VEHICLE CLASSIFICATION USING NEURAL NETWORKS AND IMAGE PROCESSING

Vehicle classification is getting important especially in security systems, surveillance, transportation congestion reduction, and accident prevention. However, it is difficult to classify the traffic objects due to the poor quality of images from videos. Hence, image processing techniques are applied to increase the accuracy of the result. The aim of this study is to propose a vehicle classification scheme where YOLO v5 algorithm and Faster R-CNN algorithm are being implemented separately into vehicle classification, followed by comparison of result between these two algorithms. In this study, vehicles are classified into five classes, namely motorcycle, car, van, bus and lorry. The labeled dataset is being split into training set and validation set and then trained under algorithm YOLO v5 and Faster R-CNN separately. Experimental results show that YOLO v5 performs better with the mean average Precision, Precision, and Recall rate up to 0.91, 0.81, and 0.86, respectivel

Linear-time heuristic partitioning technique for mapping of connected graphs into single-row networks

In this paper, a model called graph partitioning and transformation model (GPTM) which transforms a connected graph into a single-row network is introduced. The transformation is necessary in applications such as in the assignment of telephone channels to caller-receiver pairs roaming in cells in a cellular network on real-time basis. A connected graph is then transformed into its corresponding single-row network for assigning the channels to the caller-receiver pairs. The GPTM starts with the linear-time heuristic graph partitioning to produce two subgraphs with higher densities. The optimal labeling for nodes are then formed based on the simulated annealing technique. Experimental results support our hypothesis that GPTM efficiently transforms the connected graph into its single-row network

Partitioning Technique for Transformation of Connected Graphs into Single-Row Network

In this paper, we present our work called Connected Graph Sequence (CGS) which transforms a partially dense graph into the single-row network. Partially dense graph is a graph where a number of connected components, namely subgraphs, are connected by some links and each subgraph has a higher density value compare to the graph. The transformation is necessary in applications such as in the assignment of telephone channels to caller-receiver pairs roaming in cells in a cellular network on real-time basis. In this channel assignment application, each caller and receiver in a call is treated as a node, while their pair connection is treated as the edge. A specific case of the graph in the form of a partially dense graph is then transformed into its corresponding single-row network for assigning the channels to the caller-receiver pairs

Models Development for Single-Row Networks from Connected Graphs

In this paper, we present a collection of models for connected graphs mapping into single–row networks. The collection involves three specific models for perfect binary trees, trees and partially dense graphs, and three general models for connected graphs. These models are compared in terms of their structures, energy values, congestion and number of doglegs in the single–row transformation. The numerical experiments are run by each respective developed program. The transformation is necessary in applications such as in the assignment of telephone channels to caller–receiver pairs roaming in cells in a cellular network on real–time basis

Spanning Tree Transformation of Connected Graph into Single-Row Network

A spanning tree of a connected graph is a tree which consists the set of vertices and some or perhaps all of the edges from the connected graph. In this paper, a model for spanning tree transformation of connected graphs into single-row networks, namely Spanning Tree of Connected Graph Modeling (STCGM) will be introduced. Path-Growing Tree-Forming algorithm applied with Vertex-Prioritized is contained in the model to produce the spanning tree from the connected graph. Paths are produced by Path-Growing and they are combined into a spanning tree by Tree-Forming. The spanning tree that is produced from the connected graph is then transformed into single-row network using Tree Sequence Modeling (TSM). Finally, the single-row routing problem is solved using a method called Enhanced Simulated Annealing for Single-Row Routing (ESSR)

Comprehensive Development And Control Of A Path-Trackable Mecanum-Wheeled Robot

This paper presents an intuitively straightforward yet comprehensive approach in developing and controlling a Mecanum-wheeled robot (MWR), with decent path tracking performance by using a simple controller as an end objective. The development starts by implementing two computer ball mice as sensors to realize a simple localization that is immune toward wheel slippage. Then, a linearization method by using open-loop step responses is carried out to linearize the actuations of the robot. Open-loop step response is handy, as it directly portrays the non-linearity of the system, thus achieving effective counteraction. Then, instead of creating a lookup table, polynomial regression is used to generate an equation in which the equation later represents an element of the linearizer. Next, a linear angle-to-gain (LA-G) method is introduced for path tracking control. The method is as easy as just linearly maps the summation of two angles-the angle between immediate and desired positions and the MWR's heading angle, into gains to control the wheels. Unlike the conventional control method which involves inverse kinematics, the LA-G method is directly a displacement-controlled approach and does not require the knowledge of parametric values, such as the robot's dimensions and wheel radius. Finally, all the methods are implemented, and the MWR experimentally demonstrates successfully tracking various paths, by merely using proportional controllers

