System Design Issues Research Articles

Ultra Large-Scale Crowd Monitoring System Architecture and Design Issues

This article proposes a novel ultralarge-scale crowd monitoring system, namely, the ULCM system. The ULCM system enables advanced sensing and networking technologies aimed at collecting and processing multimodal, multiperspective, and real-time crowding data relevant to crowd management. This data will be further analyzed to provide a global realization of evolving events over a large geographical area as they occur in real time. The ULCM is the infrastructure component of an intelligent platform that is being developed by our research group to provide crowd intelligence to decision makers through an interactive digitized visual environment. In order to achieve a full comprehensive scene overview, the ULCM deployment utilizes a multiplicity of unmanned aerial vehicle (UAV) agents in different operational scenarios. The aerial deployment and control are realized by custom multiple UAV networks and airborne LiDAR sensors. The deployment and control on the ground sensory agents are based on multiple subnetworks, including closed-circuit television (CCTV) and infrared gas and ultrasonic sensors networks. Eventually, ULCM employs the software-defined network (SDN) and edge cloud technologies to optimize the networking and data analytics performance from the perspective of infrastructure.

Real-time FPGA implementation of concatenated AES and IDEA cryptography system

<span>The data encryption is one of the most critical issues in the communication system design. Nowadays, many encryption algorithms are being updated to keep pace with the remarkable progress in the communication field. The advanced encryption standard (AES) is a common algorithm that has proved its efficacy. The main drawback of AES is that it uses too simple algebraic structures, since every block is always encrypted in the same way that makes the hacking process possible if the hacker captures the key and the uses S-Box in the input stage. This especially applies to the unwired communication systems where chances of hacking exceed those found in the wired systems. The paper proposes a security enhancement method that is based on utilizing concatenated AES and international data encryption algorithm (IDEA) algorithms. Upon applying the proposed algorithm, the hacking process becomes a great challenge. The paper incorporates the real-time FPGA implementation of the proposed algorithm in the encryption and the decryption stages. Besides, the paper presents a clear analysis of the system’s performance.</span>

Application of UAVs for tourism security and safety

PurposeIn the tourism industry, unmanned aerial vehicles (UAVs) can perform monitoring and patrol missions to protect assets and tourists at attractions such as coastal areas, canyons, national parks, etc. Such use of UAVs can improve safety and security of tourism attraction and facilitate tourism industry. However, there is a key issue regarding economic investment and efficient operation for actual system implementation. The purpose of this paper is to provide a guideline for supporting economic investment and the efficient operation of UAV system in the tourism industry.Design/methodology/approachIdeas and methodologies have been proposed to overcome the fundamental limitations of commercial UAVs. A mathematical optimization model is developed to determine the optimal number of UAVs to be purchased, and its operation schedules simultaneously.FindingsUsing proposed concept and methodology, UAVs can support long duration of missions. Economic system design as well as the operation schedule is derived with the hypothesis data in Kkot-Ji beach in Korea. The proposed methodology and approach is expected to have huge potential at many tourism attractions to achieve the safety and security of tourists.Practical implicationsThe result of this study can facilitate practical use of UAVs in the tourism industry. Furthermore, it is applicable in many industries that need UAV systems such as national defence, agriculture, disaster management, etc.Originality/valueThe proposed study suggests a solution to handle fundamental weakness of UAVs and support long duration of missions. In addition, this study incorporates economic system design issue and operation issue simultaneously.

Is the 'never event' concept a useful safety management strategy in complex primary healthcare systems?

A sub-group of rare but serious patient safety incidents, known as 'never events,' is judged to be 'avoidable.' There is growing interest in this concept in international care settings, including UK primary care. However, issues have been raised regarding the well-intentioned coupling of 'preventable harm' with zero tolerance 'never events,' especially around the lack of evidence for such harm ever being totally preventable. We consider whether the ideal of reducing preventable harm to 'never' is better for patient safety than, for example, the goal of managing risk materializing into harm to 'as low as reasonably practicable,' which is well-established in other complex socio-technical systems and is demonstrably achievable.We reflect on the 'never event' concept in the primary care context specifically, although the issues and the polarized opinion highlighted are widely applicable. Recent developments to validate primary care 'never event' lists are summarized and alternative safety management strategies considered, e.g. Safety-I and Safety-II. Despite their rarity, if there is to be a policy focus on 'never events,' then specialist training for key workforce members is necessary to enable examination of the complex system interactions and design issues, which contribute to such events. The 'never event' term is well intentioned but largely aspirational-however, it is important to question prevailing assumptions about how patient safety can be understood and improved by offering alternative ways of thinking about related complexities.

