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In competitive electricity markets, prices are determined by the collective behaviour of suppliers and consumers. Hence, these systems rely on the balance between supply and demand, and sudden changes in the underlying conditions can lead to significant price fluctuations. In the face of the recent transformations in Italian electricity markets, which are driven by an increasing share of non-programmable renewables, energy crises, and geopolitical tensions, our study focuses on effective forecasting methodologies. We compare kernel and linear regression for predicting market equilibrium prices, both in point and probabilistic sense. We showcase the potential of both linear and non-linear models when carefully engineering the problem of interest, which involves properly selecting data and variables. The noteworthy outcome is that, while linear and non-linear models may differ in nature, their performance converges closely, attesting to the robustness of our approach in achieving reliable forecasts. We describe data sources and assumptions in exploratory univariate analyses, and the performance of the final multivariate model is evaluated over a test period on September 2023.

The frequency of drought events has increased with climate change, making it vital to monitor and predict the response to drought. In particular, the relationship among meteorological, agricultural, and groundwater droughts needs to be characterized under different drought conditions. In this study, a probabilistic framework was developed for analyzing the spatio-temporal propagation of droughts and applied to South Korea. Three drought indices were calculated using satellite data and a deep learning model to determine the spatial and temporal extents of drought. The average propagation times were calculated. The time from meteorological to agricultural drought (MD-to-AD) was 2.83 months, and that from meteorological to groundwater drought (MD-to-GD) was 4.34 months. Next, the joint distribution among three drought types based on the best-fit copula functions was constructed. The conditional probabilities of drought occurrence were calculated on temporal and spatial scales. For instance, the probabilities of MD-to-GD propagation under light, moderate, severe, and extreme meteorological drought conditions were 38%, 43%, 48%, and 53%, respectively. The propagated drought occurrence probability was confirmed to be the highest under extreme antecedent drought conditions. The results of this study provide insight into the spatio-temporal drought propagation process from a probabilistic viewpoint. The use of satellite data and a deep learning model is expected to increase the efficiency of drought management practices such as vulnerability assessment and early warning system development.

Although the GPS-based positioning is ubiquitous for its high precision, the high power consumption brought by the high sampling frequency and the poor GPS signal penetration limits its availability in locating low-power mobile devices (especially mobile phones). As a promising complement, the cellular-based positioning has attracted great attention since it consumes much less power as well as its higher availability. However, the sparsity of cellular-based data (due to lower sampling rate) and large localization errors make the measurement accuracy becomes the main challenge of the cellular-based positioning. hidden Markov model can well solve the problem of positioning error of GPS data, but it is less accurate when applied to map matching of cellular-base data. Therefore, to improve accuracy, in this article, we propose a novel algorithm called the tailored hidden Markov model (THMM) that is optimized for the cellular-based data. Specifically, the geometric, the topological, and the probabilistic characteristics have been considered and fully exploited in the THMM design. Our proposed schemes are evaluated using real-world motor vehicle movement trajectories collected in Tianjin and the experimental results are encouraging compared with the state-of-the-art algorithms. [ABSTRACT FROM AUTHOR]

Covert communications is critical in many application scenarios for ensuring transmission security and privacy. Two-way protocols are widely adopted in intelligent reflecting surface (IRS) assisted relaying networks to enable covert communications and prevent wireless signals from being overheard. To quantify the performance of covert communications in this special scenario, we derive the closed-form expression of outage probability and its asymptote in this paper. Considering the worst-case of covert communications, the optimal normalized power threshold of warden's detector is analyzed under a complex Gaussian distribution approximation. To meet the requirement of the detection error probability, the ratio of the transmission power between the covert nodes is investigated. Simulation results are provided to validate the theoretical expressions as well as the asymptotic analysis with a small number of reflecting elements. [ABSTRACT FROM AUTHOR]

In this work, we consider a hybrid aerial full-duplex (FD) relaying protocol consisting of a reconfigurable intelligent surface (RIS) mounted over an FD unmanned aerial vehicle (UAV) relay operating in the decode and forward mode to assist the information transfer between the base station and multiple users. For better spectral efficiency, we investigate the use of non-orthogonal multiple access (NOMA) in such networks and focus on both the performance analysis and design optimization of the considered RIS-NOMA network under imperfect channel state information (CSI) and successive interference cancellation (SIC) at each user, and residual-self interference (RSI) at UAV. We first formulate the sum rate maximization problem and adopt the block coordinate descent method to deal with the non-convex nature of the problem. Thereafter, we propose an algorithm based on the Riemannian conjugate gradient method to get the optimal phase shifts at the RIS, an iterative algorithm to obtain the optimal UAV/RIS position and the exhaustive method to obtain the optimum power allocation coefficients. Next, with obtained optimal position, phase shift and power coefficients, we further analyze the performance of the network and derive the closed-form expressions of outage probability, achievable throughput and ergodic capacity. We present Monte Carlo simulation-based results to validate the accuracy of the proposed algorithms and derived expressions and demonstrate the superiority of NOMA over OMA. [ABSTRACT FROM AUTHOR]

This paper studies the unmanned aerial vehicle (UAV) based multiple intelligent reflecting surface (IRS) network, where the hovering UAV acts as a base station, and the IRS enhances signal transmission to across obstacle between users and UAV. To achieve the maximum sum rate of proposed communication scenario, a non-convex problem considering IRS association results, hovering altitude of UAV, and the phase shift design of multi-IRS is formulated. From the IRS association problem, we can find that the IRS association results are coupled to the decoding order of non-orthogonal multiple access (NOMA). To tackle this, a mathematical interference expansion scheme is developed to decouple it and transform it to convex by binary relaxation method. The non-convexity of hovering altitude optimization problem is solved by logarithm operation, approximation, and auxiliary matrices. For the phase shift optimization problem of multi-IRS, we propose a gradient approximation based initial scheme and develop a univariate optimization based approach on the basis to achieve the users sum rate improvement in multi-IRS. In the end, we compare the proposed scheme with baseline scheme to present the superiority of this work under various network settings. The internal reasons for the variation of simulation results are also analyzed. [ABSTRACT FROM AUTHOR]

The relay positions or hop distances in a multi-hop relaying scheme is an important parameter that can be optimized in order to mitigate the angle-of-arrival variance or pointing error in a free-space optical (FSO) backhaul link. In this study, we have optimized the relay positions for amplify-and-forward and decode-and-forward relays in a multi-hop unmanned aerial vehicle-based relaying scheme for FSO. Particularly, we have shown that a significant performance improvement may be achieved by optimizing the outage probability as a function of the hop distance for amplify-and-forward relays when the relays are constrained by a finite power gain. Additionally, we have discovered that for a low signal-to-noise ratio channel, the optimal hop distance of a particular hop for decode-and-forward relays is inversely proportional to angle-of-arrival variance in that hop. [ABSTRACT FROM AUTHOR]