On-chip ultra low power optical wake-up receiver for wireless sensor nodes targeting structural health monitoring

Wireless sensor network (WSN) consists of distributed nodes deployed for monitoring the physical conditions and organizing collected data at the central control unit. Power consumption is the challenges in WSN as the network consists of wireless sensor nodes becomes denser. By utilizing WSN and visible light technology, a simple health monitoring system design can be approached that are smaller in size, faster and lower power consumption. This work focuses on design a low power optical wake-up receiver to reduce the energy consumption of each node in WSN. A wake-up receiver is designed to be always-on for detecting incoming signal and switches on the stand by protocol controller and WSN network for data transmission process. The characteristic of optical transmission and functional circuit of a wake-up receiver has been investigated. A low power optical wake-up receiver has been designed in 180nm Silterra CMOS process technology. The proposed wake-up receiver consumes only 443pW in standby mode and 1.89nW in active mode. The proposed optical wake-up receiver drastically reduces the power consumption by more than one third compared to other wake-up receivers which could be a milestone in the medical field if successfully conducted

Advanced Sheet Metal Manufacturing using Rapid Tooling 522

A closed loop process is proposed for making sheet metal prototyping parts by using advanced computer aided techniques and computer controlled machines. The key aspect of this process is the method used to fabricate and modify the sheet metal forming tools, which are not necessarily for mass production but should be suitable for short run production or design evaluation of sheet metal products where the prototyping cost and lead-time are greatly reduced. Various approaches are investigated in the preparation of the tooling for onward embossing on a sheet metal. The three indirect approaches use Selective Laser Sintering (SLS), Stereolithography(SLA), and high speed Computer Numerical Controlled (CNC) milling to build the masters from computer data models. And the masters are then served in the vacuum casting process to generate the non-ferrous tooling. The direct approach uses DTM’s RapidSteel to produce the metal tooling without going through any secondary process. Comparisons on quality, leading time and cost are presented.Mechanical Engineerin

On-Chip Ultra Low Power Optical Wake-Up Receiver For Wireless Sensor Nodes Targeting Structural Health Monitoring

Wireless sensor network (WSN) consists of distributed nodes deployed for monitoring the physical conditions and organizing collected data at the central control unit. Power consumption is the challenges in WSN as the network consists of wireless sensor nodes becomes denser. By utilizing WSN and visible light technology, a simple health monitoring system design can be approached that are smaller in size, faster and lower power consumption. This work focuses on design a low power optical wake-up receiver to reduce the energy consumption of each node in WSN. A wake-up receiver is designed to be always-on for detecting incoming signal and switches on the stand by protocol controller and WSN network for data transmission process. The characteristic of optical transmission and functional circuit of a wake-up receiver has been investigated. A low power optical wake-up receiver has been designed in 180nm Silterra CMOS process technology. The proposed wake-up receiver consumes only 443pW in standby mode and 1.89nW in active mode. The proposed optical wake-up receiver drastically reduces the power consumption by more than one third compared to other wake-up receivers which could be a milestone in the medical field if successfully conducte

Evaluation of Distribution Network Modelling for Electric Vehicle Charging Impact

Electric vehicle (EV) is a new and uprising technology in the transportation and power sector that benefits the economy and environment. This study presents a comprehensive review of electric vehicle technology and its associated equipment, such as battery charger and charging station. An introduction is made on the residential charging type of electric vehicles in terms of charging time, size of battery and power of charger. The influence of electric vehicle charging on utility distribution system in terms of voltage and thermal limits are investigated in this paper. The current power system may not able to support the EV charging loads. The usage of electric vehicles, customer power consumption behavior and the distribution of electric vehicle used in a residential area may affect its power system structure. To study the influence of EV charging in a power distribution system, analysis were conducted based on these three factors. Firstly, the new network will be simulated using all the standard parameter for residential. Secondly, the EV load will be inserted into the network based on different scenarios of EV’s penetration level and the investigation will be carried out to study the impact of EV on the distribution network in terms of voltage and thermal limits. It is found that the higher penetration level of EV charging will lead to the higher voltage drop and feeders’ thermal limit