Calibration and validation for a real-time membrane bioreactor: A sliding window approach

The paper presents a novel model calibration and validation strategy of membrane bioreactor (MBR) for wastewater treatment. The approach is based on a dynamic model of the activated sludge process and it consists simultaneously on estimating the model’s parameters and computing the dissolved oxygen control input. Activated sludge model No. 1 (ASM1) has been widely used to describe the biological process of activated sludge processes. However, most system states and parameters within ASM1 are not easily obtained, hence not applicable for model calibration and validation. In this work, a reduced-order model presented herein serves as a tool for predicting the dynamic behavior of the MBR plant. The model contains only 4 measurable states, where 13 parameters need to be identified. To reduce the complexity of the calibration, the static sensitivity analysis is performed to select the sensitive parameters. The selected parameters are identified based on directly measurable real-time data obtained from the plant. In addition, the dissolved oxygen is also maintained at a certain level to mimic the real-time control behavior. Model calibration is achieved based on a sliding window optimization problem, which searches for the optimal parameters set and control variables during each identification cycle. Different datasets sampled for the same MBR plant have been used for model validation. Both calibration and validation results are evaluated by several performance indexes, which indicates an acceptable correspondence with the experimental data. The developed model can be employed for process state estimation and control purpose as well as design issues for MBR systems.

Artificial Noise-Aided Secure Relay Communication With Unknown Channel Knowledge of Eavesdropper

In this article, a new relay-aided secure communication system is investigated, where a transmitter sends signals to a destination via an amplify-and-forward (AF) relay in the presence of an eavesdropper. We consider a general system configuration, where the source, relay, destination, and eavesdropper are all equipped with multiple antennas. In the practical scenarios of unknown eavesdropper's channel state information (CSI) and uncertainty of the eavesdropper's location, we aim to maximize the expected value of the system secrecy rate over the presumed distribution of the eavesdropper's channels, by exploiting the artificial noise (AN) transmitted by the source and relay nodes. The system design issue is formulated as a nonconvex stochastic optimization problem with a source transmission power constraint and a nonconvex relay transmission power constraint. A novel computational method is proposed to solve this challenging problem. The new method is developed based on an exact penalty function method together with a parallel stochastic decomposition algorithm. Numerical simulations are performed to study the effectiveness of the proposed scheme at various locations of the eavesdropper. Simulation results show that for most cases, secure communication can be achieved without the CSI knowledge of eavesdropper's channels, and the achievable secrecy rate follows the trend of a benchmark system where the eavesdropper's full CSI is available. In particular, the achievable system secrecy rate increases with the number of antennas at the legitimate users. Moreover, the optimal power allocated for the transmission of the AN increases with the system signal-to-noise ratio. The proposed computational method achieves a higher system secrecy rate than a conventional penalty function based approach.

Zone Fare System Design in a Rail Transit Line

As a widely existing form of public transit fare structures, zone fare system is traditionally designed in a separate way, which may lead to suboptimal results. This paper aims to concurrently address the zone division and fare calculation issues of the zone fare system design in a rail transit line. It is necessary to consider passengers as well as operators to find an impartial zone fare system. A fair zone fare system is one where the zone fares are as close as possible to the distance-based fares, for the fares of the distance-based fare system are highly correlated with the actual distance of trips. Thus, the fare deviations for the trips between the zone fare system and the distance-based fare system are utilized as the evaluation metric of fairness. To achieve the goal of minimizing fare deviations for all trips, we introduce three indexes: average absolute deviation, average squared deviation, and maximum mileage fare deviation. With the three indexes as the objective functions, we develop a joint optimization algorithm where a novel zone boundary adjustment scheme is proposed as the key technique. Numerical results show that the proposed algorithm can effectively provide a joint optimal scheme and the optimal number of planned zones is 5 for Changsha Metro Line 2. The proposed algorithm can provide guidance for the practical design and adjustment of the zone fare system.

