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It is now possible to detect dangerous arcing faults in the paper insulation of transformers and distinguish them from arcing faults in oil, using new sub-zones of Duval Pentagons 1 and 2. [ABSTRACT FROM AUTHOR]

This year the IEEE Transactions on Dielectrics and Electrical Insulation (TDEI) is celebrating its fiftieth anniversary. TDEI actually began in 1994 when 'Dielectrics' was added to the previous title of the same publication of IEEE Transactions on Electrical Insulation (TEI). The first issue of TEI was published in March 1965, fifty years ago, with a very modest beginning. That first issue, which can be accessed on IEEE Xplore, had only four papers constituting a total of 19 printed pages. TEI was international in outlook right from its beginning. The four papers in the first issue were submitted from Japan (one paper) and the USA (three papers). The second issue of TEI was published in November 1965 and had papers from the United Kingdom (two) and the USA (one). In its first year TEI had a total of seven papers totaling 48 pages. These papers covered a wide range of topics such as electrical failure of organic insulators, thermal behavior of enamel wires and other solid insulation, electrical breakdown of solids and gaseous insulation. Papers on these topics may still be seen in recent issues of TDEI. [ABSTRACT FROM AUTHOR]

This paper is concerned with the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. In contrast to existing synchronization network models, the current study considers both internal time‐varying delays and coupling time‐varying delays. By analyzing the two factors (i.e. time‐varying delays and uncertainties) on the synchronization performance of stochastic uncertain complex dynamic networks, a new inverse optimal adaptive control is proposed. The analysis tool developed in this paper is based on Lyapunov technique, algebraic graph theory and inverse optimality, which does not need to solve Hamilton‐Jacobi‐Bellman equation. Some sufficient conditions are established for the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. To demonstrate the effectiveness of the present approach, simulation results are illustrated. In this paper, we consider the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. Different from the existing synchronization of the networks model, we take the internal time‐varying delays and the coupling time‐varying delays into account. By analyzing the two factors (i.e. time‐varying delays and uncertainties) on the synchronization performance of stochastic uncertain complex dynamic networks, a novel inverse optimal adaptive control is proposed. The analysis tool developed in this paper is based on Lyapunov technique, algebraic graph theory and inverse optimality, which does not need to solve Hamilton‐Jacobi‐Bellman equation. Some sufficient conditions are established for the synchronization of stochastic uncertain complex dynamic networks with time‐varying delays. [ABSTRACT FROM AUTHOR]

Time-domain indirect methods based on Lyapunov stability theory and linear matrix inequality techniques (LMIs) have been applied for delay-dependent stability analysis of large-scale load frequency control (LFC) schemes. This paper aims to enhance the numerical tractability of large-scale LMIs by exploiting the special characteristics of the LFC loops. First, in the typical LFC model, only a few delayed states that are directly influenced by transmission delays are distinguished from other normal system states. Hence, an improved reconstruction model is formed, based on which the delay-dependent stability condition is established with the decreased order of the LMIs and decision variables. Then, to further improve the numerical tractability of the developed stability criterion, all weighting matrices required in the augmented Lyapunov functional are enforced to have structural restrictions by proposing an extended symmetry-exploiting technique. Case studies show that the method proposed in this paper significantly improves the calculation efficiency of stability criterion established for multi-area power systems at the cost of only a minor reduction in computational accuracy. [ABSTRACT FROM AUTHOR]

Delays and cost overruns in turnkey projects can lead to significant economic losses, disputes and even project abandonment. These facts negatively impact the environmental, social and governance (ESG) policies of companies involved in the project. In this paper, a bibliographic review was conducted to identify the leading causes of delays and cost overruns in turnkey industrial projects in the refining, gas and conventional electricity generation (RGE) sector and propose good practices to avoid or mitigate them. We identified 893 causes of delays and cost overruns and 147 mitigation measures. The causes and mitigation measures were grouped into eight categories based on the execution phases of an RGE project. A critical analysis was carried out to avoid duplication, and the result was evaluated by experts in turnkey project management, reducing the causes and mitigation measures to a final set of 103 and 49, respectively. The construction category showed the most significant influence on project delays and cost overruns, and this, together with the preliminary phase and project management categories, contributed to 60% of the identified causes. The findings of this study can help project managers improve the profitability of turnkey industrial projects, promoting innovation and sustainability within companies and society. [ABSTRACT FROM AUTHOR]

