人工智能技术学报(英文)最新文献

{"title":"Lightweight Classification Network for Pulmonary Tuberculosis Based on CT Images","authors":"Junlin Tian, Yi Zhang, J. Lei, Chunyou Sun, Gang Hu","doi":"10.37965/jait.2023.0153","DOIUrl":"https://doi.org/10.37965/jait.2023.0153","url":null,"abstract":"With the continuous development of medical informatics and digital diagnosis, the classification of tuberculosis cases from computed tomography (CT) images of the lung based on deep learning is an important guiding aid in clinical diagnosis and treatment. Due to its potential application in medical image classification, this task has received extensive research attention. Existing related neural network techniques are still challenging in terms of feature extraction of global contextual information of images and network complexity in achieving image classification. To address these issues, this paper proposes a lightweight medical image classification network based on a combination of Transformer and convolutional neural network (CNN) for the classification of tuberculosis cases from lung CT. The method mainly consists of a fusion of the CNN module and the Transformer module, exploiting the advantages of both in order to accomplish a more accurate classification task. On the one hand, the CNN branch supplements the Transformer branch with basic local feature information in the low level; on the other hand, in the middle and high levels of the model, the CNN branch can also provide the Transformer architecture with different On the other hand, in the middle and high levels of the model, the CNN branches can also provide different local and global feature information to the Transformer architecture to enhance the ability of the model to obtain feature information and improve the accuracy of image classification. A shortcut is used in each module of the network to solve the problem of poor model results due to gradient divergence and to optimise the effectiveness of TB classification. The proposed lightweight model can well solve the problem of long training time in the process of TB classification of lung CT and improve the speed of classification. The proposed method was validated on a computed tomography (CT) image dataset provided by the First Hospital of Lanzhou University. The experimental results show that the proposed lightweight classification network for tuberculosis based on CT medical images of lungs can fully extract the feature information of the input images and obtain high accuracy classification results.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42595897","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}

{"title":"Evolutionary Multitask Optimization in Real-World Applications: A Survey","authors":"Yue Wu, Han-Yan Ding, Benhua Xiang, Jinlong Sheng, Wenping Ma","doi":"10.37965/jait.2023.0149","DOIUrl":"https://doi.org/10.37965/jait.2023.0149","url":null,"abstract":"Due to its good ability to solve problems, evolutionary multitask optimization (EMTO) algorithm has been widely studied recently. Evolutionary algorithm has the advantage of fast searching for the optimal solution, but it is easy to fall into local optimum and difficult to generalize. To solve these problems, it is an effective method to combine with multitask optimization algorithm. Through the implicit parallelism of tasks themselves and the knowledge transfer between tasks, more promising individuals can be generated in the evolution process, which can jump out of the local optimum. How to better combine the two has also been studied more and more. This paper will explore the existing evolutionary multitasking theory and improvement scheme in detail. Then it summarizes the application of evolutionary multitask optimization in different scenarios. Finally, according to the existing research, the future research trends and potential exploration directions are revealed.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48015634","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}

{"title":"Human Ear Image Recognition Method Using PCA and Fisherface Complementary Double Feature Extraction","authors":"Yang Wang, Ke Cheng, Shenghui Zhao, Xu E","doi":"10.37965/jait.2022.0146","DOIUrl":"https://doi.org/10.37965/jait.2022.0146","url":null,"abstract":"Ear recognition is a new kind of biometric identification technology now. Feature extraction is a key step in pattern recognition technology, which determines the accuracy of classification results. The method of single feature extraction can achieve high recognition rate under certain conditions, but the use of double feature extraction can overcome the limitation of single feature extraction. In order to improve the accuracy of classification results, this paper proposes a new method, that is, the method of complementary double feature extraction based on PCA and Fisherface, and we apply it to human ear image recognition. Experimental results on the ear image database provided by Beijing University of Science and Technology show that the ear recognition rate of the proposed method is significantly higher than the single feature extraction using PCA, Fisherface or ICA alone.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44880944","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}