A Collaborative Decision Support System Framework for Vertical Farming Business Developments

The emerging industry of vertical farming (VF) faces three key challenges: standardisation, environmental sustainability, and profitability. High failure rates are costly and can stem from premature business decisions about location choice, pricing strategy, system design, and other critical issues. Improving knowledge transfer and developing adaptable economic analysis for VF is necessary for profitable business models to satisfy investors and policy makers. A review of current horticultural software identifies a need for a decision support system (DSS) that facilitates risk-empowered business planning for vertical farmers. Data from the literature alongside lessons learned from industry practitioners are centralised in the proposed DSS, using imprecise data techniques to accommodate for partial information. The DSS evaluates business sustainability using financial risk assessment. This is necessary for complex/new sectors such as VF with scarce data.

Reliable applied objective for identifying simple and detailed photovoltaic models using modern metaheuristics: Comparative study

The first issue in the optimal photovoltaic system design is providing an accurate PV model that emulates the system behaviour under several environmental conditions. The accuracy of the photovoltaic model stands on its identified parameters that are mainly based on the executed optimization technique and the employed objective function. As per the literature, two methodologies have been applied for computing the estimated current in the objective function, detecting the most efficient one is the first step for achieving high qualified and precise solutions. Motivated by that, we investigate the two objective functions with considering several novel optimization algorithms. The implemented algorithms are marine predators algorithm, Slime mould algorithm, atom search optimization, Political Optimizer, Parasitism–Predation algorithm as well as harris hawk optimizer and salp swarm algorithm. The Lambert function forms have been used for validating the results. Several profiles of the experimental datasets are measured under different levels of temperature and irradiation conditions to identify the single, double and three diode models parameters of the RTC France solar cell and Canadian-Solar-(CS6P-240P) multi-crystalline solar panel. The main findings show that, applying Newton–Raphson while computing the estimated current in the objective function enhances the algorithms performance to provide the more precise and accurate parameters in comparison with using the measured current and solve the photovoltaic model equation linearly. Moreover, the marine predators algorithm confirms the quality of its solutions and provides a better representation for the photovoltaic datasets with high stability based on the lambert forms and the statistical analyses.

UTree

Tail latency is a critical design issue in recent storage systems. B + -tree, as a fundamental building block in storage systems, incurs high tail latency, especially when placed in persistent memory (PM). Our empirical study specifies two factors that lead to such latency spikes: ( i ) the internal structural refinement operations (i.e., split, merge, and balance), and ( ii ) the interference between concurrent operations. The problem is even worse when high concurrency meets with the low write bandwidth of persistent memory. In this paper, we propose a B + -tree variant named μTree. It incorporates a shadow list-based layer to the leaf nodes of a B + -tree to gain benefits from both list and tree data structures. The list layer in PM is exempt from the structural refinement operations since list nodes in the list layer own separate PM spaces, which are organized in an element-based way. Meanwhile, μTree still gains the locality benefit from the tree-based nodes. To alleviate the interference overhead, μTree coordinates the concurrency control between the tree and list layer, which moves the slow PM accesses out of the critical path. We compare μTree to state-of-the-art designs of PM-aware B + -tree indices under both YCSB workload and real-world applications. μTree achieves a 99th percentile latency that is one order of magnitude lower and 2.8 - 4.7 times higher throughput.

Research Challenges for Heterogeneous Cyberphysical System Design

Heterogeneous computing is widely used at all levels of computing. However, heterogeneity presents challenges. This article considers research issues in heterogeneous cyberphysical system design, including interoperability, physical modeling, models of computation, selfawareness and adaptation, architecture, and scheduling.

