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In this work, we provide a framework analysis of dual-hop hybrid Millimeter Wave Radio Frequency (RF)/Free Space Optical (FSO) MIMO relaying system. The source is equipped with multiple antennas and employs conjugate beamforming while the destination consists of multiple apertures with selection combining. The system also consists of a relay operating at amplify-and-forward mode. The RF channels are subject to Nakagami-m fading while the optical links experience the Málaga distribution. In addition, we introduce the impairments to the relay and receiver. In fact, the relay is impaired by the High Power Amplifier (HPA) nonlinearities while the receiver suffers from the In phase and Quadrature Imbalance. Moreover, we assume two types of HPA nonlinearities impairments called Soft Envelope Limiter (SEL) and Traveling Wave Tube Amplifier (TWTA). Closed-forms of the outage probability, the bit error probability, and the ergodic capacity are derived. Capitalizing on these performances, we derive the high SNR asymptotes to unpack insightful metrics such as the diversity gain. We also address the impacts of some key factors on the system performance such as the impairments, the interferers, the number of antennas and apertures and the pointing errors, etc. Finally, the analytical expressions are confirmed by Monte Carlo simulation. [ABSTRACT FROM AUTHOR]

Semi-grant-free (SGF) transmission has recently received significant attention due to its capability to accommodate massive connectivity and reduce access delay by admitting grant-free users to channels which would otherwise be solely occupied by grant-based users. In this paper, a new SGF transmission scheme that exploits the flexibility in choosing the decoding order in non-orthogonal multiple access (NOMA) is proposed. Compared to existing SGF schemes, this new scheme can ensure that admitting the grant-free users is completely transparent to the grant-based users, i.e., the grant-based users’ quality-of-service experience is guaranteed to be the same as for orthogonal multiple access. In addition, compared to existing SGF schemes, the proposed SGF scheme can significantly improve the robustness of the grant-free users’ transmissions and effectively avoid outage probability error floors. To facilitate the performance evaluation of the proposed SGF transmission scheme, an exact expression for the outage probability is obtained and an asymptotic analysis is conducted to show that the achievable multi-user diversity gain is proportional to the number of participating grant-free users. Computer simulation results demonstrate the performance of the proposed SGF transmission scheme and verify the accuracy of the developed analytical results. [ABSTRACT FROM AUTHOR]

We consider a wireless-powered ad hoc network with clustered Power Beacons (PBs). The wireless-powered transmitters (WP-Txs) only activate stochastically deployed PBs within the circles centered at their locations. The PBs transmit radio frequency (RF) signals, which are harvested by the WP-Txs to transmit information to their target receivers. The nodes are modeled as following $\beta $ -Ginibre Point Processes ($\beta $ -GPP), which incorporate repulsion among PBs or active WP-Txs. Lacking analytical mathematical tools to describe the distribution of clustered PBs, we establish lower and upper bounds on the energy outage probability, as well as an approximated expression of it. We then derive the information outage probability, an approximate expression of it by approximating the reduced Palm distribution of $\beta $ -GPP as an inhomogeneous Poisson point process (IPPP), and an analytical approximate expression of it by further ignoring the small-scale fading of interfering WP-Tx links. Finally, the transmission capacity is obtained based on the overall outage probability. The simulation results show that the derived theoretical expressions accurately reflect the performance of the wireless-powered ad hoc networks and the performance gap introduced by approximations is negligible. Transmission capacity optimization based on the derived expressions is also possible and demonstrated. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is considered as a potential multiple access technique for supporting massive number of devices with high spectral efficiency for the 5 G and beyond networks. Simultaneous wireless information and power transfer (SWIPT) is considered as an efficient solution for fully autonomous and sustainable communication networks. In this paper, application of SWIPT in heterogeneous networks (HetNets) employing cooperative NOMA (CNOMA) is investigated. The HetNets consists of macro-base stations (MBS) under-laid by small-base stations (SBS). The distribution of MBSs follow Poisson point process model, while the SBS tier supports NOMA and carrier sensing for its transmission. Carrier sensing helps in reducing interference by blocking the base stations within a specific range from transmitting. In this work, the analysis at SBS tier is carried out in two phases. In the direct phase transmission, the SBS transmits the superimposed signal to a user pair, comprising of a cell-centre user (CCU) and a cell-edge user (CEU), using NOMA principle. The CCU acts as a cooperative relay to forward information to the CEU in the cooperative phase. Unlike existing literature, instead of using only the superimposed signal for energy harvesting (EH), in this work, the cooperating user (i.e. CCU) employs EH using interference from the adjacent base stations along with the EH from the superimposed signal. Expressions for outage probability and throughput are derived at the user pair served using NOMA. Comparison of the proposed EH system with existing solutions are highlighted and useful insights are drawn. Monte Carlo simulations are carried out to validate the analytical results. [ABSTRACT FROM AUTHOR]

Full duplex (FD) is one of the most attractive technologies in enhancing spectral efficiency for potentially doubling the system throughput. In this work, we employ FD jamming to improve the secrecy performance of an uplink non-orthogonal multiple access (NOMA) system at the presence of one eavesdropper. We first evaluate the individual secrecy performance in terms of effective secrecy throughput (EST), by deriving its closed-form expression. Valuable insights are provided into the impacts of transmit power, jamming power as well as the number of antennas. Asymptotic analyses concerning these three arguments show the secrecy performance is location-dependent only in the high regime of transmit power and approaches to the main capacity in the high regime of the other two arguments. A special case, beamforming FD jamming, is next studied such that $N$ -fold power gain on jamming is available, in turn, improving the secrecy performance. Limited gains from high transmit and jamming power prompt us to further investigate two optimal power allocation problems: (1) optimal power allocation to minimize total power, subject to an overall secrecy performance requirement; (2) optimal power allocation to maximize overall secrecy performance, with constraint of total power. The solutions to these two optimization problems are given and demonstrated numerically with appropriate cases. [ABSTRACT FROM AUTHOR]