Stream processing is used in various fields. In the field of big data, stream aggregation is a popular processing technique, but it suffers serious setbacks when the order of events (e.g., stream elements) occurring is different from the order of events arriving to the systems. Such data streams are called “non-FIFO steams”. This phenomenon usually occurs in a distributed environment due to many factors, such as network disruptions, delays, etc. Many analyzing scenarios require efficient processing of such non-FIFO streams to meet various data processing requirements. This paper proposes an efficient scalable checkpoint-based bidirectional indexing approach, called $CPiX$ C P i X , for faster real-time analysis over non-FIFO streams. CPiX maintains the partial aggregation results in an on-demand manner per checkpoint. CPiX needs less time and space than the state-of-the-art approach. Extensive experiments confirm that CPiX can deal with out-of-order streams very efficiently and is, on average, about 3.8 times faster than the state-of-the-art approach while consuming less memory. [ABSTRACT FROM AUTHOR]

This paper presents an edge‐based event‐triggered delay distributed algorithm for solving the economic dispatch problem (EDP) in smart grids. The objective of the EDP is to minimize the total generation cost by allocating power to individual generators, each with its local generation constraint. To save the overhead of communication resources between agents, an edge‐based event‐triggered mechanism is suggested. By setting distinct triggering thresholds for each communication edge, the agent may efficiently regulate the communication frequency among all neighbors. However, in practice, owing to the instability of the network, the agent may receive information regarding its neighbors, leading to communication lags for every communication link. The virtual agent technique and double‐stochastic matrix augmentation technique provide an equivalent delay‐free EDP. It is demonstrated that the proposed algorithm can asymptotically converge to the global optimal solution as long as the communication delay is arbitrary, time‐varying, and random, but bounded. Objective and clear evidence is provided through a case study in smart grids to verify the algorithm's feasibility. [ABSTRACT FROM AUTHOR]

Construction project delays can stem from a myriad of factors and pose significant challenges for owners and contractors. While numerous methods for analyzing delays exist, the majority are designed for network scheduling, lack contemporaneous tracking (i.e., do not allow for identifying and tracking delays as they occur), and struggle with attributing delays to specific stakeholders. Therefore, this paper introduces a novel graphical approach to monitor delays by comparing as-planned and as-built schedules at the activity level. Distinguished by its contemporaneous nature, the new method allows real-time tracking and quantification of delays. This facilitates identifying their origin and potential causes. Rules for constructing the graphs of various delay scenarios are demonstrated for typical activity combinations. The effectiveness of the proposed method is validated via a case study that showcases its practical application. Implementing it is straightforward, and while the method could be applied to network schedules, its relevance lies in linear and repetitive schedules. The cyclic nature of tasks in such schedules underscores the importance of contemporaneous delay tracking to facilitate swift remedial actions and pinpoint liability. Practical Applications: In this study, the authors present a new way to track delay using graphs by comparing starts, productivities, and finishes of as-planned and as-built schedules at the activity level. Because it is contemporaneous, the new approach tracks and measures delays in real time, currently manually, but easily implemented as computer code. This method makes it easier to find the source and possible causes of activity and project delays. Detailed rules are derived for common activity scenarios and interactions on how to create the respective graphs. A real-world study demonstrates how the proposed method can be used to substantiate its potential value to practitioners in industry. The proposed approach is practical, and while it could be used for network schedules, it is especially useful for linear and repetitive schedules. [ABSTRACT FROM AUTHOR]

In one of the several manifestations, the future cellular networks are required to accommodate a massive number of devices, several orders of magnitude compared to today’s networks. At the same time, the future cellular networks will have to fulfill stringent latency constraints. To that end, one problem that is posed as a potential showstopper is extreme congestion for requesting uplink scheduling over the physical random access channel (PRACH). Indeed, such congestion drags along scheduling delay problems. In this paper, the use of self-organized device-to-device (D2D) clustering is advocated for mitigating PRACH congestion. To this end, this paper proposes two D2D clustering schemes, namely, random-based clustering and channel-gain-based clustering. Accordingly, this paper sheds light on random access within the proposed D2D clustering schemes and presents a case study based on a stochastic geometry framework. For the sake of objective evaluation, the D2D clustering is benchmarked by the conventional scheduling request procedure. Accordingly, this paper offers insights into useful scenarios that minimize the scheduling delay for each clustering scheme. Finally, this paper discusses the implementation algorithm and some potential implementation issues and remedies. [ABSTRACT FROM AUTHOR]

