Search results for: aerial imaging and detection

Authors: Benselama Amel, Ounane S. Mohamed, Bekki Abdelkader

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A collection of 20 isolates from fresh Nodules of the legume plant Lablab purpureus was isolated. These isolates have been authenticated by seedling inoculation grown in jars containing sand. The results obtained after two months of culture have revealed that the 20 isolates (100% of the isolates) are able to nodulate their host plants. The results obtained were analyzed statistically by ANOVA using the software statistica and had shown that the effect of the inoculation has significantly improved all the growth parameters (the height of the plant and the dry weight of the aerial parts and roots, and the number of nodules). We have evaluated the tolerance of all strains of the collection to the major stress factors as the salinity, pH and extreme temperature. The osmotolerance reached a concentration up to 1710mm of NaCl. The strains were also able to grow on a wide range of pH, ranging from 4.5 to 9.5, and temperature, between 4°C and 40°C. Also, we tested the effect of the acidity, aluminum and ferric deficit on the Lablab-rhizobia symbiosis. Lablab purpureus has not been affected by the presence of high concentrations of aluminum. On the other hand, iron deficiency has caused a net decrease in the dry biomass of the aerial part. The results of all the phenotypic characters have been treated by the statistical Minitab software, the numerical analysis had shown that these bacterial strains are divided into two distinct groups at a level of similarity of 86 %. The SDS-PAGE was carried out to determine the profile of the total protein of the strains. The coefficients of similarity of polypeptide bands between the isolates and strains reference (Bradyrhizobium, Mesorizobium sp.) confirm that our strain belongs to the groups of rhizobia.

Keywords: SDS-PAGE, rhizobia, symbiosis, phenotypic characterization, Lablab purpureus

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Authors: Yousef Reda

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Pancreatic cancer has an overall dismal prognosis. CT, MRI and Endoscopic Ultrasound are most often used to establish the diagnosis. We present a case of a patient found on abdominal CT and MRI to have an 8 mm cystic lesion within the head of the pancreas which was thought to be a benign intraductal papillary mucinous neoplasm (IPMN). Further evaluation by EUS demonstrated a 1 cm predominantly solid mass that was proven to be an adenocarcinoma by EUS-guided FNA. The patient underwent a Whipple procedure. The final pathology confirmed a 1 cm pT1 N0 pancreatic ductal adenocarcinoma. Case: A 63-year-old male presented with left upper quadrant pain and an abdominal CT demonstrated an 8 mm lesion within the head of the pancreas that was thought to represent a side branch IPMN. An MRI also showed similar findings. Four months later due to ongoing symptoms an EUS was performed to re-evaluate the pancreatic lesion. EUS revealed a predominantly solid hypoechoic, homogeneous mass measuring 12 mm x 9 mm. EUS-guided FNA was performed and was positive for adenocarcinoma. The patient underwent a Whipple procedure that confirmed it to be a ductal adenocarcinoma, pT1N0. The solid mass was noted to be adjacent to a cystic dilation with no papillary architecture and scant epithelium. The differential diagnosis resided between cystic degeneration of a primary pancreatic adenocarcinoma versus malignant degeneration within a side-branch IPMN. Discussion: The reported sensitivity of CT for pancreatic cancer is approximately 90%. For pancreatic tumors, less than 3 cm the sensitivity of CT is reduced ranging from 67-77%. MRI does not significantly improve overall detection rates compared to CT. EUS, however is superior to CT in the detection of pancreatic cancer, in particular among lesions smaller than 3 cm. EUS also outperforms CT and MRI in distinguishing neoplastic from non-neoplastic cysts. In this case, both MRI and CT failed to detect a small pancreatic adenocarcinoma. The addition of EUS and FNA to abdominal imaging can increase overall accuracy for the diagnosis of neoplastic pancreatic lesions. It may be prudent that when small lesions although appearing as a benign IPMN should further be evaluated by EUS as this would lead to potentially identifying earlier stage pancreatic cancers and improve survival in a disease which has a dismal prognosis.

