Search results for: energy detection

Authors: Nam-Uk Kim, Sung-Hwan Kim, Tai-Myoung Chung

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Typical security management systems are not suitable for detecting APT attack, because they cannot draw the big picture from trivial events of security solutions. Although SIEM solutions have security analysis engine for that, their security analysis mechanisms need to be verified in academic field. Although this paper proposes merely an architectural model for APT detection, we will keep studying on correlation analysis mechanism in the future.

Keywords: advanced persistent threat, anomaly detection, data mining

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Authors: Yeongyu Choi, Ju H. Park, Ho-Youl Jung

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In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments.

Keywords: Canny edge detection, k-means algorithm, RANSAC, inverse perspective mapping

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Authors: A. Beril Tugrul

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Demand on production and thereby the global need of energy is growing continuously. Each country has different trends on energy demand and supply according to their geopolitical and geographical locations, underground reserves, weather conditions and level of industrialization. Conventional energy resources such as oil, gas and coal –in other words fossil resources- remain dominant on primary energy supply in spite of causing of environmental problems. Energy supply and demand securities are essential within the energy importing and exporting countries. This concept affected all sectors, but especially impressed on political aspects of the countries and also global economic views.

Keywords: energy policy, energy economics, energy strategy, global trends, petro-dollar recycling

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Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

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Authors: Kun Xu, Yuan Xu, Jia Qiao

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The document detection plays an important role in optical character recognition and text analysis. Because the traditional detection methods have weak generalization ability, and deep neural network has complex structure and large number of parameters, which cannot be well applied in mobile devices, this paper proposes a lightweight Document Corner Detection Network (DCDNet). DCDNet is a two-stage architecture. The first stage with Encoder-Decoder structure adopts depthwise separable convolution to greatly reduce the network parameters. After introducing the Feature Attention Union (FAU) module, the second stage enhances the feature information of spatial and channel dim and adaptively adjusts the size of receptive field to enhance the feature expression ability of the model. Aiming at solving the problem of the large difference in the number of pixel distribution between corner and non-corner, Weighted Binary Cross Entropy Loss (WBCE Loss) is proposed to define corner detection problem as a classification problem to make the training process more efficient. In order to make up for the lack of Dataset of document corner detection, a Dataset containing 6620 images named Document Corner Detection Dataset (DCDD) is made. Experimental results show that the proposed method can obtain fast, stable and accurate detection results on DCDD.

Keywords: document detection, corner detection, attention mechanism, lightweight

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Authors: Jiandong Lv, Xingang Wang, Cuiling Shao

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The rapid development of social media platforms has made it one of the important news sources. While it provides people with convenient real-time communication channels, fake news and rumors are also spread rapidly through social media platforms, misleading the public and even causing bad social impact in view of the slow speed and poor consistency of artificial rumor detection. We propose an end-to-end rumor detection model-TIMF, which captures the dependencies between multimodal data based on the interactive attention mechanism, uses a transformer for cross-modal feature sequence mapping and combines hybrid fusion strategies to obtain decision results. This paper verifies two multi-modal rumor detection datasets and proves the superior performance and early detection performance of the proposed model.

Keywords: hybrid fusion, multimodal fusion, rumor detection, social media, transformer

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Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Ebrahim Farahmand, Ali Mahani

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Wireless sensor networks (WSNs) can facilitate continuous monitoring of patients and increase early detection of emergency conditions and diseases. High density WSNs helps us to accurately monitor a remote environment by intelligently combining the data from the individual nodes. Due to energy capacity limitation of sensors, enhancing the lifetime and the reliability of WSNs are important factors in designing of these networks. The clustering strategies are verified as effective and practical algorithms for reducing energy consumption in WSNs and can tackle WSNs limitations. In this paper, an Energy-efficient weight-based Clustering Protocol (EWCP) is presented. Artificial retina is selected as a case study of WSNs applied in body sensors. Cluster heads’ (CHs) selection is equipped with energy efficient parameters. Moreover, cluster members are selected based on their distance to the selected CHs. Comparing with the other benchmark protocols, the lifetime of EWCP is improved significantly.

