This paper explored the application of mmWave radar sensors in robotic navigation. With the growing need for indoor navigation and object avoidance employing mmWave technology, a mobile robot equipped with a mmWave ra...
This paper explored the application of mmWave radar sensors in robotic navigation. With the growing need for indoor navigation and object avoidance employing mmWave technology, a mobile robot equipped with a mmWave radar system was developed using the ROS libraries and the mmWave ROS driver package. The system exhibited promising performance, showcasing its potential for addressing the rising demand in this field.
Ethereum technology has brought upon the smart contract concept, enabling multiple independent parties to engage in transactions without the need for an external trusted authority. While this distributed network opera...
Ethereum technology has brought upon the smart contract concept, enabling multiple independent parties to engage in transactions without the need for an external trusted authority. While this distributed network operates correctly and autonomously, smart contracts may expose security vulnerabilities, which may be exploited by malicious actors to illegitimately transfer funds. Furthermore, once a smart contract is created, it cannot be changed due to the immutability of the blockchain structure. Hence, it is critical to detect smart contract vulnerabilities before they are deployed. In this work, we propose VASCOT, a Vulnerability Analyzer for Smart COntracts using Transformers, to automatically perform sequential analysis on the EVM bytecode of smart contracts, to detect trace vulnerabilities. We construct a data set comprising Ethereum smart contracts verified in 2022; our evaluation of VASCOT on this data set demonstrates improvement in accuracy and significant reduction in time cost compared to the previously proposed sequential vulnerability scanners. To the best of our knowledge, this work constitutes the first use of transformers for smart contract security.
Transfer learning is the ability to transfer knowledge from one context to another. This paper investigates, for the first time, the possibility of transfer learning on Monte Carlo Tree Search (MCTS). We use distribut...
Transfer learning is the ability to transfer knowledge from one context to another. This paper investigates, for the first time, the possibility of transfer learning on Monte Carlo Tree Search (MCTS). We use distributed parallel MCTS to construct game-playing models for one variant of chess and then transfer these models to another domain to play a different variant of chess. We also introduce a novel pruning mechanism for MCTS to cope with memory requirements of large game trees. Our results show that positive transfer learning in MCTS is possible, and in our case, highly successful. Transferred models significantly outperform models that have to be trained from scratch.
Inner Mongolia is one of the important egg production areas within China. To encourage the egg business in Inner Mongolia to grow in a healthy and sustainable manner, a total of 244 sets of monthly average egg prices ...
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In the practice of maintaining industrial production safety, fault detection in industrial processes plays a crucial role. The data generated during industrial production is influenced by numerous operating conditions...
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In this paper a novel deep learning model for detection of plant leaf disease and agricultural pests. The proposed integreated hybrid model development based on EfficientNetB0 deep learning architecture allows model d...
In this paper a novel deep learning model for detection of plant leaf disease and agricultural pests. The proposed integreated hybrid model development based on EfficientNetB0 deep learning architecture allows model deployment in low resource settings with limited training data, allowing new and rare plant diseases and agricultural pests to be detected accurately.
This project explores the use of data visualisation techniques to render the outcome of an inference process using graphics, symbolic and schemas in stylised pictograms that supports understanding. The example demonst...
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ISBN:
(纸本)9781665495523
This project explores the use of data visualisation techniques to render the outcome of an inference process using graphics, symbolic and schemas in stylised pictograms that supports understanding. The example demonstrated in this paper is a continuation of CRISIS-Expert, an intelligent decision support system that accepts multiple input of various data types and then generate an outcome which is further rendered into symbols that within reason is, understandable by the end user.
Recently, there has been a growing interest in exploring new multi-antenna technologies for 6 G wireless networks, including the use of extremely largescale antenna arrays, tremendously high frequencies, and novel ant...
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This paper selects the data of China's consumer price index(CPI) from 1985 to 2020. Through the establishment of traditional prediction model ARIMA and machine learning prediction model LSTM, the trend of China...
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Decentralized identification is an interesting topic for Internet-based systems. Although the use of centralized systems for identification is prevalent, there is still a need for decentralized identification systems ...
Decentralized identification is an interesting topic for Internet-based systems. Although the use of centralized systems for identification is prevalent, there is still a need for decentralized identification systems that do not rely on a centralized entity. We propose using Distributed Ledger Technology (DLT) to fulfill the needs. Although DLT and Distributed Hash Table (DHT) can be used as technologies in Decentralized Identifiers (DIDs), immutability and the growth of transactions are still challenging. This paper investigates DIDs under the W3C standard and DLT-based technology as one of the solutions for verifiable data registries in DIDs. We evaluate our proposed solution by comparing three models wrt. query time for verifiable data registries. Our proposed architecture for data registry achieves better query time by concealing old transactions from the main DLT.
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