A Retrodirective Array Enabled by CMOS Chips for Two-Way Wireless Communication with Automatic Beam Tracking

This article proposes and demonstrates a retrodirective array(RDA)for two-way wireless communication with automatic beam tracking.The proposed RDA is enabled by specifically designed chips made using a domestic complementary metal-oxide semiconductor(CMOS)process.The highly integrated CMOS chip includes a receiving(Rx)chain,a transmitting(Tx)chain,and a unique tracking phaselocked loop(PLL)for the crucial conjugated phase recovery in the RDA.This article also proposes a method to reduce the beam pointing error(BPE)in a conventional RDA.To validate the above ideas simply yet without loss of generality,a 2.4 GHz RDA is demonstrated through two-way communication links between the Rx and Tx chains,and an on-chip quadrature coupler is designed to achieve a nonretrodirective signal suppression of 23 dBc.The experimental results demonstrate that the proposed RDA,which incorporates domestically manufactured low-cost 0.18 lm CMOS chips,is capable of automatically tracking beams covering±40with a reduced BPE.Each CMOS chip in the RDA has a compact size of 4.62 mm^(2) and a low power consumption of 0.15 W.To the best of the authors’knowledge,this is the first research to demonstrate an RDA with a fully customized CMOS chip for wireless communication with automatic beam tracking。

Reference-frame-independent quantum key distribution with two-way classical communication

The data post-processing scheme based on two-way classical communication(TWCC)can improve the tolerable bit error rate and extend the maximal transmission distance when used in a quantum key distribution(QKD)system.In this study,we apply the TWCC method to improve the performance of reference-frame-independent quantum key distribution(RFI-QKD),and analyze the influence of the TWCC method on the performance of decoy-state RFI-QKD in both asymptotic and non-asymptotic cases.Our numerical simulation results show that the TWCC method is able to extend the maximal transmission distance from 175 km to 198 km and improve the tolerable bit error rate from 10.48%to 16.75%.At the same time,the performance of RFI-QKD in terms of the secret key rate and maximum transmission distance are still greatly improved when statistical fluctuations are considered.We conclude that RFI-QKD with the TWCC method is of practical interest.

Beamforming Design for IRS-and-UAV-Aided Two-Way Amplify-and-Forward Relay Networks in Maritime IoT

In this paper,an intelligent reflecting surface(IRS)-and-unmanned aerial vehicle(UAV)-assisted two-way amplify-and-forward(AF)relay network in maritime Internet of Things(IoT)is proposed,where ship1(S1)and ship2(S2)can be viewed as data collecting centers.To enhance the message exchange rate between S1 and S2,a problem of maximizing minimum rate is cast,where the variables,namely AF relay beamforming matrix and IRS phase shifts of two time slots,need to be optimized.To achieve a maximum rate,a low-complexity alternately iterative(AI)scheme based on zero forcing and successive convex approximation(LC-ZF-SCA)algorithm is presented.To obtain a significant rate enhancement,a high-performance AI method based on one step,semidefinite programming and penalty SCA(ONSSDP-PSCA)is proposed.Simulation results show that by the proposed LC-ZF-SCA and ONS-SDP-PSCA methods,the rate of the IRS-and-UAV-assisted AF relay network surpass those of with random phase and only AF relay networks.Moreover,ONS-SDP-PSCA perform better than LC-ZF-SCA in aspect of rate.

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.

Security-Reliability Analysis and Optimization for Cognitive Two-Way Relay Network with Energy Harvesting

This paper investigates the security and reliability of information transmission within an underlay wiretap energy harvesting cognitive two-way relay network.In the network,energy-constrained secondary network(SN)nodes harvest energy from radio frequency signals of a multi-antenna power beacon.Two SN sources exchange their messages via a SN decode-and-forward relay in the presence of a multiantenna eavesdropper by using a four-phase time division broadcast protocol,and the hardware impairments of SN nodes and eavesdropper are modeled.To alleviate eavesdropping attacks,the artificial noise is applied by SN nodes.The physical layer security performance of SN is analyzed and evaluated by the exact closed-form expressions of outage probability(OP),intercept probability(IP),and OP+IP over quasistatic Rayleigh fading channel.Additionally,due to the complexity of OP+IP expression,a self-adaptive chaotic quantum particle swarm optimization-based resource allocation algorithm is proposed to jointly optimize energy harvesting ratio and power allocation factor,which can achieve security-reliability tradeoff for SN.Extensive simulations demonstrate the correctness of theoretical analysis and the effectiveness of the proposed optimization algorithm.

