With the rapid development of information technology, the scale of software has increased exponentially. Binary code similarity detection technology plays an important role in many fields, such as detecting software p...
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Data-driven machine learning(ML) is widely employed in the analysis of materials structure-activity relationships,performance optimization and materials design due to its superior ability to reveal latent data pattern...
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Data-driven machine learning(ML) is widely employed in the analysis of materials structure-activity relationships,performance optimization and materials design due to its superior ability to reveal latent data patterns and make accurate ***,because of the laborious process of materials data acquisition,ML models encounter the issue of the mismatch between a high dimension of feature space and a small sample size(for traditional ML models) or the mismatch between model parameters and sample size(for deep-learning models),usually resulting in terrible ***,we review the efforts for tackling this issue via feature reduction,sample augmentation and specific ML approaches,and show that the balance between the number of samples and features or model parameters should attract great attention during data quantity *** this,we propose a synergistic data quantity governance flow with the incorporation of materials domain *** summarizing the approaches to incorporating materials domain knowledge into the process of ML,we provide examples of incorporating domain knowledge into governance schemes to demonstrate the advantages of the approach and *** work paves the way for obtaining the required high-quality data to accelerate materials design and discovery based on ML.
The development of Cyber-Physical Fusion Technology gradually takes the power grid in the direction of intelligence, making the smart substation a typical cyber-physical fusion system. However, while the introduction ...
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Dear editor,The issue on how to ensure the smart grid environment’s security and reliability has always been a focus in current research. The rapid expansion of the Internet of Things enables billions of smart device...
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Dear editor,The issue on how to ensure the smart grid environment’s security and reliability has always been a focus in current research. The rapid expansion of the Internet of Things enables billions of smart devices to be involved in the smart grid, such as smart meters, who play a part in monitoring and recording consumers’ power usage. The smart meter first amasses the information of energy consumption and then sends it to utility control.
Self-assembled monolayers（SAMs） are widely used as hole transport materials in inverted perovskite solar cells,offering low parasitic absorption and suitability for semitransparent and tandem solar *** SAMs have sho...
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Self-assembled monolayers（SAMs） are widely used as hole transport materials in inverted perovskite solar cells,offering low parasitic absorption and suitability for semitransparent and tandem solar *** SAMs have shown to be promising in small-area devices（≤1 cm2）,their application in larger areas has been limited by a lack of knowledge regarding alternative deposition methods beyond the common spin-coating ***,we compare spin-coating and upscalable methods such as thermal evaporation and spray-coating for [2-（9H-carbazol-9-yl）ethyl]phosphonic acid（2PACz）,one of the most common carbazole-based *** impact of these deposition methods on the device performance is investigated,revealing that the spray-coating technique yields higher device ***,our work provides guidelines for the deposition of SAM materials for the fabrication of perovskite solar *** addition,we provide an extensive characterization of 2PACz films focusing on thermal evaporation and spray-coating methods,which allow for thicker 2PACz *** is found that the optimal 2PACz deposition conditions corresponding to the highest device performances do not always correlate with the monolayer characteristics.
Pushing artificial intelligence(AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things(AIoT) in the sixth-gen...
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Pushing artificial intelligence(AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things(AIoT) in the sixth-generation(6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like intelligence from the vast amount of data scattered at the wireless network edge. Typically, realizing edge intelligence corresponds to the processes of sensing, communication,and computation, which are coupled ingredients for data generation, exchanging, and processing, ***, conventional wireless networks design the three mentioned ingredients separately in a task-agnostic manner, which leads to difficulties in accommodating the stringent demands of ultra-low latency, ultra-high reliability, and high capacity in emerging AI applications like auto-driving and metaverse. This thus prompts a new design paradigm of seamlessly integrated sensing, communication, and computation(ISCC) in a taskoriented manner, which comprehensively accounts for the use of the data in downstream AI tasks. In view of its growing interest, this study provides a timely overview of ISCC for edge intelligence by introducing its basic concept, design challenges, and enabling techniques, surveying the state-of-the-art advancements, and shedding light on the road ahead.
Proprietary(or semi-proprietary)protocols are widely adopted in industrial control systems(ICSs).Inferring protocol format by reverse engineering is important for many network security applications,e.g.,program tests ...
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Proprietary(or semi-proprietary)protocols are widely adopted in industrial control systems(ICSs).Inferring protocol format by reverse engineering is important for many network security applications,e.g.,program tests and intrusion *** protocol reverse engineering methods have been proposed which are considered time-consuming,tedious,and ***,automatical protocol reverse engineering methods have been proposed which are,however,neither effective in handling binary-based ICS protocols based on network traffic analysis nor accurate in extracting protocol fields from protocol *** this paper,we present a framework called the industrial control system protocol reverse engineering framework(ICSPRF)that aims to extract ICS protocol fields with high *** is based on the key insight that an individual field in a message is typically handled in the same execution context,e.g.,basic block(BBL)*** a result,by monitoring program execution,we can collect the tainted data information processed in every BBL group in the execution trace and cluster it to derive the protocol *** evaluate our approach with six open-source ICS protocol *** results show that ICSPRF can identify individual protocol fields with high accuracy(on average a 94.3%match ratio).ICSPRF also has a low coarse-grained and overly fine-grained match *** the same metric,ICSPRF is more accurate than AutoFormat(88.5%for all evaluated protocols and 80.0%for binary-based protocols).
With the wide application of network attached storage (NAS), the security problem is becoming more and more serious, together with the increasingly fierce attacks against NAS devices of different manufacturers. In ord...
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Although large language models (LLMs) trained on extensive multilingual corpora exhibit impressive language transfer, they often fail to respond in the user's desired language due to corpus imbalances, an embarras...
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Industrial network boundary protection equipment faces threats from attackers when protecting the industrial control system network. The similarity and static characteristics caused by large-scale and long-term deploy...
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