Cognitive Robotics最新文献

{"title":"Machine learning model for discrimination of mild dementia patients using acoustic features","authors":"Kazu Nishikawa,&nbsp;Kuwahara Akihiro,&nbsp;Rin Hirakawa,&nbsp;Hideaki Kawano,&nbsp;Yoshihisa Nakatoh","doi":"10.1016/j.cogr.2021.12.003","DOIUrl":"10.1016/j.cogr.2021.12.003","url":null,"abstract":"<div><p>In previous research on dementia discrimination by voice, a method using multiple acoustic features by machine learning has been proposed. However, they do not focus on speech analysis in mild dementia patients (MCI). Therefore, we propose a dementia discrimination system based on the analysis of vowel utterance features. The analysis results indicated that some cases of dementia appeared in the voice of mild dementia patients. These results can also be used as an index for future improvement of speech sounds in dementia. Taking advantage of these results, we propose an ensemble discrimination system using a classifier with statistical acoustic features and a Neural Network of transformer models, and the F-score is 0.907, which is better than the state-of-the-art methods.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"2 ","pages":"Pages 21-29"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667241321000288/pdfft?md5=01f437a574b872e24a624b0dbf0fd73d&pid=1-s2.0-S2667241321000288-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76595547","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint extraction of entities and relations by entity role recognition","authors":"Xi Han,&nbsp;Qi-Ming Liu","doi":"10.1016/j.cogr.2022.11.001","DOIUrl":"10.1016/j.cogr.2022.11.001","url":null,"abstract":"<div><p>Joint extracting entities and relations from unstructured text is a fundamental task in information extraction and a key step in constructing large knowledge graphs, entities and relations are constructed as relational triples of the form (subject, relation, object) or (s, r, o). Although triple extraction has been extremely successful, there are still continuing challenges due to factors such as entity overlap. Recent work has shown us the excellent performance of joint extraction models, however these methods still suffer from some problems, such as the redundancy prediction problem. Traditional methods for solving the overlap problem require triple extraction under the full class of relations defined in the dataset, however the number of relations in a sentence is much smaller than the full relational class, which leads to a large number of redundant predictions. To solve this problem, this paper decomposes the task into two steps: entity and potential relation extraction and entity-semantic role determination of triples. Specifically, we design several modules to extract the entities and relations in the sentence separately, and we use these entities and relations to construct possible candidate triples and predict the semantic roles (subject or object) of the entities under the relational constraints to obtain the correct triples. In general we propose a model for identifying the semantic roles of entities in triples under relation constraints, which can effectively solve the problem of redundant prediction, We also evaluated our model on two widely used public datasets, and our model achieved advanced performance with F1 scores of 90.8 and 92.4 on NYT and WebNLG, respectively.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"2 ","pages":"Pages 234-241"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667241322000210/pdfft?md5=52b08deb4b35e7b962f6357768547469&pid=1-s2.0-S2667241322000210-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80809723","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Eye fatigue estimation using blink detection based on Eye Aspect Ratio Mapping(EARM)","authors":"Akihiro Kuwahara,&nbsp;Kazu Nishikawa,&nbsp;Rin Hirakawa,&nbsp;Hideaki Kawano,&nbsp;Yoshihisa Nakatoh","doi":"10.1016/j.cogr.2022.01.003","DOIUrl":"10.1016/j.cogr.2022.01.003","url":null,"abstract":"<div><p>With the advent of the information society, the eyes' health is threatened all over the world. Rules and systems have been proposed to avoid these problems, but most users do not use them due to the physical and time constraints and costs involved and the lack of awareness of eye health. In this paper, we estimate the eye fatigue sensitivity by detecting spontaneous blinks with high accuracy. The experimental results show that the proposed Eye Aspect Ratio Mapping can classify blinks with high accuracy at a low cost. We also found a strong correlation between the median SBR (Spontaneous Blink Rate) and the time between the objective estimation of eye fatigue and the subject's awareness of eye fatigue.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"2 ","pages":"Pages 50-59"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667241322000039/pdfft?md5=c2e21075b740c06c6149dbaff21cd926&pid=1-s2.0-S2667241322000039-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90674752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pinocchio: A language for action representation","authors":"Pietro Morasso ,&nbsp;Vishwanathan Mohan","doi":"10.1016/j.cogr.2022.03.007","DOIUrl":"10.1016/j.cogr.2022.03.007","url":null,"abstract":"<div><p>The development of a language of action representation is a central issue for cognitive robotics, motor neuroscience, ergonomics, sport, and arts with a double goal: analysis and synthesis of action sequences that preserve the spatiotemporal invariants of biological motion, including the associated goals of learning and training. However, the notation systems proposed so far only achieved inconclusive results. By reviewing the underlying rationale of such systems, it is argued that the common flaw is the choice of the ‘primitives’ to be combined to produce complex gestures: basic movements with a different degree of “granularity”. The