5G wireless networks are expected to support ultra-reliable low latency communications (URLLC) traffic which requires very low packet delays (< 1 ms) and extremely high reliability (~99.999%). In this paper, we focus on the design of a wireless system supporting downlink URLLC traffic. Using a queuing network-based model for the wireless system, we characterize the effect of various design choices on the maximum URLLC load it can support, including: 1) system parameters such as the bandwidth, link SINR, and QoS requirements; 2) resource allocation schemes in orthogonal frequency-division multiple access (OFDMA)-based systems; and 3) hybrid automatic repeat request schemes. Key contributions of this paper which are of practical interest are: 1) study of how the minimum required system bandwidth to support a given URLLC load scales with associated QoS constraints; 2) characterization of optimal OFDMA resource allocation schemes which maximize the admissible URLLC load; and 3) optimization of a repetition code-based packet re-transmission scheme. [ABSTRACT FROM AUTHOR]

This paper describes a test compaction procedure that combines the advantages of using multicycle tests for test compaction with the advantages of using both broadside and skewed-load tests for increasing the fault coverage and achieving test compaction. The procedure is the first to combine these two concepts in a single procedure. The combination is made possible by a definition of a multicycle skewed-load test that is suggested in this paper, and complements the definition of a multicycle broadside test. Experimental results demonstrate the effectiveness of multicycle broadside and skewed-load tests in achieving test compaction for benchmark circuits. [ABSTRACT FROM AUTHOR]

Absolute time synchronization is a basic issue in wireless communication. With the advent of 5G, many emerging vertical industry applications have put forward demands for timing accuracy over air interface. High Precision Timing method over Air Interface based on PHY Layer Signals (TAP) is proposed for mobile networks. It is designed to provide microsecond level timing accuracy at a relatively low cost compared to the existing timing methods, such as GNSS, NTP, PTP, etc. The purpose of this paper is to comprehensively improve TAP, including timing accuracy, stability and compatibility, so as to promote its practical application. This paper proposes improvements to TAP from four aspects: timing algorithm, timing pilot signal, terminal timing process and timing parameters determination. We improve the TAP’s deficiencies in delay estimation, delay compensation accuracy and real-time matching of timing information. We implement the workflow of TAPv2 for UE based on FPGA. Finally, we settle the problem of TAP parameters determination by applying a DQN method. The simulations and tests not only show that the DQN model can effectively determine the TAP parameters, but also show TAPv2 can achieve higher accuracy and stability than TAP in multiple scenarios based on the interaction with baseband. [ABSTRACT FROM AUTHOR]

Due to the non-uniform geographic distribution and time-varying characteristics of the ground traffic request, how to make full use of the limited beam resources to serve users flexibly and efficiently is a brand-new challenge for beam hopping satellite systems. The conventional greedy-based beam hopping methods do not consider the long-term reward, which is difficult to deal with the time-varying traffic demand. Meanwhile, the heuristic algorithms such as genetic algorithm have a slow convergence time, which can not achieve real-time scheduling. Furthermore, existing methods based on deep reinforcement learning (DRL) only make decisions on beam patterns, lack of the freedom of bandwidth. This paper proposes a dynamic beam pattern and bandwidth allocation scheme based on DRL, which flexibly uses three degrees of freedom of time, space and frequency. Considering that the joint allocation of bandwidth and beam pattern will lead to an explosion of action space, a cooperative multi-agents deep reinforcement learning (MADRL) framework is presented in this paper, where each agent is only responsible for the illumination allocation or bandwidth allocation of one beam. The agents can learn to collaborate by sharing the same reward to achieve the common goal, which refers to maximize the throughput and minimize the delay fairness between cells. Simulation results demonstrate that the offline trained MADRL model can achieve real-time beam pattern and bandwidth allocation to match the non-uniform and time-varying traffic request. Furthermore, when the traffic demand increases, our model has a good generalization ability. [ABSTRACT FROM AUTHOR]

