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The recent advances in the development of coding metasurfaces created new opportunities in realization of radar cross section (RCS) reduction. Metasurfaces, composed of optimized geometries of meta-atoms arranged as periodic lattices, are devised to obtain desired electromagnetic (EM) scattering characteristics. Despite potential benefits, their rigorous design methodologies are still lacking, especially in the context of controlling the EM wavefront through parameter tuning of meta-atoms. One of the practical obstacles hindering efficient design of metasurfaces is implicit handling of RCS performance. To achieve essential RCS reduction, the design task is normally formulated in terms of phase reflection characteristics of the meta-atoms, whereas their reflection amplitudes—although contributing to the overall performance of the structure—is largely ignored. As a result, the conventional approaches are unable to determine truly optimum solutions. This article proposes a novel formulation of the metasurface design task with explicit handling of RCS reduction at the level of meta-atoms. Our methodology accounts for both the phase and reflection amplitudes of the unit cells. The design objective is defined to directly optimize the RCS reduction bandwidth at the specified level (e.g., 10 dB) w.r.t. the metallic surface. The benefits of the presented scheme are twofold: (i) it provides a reliable insight into the metasurface properties even though the design process is carried out at the level of meta-atoms, (ii) the obtained design requires minimum amount of tuning at the level of the entire metasurface. None of these is possible for phase-response-based approach fostered in the literature. For practical purposes, the design is conducted using a surrogate-assisted procedure involving kriging metamodels, which enables global optimization at a low computational cost. To corroborate the utility of our formulation, a high-performance metasurface incorporating crusader-cross-shaped meta-atoms has been developed. The obtained results indicate that the system characteristics predicted at the design stage are well aligned with those of the EM-simulated structure (which is not the case for the traditional design approach). The metasurface features 10-dB RCS reduction in the frequency range of 16.5 GHz to 34.6 GHz, as validated both numerically and experimentally.

Nonlinear transmission lines (NLTLs) have been increasingly studied to produce high power microwaves (HPM) at higher repetition rates than conventional HPM devices without requiring the same auxiliary systems. The ability to array NLTLs to produce higher power and achieve beam steering provides an additional capability. This review summarizes the various NLTL topologies designed to achieve these design objectives. Specifically, we summarize modeling and experimental studies for three primary topologies: the lumped element NLTL, the split ring resonator, and the traditional transmission line geometry using nonlinear materials. The lumped element NLTL and the traditional transmission line constructed with nonlinear materials lend themselves to higher power applications, while the split ring resonator is better suited for applications involving antennas. We provide a detailed summary of past studies for these topologies and conclude by exploring ongoing work and future opportunities for technological development.

This paper studies a multi-objective optimization (MOO) problem in full-duplex (FD) networks with simultaneous wireless information and power transfer (SWIPT). In the considered networks, an FD base station (BS) communicates with multiple half-duplex (HD) uplink (UL) and downlink (DL) users simultaneously. The energy receivers (ERs) harvest energy from the ambient radio frequency (RF) signals and may act as potential eavesdroppers. Specifically, there exists two conflicting yet important system design objectives, i.e., secrecy energy efficiency (SEE) maximization and energy harvesting efficiency (EHE) maximization. An MOO design based on the weighted Tchebycheff approach is proposed to investigate the tradeoff between these two design objectives. The proposed design takes into account the quality-of-service (QoS) guarantees of secrecy rate and energy harvesting (EH) under the imperfect channel state information (CSI) of ERs. The formulated MOO problem is solved with a two-layer optimization algorithm, where the modified Dinkelbach method is applied to deal with the generalized fractional programming (FP) in the outer layer problem and semidefinite relaxation (SDR), successive convex approximation (SCA) as well as S-procedure methods are applied to transfer the inner layer problem into a convex iterative program. Moreover, we propose a suboptimal solution to the formulated problem and analyze the computational complexities. Finally, numerical results are provided to demonstrate the effectiveness of the proposed algorithms and reveal a tradeoff region between SEE and EHE.

The development of high-frequency, wide-bandwidth, high-power extended interaction oscillators (EIOs) has always been the focus of researchers working on millimeter-wave and terahertz electronic devices. However, these design objectives are affected by many structural and operating parameters, and traditional manual optimization and local optimization are no longer suitable for solving these problems. In this paper, based on a one-dimensional, nonlinear, self-consistent program of EIOs, a multiobjective optimization method that employs the nondominated sorting genetic algorithm II (NSGA-II) is proposed to simultaneously optimize device output power, bandwidth, and structure length. By using this approach, the optimization process of a 95-GHz EIO is presented, and the corresponding Pareto solutions are obtained after 500 generations with a population size of 50. The results show that the beam-wave interaction and the coupling mechanism lead to synchronization of the structural parameters and the electrical parameters with each other, and the coexistence of multiple objectives guides the zonal distribution of the optimal solutions. That is, the oscillators with fewer gaps have shorter structure length and higher power, whereas those with more gaps are prone to start oscillation and have wider bandwidth. Several sets of optimization results obtained using the proposed method agree well with the results obtained in the CST-PIC solver, which proves that the proposed algorithm is effective for optimizing EIOs because it considers multiple design goals and can serve as a theoretical basis for engineering development.