The paper studies a wireless-powered full-duplex non-orthogonal multiple access (NOMA) system with one base station and two groups of near and far users, where the near users can be regarded as the self-energy recycling relays to assist the far users. In particular, the locations of the near and far users are modeled as the uniformly distributed and homogeneous Poisson Point Process respectively. From the beneficial perspective of the near users, we propose a novel power allocation scheme, which can utilize the partial channel state information to switch the transmission mode dynamically between cooperative NOMA and non-cooperative NOMA. Further, since the users’ locations have a significant influence on our proposed power allocation scheme, three different user selection strategies namely random near user and random far user (RNRF), optimal near user and nearest far user (ONNF), and optimal near user and farthest far user (ONFF) are investigated to carry out NOMA pairing. Firstly, the RNRF allows all of users to communicate with the base station by a fair opportunity compared to the others strategies, and then a two-stage user selection method is proposed by considering the actual states of near users to determine an optimal near user who can maximize the outage performance of far user for ONNF and ONFF strategies. In addition, outage probabilities, diversity orders, and system throughputs are derived to characterize the performance of three strategies. Finally, numerical results are shown to verify that not only our proposed power allocation scheme can improve the quality of service of near users but also user selection strategies can fully exploit multi-user diversity in comparison to the existing work. [ABSTRACT FROM AUTHOR]

This article analyzes the robustness and timeliness for cooperative lossy communications in unmanned aerial vehicle (UAV) networks. The analytical framework consists of two steps: 1) calculating the outage probability, and 2) characterizing the Age-of-Information (AoI) for a given outage probability. Initially, we determine the outage probability based on the Shannon's lossy source-channel separation theorem. Numerical results indicate that joint decoding reduces the outage probability, and the system can achieve higher diversity order for less stringent distortion requirement. Then, we derive a closed-form expression of the lower bound on the average AoI for the communication system where outage events are constrained to an acceptable level. Moreover, we conduct a series of simulations for verifying the lower bound on the average AoI and evaluating the impact of UAV locations on the average AoI. It is demonstrated that the lower bound is tight when the server utilization ratio is either relatively busy or idle. For the case with a relatively large outage probability, we propose an intermittent transmission scheme to refine the AoI performance without extra energy consumption. The effectiveness of the intermittent transmission scheme for reducing the average AoI is verified by both the simulations and the lower bound analysis. [ABSTRACT FROM AUTHOR]

Terahertz (THz) frequency bands can be promising for data transmissions between the core network and access points (AP) for next-generation wireless systems. In this paper, we analyze the performance of a dual-hop THz-RF wireless system where an AP facilitates data transmission between a core network and user equipment (UE). We consider a generalized model for the end-to-end channel with independent and not identically distributed (i.ni.d.) fading model for THz and RF links using the $\alpha$ - $\mu$ distribution, the THz link with pointing errors, and asymmetrical relay position. We derive a closed-form expression of the cumulative distribution function (CDF) of the end-to-end signal to noise ratio (SNR) for the THz-RF link, which is valid for real-valued $\mu$ for a generalized performance analysis over THz fading channels. Using the derived CDF, we analyze the performance of the THz-RF relayed system using decode-and-forward (DF) protocol by deriving closed-form expressions of outage probability, moments of SNR, average BER, and a tight approximation of ergodic capacity in terms of system parameters. We develop asymptotic analysis on the ergodic capacity, outage probability, and average BER in the high SNR region and derive the diversity order of the system. We also analyze the considered system with an i.i.d. model and develop simplified performance to provide insight on the system behavior analytically under various practically relevant scenarios. Simulation and numerical analysis show a significant effect of fading parameters of the THz link and a nominal effect of normalized beam-width on the performance of the relay-assisted THz-RF system. [ABSTRACT FROM AUTHOR]

Proactive caching is capable of reducing access latency and improving network throughput, thereby attracting attention from both industry and academia. However, the energy efficiency (EE) of proactive caching over fading channels has not been well studied yet. In this paper, we aim at presenting an energy-efficient content pushing policy by carefully adapting the transmit rate and power in pushing and on-demand delivery phases, while assuring delivery delay constraints. To this end, the average delay, delay-outage probability, and EE are analyzed for a general adaptive pushing policy based on the saddle point approximation. According to these results, we formulate EE maximization problems under average delay and delay-outage constraints, respectively, for two special types of adaptive pushing policies, namely, opportunistic pushing and water-filling-based pushing. Due to the high complexity of the grid search for solving the formulated problems, suboptimal algorithms are presented based on gradient descent and golden section search methods. Moreover, we mathematically derive the scaling property and numerically obtain request probability and delivery delay thresholds for content pushing. Simulations show that the presented pushing policies achieve higher EE than on-demand transmissions, especially when the content item is popular and the tolerable delivery delay is small. [ABSTRACT FROM AUTHOR]

A UAV-aided wireless power transfer and data collection network is studied, where it is assumed that when the harvested energy at the sensor node (SN) cannot surpass its circuit activation threshold or the received data rate at UAV falls below a minimal required rate threshold, the information outage occurs. The closed-form expressions of energy outage probability and rate outage probability are derived at first, and then the overall outage probability and coverage performance of the system are analyzed. Based on which, an optimization problem is formulated to minimize the overall outage probability by optimizing UAV’s elevation angle and the time splitting (TS) factor. Since the problem is non-convex and has no known solution, an alternating optimization (AO)-based algorithm with Golden-section (GS) based linear search method is designed to find the global optimal solution. In order to explore the maximum coverage area of the UAV for a given tolerable outage probability, another optimization problem is also formulated to maximize the coverage range by optimizing UAV’s elevation angle. By using Karush-Kuhn-Tucker (KKT) conditions, the closed-form solution of the optimal elevation angle for maximizing the coverage area is derived. Monte Carlo simulations verify the accuracy of the derived closed-form expression of the overall outage probability and the semi-closed-form expressions of the optimum UAV’s elevation angle and TS factor. It shows that there exist a unique optimum elevation angle and the TS factor to achieve the minimum overall outage probability, and significant performance gain can be obtained by using our proposed optimization scheme. The developed theoretical results can be useful to the design of UAV-aided wireless communication systems with wireless power transfer. [ABSTRACT FROM AUTHOR]

Relay-assisted free-space optical (FSO) communication systems are exploited as a means to mitigate the limiting effects of the turbulence induced atmospheric scintillation. However, conventional ground relays are stationary, and their optimal placement is not always feasible. Due to their mobility and flexibility, unmanned aerial vehicles (UAVs) provide new opportunities for FSO relaying systems. In this paper, a hovering UAV-based serial FSO decode-and-forward relaying system is investigated. In the channel modelling for such a system, four types of impairments (i.e., atmospheric loss, atmospheric turbulence, pointing error, and link interruption due to angle-of-arrival fluctuation) are considered. Based on the proposed channel model, a tractable expression for the probability density function of the total channel gain is obtained. Closed-form expressions of the link outage probability and end-to-end outage probability are derived. Asymptotic outage performance bounds for each link and the overall system are also presented to reveal insights into the impacts of different impairments. To improve system performance, we optimize the beam width, field-of-view and UAVs’ locations. Numerical results show that the derived theoretical expressions are accurate to evaluate the outage performance of the system. Moreover, the proposed optimization schemes are efficient and can improve performance significantly. [ABSTRACT FROM AUTHOR]