problem is that in motor cybernetics movements do not add: whatever the degree of granularity of the chosen primitives their simple summation is unable to produce the spatiotemporal invariants that characterize biological motion. The proposed alternative is based on the Equilibrium Point Hypothesis and, in particular, on a computational formulation named Passive Motion Paradigm, where whole-body gestures are produced by applying a small set of force fields to specific key points of the internal body schema: its animation by carefully selected force fields is analogous to the animation of a marionette using wires or strings. The crucial point is that force fields do add, thus suggesting to use force fields as a consistent set of primitives instead of basic movements. This is the starting point for suggesting a force field-based language of action representation, named Pinocchio in analogy with the famous marionette. The proposed language for action description and generation includes three main modules: 1) Primitive force field generators, 2) a Body-Model to be animated by the primitive generators, and 3) a graphical staff system for expressing any specific notated gesture. We suggest that such language is a crucial building block for the development of a cognitive architecture of cooperative robots.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"2 ","pages":"Pages 119-131"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667241322000106/pdfft?md5=a0ea6d039e0a4dc852711de82c9c4bd5&pid=1-s2.0-S2667241322000106-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91431809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A survey of quantum computing hybrid applications with brain-computer interface","authors":"Dandan Huang ,&nbsp;Mei Wang ,&nbsp;Jianping Wang ,&nbsp;Jiaxin Yan","doi":"10.1016/j.cogr.2022.07.002","DOIUrl":"10.1016/j.cogr.2022.07.002","url":null,"abstract":"<div><p>In recent years, researchers have paid more attention to the hybrid applications of quantum computing and brain-computer interfaces. With the development of neural technology and artificial intelligence, scientists have become more and more researching brain-computer interface, and the application of brain-computer interface technology to more fields has gradually become the focus of research. While the field of brain-computer interface has evolved rapidly over the past decades, the core technologies and innovative ideas behind seemingly unrelated brain-computer interface systems are rarely summarized from the point of integration with quantum. This paper provides a detailed report on the hybrid applications of quantum computing and brain-computer interface, indicates the current problems, and gives suggestions on the hybrid application research direction.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"2 ","pages":"Pages 164-176"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667241322000155/pdfft?md5=d3e94765005e1d76d972377ee08bd0a0&pid=1-s2.0-S2667241322000155-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85395111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Significant applications of Cobots in the field of manufacturing","authors":"Mohd Javaid ,&nbsp;Abid Haleem ,&nbsp;Ravi Pratap Singh ,&nbsp;Shanay Rab ,&nbsp;Rajiv Suman","doi":"10.1016/j.cogr.2022.10.001","DOIUrl":"10.1016/j.cogr.2022.10.001","url":null,"abstract":"<div><p>The term \"collaborative robot\" is commonly known as Cobot, which refers to a partnership between a robot and a human. Aside from providing physical contact between a robot and a person on the same production line simultaneously, the Cobot is designed as user-friendly. They enable operators to respond immediately to work done by the robot based on the company's urgent needs. This paper aims to explore the potential of Cobots in manufacturing. Cobots are widely employed in various industries such as life science, automotive, manufacturing, electronics, aerospace, packaging, plastics, and healthcare. For many of these businesses, the capacity to maintain a lucrative man-machine shared workplace can provide a considerable competitive edge. Cobots are simple to use while being dependable, safe, and precise. A literature review was carried out from the database from ScienceDirect, Scopus, Google Scholar, ResearchGate and other research platforms on the keyword “Cobots” or “Collaborative robots” for manufacturing. The Paper briefly discusses and provides the capabilities of this technology in manufacturing. Cobots are programmed to do crucial things such as handling poisonous substances, from putting screws on a vehicle body to cooking a meal, etc. Human operators can readily control this technology remotely and perform dangerous jobs. This paper's overview of Cobots and how it is differentiated from Robot is briefly described. The typical Features, Capabilities, Collaboration &amp; Industrial Scenarios with Cobots are also discussed briefly. Further, the study identified and discussed the significant applications of Cobots for manufacturing. Cobots are utilised in several methods and a wide range of application areas. These elevate manufacturing and other operations to new heights. They also collaborate with humans to balance the demand for safety and the need for flexibility and efficiency.