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Radio frequency identification technology has been widely used to verify the presence of items in many applications such as warehouse management and supply chain logistics. In these applications, the challenge of how to timely identify the missing tags (namely tag searching or missing tag identification) is a key focus. Existing missing tag identification solutions have not achieved their full potentials because collision slots have not been well explored. In this paper, we propose an approach named collision resolving based missing tag identification (CR-MTI) to break through the performance bottleneck of existing missing tag identification protocols. In CR-MTI, multiple tags are allowed to respond with different binary strings in a collision slot. Then, the reader can verify them together by using the bit tracking technology and particularly designed string, thereby significantly improve the time efficiency. CR-MTI also reduces the number of messages transmitted by the reader using customized coding. We further explore the optimal parameter settings to maximize the performance of our proposed CR-MTI. Extensive simulation results show that our proposed CR-MTI outperforms prior art in terms of time efficiency, total executive time and communication complexity.

This article investigates the synchronization of communication-constrained complex dynamic networks subject to malicious attacks. An observer-based controller is designed by virtue of the bounded encode sequence derived from an improved coding-decoding communication protocol. Moreover, taking the security of data transmission into consideration, the denial-of-service attacks with the frequency and duration characterized by the average dwell-time constraint are introduced into data communication, and their influence on the coder string is analyzed explicitly. Thereafter, by imposing reasonable restrictions on the transmission protocol and the occurrence of attacks, the boundedness of coding intervals can be obtained. Since the precision of data is generally limited, it may lead to the situation that the signal to be encoded overflows the coding interval such that it results in the unavailability of the developed coding scheme. To cope with this problem, a dynamic variable is introduced to the design of the protocol. Subsequently, based on the Lyapunov stability theory, sufficient conditions for ensuring the input-to-state stability of the synchronization error systems under the communication-constrained condition and malicious attacks are presented. The validity of the developed method is finally verified by a simulation example of chaotic networks.\enlargethispage-8pt.

String prediction (SP) is a very efficient screen content coding (SCC) tool which has been adopted in the third generation of Audio Video Standard (AVS3). It is observed that two special types of strings occur frequently. To further improve the coding efficiency for SCC on top of the original SP, a new variation of SP named Equal-value-string and Copy-above-string based SP (ECSP) is proposed. An ECSP coding unit uses only three types of string: Equal-value-string, Copy-above-string, and Unpredictable-pixel-string. Compared with the AVS3 reference software HPM9.0 with ECSP disabled, using AVS3 SCC Common Test Condition and YUV 4:2:0 test sequences, the proposed technique achieves an average Y BD-rate reduction of 5.54% and 3.01% for All Intra and Low Delay configurations, espectively, with low additional encoding and decoding complexity. The proposed ECSP has been adopted in the AVS3 standard.

Existing deep reinforcement learning (DRL) based methods for solving the capacitated vehicle routing problem (CVRP) intrinsically cope with homogeneous vehicle fleet, in which the fleet is assumed as repetitions of a single vehicle. Hence, their key to construct a solution solely lies in the selection of the next node (customer) to visit excluding the selection of vehicle. However, vehicles in real-world scenarios are likely to be heterogeneous with different characteristics that affect their capacity (or travel speed), rendering existing DRL methods less effective. In this paper, we tackle heterogeneous CVRP (HCVRP), where vehicles are mainly characterized by different capacities. We consider both min-max and min-sum objectives for HCVRP, which aim to minimize the longest or total travel time of the vehicle(s) in the fleet. To solve those problems, we propose a DRL method based on the attention mechanism with a vehicle selection decoder accounting for the heterogeneous fleet constraint and a node selection decoder accounting for the route construction, which learns to construct a solution by automatically selecting both a vehicle and a node for this vehicle at each step. Experimental results based on randomly generated instances show that, with desirable generalization to various problem sizes, our method outperforms the state-of-the-art DRL method and most of the conventional heuristics, and also delivers competitive performance against the state-of-the-art heuristic method, i.e., SISR. Additionally, the results of extended experiments demonstrate that our method is also able to solve CVRPLib instances with satisfactory performance., Comment: This paper has been accepted at IEEE Transactions on Cybernetics

Oil and gas industry continues to the increasing demand of more cost-effective well design and operations. Thus, team successfully eliminated intermediate casing string from the design thereby achieving not only a 33% reduction in dry hole cost/meter, but also delivering wells and producing oil 25% faster than before. Removing an intermediate casing string resulted in a longer open hole (more than 2000 mMD) which by default created new challenges which had to be dealt with and solved without compromising the targeted cost saving. The challenges can be summarized as follow: • Combining loss of circulation zone with unstable shale formations in one section. • PPFG uncertainties. • Bit selection and design optimization. • BHA selection and drive optimization. • Running wireline logging through a long open hole. • Running casing and having good quality cement. • Hole cleaning and displacement efficiency when changing mud systems. • Proper contingencies in place to meet the required completion strategy. Risk assessment, feasibility studies, workshops, and co-operation among all involved personnel has been conducted to ensure that this design optimization would result in positive outcome. Since the first implementation in 2019, more than 17 wells have been successfully delivered and completed in Best in Class performance based on latest update of Rushmore data tracking. The longest open hole section of 2790 m measured depth (MD) with total depth (TD) of 3910 mMD has been achieved generating above 800 Kusd saving per well, thus setting new benchmarks for the field and opening up new opportunities for the future. All this ensure Process Safety and compliance with Well Delivery process. This paper not only describes how two string design was successfully engineered and executed but also serves as a guide for selecting proper candidates for this design and an operational guide for two section wells design to ensure that these challenging long open hole will be successfully drilled while minimizing risks.