PN code tracking based on sub‐Nyquist and non‐commensurate sampling

Increasingly high bandwidths are desired in modern navigation and autonomous RF ranging signal design to achieve better pseudo-noise (PN) ranging accuracy. However, fulfilling the Nyquist criterion for such high-bandwidth signals would be a challenging issue for system design. Considering that the Nyquist criterion is not a necessary condition for PN code tracking, sub-Nyquist sampling can be adopted as a feasible solution to this issue. Nevertheless, it is at the expense of an increase in thermal noise caused by tracking error. This problem is particularly prominent for tracking weak signals such as navigation signals, which limits the applicability of this sampling scenario. As far as high-precision autonomous PN ranging is concerned, however, the tracking error due to digital implementation is not negligible and even becomes the dominating factor instead of thermal noise. This means that the performance loss incurred by sub-Nyquist sampling can be eliminated under high-signal-to-noise ratio conditions. Exploiting this fact, this Letter proposes a novel PN code tracking approach based on sub-Nyquist and non-commensurate sampling, providing a solution to achieving high-ranging accuracy while breaking the bounds of the Nyquist sampling theorem without performance degradation. The approach is very attractive for precise PN ranging applications demanding miniaturised implementation.

Dose Verification Errors in Hospitals: Literature Review of the eMAR-based Systems Used by Nurses.

The effectiveness of the dose verification features of the electronic medication administration record (eMAR) and complementary systems in the hospital setting is not well understood. The authors completed a narrative synthesis of literature findings on the effectiveness of eMAR-based systems in the hospital setting. A literature review was carried out across 5 bibliographic databases to evaluate the safety features of current eMAR-based systems in preventing dosing errors and design issues that impede their usability. While eMAR-based systems are beneficial to reducing order and drug cross-checking errors, safe dose verification features are sporadically available for targeted tasks. Overall, the eMAR had little impact on preventing low to moderate dosing errors. Dosing errors may occur because of error-prone activities that result from system design and work process issues during medication administration.

Resource Allocation and Node Placement in Multi-Hop Heterogeneous Integrated-Access-and-Backhaul Networks

We consider a heterogeneous MIMO-OFDMA based dense small cell (SC) system in which each macro cell base station (MBS) serves its coverage area with the help of small cell base stations (SBSs) through multi-hop wireless connections. The SBSs act as integrated access and backhaul (IAB) nodes that handle both access and backhaul traffics with wireless links. We first develop an optimal (sum-rate maximization) resource allocation (RA) algorithm which considers subcarriers/spatial subchannels assignment and the associated power allocations. We also present two low-complexity suboptimal RA schemes which, as verified by simulations, incur only minor performance loss in the high SNR region. Our RA algorithms can be applied to other multi-hop networks with general UE association rule and node location distributions. We study the channel aging effect caused by the time lag between the time channel state information (CSI) is measured and that when data transmission occurs. We show the benefit of channel prediction and the limit of a centralized RA approach. The advantages of frequency (channel) reuse and the multi-hop architecture are demonstrated as well. A related but perhaps more important system design issue for an IAB cellular network is the IAB node placement problem. With the given UE association rule and UE location distribution, we present systematic approaches to find the optimal node locations. For two special propagation models, we derive closed-form expressions for the node locations that maximizes a spectral efficiency lower bound. Numerical results validate the accuracy of our estimates based on either numerical evaluations or closed-form solutions.

A Study on Evolution Issue in Product-Service System Design

A Study on Evolution Issue in Product-Service System Design

Protective effect of pyrolysis gases combustion against surface ablation under different Mach numbers

Whether pyrolysis gases combustion has effect on surface ablation of charring material is a key issue in the optimization design of thermal protection system for hypersonic vehicles. The coupled method considering combustion of pyrolysis gases in shock layer is presented, realized in MATLAB and validated by comparison with the arcjet experiments. Relationship between surface ablation and mole fraction of oxygen, mass injection rate of pyrolysis gases and surface temperature of charring material under different Mach numbers are predicted by this coupled method. Numerical results indicate that the protective effect of pyrolysis gases combustion on surface ablation is more and more obvious with increase of Mach number. This study is helpful to the optimization of thermal protection system for hypersonic vehicles.

