Proceedings of the 3rd International Conference on Applications of Intelligent Systems最新文献_第2页

A Smart Virtual Assistant for Students 学生智能虚拟助手

Proceedings of the 3rd International Conference on Applications of Intelligent Systems Pub Date : 2020-01-07 DOI: 10.1145/3378184.3378199

M. Mekni, Zakaria Baani, Dalia Sulieman

引用次数: 16

Investigating Comorbidity of Mental and Physical Disorders in Online Health Forums 在线健康论坛调查精神和身体疾病的共病

Proceedings of the 3rd International Conference on Applications of Intelligent Systems Pub Date : 2020-01-07 DOI: 10.1145/3378184.3378195

M. Abdollahyan, F. Smeraldi, R. Patel, C. Bessant

引用次数: 3

Confidence Bound Minimization for Bayesian optimization with Student's-t Processes 基于Student's-t过程的贝叶斯优化置信界最小化

Proceedings of the 3rd International Conference on Applications of Intelligent Systems Pub Date : 2020-01-07 DOI: 10.1145/3378184.3378193

Conor Clare, G. Hawe, Zhiwei Lin, S. McClean

{"title":"Confidence Bound Minimization for Bayesian optimization with Student's-t Processes","authors":"Conor Clare, G. Hawe, Zhiwei Lin, S. McClean","doi":"10.1145/3378184.3378193","DOIUrl":"https://doi.org/10.1145/3378184.3378193","url":null,"abstract":"Bayesian optimization seeks the global optimum of a black-box, objective function f (x), in the fewest possible iterations. Recent work applied knowledge of the true value of the optimum to the Gaussian Process probabilistic model typically used in Bayesian optimization. This, together with a new acquisition function called Confidence Bound Minimization, resulted in a Gaussian probabilistic posterior in which the predictions were no greater than the known maximum (and no less than for minimum). Our novel work applies Confidence Bound Minimization to Bayesian optimization with Student's-t Processes, a probabilistic alternative which addresses known weaknesses in Gaussian Processes - outliers' probability and the calculation of posterior covariance. The new model is applied to the problem of hyperparameter tuning for an XGBoost classifier. Experiments show superior regret minimization and predictive accuracy, versus the popular Expected Improvement acquisition function. Combining Confidence Bound Minimization with a transformed Student's-t Process probabilistic model and known optima produces superior training regret minimization and posterior predictions for the Six-Hump Camel(2D) and Levy(4D) benchmark problems, which do not fall below true minima.","PeriodicalId":437507,"journal":{"name":"Proceedings of the 3rd International Conference on Applications of Intelligent Systems","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124000359","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: 1

Mining drug-drug interactions for healthcare professionals 为医疗保健专业人员挖掘药物-药物相互作用

Proceedings of the 3rd International Conference on Applications of Intelligent Systems Pub Date : 2020-01-07 DOI: 10.1145/3378184.3378196

Lizzy Farrugia, C. Abela

引用次数: 2

Generating Cooking Recipes from Cooking Videos Using Deep Learning Considering Previous Process with Video Encoding 基于视频编码的前一过程深度学习烹饪视频生成食谱

Proceedings of the 3rd International Conference on Applications of Intelligent Systems Pub Date : 2020-01-07 DOI: 10.1145/3378184.3378217

T. Fujii, R. Orihara, Y. Sei, Yasuyuki Tahara, Akihiko Ohsuga

引用次数: 2

An Evaluation of Gas Source Localization Algorithms for Mobile Robots 移动机器人气源定位算法评价

Proceedings of the 3rd International Conference on Applications of Intelligent Systems Pub Date : 2020-01-07 DOI: 10.1145/3378184.3378220

Pepe Ojeda, J. Monroy, Javier González

引用次数: 6

A deep convolutionary network for automatic detection of audio events 用于自动检测音频事件的深度卷积网络

Proceedings of the 3rd International Conference on Applications of Intelligent Systems Pub Date : 2020-01-07 DOI: 10.1145/3378184.3378186

Antonio Roberto, Alessia Saggese, M. Vento

引用次数: 4

Adaptive Workflow of Service Oriented IoT Architectures for Small and Distributed Automation Systems 小型和分布式自动化系统面向服务的物联网架构的自适应工作流

Proceedings of the 3rd International Conference on Applications of Intelligent Systems Pub Date : 2020-01-07 DOI: 10.1145/3378184.3378189