This article addresses the problem of threshold region characterization of the maximum likelihood (ML) sinusoid frequency estimation. We first study on the exact analytical expression of the probability of detection for the ML mean square error for all the signal-to-noise ranges. Then, we propose a simple asymptotic expression to this ML detection probability and propose a model for the characterization of the variance of the frequency estimation. We also provide asymptotic closed-form expressions to the threshold and the no-information signal-to-noise ratio breakdowns for the ML frequency estimation, respectively. Outcomes of extensive numerical simulations verify our proposed theoretical derivations. [ABSTRACT FROM AUTHOR]

With the explosion of GPS-enabled smartphones and social media platforms, geo-social networks are increasing as tools for businesses to promote their products or services. Influence maximization, which aims to maximize the expected spread of influence in the networks, has drawn increasing attention. However, most recent work tries to study influence maximization by only considering geographic distance, while ignoring the influence of users’ spatio-temporal behavior on information propagation or location promotion, which can often lead to poor results. To relieve this problem, we propose a Similarity-aware Influence Maximization (SIM) model to efficiently maximize the influence spread by taking the effect of users’ spatio-temporal behavior into account, which is more reasonable to describe the real information propagation. We first calculate the similarity between users according to their historical check-ins, and then we propose a Propagation to Consumption (PTC) model to capture both online and offline behaviors of users. Finally, we propose two greedy algorithms to efficiently maximize the influence spread. The extensive experiments over real datasets demonstrate the efficiency and effectiveness of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Faced with massive data, subsampling is a commonly used technique to improve computational efficiency, and using nonuniform subsampling probabilities is an effective approach to improve estimation efficiency. For computational efficiency, subsampling is often implemented with replacement or through Poisson subsampling. However, no rigorous investigation has been performed to study the difference between the two subsampling procedures such as their estimation efficiency and computational convenience. This paper performs a comparative study on these two different sampling procedures. In the context of maximizing a general target function, we first derive asymptotic distributions for estimators obtained from the two sampling procedures. The results show that the Poisson subsampling may have a higher estimation efficiency. Based on the asymptotic distributions for both subsampling with replacement and Poisson subsampling, we derive optimal subsampling probabilities that minimize the variance functions of the subsampling estimators. These subsampling probabilities further reveal the similarities and differences between subsampling with replacement and Poisson subsampling. The theoretical characterizations and comparisons on the two subsampling procedures provide guidance to select a more appropriate subsampling approach in practice. Furthermore, practically implementable algorithms are proposed based on the optimal structural results, which are evaluated through both theoretical and empirical analyses. [ABSTRACT FROM AUTHOR]

Unmanned-aerial-vehicle (UAV)-based communications are expected to play an important role in the future generation wireless communication networks. It is a promising solution to enhance the wireless connectivity of devices without infrastructure. As compared to the terrestrial communications, UAVs offer various advantages such as line-of-sight (LoS) connectivity, dynamic deployment and flexible reconfiguration. Further, free space optics (FSO) communication is considered as a possible solution to enable UAV-based communication links due to its cost effective and high bandwidth nature. However, despite offering large bandwidth, UAV-based FSO links are marred by atmospheric path loss, atmospheric turbulence, non-zero boresight pointing errors, and angle-of-arrival (AoA) fluctuations. In this paper, the performance of a hovering UAV-based FSO communication system is investigated. The closed-form expressions for outage probability, average symbol error rate (SER), and ergodic capacity are derived taking into account both heterodyne (HD) and direct detection (DD) techniques for ground-to-UAV (G2U), UAV-to-UAV (U2U), and UAV-to-ground (U2G) links over the generalized Málaga distribution. Moreover, the asymptotic expressions for the above performance metrics are also derived to get the diversity gain of the system. [ABSTRACT FROM AUTHOR]

In this paper, we model the multi-layer vertical underwater link as a cascaded channel and unify the performance analysis for the underwater optical communication (UWOC) system using generalized Gamma (GG), exponential GG (EGG), exponentiated Weibull (EW), and Gamma-Gamma ($\Gamma \Gamma$) oceanic turbulence models. We derive unified analytical expressions for probability density function (PDF) and cumulative distribution function (CDF) for the signal-to-noise ratios (SNR) considering independent and non-identical (i.ni.d.) turbulent models and zero bore-sight model for pointing errors. We develop performance metrics of the considered UWOC system using outage probability, average bit error rate (BER), and ergodic capacity with asymptotic expressions for outage probability and average BER. We develop the diversity order of the proposed system to provide a better insight into the system performance at a high SNR. We also integrate a terrestrial OWC (TOWC) subjected to the combined effect of generalized Malága atmospheric turbulence, fog-induced random path gain, and pointing errors to communicate with the UWOC link using the fixed-gain amplify-and-forward (AF) relaying. We analyze the performance of the mixed TWOC and multi-layer UWOC system by deriving PDF, CDF, outage probability, and average BER using the bivariate Fox H-function. We use Monte-Carlo simulation results to validate our exact and asymptotic expressions and demonstrate the performance of the considered underwater UWOC system using measurement-based parametric data available for turbulent oceanic channels. [ABSTRACT FROM AUTHOR]

Process mining is the discipline of analyzing and improving processes which are known as an event log. The real-life event log contains noise, infrequent behaviors, and numerous concurrency, in effect the generated process model through process discovery algorithms will be inefficient and complex. Shortcomings in an event log result in current process discovery algorithms failing to pre-process data and describe real-life phenomena. Existing process mining algorithms are limited based on the algorithm’s filtering, parameters, and pre-defined features. It is critical to use a high-quality event log to generate a robust process model. However, pre-processing of the event log is mostly cumbersome and is a challenging procedure. In this paper, we propose a novel pre-processing step aimed to obtain superior quality event log from a set of raw data, consequently a better performing process model. The proposed approach concatenates events which hold concurrent relations based on a probability algorithm, producing simpler and accurate process models. This proposed pre-processing step is based on the probability of the frequency of concurrent events. The performance of the pre-processing approach is evaluated on 18 real-life benchmark datasets that are publicly available. We show that the proposed pre-processing framework significantly reduces the complexity of the process model and improves the model’s F-Measure.

