodes have been used in the experimental work with an average flex sensor resistance of 3.962 cm/kΩ. In a nutshell, this proposed method manifests the farmers to detect the rhizome rot disease at its earlier stage and to prevent it as well by screening the growth of the turmeric fingers when it is under the soil.

A Low-Cost Active Control Multi-Fan Turbulence Wind Tunnel with an Embedded System to Generate Natural Wind

This paper describes a new actively controlled multi-fan wind tunnel that generates natural wind as a type of turbulence wind tunnel at a reduced cost. The driving section of the wind tunnel has 100 PC cooling fans that are controlled by an original embedded system. The fluctuating velocity wind is successfully generated with a mean velocity of 7 m/s and two turbulent intensities of 2% and 3% based on Karman’s power spectrum density function. The case of 2% has the integral scales of 5 m, 10m and 20 m, and the case of 3% has the integral scales of 3 m, 6 m and 15 m with a turbulence grid. In particular, the wind with the turbulent intensity of 2% satisfies the Kolmogorov’s -5/3 multiplication rule of inertial subrange with the frequency range from 0.01 Hz to 2.0 Hz. Consequently, the new wind tunnel can be used for studying engineering technology and research regarding conditions with natural wind.

A State-of-the-Art Survey on Real-Time Issues in Embedded Systems Virtualization

Virtualization has gained great acceptance in the server and cloud computing arena. In recent years, it has also been widely applied to real-time embedded systems with stringent timing constraints. We present a comprehensive survey on real-time issues in virtualization for embedded systems, covering popular virtualization systems including KVM, Xen, L4 and others.

Lookup Table Optimization for Sensor Linearization in Small Embedded Systems

This paper treats the problem of designing an optimal size for a lookup table used for sensor linearization. In small embedded systems the lookup table must be reduced to a minimum in order to reduce the memory footprint and intermediate table values are estimated by linear interpolation. Since interpolation introduces an estimation uncertainty that increases with the sparseness of the lookup table there is a trade-off between lookup table size and estimation precision. This work will present a theory for finding the minimum allowed size of a lookup table that does not affect the overall precision, i.e. the overall precision is determined by the lookup table entries’ precision, not by the interpolation error.

Embedded System Implementation of Airborne Communication Terminals

Airborne communication terminal is a key unit in Ad hoc network of aircrafts. This paper mainly focuses on its implementation by embedded system, which is based on Samsung S3C2410 chip. System architecture, Linux tailoring and touch-screen driver design are discussed in detail. Considering the requirements of stability and efficiency of the operating system, dynamic driver-loading method was employed firstly and only the necessary library files were transplanted to assist and test. The drivers finally were directly put into kernel configuration and then an integrated kernel was transplanted. Regarding to the problem of positioning issues on touch-screen, which is implemented in this system, an accurate positioning method is also presented.

Microkernel Development for Embedded Systems

This paper presents the development of a microkernel with a device driver controller for embedded systems. The implementation was done in C language aiming low cost microcontrollers. The proposed system allowed to perform soft real-time activities while keeping the drivers and the application isolated by a secure layer. The callback system proved itself extremely simple to use while still maintaining the security of the system regarding the temporal constraints.

Analysis and Programming of Kernel for Embedded Systems

In this study, we present a miniOS kernel implemented via analysis of the context switching, the scheduler, and the memory management of the original OS kernel for an embedded system based on ARM core. Since this is a large subject, we have limited our scope to them only that made up an embedded operating system. The implemented miniOS kernel is composed only by them, to the exclusion of all other functions of the original kernel. Our goal is to modify the OS kernel depending on the product function. The implementation method of the miniOS kernel can be applicable to any OS being mounted based on the ARM core. Modifying the kernel depending on the product function can improve the OS booting speed as well as save the system memory. The functions of the scheduler, the context switching, and the memory management are described with the source in each section. The miniOS kernel was implemented in the Assembly and C language and was verified through the build and the test. The results are shown in the Section 5.

New Approach for Hardware/Software Embedded System Conception Based on the Use of Design Patterns

This paper deals with a new hardware/software embedded system design methodology based on design pattern approach by development of a new design tool called smartcell. Three main constraints of embedded systems design process are investigated: the complexity, the partitioning between hardware and software aspects and the reusability. Two intermediate models are carried out in order to solve the complexity problem. The partitioning problem deals with the proposed hardware/software partitioning algorithm based on Ant Colony Optimisation. The reusability problem is resolved by synthesis of intellectual property blocks. Specification and integration of an intelligent controller on heterogeneous platform are considered to illustrate the proposed approach.

Design Pattern Representation for Safety-Critical Embedded Systems

Design Patterns, which give abstract solutions to commonly recurring design problems, have been widely used in the software and hardware domain. As non-functional requirements are an important aspect in the design of safety-critical embedded systems, this work focuses on the integration of non-functional implications in an existing design pattern concept. We propose a pattern representation for safety-critical embedded application design methods by including fields for the implications and side effects of the represented design pattern on the non-functional requirements of the overall systems. The considered requirements include safety, reliability, modifiability, cost, and execution time.

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.

Using deep learning in an embedded system for real-time target detection based on images from an unmanned aerial vehicle: vehicle detection as a case study

For a majority of remote sensing applications of unmanned aerial vehicles(UAVs),the data need to be downloaded to ground devices for processing,but this procedure cannot satisfy the demands of real-time target detection.Our objective in this study is to develop a real-time system based on an embedded technology for image acquisition,target detection,the transmission and display of the results,and user interaction while providing support for the interactions between multiple UAVs and users.This work is divided into three parts:(1)We design the technical procedure and the framework for the implementation of a real-time target detection system according to application requirements.(2)We develop an efficient and reliable data transmission module to realize real-time cross-platform communication between airborne embedded devices and ground-side servers.(3)We optimize the YOLOv4 algorithm by using the K-Means algorithm and TensorRT inference to improve the accuracy and speed of the NVIDIA Jetson TX2.In experiments involving static detection,it had an overall confidence of 89.6%and a rate of missed detection of 3.8%;in experiments involving dynamic detection,it had an overall confidence and a rate of missed detection of 88.2%and 4.6%,respectively.

Real-time K-TIG welding penetration prediction on embedded system using a segmentation-LSTM model

Keyhole tungsten inert gas(K-TIG)welding is capable of realizing single-sided welding and double-sided forming and has been widely used in medium and thick plate welding.In order to improve the accuracy of automatic weld identification and weld penetration prediction of robot in the process of large workpiece welding,a two-stage model is proposed in this paper,which can monitor the K-TIG welding penetration state in real time on the embedded system,called segmentation-LSTM model.The proposed system extracts 9 weld pool geometric features with segmentation network,and then extracts the weld gap using a traditional algorithm.Then these 10-dimensional features are input into the LSTM model to predict the penetration state,including under penetration,partial penetration,good penetration and over penetration.The recognition accuracy of the proposed system can reach 95.2%.In this system,to solve the difficulty of labeling data and lack of segmentation accuracy,an improved LabelMe capable of live-wire annotation tool and a novel loss function were proposed,respectively.The latter was also called focal dice loss,which enabled the network to achieve a performance of 0.933 mloU on the testing set.Finally,an improved slimming strategy compresses the network,making the segmentation network achieve real-time on the embedded system(RK3399pro).

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.