ليست موضوع پايان نامه هاي لاتين Security in Industry 4.0 is a modern-day problem. Integrity verification for the nodes in Industry 4.0 can be solved by attestation. Attestation is about confirming that the state of a prover node is what it really should be. The Efficiency of this process for a large number of nodes is being researched upon in recent years. The assumptions regarding the scenarios are either very general or too specific. Another problem is that most of the attestation schemes are so complex and cumbersome for the prover nodes that attestation itself sufficiently obstructs the actual working of the nodes. Lastly, in most schemes, for the verifier node to conclude about the node's state, it needs to perform very complex computations such as encryption, decryption, and other such operations. For the industry 4.0 scenario, keeping in view well-stated assumptions regarding the scenario, we have presented a scheme that is least obstructive for the prover nodes and verifier-friendly at the same time so that it does not need to perform complex and cumbersome computations for each node in the network. Our proposed scheme relies on hash chains and organizes the prover nodes in layers. The verifier node can report the problematic node by employing the simple set intersection operations. We conclude that our scheme results in reduction of load on provers as well as the verifier, network traffic, runtime, energy, and communication costs. Stand-alone literature reviews are created to summarize the extensive amount of information in modern academia (Wright, 2019). However, there is limited research on this type of review writings. This study aimed to investigate the occurrence, distribution, and purposes of lexical bundles in stand-alone literature reviews. A corpus consisting of 1.2 million words and 218 literature reviews in Linguistics, Dentistry, and Mechanical Engineering in English language assembled. Four-word combinations that appeared more than 20 times per 500,000 words were extracted. The corpus was then divided into sections (abstracts and conclusions), and the frequency, distribution, and functions of these lexical bundles were analysed within each section. The results showed that the lexical bundles in stand-alone literature reviews weren’t similar to those found in other studies of academic writing, discourse organization bundles were the most common, followed by stance bundles and then referential bundles. However, the frequency of each bundle varied across sections, and analysis of concordance lines revealed a range of functions. These bundles filled research gaps, clarified results and methods, presented data, supported interpretations, and provided context for findings. Further research is necessary to understand the frequency and function patterns of lexical bundles within different sections of stand-alone literature reviews in order to establish guidelines for their effective use. Keywords: Academic Writing; Corpus; Corpus Analysis; Function; Lexical Bundles; Stand Alone-Literature Review

<< پايان نامه هاي لاتين >>

<< بر اساس موضوع >>

Security in Industry 4.0 is a modern-day problem. Integrity verification for the nodes in Industry 4.0 can be solved by attestation. Attestation is about confirming that the state of a prover node is what it really should be. The Efficiency of this process for a large number of nodes is being researched upon in recent years. The assumptions regarding the scenarios are either very general or too specific. Another problem is that most of the attestation schemes are so complex and cumbersome for the prover nodes that attestation itself sufficiently obstructs the actual working of the nodes. Lastly, in most schemes, for the verifier node to conclude about the node's state, it needs to perform very complex computations such as encryption, decryption, and other such operations. For the industry 4.0 scenario, keeping in view well-stated assumptions regarding the scenario, we have presented a scheme that is least obstructive for the prover nodes and verifier-friendly at the same time so that it does not need to perform complex and cumbersome computations for each node in the network. Our proposed scheme relies on hash chains and organizes the prover nodes in layers. The verifier node can report the problematic node by employing the simple set intersection operations. We conclude that our scheme results in reduction of load on provers as well as the verifier, network traffic, runtime, energy, and communication costs.

Stand-alone literature reviews are created to summarize the extensive amount of information in modern academia (Wright, 2019). However, there is limited research on this type of review writings. This study aimed to investigate the occurrence, distribution, and purposes of lexical bundles in stand-alone literature reviews. A corpus consisting of 1.2 million words and 218 literature reviews in Linguistics, Dentistry, and Mechanical Engineering in English language assembled. Four-word combinations that appeared more than 20 times per 500,000 words were extracted. The corpus was then divided into sections (abstracts and conclusions), and the frequency, distribution, and functions of these lexical bundles were analysed within each section. The results showed that the lexical bundles in stand-alone literature reviews weren’t similar to those found in other studies of academic writing, discourse organization bundles were the most common, followed by stance bundles and then referential bundles. However, the frequency of each bundle varied across sections, and analysis of concordance lines revealed a range of functions. These bundles filled research gaps, clarified results and methods, presented data, supported interpretations, and provided context for findings. Further research is necessary to understand the frequency and function patterns of lexical bundles within different sections of stand-alone literature reviews in order to establish guidelines for their effective use. Keywords: Academic Writing; Corpus; Corpus Analysis; Function; Lexical Bundles; Stand Alone-Literature Review