Keywords: WSN, healthcare monitoring, weighted based clustering, lifetime

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Authors: Maher un Nisa, Ahsan Khawaja

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Retinal imaging with Ultra-WideField (UWF) view technology has opened up new avenues in the field of retinal pathology detection. Recent developments in retinal imaging such as Optos California Imaging Device helps in acquiring high resolution images of the retina to help the Ophthalmologists in diagnosing and analyzing eye related pathologies more accurately. This paper investigates the acquired retinal details by comparing vessel detection in standard 450 color fundus images with the state of the art 2000 UWF retinal images.

Keywords: color fundus, retinal images, ultra-widefield, vessel detection

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Authors: Endang Jati Mat Sahid, Hussain Ali Bekhet

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Robust economic growth, increasing population, and personal consumption are the main drivers for the rapid increase of energy demand in Malaysia. Increasing demand has compounded the issue of national energy security due to over-dependence on fossil fuel, depleting indigenous domestic conventional energy resources which in turns has increased the country’s energy import dependence. In order to improve its energy security, Malaysia has seriously embarked on a renewable energy journey. Many initiatives on renewable energy have been introduced in the past decade. These strategies have resulted in the exploding growth of renewable energy deployment in Malaysia. Therefore, this study investigated the impact of renewable energy deployment on energy security. Secondary data was used to calculate the energy security indicators. The study also compared the results of applying different energy security indicators namely availability, applicability, affordability and acceptability dimension of energy resources. The evaluation shows that Malaysia will experience slight improvement in availability and acceptability dimension of energy security. This study suggests that energy security level could be further enhanced by efficient utilization of energy, reducing carbon content of energy and facilitating low-carbon industries.

Keywords: energy policy, energy security, Malaysia, renewable energy

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Authors: Waleed K. Saib, Abdulsalam M. Alhawsawi, Essam Banoqitah

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The idea of this research is to design a radiation spectrometer using LSO scintillation detector coupled to a C series of SiPM (silicon photomultiplier). The device can be used to detects gamma and X-ray radiation. This device is also designed to estimates the activity of the source contamination. The SiPM will detect light in the visible range above the threshold and read them as counts. Three gamma sources were used for these experiments Cs-137, Am-241 and Co-60 with various activities. These sources are applied for four experiments operating the SiPM as a spectrometer, energy resolution, pile-up set and efficiency. The SiPM is connected to a MCA to perform as a spectrometer. Cerium doped Lutetium Silicate (Lu₂SiO₅) with light yield 26000 photons/Mev coupled with the SiPM. As a result, all the main features of the Cs-137, Am-241 and Co-60 are identified in MCA. The experiment shows how photon energy and probability of interaction are inversely related. Total attenuation reduces as photon energy increases. An analytical calculation was made to obtain the FWHM resolution for each gamma source. The FWHM resolution for Am-241 (59 keV) is 28.75 %, for Cs-137 (662 keV) is 7.85 %, for Co-60 (1173 keV) is 4.46 % and for Co-60 (1332 keV) is 3.70%. Moreover, the experiment shows that the dead time and counts number decreased when the pile-up rejection was disabled and the FWHM decreased when the pile-up was enabled. The efficiencies were calculated at four different distances from the detector 2, 4, 8 and 16 cm. The detection efficiency was observed to declined exponentially with increasing distance from the detector face. Conclusively, the SiPM board operated with an LSO scintillator crystal as a spectrometer. The SiPM energy resolution for the three gamma sources used was a decent comparison to other PMTs.

Keywords: PMT, radiation, radiation detection, scintillation detectors, silicon photomultiplier, spectrometer

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Authors: Sergei Aleinik, Yuri Matveev

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In this paper a novel method for the detection of clipping in speech signals is described. It is shown that the new method has better performance than known clipping detection methods, is easy to implement, and is robust to changes in signal amplitude, size of data, etc. Statistical simulation results are presented.

