Mohamed Shehata

Automatic License Plate Recognition (ALPR): A State-of-the-Art Review

Automatic license plate recognition (ALPR) is the extraction of vehicle license plate information from an image or a sequence of images. The extracted information can be used with or without a database in many applications, such as electronic payment systems (toll payment, parking fee payment), and freeway and arterial monitoring systems for traffic surveillance. The ALPR uses either a color, black and white, or infrared camera to take images. The quality of the acquired images is a major factor in the success of the ALPR. ALPR as a real-life application has to quickly and successfully process license plates under different environmental conditions, such as indoors, outdoors, day or night time. It should also be generalized to process license plates from different nations, provinces, or states. These plates usually contain different colors, are written in different languages, and use different fonts; some plates may have a single color background and others have background images. The license plates can be partially occluded by dirt, lighting, and towing accessories on the car. In this paper, we present a comprehensive review of the state-of-the-art techniques for ALPR. We categorize different ALPR techniques according to the features they used for each stage, and compare them in terms of pros, cons, recognition accuracy, and processing speed. Future forecasts of ALPR are given at the end.

Managing Policy Interactions in KNX-Based Smart Homes

Smart homes have enjoyed increasing popularity in recent years. In order for them to further expand their market share, users need to be able to fully control devices. Policies are one way for users to achieve such flexible control of devices. However, user policies often tend to interact in unwanted ways leading to unexpected behavior of devices. This paper describes the design of a run-time policy interaction management module (PIMM) that serves as manager for detecting and resolving interactions between user policies in KNX-based smart homes. This module extends the traditional KNX networking system with the ability to manage policy interactions. The module operates in the run-time S-mode of the KNX network and works as part of the engineering tool software (ETS) used to configure and control the operation of the KNX network in smart homes. The proposed module serves as the first of its kind that can be implemented inside the KNX networking system to detect and resolve unwanted policies interactions.

Effects of Alumina Nanoparticles Additives Into Jojoba Methyl Ester-Diesel Mixture on Diesel Engine Performance

Currently, using biofuels to operate diesel engines gets a great attention to the extent that it could replace the limited conventional fossil fuels. These fuels have a closed life cycle (renewable) and they have a remarkable effect on the global greenhouse phenomena. Moreover, the use of non-edible vegetable oils is considered a good choice after a suitable chemical and/or thermal treatment to convert them into esters. The use of jojoba oil shows a promising alternative fuel for conventional diesel fuel even there were unfavorable effects including power reduction. The wide spread usage of nano additives to improve the combustion quality may be a good solution for these problems. This study represents an experimental investigation to examine the effect of nano additives on diesel engine performance at variable operating conditions of load and speed. In this work, alumina nano-particles are added to a mixture of jojoba methyl ester (biodiesel) and conventional diesel fuel at the most recommended value (20% biodiesel and 80% diesel fuel) with different doses from 10 up to 50 mg/l. The received mixture is homogenized with an ultrasonicator mixer. It is found that, the appropriate nano-additives dose corresponding to optimal engine performance is about 30 mg/l. At this dose, the overall BSFC is reduced by about 6%, engine thermal efficiency is increased up to 7%, and all engine emissions have been reduced (NOx about 70%, CO about 75 %, smoke opacity about 5%, and UHC about 55 %) compared with the corresponding values obtained when only a blended fuel of 20% biodiesel is used.Copyright

An Algorithm to Compensate for Road Illumination Changes for AID Systems

Many ITS systems suffer from high false alarm rates due to static glare. Static glare appears in video scenes when the road is wet and light originating from static light source, such as road lamp, is reflected on the road. Often an Automatic Incidents Detection (AID) system will detect occurrences of static glare as incidents, causing the generation of false alarms. In this paper, an effective real-time algorithm is proposed to detect static glare. This algorithm generates a static glare map that can be used by an AID system to avoid static glare false alarms.

A Robust Video-Based Algorithm for Detecting Snow Movement in Traffic Scenes

Video-based Automatic Incident Detection (AID) systems are widely deployed in many cities for detecting traffic incidents to provide smoother, safer and congestion free traffic flow. However, the accuracy of an AID system operating in an outdoor environment suffers from high false alarm rates due to environmental factors. These factors include snow movement, static shadow and static glare on the roads. In this paper, a robust real-time algorithm is proposed to detect snow movement in video streams to improve the rate of detection. This is done by having the AID system reducing its sensitivity in the areas that have snow movements. The feasibility of the proposed algorithm has been evaluated using traffic videos captured from several cameras at the City of Calgary.