In order to realize automatic detection of corrosion on the piston rod of hydraulic hoist of hydropower station, it is important to find the location of corrosion and prevent oil leakage of hydraulic hoist and the blocking of control valve or other adverse consequences. A quick and convenient inspection robot for piston rod of hydraulic hoist is developed. Firstly, according to the specific working requirements of the piston rod of the hydraulic hoist of hydropower station and the basic principle of the robot, the structure scheme of the design of the testing robot is put forward. Then the robot control system is designed for the detection robot, and the basic idea of image recognition is introduced. Next the human-computer interaction interface is designed. Finally, the performance of the detection robot was tested to verify whether the reliability of the robot and the accuracy of image recognition meet the design objectives, and to ensure that the performance of the piston rod detection robot meets the design requirements..

The rapid and massive development of technology is a challenge for Higher Education to continue adapting and innovating to maintain academic quality. Therefore, this study aims to analyze the diffusion of innovation models to increase the use of information technology so that every application developed in higher education can run optimally following the design objectives. The method used in this study is an innovation diffusion model, which includes an analysis of the essence of communication channel innovation, the reception process, and social systems. Technology acceptance is assessed based on the innovation-decision process stage, which includes the degree of knowledge, persuasion, decision-making process, implementation, and confirmation of the benefits of using technology. The results show that the process of innovation diffusion can run effectively when paying attention to the profile of human resources (brain-ware), technological conditions (software and hardware), organizational policies (orga-ware), documentation (info-ware), and environmental dynamics (social systems).

Reducing the power and energy consumption of Convolutional Neural Network (CNN) Accelerators is becoming an increasingly popular design objective for both cloud and edge-based settings. Aiming towards the design of more efficient accelerator systems, the accelerator architect must understand how different design choices impact both power and energy consumption. The purpose of this work is to enable CNN accelerator designers to explore how design choices affect the memory subsystem in particular, which is a significant contributing component. By considering high-level design parameters of CNN accelerators that affect the memory subsystem, the proposed tool returns power and energy consumption estimates for a range of networks and memory types. This allows for power and energy of the off-chip memory subsystem to be considered earlier within the design process, enabling greater optimisations at the beginning phases. Towards this, the paper introduces POMMEL, an off-chip memory subsystem modelling tool for CNN accelerators, and its evaluation across a range of accelerators, networks, and memory types is performed. Furthermore, using POMMEL, the impact of various state-of-the-art compression and activity reduction schemes on the power and energy consumption of current accelerations is also investigated.

In this paper, we seek to identify an effective management policy that could reduce supply-demand gaps at taxi queues serving high-density locations where demand surges frequently happen. Unlike current industry practice, which relies on broadcasting to attract taxis to come and serve the queue, we propose more proactive and adaptive approaches to handle demand surges. Our design objective is to reduce the cumulative supply-demand gaps as much as we could by sending notifications to individual taxis. To address this problem, we first propose a highly effective passenger demand prediction system that is based on the real-time flight arrival information. By monitoring cumulative passenger arrivals, and control for factors such as the flight's departure cities, we demonstrate that a simple linear regression model can accurately predict the number of passengers joining taxi queues. We then propose an optimal control strategy based on a Markov Decision Process to model the decisions of notifying individual taxis that are at different distances away from the airport. By using a real-world dataset, we demonstrate that an accurate passenger demand prediction system is crucial to the effectiveness of taxi queue management. In our numerical studies based on the real-world data, we observe that our proposed approach of optimal control with demand predictions outperforms the same control strategy, yet with Poisson demand assumption, by 43%. Against the status quo, which has no external control, we could reduce the gap by 23%. These results demonstrate that our proposed methodology has strong real-world potential.

Future shipboard electrical systems utilizing zonal Medium Voltage dc (MVdc) distribution, face conflicting design objectives. The system must be simultaneously power dense, cost effective, and survivable. DC zonal distribution with multiple generation sources offers survivability advantages. Shipboard electrical distribution systems can utilize a floating ground design to increase survivability in single line-to-ground (SLG) fault scenarios. However, this could decrease the survivability upon the incidence of a second line-to-ground (LG) fault or during multiple line-to-ground fault (MLG) scenarios. Particularly when it comes to critical loads that are cross-fed from opposite sides of the ship and MLG faults on opposite polarity buses or between ac and dc buses occurring in different zones. This work characterizes the most problematic MLG fault scenarios and analyzes mitigation anpproaches.

Plate shape is one of the key quality indices of steel plates after quenching. It is of great significance to realize the prediction and optimization of plate shape for obtaining high quality steel plates. This paper designs a prediction and optimization system for plate shape in roller quenching process. Firstly, the roller quenching process is described in detail, the design objectives are analyzed, and the architecture of the system is designed. Then, the system is designed from four parts: the prediction model of plate shape, the comprehensive evaluation model of plate shape, the intelligent optimization model of operating parameters and the case matching. Finally, the prediction and optimization system is applied to the industrial site. The results of preliminary tests show that the system improves the quality of plate shape.