Keywords: clipping, clipped signal, speech signal processing, digital signal processing

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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Authors: Antigoni Panagiotopoulou, Lemonia Ragia

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High-resolution satellite images can provide detailed information about change detection on the earth. In the present work, QuickBird images of spatial resolution 60 cm/pixel and WorldView images of resolution 30 cm/pixel are utilized to perform automatic change detection in urban and suburban areas of Crete, Greece. There is a relative time difference of 13 years among the satellite images. Multiindex scene representation is applied on the images to classify the scene into buildings, vegetation, water and ground. Then, automatic change detection is made possible by pixel-per-pixel comparison of the classified multi-temporal images. The vegetation index and the water index which have been developed in this study prove effective. Furthermore, the proposed change detection approach not only indicates whether changes have taken place or not but also provides specific information relative to the types of changes. Experimentations with other different scenes in the future could help optimize the proposed spectral indices as well as the entire change detection methodology.

Keywords: change detection, multiindex scene representation, spectral index, QuickBird, WorldView

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Authors: Pavel Chmelar, Martin Dobrovolny

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Laser projection or laser footprint detection is today widely used in many fields of robotics, measurement, or electronics. The system accuracy strictly depends on precise laser footprint detection on target objects. This article deals with the laser line detection based on the RGB segmentation and the component labeling. As a measurement device was used the developed optical rangefinder. The optical rangefinder is equipped with vertical sweeping of the laser beam and high quality camera. This system was developed mainly for automatic exploration and mapping of unknown spaces. In the first section is presented a new detection algorithm. In the second section are presented measurements results. The measurements were performed in variable light conditions in interiors. The last part of the article present achieved results and their differences between day and night measurements.

Keywords: color segmentation, component labelling, laser line detection, automatic mapping, distance measurement, vector map

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Authors: Hyojin Lim, Cuong Nguyen Khac, Ho-Youl Jung

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In this paper, we propose moving object detection method which is helpful for driver to safely take his/her car out of parking lot. When moving objects such as motorbikes, pedestrians, the other cars and some obstacles are detected at the rear-side of host vehicle, the proposed algorithm can provide to driver warning. We assume that the host vehicle is just before departure. Gaussian Mixture Model (GMM) based background subtraction is basically applied. Pre-processing such as smoothing and post-processing as morphological filtering are added.We examine “which color space has better performance for detection of moving objects?” Three color spaces including RGB, YCbCr, and Y are applied and compared, in terms of detection rate. Through simulation, we prove that RGB space is more suitable for moving object detection based on background subtraction.

Keywords: gaussian mixture model, background subtraction, moving object detection, color space, morphological filtering

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Authors: Urvee B. Trivedi, U. D. Dalal

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As wireless communication services grow quickly; the seriousness of spectrum utilization has been on the rise gradually. An emerging technology, cognitive radio has come out to solve today’s spectrum scarcity problem. To support the spectrum reuse functionality, secondary users are required to sense the radio frequency environment, and once the primary users are found to be active, the secondary users are required to vacate the channel within a certain amount of time. Therefore, spectrum sensing is of significant importance. Once sensing is done, different prediction rules apply to classify the traffic pattern of primary user. Primary user follows two types of traffic patterns: periodic and stochastic ON-OFF patterns. A cognitive radio can learn the patterns in different channels over time. Two types of classification methods are discussed in this paper, by considering edge detection and by using autocorrelation function. Edge detection method has a high accuracy but it cannot tolerate sensing errors. Autocorrelation-based classification is applicable in the real environment as it can tolerate some amount of sensing errors.

