The photovoltaic virtual synchronous generator (PV-VSG) solves the problem of lack inertia in PV power-generation system.The existing plants without energy storage are required to participate power grid's frequency modulation (FM), but PV-VSGs with have high requirements for coordinated control.Therefore, active reserve PV-VSG (APR-PV-VSG) is studied.Based on different methods obtain maximum point (MPP), peer-to-peer and master-slave APR-PV-VSG strategies proposed.The inverters deviated from...

Web recommendations provide personalized items from massive catalogs for users, which rely heavily on retrieval stages to trade off the effectiveness and efficiency of selecting a small relevant set billion-scale candidates in online digital platforms. As one largest Chinese search engine news feed providers, Baidu resorts Deep Neural Network (DNN) graph-based Approximate Nearest Neighbor Search (ANNS) algorithms accurate relevance estimation efficient items. However, current at fails...

Analysis of pavement deterioration is critical for road maintenance. Many section-based performance evaluation methodologies have been investigated to determine the deteriorating tendency from a macro perspective. However, little research shed light on refined analysis single distress, which valuable daily and preventive This paper proposed deep-learning-based tracking framework construct large-scale continuous observation data set every distress. A deep learning model applied detect six...

Summary In recent years, Docker container technology is being applied in the field of cloud computing at an explosive speed. The scheduling resources has gradually become a research hotspot. Existing big data and storage platforms apply with traditional virtual machine technology, which often results low resource utilization, long time for flexible scaling expanding clusters. this paper, we propose improved algorithm applications named Kubernetes‐based particle swarm optimization(K‐PSO)....

In modern internet industries, deep learning based recommender systems have became an indispensable building block for a wide spectrum of applications, such as search engine, news feed, and short video clips. However, it remains challenging to carry the well-trained models online real-time inference serving, with respect time-varying web-scale traffics from billions users, in cost-effective manner. this work, we present JIZHI - Model-as-a-Service system that per second handles hundreds...

The application of deep learning algorithms for subsurface distress detection using ground penetrating radar (GPR) data has seen extensive utilization. However, a significant impediment arises because the challenge in acquiring ground-truth samples. This scarcity labeled leads to incomplete training and gives rise critical concern with respect over-fitting. Generating additional samples through numerical simulation constitutes one most efficient methods overcome insufficient GPR If both real...

Due to the characteristics of intermittent photovoltaic power generation and fluctuations in distributed generation, grid-connected systems are usually equipped with energy storage units. Most structures combined used as DC side. At same time, virtual synchronous generators have been widely due their inertial damping frequency voltage regulation. For PV-storage system based on generators, existing control strategy has unclear function allocation, inverter output power, high requirements for...

Abstract In this paper, we propose a target detection and localization method on distributed monopulse arrays for tracking radar. An optimized mainlobe jamming (MLJ) cancellation filter was designed by maximizing the power ratio of received siackgnal to jamming-plus-noise. By exploiting different correlation characteristics between echo MLJ antennas, is able cancel maintain echo. applying identical sum-difference beams, can be cancelled, maintained simultaneously. Hence, simply detect locate...

Pavement roughness serves as a crucial indicator for evaluating road performance. However, traditional measurement methods, such laser detection vehicles, are limited to providing values single profile, failing capture the overall pavement condition comprehensively. To address this limitation, study utilized high-precision light and ranging technology (LiDAR) acquire three-dimensional point cloud data 25 km section in Shanghai. Road elevations were extracted from different lateral survey...

This paper proposes a multi-agent query refinement approach to comprehensively track the users' behaviors. Based on approach, this creates personalized ontology profile, with which it refines and expands initial query. We use four agents in our entire system. First, we Client Agent verify user identities by creating union account monitor whether device is ready run profile creation task; then Personalized Ontology Profile create not only can consider Knowledge structure but also behavior....

In wireless network, backbone network plays an important role on forwarding data. Further, in order to reduce the delay and save energy, minimum connected dominating set (MCDS) is effective way construct a backbone. However, it NP-hard MCDS. this paper, we propose efficient centralized algorithm, redundancy (RCDS), relatively optimal with economic computation cost of O(Δ2n) Specifically, local strategy employed obtain maximal independent (MIS) firstly, then virtual generated by adding joint...

