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This paper presents motion planning strategies that assure stable hovering for a transformable unmanned aerial vehicle (UAV) throughout its transformation. The considered multirotor UAV consists of multiple links equipped with rotors. The UAV can transform its structure by changing the lateral joint angle connecting these links. We first introduce the concept of hoverability, which assures static hovering with a linear state feedback controller. Because the hoverability can be evaluated quantitatively by utilizing a convex hull yielded by the positions of rotors, we propose motion planning methods that leverage the hoverability to achieve transformation while guaranteeing stable hovering with desired margin. As the hoverability can be investigated geometrically without analyzing the dynamics of UAVs, the proposed method can be readily employed for a wide class of transformable UAVs, including the one in which clockwise and counterclockwise rotors are not arranged alternately. The proposed motion planning is designed to secure the specified threshold for hoverability and avoid interferences between links or rotors. We then present two types of costs for motion planning: one minimizes the transformation duration, and the other maximizes the hoverability during the transformation. The proposed motion planning is optimized via Dijkstra's algorithm and demonstrated in simulation. [ABSTRACT FROM AUTHOR]

With the development and characterization of biomarkers that may reflect neural network state as well as a patient’s clinical deficits, there is growing interest in more complex stimulation designs. While current implantable neuromodulation systems offer pathways to expand the design and application of adaptive stimulation paradigms, technological drawbacks of these systems limit adaptive neuromodulation exploration. In this paper, we discuss the implementation of a phase-triggered stimulation paradigm using a research platform composed of an investigational system known as the CorTec Brain Interchange (CorTec GmbH, Freiburg, Germany), and an open-source software tool known as OMNI-BIC. We then evaluate the stimulation paradigm’s performance in both benchtop and in vivo human demonstrations. Our findings indicate that the Brain Interchange and OMNI-BIC platform is capable of reliable administration of phase-triggered stimulation and has the potential to help expand investigation within the adaptive neuromodulation design space.

This paper proposes an analytical framework for co-designing wireless networked control systems (WNCSs) demonstrated in an industrial scenario. The framework allows us to quantitatively characterize the impact of wireless channel model accuracy when designing a controller to stabilize a WNCS. We consider a scenario consisting of two co-located wireless networks: the first connects the plant automation network backbone to field devices via WirelessHART, ISA-100.11a, or IEEE 802.15.4e, and the second uses IEEE 802.11 equipment to supply real-time multimedia data to the supervisory devices. First, we derive a parametric 802.11 interference characterization for an arbitrary number of active interfering devices and perform extensive parametric analysis. We then derive the message and packet error probability expressions necessary to develop an appropriate finite-state Markov channel model. Finally, we ran sizeable Monte Carlo simulations to evaluate the impact of our channel model on the control performance of a wireless closed-loop system and compared it with the performance obtained using a Bernoulli channel model.

Contact tracing is the cornerstone of epidemic control of infectious diseases, especially in the era of COVID-19. This labor-intensive task calls for the use of digital technology to help identify individuals who have potentially been exposed to the infection to deliver necessary interventions and treatment. Mobile applications based on different technologies and system architectures have been developed and widely used in concert with public health policies and regulations. Three main types of digital contact-tracing technologies, namely Bluetooth low energy (BLE), location tracking, and check-in, were adopted in contact-tracing apps and implemented with a centralized or decentralized system architecture to protect privacy and facilitate spatiotemporal co-occurrence matching. Passive data collection methods, including BLE and location tracking, could be contrasted with check-in-based apps, which require users' effort to record their whereabouts. Persuasive computing with a centralized system for collecting contact-tracing data from users might require additional legislation for authorization and privacy protection. Technology options should therefore be taken into account when designing enforceable public health policies on the use of contact-tracing apps. At the same time, public health policies also inform the information system's design. This paper aims to delineate and contrast current technologies and system architectures used for developing contact-tracing apps and examine the intertwined relationship between the design and implementation of public health policies and the design of digital contact-tracing systems. [ABSTRACT FROM AUTHOR]

In the grid-connected systems, LCL filters are widely used for eliminating the generated switching current ripples due to better attenuation in comparison with L or LC filter. However it is known that stability of digital controlled LCL filter can present a challenge due to induced delay. This paper presents conditions of system stability in dependence of filter characteristics such as resonant frequency, inductors and capacitor parameter variations. Stability analysis and system performance are observed and compared. Derived results are tested and confirmed on Hardware-in-the-loop HIL402 device. Obtained results are discussed and suggestions are provided in terms of the practical implementation of the control system.