Keywords: cognitive radio (CR), probability of detection (PD), probability of false alarm (PF), primary user (PU), secondary user (SU), fast Fourier transform (FFT), signal to noise ratio (SNR)

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Authors: Xinyi Zhao, Furong Tian

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Mycotoxins are secondary metabolic products of fungi. These are poisonous, carcinogens and mutagens in nature and pose a serious health threat to both humans and animals, causing severe illnesses and even deaths. The rapid, simple and cheap detection methods of mycotoxins are of immense importance and in great demand in the food and beverage industry as well as in agriculture and environmental monitoring. Lateral flow immunochromatographic strips (ICSTs) have been widely used in food safety, environment monitoring. Forty-six papers were identified and reviewed on Google Scholar and Scopus for their limit of detection and nanomaterial on Lateral flow immunochromatographic strips on different types of mycotoxins. The papers were dated 2001-2021. Twenty five papers were compared to identify the lowest limit of detection of among different mycotoxins (Aflatoxin B1: 10, Zearalenone:5, Fumonisin B1: 5, Trichothecene-A: 5). Most of these highly sensitive strips are competitive. Sandwich structure are usually used in large scale detection. In conclusion, the mycotoxin receives that most researches is aflatoxin B1 and its limit of detection is the lowest. Gold-nanopaticle based immunochromatographic test strips has the lowest limit of detection. Five papers involve smartphone detection and they all detect aflatoxin B1 with gold nanoparticles. In these papers, quantitative concentration results can be obtained when the user uploads the photograph of test lines using the smartphone application.

Keywords: aflatoxin B1, limit of detection, gold nanoparticle, lateral flow immunochromatographic strips, mycotoxins

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Authors: Vanessa Funk, Steven Blum, Stephanie Cole, Jorge Maciel, Matthew Lux

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Paper-based synthetic gene circuits offer a new paradigm for programmable, fieldable biodetection. We demonstrate that by freeze-drying gene circuits with in vitro expression machinery, we can use complimentary RNA sequences to trigger colorimetric changes upon rehydration. We have successfully utilized both green fluorescent protein and luciferase-based reporters for easy visualization purposes in solution. Through several efforts, we are aiming to use this new platform technology to address a variety of needs in portable detection by demonstrating several more expression and reporter systems for detection functions on paper. In addition to RNA-based biodetection, we are exploring the use of various mechanisms that cells use to respond to environmental conditions to move towards all-hazards detection. Examples include explosives, heavy metals for water quality, and toxic chemicals.

Keywords: cell-free lysates, detection, gene circuits, in vitro

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Authors: Hojat Heidari-Bafroui, Amer Charbaji, Constantine Anagnostopoulos, Mohammad Faghri

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Phosphorus is an essential nutrient for plant life which is most frequently found as phosphate in water. Once phosphate is found in abundance in surface water, a series of adverse effects on an ecosystem can be initiated. Therefore, a portable and reliable method is needed to monitor the phosphate concentrations in the field. In this paper, an inexpensive dip strip device with the ascorbic acid/antimony reagent dried on blotting paper along with wet chemistry is developed for the detection of low concentrations of phosphate in water. Ammonium molybdate and sulfuric acid are separately stored in liquid form so as to improve significantly the lifetime of the device and enhance the reproducibility of the device’s performance. The limit of detection and quantification for the optimized device are 0.134 ppm and 0.472 ppm for phosphate in water, respectively. The device’s shelf life, storage conditions, and limit of detection are superior to what has been previously reported for the paper-based phosphate detection devices.

Keywords: phosphate detection, paper-based device, molybdenum blue method, colorimetric assay

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Authors: M. M. Wagh, V. V. Kulkarni

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The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

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Authors: Naci Büyükkaracığan, Murat Ahmet Ökmen

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Emerging demand for energy in developing countries rapid population growth and industrialization are causing a rapid increase, such as Turkey. Energy is an important and indispensable factor in the industry. At the same time, energy is one of the main indicators that reflect a country's economic and social development potential. There is a linear relationship between the energy consumption and social development, and in parallel this situation, it is seen that energy consumption increase with economic growth and prosperity. In recent year’s, energy sources consumption is increasingly continuing, because of population growth and economy in Turkey. 80% of the energy used in Turkey is supplied from abroad. At the same time, while almost all of the energy obtained from our country is met by hydropower. Alternatively, studies of determining and using potential renewable energy sources such as solar energy have been realized for recent years. In this study, first of all, the situation of energy sources was examined in Turkey. Information of reserve/capacity, production and consumption values of energy sources were emphasized. For this purpose, energy production and consumption, CO2 emission and electricity energy consumption of countries were investigated. Energy consumption and electricity energy consumption per capita were comparatively analyzed.