The IPv6 routing protocol for low-power and lossy networks (RPL) was standardized by the IETF to allow multiple resource-constrained devices to interconnect in an IPv6 multihop mesh network. One of its design objectives is the ability to customize the routing objectives according to different application requirements. This is achieved through the support of various routing metrics and constraints that are then used by objective functions to pick the best path. Another objective is the ability to scale to networks composed of hundreds to thousands of devices.In this paper, we focus on the specific topic of multi-instance, a feature discussed in the RPL standard but not investigated through much research, a situation we attribute to a lack of publicly available implementation. We detail the architecture of RPL when operating in a multi-instance environment, clarify parts of the standard related to forwarding packets along a specific instance and present an implementation based on ContikiRPL we developed during the last few years. We detail some of our design choices. Then, using our prototype, we present a first systematic performance evaluation of multi-instance RPL through experiments in a large scale testbed. Our results indeed show a tipping-point when the number of instances becomes excessive but more importantly confirm that a limited number of instances can efficiently cohabit on a common network without negatively impacting the packet delivery ratio and RPL convergence time.

Isolated renewable microgrids represent one promising solution to reach objectives of rural electricity access. Optimising cost and reliability of these systems is however crucial and there exists an inherent trade-off between environmental, economic and reliability objectives. Furthermore, investments are often fixed at the beginning of the project, although repowering can be made during the project life. The method presented in this paper allows for evolutive sizing of isolated microgrids and uses a genetic algorithm to return the set of optimal solutions under the three objectives of long-term cost, renewable integration, and reliability. As a case study, we consider a rural microgrid currently in the process of being deployed in Mali. The results show that there is an opportunity to improve system cost and reliability on renewable microgrids by considering evolutive sizing. The results enable us to observe the trade-off between all design objectives.

Traditional rugged enclosures utilizing forced-air cooling provide inadequate operating margins for modern, high-power modular electronics in typical military environments. VITA’s recent mechanical standard seeks to improve SWAP-C for 3U and 6U form factor plug-in modules by adopting air-flow-through (AFT) technology, namely ANSI/VITA 48.8-2017. By delivering coolant flow through the plug-in module heatframe, the conductive heat path is optimized, shifting the design objectives from maximizing convective heat transfer along a common coldwall towards obtaining acceptable flow distributions across all AFT modules with minimum supplied pressure head. Rugged chassis designs supporting AFT modules create a flow network of parallel channels which share common inlets and outlets, effectively operating as a manifold. An extensive matrix of operating conditions and compliant designs are numerically investigated with parametric design sweeps. Simulations adopt varying distributions of flow resistance that hypothetical AFT modules would produce. Z-type, U-type, and combining manifold configurations are investigated. Given the number of configurations, exclusive use of 2-dimensional steady RANS simulations is made within STAR-CCM+ commercial CFD software. Results confirm that the combining manifold avoids considerable losses associated with the delivery of flow through a header, yielding flow rates superior to U and Z-type manifolds. A positive correlation is observed between mean slot resistance and flow uniformity among slots. The adoption of ANSI/VITA 48.8-2017 is simplified by providing a thorough presentation of data, enabling critical insights into system performance for various design strategies.

Since electronic devices based on System-in-Package technologies become sophisticated, the number of components and the complexity of internal structure of individual devices increase dramatically. Therefore, how to optimally design such packages turns into one of the most crucial issues. However, this increasing complexity greatly enlarges not only the amount of design variables, but also the design objectives, making it extremely burdensome to examine every design neither by prototyping nor by numerical simulation. For the past, design of experiment, response surface analysis and other common statistical methods are widely used for such purpose, but their effectiveness drops rapidly with the intricacy increasing. To overcome this limitation, we implement multi-objective Gaussian process, Bayesian optimization and multi-objective multifactorial evolution algorithm to form a framework in this study to tackle this design problem with high-dimensional inputs and multiple outputs. Some variations of this framework were tested, and the modelling accuracy and optimization efficiency were used as the indicative merits to evaluate the performance of this framework. This interdisciplinary study shows benefits in introducing advance intelligent algorithms into packaging design process and present a viable approach to achieve both automation and optimization for complicated packaging design.

We consider a dynamic sensor fusion problem where a large number of remote sensors observe a common Gauss-Markov process and the observations are transmitted to a fusion center over a resource constrained communication network. The design objective is to allocate an appropriate data rate to each sensor in such a way that the total data traffic to the fusion center is minimized, subject to a constraint on the fusion center's state estimation error covariance. We show that the problem can be formulated as a difference-of-convex program, to which we apply the convex-concave procedure (CCP) and the alternating direction method of multiplier (ADMM). Through a numerical study on a truss bridge sensing system, we observe that our algorithm tends to allocate zero data rate to unneeded sensors, implying that the proposed method is an effective heuristic for sensor selection.