Military technologies are typically the product of long-term development efforts. These technologies are often adapted late in the development process for use by other users, including other members of the defense enterprise, foreign militaries, or the commercial sector. The need to adapt a technology can arise from cost over-runs or changing operational requirements. This article describes a value-based methodology for developing a transition plan early in the development process, when the system is still in the conceptual phase. Performing this analysis early in the design phase allows for design choices that will support adapting the system for other users. Moreover, it provides a risk mitigation strategy against cost over-run and changes in operational requirements. The process begins by capturing the functional architecture of the technology and analyzing them against a set of tasks associated with different military positions. From there, the adapted technology is evaluated for its projected adequacy based on the value added and the effort required for adaptation. The end-state of this analysis is a value-based model that identifies a portfolio of possible alternative markets and/or uses, which can be comparatively analyzed. A case study is presented for adapting a military augmented reality system for a different market. [ABSTRACT FROM AUTHOR]

Digitization initiatives have become increasingly prominent for libraries and information centers. These initiatives have, in turn, also led to an increase in the use of digital management systems to store digitization outputs. Since these are large volumes of documents, potential alternatives to providing access to these materials aside from manual data entry processes such as indexing and cataloging are explored. In this area, the potential of Optical Character Recognition (OCR) mechanisms is gaining prominence as the tool that can process a large number of documents and provide automated text recognition at high speed. Leveraging the potential of OCR, this paper describes the design of a digital asset management system and the application of Tesseract, an opensource OCR engine, to create a functional and adaptive system to manage digital assets and retrieve information from these contents. [ABSTRACT FROM AUTHOR]

Contact tracing is the cornerstone of epidemic control of infectious diseases, especially in the era of COVID-19. This labor-intensive task calls for the use of digital technology to help identify individuals who have potentially been exposed to the infection to deliver necessary interventions and treatment. Mobile applications based on different technologies and system architectures have been developed and widely used in concert with public health policies and regulations. Three main types of digital contact-tracing technologies, namely Bluetooth low energy (BLE), location tracking, and check-in, were adopted in contact-tracing apps and implemented with a centralized or decentralized system architecture to protect privacy and facilitate spatiotemporal co-occurrence matching. Passive data collection methods, including BLE and location tracking, could be contrasted with check-in-based apps, which require users’ effort to record their whereabouts. Persuasive computing with a centralized system for collecting contact-tracing data from users might require additional legislation for authorization and privacy protection. Technology options should therefore be taken into account when designing enforceable public health policies on the use of contact-tracing apps. At the same time, public health policies also inform the information system’s design. This paper aims to delineate and contrast current technologies and system architectures used for developing contact-tracing apps and examine the intertwined relationship between the design and implementation of public health policies and the design of digital contact-tracing systems.

Alvis is a formal modelling language developed primarily for modelling concurrent systems including real-time systems. The prepared model is compiled, and the resulting runnable model allows, e.g., to generate the state space and to verify the model using model checking techniques. The default version assumes that each system component (agent) executes its computations in parallel and that the hardware platform is not a shared resource. This paper describes an alternative approach in which agents remain concurrent, but compete for access to a single shared processor. This situation significantly affects the correctness of the system, in particular from the perspective of the timing properties of real-time systems. The key element of the presented solution is the fact that changing the runtime environment comes down to changing compiler options and does not require changes to the original model. This paper presents a method of designing Alvis language models for a single-processor hardware platform. The presented concepts are illustrated with examples.

We provide a comprehensive solution to the estimation problem of the state for a linear time-invariant system in a distributed fashion over networks that allow only intermittent information transmission. By attaching to each node an observer that employs information received from its neighbors triggered by asynchronous communication events, we propose a distributed state observer that guarantees global exponential stability of the zero estimation error set. The design of parameters is formulated as linear matrix inequalities. A thorough robustness analysis of the proposed observer to unmodeled dynamics, unknown communication times, as well as measurement and communication noise characterized in terms of input-to-state stability is presented. These properties of the proposed observer are shown analytically and validated numerically.

Connected vehicles, whether equipped with advanced driver-assistance systems or fully autonomous, require human driver supervision and are currently constrained to visual information in their line-of-sight. A cooperative perception system among vehicles increases their situational awareness by extending their perception range. Existing solutions focus on improving perspective transformation and fast information collection. However, such solutions fail to filter out large amounts of less relevant data and thus impose significant network and computation load. Moreover, presenting all this less relevant data can overwhelm the driver and thus actually hinder them. To address such issues, we present Augmented Informative Cooperative Perception (AICP), the first fast-filtering system which optimizes the informativeness of shared data at vehicles to improve the fused presentation. To this end, an informativeness maximization problem is presented for vehicles to select a subset of data to display to their drivers. Specifically, we propose (i) a dedicated system design with custom data structure and lightweight routing protocol for convenient data encapsulation, fast interpretation and transmission, and (ii) a comprehensive problem formulation and efficient fitness-based sorting algorithm to select the most valuable data to display at the application layer. We implement a proof-of-concept prototype of AICP with a bandwidth-hungry, latency-constrained real-life augmented reality application. The prototype adds only 12.6 milliseconds of latency to a current informativeness-unaware system. Next, we test the networking performance of AICP at scale and show that AICP effectively filters out less relevant packets and decreases the channel busy time. [ABSTRACT FROM AUTHOR]