As an efficient and interference-resistant coding technique, multiple description coding (MDC) is proposed with the aim to solve the transmission unreliability problem caused by packet errors, loss or blocking delays. The integration of MDC with non-orthogonal multiple access (NOMA) scheme (MDC-NOMA) can effectively boost the robustness and throughput of the underlying system. Additionally, space-time block coding (STBC) can further enhance the system reliability with increased diversity gain, as well as reduced decoding complexity. In this paper, we propose a novel framework referred to as MDC-NOMA-STBC, in which we apply Alamouti STBC integrated with MDC and NOMA to implement more reliable transmission. Specifically, NOMA signals are constructed by superimposing the descriptions from different users, then transmitted by the base station (BS) using Alamouti STBC. In order to substantiate the performance of the proposed framework, first, we derive closed-form expressions of both the outage probability and ergodic rate for each user in a two-antenna BS scenario. Second, for multi-antenna BS, we investigate different antenna selection strategies to further enhance the outage performance under the considered framework, whose analytical expression is provided wherever possible. Third, Monte Carlo simulation results are presented to validate our theoretical framework and to corroborate the superiority of the proposed MDC-NOMA-STBC over state-of-the-art MDC-NOMA scheme. Moreover, under realistic contexts with image transmission, it is confirmed that MDC-NOMA-STBC outperforms its counterpart MDC-NOMA in terms of the peak signal-to-noise ratio and the bit error rate. [ABSTRACT FROM AUTHOR]

We consider multiple unmanned aerial vehicles (UAVs) serving a density of ground terminals (GTs) as base stations. The objective is to minimize the outage probability of GT-to-UAV transmissions. Optimal placement of UAVs under different UAV altitude constraints and GT densities is studied. A practical variant of the Rician fading model, which has been developed by Azari et al. (2018) specifically for UAV systems, is used to model the communication channels. First, the structure of optimal deployments is determined when the common altitude constraint is large. For a wide class of GT densities, it is shown that all UAVs should be placed to the same location in an optimal deployment. A design implication is that one can use a single multi-antenna UAV as opposed to multiple single-antenna UAVs without loss of optimality. Next, using a random deployment argument, a general upper bound on the optimal outage probability is found for any density of GTs and any number of UAVs. Further, for any arbitrary user density, centralized and distributed numerical algorithms are designed using particle swarm optimization and modified gradient descent algorithms, respectively. Simulations show that our distributed algorithm provides almost optimal results even with considerably reduced communication and sensing ranges at the UAVs. [ABSTRACT FROM AUTHOR]

This article establishes an analytical framework for the upper bound on the average Age-of-Information (AoI) in first-come-first-served (FCFS) wireless communications where a certain level of outage probability is unavoidable. To begin with, we analyze the average AoI and derive a general upper bound for G/G/1 systems with a certain outage probability. Subsequently, for an M/M/1 system with the FCFS scheme, we obtain a concise closed-form expression of the upper bound, and further refine the upper bound after analyzing the relative error. Interestingly, it is found by the analysis that the relative error is independent of the service rate, and the upper bound becomes tighter as the outage probability increases. Based on the refined upper bound, we minimize the average AoI for the communications suffering from block Rayleigh fading. We derive a closed-form expression of the outage probability over a fading channel, and then prove that the refined upper bound is a convex function with respect to the average update generating rate. Consequently, we optimize the AoI performance by solving a convex optimization problem formulated utilizing the refined upper bound expression. The numerical results indicate that the minimum average AoI can be reduced by either increasing the service rate or the transmission power. [ABSTRACT FROM AUTHOR]

In this paper, we propose a robust secrecy transmission scheme for intelligent reflecting surface (IRS) aided communication systems. Different from all the existing works where IRS has already been deployed at a fixed location, we take the location of IRS as a variable to maximize the secrecy rate (SR) under the outage probability constraint by jointly optimizing the location of IRS, transmit beamformer and IRS phase shifts with imperfect channel state information (CSI) of Eve, where we consider two cases: a) the location of Eve is known; b) only a suspicious area of Eve is available. We show a critical observation that CSI models are different before and after IRS deployment, thus the optimization problem could be decomposed and solved via a two-stage framework. For case a), in the first stage, universal upper bounds of outage probabilities only related to the location of IRS are derived which can be optimized via successive convex approximation (SCA) method. In the second stage, we develop an alternative optimization (AO) algorithm to optimize beamformer and phase shifts iteratively. For case b), we propose a Max-Min SR scheme based on two-stage framework, where the location of IRS is optimized based on the worst location of Eve. Simulation results indicate the importance of the location of IRS optimization. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the physical layer security for a cognitive multiuser network which is composed of multiple cognitive sources, a cognitive destination and an eavesdropper under the joint impact of hardware impairments (HIs) and channel estimation errors (CEEs). We consider a practical scenario where mutual interference exists between the primary users and cognitive users. To achieve high physical layer security with low implementation complexity, we propose three pure user scheduling schemes, namely, selection combining (SC) scheme, threshold-based switched diversity (tSD) scheme and switch-and-examine combining with post-selection (SECps) scheme. To further improve physical layer security, we present an extension of our SC framework to a jammer aided multiuser network and propose a jammer aided SC (JSC) scheme. We derive the closed-form intercept probability (IP), outage probability (OP) and effective secrecy throughput (EST) expressions for SC, tSD, SECps and JSC schemes over Nakagami- $m$ channels to analyze the system performance. Numerical results show that among the three pure multiuser scheduling schemes, the SC scheme achieves the best secrecy performance with the highest complexity, the SECps scheme obtains the worst secrecy performance with the lowest complexity. In addition, the secrecy performance of JSC scheme is better than that of SC scheme in the high SNR region. [ABSTRACT FROM AUTHOR]

The reconfigurable intelligent surface (RIS) is a promising technology that is anticipated to enable high spectrum and energy efficiencies in future wireless communication networks. This paper investigates optimum location-based RIS selection policies in RIS-aided wireless networks to maximize the end-to-end signal-to-noise ratio for product-scaling and sum-scaling path-loss models where the received power scales with the product and sum of the transmitter-to-RIS and RIS-to-receiver distances, respectively. These scaling laws cover the important cases of end-to-end path-loss models in RIS-aided wireless systems. The random locations of all available RISs are modeled as a Poisson point process. To quantify the network performance, the outage probabilities and average rates attained by the proposed RIS selection policies are evaluated by deriving the distance distribution of the chosen RIS node as per the selection policies for both product-scaling and sum-scaling path-loss models. We also propose a limited-feedback RIS selection framework to achieve distributed network operation. The outage probabilities and average rates obtained by the limited-feedback RIS selection policies are derived for both path-loss models as well. The numerical results show notable performance gains obtained by the proposed RIS selection policies. [ABSTRACT FROM AUTHOR]

