In this paper, we present the first results of a study exploring how to support collaborative learning of surgical nursing students in a 3D virtual world. A Virtual Operating room, resembling the one at St. Olav's...
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In this paper, design and development of a ubiquitous tracking system is proposed, in which vehicles are tracked and controlled using the prevailing cellular technologies. The system contains a GPS receiver and a GSM ...
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In this paper, design and development of a ubiquitous tracking system is proposed, in which vehicles are tracked and controlled using the prevailing cellular technologies. The system contains a GPS receiver and a GSM modem interfaced with a microcontroller. To track any vehicle, the vehicle's owner has to send an SMS to the tracking system installed inside the vehicle. Upon receiving the SMS, the microcontroller takes the current location's longitude and latitude coordinates from GPS receiver, packs it into an SMS and sends it to the owner and on a web server using GSM modem. When the web server receives the SMS containing vehicles coordinates, it will show location of the vehicle on Google Maps. For android users, the location is also displayed on an android application. In case of vehicle theft, the owner is able to turn off the main ignition switch, check status and speed of the vehicle simply by sending an SMS. The system is also equipped with a special security button for parked vehicles. By turning the button ON, the system will come in ACTIVE mode and will keep a special check on the vehicle's movement meanwhile performing the normal tasks. If the system senses any movement of vehicle during the ACTIVE mode, it will turn the main ignition OFF and will inform the owner immediately be sending 5 SMSs. Record of the vehicle's movement will be continuously managed on the web server where each owner will have vehicle's account. We have used a wide number of technologies including, but not limited to, Global Positioning System (GPS), Global System for Mobile Communication (GSM) and Microcontroller.
Video tools developed today, teachers can record lecture videos and upload these lecture videos to e-learning system themselves. However, some students may only do not understand some fragments but they have to waste ...
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Video tools developed today, teachers can record lecture videos and upload these lecture videos to e-learning system themselves. However, some students may only do not understand some fragments but they have to waste unnecessary time download entire video, and therefore video scene segmentation is relative importance. In addition, in traditional teaching model, students must listen and transcribe content on blackboard, when the lecture's write speed is too fast, students are very difficult to pay attention in class and easy to transcription errors. If we can record the lecture video and automatically extract content on the blackboard, students not only enable index videos easily, but also not easily transcribe the wrong notes. Hence, this paper presents an intelligent assistance system for lecture videos. We use K-mean Segmentation to extract blackboard area and then only update this area to avoid lecturer's body cover the content on blackboard. Then we use adaptive threshold to extract chalk and design a method to reduce noise. After that we detecting the lecture videos split timing with statistics chalk pixel count and analysis the variation. Finally, we further interception the most complete content as lecture note to facilitate the students to search for video clips.
Vehicular Ad-hoc Networks (VANET) are employing heterogeneous technologies now a days to meet the increasing demands of Intelligent Transportation System (ITS) applications such as enriched multimedia, video conferenc...
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Vehicular Ad-hoc Networks (VANET) are employing heterogeneous technologies now a days to meet the increasing demands of Intelligent Transportation System (ITS) applications such as enriched multimedia, video conferencing, gaming and online collaboration. Deployment and maintenance cost for infrastructures are also a major concern. This work proposes a framework, capable of catering multiple technologies simultaneously (such as local area network, wide area networks and cellular networks), that deploys wired and wireless integrated technologies to exploit the advantages of both. Therefore, it offers the architecture based on radio over fiber technology to meet the future requirements of high data rate for Road Vehicle Communication (RVC) in VANETs and it comes up with the most important and perhaps desperately needed feature of ‘Future technology Support’ yielding very high data rates support. Several traditionally deployed architectures are striving to come up with the future needs but due to their various limitations they were unable to attain their expected outcomes. The proposed RoF based architecture justifies its need inducing a true value and powerful features to dramatically enhance the overall performance of the entire system. Several evaluation parameters have been chosen that clearly present the strength of proposed RoF framework and prove that RoF framework is the better option for the service providers in the area of ITS applications.
The paper reviews the status of fuzziness, vagueness, uncertainty, and probability in natural language with an emphasis on: aspects of natural language that pertain to each of the four phenomena; methods of their mode...
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The paper reviews the status of fuzziness, vagueness, uncertainty, and probability in natural language with an emphasis on: aspects of natural language that pertain to each of the four phenomena; methods of their modeling and representation; computational treatment of these phenomena in natural language and information processing. The main thrust of the paper is the procedure for calculating the predominant type of uncertainty for a NL sentence.
Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, a novel leaf image...
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Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, a novel leaf image recognition technique via sparse representation is proposed for automatic plant identification. In order to model leaf images, we learn an overcomplete dictionary for sparsely representing the training images of each leaf species. Each dictionary is learned using a set of descriptors extracted from the training images in such a way that each descriptor is represented by linear combination of a small number of dictionary atoms. For each test leaf image, we calculate the correlation between the image and each learned dictionary of leaf species to achieve the identification of the leaf image. As a result, efficient leaf recognition can be achieved on public leaf dataset based on the proposed framework leading to a more compact and richer representation of leaf images compared to traditional clustering approaches. Moreover, our method is also adapted to newly added leaf species without retraining classifiers and suitable to be highly parallelized as well as integrated with any leaf image descriptors/features.
Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, we conduct a compa...
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Automatic plant identification via computer vision techniques has been greatly important for a number of professionals, such as environmental protectors, land managers, and foresters. In this paper, we conduct a comparative study on leaf image recognition and propose a novel learning-based leaf image recognition technique via sparse representation (or sparse coding) for automatic plant identification. In our learning-based method, in order to model leaf images, we learn an overcomplete dictionary for sparsely representing the training images of each leaf species. Each dictionary is learned using a set of descriptors extracted from the training images in such a way that each descriptor is represented by linear combination of a small number of dictionary atoms. Moreover, we also implement a general bag-of-words (BoW) model-based recognition system for leaf images, used for comparison. We experimentally compare the two approaches and show unique characteristics of our sparse coding-based framework. As a result, efficient leaf recognition can be achieved on public leaf image dataset based on the two evaluated methods, where the proposed sparse coding-based framework can perform better.
This paper presents improved Adaptive Medium Access Control (iA-MAC) protocol for Wireless Body Area Networks (WBANs). In addition to the adaptive guard band assignment technique, the newly proposed protocol has an im...
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This paper presents improved Adaptive Medium Access Control (iA-MAC) protocol for Wireless Body Area Networks (WBANs). In addition to the adaptive guard band assignment technique, the newly proposed protocol has an improved as well as adaptive sleep/wakeup mechanism. We consider a simple temperature measuring application, where sensors (nodes) sense human body for updated information. If the current readings are within normal range, nodes stay in idle state (do not access channel). On the other hand, if the current sensed information is within high range then nodes switch to active state and access the channel because critical information needs to be transmitted as soon as possible. Besides the normal and high ranges of temperature, if the current sensed temperature lies with pre-high range then nodes access for channel if and only if the current sensed data is not duplicated version of the previously sensed data. Moreover, iA-MAC uses well defined synchronization mechanism to avoid collisions between data as well as control packets. Simulation results show that performance of the newly proposed iA-MAC protocol is better than its existing counter part protocols in terms of the selected performance metrics.
VoIP, which is used to deliver voice data on the Internet, is being welcomed as a means of replacing the PSTN. In VoIP, voice data are converted to Internet protocol data packets so that they can be delivered in an or...
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