Modern engineering systems are increasing in complexity and demanding higher levels of performance, safety, durability, and quality. This has led to an increase in the number of functional requirements and system elements. Subsequently, meeting the target performances and schedules requires more design effort and cost. To ensure on-time development and delivery of the final system, engineers need to allocate the right amount of available resources to design and develop various subsystems. However, estimating the efforts required to design and develop a system and its constituents during the early design stage is significantly challenging. Often, initial estimations are made by subject matter experts who base their judgments on the perceived difficulty of designing the subsystems. In this article, to quantify the perceived design difficulty, a new metric based on the degree of relationship between the system requirements and elements is proposed. This metric utilizes the domain mapping matrix and matrix energy to quantify the complexity of system design. Using the proposed metric, the relationship between system design complexity and design difficulty perceived by engineering experts is established and demonstrated through a case study involving a column-type electric power steering system. [ABSTRACT FROM AUTHOR]

This article presents a performance comparison of the solid, low impedance, high impedance, frequency-selective, and isolated grounding systems. A grounding system (for any power system component) is designed as an impedance ($\bar{Z}_{G}$) that connects the neutral point to the ground. The impedance $\bar{Z}_{G}$ is constructed using a combination of $R$ , $L$ , and $C$ elements. The values and combination type (series or parallel) of $R$ , $L$ , and $C$ determine the possible influence of $\bar{Z}_{G}$ on ground currents and potentials. Each grounding system is related to a system voltages level, a specific combination of $R$ , $L$ , and $C$ , and a range of $R$ , $L$ , and $C$ values. The solid, low impedance, high impedance, frequency-selective, and isolated grounding systems are designed for a $3\phi$ transformer and a $3\phi$ synchronous generator in order to compare their influences on ground currents and potentials during ground faults. The transformer and generator are tested for line-to-ground and double line-to-ground faults with all designed grounding systems. Test results show that some grounding systems can reduce ground currents only, while others can reduce ground potentials only. Such capabilities can be used to fulfill certain system and operation requirements (e.g., service continuity, ground capacity, etc.). [ABSTRACT FROM AUTHOR]

The selection of a grounding configuration and design of a grounding impedance is of vital importance for the stability and functionality of power systems, including industrial and commercial power systems. These key aspects of grounding systems have been the subject of various standards, industrial codes, and recommended practices. In this article, a review, modeling, and analysis of different grounding system designs are provided. The different grounding system design discussed in this article is compared in terms of the ground potential, ground currents, and overvoltage during ground faults. The various grounding system designs are implemented for power systems components in order to assess their capabilities and performance. Several tests are conducted for ground faults, when different grounding system designs are used. Test results show that some grounding system design can limit ground currents, with minor effects on ground potentials. Other grounding system design can limit ground potentials, while fail to limit ground currents. [ABSTRACT FROM AUTHOR]

In recent years, there has been a steady increase in awareness of the need to design technology more ethically. The crashes of two Boeing 737 MAX airplanes as well as the Volkswagen scandal have contributed to the questioning of ethical practices in classic engineering departments. Several studies revealed the potential bias and manipulability of software systems, including critical judicial systems and social networks. The lack of artificial intelligence (AI) transparency became subject to a stream of criticism. To the positive surprise of long-term scholars in the social issues of technology, the IT industry woke up to the need for a more forward-looking, responsible, and ethical planning of IT systems. [ABSTRACT FROM AUTHOR]

Nonlinear system design is often a multiobjective optimization problem involving the search for a design that satisfies a number of predefined constraints. The design space is typically very large since it includes all possible system architectures with different combinations of components composing each architecture. In this article, we address nonlinear system design space exploration through a two-step approach encapsulated in a framework called fast design space exploration of nonlinear systems (ASSENT). In the first step, we use a genetic algorithm to search for system architectures that allow discrete choices for component values or else only component values for a fixed architecture. This step yields a coarse design since the system may or may not meet the target specifications. In contrast to prior works on design space exploration that rely on forward design, we use an inverse design in step 2 to search over a continuous space and fine-tune the component values with the goal of improving the value of the objective function. We use a neural network (NN) to model the system response. The NN is converted into a mixed-integer linear program for active learning to sample component values efficiently. We illustrate the efficacy of ASSENT on problems ranging from nonlinear system design to the design of electrical circuits. Experimental results show that ASSENT achieves the same or better value of the objective function compared to various other optimization techniques for nonlinear system design by up to 53%. We improve sample efficiency by 6– $12\times $ compared to reinforcement learning-based synthesis of electrical circuits. [ABSTRACT FROM AUTHOR]

The Cramér-Rao bound (CRB) has been extensively used as a benchmark for estimation performance in both Bayesian and non-Bayesian frameworks. In many practical periodic parameter estimation problems, such as phase, frequency, and direction-of-arrival estimation, the observation model is periodic with respect to the unknown parameters and thus, the appropriate criterion is periodic in the parameter space. Consequently, Bayesian lower bounds on the mean-squared-error (MSE) are not valid bounds for periodic estimation problems. In addition, many Bayesian MSE lower bounds cannot be derived in the periodic case due to their restrictive regularity conditions. For example, the regularity conditions of the Bayesian CRB (BCRB) are not satisfied for parameters with uniform prior distribution. In this letter, we derive a Bayesian Cramér-Rao-type lower bound on the mean-squared-periodic-error (MSPE). The proposed periodic BCRB (PBCRB) is a lower bound on the MSPE of any estimator and has less restrictive regularity conditions than the BCRB. The PBCRB is compared with the MSPE of the minimum MSPE estimator for phase estimation in Gaussian noise and it is shown that the PBCRB is a valid and tight lower bound for this problem. [ABSTRACT FROM AUTHOR]