Reference Modulation for Performance Enhancement of Motion Control Systems With Nonlinear Parameter Variations

In general, it is not intuitive to quantify the performance of nonlinear systems; thus, designing controllers and/or estimators is not easy. Moreover, there are situations in which a system designed with a fixed feedback controller is not customizable, and yet its closed-loop performance (e.g., disturbance attenuation) is not satisfactory. In this study, we first present an equivalent linear model for motion control systems with nonlinear parameter variations. The linear model facilitates the quantitative analysis of the motion control system. Furthermore, we introduce a reference modulation technique that enhances the performance by boosting loop-gain over a desired range of frequencies. The proposed approach, by introducing an additional modulated function and a direct feedforward channel, facilitates the separation of the closed-loop sensitivity function from other issues of the closed-loop system design so that both disturbance attenuation and tracking performance can be improved. We also provide robust stability analysis of the motion control systems by reference modulation. The simulations and experiments are performed on a permanent magnet synchronous motor system with a predesigned feedback controller. The simulation and experimental results show that both the tracking and disturbance attenuation performance of the closed-loop system are enhanced via reference modulation.

Carbon footprint for designing reverse logistics network with hybrid manufacturing-remanufacturing systems

This article proposes one further step toward the design of Sustainable Manufacturing Enterprise. This article presents an integrated approach for designing a reverse logistics network by minimizing the carbon emissions and the transportation distances between different candidate centers while considering several system design and operational issues of a Hybrid Manufacturing-Remanufacturing System operating within the above-mentioned reverse logistics network. Accordingly, the article attempts to integrate various sustainability aspects indoctrinated in the Sustainable Manufacturing philosophy. In view of this, a mixed integer programming model for designing a reverse logistics network is developed. The model considers the carbon foot print, facility location, and the material flow aspects of the reverse logistics network; in which a hybrid manufacturing-remanufacturing system is integrated. A detailed discussion of a numerical example is presented to illustrate the proposed model. The model has potential applications for supply chain managers designing a reverse logistics networks as well as for production managers at the operations level.

The role of banks and the state in the shaping of the French fund industry

The article deals with the issue of the French financial system design based on a historical analysis of the development of the fund management industry. It recounts how the main banks have become leaders in the global asset management industry. This success relies on a long-term institutional evolution towards a hybrid model and the ongoing close relationships between banks and the State since the end of World War II. The establishment of a friendly institutional framework for the bank intermediation expansion was rooted in the seizure of power by reformist civil servants in the late 1950s and the early 1960s, who would later become heads at the Treasury and the main banks. We also argue that the State’s ability to develop new forms of interventions, especially during financial liberalization and European construction, has been crucial in the development of a competitive fund industry. Finally, we show that the State’s and banks’ interests have driven the hybridization process of the fund sector and that the fund sector serves primarily the State’s interests and the funding needs of the financial sector at the expense of the real economy.

Optimized approach for antipattern detection in service computing architecture

Maintainability of a software can be enhanced by using refactoring activities. Refactoring activities aims at eliminating antipatterns from the system Application of refactoring techniques negatively impacts the power and energy consumption behavior of software systems. In other words, maintainability sometimes leads to sustainability degradation. Antipatterns depict suboptimal implementation choices that lead to more error prone and highly maintainable systems. A large number of antipatterns have been defined in the literature which are used by developers to detect system design issues. Despite the large number of antipatterns which are defined, their accuracy is still a subjective measure. Objective: There are multiple issues like uncertainty, boundary definition, metric combination and rule conversion. To overcome these limitations the research paper focusses on the use of optimized algorithms for antipattern detection. Method: The research paper deals with the existing antipattern detection techniques and proposal of a new optimized algorithm which not only works on static metrics but also takes into consideration dynamic metrics for execution. Later on the results are optimized using genetic algorithm. A comparative analysis of the existing models with the proposed model is also done. The analysis clearly depicted that the proposed approach has better precision and recall rate of approximately 90 %. Result: The proposed approach was successful in identification of five antipatterns (Multi Service, Fine Grained Web Service, Chatty Web Service, Data Web Service and Ambiguous Web Service).