Keywords: energy potential, alternative energy sources, solar energy, Turkey

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Authors: Mohammad Reza Ebrahimi

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In new restructured power systems, swift fault detection is very important. The parallel transmission-lines are vastly used in this kind of power systems because of high amount of energy transferring. In this paper, a method based on the comparison of two schemes, i.e., i) maximum magnitude of travelling-wave (TW) energy ii) the instants of maximum energy occurrence at the circuits of parallel transmission-line is proposed. Using the travelling-wave of fault in order to faulted line identification this method has noticeable operation time. Moreover, the algorithm can cover for identification of faults as external or internal faults. For an internal fault, the exact location of the fault can be estimated confidently. A lot of simulations have been done with PSCAD/EMTDC to verify the performance of the proposed algorithm.

Keywords: travelling-wave, maximum energy, parallel transmission-line, fault location

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Authors: Andrey V. Timofeev

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An adaptive nonparametric method is proposed for stable real-time detection of seismoacoustic sources in multichannel C-OTDR systems with a significant number of channels. This method guarantees given upper boundaries for probabilities of Type I and Type II errors. Properties of the proposed method are rigorously proved. The results of practical applications of the proposed method in a real C-OTDR-system are presented in this report.

Keywords: guaranteed detection, multichannel monitoring systems, change point, interval estimation, adaptive detection

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Authors: Rana I. Abdulghani, Amera I. Melhum

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With the abnormal growth of the usage of computers over networks and under the consideration or agreement of most of the computer security experts who said that the goal of building a secure system is never achieved effectively, all these points led to the design of the intrusion detection systems(IDS). This research adopts a comparison between two techniques for network intrusion detection, The first one used the (Particles Swarm Optimization) that fall within the field (Swarm Intelligence). In this Act, the algorithm Enhanced for the purpose of obtaining the minimum error rate by amending the cluster centers when better fitness function is found through the training stages. Results show that this modification gives more efficient exploration of the original algorithm. The second algorithm used a (Back propagation NN) algorithm. Finally a comparison between the results of two methods used were based on (NSL_KDD) data sets for the construction and evaluation of intrusion detection systems. This research is only interested in clustering the two categories (Normal and Abnormal) for the given connection records. Practices experiments result in intrude detection rate (99.183818%) for EPSO and intrude detection rate (69.446416%) for BP neural network.

Keywords: IDS, SI, BP, NSL_KDD, PSO

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Authors: Narong Kulnides

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This research involved fingerprints on ballistics after shooting. Two objectives of research were as follows; (1) to study the duration of the existence of latent fingerprints on .38, .45, 9 mm and .223 cartridge case after shooting, and (2) to compare the effectiveness of the detection of latent fingerprints by Black Powder, Super Glue, Perma Blue and Gun Bluing. The latent fingerprint appearance were studied on .38, .45, 9 mm. and .223 cartridge cases before and after shooting with Black Powder, Super Glue, Perma Blue and Gun Bluing. The detection times were 3 minute, 6, 12, 18, 24, 30, 36, 42, 48, 54, 60, 66, 72, 78 and 84 hours respectively. As a result of the study, it can be conclude that: (1) Before shooting, the detection of latent fingerprints on 38, .45, and 9 mm. and .223 cartridge cases with Black Powder, Super Glue, Perma Blue and Gun Bluing can detect the fingerprints at all detection times. (2) After shooting, the detection of latent fingerprints on .38, .45, 9 mm. and .223 cartridge cases with Black Powder, Super Glue did not appear. The detection of latent fingerprints on .38, .45, 9 mm. cartridge cases with Perma Blue and Gun Bluing were found 100% of the time and the detection of latent fingerprints on .223 cartridge cases with Perma Blue and Gun Bluing were found 40% and 46.67% of the time, respectively.