In this article, a multidisciplinary and multi-objective optimal design of ailerons' sizes and active control systems for an aircraft's wing with three control surfaces is developed. A Multi-Input-Multi-Output (MIMO) controller is designed using the LQR (Linear Quadratic Regulator) algorithm. The geometrical parameters of the control surfaces and the design details of the LQR penalty matrices are tuned by the NSGA-II (Non-dominated Sorting Genetic Algorithm). Three objectives are considered: minimizing impacts of external gust loads, maximizing stability robustness, and reducing control energy consumption. To investigate the effect of the air stream velocity on the solution of the optimization problem, three multi-objective optimization problems (MOPs) are formulated and solved at three different airspeeds. The optimization results demonstrate competing relationships among the design objectives and the necessity of handling the design problem in multidisciplinary and multi-objective settings. Three major results are obtained 1) a unique control gain can be designed for the entire flight envelope, 2) the flutter boundaries are extended to more than 92% beyond the design envelope, and 3) the MOP designed at higher air stream velocities offers better design options.

In this paper, an axial flux permanent magnet motor (AFPM) is designed based on multi-objective optimization algorithm for using in electric vehicle. The performance of axial flux permanent magnet motor depends on the values of its parameters. Optimization of motor parameters is basically a multi-objective problem. The electric motor used in transportation system must have features such as high torque, high efficiency and low volume to meet the needs of electric vehicles. Since the design objectives such as efficiency and power density is inversely relative to each other multi-objective genetic algorithm is used for optimization. First, the motor is designed using the design algorithm and multi-objective optimization and then, by using Pareto front obtained from optimization algorithm the desired optimal point is determined.

Generating new solutions in innovative business environments requires engaging more collaboration-based practices to support the interaction and interchange of ideas among multi-stakeholders. Co-design is increasingly popular on these occasions. Combine with gamification, co-design provides a distinct set of playful approaches for unfolding challenges and generating solutions. Although many have explored gamification to organize co-design participation, it is still uncovered how games contribute to the design objectives. This paper demonstrates a framework of “game principles” in a case study to understand further how gamification as a multi-principles system enhances the process of co-designing new solutions. Also, we provide insight for managers and facilitators on facilitating the co-design sections for innovation through the case study.

Users usually have different privacy demands when they contribute individual data to a dataset that is maintained and queried by others. To tackle this problem, several personalized differential privacy (PDP) mechanisms have been proposed to render statistical information of the entire dataset without revealing individual privacy. However, existing mechanisms produce query results with low accuracy, which leads to poor data utility. This is primarily because (1) some users are over protected; (2) utility is not explicitly included in the design objective. Poor data utility impedes the adoption of PDP in the real-world applications. In this paper, we present an adaptive personalized differential privacy framework, called AdaPDP. Specifically, to maximize data utility in different cases, AdaPDP adaptively selects underlying noise generation algorithms and calculates the corresponding parameters based on the type of query functions, data distributions and privacy settings. In addition, AdaPDP performs multiple rounds of utility-aware sampling to satisfy different privacy requirements for users. Our privacy analysis shows that the proposed framework renders rigorous privacy guarantee. We conduct extensive experiments on synthetic and real-world datasets to demonstrate the much less utility losses of the proposed framework over various query functions.

Fairness is a crucial design objective in virtually all network optimization problems, where limited system resources are shared by multiple agents. Recently, reinforcement learning has been successfully applied to autonomous online decision making in many network design and optimization problems. However, most of them try to maximize the long-term (discounted) reward of all agents, without taking fairness into account. In this paper, we propose a family of algorithms that bring fairness to actorcritic reinforcement learning for optimizing general fairness utility functions. In particular, we present a novel method for adjusting the rewards in standard reinforcement learning by a multiplicative weight depending on both the shape of fairness utility and some statistics of past rewards. It is shown that for proper choice of the adjusted rewards, a policy gradient update converges to at least a stationary point of general αfairness utility optimization. It inspires the design of fairness optimization algorithms in actor-critic reinforcement learning. Evaluations show that the proposed algorithm can be easily deployed in real-world network optimization problems, such as wireless scheduling and video QoE optimization, and can significantly improve the fairness utility value over previous heuristics and learning algorithms.

Achieving high energy efficiency is a primary design objective for multi-core systems. Dynamic voltage and frequency scaling (DVFS) is one of the most widely-adopted low-power techniques. In this paper, we present a reinforcement learning-based DVFS control approach to reduce energy con­sumption under user-specified performance requirements. The learning agent periodically selects the voltage and frequency level for all cores based on observations of their computation intensiveness, memory behaviors as well as synchronization among cores. Experimental results on multiple real applications show that the proposed method can achieve significant energy reduction.

In order to further increase the usage amount of recycling smoke box, this paper solve the warehousing of the cigarette products using the recycling smoke box with oddment and stock, the distinction between storage and classification management problems, based on with the Project 1 bar code online printed in the early paper, the electric control system of automatic logistics was transformed as following: 1) Increasing the warehouse bar code to provide storage recognition of identity; 2) Adding the corresponding bar code scanner into the bus control to set up vigorous hardware; 3) Reconstructing the working logic of the two bar code scanners and modifying the judging conditions to determine the storage in the PLC control program to perfect the software. The results of application showed that the system meets the design objective after improvement, the cigarette finished products using the recycling smoke box are 100% put in storage in a more efficient way, in contrast with former no warehousing, and can be divided according to brand, specification, old and new smoke box, and machine type. We have realized automatic sorting of cigarette products, and classification storage and management, what’s more, the two functions are extended to four functions flexible switching between each other implemented on the same device.