The combination of reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) has been recognized as a critical method to improve the sixth generation networks performance. In this paper, a distributed RIS-aided downlink multiple-input multiple-output (MIMO) NOMA systems with discrete phase shifts are studied, where the channel directions from base station to paired users can be manipulated with the assistance of RISs by employing the concept of signal alignment. In order to ensure base station can flexibly serve some users with NOMA and others users with spatial division multiple access, a unified precoder and decoder are provide to cancel inter-cluster interference. Subsequently, the channel statistics over Nakagami- $m$ fading channels are derived for near and far users. In particular, considering the cascade channel gain may exists two different cases, Beaulieu series is further adopted to characterize their corresponding cumulative distribution function. In what follows, the outage probability and ergodic rate for three situations within one cluster are derived by utilizing the obtained channel statistics, respectively. Based on the derived results, we also analyze the diversity order and high signal-to-noise ratio slope to provide essential insights into the considered systems. Finally, simulation results are presented to reveal that: 1) selecting the setting of 3-bits resolution can realize a near-aligned performance for our proposed systems; 2) the cascade channel statistic caused by RIS can be evaluated with any number of RIS element and any channel gain via Beaulieu series. [ABSTRACT FROM AUTHOR]

In the past few years, many companies are considering “social recommendation” for their businesses, e.g., firms are offering rewards to customers who recommend the firms’ products/services in online social networks (OSNs). However, the pros and cons of such social recommendation scheme are still unclear. Thus, it is difficult for firms to design rewarding schemes, and for OSN platforms to design regulating policies. By analyzing real data from Weixin and Yelp, we first identify key factors that affect the spreading of products/services in OSNs. These findings enable us to develop an accurate (i.e., with a high validation accuracy) mathematical model on social recommendations. Our model captures how users decide whether to recommend an item, which is a key factor but often ignored by previous social recommendation models such as the “Independent Cascade model”. We also design algorithms to infer model parameters. Using our model, we uncover conditions when social recommendation improves a firm’s profit and users’ utilities, as well as when it cannot improve the profit or hurts users’ utilities. These conditions help the design of both rewarding schemes and regulating policies. Moreover, we extend our model to a dynamic setting, so that a firm can improve its profit by dynamically optimizing its rewarding schemes. [ABSTRACT FROM AUTHOR]

In ICISC-05, and in the ePrint 2010/287, Patarin claimed a lower bound on the number of $2 q$ tuples of $n$ -bit strings $(P_{1}, \ldots, P_{2q}) \in ({\{0,1\}}^{n})^{2q}$ satisfying $P_{2i - 1} \oplus P_{2i} = \lambda _{i}$ for $1 \leq i \leq q$ such that $P_{1}, P_{2}, \ldots $ , $P_{2q}$ are distinct and $\lambda _{i} \in {\{0,1\}} ^{n} \setminus \{0^{n}\}$. This result is known as Mirror theory and widely used in cryptography. It stands as a powerful tool to provide a high-security guarantee for many block cipher-(or even ideal permutation-) based designs. In particular, Mirror theory has a direct application in the security of XOR of block ciphers. Unfortunately, the proof of Mirror theory contains some unverifiable gaps and several mistakes. This paper provides a simple and verifiable proof of Mirror theory. [ABSTRACT FROM AUTHOR]

This article introduces a probabilistic machine learning framework for the uncertainty quantification (UQ) of electronic circuits based on the Gaussian process regression (GPR). As opposed to classical surrogate modeling techniques, GPR inherently provides information on the model uncertainty. The main contribution of this work is twofold. First, it describes how, in a UQ scenario, the model uncertainty can be combined with the uncertainty of the input design parameters to provide confidence bounds for the statistical estimates of the system outputs, such as moments and probability distributions. These confidence bounds allow assessing the accuracy of the predicted statistics. Second, in order to deal with dynamic multioutput systems, principal component analysis (PCA) is effectively employed to compress the time-dependent output variables into a smaller set of components, for which the training of individual GPR models becomes feasible. The uncertainty on the principal components is then propagated back to the original output variables. Several application examples, ranging from a trivial RLC circuit to real-life designs, are used to illustrate and validate the advocated approach. [ABSTRACT FROM AUTHOR]

In this paper, we study the physical-layer security of a hybrid satellite-terrestrial network composed of a satellite, multiple terrestrial decode-and-forward (DF) relays and users in the presence of a terrestrial eavesdropper who attempts to tap legitimate information from both satellite and relays. We consider two different scenarios: I) the channel state information (CSI) of wiretap links is known, and II) the CSI of wiretap links is unknown. Accordingly, optimal and suboptimal relay-user pairing schemes are proposed for the aforementioned two scenarios, respectively. Specifically, a relay-user pair maximizing the secrecy rate is chosen as the optimal one to participate in the transmission, where all links’ CSI is used to perform relay-user pairing. However, suboptimal relay-user pairing scheme is designed only relying on the main links’ CSI without requiring wiretap links’ CSI, where a relay-user pair with the maximal transmission rate of main link is selected. Also, closed-form expressions of secrecy outage probability with both integer and rational fading severity parameter are derived in the case of satellite links undergo Shadowed-Rician fading and terrestrial links subject to Rayleigh fading. Furthermore, asymptotic secrecy outage probability analysis is conducted in the high signal-to-noise ratio region. Numerical results reveal that relay-user pairing is beneficial to further improve physical-layer security of the hybrid satellite-terrestrial network. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of an intelligent reflective surface (IRS) assisted non-orthogonal multiple access (NOMA) system, where the IRS is mounted on an unmanned aerial vehicle (UAV) to assist the transmissions from a base station (BS). The BS utilizes the UAV as a relay to serve multiple user equipments (UEs) on the ground. In addition to the IRS relaying links, we also incorporate direct non line-of-sight links between the BS and UEs. We derive the outage probability for this system configuration. Moreover, we obtain a bound of the ergodic spectral efficiency to extract various useful insights. Furthermore, we also compare the performance of the proposed system design against the baseline scheme. Finally, we present numerical results to highlight the benefits of the proposed IRS-aided UAV relaying system and the accuracy of the derived analytical results. [ABSTRACT FROM AUTHOR]