This paper investigates a platooning problem of connected vehicles subject to communication interruptions and latency. For a heterogeneous platoon of vehicles, a hybrid reference model with cooperative adaptive cruise control (CACC) and adaptive cruise control (ACC) is established. Then a novel CACC-ACC switching control method is suggested, which activates either a CACC scheme or an augmented ACC strategy depending on the status of communications. By introducing a platoon state tracking error system, a control algorithm is derived using finite-time sliding-mode control theory, which can robustly guarantee string stability and zero steady-state spacing error of the vehicular platoon. Simulations have shown the effectiveness and superiority of the method.

This paper is about obtaining stable vehicle platooning by using Cooperative Adaptive Cruise Control when the communication is unreliable and suffers from message losses. We model communication losses as independent random events and we propose an original design for the cooperative controller, which mitigates the effect of losses. This objective is obtained by a switching controller that has a twofold objective: on the one hand, it promotes both plant stability and string stability of the average error dynamics by an $H_infty$ approach, and on the other hand it minimizes the variance around the average. We show by simulations that the proposed controller is able to compensate even for high probability of losses., Comment: 10 pages, 7 figures; submitted to journal

This study focuses on an adaptive fault-tolerant boundary control (BC) for a flexible string (FS) in the presence of unknown external disturbances, dead zone, and actuator fault. To tackle these issues, by employing some transformations, a part of the unknown dead zone and external disturbance can be regarded as a composite disturbance. Subsequently, an adaptive fault-tolerant BC is developed by utilizing strict formula derivations to compensate for unknown composite disturbance, dead zone, and actuator fault in the FS system. Under the proposed control strategy, the closed-loop system proves to be uniformly ultimately bounded, and the vibration amplitude is guaranteed to converge ultimately to a small compact set by choosing suitable design parameters. Finally, a numerical simulation is performed to demonstrate the control performance of the proposed scheme.

Vehicular platoon control can effectively achieve group consensus, improve vehicular running safety and increase road capacity. However, some constraints exist in practical situations due to the limitations of traffic environment in time-varying metrics (time-delay, packet-dropout or interruption) in wireless communication systems. In this work, a distributed model predictive control (MPC) algorithm is proposed for connected vehicle platoon with a focus on switching communication topologies and control strategy under abnormal communications. Firstly, the predecessor-leader following is selected as the basic communication topology, by which the switching communication topology and the desired vehicle spacing policy are established. Secondly, the platoon control algorithm of connected vehicles is established and a set of constraints is analyzed. Thirdly, the L₂ -norm string stability criterion and the asymptotic stability criterion are considered within the proposed MPC. Finally, a co-simulation platform for connected vehicle platoon is developed based on Prescan/Matlab/V2X communication simulator. In addition, the platoon control algorithm is tested in three traffic scenarios including normal communication, leading vehicle with abnormal communication and following vehicle with abnormal communication. The experiments demonstrate that the communication topologies in different communication environments can be switched well in real time through the proposed platoon control algorithm. In addition, the string stability, the consistency of vehicle spacing, speed and acceleration are proven to be guaranteed simultaneously.

In this paper, a novel modular multilevel dc-dc converter with high power-density potential is proposed based on a cascaded string of voltage source submodules (VSM) merged with a current source submodule (CSM) that is configured to rapidly invert the polarity of the current in the VSM string. The proposed hybrid converter combines the i) modularity advantages of the modular multilevel converter (MMC) and ii) the high effective frequency advantages of the flying capacitor converter (FCC). Unlike other hybrid non-isolated MMC structures the proposed converter features a novel CSM stage enabling i) a near 50% reduction in string current, and ii) the input source and output load to be commonly grounded. In addition, the proposed operational approach enables self-balancing of the VSMs and a simple overall control structure. This article introduces the main operating principles of this novel topology termed the Current Shaping Modular Multilevel Forward Converter (CS-M2FC) along with a proposed control design. A peak efficiency of 97.1% is measured for a laboratory-scale prototype at 950-137V and 1.45 kW.

Scaffold filling is a critical step in DNA assembly. Its basic task is to fill the missing genes (fragments) into an incomplete genome (scaffold) to make it similar to the reference genome. There have been a lot of work under distinct measurements in the literature of genome comparison. For genomes with gene duplications, common string partition reveals the similarity more precisely, since it constructs a one-to-one correspondence between the same segments in the two genomes. In this paper, we adopt duo-preservation as the measurement, which is the complement of common string partition, i.e., the number of duo-preservations added to the number of common strings is exactly the length of a genome. Towards a proper scaffold filling, we just focus on the increased duo-preservations. This problem is called scaffold filling to maximize increased duo-preservations (abbr. SF-MIDP). We show that SF-MIDP is solvable in linear time for a simple version where all the genes of the scaffold are matched in a block-matching, but MAX SNP-complete for the general version, and cannot be approximated within [Formula: see text]. Moreover, we present a basic approximation algorithm of factor 2, by which the optimal solution can be described in a new way, and then, improve the approximation factor to [Formula: see text] via a greedy method.

