Search results for: dynamic ROI detection

Authors: Mehdi Moradi Sarmeidani, Peyman Keyhani, Hasan Momtaz

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Chlamydophila psittaci is a avian pathogen that may cause respiratory disorders in humans. Conjunctival and cloacal swabs from 54 captive psittacine birds presented at veterinary clinics were collected to determine the prevalence of C. psittaci in domestic birds in Isfahan. Samples were collected during 2014 from a total of 10 different species of parrots, with African gray(33), Cockatiel lutino(3), Cockatiel gray(2), Cockatiel cinnamon(1), Pearl cockatiel(6), Timneh African grey(1), Ringneck parakeet(2), Melopsittacus undulatus(1), Alexander parakeet(2), Green Parakeet(3) being the most representative species sampled. C. psittaci was detected in 27 (50%) birds using molecular detection (PCR) method. The detection of this bacterium in captive psittacine birds shows that there is a potential risk for human whom has a direct contact and there is a possibility of infecting other birds.

Keywords: chlamydophila psittaci, psittacine birds, PCR, Isfahan

Procedia PDF Downloads 348

Authors: Mohamed Gaith, Zaid Haddadin, Abdulah Wahbe, Mahmoud Hamam, Mahmoud Qunees, Mohammad Al Khatib, Mohammad Bsaileh, Abd Al-Aziz Jaber, Ahmad Aqra’a

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The crack is one of the most common types of failure in pipelines that convey fluid, and early detection of the crack may assist to avoid the piping system from experiencing catastrophic damage, which would otherwise be fatal. The influence of flow velocity and the presence of a crack on the performance of a tapered simply supported pipe containing moving fluid is explored using the finite element approach in this study. ANSYS software is used to simulate the pipe as Bernoulli's beam theory. In this paper, the fluctuation of natural frequencies and matching mode shapes for various scenarios owing to changes in fluid speed and the presence of damage is discussed in detail.

Keywords: damage detection, finite element, tapered pipe, vibration characteristics

Procedia PDF Downloads 146

Authors: M. Kastek, M. Kowalski, M. Szustakowski, H. Polakowski, T. Sosnowski

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Development of highly efficient security systems is one of the most urgent topics for science and engineering. There are many kinds of threats and many methods of prevention. It is very important to detect a threat as early as possible in order to neutralize it. One of the very challenging problems is detection of dangerous objects hidden under human’s clothing. This problem is particularly important for safety of airport passengers. In order to develop methods and algorithms to detect hidden objects it is necessary to determine the thermal signatures of such objects of interest. The laboratory measurements were conducted to determine the thermal signatures of dangerous tools hidden under various clothes in different ambient conditions. Cameras used for measurements were working in spectral range 0.6-12.5 μm An infrared imaging Fourier transform spectroradiometer was also used, working in spectral range 7.7-11.7 μm. Analysis of registered thermograms and hyperspectral datacubes has yielded the thermal signatures for two types of guns, two types of knives and home-made explosive bombs. The determined thermal signatures will be used in the development of method and algorithms of image analysis implemented in proposed monitoring systems.

Keywords: hyperspectral detection, nultispectral detection, image processing, monitoring systems

Procedia PDF Downloads 336

Authors: Noha Seddik, Sherine Youssef, Mohamed Kholeif

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The automated epileptic seizure detection research field has emerged in the recent years; this involves analyzing the Electroencephalogram (EEG) signals instead of the traditional visual inspection performed by expert neurologists. In this study, a Support Vector Machine (SVM) that uses Weighted Permutation Entropy (WPE) as the input feature is proposed for classifying normal and seizure EEG records. WPE is a modified statistical parameter of the permutation entropy (PE) that measures the complexity and irregularity of a time series. It incorporates both the mapped ordinal pattern of the time series and the information contained in the amplitude of its sample points. The proposed system utilizes the fact that entropy based measures for the EEG segments during epileptic seizure are lower than in normal EEG.

Keywords: electroencephalogram (EEG), epileptic seizure detection, weighted permutation entropy (WPE), support vector machine (SVM)

Procedia PDF Downloads 351

Authors: Evgeniia V. Mekhonoshina, Vladimir Ya. Modorskii, Vasilii Yu. Petrov

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At present, vibrations of rotors of gas transmittal unit evade sustainable forecasting. This paper describes elastic oscillation modes in resilient supports and rotor impellers modeled during computational experiments with regard to interference in the system of gas-dynamic flow and compressor rotor. Verification of aeroelastic approach was done on model problem of interaction between supersonic jet in shock tube with deformed plate. ANSYS 15.0 engineering analysis system was used as a modeling tool of numerical simulation in this paper. Finite volume method for gas dynamics and finite elements method for assessment of the strain stress state (SSS) components were used as research methods. Rotation speed and material’s elasticity modulus varied during calculations, and SSS components and gas-dynamic parameters in the dynamic system of gas-dynamic flow and compressor rotor were evaluated. The analysis of time dependence demonstrated that gas-dynamic parameters near the rotor blades oscillate at 200 Hz, and SSS parameters at the upper blade edge oscillate four times higher, i.e. with blade frequency. It has been detected that vibration amplitudes correction in the test points at magnetic bearings by aeroelasticity may correspond up to 50%, and about -π/4 for phases.

