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As one of the most fundamental problems in graph data mining, the densest subgraph discovery (DSD) problem has found a broad spectrum of real applications, such as social network community detection, graph index construction, regulatory motif discovery in DNA, fake follower detection, and so on. Theoretically, DSD closely relates to other fundamental graph problems, such as network flow and bipartite matching. Triggered by these applications and connections, DSD has garnered much attention from the database, data mining, theory, and network communities. In this tutorial, we first highlight the importance of DSD in various applications and the unique challenges that need to be addressed. Subsequently, we classify existing DSD solutions into several groups, which cover around 50 research papers published in many well-known venues (e.g., SIGMOD, PVLDB, TODS, WWW), and conduct a thorough review of these solutions in each group. Afterwards, we analyze and compare the models and solutions in these works. Finally, we point out a list of promising future research directions. We believe that this tutorial not only helps researchers have a better understanding of existing densest subgraph models and solutions, but also provides them insights for future study.

This article proposes a sliding-mode-observer (SMO)-based control strategy to regulate the dc-link voltage for a three-phase two-level active front end (AFE). The SMO is designed for the voltage control loop to estimate the external load which is abruptly connected to the AFE dc-link and consequently causes the dc-link voltage fluctuation. The estimated load value is used to compensate the voltage loop controller, therefore, the voltage loop gains more robustness against the load perturbation and its disturbing effect is greatly reduced. The effectiveness and advantage of the proposed control strategy has been verified through theoretical analysis, simulations, and the real-application experiments conducted on a 5 KVA laboratory AFE. The results show that the proposed control strategy provides obvious improvement of the dc-link voltage control performance comparing with the conventional PI controller and demonstrates stronger robustness against the operating point variations caused by the changes in external load and dc-link capacitance.

Top-t queries, which return t results with the highest scores according to the user’s preferences, have been extensively studied. However, many studies often fail to take into account the social relationships among users, and close social relationships usually guarantee the consistency of users’ preferences. Many real-world applications, such as community-based product recommendation services, require such queries. In this paper, we propose a new problem: the k-truss community most favorites querying problem based on user top-t favorites. Specifically, both the k-truss community and the corresponding most favorite object are retrieved. We first present the baseline solution to the problem. The main idea is to find the same object in the top-t favorites of the users in the social network and build the k-truss community for these users with the same preferences. Furthermore, we propose a reverse query algorithm to speed up the processing of the k − t CMF querying problem by filtering users in the social network. The experiment results on both real and synthetic datasets significantly demonstrate that the proposed solutions are efficient and scalable.

With the participation of a significant number of plug-in electric vehicles (PEVs), it is really challenging to achieve economic-effective in load frequency control (LFC) while sustaining satisfiable system performance. To tackle this challenge, a new distributed economic model predictive control (DEMPC) strategy is proposed for the LFC with the large-scale PEV participation. In the light of the vulnerability of LFC to false data injection (FDI) attacks, a model-based $\chi ^{2}$ intrusion detection unit is integrated with the proposed DEMPC. This model-based intrusion detection unit can not only monitor the FDI attacks, but also generate a model-based state prediction for the DEMPC once the data is identified as compromised. Then, an event-triggering mechanism is presented to reduce the computation and communication burdens of each area controller. Simulation studies of a four-area power system are conducted and the results validate the effectiveness of the proposed intrusion detection unit and event-triggering conditions for the DEMPC.

Modular converters such as the multilevel cascaded H-bridge (CHB) are an attractive option for multiple applications mainly because of inherent modularity and fault-tolerant operation. This article is focused on the CHB converter operating with unbalanced conditions (different dc voltages and/or modulation indexes). Under these circumstances, applying the conventional control and modulation strategies, the output voltage harmonic spectrum is degraded. In this article, a generalized variable-angle phase-shifted pulsewidth modulation (PS-PWM) technique for CHB converters with a large number of power modules $(>\!\!3)$ is presented. The method considers all possible cells’ combinations to form groups and assigns the role of each cell in the group. This cell role defines the identifier of the cell in the variable-angle PS-PWM technique. In the steady state, in each group of cells, the harmonic distortion of the CHB output voltage located at twice the carrier frequency $f_c$ is eliminated, while the distortion at $4f_c$ is also diminished. Experimental results show how the proposed technique achieves superior harmonic performance without introducing any significant disadvantage.