This paper proposes a propagation prediction model including the statistics of location variability for over-rooftop path in millimeter-wave suburban environments. The predictive model derived from the measurement was developed to analyze the propagation characteristic of the signal according to the distance within the area of a millimeter-wave band or future fifth-generation service band. The measurement was carried out using a radio wave characteristic measurement system called the channel sounder, and the signal transmitted to the air was captured to make the received signal level data. The measurement system was constructed to predict spatial propagation characteristics by transmitting and receiving a signal with a 500 MHz bandwidth, and this system was capable of predicting characteristics of a signal that varied with space and time by capturing wideband multipath signals. Measurements were performed in a small town covered with low-rise commercial restaurants or houses. The transmission signal propagated through the rooftops of low-rise houses on average 10 meters high. Their multipath signal arrived at a receiving station located under the roof of the house through reflection, diffraction, and scattering mechanisms. The change in the signals due to the variation in location was measured up to a distance of about 500 meters from the transmitter. The basic transmission loss prediction model with a probability density distribution was analyzed and interpreted based on these measurements. In practice, it was necessary to statistically model for path loss according to the characteristics of the location due to the various environment changes, such as buildings and roads. The proposed prediction model derived from the measurement data reflects the propagation impact on over-rooftop paths in a small town and includes the statistics of location variability in line-of-sight and non-line-of-sight regions.

When we try to solve new or known problems to which we want to give new solutions, we create new knowledge and realize new discoveries. To date, the scientific methods have used the probability in order to analyze problems, make inference and build forecasts. However, everyone agreed that most problems do not follow standard probabilistic rules. In this study we will build an uncertainty logic by using the concept of probability, with those of plausibility, credibility and possibility. We will provide several models which treats uncertainty information and allow to perform more reliable forecasts. After that, we will prove the models reliability through a final simulation on the Biometrics and Sport fields using one of the models; these simulation are fully replicabile for each field and for each of the provided models.

We present a new approach for early analysis of logic gates that is based on formal methods. As device technology research takes years and is very expensive, it is desirable to evaluate a technology's potential as early as possible, which is hard to do with current techniques. The actual impact of new devices on circuit design and their performance in complex circuits, are difficult to predict using simulation-based techniques. We propose a new approach that supplements simulation-based analysis and enables the development of standard cells alongside ongoing fundamental device research. Thereby, it potentially shortens the development cycle and time to market of a new technology. We develop a new discrete charge-transport model for electrical networks and a new flexible model of polarity-reconfigurable transistors as our formal basis. These models make circuit designs accessible to an analysis using probabilistic model checking and power our experiments. Besides worst-case analysis, we leverage measures hardly accessible to simulation such as average delay and average energy consumption per switching operation. We complement this with an automated design-space exploration that yields all reasonable implementations of a switching function built with reconfigurable transistors. After demonstrating the accuracy of our approach by comparison with finite element method analysis results, we undergo a comprehensive design-space exploration and analysis of the 3-minority function. The quantitative results are ranked with respect to various performance metrics, and we analyze the most promising circuit implementations in detail to derive a design guide that yields the best implementation for given statistics of the input patterns.

Probabilistic decision-making is a fundamental problem considered in many disciplines from engineering to social sciences. In this article, we address decision-making in contexts where the law of large numbers (LLN) does not apply. Non-LLN regimes include almost all high-impact decisions. The rise of artificial intelligence (AI) decision making is further increasing the importance of developing principled approaches for such problems. In this regard, we first introduce a method called bounded expectation (BE) to apply the accepted principle of ignoring negligible probabilities. We show that BE provides some satisfactory results and insights into some decision-making problems. Pointing out some shortcomings of BE, we then turn to a much more general setting, using change-of-probability measures. We show that the proposed approach can be considered a generalization of expected utility theory (EUT) from two different perspectives. First, the approach converges to EUT as the number of repetitions grows. Additionally, when the fundamental distortion parameter, $\epsilon $ , is set to zero, the proposed theory reduces to EUT. We then propose a systematic approach to applying the developed framework to non-LLN decisions. Finally, through a real-world example, we compare the decisions made with the proposed method and the conventional methods. It is speculated that due to the complexity and multidimensionality of decision-making under non-LLN regimes, the presented ideas can potentially lead to considerable further research, some of which is discussed in this article.

The risk assessment of runway excursion accidents in the high-plateau airport is a significant part of the airport operations and risk management. This article proposes a method to evaluate the risk of runway excursion accidents in the high-plateau airport with the probability and severity estimations of runway excursion in the high-plateau airport. Firstly, the probability estimation is calculated by combining the correction model and the Bayesian network. The probability correction model considers the runway length required for takeoff and landing, specific ambient temperature, and wind speeds in the high-plateau airport. Then, a high-plateau airport simulation evacuation model of evacuation capacity is established by the VR experiment, and the severity of evacuation in the high-plateau airport is evaluated, combining the endurance of fire products. Finally, based on probability and severity, the quantitative calculation value of risk is given. We also utilize the model on a case study to find the effect of temperature, wind speed, and altitude on this risk index. The results show that the risk of runway excursion accidents in the high-plateau airport is greatly affected by temperature and wind speed. The experimental airport's risk value in February is about 11.8 times of that in September, and the risk value of the high-plateau airport is 7.32 times higher than that in a plain airport. The model successfully simulates the various scenarios at a high-plateau airport and other airports at different altitudes. It is proved that the fire risk of high-plateau airport runway excursion accidents should be paid attention to and provides scientific guidance for the airport's aviation safety management based on the actual characteristics of a high-plateau airport.