{"title":"HSCA-Net: A Hybrid Spatial-Channel Attention Network in Multi-Scale Feature Pyramid for Document Layout Analysis","authors":"Honghong Zhang, Canhui Xu, Cao Shi, Hengyue Bi, Yuteng Li","doi":"10.37965/jait.2022.0145","DOIUrl":"https://doi.org/10.37965/jait.2022.0145","url":null,"abstract":"Document images often contain various page components and complex logical structures, which makes document layout analysis task challenging. For most deep learning based document layout analysis methods, convolutional neural networks (CNNs) are adopted as the image feature extraction networks. In this paper, a hybrid spatial-channel attention network (HSCA-Net) is proposed to improve feature extraction capability by exerting attention mechanism to explore more salient properties within document pages. The HSCA-Net contains two modules: spatial attention module (SAM) and channel attention module (CAM). They are embedded in the multi-scale feature network by lateral attention connection. SAM extracts contextual information with learning offset in spatial dimension and CAM performs feature recalibration by focusing more on feature channels with important contents. The lateral attention connection is to incorporate SAM and CAM into multi-scale feature pyramid network and retain more of the original feature information. The effectiveness and adaptability of HSCA-Net are evaluated through multiple experiments on publicly available datasets PubLayNet, ICDAR-POD and Article Regions. The mAP on these datasets is as high as 0.940,0.939 and 0.967 respectively, which demonstrate that our HSCA-Net achieves competitive results on document layout analysis task. Text.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45475920","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}

{"title":"On Incentive and Coordination Mechanism of Service Outsourcing Based on Principal-Agent Theory and Blockchain Technology","authors":"Chen Yan, Xiao Wang, R. Xu","doi":"10.37965/jait.2022.0144","DOIUrl":"https://doi.org/10.37965/jait.2022.0144","url":null,"abstract":" To address the issue of information asymmetry between the two parties and moral hazard among service providers in the process of service outsourcing, this paper first builds the Stackelberg game model based on the principal-agent framework, examines the dynamic game situation before the contract being signed, and develops four information models. Second, the analysis reveals a Pareto improvement in the game's Nash equilibrium when comparing the four models from the standpoint of the supply chain. In the complete information scenario, the service level of the service provider, the customer company's incentive effectiveness, and the supply chain system's ultimate profit are all maximized. Once more, a coordinating mechanism for disposable profit is built in this study. The paper then suggests a blockchain-based architecture for the service outsourcing process supervision and a distributed incentive mechanism under the coordination mechanism in response to the inadequacy of the principal-agent theory to address the information asymmetry problem and the moral hazard problem. The experiment's end findings demonstrate that both parties can benefit from the coordination mechanism and that the application of blockchain technology can resolve these issues and effectively encourage service providers.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48550647","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}

{"title":"Latest Advances on AI and Robotics Applications","authors":"Manuel Silva","doi":"10.37965/jait.2022.0139","DOIUrl":"https://doi.org/10.37965/jait.2022.0139","url":null,"abstract":"\u0000\u0000\u0000The applications of artificial intelligence and robotics, their associated technologies, and their integration continue to grow and are seen in more and more diverse fields. With these considerations in mind, this issue of the Journal of Artificial Intelligence and Technology presents five state-of-the-art peer-reviewed contributions, ranging from theory to prototyping, and covering several distinct application topics.\u0000\u0000\u0000","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43483831","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}

{"title":"Stand-Up Assistive Devices Allowing Patients to Perform Voluntary Movements Within the Safety Movement Tolerance","authors":"D. Chugo, S. Muramatsu, S. Yokota, Jin-Hua She, H. Hashimoto","doi":"10.37965/jait.2022.0121","DOIUrl":"https://doi.org/10.37965/jait.2022.0121","url":null,"abstract":"This paper proposes a novel standing assistance robot, which realizes voluntary movements of the patient within a safety motion range. In previous studies, conventional assistive robots did not require patients to use their own physical strength to stand, which leads to decreased strength in the elderly. Such general assistive robots helped patients by using a fixed motion reference pathway in spite of their original intention, and as a result, these robots failed to use the physical strength of the patients. Therefore, this study proposes a novel method for assisting the patient to stand up safely while using their physical abilities, by determining the range of movements that can be safely performed from the patient's physical condition, and allowing the patient to move freely within this range. The standing motion is a set of different movements: inclining the trunk forward, lifting the trunk and extending the trunk. In this study, the range of movements in which the patient can safely stand in each movement was determined in terms of body stability and the muscle output that the patient can generate. Furthermore, this study proposes a robot control method that allows movements based on the patient's free will if the patient's posture is within the safety tolerance, and corrects the movements when the patient's posture is estimated to fall outside of it. Proposed idea is implemented to our new prototype and its effectiveness is verified by experimental results with elderly subjects who lives in the nursing care house.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43429586","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}