Blockchains (BC) and Distributed Ledgers (DL) offer favorable properties, especially immutability and decentralization, which are suitable for voting systems’ Bulletin Boards (BB). In recent years, an influx of BC-based voting systems have been observed. Distributing trust among multiple trustees is a crucial reason to adopt BCs and DLs in voting systems. The practical deployment must be decentralized, too, and not just done through virtualizing interconnected systems. As discussed widely, adopting a BC or DL can incur threats to a system that assumed a trusted and centralized Public Bulletin Board (PBB). Therefore, the exploitation of BCs or DLs requires careful consideration of cryptographic mechanisms and the overall system design, as well as the adversary model. Besides these operational necessities, the long-term privacy of ballots is essential. Thus, the key question investigated in this article is: Can BC, and DL-based voting systems be considered harmful? Hence, first (i) requirements of BC-based voting systems are provided, followed by (ii) terminology definitions, and (iii) complemented by the design and implementation of a fully decentralized voting system: Æternum, which achieves Unconditional Privacy (UP) and neither relies on computational hardness assumptions nor on a trusted Trusted Third Party (TTP). Achieving UP is crucial because future adversaries may be able to break hardness assumptions. Æternum does not present a Single-Point-of-Failure (SPoF) either, since (i) the PBB in use is based on a permissioned DL, and (ii) the final tally and proofs can be verified by anyone, without requiring trust in any authority. [ABSTRACT FROM AUTHOR]

Hysteresis current control (HCC) is one of the most simple and rapid modulation techniques for multilevel grid-connected inverters (MGCIs). It controls the output current by limiting its ripple within fixed hysteresis limits. This results in a varying switching frequency, which is not known implicitly. The knowledge of switching frequency is essential for filter design, device selection, and loss calculations of the MGCI. The existing frequency estimations for HCC assume linear ripple current considering high-frequency operation. This assumption is invalid for the range of low frequencies. This leads to inaccurate estimation of switching frequency, which can have a considerable effect on system design. In this article, a more precise and generalized expression to estimate the switching frequency of the MGCI is obtained. The improvement in accuracy is demonstrated with an example of second-order filter design. The effect of change in hysteresis limits and input voltage on the switching frequency is analyzed to determine the operating point for accurate system design. Simulation and experimental results are found to be in good agreement with the theoretical claims. [ABSTRACT FROM AUTHOR]

In this tutorial, we discuss trade-offs in sensor system design. With examples from engineered systems in our laboratories, we address design considerations at the different system levels, from the choice of a particular sensor to the signal conditioning circuits, the choice of data converter, and data communication physical interfaces. Fundamental concepts from communication and information theory, as well as practical considerations applied to specific case studies, are presented for sensor readout systems. In particular, we address both fundamental trade-offs such as choice of signal representation for signal conditioning and conversion, as well as practical and technological trade-offs such as place of quantization (signal data conversion) application demands and integration technologies. The tutorial deals with what is commonly referred to as the Analog Front End (AFE) up to the point where the physical signal is represented in digital symbols. Although the discussion focuses on all the processing steps of the AFE, a more system-level approach is further explored, including stand-alone system approaches and system communication. Major system trade-offs during system design are discussed, providing important methodology insights towards the design of sensory systems operating within demanding constraints. [ABSTRACT FROM AUTHOR]

The critical problem in managing a bike sharing system (BSS) is to solve the imbalance in the number of available bikes by stations and times, which negatively affects the users’ riding experience. To address this issue, many BSS operators rearrange bikes using a fleet of trucks. Moreover, the effectiveness and efficiency of rebalancing operations heavily rely on accurate traffic prediction in BSS. Hence, many researchers have developed methods to enhance the prediction performance. One approach to increase the accuracy is to hierarchically predict demand from higher level (cluster or system) to station level. In the hierarchical prediction frameworks, the cluster-level to predict the demand of the total usage of groups of stations is introduced and it is crucial to partition stations into clusters that can increase the stability of actual usage and prediction. Therefore, the present work proposes a new spatial contiguity-constrained hierarchical clustering algorithm for BSS. The proposed algorithm is based on hierarchical clustering, which is deterministic, and uses the hourly proportions of check-outs and check-ins to define the temporal usage pattern of each station that does not require cluster assignment. Thus, different from existing methods, our proposed algorithm is deterministic and fast. In addition, the proposed algorithm is proven to be superior to other clustering methods in terms of traffic prediction at both the cluster and station levels. [ABSTRACT FROM AUTHOR]