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"2 ","pages":"Pages 222-233"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667241322000209/pdfft?md5=3d05e788ca43f15b3a9104328498ef7b&pid=1-s2.0-S2667241322000209-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88829188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medical named entity recognition based on dilated convolutional neural network","authors":"Ruoyu Zhang,&nbsp;Pengyu Zhao,&nbsp;Weiyu Guo,&nbsp;Rongyao Wang,&nbsp;Wenpeng Lu","doi":"10.1016/j.cogr.2021.11.002","DOIUrl":"10.1016/j.cogr.2021.11.002","url":null,"abstract":"<div><p>Named entity recognition (NER) is a fundamental and important task in natural language processing. Existing methods attempt to utilize convolutional neural network (CNN) to solve NER task. However, a disadvantage of CNN is that it fails to obtain the global information of texts, leading to an unsatisfied performance on medical NER task. In view of the disadvantages of CNN in medical NER task, this paper proposes to utilize the dilated convolutional neural network (DCNN) and bidirectional long short-term memory (BiLSTM) for hierarchical encoding, and make use of the advantages of DCNN to capture global information with fast computing speed. At the same time, multiple feature words are inserted into the medical text datasets for improving the performance of medical NER. Extensive experiments are done on three real-world datasets, which demonstrate that our method is superior to the compared models.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"2 ","pages":"Pages 13-20"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667241321000197/pdfft?md5=d7c76f5b56d0a24ccedc158c4fd7c2cb&pid=1-s2.0-S2667241321000197-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82664175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Overview of robotic grasp detection from 2D to 3D","authors":"Zhiyun Yin,&nbsp;Yujie Li","doi":"10.1016/j.cogr.2022.03.002","DOIUrl":"https://doi.org/10.1016/j.cogr.2022.03.002","url":null,"abstract":"<div><p>With the wide application of robots in life and production, robotic grasping is also experiencing continuous development. However, in practical application, some external environmental factors and the factors of the object itself have an impact on the accuracy of grasping detection. There are many classification methods of grasping detection. In this paper, the parallel gripper is used as the end of grasping to carry out research. Aiming at the angle problem of robot grasping, this paper summarizes some research status of grasping detection from 2D image to 3D space. According to their respective application, advantages, and disadvantages, this paper analyzes the development trend of the two methods. At the same time, several commonly used grasping datasets are introduced and compared.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"2 ","pages":"Pages 73-82"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667241322000052/pdfft?md5=6378a377be535e9f4a4497eee9251a1d&pid=1-s2.0-S2667241322000052-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92091650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large scale log anomaly detection via spatial pooling","authors":"Rin Hirakawa ,&nbsp;Hironori Uchida ,&nbsp;Asato Nakano ,&nbsp;Keitaro Tominaga ,&nbsp;Yoshihisa Nakatoh","doi":"10.1016/j.cogr.2021.10.001","DOIUrl":"10.1016/j.cogr.2021.10.001","url":null,"abstract":"<div><p>Log data is an important clue to understanding the behaviour of a system at runtime, but the complexity of software systems in recent years has made the data that engineers need to analyse enormous and difficult to understand. While log-based anomaly detection methods based on deep learning have enabled highly accurate detection, the computational performance required to operate the models has become very high. In this study, we propose an anomaly detection method, SPClassifier, based on sparse features and the internal state of the model, and investigate the feasibility of anomaly detection that can be utilized in environments without computing resources such as GPUs. Benchmark with the latest deep learning models on the BGL dataset shows that the proposed method can achieve competitive accuracy with these methods and has a high level of anomaly detection performance even when the amount of training data is small.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"1 ","pages":"Pages 188-196"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2667241321000173/pdfft?md5=7d47126ac817ab84febc1c4f3273aa7d&pid=1-s2.0-S2667241321000173-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78453136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Decentralised task allocation using GDL negotiations in Multi-agent system","authors":"Hui Zou ,&nbsp;Yan Xi","doi":"10.1016/j.cogr.2021.07.003","DOIUrl":"10.1016/j.cogr.2021.07.003","url":null,"abstract":"<div><p>In large distributed systems, the optimization algorithm of task scheduling may not meet the special requirements of the domain control mechanism, i.e. robustness, optimality, timeliness of solution and computational ease of processing under limited communication. In or- der to satisfy these requirements, a novel decentralized agent scheduling method for dynamic task allocation problems based on Game Descrip- tion Language (GDL) and Game Theory is proposed. Specifically, we define the task allocation problem as a stochastic game model, in which the agent's utility is derived from the marginal utility, and then prove that the global optimal task allocation scheme resides in the Nash equi- librium set by the non-cooperative game. In order to generate an optimal solution, we define Multi-agent Negotiation Game (MNG), in which ne- gotiations are held between agents to decide which tasks to act on next. Building on this, we make a simple extension to adopt GDL more suit- able for negotiations and propose to use it to model such negotiation scenarios. Finally, we use a negotiation example to show that our ap- proach is more amenable to automatic processing by autonomous agents and of great practicality than a centralized task scheduler.</p></div>","PeriodicalId":100288,"journal":{"name":"Cognitive Robotics","volume":"1 ","pages":"Pages 197-204"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.cogr.2021.07.003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83838608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}