For traveling wave ultrasonic motor, the contact transmission between stator and rotor is a very important power transmission process, which determines the final output characteristics of the motor. Based on the idea that the uniform dynamic response at each position of the stator tooth surface helps to ensure the close contact between the stator friction plate and the rotor and the efficient operation, this paper proposes that the amplitude ratio of the outer ring and inner ring of the stator tooth surface is taken as the optimization design objective to optimize the stator material and optimize the design of the tooth slot inclination angle. In the finite element model, a refined geometric model including rotor assembly is established, and the influence of pre-pressure on the vibration characteristics of ultrasonic motor and the contact model between stator friction plate material and rotor are considered. The simulation results based on workbench software show that TC11 material has better uniformity of dynamic response of tooth surface among the three candidate materials, and the uniformity of dynamic response on tooth surface is the best when the inclination angle of tooth slot is about 4°.

High-level synthesis (HLS) tools have gained great attention in recent years because it emancipates engineers from the complicated and heavy hardware description language writing, by using high-level languages and HLS directives. However, previous works seem powerless, due to the time-consuming design processes, the contradictions among design objectives, and the accuracy difference between the three stages (fidelities). To find good HLS directives, in this paper, a novel correlated multi-objective non-linear optimization algorithm is proposed to explore the Pareto solutions while making full use of data from different fidelities. A non-linear Gaussian process is proposed to model relationships among the analysis reports from different fidelities for the same objective. For the first time, correlated multivariate Gaussian process models are introduced into this domain to characterize the complex relationships of multiple objectives in each design fidelity. A tree-based method is proposed to erase invalid solutions and obviously non-optimal solutions. Experimental results show that our non-linear and pioneering correlated models can approximate the Pareto-frontier of the directive design space in a shorter time with much better performance and good stability, compared with the state-of-the-art.

In this paper, the parameter optimization along with the gray correlation analysis is used for design of interior V-shaped permanent magnet synchronous motor (IVS-PMSM), which is used in solar water pump system (SWPS). The motor design based on the fundamental equations does not produce the optimal performance indicators. This necessitates the optimization of initially designed motor to improve its performance in terms of torque ripples and saliency ratio. This also improves the overall system performance. Thus, the parameter optimization based on finite element methods, is used here for achieving the optimum design of IVS-PMSM. However, the selection of final design values is not so obvious due to the contradictory needs of various design objectives and the presence of a number of design variables. Therefore, a statistical method based on the gray correlation analysis is used for selection of final design. Thereafter, a comparison is carried out between the two designs to demonstrate the superiority of later over the former through various performance indicators.

With the rapid development of science and technology, the automobile industry presents a good development prospect. Especially, the application of new technology and new equipment, and the automatic driving technology have gradually entered people's vision. The automatic driving system of bus planning and design is essentially in order to escape from the wrong operation of the driver, automatically perceive the hidden danger in driving, reasonably plan and control, and avoid the occurrence of safety accidents to the greatest extent. Based on the actual requirements of bus automatic driving integration, combined with the characteristics of bus, this paper studies the system architecture and core control technology of automatic driving technology on bus. In this paper, multi-sensor data fusion, high-precision positioning, secondary path planning and other control technology means are determined, and then the perception system, decision-making system, execution system are designed and implemented to complete the design of automatic driving bus. Finally, the function, performance, reliability and other aspects of the designed automatic driving bus are tested. The test results show that the vehicle meets the basic actual needs and the expected design objectives, and can realize L3 level automatic driving under the conditions of low-speed closed Park, expressway and urban expressway.

Electromagnetic (EM)-driven design has become a commonplace of contemporary microwave engineering, primary reasons being reliability and versatility of EM analysis. For certain classes of structures such as miniaturized components, it is a practical necessity as simpler representations (e.g., equivalent networks) are either inadequate or simply not available. On the other hand, simulation-based procedures such as parameter tuning or statistical analysis entail considerable computational expenses. This paper proposes a technique for accelerated design optimization of compact microwave structures. Our methodology involves kriging metamodels constructed using already available designs as well as an iterative correction procedure, feeding the accumulated discrepancies between the target and the actual design objective values back to the metamodel to yield improved predictions. The presented approach is comprehensively validated using a three-section impedance matching transformer and compared to a gradient-based correction scheme. As demonstrated, the designs optimized for wide ranges of the operating bandwidths are obtained at the cost of just a few EM analyzes of the transformer circuit.

The stretchers and other similar furniture is not limited to hospitals only. However, it is also available in several other facilities and healthcare facilities, such as assisted living quarters, nursing homes, outpatient clinics, and home health care services. Separate experiments were performed to determine the patients’ physical features and ergonomic consideration through the analytical hierarchy process (AHP) which gained comprehensive approach. But design specifications leads to some deficiencies responsible for poor blood circulation, back pain and other related musculoskeletal disorders among the patient. The proposed mechanism is obtained by a design process that considers design objectives specified by the hospital’s medical staff. A manufacturing kinematic mechanism with the help of an electronic sensor was performed to find a connection between the deck’s various positions and the minimum force needed to drive the height adjustment mechanism.