Dynamic optimization, for which the objective functions change over time, has attracted intensive investigations due to the inherent uncertainty associated with many real-world problems. For its robustness with respect to noise, evolutionary algorithms (EAs) have been expected to have great potential for dynamic optimization. Many dynamic optimization methods, such as diversity-driven methods, memory methods, and prediction methods have been proposed based on EAs to deal with environmental changes. However, they face difficulties in adapting to fast changes in dynamic optimization as EAs normally need quite a few fitness evaluations to find a near-optimum solution. To address this issue, this article proposes a new framework of applying EAs in the context of dynamic optimization to deal with fast changing environments. We suggest that instead of online evolving (searching) solutions for the ever-changing objective function, EAs are more suitable for acquiring an archive of solutions in an offline way, which could be adopted to construct a system to provide high-quality solutions efficiently in a dynamic environment. To be specific, we formulate the offline search as a static set-oriented optimization problem. Then, a set of solutions is obtained by an EA for this set-oriented optimization problem. After this, the obtained solution set is adopted to do fast adaptation to the corresponding dynamic optimization problem. The general framework is instantiated for continuous dynamic-constrained optimization problems, and the empirical results show the potential of the proposed framework. The superiority of the framework is also verified on a dynamic vehicle routing problem with changing demands. [ABSTRACT FROM AUTHOR]

Testing has always been a crucial part of application development. It involves different techniques for verifying and validating the features of the target systems. For a complicated and/or complex system, tests are preferred to be carried out in different stages of the development process and as early as possible to avoid extra costs due to the errors caught at later stages. With the increasing system complexity, the cost of testing is also increasing in terms of resources and time, which introduce further impact against development constraints such as time-to-market. On the other hand, more and more associated electronic components lead to an ever-increasing system complexity in high reliable applications such as automotive ones different from heterogeneous systems such as advanced driver assistance systems, sensor fusion systems, etc. In this article, we present a testing framework utilizing the continuous integration (CI) solution from software engineering, a commercial virtual platform, and a hardware field programmable gate array based verification platform focusing on the engine control unit to demonstrate the feasibility of the proposed method. The efficiency and viability of the CI method have been demonstrated on a real heterogeneous automotive system. [ABSTRACT FROM AUTHOR]

Autonomous driving systems (ADSs) need to be able to respond quickly to changes in the dynamic traffic scenario. However, regardless of the changes occurring in traffic scenes, the current local path planning frameworks of ADSs are based on the fixed frequency re-planning path (i.e., running their planning algorithms repeatedly). This planning method makes it difficult to provide a reasonable traveling path, agility, and comfort for driverless vehicles in changing traffic scenarios. Therefore, this article performs an in-depth analysis of the problems of traditional planning frameworks which use a fixed frequency to replan the path and proposes a novel path planning framework that is universal based on multiple-models. The proposed framework divides the planning process into several layers, each of which has different functions. With this framework, the ADS can adaptively adjust the planning process according to the changes in traffic scenes and then provide different path planning algorithms to ensure its safety and flexibility in the process of driving. Moreover, the problems caused by the traditional planning framework can be solved. This framework has been applied to the autonomous vehicle “Pioneer”, which won first place in the 2019 China Intelligent Vehicle Future Challenge (IVFC). The effectiveness and rationality of the integrated framework of local path planning proposed in this article were verified by a large number of tests in real-world traffic scenarios. [ABSTRACT FROM AUTHOR]

Two-dimensional (2-D) quasi-optical systems have been widely applied. However, the analysis and design of 3-D systems still need to be further developed. In this letter, an approach to rapidly analyze the performance of 3-D multireflector systems based on Gaussian beam mode analysis is proposed. The influence of reflector parameters, such as input distance, incidence angle, and so on, on the co- and cross polarization is discussed. Furthermore, a novel design method of high-performance 3-D multireflector systems is proposed. High computational efficiency is one of the advantages of this method due to the application of particle swarm optimization algorithm. 3-D systems with low cross polarization or other electromagnetic properties can be designed rapidly by this novel method. The proposed methods greatly improve the calculation efficiency, while providing calculation accuracy similar to that of physical optics (PO) in GRASP10. [ABSTRACT FROM AUTHOR]

Methods for improving the energy efficiency in pneumatics typically aim at optimizing single cylinder drives—either by an enhanced design or by advanced control strategies. However, both approaches exhibit two major limitations in practice: the measures rely on a profound and detailed system knowledge—being hardly scalable to production plants—and the methods cannot exploit the potential arising from the operation of several drives in a compound. In this article, we give the conception, derivation, and implementation of three energy saving measures in pneumatically driven plants avoiding those restrictions. The considered measures include two structural means: a cascaded concept for exploiting the expansion potential of compressed air, and an adaptive control pattern. Conclusively, the methods are validated at a demonstrator yielding compressed air savings of up to 65% by measurements. [ABSTRACT FROM AUTHOR]