We study the phase synchronization problem with noisy measurements $Y=z^{*}z^{* { \mathrm {\scriptscriptstyle H} }}+\sigma W\in \mathbb {C}^{n\times n}$ , where $z^{*}$ is an $n$ -dimensional complex unit-modulus vector and $W$ is a complex-valued Gaussian random matrix. It is assumed that each entry $Y_{jk}$ is observed with probability $p$. We prove that an SDP relaxation of the MLE achieves the error bound $(1+o(1))\frac {\sigma ^{2}}{2np}$ under a normalized squared $\ell _{2}$ loss. This result matches the minimax lower bound of the problem, and even the leading constant is sharp. The analysis of the SDP is based on an equivalent non-convex programming whose solution can be characterized as a fixed point of the generalized power iteration lifted to a higher dimensional space. This viewpoint unifies the proofs of the statistical optimality of three different methods: MLE, SDP, and generalized power method. The technique is also applied to the analysis of the SDP for $\mathbb {Z}_{2}$ synchronization, and we achieve the minimax optimal error $\exp \left ({-(1-o(1))\frac {np}{2\sigma ^{2}}}\right)$ with a sharp constant in the exponent. [ABSTRACT FROM AUTHOR]

We study the problem of off-policy evaluation in the multi-armed bandit model with bounded rewards, and develop minimax rate-optimal procedures under three settings. First, when the behavior policy is known, we show that the Switch estimator, a method that alternates between the plug-in and importance sampling estimators, is minimax rate-optimal for all sample sizes. Second, when the behavior policy is unknown, we analyze performance in terms of the competitive ratio, thereby revealing a fundamental gap between the settings of known and unknown behavior policies. When the behavior policy is unknown, any estimator must have mean-squared error larger—relative to the oracle estimator equipped with the knowledge of the behavior policy— by a multiplicative factor proportional to the support size of the target policy. Moreover, we demonstrate that the plug-in approach achieves this worst-case competitive ratio up to a logarithmic factor. Third, we initiate the study of the partial knowledge setting in which it is assumed that the minimum probability taken by the behavior policy is known. We show that the plug-in estimator is optimal for relatively large values of the minimum probability, but is sub-optimal when the minimum probability is low. In order to remedy this gap, we propose a new estimator based on approximation by Chebyshev polynomials that provably achieves the optimal estimation error. Numerical experiments on both simulated and real data corroborate our theoretical findings. [ABSTRACT FROM AUTHOR]

Line-of-sight (LoS) path is essential for the reliability of air-to-ground (A2G) communications, but the existence of the LoS path is difficult to predict due to random obstacles on the ground. Based on the statistical geographic information and Fresnel clearance zone, a general stochastic LoS probability model for 3-D A2G channels under urban scenarios is developed. By considering the factors, that is, building height distribution, building width, building space, carrier frequency, and transceiver’s heights, the proposed model is suitable for different frequencies and altitudes. Moreover, in order to get a closed-form expression and reduce the computational complexity, an approximate parametric model is also built with the machine-learning (ML) method to estimate the model parameters. The simulation results show that the proposed model has good consistency with existing models at low altitude. When the altitude increases, it has a better performance by comparing with that of the ray-tracing (RT) Monte-Carlo simulation data. The analytical results of the proposed model are helpful for the channel modeling and performance analyses such as cell coverage, outage probability, and bit error rate in A2G communications. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a mobile edge computing (MEC) network, where the user has some computational tasks to be assisted by multiple computational access points (CAPs) through offloading. We consider practical communication scenarios with limited spectrum resources, and the cochannel interference arising from the aggressive reuse of frequency severely degrades the system offloading performance. To enhance the system performance, we provide three CAP selection criteria to choose one best CAP among multiple ones. Specifically, criterion I maximizes the computational capability at the CAP, criterion II minimizes the interfering power, while criterion III maximizes the instantaneous channel gain of data link. In time-varying channel environments, the CAP selection may be outdated, which deteriorates the system performance. For the three criteria, we evaluate the system outage probability in the outdated channel state information (CSI) by taking into account the latency, energy consumption and data rate, and provide the analytical and asymptotic expressions of outage probability, from which we obtain some critical insights on the system design. Simulation results are finally demonstrated to verify the proposed studies. In particular, criterion III under the perfect CSI can achieve the system whole diversity order coming from multiple CAPs. [ABSTRACT FROM AUTHOR]

In this paper, we address the antenna selection (AS) problem in full-duplex (FD) cooperative non-orthogonal multiple access (NOMA) systems, where a multi-antenna FD relay bridges the connection between the multi-antenna base station and NOMA far user. Specifically, two AS schemes, namely max-U1 and max-U2, are proposed to maximize the end-to-end signal-to-interference-plus-noise ratio at either or both near and far users, respectively. Moreover, a two-stage AS scheme, namely quality-of-service (QoS) provisioning scheme, is designed to realize a specific rate at the far user while improving the near user’s rate. To enhance the performance of the QoS provisioning AS scheme, the idea of dynamic antenna clustering is applied at the relay to adaptively partition the relay’s antennas into transmit and receive subsets. The proposed AS schemes’ exact outage probability and achievable rate expressions are derived. To provide more insight, closed-form asymptotic outage probability expressions for the max-U1 and max-U2 AS schemes are obtained. Our results show that while the QoS provisioning AS scheme can deliver a near-optimal performance for static antenna setup at the relay, it provides up to 12% average sum rate gain over the optimum AS selection with fixed antenna setup. [ABSTRACT FROM AUTHOR]

Superdirective arrays have been extensively studied because of their considerable potential accompanied, unfortunately, by a high sensitivity to random errors that affect the responses and positions of array elements. However, the statistics of their actual beam pattern (BP) has never been systematically investigated. This paper shows that the Rician probability density function (PDF), sometimes adopted to study the impact of errors in conventional arrays, is a valid approximation for superdirective BP statistics only where some mathematical terms are negligible. The paper also shows that this is the case for all linear end-fire arrays considered. A similar study is proposed concerning the correlation between BP lobes, showing that for the superdirective arrays considered the lobes, especially non-adjacent ones, are almost independent. Furthermore, knowledge of the PDF of the actual BP allows one to define quantile BP functions, whose probability of being exceeded, at any point, is fixed. Combining the lobes’ independence with quantile BP functions, an empirical equation for the probability that the entire actual BP will not exceed a quantile function over an interval larger than a given size is obtained. This new knowledge and these tools make it possible to devise new methods to design robust superdirective arrays via optimization goals with clearer and more relevant statistical meaning. [ABSTRACT FROM AUTHOR]