Active brake control systems are able to use more accurate control designs on the real-time knowledge of wheel slip such as tire braking forces and external momentums. A multi-objective Pareto type optimization approach is used to evaluate the inconsistent points of the optimization design namely those of minimizing the directional deviation while achieving maximum braking forces on wheels. Moreover, the optimal target slip values defined by the braking purposes like as shorter stopping distance and stability increment by keeping the vehicle in the straight line. This gets by the control of the longitudinal and lateral slip dynamics of each wheel concerning to the road conditions. A controller is optimally brought up by manipulating optimal control law with weights of two control inputs with mathematical and probabilistic characterization. The first-passage probability of critical response levels is used to directly control the vehicle directional stability. An impressive simulation technique based on Monte Carlo method named asymptotic sampling is applied to define the required first-passage probabilities and the Latin Hypercube sampling is used to design of experiments and to cover the design space. Afterwards, a Pareto-type optimization approach is applied to a trade-off between the inconsistent points of the optimization design. The simulation is conducted by the validated vehicle model and the results are indicated that the probability-based control design is represented as a preferable braking performance in comparison with the other systems for braking in sever conditions.

This article presents a novel methodology to detect insurance claim related frauds in the healthcare system using concepts of sequence mining and sequence prediction. Fraud detection in healthcare is a non-trivial task due to the heterogeneous nature of healthcare records. Fraudsters behave as normal patients and with the passage of time keep on changing their way of planting frauds; hence, there is a need to develop fraud detection models. The sequence generation is not the part of previous researches which mostly focus on amount based analysis or medication versus diseases sequential analysis. The proposed methodology is able to generate sequences of services availed or prescribed by each specialty and analyse via two cascaded checks for the detection of insurance claim related frauds. The methodology addresses these challenges and self learns from historical medical records. It is based on two modules namely “Sequence rule engine and Prediction based engine”. The sequence rule engine generates frequent sequences and probabilities of rare sequences for each specialty of the hospital. The comparison of such sequences with the actual patient sequences leads to the identification of anomalies as both sequences are not compliant to the sequences of the rule engine. The system performs further in detail analysis on all non-compliant sequences in the prediction based engine. The proposed methodology is validated by generating patient sequences from last five years transactional data of a local hospital and identifies patterns of service procedures administered to patients using Prefixspan algorithm and Compact prediction tree. Various experiments have been performed to validate the applicability of the developed methodology and the results demonstrate that the methodology is pertinent to detect healthcare frauds and provides on average 85% of accuracy. Thus can help in preventing fraudulent claims and provides better insight into how to improve patient management and treatment procedures.

At present, many enterprises provide users with better services by collecting their sensitive information. However, these enterprises will inevitably cause the leakage of users' information, thereby infringing on users' privacy. Local differential privacy resolves this problem by only aggregating randomized values from each user, providing plausible deniability. However, different users might have diverse privacy requirements for different attributes. Moreover, the dimensions of these attributes may be unbalanced. Traditional local differential privacy algorithms usually assign the same privacy budget to all attributes, resulting in undesired frequency estimation. To obtain highly accurate of the results while satisfying local differential privacy, the aggregator needs to implement a reasonable privacy budget allocation scheme. Motivated by this, this paper proposed a novel local differential privacy scheme. The proposed method combines the advantages of BRR and MRR to address the problem of high and low privacy requirements. It employs the Lagrange multiplier algorithm to transform the privacy budget allocation problem between unbalanced attributes into a problem of calculating minima from unconditionally constrained convex functions. The solution to the resulting nonlinear equation is used as the final privacy budget allocation scheme. Simulation experiments show that the novel local differential privacy scheme proposed by this paper can significantly reduce the estimation error under the premise of satisfying the local differential privacy.

Aiming at the defect of the lack of quantitative detection probability evaluation method, we design two models which affect the detection probability of image fusion system. They are spectral contrast modeling of target and background and probability model of transformer fault detection and recognition under the influence of multiple factors. Based on the infrared optical imaging method, we established the fault identification model of multi-mode transformer or its connected parts; Studied several infrared optical imaging fusion test systems, and deduced the calculation method of transformer fault detection based on false alarm probability; Analyzed the correlation between the detection ability of the detection system and the characteristics of the target itself, environmental illumination, detection distance and so on. According to the relationship among SNR, detection range and detection probability, we derived the calculation model of target detection probability of optical imaging system under complex background. Through calculation and experimental analysis, the results show that the proposed method can effectively evaluate the detection probability of photoelectric detection imaging system under different background in practical application. [ABSTRACT FROM AUTHOR]

With the advent of 5G and the need for energy-efficient massively connected wireless networks, in this work, we consider an energy harvesting (EH) based multi-relay downlink cooperative non-orthogonal multiple access (NOMA) system with practical constraints. The base station serves NOMA users with the help of decode-and-forward based multiple EH relays, where relays harvest the energy from the base station's radio frequency. A relay is selected from the multiple $K$ -relays by using a partial relay selection protocol. The system is considered to operate in half-duplex mode over a generalized independent and identical Nakagami $-m$ fading channel. The closed-form expression of outage probability and ergodic rate are derived for users, under the assumption of imperfect channel state information (CSI) and imperfect successive interference cancellation (SIC) at the receiver node. Expression of outage probability and ergodic rate for two users under the assumption of perfect CSI and perfect SIC are also presented. Further, the asymptotic expression for the outage probability is also shown. The derived analytical expressions are verified through Monte-Carlo simulations. [ABSTRACT FROM AUTHOR]

In this paper, the performance of an unmanned aerial vehicle (UAV)-based free-space optical relay system with amplify-and-forward relaying is analyzed. In particular, the statistical probability of end-to-end signal-to-noise ratio at the destination is obtained under a general condition that takes into account the effects of nonzero boresight pointing errors along with the effects of orientation and position fluctuations of the UAV relay, the UAV position with respect to the source and destination nodes, the optical beamwidth, turbulence strength of both source-to-relay and the relay-to-destination links. Subsequently, the closed-form expressions are derived for the bit-error rate and outage probability of the considered system. The accuracy of the analytical expressions is verified by performing extensive simulations. Analytical results are then utilized to study of the relationship between the optimal system parameters design and UAV's position in the sky. The results show that the optimal UAV's position that achieves a minimum outage probability highly depends on the optical beamwidth at the destination. Moreover, to achieve a minimum outage probability, the relay-to-destination link length must be shorter than source-to-destination (SR) link and by deceasing beamwidth at the destination, the optimal value for SR link length increases. [ABSTRACT FROM AUTHOR]