In recent years, the adaptive cruise control (ACC) system has become widely adopted. The vehicle-positioning system plays an important role in automotive platoon driving and can provide vehicle-position information through vehicle-to-vehicle communication. However, the acquired vehicle-position information often presents uncertainties given the existence of variations in the traffic environment and of noise in the vehicle-positioning system. These uncertainties, in turn, influence the car-following performance of a vehicle platoon. In this study, we employ the desired safety margin (DSM) model, an ACC control strategy, to investigate the influence of the uncertainty level of vehicle-position information (ULVPI) on string stability and car-following safety. The stability criterion of the DSM model with ULVPI is derived through linear stability theory. Theoretical analysis results are verified by numerical simulations. Analytical results indicate that a negative ULVPI value can expand the stable region and improve string stability and that a positive ULVPI value can reduce delay time. Moreover, a negative ULVPI value can improve car-following safety during the stopping and evolution processes, whereas a positive ULVPI values can increase the safety margins of vehicles during the starting process. In the car-following process, a negative ULVPI value can improve car-following safety and reduce rear-end collision risk. The variation in ULVPI values can improve string stability and reduce the risk of rear-end collisions when mean and standard deviation are reasonable. Therefore, the improvement of a vehicle's dynamic performance, string stability, and safety relies on the effect of ULVPI in different traffic scenarios. These results are useful in designing different control strategies that stabilize traffic flow and improve traffic safety for vehicles with ACC systems.

Among other motif finding algorithms Planted Motif Search (PMS) or (l, d) motif search algorithms are considered as next-generation motif finding algorithms. Here, n strings and two integer l and d are provided as input in PMS. It gives outputs of all sequences of length M in each input string, where each occurrence varies from Min at most d points. This paper proposes a new algorithm, for the (l, d) motif discovery problem in which we find all strings of length l that seems in every string of a provided set of strings with at most d mismatches has been. After proper investigation of the PMS problem, it has been shown that this is an NP-hard exact algorithm. Usually, in the worst-case scenarios, all the known exact algorithms for PMS need exponential time in some of the underlying parameters. In this paper, we proposed a faster approach that reduces the searching time in the sample-driven part of the algorithm. In particular, we used dynamic programming techniques to eliminate the recalculation of the values of some common subtree and introduced some new speedup techniques like using a linked list, reduced l-mers for making the algorithm faster. Due to the use of Linked List as a main speedup technique, we named our proposed algorithm as Linked List Implementation technique of PMS8 (LL-PMS8).

This article considers the third-order connected vehicle systems (CVSs) to implement cooperative formation control for autonomous vehicles. The error dynamics is modeled based on the proposed distributed control protocols for two large classes of general network topologies. The performance indices, such as stability, scalability, speedability, and string stability (4S) indices, are investigated. The necessary and sufficient conditions of stability for CVSs are derived and properties of characteristic roots are discussed. These roots are dependent on information of the given network topology. The sufficient conditions of stability, which are independent of network topology, are given by analyzing the range of eigenvalues of the Laplacian matrix of the corresponding network topology, so scalability is guaranteed. To guarantee fast convergence speed, the upper boundary of stability margin is derived, which is also independent of the size of the network topology and can be conveniently tuned by the controller gains and model parameter. The necessary and sufficient conditions of stability are also achieved for the bidirectional-leader following (BLF) network topology. The conditions of string stability are further derived to ensure that spacing errors (caused by disturbances) decay along the vehicle platoon. Furthermore, combining the conditions of stability, speedability, and string stability, the CVSs are proven to be not only stable but also string stable and quickly convergent. Thus, the 4S indices can be guaranteed. Numerical simulations are provided to validate the theoretical results.

This research proposed a robust Cooperative Adaptive Cruise Control (CACC) to overcome the shortcoming of the existing CACC controllers in dealing with unexpected events, such as malware attack, phishing attack, and DNS tunneling attack, where perception and data received via communication contradict with the reality. The proposed controller combines the advantage of two information flow topologies - All-Predecessor Following (APF) and Predecessor-Leader Following (PLF) control methods - to improve the capability of CACC platoons. The string stability of the proposed CACC controller was proven. The robustness to time delay switch (TDS) attacks was assessed using simulation. The normal cruise was simulated to show the capability of the proposed controller in a wide range of speeds. TDS attacks, which encompassed four different unexpected events, were tested to verify the robustness of the proposed CACC. Results confirmed that the proposed CACC controller is string stable and robust against these TDS attacks without crashing or causing jerks. It also showed that the proposed CACC controller outperformed a state-of-the-art CACC controller.

The twisted string actuator (TSA) has been extensively studied as an alternative to metallic gear reducers due to its low-cost, lightweight, compliance, and highly adjustable actuation characteristics. Owing to these advantages, TSAs were utilized to realize lightweight human-robot interactive robots requiring safe interaction, such as wearables and prosthetics, at a relatively low cost. However, because its force transmission ratio is almost proportional to the length of the string, the string of the conventional TSA must be elongated to achieve high force output. Thus, it is difficult to obtain high force capacity while maintaining a small size. To overcome this limitation, we propose a novel TSA based on parallel bundle-driven actuation to significantly reduce the length of the TSA while achieving high force output. Furthermore, in order to boost the proposed TSA performance, we also present a passive mechanism of an asymmetric behavior compensator. The experimental results show that the force transmission ratio of the proposed TSA is increased by 21%, compared with that of the conventional TSA. Consequently, the proposed TSA has a 44% higher torque capacity with a 37% shorter string than those of the conventional TSA.

A highly precise and timely diagnosis technology can help effectively monitor and adjust the sucker rod production system (SRPS) used in oil wells to ensure a safe and efficient production. The current diagnosis method is pattern recognition of a dynamometer card (DC) based on feature extraction and perceptron. The premise of this method is that the training and target data have the same distribution. However, the training data are collected from a field SRPS with different system parameters designed to adapt to production conditions, which may significantly affect the diagnostic accuracy. To address this issue, in this study, an improved model of the sucker rod string (SRS) is derived by adding fault-parameter dimensions, with which DCs under 16 working conditions could be generated. Subsequently an adaptive diagnosis method is proposed by taking simulated DCs generated near the working point of the target SRPS as training data. Meanwhile, to further improve the accuracy of the proposed method, the DC features are improved by relative normalization and using additional features of the DC position to increase the distance between different types of samples. The parameters of the perceptron are optimized to promote its discriminability. Finally, the accuracy and real-time performance of the proposed adaptive diagnosis method are validated using field data.

