Social media has become a prevalent issue that has attracted the attention of both society and researchers. Social media platforms have undergone tremendous expansion over the past ten years, offering users the abilit...
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As the utilization of supercapacitors in power system applications continues to increase, it is important to observe their behavior under transient and long-term operations in order to understand their impact on power...
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Microfiche was a common format used in microforms reproductions of documents, extensively used for archival storage before the move to digital formats. While contemporary documents are still available for digitization...
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A case study on modeling adequacy of a grid in presence of renewable resources based on grid-forming converters (GFCs) is the subject matter of this paper. For this purpose, a 4-machine 11-bus IEEE benchmark model is ...
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ISBN:
(数字)9798350381832
ISBN:
(纸本)9798350381849
A case study on modeling adequacy of a grid in presence of renewable resources based on grid-forming converters (GFCs) is the subject matter of this paper. For this purpose, a 4-machine 11-bus IEEE benchmark model is modified by considering GFCs replacing synchronous generators that led to unstable subsynchronous oscillations (SSOs). We aim to: (a) understand if transmission network dynamics should be considered in such cases, (b) revisit the space-phasor-calculus (SPC) in d-q frame under balanced condition that captures such phenomena and lends itself to eigenvalue analysis, and (c) emphasize limitations of such models while underscoring their importance for large-scale power system simulations. Time-domain and frequency-domain results from SPC and quasistationary phasor calculus (QPC) models are compared with electromagnetic transient (EMT)-based simulations. It is shown that models with transmission line dynamics in SPC framework can capture the SSO mode while QPC models that neglect these dynamics fail to do so.
As increasingly more APIs are published on the Internet, effective API recommendation remains a challenge yet highly demanded for mashup developers. This paper formalizes API recommendation as an incremental context-a...
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ISBN:
(数字)9798350368512
ISBN:
(纸本)9798350368529
As increasingly more APIs are published on the Internet, effective API recommendation remains a challenge yet highly demanded for mashup developers. This paper formalizes API recommendation as an incremental context-aware recom-mendation problem starting from a set of descriptive words and a set of APIs selected to date, supported by a fine-grained mashup-oriented knowledge graph (MKG). In contrast to traditional knowledge graphs where nodes are coarse-grained entities, entity-and relationship-encapsulated features are extracted as first-class citizens in an MKG, so that implicit feature relationships can be turned into explicit structural relationships. Two models are trained to learn fine-grained API selection strategies through path type patterns in the MKG, starting from intended descriptions and APIs selected, respectively. Extensive experiments over real-world datasets have demonstrated the effectiveness of the method.
Social Network sites are fertile ground for several polluting phenomena affecting online and offline spaces. Among these phenomena are included echo chambers, closed systems in which the opinions expressed by the peop...
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Chinese Spelling Check (CSC) aims to detect and correct Chinese spelling errors. Most Chinese spelling errors are the misuse of semantically, phonetically or graphically similar characters. Previous state-of-the-art w...
Chinese Spelling Check (CSC) aims to detect and correct Chinese spelling errors. Most Chinese spelling errors are the misuse of semantically, phonetically or graphically similar characters. Previous state-of-the-art works on the CSC task pursue transitions from misspelled sentences to correct sentences directly. However, it is difficult to force the current CSC methods to find the correct answer at one run. Thus, we propose a simple and effective method for CSC task by making fully use of the trained model to generate multiple candidate sentences and simply ranking to select the best, in which no additional training and parameters are required. The experimental results show that our approach outperforms previous methods and achieves the state-of-the-art performances.
Open-set face recognition describes a scenario where unknown subjects, unseen during training stage, appear on test time. Not only it requires methods that accurately identify individuals of interest, but also demands...
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A swarm of unmanned aerial vehicles (S-UAVs) consists of UAVs flying together with the target of accomplishing a certain task in a faster and more reliable way as compared to a single UAV. In a crisis scenario, UAVs h...
A swarm of unmanned aerial vehicles (S-UAVs) consists of UAVs flying together with the target of accomplishing a certain task in a faster and more reliable way as compared to a single UAV. In a crisis scenario, UAVs have been widely used in rescue missions. Clustering is one of the most reliable routing schemes for S-UAVs. The UAVs are grouped into clusters with a cluster-head (CH) and cluster-members (CM). The CH plays a major role in clustering schemes as it handles all inter-cluster communication. In a crisis case, any UAV is at risk of getting non-functional, thus resulting in a disconnected cluster. This paper proposes a new clustering scheme based on K-means and weighted formulas. The K-means protocol is applied to generate pilot phase clusters. Afterward, whenever the metrics of the networks are established, the weighted formula is applied for cluster formation and CH selection. The weighted formula is based on the performance index, the relative movement, and the remaining energy. To ensure end-to-end communication despite CH non-functionality, our proposed protocol selects a redundant CH for every CH. This protocol had been simulated using MATLAB. The results obtained and analyzed towards the end of this paper demonstrate that the proposed scheme is very promising.
Traffic congestion represents a daunting challenge for all facets of urban development, as well as represents a universal problem in all urban areas, to various extents. In recent years, many cities have adopted the u...
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ISBN:
(数字)9798350368130
ISBN:
(纸本)9798350368147
Traffic congestion represents a daunting challenge for all facets of urban development, as well as represents a universal problem in all urban areas, to various extents. In recent years, many cities have adopted the use of Intelligent Transport Systems (ITS) to manage traffic congestion. These systems are indeed useful, but they are mainly geared to predict real-time traffic congestion, yielding to a certain short-sightedness in our prediction model. Through the use of Time Series Analysis, and Regression models for traffic congestion prediction, we posit that we can address the issue. The data that these models were trained on derives from two datasets, namely a dataset from Kaggle and another from the road traffic footage of Tirana. The data then points to Gated Recurrent Units (GRU) being a more accurate time series category, and Support Vector Regression (SVR) to be a better performer than linear regression.
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