Keywords: ballistic, fingerprint, shooting, detection times

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Authors: Marinko Skare, Malgorzata Porada Rochon

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This paper study the link between energy justice and economic growth. The link between energy justice and growth has not been extensively studied. Here we study the impact and importance of energy justice, as a part of the energy transition process, on economic growth. Our study shows energy justice growth is an important determinant of economic growth and development that should be addressed at the industry and economic levels. We use panel data modeling and causality testing to research the empirical link between energy justice and economic growth. Industry and economy-level policies designed to support energy justice initiatives are beneficial to economic growth. Energy justice is a necessary condition for green growth and sustainability targets.

Keywords: energy justice, economic growth, panel data, energy transition

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Authors: Moein Izadi, Ali Mohammadzadeh

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Detection of damaged parts of roads after earthquake is essential for coordinating rescuers. In this study, an approach is presented for the semi-automatic detection of damaged roads in a city using pre-event vector maps and both pre- and post-earthquake QuickBird satellite images. Damage is defined in this study as the debris of damaged buildings adjacent to the roads. Some spectral and texture features are considered for SVM classification step to detect damages. Finally, the proposed method is tested on QuickBird pan-sharpened images from the Bam City earthquake and the results show that an overall accuracy of 81% and a kappa coefficient of 0.71 are achieved for the damage detection. The obtained results indicate the efficiency and accuracy of the proposed approach.

Keywords: SVM classifier, disaster management, road damage detection, quickBird images

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Authors: Sarah A. Goodchild, Rachel Gao, Philip N. Bartlett

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A novel detection approach using immobilized DNA probes labeled with Anthraquinone (AQ) as an electrochemically active reporter moiety has been successfully developed as a new, simple, reliable method for the detection of DNA. This method represents a step forward in DNA detection as it can discriminate between multiple nucleotide polymorphisms within target DNA strands without the need for any additional reagents, reporters or processes such as melting of DNA strands. The detection approach utilizes single-stranded DNA probes immobilized on gold surfaces labeled at the distal terminus with AQ. The effective immobilization has been monitored using techniques such as AC impedance and Raman spectroscopy. Simple voltammetry techniques (Differential Pulse Voltammetry, Cyclic Voltammetry) are then used to monitor the reduction potential of the AQ before and after the addition of complementary strand of target DNA. A reliable relationship between the shift in reduction potential and the number of base pair mismatch has been established and can be used to discriminate between DNA from highly related pathogenic organisms of clinical importance. This indicates that this approach may have great potential to be exploited within biosensor kits for detection and diagnosis of pathogenic organisms in Point of Care devices.

Keywords: Anthraquinone, discrimination, DNA detection, electrochemical biosensor

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Authors: L. Sellami, D. Idoughi, P. F. Tiako

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Cloud computing provides infrastructure to the enterprise through the Internet allowing access to cloud services at anytime and anywhere. This pervasive aspect of the services, the distributed nature of data and the wide use of information make cloud computing vulnerable to intrusions that violate the security of the cloud. This requires the use of security mechanisms to detect malicious behavior in network communications and hosts such as intrusion detection systems (IDS). In this article, we focus on the detection of intrusion into the cloud sing IDSs. We base ourselves on client authentication in the computing cloud. This technique allows to detect the abnormal use of ubiquitous service and prevents the intrusion of cloud computing. This is an approach based on client authentication data. Our IDS provides intrusion detection inside and outside cloud computing network. It is a double protection approach: The security user node and the global security cloud computing.

Keywords: cloud computing, intrusion detection system, privacy, trust

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