Two string links are equivalent up to 2n-moves and link-homotopy if and only if their all Milnor link-homotopy invariants are congruent modulo n. Moreover, the set of the equivalence classes forms a finite group generated by elements of order n. The classification induces that if two string links are equivalent up to 2n-moves for every n > 0, then they are link-homotopic., Deux enlacements d’intervalles sont équivalents à 2n-mouvements et homotopie près si et seulement si leurs invariants d’homotopie de Milnor sont congrus modulo n. De plus, l’ensemble des classes d’équivalence forme un groupe fini engendré par des éléments d’ordre n. Cette classification implique que si deux enlacements d’intervalles sont équivalents à 2n-mouvements près pour tout n > 0, alors ils sont homotopes.

In this paper, we formulate a common design methodology to derive an adaptive cruise control algorithm in order to compensate the effect of the lower level time-lag on the stability. Here the dynamics of the vehicle is approximated by a first order system. The lower level time-lag is referred to the lag associated with the vehicle dynamics to attain the desired condition computed by the adaptive cruise controller. Inclusion of such dynamics reduces the performance of an adaptive cruise control system, both locally and collectively. The solutions presented here can be applied to design a new adaptive cruise control model or to extend any model with velocity dependent spacing function. The derived design method fulfills the over-damped string stability condition in presence of a time-lag in the plant, irrespective of the choice of the equilibrium operating point of linearization. The over-damped characteristic improves both safety and performance. To demonstrate the application of the presented method, two existing models are extended using the derived strategy, viz. the variable time gap and the quadratic range policy. Later the extended models are simulated with rigorous driving conditions, in order to illustrate the improvements in comparison with the respective original models as well as with the extended models using an existing compensation strategy.

Previous studies have either learned drug's features from their string or numeric representations, which are not natural forms of drugs, or only used genomic data of cell lines for the drug response prediction problem. Here, we proposed a deep learning model, GraOmicDRP, to learn drug's features from their graph representation and integrate multiple -omic data of cell lines. In GraOmicDRP, drugs are represented as graphs of bindings among atoms; meanwhile, cell lines are depicted by not only genomic but also transcriptomic and epigenomic data. Graph convolutional and convolutional neural networks were used to learn the representation of drugs and cell lines, respectively. A combination of the two representations was then used to be representative of each pair of drug-cell line. Finally, the response value of each pair was predicted by a fully connected network. Experimental results indicate that transcriptomic data shows the best among single -omic data; meanwhile, the combinations of transcriptomic and other -omic data achieved the best performance overall in terms of both Root Mean Square Error and Pearson correlation coefficient. In addition, we also show that GraOmicDRP outperforms some state-of-the-art methods, including ones integrating -omic data with drug information such as GraphDRP, and ones using -omic data without drug information such as DeepDR and MOLI.

The application of inter-vehicle wireless communi-cation offers significant advantages in terms of improving traffic efficiency and safety while also suffering from unreliable communication links. This paper deals with the problem of event-triggered vehicular platoon control with communication time delay and package dropout, aiming to achieve a suitable trade-off between communication utilization and vehicle following performance. A disturbance based platoon model with communication time delay, package dropout and event-triggered scheme is established. Subsequently, the criterion for co-designing the event-trigger parameters and CACC controller parameters is derived by adopting the parameter space approach with the requirements to ensure individual vehicle internal stability, following accuracy and platoon string stability. To achieve a superior trade-off between communication resource utilization and following performance under unreliable communication condition, the adaptive event-triggered threshold is designed for the varying failure probability. The effectiveness of the proposed adaptive CACC strategy is verified using numerical simulations of a six-vehicle platoon during the FTP 72 drive cycle. The comparison results of three different scenarios show that the adaptive event-triggered scheme guarantees the following performance even when failure probability is 0.4.

The string stability of cooperative adaptive cruise control (CACC) platoons is largely affected by complex driving environment and abnormal driving behaviors. Fast and repetitive driving-state changes always occur during the period of changing driving states (such as leaving a platoon or lane-change), due to errors made in driver decisions or automatic driving system. This research proposes a framework which combines recognition of driving states with platoon operations and risk-prediction in order to reduce disturbance and unnecessary platoon operations resulting from driving-state jitters. First of all, long short-term memory (LSTM) neural networks were used in this research combined with a time-window in order to recognize driving states. Based on this research, the LSTM mode with an added time-window was found to be able to effectively reduce comparatively the jitters of recognition results. After that, an integrated mode which incorporates a recognition mode with danger probabilities was demonstrated to present better platoon operations. Monte Carlo simulation and importance sampling method will be given to predict platoons' and vehicles' trajectories and compute danger probabilities. In addition, an innovative strategy is implemented to identify an additional leader and execute a platoon splitting in order to improve driving smoothness, if a vehicle is recognized in an abnormal car-following state with a high danger-probability. In summary, this research has conducted extensive numerical tests to evaluate performances of the proposed system and the analysis results show that the proposed strategies will effectively increase smoothness and safety for a multi-platooning system.

