Algorithm Design

Particle Swarm Optimization is a popular heuristic search algorithm which is inspired by the social learning of birds or fishes. It is a swarm intelligence technique for optimization developed by Eberhart and Kennedy [1] in 1995. Inertia weight is an important parameter in PSO, which significantly affects the convergence and exploration-exploitation trade-off in PSO process. Since inception of Inertia Weight in PSO, a large number of variations of Inertia Weight strategy have been proposed. In order to propose one or more ...

In this paper, a new algorithm for Automatic License Plate Localisation and Recognition (ALPR) is proposed on the basis of isotropic dilation that can be achieved using the binary image Euclidean distance transform. In a blob analysis problem, any two Region of Interest (RoIs) that is discontinuous are typically treated as separate blobs. However, the proposed algorithm combine with Connected Component Analysis (CCA) are coded to seek for RoI within a certain distance of other RoI to be treated as non-unique. This paper investigates the design and implementation of several pre-processing techniques and isotropic dilation algorithm to classify moving vehicles with different backgrounds and varying angles. A multi-layer feed-forward back-propagation Neural Network is used to train the segmented and refined characters. The results obtained can be used for implementation in the vehicle parking management system.

Satellite-based navigation systems uses one-way ranging measurements for system orbit estimation and time-keeping, due to its operational advantage when compared with two-way ranging technique, in terms of complexity of ground monitoring stations (completely passive and requiring a simple omnidirectional antenna to track all the satellites in view). However, a sufficient number of simultaneous independent measurements is required to solve the system unknowns: in particular simultaneous visibility of multiple stations by an individual satellite (allowing to separate the ground stations clocks contributions since the SVs clocks disappear), as well as simultaneity of observations from the same monitor stations of a large number of satellites (allowing to recover the SVs clocks parameters, since the GSS clocks drop out) is the key to an effective separation in the solution of the clock contributions from the pseudo-ranges. In the Galileo IOV phase (consisting of 4 satellites on two orbital planes and a ground network of 20 Sensor Stations), the first condition is clearly fulfilled, however the second condition is not met for a considerable part of the time. If two GSSs do not see simultaneously a single Galileo satellite, they will not be able to estimate their clocks time and frequency drifts, i.e. they will not be synchronized. The free running clocks will essentially enter a holdover mode, were the relative time between the two stations will be slowly drifting as a function of the initial conditions and the stability of the clocks. The ground stations synchronization will gradually degrade with time and when a satellite will rise on the horizon they will be essentially not synchronized to the extent required to carry on a one-way-based Orbit Determination & Time Synchronization (OD&TS). During the IOV phase, the limited number of satellites available and the peculiar characteristics of the Galileo orbits will make difficult for the Orbit Determination and Time Synchronization to start producing meaningful data, therefore some form of intermediate operational configuration must be sought to help in the OD&TS process initialization. The paper will address the proposed solution to overcome the problem of Galileo system initialization starting from the intermediate configuration with first 2 satellites (first IOV Launch) up to final IOV Configuration after second IOV launch. The proposed solution will be based on a limited use of GPS to insure the synchronization of the Galileo Sensor Stations, relying on the exploitation of the Linked Common View Time Transfer (LCVTT) Technique, while the Galileo Orbit Determination and SVs clocks characterization will be carried on autonomously and independently by GPS, in a two step process, up to the achievement of the IOV Configuration with 4 satellites, when the nominal Orbit Determination and Time Synchronization process will be operated. Moreover the paper will address the development of the LCVTT Algorithm, carried on as part of development of the infrastructure aiming to support the Galileo Verification Phase currently under definition as part of Galileo Phase C/D/E1 contract. The algorithm design and implementation will be presented together with the validation carried out (both for LCVTT and MLCVTT) to verify that the synchronization accuracy is adequate to support the Galileo System Initialization.

This paper presents a framework that develops algorithms for solving combined locational and multihop routing optimization problems. The objective is to determine resource node locations in a multiagent network and to specify the multihop routes from each agent to a common destination through a network of resource nodes that minimize total communication cost. These problems are computationally complex (NP-hard) where

Many studies have focused in designing a set of good DNA sequences as it is one of the crucial tools in improving the reliability and efficiency of DNA computing. In this paper, an improved model of Ant Colony System is developed in optimizing DNA sequences design. The proposed model suggests that each artificial ant represents a possible solution of the

This paper discusses opportunities to parallelize graph based path planning algorithms in a time varying environment. Parallel architectures have become commonplace, requiring algorithm to be parallelized for efficient execution. An additional focal point of this paper is the inclusion of inaccuracies in path planning as a result of forecast error variance, accuracy of calculation in the cost functions and a different observed vehicle speed in the real mission than planned. In this context, robust path planning algorithms will be described. These algorithms are equally applicable to land based, aerial, or underwater mobile autonomous systems. The results presented here provide the basis for a future Research project in which the parallelized algorithms will be evaluated on multi and many core systems such as the dual core ARM Panda board and the 48 core Single-chip Cloud Computer (SCC). Modern multi and many core processors support a wide range of performance vs. energy tradeoffs th...

