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Article
Publication date: 4 December 2023

Yang Liu, Xin Xu, Shiqing Lv, Xuewei Zhao, Yuxiong Xue, Shuye Zhang, Xingji Li and Chaoyang Xing

Due to the miniaturization of electronic devices, the increased current density through solder joints leads to the occurrence of electromigration failure, thereby reducing the…

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Abstract

Purpose

Due to the miniaturization of electronic devices, the increased current density through solder joints leads to the occurrence of electromigration failure, thereby reducing the reliability of electronic devices. The purpose of this study is to propose a finite element-artificial neural network method for the prediction of temperature and current density of solder joints, and thus provide reference information for the reliability evaluation of solder joints.

Design/methodology/approach

The temperature distribution and current density distribution of the interconnect structure of electronic devices were investigated through finite element simulations. During the experimental process, the actual temperature of the solder joints was measured and was used to optimize the finite element model. A large amount of simulation data was obtained to analyze the neural network by varying the height of solder joints, the diameter of solder pads and the magnitude of current loads. The constructed neural network was trained, tested and optimized using this data.

Findings

Based on the finite element simulation results, the current is more concentrated in the corners of the solder joints, generating a significant amount of Joule heating, which leads to localized temperature rise. The constructed neural network is trained, tested and optimized using the simulation results. The ANN 1, used for predicting solder joint temperature, achieves a prediction accuracy of 96.9%, while the ANN 2, used for predicting solder joint current density, achieves a prediction accuracy of 93.4%.

Originality/value

The proposed method can effectively improve the estimation efficiency of temperature and current density in the packaging structure. This method prevails in the field of packaging, and other factors that affect the thermal, mechanical and electrical properties of the packaging structure can be introduced into the model.

Details

Soldering & Surface Mount Technology, vol. 36 no. 2
Type: Research Article
ISSN: 0954-0911

Keywords

Article
Publication date: 1 April 2024

Xiaoxian Yang, Zhifeng Wang, Qi Wang, Ke Wei, Kaiqi Zhang and Jiangang Shi

This study aims to adopt a systematic review approach to examine the existing literature on law and LLMs.It involves analyzing and synthesizing relevant research papers, reports…

Abstract

Purpose

This study aims to adopt a systematic review approach to examine the existing literature on law and LLMs.It involves analyzing and synthesizing relevant research papers, reports and scholarly articles that discuss the use of LLMs in the legal domain. The review encompasses various aspects, including an analysis of LLMs, legal natural language processing (NLP), model tuning techniques, data processing strategies and frameworks for addressing the challenges associated with legal question-and-answer (Q&A) systems. Additionally, the study explores potential applications and services that can benefit from the integration of LLMs in the field of intelligent justice.

Design/methodology/approach

This paper surveys the state-of-the-art research on law LLMs and their application in the field of intelligent justice. The study aims to identify the challenges associated with developing Q&A systems based on LLMs and explores potential directions for future research and development. The ultimate goal is to contribute to the advancement of intelligent justice by effectively leveraging LLMs.

Findings

To effectively apply a law LLM, systematic research on LLM, legal NLP and model adjustment technology is required.

Originality/value

This study contributes to the field of intelligent justice by providing a comprehensive review of the current state of research on law LLMs.

Details

International Journal of Web Information Systems, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1744-0084

Keywords

Article
Publication date: 28 March 2022

Nidhi Raghav and Anoop Kumar Bhola

To make more smart health-care system, the health-care data should be shared in the secure manner, and it improves health-care service quality. This paper aims to implement a…

Abstract

Purpose

To make more smart health-care system, the health-care data should be shared in the secure manner, and it improves health-care service quality. This paper aims to implement a modern decentralized blockchain, safe and easy-to-use health-care technology application in the cloud.