As cloud computing and Internet of Things (IoT) are becoming more and more deeply integrated, the new secure challenge for IoT data has attracted great attention. Privacy preserving keyword search, as one important secure technique, achieves search over encrypted cloud-based IoT data. Forward security and verifiability are two important security properties for privacy preserving keyword search for cloud-based IoT data. Forward security makes privacy preserving keyword search schemes for cloud-based IoT data able to resist file injection attack, which is one new attack on privacy preserving keyword search when IoT data is updated. Verifiability makes privacy preserving keyword search schemes for cloud-based IoT data able to ensure the validity of the search results returned by cloud. However, to the best of our knowledge, all of existing privacy preserving keyword search schemes at most achieve forward security and partial verifiability. In order to solve this problem, we explore how to simultaneously achieve the forward security and the full verification for intelligent encrypted data processing in cloud-based IoT and propose the first fully verifiable forward secure privacy preserving keyword search scheme for IoT outsourced data. In order to achieve forward security, we construct the secure index based on the hash chain. In each update, the IoT data owner randomly chooses a string as a new state to generate the new trapdoor. The new trapdoor cannot match previous trapdoors. In order to achieve the full verifiability while still maintaining forward security for intelligent encrypted data processing in cloud-based IoT, we design novel authentication construction called Forward Secure Accumulative Authentication Tag (FSAAT). This kind of tag has the incremental property and supports the verification on the basis of efficient data update. We prove that our scheme is secure and efficient through detailed security analysis and experiments.

Traditionally, ensembles of Slepian-Wolf (SW) codes are defined such that every bin of each $n$-vector of each source is randomly drawn under the uniform distribution across the sets $\{0,1,\ldots,2^{nR_X}-1\}$ and $\{0,1,\ldots,2^{nR_Y}-1\}$, where $R_X$ and $R_Y$ are the coding rates of the two sources, $X$ and $Y$, respectively. In a few more recent works, where only one source, say, $X$, is compressed and the other one, $Y$, serves as side information available at the decoder, the scope is extended to variable-rate S-W (VRSW) codes, where the rate is allowed to depend on the type class of the source string, but still, the random-binning distribution is assumed uniform within the corresponding, type-dependent, bin index set. In this expository work, we investigate the role of the uniformity of the random binning distribution from the perspective of the trade-off between the reliability (defined in terms of the error exponent) and the compression performance (measured from the viewpoint of the source coding exponent). To this end, we study a much wider class of random-binning distributions, which includes the ensemble of VRSW codes as a special case, but it also goes considerably beyond. We first show that, with the exception of some pathological cases, the smaller ensemble, of VRSW codes, is as good as the larger ensemble in terms the trade-off between the error exponent and the source coding exponent. Notwithstanding this finding, the wider class of ensembles proposed is motivated in two ways. The first is that it outperforms VRSW codes in the above-mentioned pathological cases, and the second is that it allows robustness: in the event of a system failure that causes unavailability of the compressed bit-stream from one of the sources, it still allows reconstruction of the other source within some controllable distortion.

The paper deals with the consensus problem in a leaderless network of agents that have to reach a common velocity while forming a uniformly spaced string. Moreover, the final common velocity (reference velocity) is determined by the agents in a distributed and leaderless way. Then, the consensus protocol parameters are optimized for networks characterized by a communication topology described by a class of directed graphs having a directed spanning tree, in order to maximize the convergence rate and avoid oscillations. The advantages of the optimized consensus protocol are enlightened by some simulation results and comparison with a protocol proposed in the related literature. The presented protocol can be applied to coordinate agents such as mobile robots, automated guided vehicles (AGVs) and autonomous vehicles that have to move with the same velocity and a common inter-space gap.

Identifying interactions between compound and protein is a substantial part of the drug discovery process. Accurate prediction of interaction relationships can greatly reduce the time of drug development. The uniqueness of our method lies in three aspects:1) it represents a compound with a distance matrix. A distance matrix can capture the structural information, compared with the SMILES string. On the other hand, a distance matrix does not require complex data preprocessing for the molecular structure as the molecular graph representation, and is easier to obtain; 2) it uses SPP(Spatial pyramid pooling)-net to extract compound features, which has been successfully applied in image classification; and 3) it extracts protein features through the natural language processing method (doc2vec) to obtain sequence semantic information. We evaluated our method on three benchmark datasets-human, C.elegans, and DUDE-and the experimental results demonstrate that our proposed model presents competitive performance against state-of-the-art predictors. We also carried out drug-drug interaction (DDI) experiments to verify the strong potential of distance matrix as molecular characteristics. The source code and datasets are available at https://github.com/lxlsu/SPP_CPI.

Formal language theory is defined as computational theory of languages. It provides theoretical aspects of computer science and helps to determine infinite languages in finite number of ways. So, algorithms can be constructed for relevant problems. Then again, decide either a string is existed in language or not under the language. A formal language is an abstraction of the common features of programming languages. Furthermore, a formal language comprises a set of symbols and then some rules of creation by way of these symbols may be combined into entities which is called as sentences. Additionally, a formal language is the grouping the strings accepted by the rules of construction. Even though, many of the formal languages easier than programming languages that they have lot of similar essential properties. It is a great deal to study about programming languages from formal languages. Mathematical structure of languages and its basic properties are the natural languages. It is an integrative area of science.

This paper investigates an event triggered control problem of connected vehicles under multiple cyber-attacks, including denial-of-service attacks (DoS) and deception attacks, which occur aperiodically. Then, a novel event triggered control scheme is proposed in the presence of multiple cyber-attacks. The upper bound of attack frequency, attack length rate of DoS attacks and the conditions of controller gains are obtained. It is proven that the proposed distributed control scheme can realize the asymptotic tracking performance of connected vehicles while avoiding Zeno behavior. A string stability analysis under multiple cyber-attacks is also provided. Simulation results confirm the effectiveness of the event triggered control schemes under multiple cyber-attacks.