In this article, we study the secrecy performance of an unmanned aerial vehicle (UAV)-assisted relay communication system, where a ground base station (GBS) intends to send confidential information to the ground legitimate user Bob with the help of a UAV relay in the presence of multiple aerial and ground eavesdroppers. We consider the height-dependent probabilistic line-of-sight and the general $\kappa$ - $\mu$ shadowed channel fading model in the system. To enhance the secrecy performance, the GBS and UAV relay apply directional beamforming transmission while implementing protection zones around their intended receiving destinations. We then derive the approximate closed-form expressions of the secrecy outage probability (SOP) under different aerial and ground eavesdropperscolluding strategies. To get insights, we also obtain the SOP expression over Rayleigh fading as a special case. After discussing the impacts of transmitting and multiple aerial and ground eavesdropping parameters on the SOP, we show that the optimal altitude of UAV relay exists with the minimal SOP value under different urban environments. We also show that UAV eavesdroppers have a larger effect on the system performance than ground eavesdroppers. [ABSTRACT FROM AUTHOR]

Change impact analysis evaluates the changes that are made in the software and finds the ripple effects, in other words, finds the affected software components. Code changes and bug fixes can have a high impact on code quality by introducing new vulnerabilities or increasing their severity. A recent high-visibility example of this is the code changes in the log4j web software CVE-2021-45105 to fix known vulnerabilities by removing and adding method called change types. This bug fix process exposed further code security concerns. In this article, we analyze the most common set of bug fix change patterns to have a better understanding of the distribution of software changes and their impact on code quality. To achieve this, we implemented a tool that compares two versions of the code and extracts the changes that have been made. Then, we investigated how these changes are related to change impact analysis. In our case study, we identified the change types for bug-inducing and bug fix changes using the Quixbugs dataset. Furthermore, we used 13 of the projects and 621 bugs from Defects4J to identify the common change types in bug fixes. Then, to find the change types that cause an impact on the software, we performed an impact analysis on a subset of projects and bugs of Defects4J. The results have shown that, on average, 90% of the bug fix change types are adding a new method declaration and changing the method body. Then, we investigated if these changes cause an impact or a ripple effect in the software by performing a Markov chain-based change impact analysis. The results show that the bug fix changes had only impact rates within a range of 0.4–5%. Furthermore, we performed a statistical correlation analysis to find if any of the bug fixes have a significant correlation with the impact of change. The results have shown that there is a negative correlation between caused impact with the change types adding new method declaration and changing method body. On the other hand, we found that there is a positive correlation between caused impact and changing the field type. [ABSTRACT FROM AUTHOR]

This paper presents a time-domain differential protection method based on the Bayes’ Theorem and on the current samples to determine the fault occurrence probability as a function of time. It also describes the theory involved in developing the proposed protection method when considering the differential protection of transmission lines. The authors performed fault simulations using an existing electrical system modeled in EMTP varying the fault type, phases involved, fault resistance, inception angle, and fault location, and carried out a sensitivity analysis regarding high impedance faults, current transformer saturation, noisy data, misalignments between terminal samples and power swings. The authors also tested the proposed method against actual fault events from four existing transmission lines of the Brazilian interconnected power system. All results indicate that the proposed solution is fast, accurate, secure, and dependable. [ABSTRACT FROM AUTHOR]

Efficient connectivity in cellular-connected unmanned aerial vehicles (UAV)s is limited by scarcity of the radio spectrum and strong inter-cell interference (ICI). To address these issues, we propose an aerial-terrestrial network non-orthogonal multiple access (ATN-NOMA) scheme. In this proposed scheme, we pair the aerial user (AU) and terrestrial user (TU) in a NOMA setting to leverage their asymmetric channel gains and rate demands in downlink communications. In ATN-NOMA, the strong ICI issue at the AU receiver is further managed by an elevation-angle based user association, equipping the AU with an adjustable beamwidth directional antenna, and forming a beamforming among the coordinated terrestrial base stations (BS)s. We then obtain the optimal beamwidth and suboptimal power allocation so that the TUs’ sum-rate is maximized subject to the AU’s Quality-of-Service (QoS) requirement. The corresponding optimization problem is non-convex in which we exploit the structure of the problem and apply successive convex approximation (SCA) to obtain a suboptimal solution. We then derive the statistical properties, which consequently enable us to estimate the aggregated ICI. In cases where no interfering BSs have the same elevation angle as the coordinated BSs, we further approximate the AU’s outage probability. We then compare the TUs’ sum-rate and the outage probability of the ATN-NOMA with multiple existing schemes. Extensive simulation results show that our proposed ATN-NOMA scheme outperforms existing schemes by 52-91% in terms of the sum-rate, and its analytical outage probability can be as low as the order of $10^{-17}$. Furthermore, we show that the pairing of AU and TU in multi-cell networks remains beneficial, subject to effective mitigation of ICI. [ABSTRACT FROM AUTHOR]

The mixture of wireless and power line communications (PLC) is vital for implementing new applications in smart grid and vehicular communications. In this work, we investigate the performance of non-orthogonal multiple access (NOMA) based dual-hop hybrid communication systems with decode-and-forward relay. The wireless channel is characterized by Nakagami-m fading under an additive white Gaussian noise (AWGN), while the PLC channels are characterized by Log-normal distribution with Bernoulli Gaussian noise including both background and impulsive noise components. New closed-form expressions for the outage probability, the asymptotic outage probability and ergodic capacity are derived and verified via extensive representative simulations. For more insights on the outage performance, we analyze the diversity order. Additionally, we proposed a power allocation optimization technique to achieve an outage-optimal performance. The results show that the system outage probability improves as the impulsive noise index and the arrival probability of the impulsive component of the PLC additive noise decrease, while their effect is negligible on the ergodic capacity. Finally, the performance of the proposed system is compared against a benchmark OMA-based system. [ABSTRACT FROM AUTHOR]

