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检索条件"主题词=Cognitive informatics"

共 478 条记录，以下是411-420 订阅

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Using the 5th dimensions of human visual perception to inspire automated edge and texture segmentation: A fuzzy spatial-taxon approach

Using the 5th dimensions of human visual perception to inspi...

引用

IEEE International Conference on cognitive informatics

作者： Lauren Barghout Visiting Scholar at Berkeley Initiative for Soft Computing Electrical Engineering and Computer Science University of California at Berkeley Berkeley CA USA

ISBN: (纸本)9781509038473

With the recent stunning success of machine learning, artificially intelligent machine vision research falls (roughly) into two camps: the big data camp and cognitive informatics camp. Big data uses statistical methods to discover latent structures that emerge from the co-occurrences of relevant features when sampling over enormous quantities of data. The cognitive informatics methods design computer vision systems to mimic human cognition. Though some visual latent features that emerge from deep learning networks, mimic mammalian visual detectors, as of yet the information processing mechanisms (analogous to human psychophysical mechanisms) remain hidden within the complexity of the deep nets. Furthermore, the sampling requirements of big data systems require limiting samples to pre-processed sets, such as SHIFT (shift invariant feature transform (Lowe 1999)). Techniques, such as the ones introduced in this paper, provide fast cognitively relevant methods for selecting samples and reducing the number of candidate features. The approach described in this paper live squarely in the camp of designing computer vision A.I. to mimics human cognitive processes. I introduce a novel definition of edges, based on human hierarchical scene perception. Hierarchical scene perception views vision within the 5 dimensions of horizontal & vertical position, depth, time and scene abstraction level (spatial-taxon). Fuzzy inference selects candidate edge elements using the Gestalt psychology principal of good curvilinear continuation, proximity and edges attachment. Spatial-taxon inference infers an edge outline for each level of abstraction within the scene architecture. The system was tested on 60 natural images and the results provide edges more aligned with human intuition of what edges should look like. ROC plots indicate solid performance, with the majority of human subjects rating the edge detection as high quality. The inferred edges are consistent with the finding of neurons r

关键词： Image edge detection Computer vision Laplace equations Big data Image segmentation cognitive informatics Visualization

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Identifying Application Key Knowledge through System Operations Modeling

Identifying Application Key Knowledge through System Operati...

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IEEE International Conference on cognitive informatics

作者： Pedro P. Alarcon Juan Garbajosa Systems and Software Technology Group E.U. Informática Universidad Politécnica de Madrid Technical University of Madrid Madrid Spain

One of the problems associated with complex systems engineering is identifying the system knowledge relevant to build system implementation. System operations are an essential part of this knowledge. Software and system engineering standards highlight the importance of system operations; templates for a concept of operations document are available from different standard bodies in the context of requirements engineering and specification. However, specific guidelines for operations modeling are not usually provided. This paper introduces an approach to systematically model system operations. The cornerstone for this is an operations metamodel; this metamodel is presented within this paper and has been defined using UML 2.x. The baseline for the metamodel is a schema, also introduced within the paper, which formalizes system operations in terms of commands acting on systems, inputs to the system, and different kinds of outputs classified into responses, notifications and alarms. Operations models, as presented here, comprise system knowledge essentials from a functional point of view but reduced in size compared to the whole system specification. They can be deployed in several ways; this paper presents their use as drivers for system development and validation from early lifecycle stages.

关键词： Systems engineering and theory Software systems Software standards Application software Knowledge engineering Standards organizations Guidelines Unified modeling language cognitive informatics Information technology

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A pharmacogenomic study on the polymorphic gene response to risperidone in schizophrenia patients

A pharmacogenomic study on the polymorphic gene response to ...

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IEEE International Conference on cognitive informatics

作者： Lei Wang Daniel O'Connor Ying Wang Guoyin Feng Lin He Department of Medicine University of California San Diego La Jolla CA Bio-X Center Shanghai Jiao Tong University Shanghai China Department of Medicine University of California San Diego 9500 Gilman DR MC:0838 La Jolla 92093-0838 USA The Fourth City Hospital Xian Shaanxi China Shanghai Institute of Mental Health Shanghai China

ISBN: (纸本)9781424425389

Risperidone is a widely used atypical antipsychotic medication, which has currently raised considerable interest in individual differences in patient response to it. Although risperidone is one of the major atypical anti-psychotics, there is a lack of pharmacogenetic studies on it, especially in Asian populations. This paper investigates the relationship between the -1438 A/G polymorphism of 5-HT2A and response to risperidone treatment. In this study, 130 schizophrenia patients were recruited, who were treated with risperidone monotherapy for eight weeks. Clinical response was assessed on the positive and negative syndrome scale (PANSS) on the day of admission and was subsequently assessed after eight weeks following the treatment. The -1438 A/G polymorphism was identified by direct sequencing. The confounding effects of nongenetic factors were estimated and the baseline symptom score was included as a covariate for adjustment. Association tests between genotype and percentage improvement in total PANSS scores, as well as positive symptom scores and negative symptom scores, were performed using analysis of variance (ANOVA). We find no significant differences in response to the treatment in terms of PANSS or subscore improvements among the subgroups according to different genotypes. Further studies on larger groups are planned to confirm the result.