Keywords: Centrifugal compressor, aeroelasticity, interdisciplinary calculation, oscillation phase displacement, vibration, nonstationarity

Procedia PDF Downloads 246

Authors: Yanchun Zuo, Yingao Liu, Wei Liu, Le Yu, Run Huang, Lixin Guo

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Electric field detection is important in many application scenarios. The traditional strategy is measuring the electric field with a man walking around in the area under test. This strategy cannot provide a satisfactory measurement accuracy. To solve the mentioned problem, an autopilot measurement system is divided. A mini-car is produced, which can travel in the area under test according to respect to the program within the CPU. The electric field measurement platform (EFMP) carries a central computer, two horn antennas, and a vector network analyzer. The mini-car stop at the sampling points according to the preset. When the car stops, the EFMP probes the electric field and stores data on the hard disk. After all the sampling points are traversed, an electric field map can be plotted. The proposed system can give an accurate field distribution description of the chamber.

Keywords: autopilot mini-car measurement system, electric field detection, field map, static zone measurement

Procedia PDF Downloads 86

Authors: Faiza Belbachir, Thibault Schienhinski

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The massive development of online social networks allows users to post and share their opinions on various topics. With this huge volume of opinion, it is interesting to extract and interpret these information for different domains, e.g., product and service benchmarking, politic, system of recommendation. This is why opinion detection is one of the most important research tasks. It consists on differentiating between opinion data and factual data. The difficulty of this task is to determine an approach which returns opinionated document. Generally, there are two approaches used for opinion detection i.e. Lexical based approaches and Machine Learning based approaches. In Lexical based approaches, a dictionary of sentimental words is used, words are associated with weights. The opinion score of document is derived by the occurrence of words from this dictionary. In Machine learning approaches, usually a classifier is trained using a set of annotated document containing sentiment, and features such as n-grams of words, part-of-speech tags, and logical forms. Majority of these works are based on documents text to determine opinion score but dont take into account if these texts are really correct. Thus, it is interesting to exploit other information to improve opinion detection. In our work, we will develop a new way to consider the opinion score. We introduce the notion of trust score. We determine opinionated documents but also if these opinions are really trustable information in relation with topics. For that we use lexical SentiWordNet to calculate opinion and trust scores, we compute different features about users like (numbers of their comments, numbers of their useful comments, Average useful review). After that, we combine opinion score and trust score to obtain a final score. We applied our method to detect trust opinions in TRIPADVISOR collection. Our experimental results report that the combination between opinion score and trust score improves opinion detection.

Keywords: Tripadvisor, opinion detection, SentiWordNet, trust score

Procedia PDF Downloads 181

Authors: Mohammad Reza Ameri, Ali Massumi, Mohammad Haghbin

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Non-linear static analysis, commonly referred to as pushover analysis, is a powerful tool for assessing the seismic response of structures. A suitable lateral load pattern for pushover analysis can bring the results of this simple, quick and low-cost analysis close to the realistic results of nonlinear dynamic analyses. In this research, four samples of 10- and 15 story (two- and four-bay) reinforced concrete frames were studied. The lateral load distribution patterns recommended in FEMA 273/356 guidelines were applied to the sample models in order to perform pushover analyses. The results were then compared to the results obtained from several nonlinear incremental dynamic analyses for a range of earthquakes. Finally, a lateral load distribution pattern was proposed for pushover analysis of medium-rise reinforced concrete buildings based on the results of nonlinear static and dynamic analyses.

Keywords: lateral load pattern, nonlinear static analysis, incremental dynamic analysis, medium-rise reinforced concrete frames, performance based design

Procedia PDF Downloads 457

Authors: Ajish Sreedharan

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Security in transmission and storage of digital images has its importance in today’s image communications and confidential video conferencing. Due to the increasing use of images in industrial process, it is essential to protect the confidential image data from unauthorized access. Advanced Encryption Standard (AES) is a well known block cipher that has several advantages in data encryption. However, it is not suitable for real-time applications. This paper presents modifications to the Advanced Encryption Standard to reflect a high level security and better image encryption. The modifications are done by adjusting the ShiftRow Transformation and using On Dynamic chaotic S-BOX. In AES the Substitute bytes, Shift row and Mix columns by themselves would provide no security because they do not use the key. In Dynamic chaotic S-BOX Based AES the Substitute bytes provide security because the S-Box is constructed from the key. Experimental results verify and prove that the proposed modification to image cryptosystem is highly secure from the cryptographic viewpoint. The results also prove that with a comparison to original AES encryption algorithm the modified algorithm gives better encryption results in terms of security against statistical attacks.

