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检索条件"任意字段=8th IEEE International Enterprise Distributed Object Computing Conference"

共 1278 条记录，以下是291-300 订阅

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Low Carbon Constrained EPQ Model and computing 8

Low Carbon Constrained EPQ Model and Computing

引用

8th international conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)

作者： Zhang Ru-yun Liu Qing Wuhan Univ Technol Sch Transportat Wuhan Peoples R China North China Univ Water Resources & Elect Power Sch Management & Econ Zhengzhou Peoples R China Natl Engn Res Ctr Water Transport Safety Wuhan Peoples R China

ISBN: (纸本)9781538682463

Carbon constraints policies shall be prepared based on effects of carbon tax policies on different types of enterprises to achieve win-win results for the government and enterprises. A production-inventory model was established to the carbon tax constraints in this study to discuss the effects of carbon tax policies on inventory plans and carbon emissions of different types of enterprises and perform comparative analysis to the sensitivity of carbon tax rates for different types of enterprises. Numerical results demonstrate: enterprises may actively adjust their production-inventory arrangements under the current carbon tax policies so that carbon tax costs may fall;and as for any enterprise, the higher its production unit costs are, the weaker the sensitivity of its carbon taxes (namely its emission reduction may not be under good control by means of carbon tax policies). Suggestions were finally presented in accordance with our study conclusions to production enterprises and those who prepared carbon constraint policies.

关键词： EPQ dynamic optimization carbon tax model

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Message from the TEAR 2017 Workshop Chairs 21

Message from the TEAR 2017 Workshop Chairs

引用

21st ieee international enterprise distributed object computing conference (EDOC)

作者： Aier, Stephan Franke, Ulrik Mocker, Martin Univ St Gallen St Gallen Switzerland Swedish Inst Comp Sci RISE SICS Kista Sweden Reutlingen Univ Reutlingen Germany MIT Cambridge MA 02139 USA

this paper gives a brief overview of the 12th Workshop on Trends in enterprise Architecture Research (TEAR) held at EDOC 2017. the paper introduces the Workshop research topics and presents the accepted papers.

ISBN: (纸本)9781538615683

关键词： enterprise Architecture enterprise Architecture Management

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object Position Estimation Using Stereo Vision

Object Position Estimation Using Stereo Vision

引用

ieee international Advance computing conference, IACC

作者： T Goutham Sharma Nitya Kritin Valivati Arvind Puthige Unnikrishnan Hari Dept. of Elect. and Communication Engg SRM University Kanchipuram Dst India School of Electrical and Comp. Engg Cornell University Ithaca New York

ISBN: (纸本)9781538666791;9781538666784

this paper aims to develop a method to extract 3D information from surrounding space in real time and to develop a control system to track a target object continuously. We used two cameras and utilized the concepts of ray optics, epipolar geometry and image processing to identify the target and find its world coordinates with reference to the cameras.

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A Case Study of Stakeholder Concerns on EAM 21

A Case Study of Stakeholder Concerns on EAM

引用

21st ieee international enterprise distributed object computing conference (EDOC)

作者： Hacks, Simon Brosius, Maximilian Aier, Stephan Rhein Westfal TH Aachen Res Grp Software Construct Aachen Germany Univ St Gallen Inst Informat Management St Gallen Switzerland

ISBN: (纸本)9781538615683

As a result of growing complexities in business processes, information systems, and the technical infrastructure, a key challenge for enterprise architecture management (EAM) is to guide stakeholders from different hierarchical levels with heterogeneous concerns. EA deliverables, such as models or frameworks, are often highly comprehensive and standardized. However, these can hardly be applied without greater adaption. Although the literature selectively covers approaches for tailoring EA deliverables closer to the concerns of affected stakeholders, these approaches are often vague or not very differentiated. In the paper at hand, we aim at introducing a stakeholder perspective to EAM research that considers stakeholder concerns on EAM across hierarchical levels. To this end, we conduct a case study: Our results show homogenous concerns among stakeholders on EA deliverables. In turn, we found different concerns on the role of EAM in applying these deliverables, dependent on the hierarchical level of stakeholders. these findings stress the necessity for a more differentiated understanding of stakeholder concerns on EAM. Finally, we discuss the implications of our findings for an exemplary EAM approach.

