ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal最新文献

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Stable Feature Selection using Improved Whale Optimization Algorithm for Microarray Datasets 利用改进的鲸鱼优化算法为微阵列数据集选择稳定的特征

ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal Pub Date : 2023-12-19 DOI: 10.14201/adcaij.31187

Dipti Theng, K. Bhoyar

{"title":"Stable Feature Selection using Improved Whale Optimization Algorithm for Microarray Datasets","authors":"Dipti Theng, K. Bhoyar","doi":"10.14201/adcaij.31187","DOIUrl":"https://doi.org/10.14201/adcaij.31187","url":null,"abstract":"A microarray is a collection of DNA sequences that reflect an organism’s whole gene set and are organized in a grid pattern for use in genetic testing. Microarray datasets are extremely high-dimensional and have a very small sample size, posing the challenges of insufficient data and high computational complexity. Identification of true biomarkers that are the most significant features (a very small subset of the complete feature set) is desired to solve these issues. This reduces over-fitting, and time complexity, and improves model generalization. Various feature selection algorithms are used for this biomarker identification. This research proposed a modification to the whale optimization algorithm (WOAm) for biomarker discovery, in which the fitness of each search agent is evaluated using the hinge loss function during the hunting for prey phase to determine the optimal search agent. Also compared the results of the proposed modified algorithm with the original whale optimization algorithm and also with contemporary algorithms like the marine predator algorithm and grey wolf optimization. All these algorithms are evaluated on six different high-dimensional microarray datasets. It has been observed that the proposed modification for the whale optimization algorithm has significantly improved the results of feature selection across all the datasets. Domain experts trust the resultant biomarker/ associated genes by the stability of the results obtained. The chosen feature set’s stability was also evaluated during the research work. According to the findings, our proposed WOAm has superior stability compared to other algorithms for the CNS, colon, Leukemia, and OSCC. datasets.","PeriodicalId":504145,"journal":{"name":"ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal","volume":"4 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139171690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Generative Artificial Intelligence: Fundamentals 生成式人工智能：基础知识

ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal Pub Date : 2023-12-01 DOI: 10.14201/adcaij.31704

J. Corchado, Sebastian López F., J. Núñez V., Raul Garcia S., P. Chamoso

{"title":"Generative Artificial Intelligence: Fundamentals","authors":"J. Corchado, Sebastian López F., J. Núñez V., Raul Garcia S., P. Chamoso","doi":"10.14201/adcaij.31704","DOIUrl":"https://doi.org/10.14201/adcaij.31704","url":null,"abstract":"Generative language models have witnessed substantial traction, notably with the introduction of refined models aimed at more coherent user-AI interactions—principally conversational models. The epitome of this public attention has arguably been the refinement of the GPT-3 model into ChatGPT and its subsequent integration with auxiliary capabilities such as search features in Microsoft Bing. Despite voluminous prior research devoted to its developmental trajectory, the model’s performance, and applicability to a myriad of quotidian tasks remained nebulous and task specific. In terms of technological implementation, the advent of models such as LLMv2 and ChatGPT-4 has elevated the discourse beyond mere textual coherence to nuanced contextual understanding and real-world task completion. Concurrently, emerging architectures that focus on interpreting latent spaces have offered more granular control over text generation, thereby amplifying the model’s applicability across various verticals. Within the purview of cyber defense, especially in the Swiss operational ecosystem, these models pose both unprecedented opportunities and challenges. Their capabilities in data analytics, intrusion detection, and even misinformation combatting is laudable; yet the ethical and security implications concerning data privacy, surveillance, and potential misuse warrant judicious scrutiny.","PeriodicalId":504145,"journal":{"name":"ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal","volume":"86 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139192408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

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