This paper considers a device-to-device (D2D) fog-radio access network wherein a set of users are required to store/receive a set of files. The D2D devices are connected to a subset of the cloud data centers and thus possess a subset of the data. This paper is interested in reducing the total time of communication, i.e., the completion time, required to disseminate all files among all devices using instantly decodable network coding (IDNC). Unlike previous studies that assume a fully connected communication network, this paper tackles the more realistic scenario of a partially connected network in which devices are not all in the transmission range of one another. The joint optimization of selecting the transmitting device(s) and the file combination(s) is first formulated, and its intractability is exhibited. The completion time is approximated using the celebrated decoding delay approach by deriving the relationship between the quantities in a partially connected network. The paper introduces the cooperation graph and demonstrates that the problem is equivalent to a maximum weight clique problem over the newly designed graph. Extensive simulations reveal that the proposed solution provides noticeable performance enhancement and outperforms previously proposed IDNC-based schemes. [ABSTRACT FROM PUBLISHER]

Motivated by applications in data center networks, in this paper, we study the problem of scheduling in an input queued switch. While throughput maximizing algorithms in a switch are well-understood, delay analysis was developed only recently. It was recently shown that the well-known MaxWeight algorithm achieves optimal scaling of mean queue lengths in steady state in the heavy-traffic regime, and is within a factor less than 2 of a universal lower bound. However, MaxWeight is not used in practice because of its high time complexity. In this paper, we study several low complexity algorithms and show that their heavy-traffic performance is identical to that of MaxWeight. We first present a negative result that picking a random schedule does not have optimal heavy-traffic scaling of queue lengths even under uniform traffic. We then show that if one picks the best among two matchings or modifies a random matching even a little, using the so-called flip operation, it leads to MaxWeight like heavy-traffic performance under uniform traffic. We then focus on the case of non-uniform traffic and show that a large class of low time complexity algorithms have the same heavy-traffic performance as MaxWeight, as long as it is ensured that a MaxWeight matching is picked often enough. We also briefly discuss the performance of these algorithms in the large scale heavy-traffic regime when the size of the switch increases simultaneously with the load. Finally, we perform empirical study on a new algorithm to compare its performance with some existing algorithms. [ABSTRACT FROM AUTHOR]

Effective nonlinear control of manipulators with dynamically coupled arms, like those with direct drives, is the subject of the paper. Model-based predictive control (MPC) algorithms with nonlinear state-space models and most recent disturbance attenuation technique are proposed. This technique makes controller design and online calculations simpler, avoiding necessity of dynamic modeling of disturbances or resorting to additional techniques like SMC. The core of the paper are computationally effective MPC-NPL (Nonlinear Prediction and Linearization) algorithms, where computations at every sample are divided into two parts: prediction of initial trajectories using nonlinear model, then optimization using simplified linearized model. For a comparison, a known CTC-PID algorithm, which is also model-based, is considered. It is applied in standard form and also proposed in more advanced CTC-PID2dof version. For all algorithms a comprehensive comparative simulation study is performed, for a direct drive manipulator under disturbances. Additional contribution of the paper is investigation of influence of sampling period and of computational delay time on performance of the algorithms, which is practically important when using model-based algorithms with fast sampling. [ABSTRACT FROM AUTHOR]

Intellectual property (IP) cores used in consumer electronics devices mandate protection against reverse engineering (RE) attacks. Functional obfuscation protects the design functionality by enhancing the complexity of RE attacks. This paper proposes a novel low cost (based on power-delay tradeoff) functional obfuscation methodology through employment of robust IP locking technique. In the proposed obfuscation methodology, several strong multipairwise secure IP locking block designs are presented that can only be actuated through application of valid serial key bits. As demonstration, this paper also shows a practical example of a functional obfuscated netlist structure of FIR filter. Proposed obfuscation on comparison with a recent approach for several DSP cores yielded a power reduction of ~10%, design cost reduction ~ 6.5% and security enhancement (strength of obfuscation) of $>\,\,4.29\,\,{e+9}$ times. [ABSTRACT FROM AUTHOR]