Findings

On observing the graph, the convergence analysis of proposed Levy Flight-integrated moth flame optimization method at 80th iteration was 4.59%, 2.80%, 3.316%, 8.92% and 2.55% higher than the traditional models MFO, artificial bee colony (ABC), particle swarm optimization (PSO), moth search algorithm (MSA) and glow worm swarm optimization (GWSO), respectively, for Hungarian data set. Particularly, in best case scenario, the adopted method attains low cost value (5.672671) when compared to all other traditional models such as MFO (5.727314), ABC (5.711577), PSO (5.706499), MSA (5.764517) and GWSO (5.723353).

Originality/value

The proposed method achieved effective performance in terms of key sensitivity, sanitization effectiveness, restoration effectiveness, etc.

Details

Journal of Engineering, Design and Technology, vol. 22 no. 2
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 26 December 2023

Li Zhang and Xican Li

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle…

Abstract

Purpose

Aim to the limitations of grey relational analysis of interval grey number, based on the generalized greyness of interval grey number, this paper tries to construct a grey angle cosine relational degree model from the perspective of proximity and similarity.

Design/methodology/approach

Firstly, the algorithms of the generalized greyness of interval grey number and interval grey number vector are given, and its properties are analyzed. Then, based on the grey relational theory, the grey angle cosine relational model is proposed based on the generalized greyness of interval grey number, and the relationship between the classical cosine similarity model and the grey angle cosine relational model is analyzed. Finally, the validity of the model in this paper is illustrated by the calculation examples and an application example of related factor analysis of maize yield.

Findings

The results show that the grey angle cosine relational degree model has strict theoretical basis, convenient calculation and is easy to program, which can not only fully utilize the information of interval grey numbers but also overcome the shortcomings of greyness relational degree model. The grey angle cosine relational degree is an extended form of cosine similarity degree of real numbers. The calculation examples and the related factor analysis of maize yield show that the model proposed in this paper is feasible and valid.

Practical implications

The research results not only further enrich the grey system theory and method but also provide a basis for the grey relational analysis of the sequences in which the interval grey numbers coexist with the real numbers.

Originality/value

The paper succeeds in realizing the algorithms of the generalized greyness of interval grey number and interval grey number vector, and the grey angle cosine relational degree, which provide a new method for grey relational analysis.

Details

Grey Systems: Theory and Application, vol. 14 no. 2
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 26 July 2023

Yulong Tang, Chen Luo and Yan Su

The ballooning health misinformation on social media raises grave concerns. Drawing upon the S-O-R (Stimulus-Organism-Response) model and the information processing literature…

Abstract

Purpose

The ballooning health misinformation on social media raises grave concerns. Drawing upon the S-O-R (Stimulus-Organism-Response) model and the information processing literature, this study aims to explore (1) how social media health information seeking (S) affects health misinformation sharing intention (R) through the channel of health misperceptions (O) and (2) whether the mediation process would be contingent upon different information processing predispositions.

Design/methodology/approach

Data were collected from a survey comprising 388 respondents from the Chinese middle-aged or above group, one of China's most susceptible populations to health misinformation. Standard multiple linear regression models and the PROCESS Macro were adopted to examine the direct effect and the moderated mediation model.

Findings

Results bolstered the S-O-R-based mechanism, in which health misperceptions mediated social media health information seeking's effect on health misinformation sharing intention. As an indicator of analytical information processing, need for cognition (NFC) failed to moderate the mediation process. Contrarily, faith in intuition (FI), an indicator reflecting intuitive information processing, served as a significant moderator. The positive association between social media health information seeking and misperceptions was stronger among respondents with low FI.

Originality/value

This study sheds light on health misinformation sharing research by bridging health information seeking, information internalization and information sharing. Moreover, the authors extended the S-O-R model by integrating information processing predispositions, which differs this study from previous literature and advances the extant understanding of how information processing styles work in the face of online health misinformation. The particular age group and the Chinese context further inform context-specific implications regarding online health misinformation regulation.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2023-0157.

Details

Online Information Review, vol. 48 no. 2
Type: Research Article
ISSN: 1468-4527

Keywords

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