{"title":"Non-Assembly 3D-Printed Walking Mechanism Utilising a Hexapod Gait","authors":"G. Jackson-Mills, A. Barber, Andrew Blight, Andrew Pickering, Jordan H. Boyle, Robert C. Richardson","doi":"10.37965/jait.2022.0112","DOIUrl":"https://doi.org/10.37965/jait.2022.0112","url":null,"abstract":"Small inspection robots can allow for the exploration of environments and the collection of data from dangerous or difficult to access areas. These robots can be custom built for specific tasks, but the design and assembly process for this can be costly, both in money and time. The use of 3D Printing in creating Non-Assembly mechanisms can assist in saving time and resources by reducing the number of different components required and removing the necessity for complex assembly tasks. This paper introduces a robot to explore the capabilities of this approach, by iterating on a previous example of a robot with Non-Assembly mechanisms. This explores how altering the size, mechanism type and accompanying control circuitry can affect the efficiency of the practice. Through developing on previous knowledge, this new walking robot improves on the previous iteration by creating a more robust and reliable system, more capable of effectively exploring challenging environments accurately, while still using practices designed to save on cost and production time.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44291116","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}

{"title":"Four Way Human Quantum Turiyam Cognition Analysis","authors":"Prem Kumar Singh","doi":"10.37965/jait.2022.0123","DOIUrl":"https://doi.org/10.37965/jait.2022.0123","url":null,"abstract":"Recently, the Turiyam set was introduced for characterization of data sets beyond true, false and uncertain regions. This set is able to represent unknown, undefined, or conduit metaphor of human quantum cognition. One of the examples is USA-Russia conflicts or Cold war is beyond the characterization of win, draw or loss. It is totally based on the conduit metaphor of USA and Russia. In this case, a set of countries may support Russia (Sr) can be characterized as true regions. A set of countries does not support Russia (i.e. supporting the USA) can be characterized as false regions (Su). A set of countries supports both Russia-USA based on the given situation. These types of countries and their vote is uncertain. The fourth case is some countries like India, China, UAE choose nothing to fulfill their conduit metaphor. It is called Turiyam or four dimension cognition. The characterization of this four dimension data and its graphical visualization is one of the crucial tasks for the current researchers. To tackle this issue, the current paper will try to introduce a method for characterization of this undefined, unknown or Turiyam cognition via a defined interval-set. The objective is to provide a way to explore them in known graph (t), not known graph (f), partial graph (i) or unknown graph (l) with an example. ","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46733933","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}

{"title":"Standard NER Tagging Scheme for Big Data Healthcare Analytics Built on Unified Medical Corpora","authors":"Sarah Shafqat, Hammad Majeed, Qaisar Javaid, H. F. Ahmad","doi":"10.37965/jait.2022.0127","DOIUrl":"https://doi.org/10.37965/jait.2022.0127","url":null,"abstract":"The motivation for this research comes from the gap found in discovering the common ground for medical context learning through analytics for different purposes of  diagnosing, recommending, prescribing or treating patients for uniform phenotype features from patients’ profile. Authors of this paper while searching for possible solutions for medical context learning found that unified corpora tagged with medical nomenclature was missing to train the analytics for medical context learning. Therefore, here we demonstrated a mechanism to come up with uniform NER (Named Entity Recognition) tagged medical corpora that is fed with 14407 endocrine patients’ dataset in CSV format diagnosed with DM and comorbidity diseases. The other corpus is of ICD-10-CM coding scheme in text format taken from www.icd10data.com. ICD-10-CM corpus is to be tagged for understanding the medical context with uniformity for which we are conducting different experiments using common NLP techniques and frameworks like; TensorFlow, Keras, LSTM, and Bi-LSTM. \u0000In our preliminary experiments albeit label sets in form of (instance, label) pair were tagged with Sequential() model formed on TensorFlow.Keras and Bi-LSTM NLP algorithms. The maximum accuracy achieved for model validation was 0.8846.","PeriodicalId":70996,"journal":{"name":"人工智能技术学报(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46149990","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}