In this letter we identify, and propose a solution for, the string stability problem that may arise in frequency droop control schemes for a type of inverter-based microgrid. We consider a previously proposed frequency droop control with secondary control loop and we investigate the effect on the performance due to an increase in the number of inverters connected to the microgrid. To mitigate the observed performance deterioration, we propose a new controller that guarantees string stability of the inverter-based microgrid and show its performance via simulations.

This paper considers the L 2 string stability analysis and controller synthesis for vehicle platooning under jamming attacks and interferences from other communication channels. Jamming attacks and interferences for vehicle platooning systems are modeled as periodic denial of service attacks. Further, the vehicle platooning with denial of service attacks is modeled as a distributed switching system where an average dwell time approach is adopted for the stability analysis. Under the distributed switching system framework, this paper presents a co-design paradigm for the vehicle platooning. The distributed event-triggered method (ETM) and controllers are presented to guarantee L 2 string stability, which can ensure that the output cannot be amplified along the vehicle platooning. Sufficient conditions for L 2 string stability are then provided to guide the co-design of the ETM and controllers, which can be efficiently obtained by solving LMIs. Simulation results are presented to demonstrate the efficacy of the proposed co-design approach in addressing the denial of service attacks for vehicle platooning systems.

Suppose an oracle knows a string $S$ that is unknown to us and that we want to determine. The oracle can answer queries of the form "Is $s$ a substring of $S$?". In 1995, Skiena and Sundaram showed that, in the worst case, any algorithm needs to ask the oracle $\sigma n/4 -O(n)$ queries in order to be able to reconstruct the hidden string, where $\sigma$ is the size of the alphabet of $S$ and $n$ its length, and gave an algorithm that spends $(\sigma-1)n+O(\sigma \sqrt{n})$ queries to reconstruct $S$. The main contribution of our paper is to improve the above upper-bound in the context where the string is compressible. We first present a universal algorithm that, given a (computable) compressor that compresses the string to $\tau$ bits, performs $q=O(\tau)$ substring queries; this algorithm, however, runs in exponential time. For this reason, the second part of the paper focuses on more time-efficient algorithms whose number of queries is bounded by specific compressibility measures. We first show that any string of length $n$ over an integer alphabet of size $\sigma$ with $rle$ runs can be reconstructed with $q=O(rle (\sigma + \log \frac{n}{rle}))$ substring queries in linear time and space. We then present an algorithm that spends $q \in O(\sigma g\log n)$ substring queries and runs in $O(n(\log n + \log \sigma)+ q)$ time using linear space, where $g$ is the size of a smallest straight-line program generating the string., Comment: Accepted for publication in Theoretical Computer Science

Obtaining maximum power output even under adverse contributing factors is the main aim of all reconfiguration techniques that have been reported in literature. Although various attempt has been made to harness maximum energy via physical or electrical PV panel reconfiguration techniques. All these reconfiguration techniques increase the value of output power either by physical or electrical relocation of panel within a column or by placing it at a suitable position in the entire PV array. The placement of PV panel or reconnection of the PV panel at a new location is inspired by some optimization algorithm or by some pattern. This paper proposes a new reconfiguration scheme for maximum power output along with effective shade dispersion, lower voltage drops and lesser cost of cables. Paper also attempted to analyse the pragmatic aspect of PV modules connected under different reconfiguration schemes namely Series Parallel (SP), Total Cross Tied (TCT), Odd-Even (OE), Odd-Even-Prime (OEP), LU SHO, Sudoku etc. and evaluates the consequences of its applicability at field. Although the various reconfiguration scheme has reported to increase the output current and thereby the output power but the increase in capital cost of cables, voltage drop and power losses outweighs the increase in output current and power. Also, if the distance between the rooftop PV array and the location of the String Combiner Unit (SCU) is large, then loses will even be more. A comparative analysis of different reconfiguration techniques under various parameters is performed.

In this study, analysis of photovoltaic (PV) string currents is performed to understand the behavior of the PV array under faults. The whole analysis is summed up in just two simple statements, and an algorithm is devised on the basis of these statements. The proposed algorithm can detect, classify and localize line-to-ground (L-G) & line-to-line (L-L) faults in the PV array. The proposed method can detect faults of any mismatch level and size of the PV array by using only one current sensor per string. It is also capable of working with finite fault-resistance as well as in the presence/absence of blocking diodes. To check the accuracy of the algorithm, it has been thoroughly tested through experimental setup.

A vehicle formation control algorithm is presented to deal with the ineluctable uncertainty and guarantee the vehicle platoon Lyapunov stability (uniform boundedness, uniform ultimate boundedness, and string stability). The uncertainty here is nonlinear, possibly fast time-varying, and is assumed to be within the confines of a known set. Most important of all, the control parameters are optimized to achieve better performances. A Pareto optimal approach is employed to solve such an optimal problem. In the optimal procedure, the control parameters are considered as players and their corresponding value ranges are regarded as the decision sets. The cost function of any player includes three parts: the state cost portion, the time cost portion, and the control cost portion. The optimal parameters minimize the cost functions. The resulting vehicle formation control with optimal parameters impels the vehicle platoon both Lyapunov stability and low cost.

One of the shows invited to attend the 14th Edition of the Iaşi International Theater Festival for Young Audiences (FITPTI), outstanding performance with classic short string puppetry, was performed at the Small Hall of the Luceafărul Theater by String Theater from Great Britain. The London Company relies on the charm of the long strings animating techniques for puppets, maneuvered (manipulated) from a height. The Company started the activity in London, 2011, the founders are Soledad Zarate and Stan Middleton, descendants of several generations of artists specializing in the management and promotion of this type of theater, with Elizabethan roots and fresh puppet infusions. The Insect Circus is a gem show, a demonstration of mastery in the art of puppet handling. A performance that overturns prejudices related to this type of theater, but also a sample of good practice, an example of how the tenderness and clumsiness of these irresistible actors on strings can be enhanced.