“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.

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.

Are social embeddedness associated with food risk perception under media coverage?

Traceability system has received wide attention in solving food safety issues, via which food information could be tracked back to producer/farmers. Consumers need to obtain this information from producers or social networks, trust in the information,and consequently assess perceived risks, especially when food scandals are exposed to the media. In this study, we introduce the social embeddedness theory to understand how consumers’ social activities affect their risk perceptions on traceable food. Specifically, we investigate how risk perceptions are predicted by the interpersonal relationships, organizational level and social-level relationships. Results show that the interpersonal relationships were associated with lower levels of risk perceptions, while organizational and social relationships impacted consumer’s risk perceptions at middle and higher levels,respectively. Results also show that the "ripple effect" extended to effect of risk events with negative information, however,did not exist for the group exposed to positive information. Potential food safety implications have been proposed to identify for effective risk mitigation under media coverages.

Socio-cultural Embeddedness of Spatial Agglomeration of Creative Industries in Shanghai

Rapidly emerged creative industries receive increasing attention from a variety of disciplines. However, the space features of creative industries and its association with local socio-cultural contexts have not been fully understood, especially at a micro-city level. This study attempts to understand the agglomeration of creative industries in Shanghai from the sociology perspective. For this study, this paper utilizes primarily a questionnaire survey to explain the space features of creative industries in Shanghai. The results indicate an extensive socio-cultural embeddedness of the agglomeration of creative industries in Shanghai. First, strong emphasis on face-to-face contacts by creative professionals makes geographical agglomeration necessary for creative industries. Second, the reason why inner city of Shanghai is popular among creative professionals and enterprises lies in the diversity of cultures and special environment of the former colonial zones of Shanghai. Additionally, highly concentrated dining and entertainment facilities in the central city of Shanghai offer creative workers social networking places and nightlife venues. Third, as the educational attainment of local citizens and the protection of intellectual property are highly stressed by creative professionals, research and design specialized creative industries are more likely located near universities and research institutes.

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.

Influencing Factors of Organizational Learning Capability : From the Perspective of Knowledge Embeddedness

Organizational learning capability is an important embodiment of the competitive advantage of enterprises in the era of knowledge economy. Based on the embeddedness theory,six factors are discussed that influence organizational learning capability from the perspective of knowledge embeddedness: employees embeddedness, tools embeddedness, tasks embeddedness,interpersonal relationship embeddedness, organizational culture embeddedness and network environment embeddedness. Combined with the survey data of textile and apparel manufacturing industry,the research proves the important function of knowledge embeddedness in the construction of organizational learning capability, and proposes three research countermeasures for industrial upgrading.

Do Personality Variables Predict Job Embeddedness and Proclivity to Be Absent from Work?

The current knowledge base lacks evidence about situational-and surface-level personality variables and their impacts on job embeddedness and proclivity to be absent from work.With this recognition,drawing from the hierarchical personality model and fit theory as well as job embeddedness theory,our paper explores the influences of job resourcefulness(JR)and customer orientation(CO)on job embeddedness and propensity to be absent from work.We tapped time-lagged data gathered from hotel customer-contact employees in the United Arab Emirates to assess the aforementioned linkages via structural equation modeling.CO is a complete mediator between JR and job embeddedness,while job embeddedness completely mediates the linkage between CO and absence intentions.Specifically,hotel employees who can work under a resource-depleted environment are high on CO and therefore display job embeddedness at elevated levels.In addition,customer-oriented hotel employees have higher job embeddedness and therefore exhibit lower absence intentions.

Multi-case Study of Entrepreneurial Path Choice: Based on the Job Embeddedness of Tech-entrepreneur

This study analyzes opportunity recognition and development from the perspective of job embeddedness based on entrepreneurial action of tech-entrepreneur. The impact of job embeddedness to entrepreneurial path choice of tech-entrepreneur is tested by multi-case study. This paper also provides theoretic evidence to enhance the possibility of success of start-ups for entrepreneurs.