Keywords: IPMN, MRI, EUS, CT

Procedia PDF Downloads 263

Authors: Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, Goutam Kumar Ghorai, Gautam Sarkar, Ashis K. Dhara

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Accurate segmentation of the optic disc is very important for computer-aided diagnosis of several ocular diseases such as glaucoma, diabetic retinopathy, and hypertensive retinopathy. The paper presents an accurate and fast optic disc detection and segmentation method using an attention based fully convolutional network. The network is trained from scratch using the fundus images of extended MESSIDOR database and the trained model is used for segmentation of optic disc. The false positives are removed based on morphological operation and shape features. The result is evaluated using three-fold cross-validation on six public fundus image databases such as DIARETDB0, DIARETDB1, DRIVE, AV-INSPIRE, CHASE DB1 and MESSIDOR. The attention based fully convolutional network is robust and effective for detection and segmentation of optic disc in the images affected by diabetic retinopathy and it outperforms existing techniques.

Keywords: attention-based fully convolutional network, optic disc detection and segmentation, retinal fundus image, screening of ocular diseases

Procedia PDF Downloads 142

Authors: Khin Mar Yee, Mu Mu Than, Kyi Lint, Aye Aye Oo, Chan Mya Hmway, Khin Zar Chi Winn

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The dynamic changes of Land Use and Land Cover (LULC) changes in Yangon have generally resulted the improvement of human welfare and economic development since the last twenty years. Making map of LULC is crucially important for the sustainable development of the environment. However, the exactly data on how environmental factors influence the LULC situation at the various scales because the nature of the natural environment is naturally composed of non-homogeneous surface features, so the features in the satellite data also have the mixed pixels. The main objective of this study is to the calculation of accuracy based on change detection of LULC changes by Support Vector Machines (SVMs). For this research work, the main data was satellite images of 1996, 2006 and 2015. Computing change detection statistics use change detection statistics to compile a detailed tabulation of changes between two classification images and Support Vector Machines (SVMs) process was applied with a soft approach at allocation as well as at a testing stage and to higher accuracy. The results of this paper showed that vegetation and cultivated area were decreased (average total 29 % from 1996 to 2015) because of conversion to the replacing over double of the built up area (average total 30 % from 1996 to 2015). The error matrix and confidence limits led to the validation of the result for LULC mapping.

Keywords: land use and land cover change, change detection, image processing, support vector machines

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Authors: Boudemagh Naime

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Automatic radar detection requires some methods of adapting to variations in the background clutter in order to control their false alarm rate. The problem becomes more complicated in non-Gaussian environment. In fact, the conventional approach in real time applications requires a complex statistical modeling and much computational operations. To overcome these constraints, we propose another approach based on artificial neural network (ANN-CMLD-CFAR) using a Back Propagation (BP) training algorithm. The considered environment follows a log-normal distribution in the presence of multiple Rayleigh-targets. To evaluate the performances of the considered detector, several situations, such as scale parameter and the number of interferes targets, have been investigated. The simulation results show that the ANN-CMLD-CFAR processor outperforms the conventional statistical one.

Keywords: radat detection, ANN-CMLD-CFAR, log-normal clutter, statistical modelling

Procedia PDF Downloads 364

Authors: Sherine Farrag

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Magnetic resonance imaging (MRI) presents safety hazards, with the general physical environment. The principal hazard of the MRI is the presence of static magnetic fields. Proper architectural design of MRI’s room ensure environment and health care staff safety. This research paper presents an easy approach for numerical computation of fringe static magnetic fields. Iso-gauss line of different MR intensities (0.3, 0.5, 1, 1.5 Tesla) was mapped and a polynomial function of the 7th degree was generated and tested. Matlab script was successfully applied for MRI SMF mapping. This method can be valid for any kind of commercial scanner because it requires only the knowledge of the MR scanner room map with iso-gauss lines. Results help to develop guidelines to guide healthcare architects to design of a safer Magnetic resonance imaging suite.