关键词： enterprise architecture management (EAM) stake-holder concerns hierarchical level case study

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A distributed ALGORIthM FOR object TRACKING IN WIRELESS SENSOR NETWORKS USING DATA MINING BASED PREDICITION 8

A DISTRIBUTED ALGORITHM FOR OBJECT TRACKING IN WIRELESS SENS...

引用

8th international conference on computing, Communication and Networking Technologies (ICCCNT)

作者： Ansari, Nishat A. Deshpande, Umesh A. Tapas, Amit M. Jejani, Anushka A. Shri Ramdeobaba Coll Engn & Management Nagpur Maharashtra India Visvesvaraya Natl Inst Technol Nagpur Maharashtra India

ISBN: (纸本)9781509030385

object tracking is an important application of Wireless Sensor Networks (WSNs). One of the main challenges for designing an object tracking technique is energy conservation. Prediction based strategies are used to save energy. We consider an application where a WSN is installed in a forest for tracking the movement of animals (objects). Since, animals move in certain paths rather moving entirely randomly, we attempt to use this property. the movement patterns of the objects are extracted using a data mining technique. this information is used to predict the object movement with the aim to reduce the energy consumption in tracking. In situations where the prediction is erroneous, we propose a systematic recovery mechanism. the recovery mechanism has three levels. the number of additional nodes woken up progressively increases with the increase in the recovery level. If an object has been detected at a lower level, normal operations are resumed. It is observed that there are significant energy savings due to this systematic recovery mechanism. the proposed technique, called DESPOT, is fully distributed and energy efficient. We have carried out extensive simulation of DESPOT and have compared its performance with an existing technique, called PTSP. Simulation results show that DESPOT conserves significant energy and it has a better tracking efficiency than PTSP.

关键词： tracking prediciton data mining distributed wireless sensor networks

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Intent-based object Grasping by a Robot using Deep Learning

Intent-based Object Grasping by a Robot using Deep Learning

引用

ieee international Advance computing conference, IACC

作者： Faheem Hassan Zunjani Souvik Sen Himanshu Shekhar Aditya Powale Debadutta Godnaik G. C. Nandi Robotics and Machine Learning Laboratory Indian Institute of Information Technology Allahabad Allahabad India

ISBN: (纸本)9781538666791;9781538666784

A robot needs to predict an ideal rectangle for optimal object grasping based on the intent for that grasp. Mask Regional - Convolutional Neural Network (Detectron) can be used to generate the object mask and for object detection and a Convolutional Neural Network (CNN) can be used for ideal grasp rectangle prediction according to the supplied intent, as described in this paper. the masked image obtained from Detectron along with the metadata of the intent type has been fed to the Fully-Connected layers of the CNN which would generate the desired optimal rectangle for the specific intent and object. Before settling for a CNN for optimal rectangle prediction, conventional Neural Networks with different hidden layers have been tried and the accuracy achieved was low. A CNN has then been developed and tested with different layers and sizes of pool and strides to settle on the final CNN model that has been discussed here. the optimal predicted rectangle is then fed to a robot, ROS simulation of Baxter robot in this case, to perform the actual grasping of the object at the predicted location.

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DIMENSIONAL ANALYSIS OF objectS IN A 2D IMAGE 8

DIMENSIONAL ANALYSIS OF OBJECTS IN A 2D IMAGE

引用

8th international conference on computing, Communication and Networking Technologies (ICCCNT)

作者： Parihar, Anil Singh Gupta, Mayank Sikka, Vayu Kaur, Gurnaaz Delhi Technol Univ Dept Comp Sci & Engn Delhi India

ISBN: (纸本)9781509030385

the volume calculation and weight estimation of objects is used in many real world applications, such as calculating the nutritional content in food items, in forensic science, etc. While there are several existing models on volume estimation, a majority of these models are based on 3 dimensional images, which are difficult to obtain in real time and require expensive equipment. In this paper, a method is introduced to estimate the dimensions of an object in a 2D image provided by the user. three tasks are performed-object recognition using the algorithm of Haar Cascades, dimension calculation using a reference object and a Conversion Factor, and volume estimation using conventional 3D shape models for regular objects and a prediction model based on regression analysis for human body. the observed values are compared with the ground truth and obtained an accuracy of 93.69%.