This paper proposes an ordered sequence detection (OSD) for digital pulse interval modulation (DPIM) in optical wireless communications. Leveraging the sparsity of DPIM sequences, OSD shows a comparable performance to the optimal maximum likelihood sequence detection with much lower complexity. Compared with the widely adopted sample-by-sample optimal threshold detection (OTD), it considerably improves the bit-error-rate (BER) performance by mitigating error propagation. Moreover, this paper proposes a barrier signal-aided digital pulse interval modulation (BDPIM), where the last of every $K$ symbols is allocated with more power as an inserted barrier signal. BDPIM with OSD (BDPIM-OSD) can limit the error propagation between two adjacent barriers. To reduce the storing delay when using OSD to detect extremely large packets, we propose BDPIM with a combination of OTD and OSD (BDPIM-OTD-OSD), within which long sequences are cut into pieces and separately detected. Approximate upper bounds of the average BER performance of DPIM-OTD, DPIM-OSD, BDPIM-OSD, and BDPIM-OTD-OSD are analysed. Simulations are conducted to corroborate our analysis. Optimal parameter settings are also investigated in uncoded and coded systems by simulations. Simulation results show that the proposed OSD and BDPIM bring significant improvement in uncoded and coded systems over various channels. [ABSTRACT FROM AUTHOR]

In this paper, a second-order bang–bang digital phase-locked loop (BBPLL) with dominant random walk phase noise and transport delay is analyzed using Fokker–Plank equations. Explicit closed-form expressions are derived for the timing error probability distribution function, jitter variance, and power spectral density (psd). For the type-II BBPLL considered in this paper, the timing error distribution is shown to be Laplacian and not Gaussian distributed as previously assumed, while the derived psd is Lorentzian, which is consistent with earlier works. The analytical solutions are valid as long as the continuous-time approximation of the BBPLL dynamics is accurate as is the case for typical operating loop bandwidths. The accuracy of the derived expressions is validated via simulation. [ABSTRACT FROM AUTHOR]

Building clock trees for tight skew constraints of clock delivery networks is standard in the industry. Tight slew constraints of high-performance designs require post-processing techniques to satisfy slew constraints after clock tree synthesis (CTS). Post-processing adversely impacts the power dissipation. This paper proposes slew merging region CTS (SMRcts); a novel algorithm to satisfy bounded slew and skew constraints simultaneously during synthesis. Experimental results performed on International Symposium on Physical Design (ISPD) 2010 benchmarks using a 20-nm FinFET technology show an average reduction of 15% power over a bounded skew approach. Comparison to the ISPD 2010 CTS contest solutions in the literature shows SMRcts producing a 51% improvement in a utility metric. Scalability of SMRcts is demonstrated on ISPD 2013 benchmarks with up to 100k sinks. [ABSTRACT FROM AUTHOR]

This paper considers the problem of reducing the broadcast decoding delay of wireless networks using instantly decodable network coding- based device-to-device communications. In contrast with the previous works that assume a fully connected network, this paper investigates a partially connected configuration in which multiple devices are allowed to transmit simultaneously. To that end, different events occurring at each device are identified so as to derive an expression for the probability distribution of the decoding delay. Afterward, the joint optimization problem over the set of transmitting devices and packet combination of each is formulated. The optimal solution of the joint optimization problem is derived using a graph-theoretic approach by introducing the cooperation graph in which each vertex represents a transmitting device with a weight translating its contribution to the network. This paper solves the problem by reformulating it as a maximum weight clique problem which can efficiently be solved. Numerical results suggest that the proposed solution outperforms state-of-the-art schemes and provides significant gain, especially for poorly connected networks. [ABSTRACT FROM AUTHOR]

Human-machine interactive systems show increasing demand for analysing fast moving objects in high-frame-rate videos. Robust foreground detection, which is able to reduce large amount of redundant background data from high-frame-rate video, becomes the essence to achieve ultra-high-speed human-machine interactions. This paper proposes a local spatial propagation based background model generation, a local linear illumination correction based background model update, and a regional central coordinates and edge keypoints constrained foreground region reselection. The three proposals make up a robust and hardware-friendly foreground detection method. Experimental results prove that the proposed hardware-friendly algorithm achieves high accuracy and robustness on various kinds of challenging cases. Meanwhile, the hardware implementation utilizes little hardware resources and achieves realtime processing of high-frame-rate (784 frame/second) video with the delay less than 1 ms/frame in image processing core. In addition, a practical system is implemented by combing a PC, a high-speed camera and a field programmable gate array (FPGA) for realworld applications. This work will significatively promote the development and application of high-speed human machine interaction. A demo of the proposed vision system working at 784 FPS is available at https://wcms.waseda.jp/em/5f84f75136a6. Note to Practitioners—This paper was motivated by the problem of high-frame-rate video contains large amount of redundant background pixels which makes ultra-high-speed human-machine interactions inaccessible. Existing approaches are mainly focused on designing complex background models, but processing speed, which is the most important issue for ultra-high-speed human-machine interactions, has received relatively little attention. This paper suggests a robust and hardware-friendly foreground detection algorithm which has been implemented as a hardware system by using an FPGA, a high-frame-rate camera, and a PC. We show that the hardware implementation utilizes less hardware resources and achieves real-time processing speed of 784 FPS with the delay less than 1 ms/frame in the image processing core. This work is a pioneering attempt of ultra-high-speed foreground detection, which will significatively speed up the wide applications of ultra-high-speed human machine interactions. [ABSTRACT FROM AUTHOR]

