دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — بخش سی و پنجم
منطق فازی (Fuzzy Logic) اولین بار در پی تنظیم نظریه مجموعه‌های فازی به وسیله پروفسور لطفی زاده (۱۹۶۵ میلادی) در صحنه محاسبات نو ظاهر شد. در واقع منطق فازی از منطق ارزش‌های «صفر و یک» نرم‌افزارهای کلاسیک فراتر رفته و درگاهی جدید برای دنیای علوم نرم‌افزاری و رایانه‌ها می‌گشاید، زیرا فضای شناور و نامحدود بین اعداد صفر و یک را نیز در منطق و استدلال‌های خود به کار می‌گیرد. در ادامه مقالات علمی انتشارات بین المللی اشپرینگر (Springer) در زمینه منطق فازی (Fuzzy Logic) برای دانلود آمده است. می توانید برای دانلود هر یک از مقالات از سرور دانلود متلب سایت، بر روی لینک دانلود هر یک از آن ها، کلیک کنید.
این نوشته حاوی بخشی از مجموعه کامل مقالات است. برای دریافت سایر بخش ها، به لینک زیر مراجعه نمایید:
دانلود رایگان مجموعه مقالات علمی اشپرینگر در زمینه منطق فازی — فهرست اصلی
| عنوان اصلی مقاله | Context-aware visual analysis of elderly activity in a cluttered home environment |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Muhammad Shoaib, Ralf Dragon, Joern Ostermann |
| چکیده / توضیح | This paper presents a semi-supervised methodology for automatic recognition and classification of elderly activity in a cluttered real home environment. The proposed mechanism recognizes elderly activities by using a semantic model of the scene under visual surveillance. We also illustrate the use of trajectory data for unsupervised learning of this scene context model. The model learning process does not involve any supervised feature selection and does not require any prior knowledge about the scene. The learned model in turn de-fines the activity and inactivity zones in the scene. An activity zone further contains block-level reference information, which is used to generate features for semi-supervised classification using transductive support vector machines. We used very few labeled examples for initial training. Knowledge of activity and inactivity zones improves the activity analysis process in realistic scenarios significantly. Experiments on real-life videos have validated our approach: we are able to achieve more than 90% accuracy for two diverse types of datasets. |
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| عنوان اصلی مقاله | Adaptive low-rank channel estimation for multi-band OFDM ultra-wideband communications |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Chia-Chang Hu, Shih-Chang Lee |
| چکیده / توضیح | In this paper, an adaptive channel estimation scheme based on the reduced-rank (RR) Wiener filtering (WF) technique is proposed for multi-band (MB) orthogonal frequency division multiplexing (OFDM) ultra-wideband (UWB) communication systems in multipath fading channels. This RR-WF-based algorithm employs an adaptive fuzzy-inference-controlled (FIC) filter rank. Additionally, a comparative investigation into various channel estimation schemes is presented as well for MB-OFDM UWB communication systems. As a consequence, the FIC RR-WF channel estimation algorithm is capable of producing the bit-error-rate (BER) performance similar to that of the full-rank WF channel estimator and superior than those of other interpolation-based channel estimation schemes. |
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| عنوان اصلی مقاله | Improved local spectrum sensing for cognitive radio networks |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Waleed Ejaz, Najam ul Hasan, Muhammad Awais Azam, Hyung Seok Kim |
| چکیده / توضیح | The successful deployment of dynamic spectrum access requires cognitive radio (CR) to more accurately find the unoccupied portion of the spectrum. An accurate spectrum sensing technique can reduce the probability of false alarms and misdetection. Cooperative spectrum sensing is usually employed to achieve accuracy and improve reliability, but at the cost of cooperation overhead among CR users. This overhead can be reduced by improving local spectrum sensing accuracy. Several signal processing techniques for transmitter detection have been proposed in the literature but more sophisticated approaches are needed to enhance sensing efficiency. This article proposes a two-stage local spectrum sensing approach. In the first stage, each CR performs existing spectrum sensing techniques, i.e., energy detection, matched filter detection, and cyclostationary detection. In the second stage, the output from each technique is combined using fuzzy logic in order to deduce the presence or absence of a primary transmitter. Simulation results verify that our proposed technique outperforms existing local spectrum sensing techniques. The proposed approach shows significant improvement in sensing accuracy by exhibiting a higher probability of detection and low false alarms. The mean detection time of the proposed scheme is equivalent to that of cyclostationary detection. |