Eliminating illumination effects by discrete cosine transform (DCT) coefficients' attenuation and accentuation

In this paper, we proposed a discrete cosine transform (DCT)-based attnuation and accentuation method to remove lighting effects on face images for faciliating face recognition task under varying lighting conditions. In the proposed method, logorithm transform is first used to convert a face image into logarithm domain. Then discrete cosine transform is applied to obtain DCT coefficients. The low-frequency DCT coefficients are attenuated since illumination variations mainly concentrate on the low-frequency band. The high-frequency coefficients are accentuated since when under poor illuminations, the high-frequency features become more important in recognition. The reconstructed log image by inverse DCT of the modified coefficients is used for the final recognition. Experiments are conducted on the Yale B database, the combination of Yale B and Extended Yale B databases and the CMU-PIE database. The proposed method does not require modeling and model fitting steps. It can be directly applied to single face image, without any prior information of 3D shape or light sources.

Combustion Characteristics of Jojoba Methyl Ester as an Alternative Fuel for Gas Turbine

The strengthened requirements of new emission norms and the limited fuel resources are the major challenges for researchers over the world. The use of biofuels produced from vegetable oil will be a promising solution. In this case, Jojoba oil comes from very surprising plant as its seed contains 40–60% of its weight as raw oil and grows in desert. The trans-esterification process is used to convert jojoba oil into a Jojoba Methyl Ester (JME). This study aims to characterize the flame of JME as an alternative fuel in the gas turbines. Using of the premixed flame resulted in higher combustion efficiency and low emissions. The premixed flames for liquid fuels can be realized via use of lean premixed pre-vaporized (LPP) combustion method. In this work the jet fuel and blends of jet-JME fuel (with JME volume faction of 10, and 20%) are burned with LPP technique keeping the same equivalence ratio as it is used for burning the base jet fuel to determine the possibility to use the fuel mixture without any modifications in a specific LPP combustor. The main results indicate that, as volume content of JME increase the NOx emissions decrease to be lower than 10 ppm in case of B20. Moreover, the CO emission in case of B20 is higher than that of the jet fuel but at the end of the test section it does not exceed 0.15 %. In the same way, B20 produces higher UHC emissions than the jet fuel; however, at the end of the test section it does not exceed 80 ppm. So it can be concluded that blended Jojoba biodiesel can be used as an alternative fuel for jet fuel.Copyright

Unique Video Technology to Help Industry With the CSA Standard Z.246.1 E9 for Security Management

The new CSA Standard, Security Management for Petroleum & Natural Gas Industry Systems, is changing the operational landscape throughout the oil and gas industry. This document focuses on an innovation that will help pipeline operators meet the new recommendations for monitoring and managing their remote assets as outlined in the new CSA standard. This paper includes an analysis of the current monitoring architecture that can be used for compliance with the new regulation as well as a detailed comparison of different architectures. New video surveillance architecture developments are also reviewed. The IntelliView technology uses software that turns passive cameras into video sensors capable of reporting video-based behavior exceptions based on user-defined rules. A hardware device known as a SmrtDVR sits on site and records the video in the highest quality (H.264) to ensure the images are clear for review and investigation. It acts like the brains of the system, able to think if the images it is seeing on the cameras are ones that it has been programmed to alert the pipeline operator about. Alerts can include: trip wire, loitering, object taken/left behind and man down. When an alarm is triggered, a real-time event notification is sent in an (optional) JPEG format to smart phones, monitoring stations and/or third party monitoring companies. These in-situ devices require minimal communication, power and IT infrastructure and notify operators with video driven alerts. A performance evaluation of the proposed system is presented that illustrates how IntelliView’s unique architecture is outperforming the current industrial practice.Copyright

Experimental Investigation of Diesel Engine Performance and Emission Characteristics Fuelled by Jojoba/Diesel Blend and Sunflower Oil

Experimental study has been carried out to investigate performance parameters, emissions, cylinder pressure, exhaust and wall temperatures at different engine speeds and different percentage of EGR using sunflower and jojoba/diesel (B20) blend in comparison to diesel fuel. Sunflower oil and B20 were selected for the study because of its being widely used in Egypt and world. Tests were conducted for three different fuels with different engine speeds. Also, series of tests were conducted at same previous conditions with different percentage of exhaust gas recirculation (EGR) rates from 0 to 12% of inlet mass of air fresh charge. Results indicate that sunflower or B20 blend gives lower brake thermal efficiency, brake power, brake mean effective pressure, and higher BSFC due to lower heating value compared to diesel fuel. Sunflower or B20 blend gives lower NOX concentration due to lower gases temperature. Sunflower or B20 blend gives higher wall/exhaust temperatures due to incomplete combustion inside engine cylinder. Sunflower or B20 blend gives higher CO and CO2 concentrations due to higher carbon/hydrogen ratio. The position of maximum pressure change for diesel fuel is earlier than for sunflower and B20 blend. The results show that sunflower and B20 blend are promising as alternatives fuel for diesel engine. One of the main advantages of vegetable oil is not requiring significant modification of existing engine hard wares. On contrast, the main disadvantages of biodiesel fuels are high viscosity, drying with time, thickening in cold conditions, flow and atomization characteristics.Copyright