String constraint solving refers to solving combinatorial problems involving constraints over string variables. String solving approaches have become popular over the last years given the massive use of strings in different application domains like formal analysis, automated testing, database query processing, and cybersecurity. This paper reports a comprehensive survey on string constraint solving by exploring the large number of approaches that have been proposed over the last decades to solve string constraints., Comment: Under consideration for "ACM Computing Surveys" journal

COVID-19 is caused by the virus SARS-CoV-2 that belongs to the Corona groups. The subgroups of the coronavirus families are α, β, γ, and δ coronavirus. On June 15, 2021, the string λ of SARS-CoV-2 was evaluated as a variant of interest via the World Health Organization. This string has a high prevalence in some parts of South American countries, but it occurred only occasionally in Brazil. This study confirms that mutations in the λ -spike protein can be destroyed the neutralizing antibodies and increase infectivity. Coronaviruses such as SARS-CoV-2 have an evolutionary superpower called “recombination” which permits the mixing of their genomes into novel combinations. Unlike regular mutation, which precedes slowly one change at a time, recombination can produce whole changes in a coronavirus genome. Although right now, δ-variant is a concern, a mixing of λ with other variants such as δ-variant is much more of a concern compared to alone variants. There is another item: the recombination can arise within the sample after it was taken from the infected person, not while it was inside their body.

In this paper, we consider a decentralized failure diagnosis problem for discrete event systems. Each local diagnoser makes a diagnosis decision based on local event observations. A sensor that detects the occurrence of an event may possibly fail due to, for example, aging degradation. It is desirable that the occurrence of any failure string should be correctly detected in the presence of sensor failures. We introduce a new notion of codiagnosability subject to permanent sensor failures, which is defined with respect to not only the set of nondeterministic local observation masks but also the global nondeterministic observation mask. Although the global observation mask is necessary to define codiagnosability, it is not used for performing decentralized diagnosis. The introduced notion of codiagnosability guarantees that the occurrence of any failure string can be correctly detected by a decentralized diagnoser within a bounded number of steps even if permanent sensor failures occur. We develop a method for verifying the codiagnosability property subject to permanent sensor failures. In addition, we compute the delay bound within which the occurrence of any failure string can be detected.

Fuzzy extractor can be used to convert the reading of a noisy non-uniform source into a reliably reproducible and almost uniform string, while reusable fuzzy extractor allows multiple extractions of the same source. In this paper, we propose multi-party fuzzy extractor, called threshold reusable fuzzy extractor, whose execution requires a threshold number of members. New definition and efficient construction are given with security proofs and experimental implementations. It preserves the inherent properties of fuzzy extractor with expanded use in multi-party scenarios. Based on the proposed threshold reusable fuzzy extractor, an application in privacy protection is given to store and share sensitive data by smart contract on blockchain , achieving joint access control via biometric information.

Spiking neural P systems with rules on synapses (RSSNP systems) are a class of computation models which are inspired by the information processing and communication manner of neurons. In this work, we consider labeled RSSNP systems (lRSSNP systems), where each rule is assigned either with a label chosen from an alphabet Σ or with the empty label λ. A string over an alphabet is accepted by an lRSSNP system if the string is processed from left to right by the system in the sense that in a step only rules labeled with the processed symbol or with λ are used (not both), and the system reaches a final configuration in the moment when the whole string is processed. The set of all accepted strings is categorized as the restricted (computations are done with the application of the rules labeled with symbols from the given alphabet) control language and the unrestricted (rules labeled with λ are allowed in the computations) control language of the system. We study the language accepting power of lRSSNP systems using only standard spiking rules by comparing the family of control languages of lRSSNP systems with the families of languages in the Chomsky hierarchy. It is proved that restricted lRSSNP systems can accept no more than context-sensitive languages, and unrestricted lRSSNP systems can accept recursively enumerable languages.

The belief revision process involves several problems considered hard. One of the crucial problems is how to represent to the knowledge base K to consider, as well as how to represent and to add new information , which may even be contradictory to the knowledge base. In this work, both the knowledge base and the new information are in conjunctive normal form. Each clause of a conjunctive normal form is encoded by a string consisting of: 0, 1, *, representing the falsifying assignments of the clause. To use the falsifying assignments of the clauses allows to perform efficiently different logical operators among conjunctive forms. Our belief revision process (K * ) between conjunctive forms is based on solving first the propositional inference, i.e. K = . Based on to count falsifying assignments represented by tertiary chains, an algorithmic proposal is made that allows to determine in a practical way, when (K E ( K * )) is inconsistent. Finally, the time-complexity analysis of our algorithmic proposal is carried out.