In this paper, we conduct rate-distortion and outage probability analyses for Wyner-Ziv (WZ) systems, where the information sequences from a source and a helper are transmitted to the destination over block Rayleigh fading multiple access channels (MACs). This work has been motivated by decision-making systems, where the aim is to make right decisions based on the observations. Hence, the most critical performance metric is the accuracy of decisions, even allowing distortion in wireless transmission. A sufficient condition for the successful transmissions is that the WZ and MAC regions intersect. For the ease of calculating the outage probability, we propose an approximated, yet accurate, WZ rate region. The outage probabilities of the WZ systems are then evaluated both in orthogonal and MAC transmissions. It is shown that the transmission efficiency of the system with MAC is significantly improved compared to orthogonal transmission. Furthermore, a helper-selection scheme is introduced to further reduce the outage probability of the WZ-MAC systems. The results show that the outage probability decreases, of which decay corresponds to the $(L+1)$ -order diversity with $L$ helpers in small value range of the average signal-to-noise ratio (SNR), while it converges into $L$ as the average SNR becomes large. [ABSTRACT FROM AUTHOR]

This paper studies the performance and key structural properties of the optimum location-based relay selection policy for wireless networks consisting of homogeneous Poisson distributed relays. The distribution of the channel quality indicator at the optimum relay location is obtained. A threshold-based distributed selective feedback policy is proposed for the discovery of the optimum relay location with finite average feedback load. It is established that the total number of relays feeding back obeys a Poisson distribution and an analytical expression for the average feedback load is derived. The analytical expressions for the average rate and outage probability with and without selective feedback are obtained for general path-loss models. It is shown that the optimum location-based relay selection policy outperforms other common relay selection strategies notably. It is also shown that utilizing location information from five relays on average is enough to achieve almost the same performance with the infinite feedback load case. As generalizations, isotropic Poisson point processes and heterogeneous source-to-relay and relay-to-destination links are also studied. [ABSTRACT FROM AUTHOR]

The success of Multi-hypothesis tracking(MHT) lies in the use of multiple scans, which can often yield improved tracking performance over single scan based data association methods in radar-centric multi-target tracking(MTT) systems. However, with the increase of the number of targets associated with measurements, there is an exponentially increasing need for formulating potential hypotheses, of which the computational cost may be prohibitively expensive. In this paper, a multi-hypothesis fractional belief propagation (MHFBP) based data association algorithm is proposed by the use of a probabilistic graph model for both the previous trajectories and the current measurements. To achieve this idea, there are two main steps. First, the trajectory-related indicators associated state variables are created by making use of a convex fractional free energy (FFE)function. Second, the convex optimization algorithm is used for the objective function and the fractional belief propagation (FBP) is exploited to obtain the best marginal belief of measurement for target association. In this way, incorrect hypotheses with extremely low probability can be eliminated. Finally, the proposed method is applied to multiple scenarios for MTT by indoor radar system. From the results, we can observe that it provides higher tracking performance compared with the classical MHT, feature-aided MHT(FA-MHT) and MHT-belief propagation (MHT-BP). In addition, we see that the computational burden of the proposed method is reduced significantly to avoid the phenomenon of exponential growth with increasing the number of targets. [ABSTRACT FROM AUTHOR]

Alignment-free sequence comparison approaches have become increasingly popular in computational biology, because alignment-based approaches are inefficient to process large-scale datasets. Still, there is no way to determine the optimal value of the critical parameter k for alignment-free approaches in general. In this article, we tried to solve the problem by involving multiple k values simultaneously. The method counts the occurrence of each k-mer with different k values in a sequence. Two weighting schemes, based on maximizing deviation method and genetic algorithm, are then used on these counts. We applied the method to enhance the three common alignment-free approaches ${D_2}$ D 2 , $D_2^S$ D 2 S , and $D_2^*$ D 2 * , and evaluated its performance on similarity search and functionally related regulatory sequences recognition. The enhanced approaches achieve better performance than the original approaches in all cases, and much better performance than some other common measures, such as Pcc, Eu, Ma, Ch, Kld, and Cos. [ABSTRACT FROM AUTHOR]

In this article, the problem of power allocation in a wireless multiple access channel with two sensors is addressed, where squared channel coefficients, and, hence, signal-to-noise ratios are assumed to have Gaussian mixture distributions and the dependence between channel coefficients is described by using copula theory. For this model, outage probability is analyzed as the objective function for formulating the power allocation, and for the product copula function or in the independent channels case, a closed form of outage probability is obtained. Considering that the corresponding optimizations do not lead to convex optimization problems, MATLAB simulation is employed to solve the power allocation problem. Various Gaussian mixture distribution parameters are exploited for the links between the sensors and the fusion center with different dependencies and the results are compared. [ABSTRACT FROM AUTHOR]

In deterministic networks where relay nodes are stationary, combined relay selection is an efficient relay selection scheme, which is capable of achieving the near-optimal outage performance with much lower system complexity. However, the efficiency of combined relay selection is only validated upon fixed topological settings. To investigate the performance of combined relay selection in spatially random networks (SRNs), we employ the Poisson point process to model the dynamical nature of cooperative networks and study the outage performance of the proposed system. It is surprising that the equivalence principle of combined relay selection appearing in deterministic networks does not hold in SRNs. [ABSTRACT FROM AUTHOR]

This article exploits the recent advances in wireless energy harvesting to develop a framework for the outage probability of energy harvesting underlay cognitive radio networks. In this model, $N$ -hop primary users are equipped with constant energy source while secondary users (SUs) harvest energy from the transmissions of primary devices. The transmit power of secondary users is regulated to ensure that it does not violate the target end-to-end outage probability constraint of the $N$ -hop primary network. Potential relays that have harvested sufficient energy are eligible to relay data for other SUs within the network. Using this model, we reveal the impacts of the number of primary hops on the relay selection region and harvested energy. An expression for the total outage probability that encapsulates the impact of $N$ primary hops is also derived. Moreover, the effects of other relevant parameters on the outage probability are shown in detail. [ABSTRACT FROM AUTHOR]

Recently, nonorthogonal multiple access (NOMA) technology has emerged as a key technology for enhancing power and spectrum efficiency of fifth-generation (5G) wireless networks. On the one hand, multiple-description coding (MDC) is a coding technique with high efficiency and strong antiinterference capabilities that can combat burst interference and solve the problem of unreliable transmission due to link impairments and network congestion. In this article, by combining the principles of MDC and NOMA, we propose a hybrid MDC-NOMA scheme to further improve system throughput and transmission robustness. In the proposed scheme, a base station communicates with two users simultaneously over two orthogonal subchannels. In this setup, one subchannel is sufficient to reconstruct an image of acceptable quality. We derive the closed-form expressions for the outage probability and ergodic rate and analyze its peak signal to noise ratio, bit error rate, and visual transmission performance. Furthermore, numerical and simulation results are presented in order to validate the analysis. [ABSTRACT FROM AUTHOR]