Keywords: advanced encryption standard (AES), on dynamic chaotic S-BOX, image encryption, security analysis, ShiftRow transformation

Procedia PDF Downloads 416

Authors: Nurullah Buker, Ezgi Karagoz, Yesim Salik Sengul, Sevay Alsen Guney, Gokhan Yoyler, Aylin Ozbek

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Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurodevelopmental disorders with heterogeneous clinical features such as inattention, hyperactivity, and impulsivity. Many different types of exercise interventions were employed for children with ADHD. However, previous studies have usually examined the effects of non-specific exercise programs or short-term effects of exercise. The aim of this study is to investigate the effect of the Neurocognitive Exercise Program (NEP), which is a structured exercise program derived from Life Kinetik, and a relatively new for children with ADHD, on symptoms, attention, and dynamic balance in medication-naïve children with ADHD. Fourteen medication-naive children (7-12 years) with ADHD were included in the intervention group. NEP was performed once a week for ten weeks. The intervention group also performed a structured home exercise program for another six days, for ten weeks. The children in the intervention group were assessed at baseline, in the third month, in the sixth month, and in the twelfth month regarding ADHD-related symptoms, attention, and dynamic balance. Fifteen age-matched typically developing children were assessed once for establishing normative values. Hyperactivity-Impulsivity score and dynamic balance were found to improve after NEP in the ADHD group in the 3rd month (p<0.05). In addition, these results were similar for both groups after NEP and at the end of the 12th month (p>0.05). The NEP may provide beneficial effects on hyperactivity-impulsivity, oppositional defiant, and dynamic balance in children with ADHD, and the improvements may be maintained in the long term.

Keywords: ADHD, attention problems, dynamic balance, neurocognitive exercise

Procedia PDF Downloads 62

Authors: Radhia Toujani, Jalel Akaichi

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Social Networks generally present a hierarchy of communities. To determine these communities and the relationship between them, detection algorithms should be applied. Most of the existing algorithms, proposed for hierarchical communities identification, are based on either agglomerative clustering or divisive clustering. In this paper, we present a hybrid hierarchical clustering approach for community detection based on both bottom-up and bottom-down clustering. Obviously, our approach provides more relevant community structure than hierarchical method which considers only divisive or agglomerative clustering to identify communities. Moreover, we performed some comparative experiments to enhance the quality of the clustering results and to show the effectiveness of our algorithm.

Keywords: agglomerative hierarchical clustering, community structure, divisive hierarchical clustering, hybrid hierarchical clustering, opinion mining, social network, social network analysis

Procedia PDF Downloads 343

Authors: Jui-Pui Hung, Yu-Sheng Lai, Tzuo-Liang Luo, Kung-Da Wu, Yun-Ji Zhan

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This study presented the investigation of the influence of the tool holder interface stiffness on the dynamic characteristics of a spindle tool system. The interface stiffness was produced by drawbar force on the tool holder, which tends to affect the spindle dynamics. In order to assess the influence of interface stiffness on the vibration characteristic of spindle unit, we first created a three dimensional finite element model of a high speed spindle system integrated with tool holder. The key point for the creation of FEM model is the modeling of the rolling interface within the angular contact bearings and the tool holder interface. The former can be simulated by a introducing a series of spring elements between inner and outer rings. The contact stiffness was calculated according to Hertz contact theory and the preload applied on the bearings. The interface stiffness of the tool holder was identified through the experimental measurement and finite element modal analysis. Current results show that the dynamic stiffness was greatly influenced by the tool holder system. In addition, variations of modal damping, static stiffness and dynamic stiffness of the spindle tool system were greatly determined by the interface stiffness of the tool holder which was in turn dependent on the draw bar force applied on the tool holder. Overall, this study demonstrates that identification of the interface characteristics of spindle tool holder is of very importance for the refinement of the spindle tooling system to achieve the optimum machining performance.

Keywords: dynamic stiffness, spindle-tool holder, interface stiffness, drawbar force

Procedia PDF Downloads 375

Authors: Fabrizio Iezzi, Claudio Valente

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The viscous damping in dynamic systems can be proportional or non-proportional. In the first case, the mode shapes are real whereas in the second case they are complex. From an engineering point of view, the complexity of the mode shapes is important in order to quantify the non-proportional damping. Different indices exist to provide estimates of the modal complexity. These indices are or not zero, depending whether the mode shapes are not or are complex. The modal density problem arises in the experimental identification when the dynamic systems have close modal frequencies. Depending on the entity of this closeness, the mode shapes can hold fictitious imaginary quantities that affect the values of the modal complexity indices. The results are the failing in the identification of the real or complex mode shapes and then of the proportional or non-proportional damping. The paper aims to show the influence of the modal density on the values of these indices in case of both proportional and non-proportional damping. Theoretical and pseudo-experimental solutions are compared to analyze the problem according to an appropriate mechanical system.