Some Comments on Embeddedness, Knowledge Transfer, Industry Clusters and Global Competitiveness

This paper develops a dynamic theoretical framework for global competitiveness, which describes the relationships among organizations in an industry cluster. The spiral for knowledge transfer, culture variables and embeddedness influence knowledge transfer. Embeddedness and knowledge transfer are the key determinants of industry clusters that lead to global competitiveness. Industry clusters are characterized by external economies, generalized reciprocity and flexible specialization.

Evaluation of the Predicted Particle Properties (P3) Microphysics Scheme in Simulations of Stratiform Clouds with Embedded Convection

To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with two P3 versions,P3-nc and P3-2ice,were evaluated against rain gauge,radar,and aircraft observations.A series of sensitivity experiments were conducted with different collection efficiencies between ice and cloud droplets.The comparison of the precipitation evolution between P3-nc and P3-2ice suggested that both P3 versions overpredicted surface precipitation along the Taihang Mountains but underpredicted precipitation in the localized region on the leeward side.P3-2ice had slightly lower peak precipitation rates and smaller total precipitation amounts than P3-nc,which were closer to the observations.P3-2ice also more realistically reproduced the overall reflectivity structures than P3-nc.A comparison of ice concentrations with observations indicated that P3-nc underestimated aggregation,whereas P3-2ice produced more active aggregation from the self-collection of ice and ice-ice collisions between categories.Efficient aggregation in P3-2ice resulted in lower ice concentrations at heights between 4 and 6 km,which was closer to the observations.In this case,the total precipitation and precipitation pattern were not sensitive to riming.Riming was important in reproducing the location and strength of the embedded convective region through its impact on ice mass flux above the melting level.

Considering explosive charge shape and embedded depth in the design of concrete shelter thickness

Cost and safety are important considerations when designing the thickness of a protective reinforced concrete shelter.The blast perforation limit(BPL)is the minimum concrete shelter thickness that resists perforation under blast loading.To investigate the influence of the depth of embedment(DOE)and length-to-diameter ratio(L/D)of an explosive charge on the BPL,the results of an explosion test using a slender explosive partially embedded in a reinforced concrete slab were used to validate a refined finite element model.This model was then applied to conduct more than 300 simulations with strictly controlled variables,obtaining the BPLs for various concrete slabs subjected to charge DOEs ranging from0 to∞and L/D values ranging from 0.89 to 6.87.The numerical results were compared with the experimental results from published literature,further verifying the reliability of the simulation.The findings indicate that for the same explosive charge mass and L/D,the greater the DOE,the larger the critical residual thickness(Rc,defined as the difference between the BPL and DOE)up to a certain constant value;for the same explosive charge mass and DOE,the greater the L/D,the smaller the Rc.Thus,corresponding DOE and shape coefficients were introduced to derive a new equation for the BPL,providing a theoretical approach to the design and safety assessment of protective structures.

Investigating the Efficiency Coefficient of Pile Group in Clay Under Two-Way Lateral Load

This research investigates the behavior of a 2×2 pile group under two-directional lateral loads in addition to the vertical load.Through three-dimensional numerical modeling based on Flac 3D software,the study examines the total bearing capacity and efficiency coefficient of the pile group,considering factors such as the angle of lateral load,relative pile spacing,and relative stiffness of the pile-soil system.The findings highlight the significance of these factors in understanding and predicting the response of pile groups to changing lateral load directions.The results reveal that increasing the angle of the lateral load from 0°to 45°enhances both the maximum total lateral load and the efficiency coefficient of the pile group.When the relative stiffness of the pile-soil system significantly increases,soil stiffening occurs and reducing the relative spacing of the piles from 7 to 3 times the diameter of the piles diminishes the influence of the pile group.Consequently,the response of the pile group to lateral loads becomes more linear,with only a slight alteration in the maximum total lateral load and the efficiency coefficient when the lateral load is angled from 0°to 45°.Conversely,increasing the relative distance between the piles,specifically from 3 to 7 times the diameter of the piles,amplifies the influence of the pile group.Both the maximum total lateral load and the efficiency coefficient of the pile group exhibit an observed increase.These provide insights for designing pile groups and optimizing their performance under lateral loading conditions.