This paper analyzes the end-to-end delay performance in an edge-computing scenario where a set of Internet of Things devices (IoTDs) access the computation facilities of an Edge Node by means of a 5G based network. In particular, the paper deals with a two power levels slotted Aloha non-orthogonal-multiple-access (NOMA) scheme and formulates a stochastic end-to-end delay bound, in terms of complementary cumulative probability distribution, by resorting to the application of the martingale theory. In order to validate the proposed analysis, the paper proposes comparisons between the achieved analytical predictions and actual values derived by resorting to extensive computer simulations. Furthermore, the well known Boole bound has been formulated and compared with the proposed Martingale approach to highlight the better behavior of the proposed solution. [ABSTRACT FROM AUTHOR]

With the rapid growth of renewable energy and power electronic loads, voltage source converters (VSCs) have been commonly applied in different VSCs-based power systems, which also bring in stability issues due to their power electronic characteristics. The impedance-based stability theory and corresponding reshaping method can be used to analyze and solve system stability issue. However, dc stability issue in VSCs-based power systems becomes more complicated when considering ac/dc coupling relationship. This paper proposes an improved reshaping control strategy based on the detailed impedance model considering grid impedance and control delay. The influence of grid impedance, control delay and control parameters of VSC on dc stability are further analyzed to identify the cause of potential resonance risk. The proposed impedance reshaping method considers the trade-off between stability improvement and control performance, and compensates the impacts of grid impedance and control delay at the same time. The validity of stability analysis and reshaping method is further verified through the simulation and experimental results. [ABSTRACT FROM AUTHOR]

This paper considers the sample-data-based consensus problem of multiagent systems with time-varying delay and packet losses. To distinguish the time delays caused by network-induced time-delay and packet losses, the switched system is utilized. A lower gain controller is designed based on the solution of a parametric algebraic Riccati equation. The Lyapunov stability theory is utilized to obtain the limitations on the frequency and the duration of packet losses which guarantees the consensus of multiagent systems. On the other hand, we theoretically prove that refined time-delay function can reduce the conservatism. A simulation example is given to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper deals with stabilization of an ideal transformer model (ITM) circuit, used as an interfacing algorithm for hardware-in-the-loop simulations. The ITM allows for the distribution of simulation model computations over multiple processors or can be used in power hardware-in-the-loop simulations. When specific impedance conditions of the partitioned circuit are not met, this interfacing algorithm becomes unstable. This paper first presents a new theoretical approach for representing the ITM interfacing algorithm that is based on delay differential equations. With a stability analysis of the obtained time-delay system, a stabilization method is proposed, which increases the stability boundaries of the ITM algorithm. Simulation examples, including the scenario of a two-level inverter system, are provided. [ABSTRACT FROM AUTHOR]

It is vital to have an exclusive modification in semiconductor production process because of meeting differentiated customer demands in dynamic and competitive global minuscule semiconductor technology market and the highly complex fabrication process. In this paper, we propose a control system based on the dynamic mixed-effect least-square support vector regression (LS-SVR) control system for overlay error compensation with stochastic metrology delay to minimize the misalignment of the patterning process. Moreover, for the stability of the control system in the presence of metrology delay and to deal with nonlinearity among the overlay factors, the novel Lyapunov-based kernel function is merged with the LS-SVR controller. The proposed controller’s operation has been validated and implemented by a major semiconductor manufacturer in Taiwan. The experiments are verified that mixed-effect LS-SVR controller has the higher validity and higher efficiency in comparison with the exponentially weighted moving average (EWMA) and threaded EWMA controllers which had been previously implemented at the company or applied in similar studies. Note to Practitioners—Due to high production complexity in semiconductor manufacturing process, a meticulous and intelligent process control is needed to achieve higher throughput and customer satisfaction. Monitoring a complex system is challenging because the process components and variables operate autonomously and interoperate with other manufacturing segments. This paper proposes a novel run-to-run (R2R) control system to compensate the overlay error during the photolithography process that efficiently deals with the high-mixed manufacturing environment and metrology delay. [ABSTRACT FROM AUTHOR]