Keywords: complex mode shapes, dynamic systems identification, modal density, non-proportional damping

Procedia PDF Downloads 370

Authors: Yanxue Shang, Jingbin Zeng

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Chlorobenzene homologues (CBHs) are a category of environmental pollutants that can not be ignored. They can stay in the environment for a long period and are potentially carcinogenic. The traditional degradation method of CBHs is dechlorination followed by sample preparation and analysis. This is not only time-consuming and laborious, but the detection and analysis processes are used in conjunction with large-scale instruments. Therefore, this can not achieve rapid and low-cost detection. Compared with traditional sensing methods, colorimetric sensing is simpler and more convenient. In recent years, chromaticity sensors based on fluorescence have attracted more and more attention. Compared with sensing methods based on changes in fluorescence intensity, changes in color gradients are easier to recognize by the naked eye. Accordingly, this work proposes to use single drop microextraction (SDME) technology to solve the above problems. After the dechlorination reaction was completed, the organic droplet extracts Cl⁻ and realizes fluorescence colorimetric sensing at the same time. This method was integrated sample processing and visual in-situ detection, simplifying the detection process. As a fluorescence colorimetric sensor material, CsPbBr₃ was encapsulated in MOF-5 to construct CsPbBr₃@MOF-5 fluorescence colorimetric composite. Then the fluorescence colorimetric sensor was constructed by dispersing the composite in SDME organic droplets. When the Br⁻ in CsPbBr₃ exchanges with Cl⁻ produced by the dechlorination reactions, it is converted into CsPbCl₃. The fluorescence color of the single droplet of SDME will change from green to blue emission, thereby realizing visual observation. Therein, SDME can enhance the concentration and enrichment of Cl⁻ and instead of sample pretreatment. The fluorescence color change of CsPbBr₃@MOF-5 can replace the detection process of large-scale instruments to achieve real-time rapid detection. Due to the absorption ability of MOF-5, it can not only improve the stability of CsPbBr₃, but induce the adsorption of Cl⁻. Simultaneously, accelerate the exchange of Br- and Cl⁻ in CsPbBr₃ and the detection process of Cl⁻. The absorption process was verified by density functional theory (DFT) calculations. This method exhibits exceptional linearity for Cl⁻ in the range of 10⁻² - 10⁻⁶ M (10000 μM - 1 μM) with a limit of detection of 10⁻⁷ M. Whereafter, the dechlorination reactions of different kinds of CBHs were also carried out with this method, and all had satisfactory detection ability. Also verified the accuracy by gas chromatography (GC), and it was found that the SDME we developed in this work had high credibility. In summary, the in-situ visualization method of dechlorination reaction detection was a combination of sample processing and fluorescence colorimetric sensing. Thus, the strategy researched herein represents a promising method for the visual detection of dechlorination reactions and can be extended for applications in environments, chemical industries, and foods.

Keywords: chlorobenzene homologues, colorimetric sensor, metal halide perovskite, metal-organic frameworks, single drop microextraction

Procedia PDF Downloads 130

Authors: Suveen Kumar

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Oral cancer (OC) is the sixth most death causing cancer in world which includes tumour of lips, floor of the mouth, tongue, palate, cheeks, sinuses, throat, etc. Conventionally, the techniques used for OC detection are toluidine blue staining, biopsy, liquid-based cytology, visual attachments, etc., however these are limited by their highly invasive nature, low sensitivity, time consumption, sophisticated instrument handling, sample processing and high cost. Therefore, we developed biosensing chips for non-invasive detection of OC via CYFRA-21-1 biomarker. CYFRA-21-1 (molecular weight: 40 kDa) is secreted in saliva of OC patients which is a non-invasive biological fluid with a cut-off value of 3.8 ng mL-1, above which the subjects will be suffering from oral cancer. Therefore, in first work, 3-aminopropyl triethoxy silane (APTES) functionalized zirconia (ZrO2) nanoparticles (APTES/nZrO2) were used to successfully detect CYFRA-21-1 in a linear detection range (LDR) of 2-16 ng mL-1 with sensitivity of 2.2 µA mL ng-1. Successively, APTES/nZrO2-RGO was employed to prevent agglomeration of ZrO2 by providing high surface area reduced graphene oxide (RGO) support and much wider LDR (2-22 ng mL-1) was obtained with remarkable limit of detection (LOD) as 0.12 ng mL-1. Further, APTES/nY2O3/ITO platform was used for oral cancer bioseneor development. The developed biosensor (BSA/anti-CYFRA-21-1/APTES/nY2O3/ITO) have wider LDR (0.01-50 ng mL-1) with remarkable limit of detection (LOD) as 0.01 ng mL-1. To improve the sensitivity of the biosensing platform, nanocomposite of yattria stabilized nanostructured zirconia-reduced graphene oxide (nYZR) based biosensor has been developed. The developed biosensing chip having ability to detect CYFRA-21-1 biomolecules in the range of 0.01-50 ng mL-1, LOD of 7.2 pg mL-1 with sensitivity of 200 µA mL ng-1. Further, the applicability of the fabricated biosensing chips were also checked through real sample (saliva) analysis of OC patients and the obtained results showed good correlation with the standard protein detection enzyme linked immunosorbent assay (ELISA) technique.