关键词： object detection weight estimation calibration

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Classification Of Ovarian Cyst Using Soft computing technique 8

Classification Of Ovarian Cyst Using Soft computing techniqu...

引用

8th international conference on computing, Communication and Networking Technologies (ICCCNT)

作者： Parekh, Aarti M. Shah, Nidhi B. Sardar Vallabhbhai Patel Inst Technol Dept Comp Engn Vasad Gujarat India

ISBN: (纸本)9781509030385

Identification of ovarian status and follicle monitoring becomes the most important part in the evaluation of an infertile woman. Ultrasound or sonography has helped in diagnosis and treatment of infertile patients. Ultrasound imaging of the follicles in the ovary gives very important information about the ovary such as type of cyst, number of follicles and size of follicles response to hormonal imbalance. Image Segmentation gives more information in the region of interest in an image and clearly differentiate the object and the background from the image. But it is very hard to perform segmentation on ultrasound images due to presence of noise so by using image preprocessing with morphological operations, detection of follicles becomes easy and effective. Classification of Ovarian cyst is done using fuzzy logic.

关键词： ovary follicle segmentation classification

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Human-fall Detection from an Indoor Video Surveillance 8

Human-fall Detection from an Indoor Video Surveillance

引用

8th international conference on computing, Communication and Networking Technologies (ICCCNT)

作者： Agrawal, Subhash Chand Tripathi, Rajesh Kumar Jalal, Anand Singh GLA Univ Dept Comp Engn & Applicat Mathura India

ISBN: (纸本)9781509030385

In this paper, we present a human fall detection method from visual surveillance. In first step, background subtraction is performed using Improved GMM to find the foreground objects. In second step, contour based human template matching is applied to categorize the human or non-human object. It helps to detect fall incident by providing sudden change in generated score after matching. Height-width ratio is computed in third step to decide whether the human shape is changed or not. In fourth step, distance between top and mid centre of rectangle covering human is computed, if it is less than a certain threshold, then human fall is confirmed. Finally, if inactive pose of human is continued till 100 consecutive frames, then an alarm is generated to alert the people at home to provide treatment on time. Experiments have been performed on 21 video sequences having different usual and unusual fall incidents. Experimental results show that proposed system works well efficiently and effectively in real-time for recognizing human fall.

关键词： Human Fall foreground object height-width ratio contour

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Vision Based Motion Tracking in Real Time Videos 8

Vision Based Motion Tracking in Real Time Videos

引用

8th ieee international conference on Computational Intelligence and computing Research (ieee ICCIC)

作者： Balasundaram, A. Chellappan, C. GKM Coll Engn & Technol Dept CSE Chennai India GKM Coll Engn & Technol Chennai India

ISBN: (纸本)9781509066216

Motion tracking in a video involves the process of following the transition of an object from its initial position to the displaced position. An object can be anything such as a human, property, vehicle etc. Motion tracking has gained significant importance especially with the increase in the desire to develop computer vision based intelligent systems for video surveillance, human tracking, gestures and behavior study, anomaly detection, traffic monitoring etc. Optical flow is a common approach used in vision based motion tracking. this paper discusses in detail, the taxonomy of different algorithms in optical flow and strikes a comparison among the different optical flow algorithms. Also, the experimental observations made by tracking the human motion using two optical flow approaches have been presented and it could be found that Lucas-Kanade algorithm produced better tracking vectors when compared to Horn-Schunck algorithm.

关键词： Optical flow Lucas-Kanade Horn and Schunck Motiont object tracking

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