Edit distance is one of the most fundamental problems in combinatorial optimization to measure the similarity between strings. Ulam distance is a special case of edit distance where no character is allowed to appear more than once in a string. Recent developments have been very fruitful for obtaining fast and parallel algorithms for both edit distance and Ulam distance. In this work, we present an almost optimal MPC (massively parallel computation) algorithm for Ulam distance and improve MPC algorithms for edit distance. Our algorithm for Ulam distance is almost optimal in the sense that (1) the approximation factor of our algorithm is $1+\epsilon$ 1 + e , (2) the round complexity of our algorithm is constant, (3) the total memory of our algorithm is almost linear ( $\widetilde{O}_\epsilon (n)$ O ˜ e ( n ) ), and (4) the overall running time of our algorithm is almost linear which is the best known for Ulam distance. We also improve the work of Hajiaghayi et al. for edit distance in terms of total memory. The best previously known MPC algorithm for edit distance requires $\widetilde{O}(n^{2x})$ O ˜ ( n 2 x ) machines when the memory of each machine is bounded by $\widetilde{O}(n^{1-x})$ O ˜ ( n 1 - x ) . In this work, we improve the number of machines to $\widetilde{O}(n^{(9/5)x})$ O ˜ ( n ( 9 / 5 ) x ) while keeping the memory limit intact. Moreover, the round complexity of our algorithm is constant and the total running time of our algorithm is truly subquadratic. However, our improvement comes at the expense of a constant factor in the approximation guarantee of the algorithm. This improvement is inspired by the recent techniques of Boroujeni et al. and Chakraborty et al. for obtaining truly subquadratic time algorithms for edit distance.

International audience; In this article, we assess the string stability of seven 2018 model year adaptive cruise control (ACC) equipped vehicles that are widely available in the US market. Seven distinct vehicle models from two different vehicle makes are analyzed using data collected from more than 1,200 miles of driving in car-following experiments with ACC engaged by the follower vehicle. The resulting dataset is used to identify the parameters of a linear second order delay differential equation model that approximates the behavior of the black box ACC systems. The string stability of the data-fitted model associated with each vehicle is assessed, and the main finding is that all seven vehicle models have string unstable ACC systems. For one commonly available vehicle model that offers ACC as a standard feature on all trim levels, we validate the string stability finding with a multi-vehicle platoon experiment in which all vehicles are the same year, make, and model. In this test, an initial disturbance of 6 mph is amplified to a 25 mph disturbance, at which point the last vehicle in the platoon is observed to disengage the ACC. The data collected in the driving experiments is made available, representing the largest publicly available comparative driving dataset on ACC equipped vehicles.

Ring signatures allow a user to sign messages as a member of a set of users, which is called the ring. This primitive ensures that nobody can detect which member in the ring signs the message. Libert, Peters, and Qian (2018) [24] proposed the first tightly secure ring signature scheme with O ( log ⁡ n ) signature size in the random oracle model, where n is the size of a ring. To our knowledge, a tightly secure ring signature scheme has never been reported without depending on the random oracle methodology. In this paper, we propose two generic constructions of tightly secure ring signatures in the standard model. Our first (resp., second) construction is secure in the common reference string model (resp., the plain model). Both of our constructions are secure under the decisional linear assumption over the pairing groups. Our first generic construction has a more efficient instantiation than our second one. While our second generic construction does not have an efficient instantiation, its signature size achieves O ( log ⁡ n ) asymptotically, which is the same as one of the Libert et al.'s scheme.

The hit-to-lead process makes the physicochemical properties of the hit molecules that show the desired type of activity obtained in the screening assay more drug-like. Deep learning-based molecular generative models are expected to contribute to the hit-to-lead process. The simplified molecular input line entry system (SMILES), which is a string of alphanumeric characters representing the chemical structure of a molecule, is one of the most commonly used representations of molecules, and molecular generative models based on SMILES have achieved significant success. However, in contrast to molecular graphs, during the process of generation, SMILES are not considered as valid SMILES. Further, it is quite difficult to generate molecules starting from a certain molecule, thus making it difficult to apply SMILES to the hit-to-lead process. In this study, we have developed a SMILES-based generative model that can be generated starting from a certain molecule. This method generates partial SMILES and inserts it into the original SMILES using Monte Carlo Tree Search and a Recurrent Neural Network. We validated our method using a molecule dataset obtained from the ZINC database and successfully generated molecules that were both well optimized for the objectives of the quantitative estimate of drug-likeness (QED) and penalized octanol-water partition coefficient (PLogP) optimization. The source code is available at https://github.com/sekijima-lab/mermaid.

Under partial shading conditions (PSCs), a series-connected photovoltaic (PV) string often shows multi-peak power-voltage (P-V) characteristics, which indicates a multi-modal distribution of maximum power points (MPPs). The phenomenon brings challenges to the maximum power point estimation (MPPE), since a single model usually cannot perform well in different modes. To address this problem, a real-time shading identification process is proposed to identify the shading information of the applied PV string. The measured data are divided into several fields according to the obtained number of peaks in the P-V curve. Multiple Gaussian process regression (M-GPR) models are then proposed to predict the MPP locus in a specific data field. Experiments are conducted to evaluate the accuracy of the proposed method. Simulation and experimental results show that the shading information enables the proposed M-GPR to obtain more accurate estimation performance compared to its single-model counterparts.

The aim of this paper is to obtain three types of expressions for calculating the probability of implementing palindromic digit combinations on a finite equally possible combination of zeros and ones. When calculating the probability of implementation of palindromic digit combinations, the classical definition of probability is applied. The main results of the paper are formulated in the form of three theorems. Moreover, the consequences of these theorems and typical examples of calculating the probability of implementing palindromic digit combinations in a data string of binary code are considered. All formulated theorems and their consequences are accompanied by proofs. The obtained numerical results of the paper can be used in the analysis of numerical computer data written as a binary code string in BIN format files. It should also be noted that the combinatorial expressions described in the article for calculating the number of palindromic combinations of digits in the binary number system can be used in number theory and in various branches of computer science. The development of these results from the point of view of obtaining an expression for calculating the number of palindromic combinations of digits in the binary number system contained in two-dimensional data arrays is also of immediate theoretical and practical interest. However, these results are not presented in this work, but they can be considered in subsequent publications.