The power grid is undergoing a transformation from synchronous generators(SGs) toward inverter-based resources(IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challeng...
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The power grid is undergoing a transformation from synchronous generators(SGs) toward inverter-based resources(IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challenges to grid resilience. Virtual power plants(VPPs) are emerging technologies to improve the grid resilience and advance the transformation. By judiciously aggregating geographically distributed energy resources(DERs) as individual electrical entities, VPPs can provide capacity and ancillary services to grid operations and participate in electricity wholesale markets. This paper aims to provide a concise overview of the concept and development of VPPs and the latest progresses in VPP operation, with the focus on VPP scheduling and control. Based on this overview, we identify a few potential challenges in VPP operation and discuss the opportunities of integrating the multi-agent system(MAS)-based strategy into the VPP operation to enhance its scalability, performance and resilience.
The rapid advancement and proliferation of Cyber-Physical Systems (CPS) have led to an exponential increase in the volume of data generated continuously. Efficient classification of this streaming data is crucial for ...
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Internet of Things (IoT) enabled Wireless Sensor Networks (WSNs) is not only constitute an encouraging research domain but also represent a promising industrial trend that permits the development of various IoT-based ...
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Reduplication is a highly productive process in Bengali word formation, with significant implications for various natural language processing (NLP) applications, such as parts-of-speech tagging and sentiment analysis....
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Image tampering detection and localization have emerged as a critical domain in combating the pervasive issue of image manipulation due to the advancement of the large-scale availability of sophisticated image editing...
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Image tampering detection and localization have emerged as a critical domain in combating the pervasive issue of image manipulation due to the advancement of the large-scale availability of sophisticated image editing *** manual forgery localization is often reliant on forensic *** recent times,machine learning(ML)and deep learning(DL)have shown promising results in automating image forgery ***,the ML-based method relies on hand-crafted ***,the DL method automatically extracts shallow spatial features to enhance the ***,DL-based methods lack the global co-relation of the features due to this performance degradation noticed in several *** the proposed study,we designed FLTNet(forgery localization transformer network)with a CNN(convolution neural network)encoder and transformer-based *** encoder extracts local high-dimensional features,and the transformer provides the global co-relation of the *** the decoder,we have exclusively utilized a CNN to upsample the features that generate tampered mask ***,we evaluated visual and quantitative performance on three standard datasets and comparison with six state-of-the-art *** IoU values of the proposed method on CASIA V1,CASIA V2,and CoMoFoD datasets are 0.77,0.82,and 0.84,*** addition,the F1-scores of these three datasets are 0.80,0.84,and 0.86,***,the visual results of the proposed method are clean and contain rich information,which can be used for real-time forgery *** code used in the study can be accessed through URL:https://***/ajit2k5/Forgery-Localization(accessed on 21 January 2025).
Most research works nowadays deal with real-time Internetof Things (IoT) data. However, with exponential data volume increases,organizations need help storing such humongous amounts of IoT data incloud storage systems...
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Most research works nowadays deal with real-time Internetof Things (IoT) data. However, with exponential data volume increases,organizations need help storing such humongous amounts of IoT data incloud storage systems. Moreover, such systems create security issues whileefficiently using IoT and Cloud Computing technologies. Ciphertext-Policy Attribute-Based Encryption (CP-ABE) has the potential to make IoT datamore secure and reliable in various cloud storage services. Cloud-assisted IoTssuffer from two privacy issues: access policies (public) and super polynomialdecryption times (attributed mainly to complex access structures). We havedeveloped a CP-ABE scheme in alignment with a Hidden HierarchyCiphertext-Policy Attribute-Based Encryption (HH-CP-ABE) access structure embedded within two policies, i.e., public policy and sensitive *** this proposed scheme, information is only revealed when the user’sinformation is satisfactory to the public policy. Furthermore, the proposedscheme applies to resource-constrained devices already contracted tasks totrusted servers (especially encryption/decryption/searching). Implementingthe method and keywords search resulted in higher access policy privacy andincreased security. The new scheme introduces superior storage in comparisonto existing systems (CP-ABE, H-CP-ABE), while also decreasing storage costsin HH-CP-ABE. Furthermore, a reduction in time for key generation canalso be ***, the scheme proved secure, even in handling IoT datathreats in the Decisional Bilinear Diffie-Hellman (DBDH) case.
Foundation models(FMs) [1] have revolutionized software development and become the core components of large software systems. This paradigm shift, however, demands fundamental re-imagining of software engineering theo...
Foundation models(FMs) [1] have revolutionized software development and become the core components of large software systems. This paradigm shift, however, demands fundamental re-imagining of software engineering theories and methodologies [2]. Instead of replacing existing software modules implemented by symbolic logic, incorporating FMs' capabilities to build software systems requires entirely new modules that leverage the unique capabilities of ***, while FMs excel at handling uncertainty, recognizing patterns, and processing unstructured data, we need new engineering theories that support the paradigm shift from explicitly programming and maintaining user-defined symbolic logic to creating rich, expressive requirements that FMs can accurately perceive and implement.
The piezoelectric coupling principle is widely used(along with capacitive coupling and piezoresistive coupling)for MEMS *** MEMS accelerometers are used primarily for vibration *** piezoelectric MEMS accelerometers of...
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The piezoelectric coupling principle is widely used(along with capacitive coupling and piezoresistive coupling)for MEMS *** MEMS accelerometers are used primarily for vibration *** piezoelectric MEMS accelerometers offer the merits of heavy-metal-free structure material and simple microfabrication *** importantly,polymeric piezoelectric MEMS accelerometers may be the basis of novel applications,such as fully organic inertial sensing microsystems using polymer sensors and organic integrated *** paper presents a novel polymer piezoelectric MEMS accelerometer design using PVDF films.A simple and rapid microfabrication flow based on laser micromachining of thin films and 3D stereolithography was developed to fabricate three samples of this *** proof-of-concept experiments,the design achieved a sensitivity of 21.82 pC/g(equivalent open-circuit voltage sensitivity:126.32 mV/g),a 5%flat band of 58.5 Hz,and a noise density of 6.02µg/√***,this design rivals state-of-the-art PZT-based counterparts in charge sensitivity and noise density,and it surpasses the performance capabilities of several commercial MEMS ***,this design has a 10-times smaller device area and a 4-times larger flat band than previous state-of-the-art organic piezoelectric MEMS *** experimentally validated performance metrics demonstrate the promising application potential of the polymeric piezoelectric MEMS accelerometer design presented in this article.
Most optimization problems of practical significance are typically solved by highly configurable parameterized *** achieve the best performance on a problem instance,a trial-and-error configuration process is required...
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Most optimization problems of practical significance are typically solved by highly configurable parameterized *** achieve the best performance on a problem instance,a trial-and-error configuration process is required,which is very costly and even prohibitive for problems that are already computationally intensive,*** problems associated with machine learning *** the past decades,many studies have been conducted to accelerate the tedious configuration process by learning from a set of training *** article refers to these studies as learn to optimize and reviews the progress achieved.
Integrated sensing and communication (ISAC) is a promising solution to mitigate the increasing congestion of the wireless spectrum. In this paper, we investigate the short packet communication regime within an ISAC sy...
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