An optimal design approach is proposed in this paper for the resonant parameters in symmetrical CLLC-type dual active bridge (DAB) converter with considerations of the efficiency of the DAB converter and stability in a cascaded system simultaneously. The main idea of priority-based method adopted in this paper is to give priority to one of the two design objectives at one time. And swarm intelligence is used in this method to find the suitable values of resonant parameters with accuracy and efficiency. Finally, the simulations and experimental results have proved the validity of this design method.

Worm gear and worm drive mechanism is widely used in mechanical drive. In traditional design, the valuation trial method is generally used, and then the design scheme is checked to verify whether the design parameters are within the performance range for the given conditions. In a sense, the design parameter values obtained by this method are not the most reasonable and economical. Under the premise of systematic study of the possible failure forms and design criteria of worm gear and worm drive, design criteria and use of materials, we determine the optimization design objectives, design variables and constraints, and use the MATLAB optimization toolbox to complete the optimized design of worm gear and worm drive. We finally obtain the optimization results and compare them with the original design data. The optimization results show that MATLAB can significantly improve the analysis efficiency and quality of worm drive design, which will reduce the cost.

In this paper, the design and geometric optimization of spoke-type permanent magnet synchronous motor (PMSM) are presented for solar photovoltaic array fed water pump. Initially, a spoke-PMSM is designed by using basic design equations and then its geometric optimization is carried out to achieve an optimum design objective. The design objective is to enable the operation of spoke-PMSM at maximum efficiency while using minimum quantity of permanent magnets. The motor parameters like stator conductors per slot and dimensions of magnets are varied over a wide range to achieve design objective. Based on this, operating point of optimized motor is selected. Meanwhile, variations of other parameters like inductances and slot-fill factor are also shown to assess the behavior of the motor. To show the superiority of an optimized design, a comparison with initial design is carried out and various performances are reported.

In this paper, the equivalence is established between the linear active disturbance rejection control (LADRC) and the two-degree of freedom (2-DOF) proportional-integral-derivative (PID) with lead-lag compensators. This allows advantage of LADRC, particularly its bandwidth-parameterization strategy, to be incorporated into the run-of-mill PID controllers. Specifically, the competing design objectives in disturbance rejection, tracking, and noise sensitivities can now be handled with ease.

The problem of system effeciency assesing of technological innovations is considered. The methodolofical approach for economic effeciency of new industrial technological process is proposed. The difference of the proposed concept is a comprehensive assessment of the effectiveness of innovative technology, including indicators of comparative economic efficiency and indicators of investment efficiency, taking into account various risk factors. These approach can be used for estimation a system efficiency of different types of technical innovations – new technological process, new equipment, new information technology, new automated control system, uses methods of system and economic analyses and take into account the type of innovation, the stage of it life cycle, the purpose and design objectives. Keywords—technological system, technological innovation, decision making, system efficiency.

The advanced control system design is turning more and more complex and, sophisticated optimization techniques become essential in order to satisfy such high requirements. In particular, multi-objective optimal (MOO) control is nowadays a way to reach a control system that conciliates at the same time several design objectives that sometimes could be contradictories. In the past ten years, numerous advances can be observed in the field of multi-objective optimization. Many optimization algorithms with high complexity are now available in order to solve different kind of optimization problems. The use of such approaches is not simple. Thus, the main contribution of this work is study of old and new MOO algorithms from the control point of view providing practical experience and design hints. A numerical study by using the pitch control system design of a wind turbine is included.

Collaborative learning techniques allow numerous clients conjointly to improve artificial intelligence models using their private datasets. The clients carry out the training locally and periodically exchanging gradient values through devices. Unlike conventional training approaches, the training data in the collaborative techniques are not revealed publicly. Regardless of privacy merits, clients are often less motivated to improve the model due to inadequate incentives procedural. In short, the resources owned are not maximally utilized. To tackle the issue, we design a collaborative learning model with a secure, fair, and immutable incentive mechanism by leveraging blockchain technology. Incentives are distributed proportionately to clients according to their respective contributions. We implement our incentive schemes on Ethereum. We also evaluate the performance of collaborative learning in a different setting. The results indicate that the design objectives are met.

The mathematical model of electromagnetic repulsion force operating mechanism for 1.14kV/630A/20kA vacuum circuit breaker is proposed, and its rotational symmetrical magnetic field model is established using finite element analysis method. Taking the characteristics of electromagnetic repulsion, starting time and displacement as the design objective, through the comparative analysis of the output characteristics of metal disc and double coil repulsion mechanism, the design scheme of the operating mechanism for the fast vacuum circuit breaker with short opening stroke and large interrupting capacity is obtained.

This paper presents an energy harvesting circuit for indoor light. The main design objective of the proposed circuit is high adaptability to various types of photovoltaic (PV) cells and coverage of a large range of PV voltages. A dual-input dual-output buck-boost running in discontinuous conduction mode (DCM) with pulse skipping modulation is adopted for the purpose. It proposes the fractional open-circuit voltage (FOCV) scheme with an adaptive fraction for maximum power point tracking (MPPT). The optimal fraction is obtained through the perturb & observe (P&O) scheme, which leads the proposed MPPT method adaptable to different types of PV cells. The circuits are designed in 0.18 μm BCDMOS process, and post-layout simulations verify correct operation of the proposed circuit.