The proliferation of the Internet of Things has enabled implementing control loops using low-capable devices over non-deterministic networks. This letter addresses the use of non-beacon enabled CSMA/CA and motivates the need of minimizing the probability of peak age surpassing a bound, given in terms of two indicators of control over networks: the maximum allowable transmit interval and the maximum allowable delay. A concrete analytical result for calculating the probability is given, which represents an improvement of 50% with respect to a known bound at the optimal rate in a 5-loops control system. [ABSTRACT FROM AUTHOR]

In this letter, we analyze the coverage performance of multi-user multiple-input multiple-output (MU-MIMO) downlink cellular networks. We model the locations of the base stations and mobile users using Poisson Point Processes and employ maximum ratio transmission precoding at the base station. Our analysis builds upon Prony’s method to approximately calculate the coverage probability using the sum of exponentials which facilitates the computation of Laplace transform of both intra-cell and inter-cell interference. We demonstrate the accuracy of derived approximate coverage probability expressions through numerical simulations for different MU-MIMO configurations. [ABSTRACT FROM AUTHOR]

This paper studies the application of network non-orthogonal multiple access (N-NOMA) to vehicular communication networks, modeled by a Poisson line Cox point process (PLC). Particularly, the road infrastructure is modeled by a Poisson line point process (PLP), whereas base stations (BSs) and users are located according to 1D homogeneous Poisson point processes (HPPPs) on each road. In the considered N-NOMA scheme, there are two types of users, i.e., coordinated multi-point (CoMP) users which are far from their BSs and NOMA users which are close to their BSs, where the CoMP users and the NOMA users are served simultaneously by applying the principle of NOMA. Specifically, the BSs collaborate with each other to provide reliable transmission for the CoMP user by applying Almouti coding, while each BS employs superposition coding to opportunistically serve an additional NOMA user. Compared to a conventional OMA based scheme, where only a CoMP user is served, the proposed N-NOMA scheme significantly improves the performance in terms of outage sum rates and user connectivity, since more users are served in the same resource block. A comprehensive analytical framework is developed to characterize the system level performance of the proposed N-NOMA scheme by applying PLC. Closed form expressions for the outage probabilities achieved by the CoMP and NOMA users are obtained. Computer simulation results are provided to show the superior performance of the proposed scheme and also validate the accuracy of the developed analytical results. [ABSTRACT FROM AUTHOR]

Consider an energy harvesting (EH) sensor that continuously monitors a system and sends time-stamped status update to a destination. The sensor harvests energy from nature and uses it to power its updating operations. The destination keeps track of the system status through the successfully received updates. With the recently introduced information freshness metric “Age of Information” (AoI), our objective is to design optimal online status updating policy to minimize the long-term average AoI at the destination, subject to the energy causality constraint at the sensor. Due to the noisy channel between the sensor and the destination, each transmitted update may be erased with a fixed probability, and the AoI at the destination will be reset to zero only when an update is successfully received. We first consider status updating without feedback available to the sensor and show that the Best-effort Uniform updating (BU) policy is optimal in a broadly defined class of online policies. We then investigate status updating with perfect feedback to the sensor and prove similar optimality of the Best-effort Uniform updating with Retransmission (BUR) policy. In order to prove the optimality of the proposed policies, for each case, we first identify a lower bound on the long-term average AoI among a broad class of online policies, and then construct a sequence of virtual policies to approach the lower bound asymptotically. Since those virtual policies are sub-optimal to the original policy, the original policy is thus optimal. [ABSTRACT FROM AUTHOR]

In this work, graphene oxide nanoparticles are dispersed in different concentrations in a soyabean extracted natural ester-based oil-blend having mineral oil as secondary oil and the resulting nanofluids are tested for various dielectric and physio-thermal properties. The results show that with the addition of nanoparticles, the breakdown voltage of nanofluids increases up to 42% as compared to pure mineral oil, 17% as compared to pure ester oil and 15% as compared to the base oil-blend. Relative permittivity and dissipation factor parameters follow a similar trend as well. Thus, the prepared nanofluids can be used as alternative insulating oils in place of the conventional mineral oil in oil-filled transformers. [ABSTRACT FROM AUTHOR]

This paper aims at the experimental study of the influence of nanoparticles (namely Fe3O4, Al2O3 and SiO2) and nanoparticles' mixtures consisting of conductive (Fe3O4) and insulating (Al2O3 or SiO2) nanoparticles at various concentrations on the AC breakdown voltage (AC-BDV) of transformer mineral oil. The breakdown voltages at 1%, 10% and 50% cumulative probabilities are deduced. A statistical analysis of experimental results obtained with nanoparticles' mixtures is also performed using normal and Weibull distribution laws. Experimental findings show that the considered nanoparticles significantly improve the average AC-BDV. The improvement can reach 114%, 76% and 75% with Fe3O4, Al2O3 and SiO2 NPs, respectively. With mixtures of nanoparticles, namely (Fe3O4 +Al2O3) and (Fe3O4 +SiO2), at investigated concentrations, the average AC-BDV always increases. The best improvements are obtained with (20% Fe3O4 +80% SiO2) and (20% Fe3 O4 +80% Al2O3), that is to say, 94% and 90%, respectively. These latter are better than with SiO2 and Al2O3 NPs when used singularly. [ABSTRACT FROM AUTHOR]

In this paper, a resource allocation and data gathering scenario of an unmanned aerial vehicle (UAV) assisted wireless powered sensor network is investigated, in which the sensor nodes (SNs) are remotely powered by power beacons (PBs) via radio-frequency wireless power transmission (RF-WPT). A time-block structure with two phases is proposed to accommodate operations in the proposed system. During Phase-I, SNs harvest energy from PBs and periodically send its sensed data to the selected cluster heads (CHs). In Phase-II, an UAV collects the data from CHs to be delivered to the data sink for further processing avoiding the need for long range transmission and multi hop communication to the data sink. Then, a closed-form expression for outage probability of the proposed system over Rayleigh and Rician fading channels is derived. Next, outage probability minimization problem is formulated to obtain optimal time allocation for RF-WPT energy harvesting to improve the system performance. Due to the complexity of the problem, Lagrangian duality method is used to develop an asymptotic optimal solution with less execution complexity avoiding complex brute force/ exhaustive search approach. Furthermore, a heuristic method is presented to further lower the computation complexity. Simulation results reveal the superiority of the proposed methods compare to brute force/ exhaustive search approach via analysis, comparison and insights of the system performance results. Finally, the performance superiority of the proposed system is demonstrated with compare to identified baseline WSNs. [ABSTRACT FROM AUTHOR]