Keywords: non-invasive, oral cancer, nanomaterials, biosensor, biochip

Procedia PDF Downloads 112

Authors: A. Bogdanovic, M. Vitanova, J. Bojadjieva, Z. Rakicevic, V. Sesov, K. Edip, N. Naumovski, F. Manojlovski, A.Popovska, A. Shoklarovski, T. Kitanovski, D. Ivanovski, I. Markovski, D. Filipovski

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The conditions of existing structures change in the course of time and can hardly be characterized particularly if a bridge has long been in function and there is no design documentation related to it. To define the real conditions of a structure, detailed static and dynamic analysis of the structure has to be carried out and its modal parameters have to be defined accurately. Modal analysis enables a quite accurate identification of the natural frequencies and mode shapes. Presented in this paper are the results from the performed detailed analyses of a steel truss bridge that has been in use for more than 7 decades by the military services of R.N. Macedonia and for which there is no documentation at all. Static and dynamic investigations and ambient vibration measurements were performed. The acquired data were used to identify the mode shapes that were used for comparison with the numerical model. Dynamic tests were performed to define the bridge behaviour and the damping index. Finally, based on all the conducted detailed analyses and investigations, conclusions on the conditions of the bridge structure were drawn.

Keywords: ambient vibrations, dynamic identification, in-situ measurement, steel truss bridge

Procedia PDF Downloads 72

Authors: Evan Lowhorn, Rocio Alba-Flores

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Traditional classification Convolutional Neural Networks (CNN) attempt to classify an image in its entirety. This becomes problematic when trying to perform classification with a drone’s camera in real-time due to unpredictable backgrounds. Object detectors with bounding boxes can be used to isolate individuals and other items, but the original backgrounds remain within these boxes. These basic detectors have been regularly used to determine what type of object an item is, such as “person” or “dog.” Recent advancement in computer vision, particularly with human imaging, is keypoint detection. Human keypoint detection goes beyond bounding boxes to fully isolate humans and plot points, or Regions of Interest (ROI), on their bodies within an image. ROIs can include shoulders, elbows, knees, heads, etc. These points can then be related to each other and used in deep learning methods such as pose estimation. For drone control based on human motions, poses, or signals using the onboard camera, it is important to have a simple method for pilot identification among multiple individuals while also giving the pilot fine control options for the drone. To achieve this, the OpenPose keypoint detection network was used with body and hand keypoint detection enabled. OpenPose supports the ability to combine multiple keypoint detection methods in real-time with a single network. Body keypoint detection allows simple poses to act as the pilot identifier. The hand keypoint detection with ROIs for each finger can then offer a greater variety of signal options for the pilot once identified. For this work, the individual must raise their non-control arm to be identified as the operator and send commands with the hand on their other arm. The drone ignores all other individuals in the onboard camera feed until the current operator lowers their non-control arm. When another individual wish to operate the drone, they simply raise their arm once the current operator relinquishes control, and then they can begin controlling the drone with their other hand. This is all performed mid-flight with no landing or script editing required. When using a desktop with a discrete NVIDIA GPU, the drone’s 2.4 GHz Wi-Fi connection combined with OpenPose restrictions to only body and hand allows this control method to perform as intended while maintaining the responsiveness required for practical use.

Keywords: computer vision, drone control, keypoint detection, openpose

Procedia PDF Downloads 167

Authors: Michael Zimba

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A duplicated image region may be subjected to a number of attacks such as noise addition, compression, reflection, rotation, and scaling with the intention of either merely mating it to its targeted neighborhood or preventing its detection. In this paper, we present an effective and robust method of detecting duplicated regions inclusive of those affected by the various attacks. In order to reduce the dimension of the image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of a suspicious image. However, unlike most existing copy move image forgery (CMIF) detection algorithms operating in the DWT domain which extract only the low frequency sub-band of the DWT of the suspicious image thereby leaving valuable information in the other three sub-bands, the proposed algorithm simultaneously extracts features from all the four sub-bands. The extracted features are not only more accurate representation of image regions but also robust to additive noise, JPEG compression, and affine transformation. Furthermore, principal component analysis-eigenvalue decomposition, PCA-EVD, is applied to reduce the dimension of the features. The extracted features are then sorted using the more computationally efficient Radix Sort algorithm. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. The proposed algorithm is not only fast but also more robust to attacks compared to the related CMIF detection algorithms. The experimental results show high detection rates.

Keywords: affine transformation, discrete wavelet transform, radix sort, SATS

Procedia PDF Downloads 212

Authors: Temesgen Geremew

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This study investigates the evolution of polythiophene nanoparticles (PThNPs) as surface-enhanced Raman spectroscopy (SERS) sensors for Pb²⁺ detection in river water. We analyze the PThNPs' optical, structural, and morphological properties at different stages of their development to understand their SERS performance. Techniques like UV-Vis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) are employed for characterization. The SERS sensitivity towards Pb²⁺ is evaluated by monitoring the peak intensity of a specific Raman band upon increasing metal ion concentration. The study aims to elucidate the relationship between the PThNPs' characteristics and their SERS efficiency for Pb²⁺ detection, paving the way for optimizing their design and fabrication for improved sensing performance in real-world environmental monitoring applications.