Ultra-reliable low latency communication (URLLC) requires the packet error rate to be on the order of $10^{-9}$ - $10^{-5}$. Determining the appropriate transmission rate to satisfy this ultra-reliability constraint requires deriving the statistics of the channel in the ultra-reliable region and then incorporating these statistics into the rate selection. In this paper, we propose a framework for determining the rate selection for ultra-reliable communications based on the extreme value theory (EVT). We first model the wireless channel at URLLC by estimating the parameters of the generalized Pareto distribution (GPD) best fitting to the tail distribution of the received powers, i.e., the power values below a certain threshold. Then, we determine the maximum transmission rate by incorporating the Pareto distribution into the rate selection function. Finally, we validate the selected rate by computing the resulting error probability. Based on the data collected within the engine compartment of Fiat Linea, we demonstrate the superior performance of the proposed methodology in determining the maximum transmission rate compared to the traditional extrapolation-based approaches. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is considered as a multiple access technique for supporting massive number of devices with high spectral efficiency. Simultaneous wireless information and power transfer (SWIPT) is an efficient solution for fully autonomous and sustainable communication networks. In this paper, application of SWIPT in networks employing cooperative NOMA (CNOMA) is investigated with imperfect channel state information (CSI). Performance of the CNOMA network with SWIPT is investigated in a multi-tier downlink scenario with macro-base stations (MBSs) and femto-base stations (FBSs). The distribution of MBSs and FBSs follow Poisson point process model. Unlike solution in the existing literature, instead of using only the superimposed signal for energy harvesting (EH), in this work, the cooperating node/user employs EH using interference from the adjacent base stations. Expressions for outage probability and throughput are derived at the user pair (comprising a cell-center user and a cell-edge user) served using NOMA. Comparison of the proposed EH system with the existing solutions is highlighted. Monte Carlo simulations are carried out to validate the analytical results. [ABSTRACT FROM AUTHOR]

The ecosystem of airborne platforms is maturing rapidly and becoming essential to meeting the communication requirements of modern wireless networks. In such a context, the speed, range, and quality of service are highly dependent on a timely access to the right amount and type of affordable spectrum. In this way, evaluating the statistical properties of the air-to-ground (AtG) channel in different built-up propagation environments with regard to the operating frequency is crucial for performance analysis of airborne platform-assisted communications. In this paper, we construct a framework for the line-of-sight (LoS) probability based on the intrusion ratio of obstacles within the first Fresnel zone, yielding an analytical expression for the LoS probability that is sensitive to the operating frequency, the transmitter and receiver heights, the horizontal distance between them, and three other parameters depicting the statistical properties of the urban environment. The model developed is accurate enough to capture scattering mechanisms such as reflection and diffraction, while being sufficiently flexible mathematically to allow, based for instance on powerful analytical tools such as stochastic geometry, a seamless and physically meaningful system-level performance evaluation of modern wireless networks in the presence of airborne platforms. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive framework to analyze the performance of non-orthogonal multiple access (NOMA) in the downlink transmission of a single-carrier and multi-carrier terahertz (THz) network. Specifically, we first develop a novel user pairing scheme for the THz-NOMA network which ensures the performance gains of NOMA over orthogonal multiple access (OMA) for each individual user in the NOMA pair and adapts according to the molecular absorption. Then, we characterize novel outage probability expressions considering a single-carrier and multi-carrier THz-NOMA network in the presence of various user pairing schemes, Nakagami- $m$ channel fading, and molecular absorption noise. We propose a moment-generating-function (MGF) based approach to analyze the outage probability of users in a multi-carrier THz network. Furthermore, for negligible thermal noise, we provide simplified single-integral expressions to compute the outage probability in a multi-carrier network. Numerical results demonstrate the performance of the proposed user-pairing scheme and validate the accuracy of the derived expressions. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) has emerged as an important transmission technology for numerous applications in Internet of Things (IoT) systems. Thus, in this paper, we investigate the application of RIS in energy harvesting (EH) based unmanned aerial vehicle (UAV) communication network with finite block length (BL) codes, where a rotary wing type flying UAV communicates with the multiple single antenna IoT users with the aid of multiple RISs mounted on several skyscraper buildings. To transmit the signal to a particular IoT user, the UAV selects an RIS on the basis of either UAV-RIS (i.e., partial) or UAV-RIS-IoT (i.e., full) channel state information (CSI) and then transmits the signal through the selected RIS along with the direct link transmission. In particular, we derive (i) the expression for probability of RIS selection, (ii) the statistical distribution of instantaneously received information signal-to-noise ratio (SNR) at the IoT user. Based on the derived statistics, we analyze the performance of the considered system under finite BL codes in terms of the average outage probability, average block error rate (ABLER) and goodput averaged over entire flying duration. Moreover, the BLER performance with finite BL codes is also compared with the infinite BL codes scenario. Additionally, we also investigate the impact of various channel and system parameters like imperfect CSI, number of RISs and the number of reflecting elements at each RIS, location of IoT users, variable altitude of the UAV, and the severity of channel fading of UAV-RIS link on the system performance. Furthermore, we have obtained the optimum UAV location in each time slot which minimizes the ABLER per time slot over all the users in the network. The analytical results are corroborated with Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Vehicle-to-vehicle (V2V) communications under dense urban environments usually experience severe keyhole fading effect especially for multi-input multi-output (MIMO) channels, which degrades the capacity and outage performance due to the rank deficiency. To avoid these, the integration of MIMO and hybrid automatic repeat request (HARQ) is proposed to assist V2V communications in this paper. By using the methods of integral transforms, the outage probabilities are derived in closed-form for different HARQ-assisted schemes, including Type I-HARQ, HARQ with chase combining (HARQ-CC), and HARQ with incremental redundancy (HARQ-IR). With the results, meaningful insights are gained by conducting the asymptotic outage analysis. Specifically, it is revealed that full time diversity order can be achieved, while full spatial diversity order is unreachable as compared to MIMO-HARQ systems without keyhole effect. Moreover, we prove that the asymptotic outage probability is a monotonically increasing and convex function of the transmission rate. More importantly, although HARQ-IR performs better than HARQ-CC owing to its higher coding complexity, this advantage becomes negligible in the large-scale array regime. Finally, the numerical results are verified by Monte-Carlo simulations along with some in-depth discussions. [ABSTRACT FROM AUTHOR]

In this letter, performance of a multiantenna multiuser unmanned aerial vehicle (UAV)-assisted terrestrial-satellite communication system over mixed free space optics (FSO)/radiofrequency (RF) channels is analyzed. Downlink transmission from the satellite to the UAV is completed through FSO link which follows gamma–gamma distribution with pointing error impairments. Both the heterodyne detection and intensity modulation direct detection techniques are considered at the FSO receiver. To avail the antenna diversity, multiple transmit antennas are considered at the UAV. Selective decode-and-forward scheme is assumed at the UAV and opportunistic user scheduling is performed while considering the practical constraints of outdated channel state information (CSI) during the user selection and transmission phase. The RF links are assumed to follow Nakagami-m distribution due to its versatile nature. In this context, for the performance analysis, analytical expressions of outage probability, asymptotic outage probability, ergodic capacity, effective capacity, and generalized average symbol-error-rate expressions of various quadrature amplitude modulation (QAM) schemes such as hexagonal-QAM, cross-QAM, and rectangular QAM are derived. A comparison of various modulation schemes is presented. Further, the impact of pointing error, number of antennas, delay constraint, fading severity, and imperfect CSI are highlighted on the system performance. Finally, all the analytical results are verified through the Monte–Carlo simulations. [ABSTRACT FROM AUTHOR]