Keywords: designing MRI suite, MRI safety, radiology occupational exposure, static magnetic fields

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Authors: Sungsoo Na, Chanho Park

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Lung cancer is one of the most common severe diseases driving to the death of a human. Lung cancer can be divided into two cases of small-cell lung cancer (SCLC) and non-SCLC (NSCLC), and about 80% of lung cancers belong to the case of NSCLC. From several studies, the correlation between epidermal growth factor receptor (EGFR) and NSCLCs has been investigated. Therefore, EGFR inhibitor drugs such as gefitinib and erlotinib have been used as lung cancer treatments. However, the treatments result showed low response (10~20%) in clinical trials due to EGFR mutations that cause the drug resistance. Patients with resistance to EGFR inhibitor drugs usually are positive to KRAS mutation. Therefore, assessment of EGFR and KRAS mutation is essential for target therapies of NSCLC patient. In order to overcome the limitation of conventional therapies, overall EGFR and KRAS mutations have to be monitored. In this work, the only detection of EGFR will be presented. A variety of techniques has been presented for the detection of EGFR mutations. The standard detection method of EGFR mutation in ctDNA relies on real-time polymerase chain reaction (PCR). Real-time PCR method provides high sensitive detection performance. However, as the amplification step increases cost effect and complexity increase as well. Other types of technology such as BEAMing, next generation sequencing (NGS), an electrochemical sensor and silicon nanowire field-effect transistor have been presented. However, those technologies have limitations of low sensitivity, high cost and complexity of data analyzation. In this report, we propose a label-free and high-sensitive detection method of lung cancer using quartz crystal microbalance based platform. The proposed platform is able to sense lung cancer mutant DNA with a limit of detection of 1nM.

Keywords: cancer DNA, resonance frequency, quartz crystal microbalance, lung cancer

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Authors: Sidi M. A. Ghaly, Mohammad O. Khan, Mohammed Shalaby, Khaled A. Al-Snaie

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Electrical capacitance tomography (ECT) is a valuable, non-invasive technique used to monitor multiphase flow processes, especially within industrial pipelines. This study focuses on the design, testing, and performance comparison of ECT sensors configured with 8, 12, and 16 electrodes, aiming to evaluate their effectiveness in imaging accuracy, resolution, and sensitivity. Each sensor configuration was designed to capture the spatial permittivity distribution within a pipeline cross-section, enabling visualization of phase distribution and flow characteristics such as oil and water interactions. The sensor designs were implemented and tested in closed pipes to assess their response to varying flow regimes. Capacitance data collected from each electrode configuration were reconstructed into cross-sectional images, enabling a comparison of image resolution, noise levels, and computational demands. Results indicate that the 16-electrode configuration yields higher image resolution and sensitivity to phase boundaries compared to the 8- and 12-electrode setups, making it more suitable for complex flow visualization. However, the 8 and 12-electrode sensors demonstrated advantages in processing speed and lower computational requirements. This comparative analysis provides critical insights into optimizing ECT sensor design based on specific industrial requirements, from high-resolution imaging to real-time monitoring needs.

Keywords: capacitance tomography, modeling, simulation, electrode, permittivity, fluid dynamics, imaging sensitivity measurement

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Authors: Konstantinos C. Kartsakalis, Angeliki Skoura, Vasileios Megalooikonomou

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The fuzzy composition of objects depicted in images acquired through MR imaging or the use of bio-scanners has often been a point of controversy for field experts attempting to effectively delineate between the visualized objects. Modern approaches in medical image segmentation tend to consider fuzziness as a characteristic and inherent feature of the depicted object, instead of an undesirable trait. In this paper, a novel technique for efficient image retrieval in the context of images in which segmented objects are either crisp or fuzzily bounded is presented. Moreover, the proposed method is applied in the case of multiple, even conflicting, segmentations from field experts. Experimental results demonstrate the efficiency of the suggested method in retrieving similar objects from the aforementioned categories while taking into account the fuzzy nature of the depicted data.