Keywords: polythiophene, Pb2+, SERS, nanoparticles

Procedia PDF Downloads 32

Authors: Daliyah S. Aljutaili, Redna A. Almutlaq, Suha A. Alharbi, Dina M. Ibrahim

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All currencies around the world look very different from each other. For instance, the size, color, and pattern of the paper are different. With the development of modern banking services, automatic methods for paper currency recognition become important in many applications like vending machines. One of the currency recognition architecture’s phases is Feature detection and description. There are many algorithms that are used for this phase, but they still have some disadvantages. This paper proposes a feature detection algorithm, which merges the advantages given in the current SIFT and SURF algorithms, which we call, Speeded up Robust Scale-Invariant Feature Transform (SR-SIFT) algorithm. Our proposed SR-SIFT algorithm overcomes the problems of both the SIFT and SURF algorithms. The proposed algorithm aims to speed up the SIFT feature detection algorithm and keep it robust. Simulation results demonstrate that the proposed SR-SIFT algorithm decreases the average response time, especially in small and minimum number of best key points, increases the distribution of the number of best key points on the surface of the currency. Furthermore, the proposed algorithm increases the accuracy of the true best point distribution inside the currency edge than the other two algorithms.

Keywords: currency recognition, feature detection and description, SIFT algorithm, SURF algorithm, speeded up and robust features

Procedia PDF Downloads 218

Authors: Praveen S. Muthukumarana, Achala C. Aponso

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A large percentage of global crop harvest is lost due to crop diseases. Timely identification and treatment of crop diseases is difficult in many developing nations due to insufficient trained professionals in the field of agriculture. Many crop diseases can be accurately diagnosed by visual symptoms. In the past decade, deep learning has been successfully utilized in domains such as healthcare but adoption in agriculture for plant disease detection is rare. The literature shows that models trained with popular datasets such as PlantVillage does not generalize well on real world images. This paper attempts to find out how to make plant disease identification models that generalize well with real world images.

Keywords: agriculture, convolutional neural network, deep learning, plant disease classification, plant disease detection, plant disease diagnosis

Procedia PDF Downloads 126

Authors: Rafael Marinho de Andrade, Elcio Hideti Shiguemori, Rafael Duarte Coelho dos Santos

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Relying on computer vision, many clever things are possible in order to make the world safer and optimized on resource management, especially considering time and attention as manageable resources, once the modern world is very abundant in cameras from inside our pockets to above our heads while crossing the streets. Thus, automated solutions based on computer vision techniques to detect, react, or even prevent relevant events such as robbery, car crashes and traffic jams can be accomplished and implemented for the sake of both logistical and surveillance improvements. In this paper, we present an approach for vehicles’ abnormal behaviors detection from highway footages, in which the vectorial data of the vehicles’ displacement are extracted directly from surveillance cameras footage through object detection and tracking with a deep convolutional neural network and inserted into a long-short term memory neural network for behavior classification. The results show that the classifications of behaviors are consistent and the same principles may be applied to other trackable objects and scenarios as well.

Keywords: artificial intelligence, behavior detection, computer vision, convolutional neural networks, LSTM, highway footage

Procedia PDF Downloads 143

Authors: Jianuo Sun, Jinghan Wang, Sirui Zhang, Chenhan Xu, Hongxia Hao, Hong Zhou

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In recent years, the diversification and industrialization of drug-related crimes have posed significant threats to public health and safety globally. The widespread and increasingly younger demographics of drug users and the persistence of drug-impaired driving incidents underscore the urgency of this issue. Drug detection, a specialized forensic activity, is pivotal in identifying and analyzing substances involved in drug crimes. It relies on pharmacological and chemical knowledge and employs analytical chemistry and modern detection techniques. However, current drug detection methods are limited by their inability to perform semi-quantitative, real-time field analyses. They require extensive, complex laboratory-based preprocessing, expensive equipment, and specialized personnel and are hindered by long processing times. This study introduces an alternative approach using nucleic acid aptamers and Aggregation-Induced Emission (AIE) technology. Nucleic acid aptamers, selected artificially for their specific binding to target molecules and stable spatial structures, represent a new generation of biosensors following antibodies. Rapid advancements in AIE technology, particularly in tetraphenyl ethene-based luminous, offer simplicity in synthesis and versatility in modifications, making them ideal for fluorescence analysis. This work successfully synthesized, isolated, and purified an AIE molecule and constructed a probe comprising the AIE molecule, nucleic acid aptamers, and exonuclease for cocaine detection. The probe demonstrated significant relative fluorescence intensity changes and selectivity towards cocaine over other drugs. Using 4-Butoxytriethylammonium Bromide Tetraphenylethene (TPE-TTA) as the fluorescent probe, the aptamer as the recognition unit, and Exo I as an auxiliary, the system achieved rapid detection of cocaine within 5 mins in aqueous and urine, with detection limits of 1.0 and 5.0 µmol/L respectively. The probe-maintained stability and interference resistance in urine, enabling quantitative cocaine detection within a certain concentration range. This fluorescent sensor significantly reduces sample preprocessing time, offers a basis for rapid onsite cocaine detection, and promises potential for miniaturized testing setups.