This article investigates observability/controllability of a networked dynamic system (NDS) in which system matrices of its subsystems are expressed through linear fractional transformations (LFTs). Some relations have been obtained between this NDS and descriptor systems about their observability/controllability. A necessary and sufficient condition is established with the associated matrices depending affinely on subsystem parameters/connections. An attractive property of this condition is that all the required calculations are performed independently on each individual subsystem. Except well posedness, not any other conditions are asked for subsystem parameters/connections. This is in sharp contrast to recent results on structural observability/controllability, which is proven to be NP-hard. Some characteristics are established for a subsystem that are helpful in constructing an observable/controllable NDS. It has been made clear that subsystems with an input matrix of full column rank are helpful in constructing an observable NDS while subsystems with an output matrix of full row rank are helpful in constructing a controllable NDS. These results are extended to an NDS with descriptor form subsystems. As a byproduct, the full normal rank condition of previous works on network observability/controllability has been completely removed. On the other hand, satisfaction of this condition is shown to be appreciative in building an observable/controllability NDS. [ABSTRACT FROM AUTHOR]

Both uniform quarantine and isolation measures, due to the COVID-19 pandemic, have brought forth unprecedented and severe socio-economic impacts. For the global post-COVID economic recovery, it is of great significance to explore scientific ways to reopen the borders with consideration of both risk and efficiency. With the development of international travel health certificate or digital travel pass, differentiated inspection and quarantine measures can be implemented to accelerate the recovery of international travel. In this paper, we study a multi-tier inspection queueing system with finite capacity based on a differentiated level of risk classification. A queueing analysis is conducted for the stochastic process of inspecting cross-border travelers under differentiated service for inspection and quarantine. Besides, we develop a computing method to determine the steady-state probability and several performance indices of the proposed queueing system, and an illustrative example is also set to introduce a step-by-step process for the method. Furthermore, we figure out the relationship between the model parameters and system performance of interest by means of a series of numerical experiments. In the data analysis, we also illustrate the monotonic and concave effects on the system performance, which can provide a visualized understanding of the trade-off between safety and efficiency in the studied multi-server queueing system with hierarchical inspection channels and finite capacity. Our findings can reveal some managerial insight into the border control problems, which could reconcile the efficiency with safety in the current epidemic prevention and control tasks.

Typing on a smartwatch is challenging because of the fat-finger problem. Rising to the challenge, we present a soft keyboard for ultrasmall touch screen devices with efficient visual feedback integrated with autocorrection and prediction techniques. After exploring the design space to support efficient typing on smartwatches, we designed a novel and space-saving text entry interface based on an in situ decoder and prediction function that can run in real-time on a smartwatch such as LG Watch Style. We outlined the details implemented through performance optimization techniques and released interface code, APIs, and libraries as open source. We examined the design decisions with the simulations and studied the visual feedback methods in terms of performance and user preferences. The experiment showed that users could type more accurately and quickly on the target device with our best-performing visual feedback design and implementation. The simulation result showed that the single word suggestion could yield a sufficiently high hit ratio using the optimized word suggestion algorithm.

Unmanned aerial vehicles (UAVs) operate with large degrees of autonomy when executing tasks from a ground-based controller. In this work, we design an (immersive) interface for drone management. Our interface supports operators in mission execution of one or several (automated) UAVs within a fleet. This allows operators to assign tasks to UAVs, while safe operations are ensured through in-flight conflict detection and prevention. Our interface fulfills both functional (e.g., reliability) and non-functional requirements (e.g., perceived cognitive load during use). A key design challenge is the latency in information exchanges, which introduces information asymmetries between the humans and UAVs. We then validate the effectiveness of our interface design across several experiments. We find that our design reduces the perceived cognitive load and improves task performance. Altogether, this work has implications for designing interfaces in human-machine collaboration, so humans can effectively control, interact, or collaborate with automated machines, such as UAVs.

This study analyzed complex causal feedback loops in Regional Technology Innovation (RTI) system and established a system dynamics (SD) model of RTI. Taking China Guangdong Pilot Free Trade Zone as a sample, and running the model in VENSIM, it shows high fitting precision and good extrapolating performance. The simulation gives out the future trends of RTI, FCD, ATD and IPR royalties international trade of the region. This study proposed an effective model of RTI, and more importantly, it points out the type, direction and magnitude of the effects caused by IPR policy in RTI system. This SD model can also be used in policy effect simulation in the future.

Taking the perspective of cybernetics theory, enterprise patent management can be described as a controllable information system which includes various activities and performances. This paper aims to analysis the relationship between enterprise patent activities and patent performance, and to help convert technological innovation achievements into patent rights more effectively and consolidate technology superiority. This paper uses System Dynamics method to construct a multiscale nonlinear enterprise patent management model. Validity of this model is tested, simulation is conducted in VENSIM, sensitivity analysis of this model shows that: Technology Disclosure Sufficiency does not have much influence on patent application quantity, but it has strongly positive effect on patent grant rate and patent portfolio diversity, it can also lower the risk of patent circumvention. Simulation shows that technology disclosure sufficiency is a key determinant to reduce information loss and improve output efficiency of enterprise patent management system. Collaboration of R&D personnel, patent engineers and patent agencies should be enhanced to improve TDS, so as to promote enterprise patent management efficiency. This SD model provides a foundation for future research in patent management optimization.