Keywords: fuzzy object, fuzzy image segmentation, motion descriptors, MRI imaging, object-based image retrieval

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Authors: Neda Seyyedi, Reza Berangi

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Voice over IP (VOIP) network, also known as Internet telephony, is growing increasingly having occupied a large part of the communications market. With the growth of each technology, the related security issues become of particular importance. Taking advantage of this technology in different environments with numerous features put at our disposal, there arises an increasing need to address the security threats. Being IP-based and playing a signaling role in VOIP networks, Session Initiation Protocol (SIP) lets the invaders use weaknesses of the protocol to disable VOIP service. One of the most important threats is denial of service attack, a branch of which in this article we have discussed as flooding attacks. These attacks make server resources wasted and deprive it from delivering service to authorized users. Distributed denial of service attacks and attacks with a low rate can mislead many attack detection mechanisms. In this paper, we introduce a mechanism which not only detects distributed denial of service attacks and low rate attacks, but can also identify the attackers accurately. We detect and prevent flooding attacks in SIP protocol using Shannon (FDP-S), Renyi (FDP-R) and Tsallis (FDP-T) entropy. We conducted an experiment to compare the percentage of detection and rate of false alarm messages using any of the Shannon, Renyi and Tsallis entropy as a measure of disorder. Implementation results show that, according to the parametric nature of the Renyi and Tsallis entropy, by changing the parameters, different detection percentages and false alarm rates will be gained with the possibility to adjust the sensitivity of the detection mechanism.

Keywords: VOIP networks, flooding attacks, entropy, computer networks

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Authors: Samir Hessas

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Modern medicine is witnessing a profound transformation as advanced technology reshapes surgical environments. Hybrid operating rooms, where state-of-the-art medical equipment, advanced imaging solutions, and Artificial Intelligence (AI) converge, are at the forefront of this revolution. In this comprehensive exploration, we scrutinize the multifaceted facets of AI and delve into an array of groundbreaking technologies. We also discuss visionary concepts that hold the potential to revolutionize hybrid operating rooms, making them more efficient and patient-centered. These innovations encompass real-time imaging, surgical simulation, IoT and remote monitoring, 3D printing, telemedicine, quantum computing, and nanotechnology. The outcome of this fusion of technology and imagination is a promising future of surgical precision, individualized patient care, and unprecedented medical advances in hybrid operating rooms.

Keywords: artificial intelligence, hybrid operating rooms, telemedicine, monitoring

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Authors: Jae-Neung Lee, Keun-Chang Kwak

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This paper describes an analysis of Yacht Simulator international trends and also explains about Yacht. Examples of yacht Simulator using Yacht Simulator include image processing for totaling the total number of vehicles, edge/target detection, detection and evasion algorithm, image processing using SIFT (scale invariant features transform) matching, and application of median filter and thresholding.

Keywords: yacht simulator, simulator, trends analysis, SIFT

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Authors: Sebastian Hiergeist