For the first time, considering the architecture of monolithic 3-D integration, we evaluate and benchmark the performance of 3-D logic circuits and stability/performance of 3-D 6T SRAM cells with monolayer and few-layer transition metal dichalcogenide (TMD) devices based on ITRS 2028 (5.9 nm) technology node. The impact of random variations on the cell stability is also investigated. With the possibility of adopting monolayer or few-layer TMDs for nFET- and pFET-tiers enabled by monolithic 3-D integration, this paper indicates that the trilayer TMD device may substantially degrade the performance of 3-D logic circuits in spite of its higher mobility. This paper also reveals that stacking the monolayer pFET-tier over the bilayer nFET-tier may provide better nominal stability and read/write performance for 6T superthreshold SRAM compared with the planar technology, whereas the optimum 3-D configuration for near-/sub-threshold operations appears to be the monolayer pFET-tier over the monolayer nFET-tier. Besides the 6T cell structure, 8T SRAM cells are also investigated with monolithic 3-D integration for near-threshold/subthreshold operation. The monolayer nFET-tier over the bilayer pFET-tier configuration is shown to be the optimum 3-D 8T near-threshold/subthreshold cell design. [ABSTRACT FROM AUTHOR]

Polarization and depolarization current measurements are promising on-site, off-line, non-destructive, non-invasive diagnostic tool for condition assessment of paper-oil insulation of transformers. Interpretation of the results of polarization and depolarization current is complex and hence not practiced as a routine diagnostic method for condition monitoring of transformers. This paper discusses various factors affecting polarization and depolarization current measurements with a deeper insight into the theoretical and practical aspects of this technique. Some of the concerns of PDC measurement are explained with support from simulation and experimental studies on paper oil insulation of a laboratory model transformer. Few case studies are discussed to highlight the difficulties in interpretation of results. [ABSTRACT FROM AUTHOR]

This paper analyzes the literature to identify ideas which may be applied to decentralized realtime railway traffic management. This system represents a new way for dealing with railway traffic perturbations in absence of a central decision maker. Specifically, we are interested in identifying techniques that may constitute suitable automatic mechanisms for the emergence of an effective system behavior. In this literature review, we discuss the possibility of exploiting the existing research works on other transport modes. The analysis of these works makes it clear that real-time railway traffic management is very peculiar. Hence, we consider different approaches: hierarchical self-organization, task allocation, reinforcement learning, consensus, auction and coopetition techniques. Some promising possibilities emerge, which we analyze proposing ideas for modeling decentralized real-time railway traffic management. [ABSTRACT FROM AUTHOR]

Wireless channel characterization and modeling is the foundation of vehicular communication systems. However, most of the existing researches on vehicle-to-vehicle (V2V) channel are aimed at the traditional scenarios such as urban and suburban, and the researches on some complicated vehicular scenarios are insufficient. For example, little attention is paid to viaduct, tunnel, and cutting scenarios in vehicular communications, and these complex scenarios often become the high-incidence area of communication interruption, and then affect the overall performance of the vehicular communication system due to the bad and unique channel characteristics. In this paper, to fill this gap, time-varying characteristics of V2V channels in viaduct, tunnel, and cutting scenarios are investigated. Specifically, based on 5.9 GHz channel measurements, channel non-stationarity is quantitatively evaluated and compared. Further, a detailed analysis of time-varying power and delay of multipath components (MPCs) is presented. Based on the obtained results, the mechanism of physical environment affecting channel characteristics is analyzed, and the impacts of vehicular scenarios are quantified. Besides, the impacts of scenarios on the spatial distribution of MPCs are investigated. The angular distributions of MPCs in the three typical V2V scenarios are revealed, and the corresponding statistical characteristics are presented. Moreover, the characteristics of MPC clusters in different scenarios are further quantified and analyzed, such as MPC number in each cluster and cluster lifetime. It is revealed that the non-stationarity of the V2V channel originates from the birth-death process of MPC clusters, and the birth-death process is modeled statistically. The results in the paper show the V2V channel propagation mechanism and can be used for the design of vehicular communication systems in complicated scenarios. [ABSTRACT FROM AUTHOR]