This paper investigates how design processes are influenced by visual analogy when designers refer to visual elements with different distances. It is found that when facing long-distance visual elements designers concerns more on external shapes. During design thinking, those designers prefer to pay more attention on connecting visual elements with design objectives and they usually focus on designing micro details instead of outputting new design concepts. Therefore, during practical design processes, the designers are able to establish a connection of the design targets and design elements with proper distances.

Main design objectives of future wireless networks are information security and efficient spectrum-and-energy utilization to serve a tremendous number of users and applications. This paper proposes overlay networks with energy scavenging and artificial noise to achieve these objectives concurrently. In these networks, unlicensed user assists and secures licensed transmission in reward for its access to licensed spectrum by relaying licensed information, producing artificial noise, and transmitting its private information. Key secrecy performance metrics of these networks such as secrecy outage probability, positive secrecy capacity probability, intercept probability, and secrecy throughput are represented in exact formulas, which are helpful in quickly assessing secrecy performances in important specifications as well as optimizing system design without computer simulations. Numerous results are provided to corroborate these formulas and have insightful understandings into secrecy capability of overlay networks with energy scavenging and artificial noise.

An observer-based control synthesis for Decentralized Networked Control System (DNCS) is proposed, where the control loop is closed by a communication network. In the proposed approach, a designer first constructs a centralized static controller that accomplishes the design objective. Then, this centralized controller is implemented as a dynamic decentralized controller. The proposed decentralized controller is designed using Linear Matrix Inequalities (LMIs). The presence of the communication network modeled as a pure time-delay is analyzed. A sufficient condition on the duration of the network time-delay guaranteeing the stability of the DNCS is given. The obtained results are applied to the design of a decentralized system consisting of two remotely controlled mobile robots and simulation results are presented.

The character of a campus is a spirit of place that cannot be touched. Design practice is a project that is implemented. How to make the campus landscape with “ideal” meaning and the design practice with “realistic” meaning influence the campus users through the means of landscape design is the research goal of this paper. The author will discuss the project location and background., site characteristics., design objectives and design strategies. We design many places for user to stay in the site., such as the large steps on the surface of the structure and the viewing platform., the display space inside the structure and the large steps in the sunken courtyard., the small private space outside the structure and the desks and chairs under the shade of trees., etc., which meet the functional requirements of campus users for staying and resting in the site.

The performance of MIMO radar is directly affected by its transmitting waveforms. The waveform design is one of the critical issues in the design of MIMO radar system. In this paper, a new MIMO radar waveform design method based on time domain and frequency domain joint optimization is proposed. Firstly, a continuous phase coded signal waveform set is chosen to be the optimization objective variable. The design objectives is that all waveforms in the set are orthogonal in time domain, and the power spectral density (PSD) of every waveform approximates to the desired distribution in the frequency domain. According to the requirements, the problems in time domain and frequency domain are analyzed, respectively. Meanwhile, two objective functions based on minimizing the weighted correlation sidelobe level (MWISL) and minimizing the stopband power spectral density (MSPSD) are established. Then, an optimal scale factor is introduced to integrate the time domain and frequency domain into a combined model and a close form solution of code element is deduced through proper simplification and equalization of the time-frequency (T-F) joint optimization model. A recursive algorithm is obtained by summarizing the derivation process. At last, numerical examples prove the effectiveness of the proposed method in matching desired spectrum distribution and decreasing correlation sidelobe.

The LLC-type dual active bridge (DAB) converter as an isolated DC-DC converter attracts increasing attention nowadays because of the popularity of the renewable energy generation. Constant voltage conversion gain (VCG) is an important indicator to assess its performance of power transfer, which may be undermined by the varying values of resonant parameters due to environmental conditions. Besides that, in practical applications, the DAB converter is often cascaded with other subsystems, which may lead to instability in the cascaded system because of impedance interactions. Therefore, the voltage conversion gain (VCG) as well as stability of the cascaded system are two design objectives for resonant parameter design for LLC-type DAB converter in this paper. A design approach is advanced to maintain both constant VCG and system stability simultaneously. In the end a design example is provided and experimentally verified.

Inductive power transfer (IPT) is an effective energy supply option for maglev trains that currently depend on pantographs to obtain enough electricity. This paper demonstrates a multi-objective optimizing method of a single-transmitter coupled multi-receiver contactless charger for maglev trains. The 3D FE model is built to obtain parameters of the magnetic coupler, and the power loss model is given to calculate the loss and efficiency. Under the given restrictions and boundaries, a multi-objective optimization process of IPT coils for maglev trains is proposed based on Pareto optimal theory. High efficiency, high power density, and low cost are selected to be the design objectives. The arrangement of ferrite is included in the process to optimize coil design in an all-sided way. A reasonable optimal solution is selected from the Pareto fronts and its detailed information is given. A scale down single-transmitter coupled dual-receiver IPT system was constructed to verify the design considerations. The efficiency of the prototype reached 80% at the condition of 1kW output power with around 100V input voltage and 50V output voltage at the switching frequency of 85kHz.