The sound absorption and sound transmission loss performances of the natural woods, hard and soft processed woods with attachment of the various natural or waste materials were investigated in the present study using impedance tube with American Society for Testing Material (ASTM) standards. The sound absorption performances of all natural and all hard processed woods were very poor. It was found that filter mat made by the coconut fibre was the best material for sound absorption improvement of the hard processed woods. The sound absorption performance of the soft processed wood (cork) was better than all natural and all hard processed woods. Among all tested woods, it was found that the cork with attached tea bag made by corn fibre is the best selection for sound absorption application. The transmission loss performances of all natural woods were good. The effects of various materials on the transmission loss performances of all hard processed woods were not very significant. For cork with and without attachment of various materials, their transmission loss performances were not as good as the hard processed woods. Among all tested woods, it was found that Pterocarpus soyauxii and Quercus spp. (natural woods) are the best woods to be used in those applications when prevention of sound transmission is needed. It is recommended that cork is the best wood to be used in those applications where sound absorption and prevention of sound transmission are needed at the same time due to its good sound absorption performance while its ability on prevention of the sound transmission is also acceptable.

This paper proposes a dynamic sliding mode control (SMC) approach to the robust voltage regulation of dc–dc boost converters by using interval type-2 fuzzy neural networks (IT2FNNs). First, uncertainties caused by the perturbation of the input inductor and the output capacitor are represented with some bounded approximation errors, by the utilization of a Takagi–Sugeno (T–S) fuzzy modeling approach. Based on the represented model of the boost converter, a new type of sliding surface is designed depending on the duty cycle and reference inputs of the converter. Then, a dynamic SMC law is designed, by considering that the perturbation of the uncertain parameters, including input inductor, output capacitor, load resistor, and input voltage, is bounded. Meanwhile, we adopt an exponential plus power approaching law in the sliding mode controller for fast reachability of the sliding surface and a small chattering in the duty cycle input. Moreover, in terms of the considered uncertainties, a novel IT2FNN-based dynamic SMC law is derived, by applying simplified ellipsoidal-type membership functions in the type-2 fuzzy neural network. To improve the capacity to manage the uncertainties, some online learning algorithms for the updating of the IT2FNN are designed by a gradient descent method (GDM), without the requirement of the boundedness of the uncertainties. The resulting tracking error system is synthesized to be bounded stable based on the designed IT2FNN-based dynamic SMC. Finally, the effectiveness of the proposed adaptive IT2FNN-based dynamic SMC method is verified by some comparative simulation results.

This paper presents voltage regulation and current tracking control strategies for three phase two-level grid-connected power converters. By using power-invariant Park’s transformation, an averaged mathematical model of power converters is obtained in dq synchronous reference frame. Then a novel control strategy using adaptive control and ${H}_{\infty }$ technique is proposed to regulate the dc-link output voltage as well as track a desired current reference for three-phase power rectifiers. More specifically, an efficient adaptive controller is established in the external loop for regulating dc-link output voltage in the presence of external disturbances. A set of ${H}_{\infty }$ controllers are designed in the internal loop to force the input currents track their desired values. Finally, simulation results obtained from the proposed control method are presented, analyzed, and compared with that of sliding mode control, and the superiority of the proposed control laws is verified.

DC/DC power converters are critical parts of railway applications because they are required in on-board, off-board, and communication systems. Traditionally sliding-mode control is only insensitive to the matched disturbances, and the system performance is reduced when mismatched disturbances appear. This study develops a non-linear disturbance observer (NDO)-based adaptive non-singular fast terminal sliding-mode control strategy for DC/DC buck converter with mismatched disturbances. The proposed strategy exhibits the following three attractive features. Firstly, the observer can estimate the matched and mismatched disturbances in finite time. Next, by taking the estimations of the disturbances into account, a sliding-mode variable is designed, the system reach the sliding-mode surface in finite time, and the output voltage tracking error converges to zero in finite time. Then, the convergence rates of the sliding-mode variable and output voltage tracking error are faster compared with those of the NDO-based non-singular terminal sliding-mode (NTSM) controller. Finally, with the adaptive law, the control gain is adjusted to an appropriate value with respect to disturbances, and the chattering of the control signal is reduced. Experimental results show that comparing with the NDO-based NTSM controller, the proposed method exhibits better steady-state performance and dynamic performance including robustness and disturbance rejection ability.