This paper proposes on-driving experience sharing algorithms at junctions in infrastructure-assisted vehicles-to-everything networks. For the purpose, a millimeter-wave (mmWave) technology is used because it provides multi-Gbps data rates which is helpful for handling users’ short stay times at junctions and spatial reuse due to high beam directionality which is helpful for interference-avoidance among densely deployed vehicles at junctions. To realize on-driving experience sharing, the proposed algorithms focus on joint resource allocation and scheduling for 3GPP-compliant multiple unicast vehicle-to-vehicle (V2V) communications where the vehicles are group leaders (GLs) in 3GPP Mode 4(d). The resource allocation stands for the roadside unit (RSU) allocation to scheduled V2V GL links where RSU is essentially required for overcoming blockage by establishing two-hop relaying. Because vehicles stay for short times at junctions, this paper designs two algorithms without or with delay considerations. Without delay considerations, the joint optimization of RSU allocation and scheduling was originally formulated as mixed 0-1 non-convex optimization. However our proposed algorithm reformulates the problem into mixed 0-1 convex optimization, which is computationally easier to solve. With delay considerations, our proposed algorithm dynamically controls video contents frame rates for time-average on-driving video sharing quality maximization subject to delay constraints, inspired by Lyapunov optimization. Extensive simulation results demonstrate that our algorithms can significantly outperform in a variety of scenarios. Furthermore, we conduct the cost analysis for the proposed algorithms in terms of capital expenditure (CAPEX) and operating expenditure (OPEX). [ABSTRACT FROM AUTHOR]

The age of information (AoI) is a key performance metric for data freshness in real-time systems, measuring the time elapsed between status updates received at a remote destination. This paper addresses the analysis of both the AoI and the delay for a system demanding timely status updates, consisting of an internet of things (IoT) community, and a multi-core edge computing node (EN). The IoT devices perform channel contention according to a slotted aloha non-orthogonal multiple access scheme with two transmission power levels to access the EN. The objective of the paper is the dynamic selection of both the EN computation capabilities and the suitable access probability for the two power levels, aiming at maximizing the time-average system utility, while guaranteeing the queues stability. The device end-to-end delay is analyzed by resorting to the martingale theoretical approximation under the condition that the Lyapunov optimization framework is performed on a time slot basis, hence leading to a novel instantaneous mixed integer problem formulation. Furthermore, the generalized benders decomposition method is employed to provide a suboptimal solution for the formulated problem. Finally, the accuracy of the proposed framework is validated by comparing the obtained analytical predictions with simulation results. [ABSTRACT FROM AUTHOR]

In recent years, the rapid growth of traffic has become a serious problem of mobile network operators. For effectively mitigating this traffic explosion problem, there have been many efforts to research on offloading the traffic from cellular links to direct communications among users. In this paper, we are motivated by users’ sharing activities, and hence propose the framework of Traffic Offloading assisted by Social network services (SNS) via opportunistic Sharing in mobile social networks (MSNs), TOSS, to offload SNS-based cellular traffic by user-to-user sharing. First, a subset of users who are to receive the same content was selected as initial population depending on their content spreading impacts in the online SNSs and their mobility patterns in the offline MSNs. Then users move, encounter and share the content via opportunistic local connectivity with each other, the content via opportunistic local connectivity with each other, e.g., Bluetooth, Wi-Fi Direct, Device-to-Device in LTE. Individual users have distinct access patterns, which potentially allow TOSS to exploit the user-dependent access delay between the content generation time and each user’s access time for content sharing purposes. The traffic offloading and content spreading among users are analyzed by taking into account various options in linking SNS and MSN traces. Four mobility traces and online SNS trace for evaluation are analyzed. An extended evaluation over a large-scale data set are further carried out, and the effectiveness of TOSS is further proved. [ABSTRACT FROM AUTHOR]