Process monitoring plays a pivotal role in elucidating the intricate interplay among process, structure, and property in additive manufacturing production. The control of powder spreading affects not only particle adh...
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Crude oil prices (COP) profoundly influence global economic stability, with fluctuations reverberating across various sectors. Accurate forecasting of COP is indispensable for governments, policymakers, and stakeholde...
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Multi-path avoidance routing for wireless sensor networks (WSNs) is a secure routing paradigm against adversaries with unbounded computational power. The key idea of avoidance routing is to encode a message into sever...
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Multi-path avoidance routing for wireless sensor networks (WSNs) is a secure routing paradigm against adversaries with unbounded computational power. The key idea of avoidance routing is to encode a message into several pieces by the XOR coding, and each piece is routed via different paths. Then, an adversary cannot obtain the original message unless she eavesdrops on all message pieces from all the paths. In this paper, we extend such an approach into secure multicast routing, which is a one-to-many communication primitive. To this end, we propose the multi-tree-based avoidance multicast routing protocol (AMRP) for WSNs, in which a set of adversary disjoint trees is discovered, i.e., a set of multicast trees with no common adversaries. When a set of multicast trees is adversary disjoint, no adversary can eavesdrop on all message pieces to recover the original message. In addition, optimized AMRP (OAMRP) is proposed in order to reduce the control overhead of AMRP, where additional multicast trees are used for only a subset of destination nodes with no single safe tree. The simulation results demonstrate that the proposed protocols achieve higher secure delivery rates than a simple extension of the existing unicast avoidance routing protocol. IEEE
Food Infestation Detection is more important for food safety and health concerns. It is a challenging task to separate the grains into infested or non-infested. It is found that in the existing system, there is no eff...
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For differentiating and customizing different classes of traffic and virtualizing physical resources of networks and machines, B5G/5G specifies several novel mechanisms, including VNF, SDN, Service Function Chaining, ...
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In this work, we present DocPedia, a novel large multimodal model(LMM) for versatile OCRfree document understanding, capable of parsing images up to 2560 × 2560 resolution. Unlike existing studies that either str...
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In this work, we present DocPedia, a novel large multimodal model(LMM) for versatile OCRfree document understanding, capable of parsing images up to 2560 × 2560 resolution. Unlike existing studies that either struggle with high-resolution documents or give up the large language model thus vision or language ability constrained, our DocPedia directly processes visual input in the frequency domain rather than the pixel space. The unique characteristic enables DocPedia to capture a greater amount of visual and textual information using a limited number of visual tokens. To consistently enhance both the perception and comprehension abilities of our DocPedia, we develop a dual-stage training strategy and enrich instructions/annotations of all training tasks covering multiple document types. Extensive quantitative and qualitative experiments are conducted on various publicly available benchmarks and the results confirm the mutual benefits of jointly learning perception and comprehension tasks. The results provide further evidence of the effectiveness and superior performance of our DocPedia over other methods.
Unmanned and aerial systems as interactors among different system components for communications,have opened up great opportunities for truth data discovery in Mobile Crowd Sensing(MCS)which has not been properly solve...
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Unmanned and aerial systems as interactors among different system components for communications,have opened up great opportunities for truth data discovery in Mobile Crowd Sensing(MCS)which has not been properly solved in the *** this paper,an Unmanned Aerial Vehicles-supported Intelligent Truth Discovery(UAV-ITD)scheme is proposed to obtain truth data at low-cost communications for *** main innovations of the UAV-ITD scheme are as follows:(1)UAV-ITD scheme takes the first step in employing UAV joint Deep Matrix Factorization(DMF)to discover truth data based on the trust mechanism for an information Elicitation Without Verification(IEWV)problem in MCS.(2)This paper introduces a truth data discovery scheme for the first time that only needs to collect a part of n data samples to infer the data of the entire network with high accuracy,which saves more communication costs than most previous data collection schemes,where they collect n or kn data ***,we conducted extensive experiments to evaluate the UAV-ITD *** results show that compared with previous schemes,our scheme can reduce estimated truth error by 52.25%–96.09%,increase the accuracy of workers’trust evaluation by 0.68–61.82 times,and save recruitment costs by 24.08%–54.15%in truth data discovery.
Bat Algorithm (BA) is a nature-inspired metaheuristic search algorithm designed to efficiently explore complex problem spaces and find near-optimal solutions. The algorithm is inspired by the echolocation behavior of ...
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The development of the Internet of Things(IoT)technology is leading to a new era of smart applications such as smart transportation,buildings,and smart ***,these applications act as the building blocks of IoT-enabled ...
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The development of the Internet of Things(IoT)technology is leading to a new era of smart applications such as smart transportation,buildings,and smart ***,these applications act as the building blocks of IoT-enabled smart *** high volume and high velocity of data generated by various smart city applications are sent to flexible and efficient cloud computing resources for ***,there is a high computation latency due to the presence of a remote cloud *** computing,which brings the computation close to the data source is introduced to overcome this *** an IoT-enabled smart city environment,one of the main concerns is to consume the least amount of energy while executing tasks that satisfy the delay *** efficient resource allocation at the edge is helpful to address this *** this paper,an energy and delay minimization problem in a smart city environment is formulated as a bi-objective edge resource allocation ***,we presented a three-layer network architecture for IoT-enabled smart ***,we designed a learning automata-based edge resource allocation approach considering the three-layer network architecture to solve the said bi-objective minimization *** Automata(LA)is a reinforcement-based adaptive decision-maker that helps to find the best task and edge resource *** extensive set of simulations is performed to demonstrate the applicability and effectiveness of the LA-based approach in the IoT-enabled smart city environment.
Environmental monitoring applications use energy harvesting to cover wide-range deployment, where devices are powered by ambient energy and operate intermittently when energy is sufficient. In such an intermittent net...
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