Hammersmith Infant Neurological Examination (HINE) is a set of tests used for grading neurological development of infants on a scale of 0 to 3. These tests help in assessing neurophysiological development of babies, especially preterm infants who are born before (the fetus reaches) the gestational age of 36 weeks. Such tests are often conducted in the follow-up clinics of hospitals for grading infants with suspected disabilities. Assessment based on HINE depends on the expertise of the physicians involved in conducting the examinations. It has been noted that some of these tests, especially pulled-to-sit and lateral tilting, are difficult to assess solely based on visual observation. For example, during the pulled-to-sit examination, the examiner needs to observe the relative movement of the head with respect to torso while pulling the infant by holding wrists. The examiner may find it difficult to follow the head movement from the coronal view. Video object tracking based automatic or semi-automatic analysis can be helpful in this case. In this paper, we present a video based method to automate the analysis of pulled-to-sit examination. In this context, a dynamic programming and node pruning based efficient video object tracking algorithm has been proposed. Pulled-to-sit event detection is handled by the proposed tracking algorithm that uses a 2-D geometric model of the scene. The algorithm has been tested with normal as well as marker based videos of the examination recorded at the neuro-development clinic of the SSKM Hospital, Kolkata, India. It is found that the proposed algorithm is capable of estimating the pulled-to-sit score with sensitivity (80%-92%) and specificity (89%-96%).

This research aims to model the process of data visualization (DV) and design to facilitate computational thinking (CT) of secondary-level students. As an interdisciplinary method for visualizing complex data, creating data visualizations requires learners to analyze data from knowledge of pure and applied science. This study investigates creating DV to facilitate CT as an interdisciplinary method which combines mathematics and information technology. The study was carried out using synthesised design-based research (DBR) method by conducting two cycles comprised of five phases: problem analysis within real-life context, design solution, develop solution, evaluate in practice and reflection. CT dimensions (decomposition, pattern recognition, abstraction, and algorithm design) were tested by using the Computational Thinking through Data Visualization Rubric and reflection form acquired during implementation. The sample consisted of secondary school students in the data visualization creation process with 27 in the first cycle and 31 in the second cycle. This research proposes a model to facilitate development of CT by DV with the analysis of complex data, creating an effective method by enabling analytics and visualizing data. The proposed DV development process facilitating CT has the potential to inform research on interdisciplinary learning environments.

As our knowledge of ductal carcinoma in situ (DCIS) continues to evolve, treatment decision-making has become increasingly complex and controversial for both patients and physicians. Treatment options include mastectomy, and breast conservation with or without radiation therapy. Data produced from the randomized clinical trials for DCIS has provided the basis for important treatment recommendations, but are not without limitations. In this article, we review our prospectively collected database consisting of 1036 patients with DCIS treated at the Van Nuys Breast Center and the USC/Norris Comprehensive Cancer Center. We review the use of the USC/Van Nuys Prognostic Index, a clinical algorithm designed to assist physicians in selection of appropriate treatments, and examine the impact of margin status as a sole predictor of local recurrence.

This paper presents an innovative traffic signal control algorithm, the IntelliGreen Algorithm (IGA), that utilizes IntelliDrive technologies to improve the efficacy of traffic signals. The IGA is fully decentralized and takes a novel approach to traffic signal control using k-means clustering. A VISSIM model of a real-world arterial was used to evaluate the IGA and its performance was compared to that of an actuated timing plan. The IGA consistently improved traffic mobility, and sustainability as volumes increased, even at lower IntelliDrive market penetration levels. The results demonstrate the power of IntelliDrive data and that decentralized traffic signal control can achieve system-wide benefits at lower computational costs.

Telugu is one of the oldest and popular languages of India, spoken by more than 66 million people, especially in South India. Not much work has been reported on the development of optical character recognition (OCR) systems for Telugu text. Therefore, it is an area of current research. Some characters in Telugu are made up of more than one connected symbol. Compound characters are written by associating modifiers with consonants, resulting in a huge number of possible combinations, running into hundreds of thousands. A compound character may contain one or more connected symbols. Therefore, systems developed for documents of other scripts, like Roman, cannot be used directly for the Telugu language. The individual connected portions of a character or a compound character are defined as basic symbols in this paper and treated as a unit of recognition. The algorithms designed exploit special characteristics of Telugu script for processing the document images efficiently. The algorithms have been implemented to create a Telugu OCR system for printed text (TOSP). The output of TOSP is in phonetic English that can be transliterated to generate editable Telugu text. A special feature of TOSP is that it is designed to handle a large variety of sizes and multiple fonts, and still provides raw OCR accuracy of nearly 98%. The phonetic English representation can be also used to develop a Telugu text-to-speech system; work is in progress in this regard.