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| عنوان اصلی مقاله | Human tracking with an infrared camera using a curve matching framework |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Suk Jin Lee, Gaurav Shah, Arka Aloke Bhattacharya, Yuichi Motai |
| چکیده / توضیح | The Kalman filter (KF) has been improved for a mobile robot to human tracking. The proposed algorithm combines a curve matching framework and KF to enhance prediction accuracy of target tracking. Compared to other methods using normal KF, the Curve Matched Kalman Filter (CMKF) method predicts the next movement of the human by taking into account not only his present motion characteristics, but also the previous history of target behavior patterns-the CMKF provides an algorithm that acquires the motion characteristics of a particular human and provides a computationally inexpensive framework of human-tracking system. The proposed method demonstrates an improved target tracking using a heuristic weighted mean of two methods, i.e., the curve matching framework and KF prediction. We have conducted the experimental test in an indoor environment using an infrared camera mounted on a mobile robot. Experimental results validate that the proposed CMKF increases prediction accuracy by more than 30% compared to normal KF when the characteristic patterns of target motion are repeated in the target trajectory. |
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| عنوان اصلی مقاله | Maneuvering target tracking using fuzzy logic-based recursive least squares filter |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | En Fan, Wei-xin Xie, Zong-xiang Liu |
| چکیده / توضیح | In this paper, a fuzzy logic-based recursive least squares filter (FLRLSF) is presented for maneuvering target tracking (MTT) in situations of observations with unknown random characteristics. In the proposed filter, fuzzy logic is applied in the standard recursive least squares filter (RLSF) by the design of a set of fuzzy if-then rules. Given the observation residual and the heading change in the current prediction, these rules are used to determine the magnitude of the fading factor of RLSF. The proposed filter has an advantage in which the restrictive assumptions of statistical models for process noise, measurement noise, and motion models are relaxed. Moreover, it does not need a maneuver detector when tracking a maneuvering target. The performance of FLRLSF is evaluated by using a simulation and real test experiment, and it is found to be better than those of the traditional RLSF, the fuzzy adaptive α-β filter (FAα-βF), and the hybrid Kalman filter in tracking accuracy. |
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| عنوان اصلی مقاله | Intelligent throat polyp detection with separable compressive sensing |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Wei Wang, Dunqiang Lu, Ying Wang, Qinghua Chen, Baoju Zhang |
| چکیده / توضیح | Compressive sensing can minimize the collection of redundant data in the acquisition step. However, it requires a huge amount of storage and creates a tremendous computation burden due to the size of random measurement matrix in compressive sensing theory for big data collection. The separable compressive sensing theory uses two-dimensional separable random measurement matrixes instead of a huge size of random matrix to remedy sensing matrix storage and computation complexity. In this paper, we proposed an intelligent throat polyp detection with singular value decomposition and support vector machine algorithms based on the vowel/a:/and/i:/voices. We compared the detection effects of the proposed intelligent detection method between original voice signals and compressed signals which were collected by separable compressive sensing theory. The experimental results showed that the matrix size of original vowel voices signal could affect the correct rate of prediction. Also, the correct rate of prediction was stable under different random measurement matrix and different compressed ratio. |
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| عنوان اصلی مقاله | Visual sensor fusion for active security in robotic industrial environments |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Sandra Robla, Jose R Llata, Carlos Torre-Ferrero, Esther G Sarabia, Victor Becerra, Juan Perez-Oria |
| چکیده / توضیح | This work presents a method of information fusion involving data captured by both a standard charge-coupled device (CCD) camera and a time-of-flight (ToF) camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time-of-flight information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time, this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localisation. Further development of these methods will make it possible to identify objects and their position in the real world and to use this information to prevent possible collisions between the robot and such objects. |