To scientifically evaluate the damage effectiveness of a projectile explosion on the equivalent target, this article studies a warhead fragment distribution parameters’ measurement method based on a six-screen-sensors’ intersection test system; establishes a parameter calculation model of the warhead fragment hitting the equivalent target, the time and space constraints’ discriminant model of six infrared detection screens, and the time-value-matching model of multiple warhead fragments; and gives the calculation of the specific fragment distribution position and the time-matching algorithm of each infrared detection screen. According to the obtained warhead fragment parameters, a calculation method of the damage probability of equivalent target is constructed. Through experiments and analysis, it is verified that the established warhead fragment parameter measurement method and the damage probability model of the equivalent target are scientific. [ABSTRACT FROM AUTHOR]

The development of artificial intelligence has brought new opportunities and challenges in the field of mechanical fault diagnosis. Especially, data-driven intelligent fault diagnosis (DIFD) methods are favored by researchers. However, commonly used DIFD methods can only recognize the fault of a known class instead of an unknown class, which results in the DIFD’s inability to self-learning. To handle this problem, novel probability confidence convolutional neural network (PCCNN) is proposed in this article. The probability of belonging to each known class calculated by the PCCNN and the confidence of each known class is used to recognize the known and unknown classes. At the same time, the ability to recognize a new class is achieved by updating the architecture and parameters of the PCCNN model with a self-learning method. The bearing experiment dataset, the gearbox experiment dataset, and the rotating machinery failure data are used in the case studies. The study results show that the proposed method achieves an average accuracy of 97.42% and 96.87% for recognizing unknown and known classes, respectively, exhibiting at least 5.18% better performance than the 12 comparison methods. All the code and experimental data are available on the website. [ABSTRACT FROM AUTHOR]

Texture characterization from the metrological point of view is addressed in order to establish a physically relevant and directly interpretable feature. In this regard, a generic formulation is proposed to simultaneously capture the spectral and spatial complexity in hyperspectral images. The feature, named relative spectral difference occurrence matrix (RSDOM) is thus constructed in a multireference, multidirectional, and multiscale context. As validation, its performance is assessed in three versatile tasks. In texture classification on HyTexiLa, content-based image retrieval (CBIR) on ICONES-HSI, and land cover classification on Salinas, RSDOM registers 98.5% accuracy, 80.3% precision (for the top 10 retrieved images), and 96.0% accuracy (after post-processing) respectively, outcompeting GLCM, Gabor filter, LBP, SVM, CCF, CNN, and GCN. Analysis shows the advantage of RSDOM in terms of feature size (a mere 126, 30, and 20 scalars using GMM in order of the three tasks) as well as metrological validity in texture representation regardless of the spectral range, resolution, and number of bands. [ABSTRACT FROM AUTHOR]

Phylogenetics study the evolutionary history of organisms using an iterative process of creating and evaluating phylogenetic trees. This process is very computationally intensive; constructing a large phylogenetic tree requires hundreds to thousands of CPU hours. In this article, we describe an FPGA-based system that can be deployed on AWS EC2 F1 cloud instances to accelerate phylogenetic analyses by boosting performance of the phylogenetic likelihood function, i.e., a widely employed tree-evaluation function that accounts for up to 95% of the overall analysis time. We exploit domain-specific knowledge to reduce the amount of transferred data that limits overall system performance. Our proof-of-concept implementation reveals that the effective accelerator throughput nearly quadruples with optimized data movement, reaching up to 75% of its theoretical peak and nearly 10× faster processing than a CPU using AVX2 extensions. [ABSTRACT FROM AUTHOR]

In this paper, we design a NOMA-based spectrum leasing scheme by considering the following three assumptions for the successive interference cancellation (SIC): (i) the primary network performs the SIC (PSIC), (ii) the secondary network performs the SIC (SSIC), (iii) either the primary or secondary network adaptively performs the SIC depending on the channel conditions (ASIC). We first analyze the achievable rate regions of these schemes. Then, we optimize the power allocation to different layers of the superimposed signal by maximizing the achievable rate of the secondary network under a QoS constraint for the primary network. Finally, we analyze these schemes in terms of the outage probability. The analysis shows that: (i) In terms of the primary network, the PSIC and ASIC schemes perform the same and these schemes outperform the SSIC scheme. (ii) In terms of the secondary network, the ASIC scheme outperforms the other two schemes. (iii) In terms of the primary network, the NOMA-based and OMA-based schemes perform the same, provided that the SIC is performed either adaptively or in a fixed manner at the primary network. (iv) In terms of the secondary network, the NOMA-based scheme outperforms the OMA-based scheme, provided that the SIC is performed adaptively. [ABSTRACT FROM AUTHOR]

Imbalance-induced energy loss accounts for a significant part of energy loss in low-voltage distribution networks. However, due to the prohibitive cost of full monitoring, high-resolution time-series data of low-voltage feeder currents are usually absent for accurate energy loss computation. This letter presents a novel method to estimate the probability distribution of imbalance-induced energy loss. In the proposed method, only the line resistance and statistical data (mean and covariance) of the phase currents are required to estimate imbalanced networks’ energy loss. Furthermore, a Bayesian statistics-based data-driven method is also proposed to get the mean and covariance value of phase current with minimal measurements. Numerical tests on a real three-phase imbalanced circuit show the proposed approach obtains the probability distribution of imbalance-induced energy loss with a low estimating error and low field measurement frequency. [ABSTRACT FROM AUTHOR]