Keywords: drug detection, aggregation-induced emission (AIE), nucleic acid aptamer, exonuclease, cocaine

Procedia PDF Downloads 46

Authors: Osama Mohamed Elrajubi, Idris El-Feghi, Mohamed Abu Baker Saghayer

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This paper describes an identification of specific shapes within binary images using the morphological Hit-or-Miss Transform (HMT). Hit-or-Miss transform is a general binary morphological operation that can be used in searching of particular patterns of foreground and background pixels in an image. It is actually a basic operation of binary morphology since almost all other binary morphological operators are derived from it. The input of this method is a binary image and a structuring element (a template which will be searched in a binary image) while the output is another binary image. In this paper a modification of Hit-or-Miss transform has been proposed. The accuracy of algorithm is adjusted according to the similarity of the template and the sought template. The implementation of this method has been done by C language. The algorithm has been tested on several images and the results have shown that this new method can be used for similar shape detection.

Keywords: hit-or-miss operator transform, HMT, binary morphological operation, shape detection, binary images processing

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Authors: Nimet Yildirim Tirgil, Ahmed Busnaina, April Z. Gu

Abstract:

Environmental waters are monitored worldwide to protect people from infectious diseases primarily caused by enteric pathogens. All long, Escherichia coli (E. coli) is a good indicator for potential enteric pathogens in waters. Thus, a rapid and simple detection method for E. coli is very important to predict the pathogen contamination. In this study, to the best of our knowledge, as the first time we developed a rapid, direct and reusable SWCNTs (single walled carbon nanotubes) based biosensor system for sensitive and selective E. coli detection in water samples. We use a novel and newly developed flexible biosensor device which was fabricated by high-rate nanoscale offset printing process using directed assembly and transfer of SWCNTs. By simple directed assembly and non-covalent functionalization, aptamer (biorecognition element that specifically distinguish the E. coli O157:H7 strain from other pathogens) based SWCNTs biosensor system was designed and was further evaluated for environmental applications with simple and cost-effective steps. The two gold electrode terminals and SWCNTs-bridge between them allow continuous resistance response monitoring for the E. coli detection. The detection procedure is based on competitive mode detection. A known concentration of aptamer and E. coli cells were mixed and after a certain time filtered. The rest of free aptamers injected to the system. With hybridization of the free aptamers and their SWCNTs surface immobilized probe DNA (complementary-DNA for E. coli aptamer), we can monitor the resistance difference which is proportional to the amount of the E. coli. Thus, we can detect the E. coli without injecting it directly onto the sensing surface, and we could protect the electrode surface from the aggregation of target bacteria or other pollutants that may come from real wastewater samples. After optimization experiments, the linear detection range was determined from 2 cfu/ml to 10⁵ cfu/ml with higher than 0.98 R² value. The system was regenerated successfully with 5 % SDS solution over 100 times without any significant deterioration of the sensor performance. The developed system had high specificity towards E. coli (less than 20 % signal with other pathogens), and it could be applied to real water samples with 86 to 101 % recovery and 3 to 18 % cv values (n=3).

Keywords: aptamer, E. coli, environmental detection, nanobiosensor, SWCTs

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Authors: Mohamad Syahrizal Ahmad, Illyas M. Isa

Abstract:

In this paper, a multiwall carbon nanotubes (MWCNT) paste electrode modified by a Zn layered hydroxide-ferulate (ZLH-F) was used for detection of hydroquinone (HQ). The morphology and characteristic of the ZLH-F/MWCNT were investigated by scanning electron microscope (SEM), transmission electron microscope (TEM) and square wave voltammetry (SWV). Under optimal conditions, the SWV response showed linear plot for HQ concentration in the range of 1.0×10⁻⁵ M – 1.0×10⁻³ M. The detection limit was found to be 5.7×10⁻⁶ M and correlation coefficient of 0.9957. The glucose, fructose, sucrose, bisphenol A, acetaminophen, lysine, NO₃⁻, Cl⁻ and SO₄²⁻ did not interfere the HQ response. This modified electrode can be used to determine HQ content in wastewater and cosmetic cream with range of recovery 97.8% - 103.0%.