Much attention has been paid internationally to the adoption of sustainable development goals to achieve sustainable outcomes. Although roadmapping is widely used by companies and other organizations to plan long-term strategies, relatively few studies have examined the development of roadmapping methods aiming at sustainability. To address this challenge, in this article, a backcasting-based method to design roadmaps that could be used to facilitate decision making and plan sustainable futures is proposed. By drawing on the concept of backcasting, the proposed roadmap design method consists of two phases: defining a sustainable vision, and describing the pathways that are required to realize that vision. In order to develop pathways that bridge the gap between the present and the vision, we develop a roadmap template called a “four-arrow model.” To demonstrate the proposed method, roadmaps are developed for Japanese manufacturing from the present to 2050 by organizing an expert workshop. As a result, two different roadmaps that connected sustainable visions and associated pathways are successfully developed. The number of ideas generated through the workshop indicates that the proposed method encouraged brainstorming and concept development. Future research will focus on making the roadmap design process more comprehensive by conducting industrial case studies. [ABSTRACT FROM AUTHOR]

Summary: Model frameworks, based on Floquet theory, have been shown to produce effective tools for accurately predicting phase‐noise response of single (free‐running) oscillator systems. This method of approach, referred to herein as macro‐modeling, has been discussed in several highly influential papers and now constitutes an established branch of modern circuit theory. The increased application of, for example, injection‐locked oscillators and oscillator arrays in modern communication systems has subsequently exposed the demand for similar rigorous analysis tools aimed at coupled oscillating systems. This paper presents a novel solution in terms of a macro‐model characterizing the phase‐response of synchronized coupled oscillator circuits and systems perturbed by weak noise sources. The framework is generalized and hence applicable to all circuit configurations and coupling topologies generating a synchronized steady‐state. It advances and replaces the phenomenological descriptions currently found in the published literature pertaining to this topic and, as such, represents a significant breakthrough w.r.t. coupled oscillator noise modeling. The proposed model is readily implemented numerically using standard routines. [ABSTRACT FROM AUTHOR]

In this work, two practical concepts related to private information retrieval (PIR) are introduced and coined full support-rank PIR and strongly linear PIR. Being of full support-rank is a technical, yet natural condition required to prove a converse result for a capacity expression and satisfied by almost all currently known capacity-achieving schemes, while strong linearity is a practical requirement enabling implementation over small finite fields with low subpacketization degree. Then, the capacity of MDS-coded, linear, full support-rank PIR in the presence of colluding servers is derived, as well as the capacity of symmetric, linear PIR with colluding, adversarial, and nonresponsive servers for the recently introduced concept of matched randomness. This positively settles the capacity conjectures stated by Freij-Hollanti et al. and Tajeddine et al. in the presented cases. It is also shown that, further restricting to strongly-linear PIR schemes with deterministic linear interference cancellation, the so-called star product scheme proposed by Freij-Hollanti et al. is essentially optimal and induces no capacity loss. [ABSTRACT FROM AUTHOR]

This article investigates a spatial- $\mathcal {L}^{\infty }$ -norm-based reliable bounded control problem for a class of nonlinear partial differential equation systems in a finite-time interval. The main novelties are reflected in the following aspects: 1) inspired by the sector-nonlinearity approach, the considered nonlinear system is reconstructed by a Takagi–Sugeno fuzzy model, which provides an effective method for control design. Besides, several actuator failures, such as stuck faulty, outage faulty, and bias faulty, are taken into account and modeled by a novel Markov process; 2) partial areas’ states are sampled and transmitted based on a new distributed event-triggered communication strategy, which reduces the cost of the system design and saves the limited network resources to some extent; and 3) on the basis of the first two works, a new piecewise fuzzy controller, which requires fewer actuators compared with the distributed control method, is constructed. Then, some sufficient conditions to guarantee the finite-time boundedness (in the sense of spatial $\mathcal {L}^{\infty }$ norm) and mixed $\mathcal {L}_{2}-\mathcal {L}_{\infty }/\mathcal {H}_{\infty }$ disturbance attenuation performance are established, and a new linear matrix inequality relax technique is introduced to deal with the strict constraint that is caused by the asynchronous phenomenon between plant and controller. Finally, two simulation studies are given to illustrate the effectiveness and advantages of the developed controller. [ABSTRACT FROM AUTHOR]

Caching content close to the end users, e.g., at cellular base stations (BSs), WiFi access points (APs), and end user devices is known to improve efficiency and effectiveness of content delivery. This motivates the development of caching-as-a-service where edge networks and devices provide storage capacity to content providers, and enable them to strategically populate these caches to improve user experience in the targeted network. In this paper, we describe Wi-Cache, a prototype for providing caching-as-a-service at the WiFi edge. Wi-Cache is an SDN (Software Defined Networking) based distributed content caching system at the WiFi edge that uses storage at the APs for caching content. Wi-Cache caches content on wireless APs and delivers them to mobile clients when they are requested. It allows content providers to have fine-grained control over the AP-caches and also execute efficient content placement and delivery algorithms at the WiFi edge using a set of APIs that are provided by Wi-Cache. We also show the effectiveness of the Wi-Cache system using an extensive set of experiments. [ABSTRACT FROM AUTHOR]