From an operational and planning perspective, it is important to quantify the impact of increasing penetration of photovoltaics on the distribution system voltage. Most existing impact assessment studies are scenario-based where derived results are scenario specific and not generalizable. Moreover, stochasticity in temporal behavior of multiple spatially distributed PVs requires a large number of scenarios to be simulated that increases with the size of the network and the level of penetration. Therefore, we propose a new computationally efficient analytical framework of voltage sensitivity analysis that allows for stochastic analysis of voltage change due to random changes in PV generation. We derive an analytical approximation for voltage change at any node of the network due to a change in power at other nodes in an unbalanced distribution network. Then, we derive the probability distribution of voltage change at a certain node due to random changes in power injections/consumptions at multiple locations of the network. The accuracy of the proposed method is illustrated using a modified version of IEEE 37 bus and IEEE 123 bus test systems. The proposed framework can serve as a powerful tool for proactive monitoring/control of voltage, and ease the computational burden associated with perturbation based cybersecurity mechanisms. [ABSTRACT FROM AUTHOR]

Password strength meters (PSMs) are being widely used, but they often give conflicting, inaccurate and misleading feedback, which defeats their purpose. Except for fuzzyPSM, all PSMs assume passwords are newly constructed, which is not true in reality. FuzzyPSM considers password reuse, six major leet transformations and initial capitalization, and performs the best as evaluated by Golla and Dürmuth at ACM CCS’18. On the basis of fuzzyPSM, we propose a new PSM based on Reuse, Leet and Separation, namely RLS-PSM. First, we classify password reuse behaviors into capitalization and those that use special characters for leet or separation, and calculate the corresponding probabilities. Then, to balance efficiency and precision, we use Long Short-Term Memory to calculate the probabilities of alphanumeric strings. Besides, we propose to use benchmark passwords to show the relative strength of a password. Due to the varied impacts of different service types and diversified economic value of websites, we consider parameter settings of RLS-PSM under six different service types. Finally, we use the Monte Carlo method and weighted Spearman coefficient to measure and compare the robustness and accuracy of RLS-PSM, leading PSMs (including Markov-based PSM, PCFG-based PSM, fuzzyPSM, RNN, and Zxcvbn), and password cracking tools (including JtR and Hashcat). We find that the robustness of RLS-PSM is significantly higher than all counterparts when evaluating attempts > 104 (e.g., on average, Fraction of Successfully Evaluated passwords of RLS-PSM is 18.9% higher than fuzzyPSM). The accuracy of RLS-PSM is also better than other mainstream PSMs used for comparison in this paper, except for fuzzyPSM. [ABSTRACT FROM AUTHOR]

Under both long (infinite) and short (finite) blocklength transmissions, this paper considers physical layer security for a wireless interference network of multiple transmitter-user pairs, which is overheard by multiple eavesdroppers (EVs). The EVs are assumed to have better channel conditions than the legitimate users (UEs), making the conventional transmission unsecured. The paper develops a novel time-fraction based transmission, under which the information is transmitted to the UEs within a fraction of the time slot and artificial noise (AN) is transmitted within the remaining fraction to counter the strong EVs’ channels. Based on channel distribution information of UEs and EVs, the joint design of transmit beamforming, time fractions and AN power allocation to maximize the worst users’ secrecy rate is formulated in terms of nonconvex problems. Path-following algorithms of low complexity and rapid convergence are proposed for their solution. Simulations are provided to demonstrate the viability of the proposed methodology. [ABSTRACT FROM AUTHOR]

This paper considers a cooperative device-to-device (D2D) system with non-orthogonal multiple access (NOMA). We assume that the base station (BS) can simultaneously communicate with all users to satisfy the full information transmission requirement. In order to characterize the impact of the weak channel and different decoding schemes, two novel decoding strategies are introduced: single signal decoding scheme and maximum ratio combining (MRC) decoding scheme, respectively. With the single signal decoding scheme, the users decode the received signals immediately after the receptions from the BS. On the other hand, the MRC decoding scheme jointly decodes the received signals via MRC until the corresponding phase comes and the users jointly decode the received signals by employing MRC. Considering Rayleigh fading channels, the ergodic sum-rate (SR), outage probability and outage capacity of the proposed D2D-NOMA system are analyzed. Moreover, approximate expressions for the ergodic SR are also provided with a negligible performance loss. Numerical results demonstrate that the ergodic SR and outage probability of the proposed D2D-NOMA scheme overwhelm that of the conventional NOMA schemes. Furthermore, it is also revealed that the system performance including the ergodic SR and outage probability are limited by the weak channel for both the single signal decoding scheme and conventional NOMA schemes, but not for the MRC decoding scheme. [ABSTRACT FROM AUTHOR]

Prompted by previous work published in this magazine, in this article we focus on the derivation of global analytical bounds for the error function of a real argument. Using an integral representation of this function, we obtain two simple and accurate lower bounds, which complement a well-known upper bound given long ago by Pólya. [ABSTRACT FROM AUTHOR]

This paper studies the modeling and synchronization problems for stochastic complex dynamical networks subject to consecutive packet dropouts. Different from some existing research results, both probability characteristic and upper bound of consecutive packet dropouts are involved in the proposed approach of controller design. First, an error dynamical network with stochastic and bounded delay is established by step-delay method, where the randomness of the bounded delay can be verified later by the probability theory method. A new modeling method is introduced to reflect the probability characteristic of consecutive packet dropouts. Based on the proposed model, some sufficient conditions are proposed under which the error dynamical network is globally exponentially synchronized in the mean square sense. Subsequently, a probability-distribution-dependent controller design procedure is then proposed. Finally, two numerical examples with simulations are provided to validate the analytical results and demonstrate the less conservatism of the proposed model method. [ABSTRACT FROM AUTHOR]

When a small portion of the decision makers hold the correct information and the majority hold the opposite, the correct ranking of the alternatives for the group decision-making cannot be obtained with the current methods. A novel method is thus developed to tackle this challenge in this article. The priori probabilities of each alternative can be calculated via the opinions of the group decision makers, which are presented as the pairwise comparisons of the alternatives in the form of the linguistic preference relation. Based on the aggregated probabilities of the alternatives in the group of the decision makers, the normalized-prediction selection rate (NPSR) is defined and calculated accordingly. The alternative with maximal NPSR is selected as the correct answer, whereas the accuracy of the correct alternative selection (CAS) is guaranteed by two propositions. The iterative algorithm is first devised to determine the ranking of the alternatives depending on the CAS. For the proposed method, the decision makers require no modification of the opinions as can avoid the consensus problem, and the CAS can be obtained under the circumstances that the correct information is held by the minority of the group. Finally, the experiment has been conducted to demonstrate the efficacy of the proposed method to obtain the CAS, and the main limitations of proposed method are carefully addressed as well. [ABSTRACT FROM AUTHOR]