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| عنوان اصلی مقاله | Logic modeling and the ridiculome under the rug |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Michael L Blinov, Ion I Moraru |
| چکیده / توضیح | Logic-derived modeling has been used to map biological networks and to study arbitrary functional interactions, and fine-grained kinetic modeling can accurately predict the detailed behavior of well-characterized molecular systems; at present, however, neither approach comes close to unraveling the full complexity of a cell. The current data revolution offers significant promises and challenges to both approaches - and could bring them together as it has spurred the development of new methods and tools that may help to bridge the many gaps between data, models, and mechanistic understanding. |
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| عنوان اصلی مقاله | Closed-loop insulin delivery for treatment of type 1 diabetes |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | Daniela Elleri, David B Dunger, Roman Hovorka |
| چکیده / توضیح | Type 1 diabetes is one of the most common endocrine problems in childhood and adolescence, and remains a serious chronic disorder with increased morbidity and mortality, and reduced quality of life. Technological innovations positively affect the management of type 1 diabetes. Closed-loop insulin delivery (artificial pancreas) is a recent medical innovation, aiming to reduce the risk of hypoglycemia while achieving tight control of glucose. Characterized by real-time glucose-responsive insulin administration, closed-loop systems combine glucose-sensing and insulin-delivery components. In the most viable and researched configuration, a disposable sensor measures interstitial glucose levels, which are fed into a control algorithm controlling delivery of a rapid-acting insulin analog into the subcutaneous tissue by an insulin pump. Research progress builds on an increasing use of insulin pumps and availability of glucose monitors. We review the current status of insulin delivery, focusing on clinical evaluations of closed-loop systems. Future goals are outlined, and benefits and limitations of closed-loop therapy contrasted. The clinical utility of these systems is constrained by inaccuracies in glucose sensing, inter- and intra-patient variability, and delays due to absorption of insulin from the subcutaneous tissue, all of which are being gradually addressed. |
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| عنوان اصلی مقاله | Relational grounding facilitates development of scientifically useful multiscale models |
| نوع مقاله | مقاله ژورنال |
| نویسندگان | C Anthony Hunt, Glen EP Ropella, Tai ning Lam, Andrew D Gewitz |
| چکیده / توضیح | We review grounding issues that influence the scientific usefulness of any biomedical multiscale model (MSM). Groundings are the collection of units, dimensions, and/or objects to which a variable or model constituent refers. To date, models that primarily use continuous mathematics rely heavily on absolute grounding, whereas those that primarily use discrete software paradigms (e.g., object-oriented, agent-based, actor) typically employ relational grounding. We review grounding issues and identify strategies to address them. We maintain that grounding issues should be addressed at the start of any MSM project and should be reevaluated throughout the model development process. We make the following points. Grounding decisions influence model flexibility, adaptability, and thus reusability. Grounding choices should be influenced by measures, uncertainty, system information, and the nature of available validation data. Absolute grounding complicates the process of combining models to form larger models unless all are grounded absolutely. Relational grounding facilitates referent knowledge embodiment within computational mechanisms but requires separate model-to-referent mappings. Absolute grounding can simplify integration by forcing common units and, hence, a common integration target, but context change may require model reengineering. Relational grounding enables synthesis of large, composite (multi-module) models that can be robust to context changes. Because biological components have varying degrees of autonomy, corresponding components in MSMs need to do the same. Relational grounding facilitates achieving such autonomy. Biomimetic analogues designed to facilitate translational research and development must have long lifecycles. Exploring mechanisms of normal-to-disease transition requires model components that are grounded relationally. Multi-paradigm modeling requires both hyperspatial and relational grounding. |
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