Over the past few decades, interest in unmanned aerial vehicles and in particular quadcopters has increased due to the wide range of possible research applications that can benefit from the use of quadcopters. Insulator inspection on overhead lines has traditionally relied heavily on visual inspection. This task is both cumbersome and relies heavily on the experience of the inspector. It is also extremely dangerous as the inspector needs to work in close proximity with overhead lines, and contact with these lines can be fatal. This paper focuses on the development of a quadcopter based system that is able to inspect insulators on overhead power lines autonomously.
Envelope tracking is one of the methods used to enhance the efficiency of power amplifiers. Shaping function is a mathematical model used in envelop tracking that shows the relation between the biased voltage and the input power of the amplifier. In this paper, a new shaping function, that will allow the user to control the performance of the amplifier with the best possible efficiency, is introduced. The introduced shaping function could be used for any amplifier and could be modified to achieve any desired performance.
Currently, there is a large move towards 5G wireless technology beyond the existing, widely used 4G technology due to an increased use of smart devices, and multimedia content. 5G technology is expected to operate at high frequencies between 15 GHz and 100 Ghz opening up a new horizon for spectrum constrained future wireless communications. Designing high efficiency power amplifiers for such high frequencies presents a new challenge. This paper presents different designs of integrated PAs operating at 15-100 GHz for 5G applications.
This paper presents an area and power efficient multi-output switched capacitor (MOSC) DC-DC buck converter for energy-equality scalable SoCs including wearable biomedical devices. The MOSC converter has an input voltage range between 1.05V to 1.4V and generates two simultaneous regulated output voltages of 1V and 0.55V. The MOSC consists of two main blocks; a switched capacitor regulator and an adaptive time multiplexing (ATM) controller. The switched capacitor regulator generates a single regulated voltage using pulse frequency modulation based on a predetermined reference voltage. In addition, the ATM controller generates two simultaneous output voltages using pulse width modulation and eliminates the reverse current during the switching between the output voltages. Addressing the reverse current problem is important to reduce the voltage droop at the output resulting in a better performance.
In this paper we evaluate our proposed modification in the Stochastic Planning Using Decision Diagrams (SPUDD) to explicitly include and describe multi-objective problems. In order to test that we have used single objective Symbolic Perseus which is a Partially Observable Markov Decision Processes (POMDP) solver. We have created a parser that reads the multi-objective costs from the SPUDD and a scalarization function in Symbolic Perseus so it can be solved. In this paper we show promising results of experiments conducted to evaluate the parser and the scalarization function with different set of weights and compare it to the original SPUDD format.
Process mining is an emerging discipline that aims to analyze business processes using event data logged by IT system. Most of existing process mining techniques assume that there is a one-to-one mapping between process model activities and the events that are recorded during process execution. However, event logs and process model activities are at different level of granularity. In this paper, we present a machine learning-based approach to map low-level event logs to high-level activities. With this work, we can bridge the abstraction levels when labels are not available. The proposed approach consists of two main phases: automatic labeling and machine learningbased classification. In automatic labeling a modified k- prototypes clustering approach has been used in order to obtain the labeled examples. Then, in the second phase, we trained different machine learning classifiers using the obtained labeled examples. We verified our proposed approach using a real-world event log.
A method for reducing streaking artifacts in 4D-CT reconstruction by generating additional projections is proposed. The proposed method uses an Artificial Neural Network (ANN)-based interpolation algorithm for image generation. Deformable image registration algorithm is used to estimates the motion between the original images. Then, a multi-layer perceptron feedforward neural network with an adaptive learning procedure is used to interpolate the in-between images from original ones. Phantom and real-patient Computed Tomography (CT) scans are going to be used to test the algorithm. The generated images will be compared to the original ones to test the accuracy of the proposed algorithm.
It is known that there have been numerous improvements in the field of Intelligent Transportation Systems using VANETs which encouraged many to develop intelligent traffic control approaches to replace the current technology using traffic lights. One approach was proposed by Elhadef in [3], which was to improve the inVANETs-based intersection control algorithm that was developed by Wu et al. to adapt to real life traffic scenarios or accidents. It is implemented using vehicle-tovehicle or vehicle-to-infrastructure communications as the vehicles exchange messages to get the opportunity to cross the intersection. In this paper, we present our work in simulating inVANETsbased traffic control for future smart cities using OMNet++, SUMO, and VEINS simulation tools.
We demonstrate an integrated model to retrieve and map satellite image from the image warehouse. Our idea is to detect the geographical location of remote sensing images using deep convolutional neural network (CNN). We train the VGGNet-16 model employing Fully-Connected2 (FC2) features based on a reference dataset based on the closest match found. Once, we obtain the closest match, we use Speeded-Up Robust Features (SURF) to detect the tie points between the new image and reference image. The tie points can be used to register the test image with the reference image automatically. Performance evaluation of our proposed model is performed on satellite image acquired in 2015 using WorldView-2 satellite over Abu Dhabi, United Arab Emirates. We also perform experimentation with Google Earth image of different resolution to demonstrate the robustness of our approach.
Vehicular Ad Hoc Networks (VANETs) are emerging as an enabler for distributed transport application such as traffic management and multimedia sharing. In urban VANET, basic routing protocols are affected by the urban environment elements such as intersections and traffic lights which lead to frequently changing network topology and uneven vehicle distribution. Multiple routing protocols overcome this problem by introducing a street connectivity metric for relay selection. This paper presents a survey of routing protocols using street connectivity prediction in urban VANETs. Moreover, a discussion of the limitations in the surveyed protocols is presented.