Keywords: 1, 4-dihydroxybenzene, hydroquinone, multiwall carbon nanotubes, square wave voltammetry

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Authors: M. Cangi, T. Dolar, C. Ersoy, Y. E. Aydogdu, A. I. Aydeniz, A. Mugan

Abstract:

The drum is one of the critical parts in a washing machine in which the clothes are washed and spin by the rotational movement. It is activated by the drum shaft which is attached to an electric motor and subjected to dynamic loading. Being one of the critical components, failures of the drum require costly repairs of dynamic components. In this study, tolerance bands between the drum shaft and its two bearings were examined to develop a relationship between the fatigue life of the shaft and the interaction tolerances. Optimization of tolerance bands was completed in consideration of the fatigue life of the shaft as the cost function. The following methodology is followed: multibody dynamic model of a washing machine was constructed and used to calculate dynamic loading on the components. Then, these forces were used in finite element analyses to calculate the stress field in critical components which was used for fatigue life predictions. The factors affecting the fatigue life were examined to find optimum tolerance grade for a given test condition. Numerical results were verified by experimental observations.

Keywords: fatigue life, finite element analysis, tolerance analysis, optimization

Procedia PDF Downloads 142

Authors: Aileen F. Wang

Abstract:

Mammography has been one of the most reliable methods for early detection and diagnosis of breast cancer. However, mammography misses about 17% and up to 30% of breast cancers due to the subtle and unstable appearances of breast cancer in their early stages. Recent computer-aided diagnosis (CADx) technology using Zernike moments has improved detection accuracy. However, it has several drawbacks: it uses manual segmentation, Zernike moments are not robust, and it still has a relatively high false negative rate (FNR)–17.6%. This project will focus on the development of a novel breast cancer detection algorithm to automatically segment the breast mass and further reduce FNR. The algorithm consists of automatic segmentation of a single breast mass using Point Region Growing Segmentation, reconstruction of the segmented breast mass using Pseudo-Zernike moments, and classification of the breast mass using the root mean square (RMS). A comparative study among the various algorithms on the segmentation and reconstruction of breast masses was performed on randomly selected mammographic images. The results demonstrated that the newly developed algorithm is the best in terms of accuracy and cost effectiveness. More importantly, the new classifier RMS has the lowest FNR–6%.

Keywords: computer aided diagnosis, mammography, point region growing segmentation, pseudo-zernike moments, root mean square

Procedia PDF Downloads 433

Authors: Abdulrahman M. Hamid

Abstract:

Dynamic Cone Penetration Test (DCPT) is widely used for field quality assessment of soils. Its application to predict the engineering properties of soil is globally promoted by the fact that it is difficult to obtain undisturbed soil samples, especially when loose or submerged sandy soil is encountered. Detailed discussion will be presented on the current development of DCPT correlations with resilient modulus, relative density, California Bearing Ratio (CBR), unconfined compressive strength and shear strength that have been developed for different materials in both the laboratory and field, as well as on the usage of DCPT in quality control of compaction of earth fills and performance evaluation of pavement layers. In addition, the relationship of the DCPT with other instruments such as falling weight deflectometer, nuclear gauge, soil stiffens gauge, and plate load test will be reported. Lastely, the application of DCPT in Saudi Arabia in recent years will be addressed in this manuscript.

Keywords: dynamic cone penetration test, falling weight deflectometer, nuclear gauge, soil stiffens gauge, plate load test, automated dynamic cone penetration

Procedia PDF Downloads 404

Authors: Sevilay Çankaya

Abstract:

The detection of deception in children’s interviews is essential for statement veracity. The widely used method for deception detection is building cognitive load, which is the logic of the cognitive interview (CI), and its effectiveness for adults is approved. This meta-analysis delves into the effectiveness of inducing cognitive load as a means of enhancing veracity detection during interviews with children. Additionally, the effectiveness of cognitive load on children's total number of events recalled is assessed as a second part of the analysis. The current meta-analysis includes ten effect sizes from search using databases. For the effect size calculation, Hedge’s g was used with a random effect model by using CMA version 2. Heterogeneity analysis was conducted to detect potential moderators. The overall result indicated that cognitive load had no significant effect on veracity outcomes (g =0.052, 95% CI [-.006,1.25]). However, a high level of heterogeneity was found (I² = 92%). Age, participants’ characteristics, interview setting, and characteristics of the interviewer were coded as possible moderators to explain variance. Age was significant moderator (β = .021; p = .03, R2 = 75%) but the analysis did not reveal statistically significant effects for other potential moderators: participants’ characteristics (Q = 0.106, df = 1, p = .744), interview setting (Q = 2.04, df = 1, p = .154), and characteristics of interviewer (Q = 2.96, df = 1, p = .086). For the second outcome, the total number of events recalled, the overall effect was significant (g =4.121, 95% CI [2.256,5.985]). The cognitive load was effective in total recalled events when interviewing with children. All in all, while age plays a crucial role in determining the impact of cognitive load on veracity, the surrounding context, interviewer attributes, and inherent participant traits may not significantly alter the relationship. These findings throw light on the need for more focused, age-specific methods when using cognitive load measures. It may be possible to improve the precision and dependability of deceit detection in children's interviews with the help of more studies in this field.

Keywords: deceit detection, cognitive load, memory recall, children interviews, meta-analysis

Procedia PDF Downloads 42