Question understanding is an extremely important part of the question and answer (Q&A) system, which is the basis of subsequent information retrieval and answer extraction. In order to improve the semantic understanding of question, we propose a method of understanding the question based on the combination of semantic element for Chinese language. Firstly, the method uses lexical and rules recognition to extract the semantic elements of questions and recognizes the functions according to the preprocessing pattern. Secondly, combining the dependency analysis tree structure of the question and the function type, it can produce the semantic elements. Finally, a normalized semantic expression was generated. We extract the user questions in Baidu-Zhidao as the test set. The result shows that the accuracy of the proposed method is 97.8%, so the semantics of the Chinese language questions can be effectively understood by this method.

This paper presents a case study that demonstrates how tools from compositional verification can be used to design and analyze complex multi-agent systems operating in dynamic and uncertain environments. The case study concerns the design of an unmanned multi-aircraft system tasked to compromise an aerial encroacher by deploying countermeasures. The constituent agents, termed defenders, are fixed-wing unmanned aircraft. To successfully compromise the encroacher, at least one defender must be within a prespecified distance from the encroacher for a certain period, and the defenders must avoid collision among themselves and with the encroacher. Verifying this global property using monolithic (system-level) verification techniques is a challenging task due to the complexity of the components (defenders) and the interactions among them. To overcome these challenges, the components are designed to have a modular architecture, thereby enabling the use of component-based reasoning to simplify the task of verifying the global system property. Results from Euclidean geometry and formal methods are used to prove most component properties. For properties where analytical tools are overly conservative, focused Monte Carlo simulations are carried out. Restricting the use of simulations (or testing) to local verification of partial component properties leads to increasing the reliability of the system.

This paper deals with the real-time simulation of a power tool battery pack on a mechatronic powertrain test bench. The ability of an easy-to-use model for quick and iterative test runs mainly depends on the effort of parameterization. For this purpose, an easily parameterizable battery model is required. The battery model used is based on the current state of research and simulates the battery's behavior with an adequate precision. The suggested parameterization allows building the model without the necessity of experimental investigation. Three different procedures for model parameterization were used and compared with the real battery behavior. In conclusion, this paper shows a good tradeoff between precision and an easy way to handle a battery model for testing mechatronic powertrains.

With the increasing scale and complexity of system, it is very necessary to analyze the safety of complex system. Fault tree is an effective method to safety analysis. However, traditional fault tree relies on manual construction and analysis. When fault nodes and systems are complex, the efficiency and correctness of manual analysis can hardly be guaranteed. To the varied understanding of analysts, it is difficult to ensure the consistency of failure mode and system architecture due to the different understanding from safety analysts and system designers. The same node needs fault analysis again in different systems, which has poor reusability and low efficiency. AltaRica is a fault-oriented Safety Modeling Language. It takes the guard transformation system(GTS) as its core, describes nodes and faults with a style of reusable object-oriented language, and describes information of interaction between nodes and systems through interface connections between nodes and nested systems. Therefore, this paper proposed an automatic system modeling and fault analysis method and its detailed computer algorithm on single class node, multiple nodes and nodes with subsystems based on AltaRica. Finally we developed a software prototype and carry out the automatic modeling and fault analysis in a detailed example. The results showed that the proposed method, algorithm and software prototype can realize automatic graphical modeling of the system on AltaRica, the automatic fault analysis is correct and efficient, has reusability of modeling and fault analysis, and greatly improve the accuracy, objectivity and efficiency of fault modeling and analysis.

Due to the serious impact of border control measures during the ongoing novel coronavirus (COVID-19) epidemic, new difficulties and challenges have been brought to the border lines of most countries and regions. Focusing on the post-COVID global economic recovery, we develop a computing method for studying the health inspection process based on a three-color risk screening management mechanism at border crossing checkpoints. In this article, to manage the cross-border risk efficiently during the epidemic prevention and control, we formulate a queueing model with hierarchical health inspection channels. The structural characteristics and properties of this three-level queueing model are also analyzed by studying the health inspection process with risk classification. Furthermore, we conduct a series of sensitivity analysis on several performance measures for the studied queueing system. In the numerical results, we figure out the monotonicity, convexity and complicated patterns of the derived formulas.

Industry 4.0 (or 4th industrial revolution) facilitates horizontal and vertical digital information flow along value chains up to the end-customer and is highly relevant in a broad variety of industries. Augmented reality (AR) is a key technology in Industry 4.0, which connects the virtual and real-world environments using such digital information flows. In doing so, the technology relies upon the systems that includes hardware and software components. Particularly, optics and photonics are of much importance in the display and processing of information in these systems. However, a particular challenge is that the AR-based systems have not been adopted in the industry as much as other technologies even after several decades of their existence. Based on review of academic literature, an industrial survey and experiments conducted in the industry, this article aims to identify success factors and challenges of AR systems and metrics of photonic components that can form the basis of an AR* framework for photonics-based system design for future research. [ABSTRACT FROM AUTHOR]