关键词： DNA Drugs Sociology Statistics Blood cognitive informatics

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Analyzing skill sets with or-relation tables in knowledge spaces

Analyzing skill sets with or-relation tables in knowledge sp...

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IEEE International Conference on cognitive informatics

作者： Feifei Xu Duoqian Miao Yiyu Yao Lai Wei Department of Computer Science and Technology University of Tongji Shanghai China University of Regina Regina SK CA Department of Computer Science and Technology Shanghai Maritime University Shanghai China

The disjunctive model of skill map in knowledge spaces can be interpreted based on an or-binary relation table between skills and questions. There may exist skills that are the union of other skills. Omitting these skills will not change the knowledge structure. Finding a minimal skill set may be formulated similar to the problem of attribute reduction in rough set theory, where an and-binary relation table is used. In this paper, an or-relation skill-question table is considered for a disjunctive model of knowledge spaces. A minimal skill set is defined and an algorithm for finding the minimal skill set is proposed. An example is used to illustrate the basic idea.

关键词： Space technology Set theory Psychology Artificial intelligence Knowledge acquisition cognitive informatics cognitive science Cognition Information processing Machine intelligence

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Sunflower Sentry: Advanced Hybrid Model for Early Disease Detection

Sunflower Sentry: Advanced Hybrid Model for Early Disease De...

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Data Intelligence and cognitive informatics (ICDICI), International Conference on

作者： Yashu Amanveer Singh Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura Punjab India Chitkara Centre for Research and Development Chitkara University Himachal Pradesh India

ISBN: (数字)9798350389609

ISBN: (纸本)9798350389616

Improving agricultural output and guaranteeing food security depends on early identification of plant diseases and precise categorisation of them. In this work, seven major diseases of sunflower such as Downy Mildew, Rust, Verticillium Wilt, Phoma Black Stem, Alternaria Leaf Spot, Sclerotinia Stem Rot, and Phomopsis Stem Canker are considered where From the advantages of both methodologies, the suggested model consists of Random Forest (RF) as well as Convolutional Neural Networks (CNN). Two sets of convolutional and max pooling layers make up the CNN architecture; then, a flattening layer. After that, a Random Forest with 14 trees—each with a maximum depth of 8—classified the obtained characteristics. From several web sources, 4,356 photos of sunflower leaves were gathered and preprocessed using cleaning, resizing, and augmentation. With an overall accuracy of 81.54%, the model was quite strong in identifying and grouping the disorders. For Phomopsis Stem Canker and Sclerotinia Stem Rot, accuracy is shown especially by precision, recall, and F1-score measurements. The confusion matrix study emphasised, even more, the strengths and opportunities for the development of the approach. Early intervention and efficient disease control made possible by this hybrid model provide a great tool for contemporary agriculture, hence allowing sustainable farming methods and maybe higher crop yields.

关键词： Radio frequency Plant diseases Accuracy Food security Forestry Data models Convolutional neural networks cognitive informatics Crop yield Farming

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Formal concept analysis based on hierarchical class analysis

Formal concept analysis based on hierarchical class analysis

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IEEE International Conference on cognitive informatics

作者： Yaohua Chen Yiyu Yao Department of Computer Science University of Regina Regina SAS Canada

The study of concept formation and learning is a central topic in cognitive informatics. Formal concept analysis can be viewed as an approach on this topic based on a formal context. In this paper, we study some basic data units for formal concept analysis based on hierarchical class analysis. In a formal context, objects and attributes can be grouped into equivalence classes based on equivalence relations. The order relations define the hierarchical structures of the equivalence classes. There exist some basic sets of objects and attributes that are used to not only reflect the equivalence relation and order relation, but also constitute all formal concepts derived from the formal context. The properties of these basic sets are studied and analyzed.

关键词： cognitive informatics Humans Information analysis Knowledge representation Artificial intelligence Brain modeling Data analysis Computer science Signal analysis Signal processing

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Signature Forgery Detection using Convolutional Neural Networks

Signature Forgery Detection using Convolutional Neural Netwo...