A. Zabasta, N. Kunicina, K. Kondratjevs, L. Ribickis

{"title":"Adaptive Workflow of Service Oriented IoT Architectures for Small and Distributed Automation Systems","authors":"A. Zabasta, N. Kunicina, K. Kondratjevs, L. Ribickis","doi":"10.1145/3378184.3378189","DOIUrl":"https://doi.org/10.1145/3378184.3378189","url":null,"abstract":"The creation of appropriate adaptive control loop for interconnection of the different levels of municipality' distributed service supply systems, including the legacy systems, is a new challenge for designers of automated control tools due to incompatibility of systems that apply a number of appropriate technical solutions and protocols that assures collaboration between automation devices such as sensors, actuators, and controllers. This paper enhances the Arrowhead Framework with support of such workflows, which promote systems within a System-of-System (SoS) to work towards its predefined goal, taking into account the dynamically changing environment, system capabilities, and use case needs. This paper offers to enhance one of the Arrowhead core systems, namely Event Handler System (EHS), which provides among others orchestration services. We describe its main services and operations, implemented by data-driven implementation way, based on dynamic workflow execution, and by employing Node-RED programming tool. Furthermore, we demonstrated implementation of EHS workflow Internet of Things (IoT) architecture for small and distributed automation systems, namely, for municipality' systems and adaptive biological systems, like beekeeping processes automation.","PeriodicalId":437507,"journal":{"name":"Proceedings of the 3rd International Conference on Applications of Intelligent Systems","volume":"506 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133011500","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: 1

An Application of Machine Learning to Marker Prediction in Garment Industry: Marker Length Estimation by Neural Network for the Exponentially Increasing Magnitude of Possible Size Combinations 机器学习在服装行业标记预测中的应用:基于神经网络的标记长度估计

Proceedings of the 3rd International Conference on Applications of Intelligent Systems Pub Date : 2020-01-07 DOI: 10.1145/3378184.3378219

Yanni Xu, S. Thomassey, Xianyi Zeng

{"title":"An Application of Machine Learning to Marker Prediction in Garment Industry: Marker Length Estimation by Neural Network for the Exponentially Increasing Magnitude of Possible Size Combinations","authors":"Yanni Xu, S. Thomassey, Xianyi Zeng","doi":"10.1145/3378184.3378219","DOIUrl":"https://doi.org/10.1145/3378184.3378219","url":null,"abstract":"GEMTEX Lab has made some efforts in the application of artificial intelligence to optimize the garment manufacturing process (Zeng, Ge & Bruniaux, 2008; Thomassey & Zeng, 2018), including cutting, sewing, ironing and packing. As for the cutting process, marker making plays an essential role. The exponentially increasing magnitude of possible size combinations due to a considerable larger size number in modern garment mass customization induce a larger workload of marker making. Compared with creating all the markers using commercial marker making software, the application of machine learning technologies for marker length estimation will benefit in both efficiency and accuracy. The results generated from the marker length estimation can be used for providing the input data of cutting order planning (COP) for lean garment production, and as well predicting the objective values of marker length for the guidance and evaluation of marker making. In this study, MLR and RBF NN were used to estimating marker lengths with various sizes (regarding mass production (MP) and mass customization (MC)). The results showed that MLR generally outperforms RBF NN. MLR is more appropriated for general markers containing articles of regular sizes and mixed markers. RBF NN can be potential for markers containing articles of irregular sizes or for group markers.","PeriodicalId":437507,"journal":{"name":"Proceedings of the 3rd International Conference on Applications of Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129085014","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: 1

Early detection of plant diseases using spectral data 利用光谱数据早期检测植物病害

Proceedings of the 3rd International Conference on Applications of Intelligent Systems Pub Date : 2020-01-07 DOI: 10.1145/3378184.3378222

Godliver Owomugisha, Ephraim Nuwamanya, J. Quinn, Michael Biehl, Ernest Mwebaze

{"title":"Early detection of plant diseases using spectral data","authors":"Godliver Owomugisha, Ephraim Nuwamanya, J. Quinn, Michael Biehl, Ernest Mwebaze","doi":"10.1145/3378184.3378222","DOIUrl":"https://doi.org/10.1145/3378184.3378222","url":null,"abstract":"Early detection of crop disease is an essential step in food security. Usually, the detection becomes possible in a stage where disease symptoms are already visible on the aerial part of the plant. However, once the disease has manifested in different parts of the plant, little can be done to salvage the situation. Here, we suggest that the use of visible and near infrared spectral information facilitates disease detection in cassava crops before symptoms can be seen by the human eye. To test this hypothesis, we grow cassava plants in a screen house where they are inoculated with disease viruses. We monitor the plants over time collecting both spectra and plant tissue for wet chemistry analysis. Our results demonstrate that suitably trained classifiers are indeed able to detect cassava diseases. Specifically, we consider Generalized Matrix Relevance Learning Vector Quantization (GMLVQ) applied to original spectra and, alternatively, in combination with dimension reduction by Principal Component Analysis (PCA). We show that successful detection is possible shortly after the infection can be confirmed by wet lab chemistry, several weeks before symptoms manifest on the plants.","PeriodicalId":437507,"journal":{"name":"Proceedings of the 3rd International Conference on Applications of Intelligent Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115483517","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: 9