Optical wireless communication (OWC) over atmospheric turbulence and pointing errors is a well-studied topic. Still, there is limited research on signal fading due to random fog in an outdoor environment for terrestrial wireless communications. In this paper, we analyze the performance of a decode-and-forward (DF) relaying under the combined effect of random fog, pointing errors, and atmospheric turbulence with a negligible line-of-sight (LOS) direct link. We consider a generalized model for the end-to-end channel with independent and not identically distributed (i.ni.d.) pointing errors, random fog with Gamma distributed attenuation coefficient, double generalized gamma (DGG) atmospheric turbulence, and asymmetrical distance between the source and destination. We develop density and distribution functions of signal-to-noise ratio (SNR) under the combined effect of random fog, pointing errors, and atmospheric turbulence (FPT) channel and distribution function for the combined channel with random fog and pointing errors (FP). Using the derived statistical results, we present analytical expressions of the outage probability, average SNR, ergodic rate, and average bit error rate (BER) for both FP and FPT channels in terms of OWC system parameters. We also develop simplified and asymptotic performance analysis to provide insight on the system behavior analytically under various practically relevant scenarios. We demonstrate the mutual effects of channel impairments and pointing errors on the OWC performance, and show that the relaying system provides significant performance improvement compared with the direct transmissions, especially when pointing errors and fog becomes more pronounced. [ABSTRACT FROM AUTHOR]

In this paper, we consider downlink low Earth orbit (LEO) satellite communication systems where multiple LEO satellites are uniformly distributed over a sphere at a certain altitude according to a homogeneous binomial point process (BPP). Based on the characteristics of the BPP, we analyze the distance distributions and the distribution cases for the serving satellite. We analytically derive the exact outage probability, and its approximated expression is obtained using the Poisson limit theorem. With these derived expressions, the system throughput maximization problem is formulated under the satellite-visibility and outage constraints. To solve this problem, we reformulate it with bounded feasible sets and propose an iterative algorithm to obtain near-optimal solutions. Simulation results perfectly match the derived exact expressions for the outage probability and system throughput. The analytical results of the approximated expressions are fairly close to those of the exact ones. It is also shown that the proposed algorithm for the throughput maximization is very close to the optimal performance obtained by a two-dimensional exhaustive search. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) is an excellent use case for line-of-sight (LOS) based technologies such as free-space optical (FSO) communications. In this paper, we analyze the performance of RIS-empowered FSO (RISE-FSO) systems by unifying Fisher-Snedecor (${\mathcal{F}}$), Gamma-Gamma ($\cal {GG}$), and Malága ($\cal {M}$) distributions for atmospheric turbulence with zero-boresight pointing errors over deterministic as well as random path-loss in foggy conditions with heterodyne detection (HD) and intensity modulation/direct detection (IM/DD) methods. By deriving the probability density function (PDF) and cumulative distribution function (CDF) of the direct-link (DL) with the statistical effect of atmospheric turbulence, pointing errors and random fog, we develop exact expressions of PDF and CDF of the resultant channel for the RISE-FSO system. Using the derived statistical results, we present exact expressions of outage probability, average bit-error-rate (BER), ergodic capacity, and moments of signal-to-noise ratio (SNR) for both DL-FSO and RISE-FSO systems. We also develop an asymptotic analysis of the outage probability and average BER and derive the diversity order of the considered systems. We validate the analytical expressions using Monte-Carlo simulations and demonstrate the performance scaling of the FSO system with the number of RIS elements for various turbulence channels, detection techniques, and weather conditions. [ABSTRACT FROM AUTHOR]

The objective of this article is to propose a novel prediction method of the breakdown (BD) probability for multiple vacuum gaps (VGs) in series considering their dielectric recovery under a lightning impulse voltage. Based on the experimental data of the BD probability for each single VG and the calculated voltage distribution of multiple VGs, the BD probability of multiple VGs in series could be calculated by the proposed prediction method. By dielectric tests under the lightning impulse voltage, we see that the calculated BD probability distributions fit well with the experimental results for double VGs and triple VGs in series. Under sphere–plane electrode VGs, the prediction error was approximately 15% in the whole range of BD probabilities. The errors of the 50% BD voltage were 11.4% and 12.9% for double VGs and triple VGs in series, respectively. Therefore, the reliability of this prediction method considering the dielectric recovery was validated. This prediction method could be used to estimate the dielectric strength of multibreak vacuum circuit breaker (VCB) and multiple floating shields inside high-voltage vacuum interrupters. [ABSTRACT FROM AUTHOR]

This article examines and calculates the probability of failure probability of a rod-plane air gap (RPAG) under a damped alternating overvoltage (DAOV) based on a large amount of experimental data and the probability density distribution of measured overvoltages in a power system. By changing the length of the RPAG, the authors propose a prediction model for the breakdown characteristics of any length of RPAG, with the variable of DAOV parameters (including the damping factor and frequency). The results show that the model can adequately predict the breakdown characteristics of any RPAG under the action of the DAOV. Based on color channel representation, we show the results of 4-D prediction in the form of a 2-D graph. The authors combine this with a system economic model to develop a model for dynamic insulation coordination (DIC). With changes in the length of the RPAG, this model can dynamically characterize the safety factor of the system to efficiently and accurately determine whether the insulation for the air gap meets the relevant safety requirements. The proposed DIC model helps improve the accuracy of insulation design and can be used in industrial applications as a statistical method for coordinating insulations in power systems. [ABSTRACT FROM AUTHOR]

Bayesian Networks are probabilistic graph models that can be used for classification, prediction, diagnosis and parameter learning. Probabilities can be inferred from the models and missing values can be imputed, based on probability theory. Missing person cases place a strain on the already overstretched resources of Police Forces. Such cases predominantly come from at risk groups such as children in care and people suffering from depression or dementia. Current approaches for dealing with such cases are manual and rely upon empirical studies and domain knowledge. This paper proposes the use of a Bayesian Network model, which can be used to predict the likely location of a missing person (misper) for a number of at risk groups. The model is evaluated using a set of misper cases and results compare very favourably with those of the manual processes currently used by UK Police forces. The novel approach described provides both a theoretical foundation and a practical framework for the future development of a decision support system. In addition to the model, a contribution is made through guidelines, which recount experiences in learning a Bayesian Network from data.