Energy storage systems (ESSs) facilitate utility grid operations on various levels, which include power generation, power transmission, and power distribution. The benefits of these systems produce an overall improvement of grid stability, security, and resilience; cost reductions resulting from the need for less expensive reserve equipment; enhanced power quality; and customer satisfaction. In line with the development of the technology, pricing standards, and operator familiarity, ESSs' role in future utility operations will be substantial. This article summarizes ESS applications and control and specific issues related to power electronic converter (PEC) applications.

This study constructed an urban traffic noise map (including road and railway traffic noises) of the Panyu District in Guangzhou City by combining field measurement and numerical modeling methods. This noise map was then used to identify the area covered by different noise quality levels and the compliance rate of traffic noise in various acoustic environment functional areas throughout the day, night and day–night. The results showed that traffic noise pollution along the traffic arteries was severe. The area with heavy noise pollution was as large as 157.5 km2 (29.72%) and 146.2 km2 (27.59%) in the day and night, respectively. The total area of the Panyu District that complied with the noise limit in the day and night was 326.5 km2 (61.62%) and 87.2 km2 (16.46%), respectively. The outcomes of the current efforts can provide new technical guidelines for novel construction and analysis methods for large scale urban traffic noise mapping.

In this paper, one new distributed load frequency regulation approach is proposed for smart power system operation under two specific practical constraints, including the limited communication resource and speed droop parametric uncertainty. To address these two constraints, the co-design of event-triggering communication scheme and distributed model-based controller is studied. Instead of using zero-order holders, the proposed model-based scheme is able to extend the maximum allowable time interval and thus reduce communication bandwidth usage. In the meantime, the proposed co-design scheme is able to get the model-based control parameters and event-triggering condition metrics simultaneously. This can loosen the conservation in the choice of control gains and event-triggering parameters faced by existing approaches where the control gains are fixed in prior. Comparisons on the multiple-area system confirm that this designed load frequency regulation method significantly reduces the number of required data transmissions without sacrificing the dynamic performance of the frequency and tie-line power. It is also shown that the proposed approach has great robustness to speed droop coefficient uncertainty.

In this article, a linear extended state observer (LESO) based second-order sliding mode (SOSM) control strategy with the direct power control is proposed for a three-phase neutral-point-clamped (NPC) power converter connected to a dc microgrid. Comparing with the PI control method, the proposed approach implements the advanced SOSM controller into the voltage regulation loop and instantaneous power tracking loop to enhance the dynamic and steady state performance. Furthermore, saturation function is applied in the SOSM method to weaken the chattering phenomenon. On the other hand, since the dc load is regarded as an external disturbance, an efficient LESO is designed in the voltage regulation loop to reject this disturbance. The design process of the proposed control strategy is shown based on the continuous averaged model of the NPC converter. Finally, comparison experiments among PI, LESO-based PI, and proposed LESO-based SOSM control strategies are implemented, which validate the superiority of the proposed approach.

In the distributed load frequency control (DLFC) scheme, the compromised areas by attackers may endanger the stable and reliable operation of the entire power system. A credibility-based secure DLFC strategy is in this work proposed to sustain the stable operation of the power system under false data injection attacks. In this secure DLFC method, the gradientvariation- based credibility metrics are defined to detect potential attacked measurements. Then, the communication isolation decisions are made based on the adaptive thresholds. To compensate the impact of the communication isolation of misbehaving areas, predictions of future measurements by using the average gradient variation of stored healthy data are feeded back to the area controller. Simulation results of a four-area power system show the proposed secure DLFC can identify and cut off the communication of the misbehaving areas and still maintain the stability of the power system.