This paper presents the design, simulation and thermal analysis of an Interior Permanent Magnet Synchronous Motor (IPMSM) which is suitable for traction application for an electric fork-lift truck. An existing squirrel cage induction motor used for electric fork-lift application has been initially studied for obtaining the required performance metrics. Similar performance indices have been achieved out of a proposed IPMSM design that has been presented. The primary design objective has been to obtain (i) the optimum dimensions and shape of the buried permanent magnet with its placement details in the rotor, and (ii) the winding arrangement in the stator which would be capable of delivering the same torque and speed characteristics at better efficiency maintaining the same stator outer diameter, number of slots, bore diameter and the shaft diameter as that of the existing squirrel cage induction motor used for the same application. An analytical approach based design of an IPMSM, employing a bottom-up approach, is presented, based on the Constant Power Speed Range (CPSR) and other performance requirements. A few possible designs verified by Finite Element Analysis (FEA) are compared, which meet all the performance specifications, and, eventually the finally accepted design is presented.

Recently, the data processing capability of the electronic chip is increased significantly. In general data processing means the arithmetic operation on that data. As a result, we have seen that the ALU is present in any data processor. So, the full adder becomes an essential part of the logical and arithmetic unit of the processor. To improve the computational performance of the chip, the improvement of a full adder is necessary. An appropriate logic style helps the designer to design an efficient full adder. In this paper, several logic styles are briefly discussed. We choose to pass transistor logic style to design our new full adder. This logic style is used for reducing power consumption and increasing operational speed. The proposed adder consists of 10 transistors. LTSPICE simulator is used for simulating the schematic. 16nm low power high-k strained silicon transistor model is used for achieving design objectives. A practical transistor model is employed to encounter all practical aspects. The overall performance of the proposed adder circuit is analyzed and compared with conventional circuits.

This paper describes optimum antenna array structure for beamforming in smart antenna technology. Different examples of array structures are analysed by the use of newly developed optimization technique called Whale Optimization Algorithm (WOA). The design objective here has been considered to get the most favourable radiation patterns with sidelobe level (SLL) reduction by optimizing amplitude excitations, inter element spacings and phases of each elements of an array. The numerical and simulation results are compared with that obtained by most popular optimization technique, Particle Swarm Optimization (PSO), Ant Lion Optimization (ALO) and Cat Swarm Optimization (CSO) by building codes using MATLAB. The results show that WOA can exhibit relatively better performance than other algorithms for the antenna array synthesis examples and beamforming applications.

In order to meet tight performance and/or energy constraints of embedded systems, the implementation of applications in hardware is often a must. However, mapping of algorithms to platforms, as for example Field-Programmable Gate Arrays (FPGAs), still requires comprehensive hardware knowledge and sometimes long design cycles. Modern High-Level Synthesis (HLS) offers a means to ease the generation of hardware implementations from a software specification of an application. Although these tools have improved greatly in recent years, they often do not provide full coverage of important programming constructs and are therefore of limited use when used with existing or automatically generated code. Soft-core processors implemented with FPGA-logic can circumvent this limitation. However, these come with drawbacks in terms of performance and resource requirements as a general-purpose architecture is used to implement the application in software rather than as a highly specialized circuit. As a remedy, our work presents a novel compiler-based synthesis methodology that generates networks of Application-Specific Instruction Set Processors (ASIPs) from unmodified C/C++ algorithms. We thereby bridge the gap between traditional soft-core processors and HLS. To show the practicability of our approach, we present a case study of a JPEG decoder application while investigating design objectives like resource costs and performance. Apart from the generality of the compiler-based approach, our approach also shows better results in terms of required hardware resources and execution times compared to Instruction Set Architecture (ISA)-fixed commercial Xilinx MicroBlaze soft-cores.

In this paper, we investigate the design of multirobot warehouse automation systems with complex high-level tasks. We consider a warehouse environment where a group of AGVs move in a grid-partitioned workspace to deliver goods upon requests automatically. The design objective is to synthesize a high-level controller/planner that coordinates the multi-robot system to fulfill the entire task. We use linear temporal logic (LTL) formulas to describe the desired task specifications. Then the controller is generated automatically based on the LTL formula using the theory of reactive synthesis. Compared with most of the existing planning algorithms for warehouse systems, the proposed method is formal in the sense that: (i) the controller is correct-by-construction with provably satisfication guarantees; (ii) it can handle complex temporal tasks in a user-friendly manner; (iii) our framework can also handle the situation of multiple robots with multiple requests. Finally, we implement the proposed synthesis procedure and illustrate our results for multi-robot systems by simulations.

This research focuses on the coordinated control of Electronic Stability Control (ESC) and Regenerative Braking System (RBS) for Parallel Hydraulic Hybrid Commercial Vehicles (PHHCV). The proposed control architecture consists of a top-level module with braking torque coordination, a middle-level module with privilege allocation between ESC and RBS and a low-level module with actuator coordination between air brake and hydraulic brake actuators.The proposed coordinated control aims at eliminating potential conflict on actuators of air brake and hydraulic brake systems and achieving maximum fuel economy while maintaining vehicle stability. PHHCV model and its actuator models have been established including both ESC and RBS system models. A coordinated control of ESC and RBS systems under proposed control architecture has been developed. Simulation has been conducted and the results demonstrates that the proposed method is valid and effective in achieving the design objectives.