Downward looking ground penetrating radar (GPR) has been considered a viable technology for landmine detection. For such GPR with the antennas positioned very close to surface, reflections from i.e., bounce, are strong and can completely dominate weak returns shallowly buried plastic mines. Hence, one of key challenges using GPRs detection is remove bounce as possible without altering return. In this paper, we first review existing removal algorithms. Then two newly devised adaptive...

This paper proposes a multi-agent personalized ontology profile based user preference construction method to comprehensively track the users' long-term behaviors and short-term by consider browsing behavior, pace times, as well using two kinds of different strategies-"Sliding-Time-Window Update Strategy" "Time-Based-Forgetting Function Strategy", so construct dynamic on profile. There are four agents in our entire system, with all communicating among each other, agent having its own...

A good emotion has a great impact on health and classification of emotions is very important to improve the quality life. In this paper, recognition system based CW Doppler radar with subspace KNN classifier which was selected as machine learning algorithm classify proposed. experiment, four including joy, sadness, neutral, fear were triggered by videos. The accuracy rates two, three 85%, 74.6% 67.4% respectively. These results suggest that proposed scheme suitable for non-contact recognition.

In military and civilian communications, signals are often interfered by hostile jamming or illegal transmission. these situations, determining the modulation format of mixed is a challenging task, which tackled using three step algorithm named PFCC(PCA, FICA, Cumulants Based Classification Algorithm) in this paper. first step, centering whitening conducted principal component analysis (PCA) to suppress noise. second separated fast independent (FICA), can transform received signal into...

Due to the influence of context information on user behavior, context-aware recommendation system (CARS) has attracted extensive attention in recent years. The most advanced maps original multi-field features into a shared hidden space and then simply connects it deep neural network (DNN) or other specially designed networks. However, for different areas, ability modeling complex interactions sufficiently flexible explicit way is limited by simple unstructured combination feature fields....

The graph neural network (GNN) based approach has been successfully applied to session-based recommendation tasks. However, in the face of complex and changing real-world situations, existing session algorithms do not fully consider context information user decision-making; furthermore, importance for behavior model widely recognized. Based on this, this paper presents a context-aware gated networks (CA-GGNNs). First, sequence as data structure. Second, embedding vector representation each...

Ground penetrating radar (GPR) has been a widely used nondestructive testing method for pavement structure conditions. Random scattering occurs when GPR waves propagate, leading to complex reflected signals with large amount of clutter from medium anomalies. The original amplitude profile cannot fully display the physical parameters and geometric dimensions subsurface anomalies, which could lead misjudgment omission distress. To overcome these challenges, we obtain instantaneous frequency,...

Knowledge about the growth vigor of grapevine rootstocks is required for scion-based rootstock selection and breeding. We performed this trial aiming to evaluate multiplication several rootstocks. Thirty-one genotypes were compared on their characteristics, phenological periods, indicators across three consecutive seasons. The results suggested that cuttings most had callus-forming indices (CFIs) over 0.5 except ‘188-08’ (0.28). rooting rate ‘420A’ was 5%, while rest greater than 48%....

Nowadays ultra wideband ground penetrating radar (GPR) is widely used in landmine detection. For shallowly buried plastic landmines, the bounce usually much stronger than weak return from landmines and their arrival time very close with each other, so removal important for following detection, imaging target recognition. In this paper, kernel independent component analysis (KICA) first introduced to GPR. A novel scheme proposed automatic (IC) selection, which vital any ICA based algorithms....

In recent years the extreme growth of digital documents brought to light need for novel approaches and more efficient techniques improve precision recall IR systems. this paper I proposed a Similarity Matching Algorithm Ontology-Based Semantic Information Retrieval Model measure whether two ontologies are matching or not from name, attribute theme concepts. Simulation shows that same recall, algorithm can increase flexibility compared with traditional semantic similarity methods.

Co-occurrence patterns among different deep road distresses (distresses below the surface) play a pivotal role in maintenance. It is essential for sustainable development of performance and draws much attention from maintenance departments. However, current work mainly focused on rapid detection evaluation pavement distress. Few studies shed light relationship them. In this paper, over 200 km field tests were conducted 87 sections highways China by ground-penetrating radar (GPR). Based...