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Data Intelligence and cognitive informatics (ICDICI), International Conference on

作者： Mohammad Arshad B. Devananda Rao M. Ratna Sirisha S. Lingaiah Kukunoor Shekar T. Benarji Department of CSE Deccan College of Engineering and Technology Hyderabad TS India Department of CSE MLR Institute of Techonology Hyderabad India Department of Computer Science and Engineering (CSE) CVR College of Engineering Hyderabad Department of Computer Science and Engineering Indur Institute of Engineering and Technology Siddipet TS

ISBN: (数字)9798350389609

ISBN: (纸本)9798350389616

Signature of a person can uniquely identify the person and it is widely used in social situations and monetary transactions with individuals and financial entities. Many fraud cases have been appearing in society where signature of a person is forged for financial and other benefits. There is need for detecting forged signatures with technology driven approaches. With the emergence of Artificial Intelligence (AI), there are unprecedented possibilities in solving problems of the real world with responsible usage of AI. Deep learning (DL) is one part of AI which extends neural networks has become very significant in computer vision applications. From the existing approaches, it is observed that there is need for a complete framework for end to end processing of signatures for efficient detection of forgeries. Towards this end, we proposed a DL based framework for automatic detection of signature forgery. The framework is designed to leverage performance of the models. We proposed an algorithm known as Learning based Signature Forgery Detection (LbSFD) which exploits pipeline of multiple DL models such as CNN, VGG16 and Siamese. All the models are CNN variants used to improve efficiency in signature forgery detection. A benchmark signature dataset is used for our empirical study. Our experiments revealed that the CNN based models are highly efficient in signature forgery detection. Highest accuracy with 98.26% is achieved when VGG16 model is employed with transfer learning.

关键词： Deep learning Computer vision Neural networks Transfer learning Pipelines Forgery Fraud Convolutional neural networks cognitive informatics Artificial intelligence

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cognitive bioinformatics: computational cognitive model for dynamic problem solving

Cognitive bioinformatics: computational cognitive model for ...

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IEEE International Conference on cognitive informatics

作者： O.A. Kuchar J.F. Reyes-Spindola M. Benaroch Pacific Northwest National Laboratory Richland WA USA Center for Creation and Management of Digital Ventures Martin J. Whitman School of Management Syracuse University Syracuse NY USA

We describe a new computational cognitive model that is being developed for solving complex problems in bioinformatics. This cognitive model was developed based on observing biologists solving problems in their current environments. Bioinformatics provides several challenges to current problem-solving environments: 1) massive heterogeneous data to mine and fuse; 2) quantity of information is growing and changing on a monthly basis; 3) knowledge base is being challenged and changed as biologists learn more (this occurs on a very short schedule). This paper describes the problem domain, evolution of this new model, the model itself how this model relates to current literature, and concludes with a summary of our ongoing research efforts.

关键词： Bioinformatics Problem-solving Biological system modeling Biology computing Humans Databases Laboratories Computational modeling Fuses cognitive informatics

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Voice-to-Text Summarization and Patient Interaction Systems

Voice-to-Text Summarization and Patient Interaction Systems

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Data Intelligence and cognitive informatics (ICDICI), International Conference on

作者： Surabhi Byju Department of Electronics Engineering VES Institute of Technology Mumbai India

ISBN: (数字)9798350389609

ISBN: (纸本)9798350389616

The integration of artificial intelligence in healthcare is revolutionizing patient care and administrative processes. This paper presents a novel system that leverages AI for voice recognition, summarization, and interaction within a healthcare setting. To enhance patient engagement and streamline appointment management, the stored data is interfaced with a Dialogflow-based chatbot. This chatbot allows patients to book appointments, set reminders, and receive personalized healthcare information. This research highlights the practical applications of AI in healthcare, showcasing the benefits of integrating voice recognition, natural language processing, and conversational agents to create a seamless, efficient, and patient-centric healthcare environment.

关键词： Refining Medical services Speech recognition Chatbots cognitive informatics Artificial intelligence

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Meta-Modeling Process of Pedagogical Strategies in Intelligent Tutoring Systems

Meta-Modeling Process of Pedagogical Strategies in Intellige...

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IEEE International Conference on cognitive informatics

作者： Adán A. Gómez Manuel F. Caro Dept.Informática Educativa Universidad de Córdoba Montería Colombia

ISBN: (纸本)9781538633618

Modeling process of personalization of pedagogical strategies in Intelligent Tutoring Systems (ITS) is a difficult and time-consuming task due to the number and complexity of processes involved. This research presents a Metamodel for the personalized adaptation of pedagogical strategies in ITS. The Metamodel called METAGOGIC (Metamodel of Personalized adaptation of Pedagogical Strategies in intelligent tutoring systems) was synthetized from the analysis of 45 ITS models that exist in the literature. The Metamodel is structured into five packages: MetaCore, Planner, Advisor Package, Assessment Package and User Package. The Metamodel Validation Process was carried out using two techniques: Comparison with other Models and Frequency-based Selection.

关键词： Handheld computers Metamodeling cognitive informatics cognitive systems Computational modeling Art Navigation

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