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It is a common view that Unmanned Aerial Vehicles (UAV) tend to migrate into the civil airspace. This trend is challenging UAV manufacturer in plenty ways, as there come up a lot of new requirements and functional aspects. On the higher application levels, this might be collision detection and avoidance and similar features, whereas all these functions only act as input for the flight control components of the aircraft. The flight control computer (FCC) is the central component when it comes up to ensure a continuous safe flight and landing. As these systems are flight critical, they have to be built up redundantly to be able to provide a Fail-Operational behavior. Recent architectural approaches of FCCs used in UAV systems are often based on very simple microprocessors in combination with proprietary Application-Specific Integrated Circuit (ASIC) or Field Programmable Gate Array (FPGA) extensions implementing the whole redundancy functionality. In the future, such simple microprocessors may not be available anymore as they are more and more replaced by higher sophisticated System on Chip (SoC). As the avionic industry cannot provide enough market power to significantly influence the development of new semiconductor products, the use of solutions from foreign markets is almost inevitable. Products stemming from the industrial market developed according to IEC 61508, or automotive SoCs, according to ISO 26262, can be seen as candidates as they have been developed for similar environments. Current available SoC from the industrial or automotive sector provides quite a broad selection of interfaces like, i.e., Ethernet, SPI or FlexRay, that might come into account for the implementation of a redundancy network. In this context, possible network architectures shall be investigated which could be established by using the interfaces stated above. Of importance here is the avoidance of any single point of failures, as well as a proper segregation in distinct fault containment regions. The performed analysis is supported by the use of guidelines, published by the aviation authorities (FAA and EASA), on the reliability of data networks. The main focus clearly lies on the reachable level of safety, but also other aspects like performance and determinism play an important role and are considered in the research. Due to the further increase in design complexity of recent and future SoCs, also the risk of design errors, which might lead to common mode faults, increases. Thus in the context of this work also the aspect of dissimilarity will be considered to limit the effect of design errors. To achieve this, the work is limited to broadly available interfaces available in products from the most common silicon manufacturer. The resulting work shall support the design of future UAV FCCs by giving a guideline on building up a redundancy network between SoCs, solely using on board interfaces. Therefore the author will provide a detailed usability analysis on available interfaces provided by recent SoC solutions, suggestions on possible redundancy architectures based on these interfaces and an assessment of the most relevant characteristics of the suggested network architectures, like e.g. safety or performance.

Keywords: redundancy, System-on-Chip, UAV, flight control computer (FCC)

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Authors: Hassina Hafida Boukhalfa, Mathieu Massinon, Fréderic Lebeau, Mohamed Belhamra

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Drop behaviour during impact affects retention. The increase of adhesion is usually seen as the objective when applying crop protection products, while bouncing and shattering are seen as detrimental to spray retention. However, observation of drop impacts using high speed shadow graphy shows that fragmentation can occur in Wenzel wetting regime. In this case, a part of the drop sticks on the surface, what contributes to retention. Using simultaneous measurements of drop impacts with high speed imaging and of retention with fluorometry for 3 spray mixtures on excised barley leaves allowed us to observe that about 50% of the drops fragmented in Wenzel state remain on the leaf. Depending on spray mixture, these impact outcomes accounted for 25 to 50% of retention, the higher contribution being correlated with bigger VMD (Volume Median Diameter). This contribution is non-negligible and should be considered when a modelling of spray retention process is performed.

Keywords: drop impact, retention, fluorometry, high speed imaging

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Authors: Sangeeta Palekar, Mahima Rana, Jayu Kalambe

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In this paper, a microfluidic-based platform for the quantification of contaminants in the water is proposed. The proposed system uses microfluidic channels with an embedded environment for contaminants detection in water. Microfluidics-based platforms present an evident stage of innovation for fluid analysis, with different applications advancing minimal efforts and simplicity of fabrication. Polydimethylsiloxane (PDMS)-based microfluidics channel is fabricated using a soft lithography technique. Vertical and horizontal connections for fluid dispensing with the microfluidic channel are explored. The principle of colorimetry, which incorporates the use of Griess reagent for the detection of nitrite, has been adopted. Nitrite has high water solubility and water retention, due to which it has a greater potential to stay in groundwater, endangering aquatic life along with human health, hence taken as a case study in this work. The developed platform also compares the detection methodology, containing photodetectors for measuring absorbance and image sensors for measuring color change for quantification of contaminants like nitrite in water. The utilization of image processing techniques offers the advantage of operational flexibility, as the same system can be used to identify other contaminants present in water by introducing minor software changes.

Keywords: colorimetric, fluid contaminants, nitrite detection, microfluidics

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Authors: Samuel B. Dulay, Sandra Julich, Herbert Tomaso, Ciara K. O'Sullivan

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An early, rapid and definite detection for the presence of biowarfare agents, pathogens, viruses and toxins is required in different situations which include civil rescue and security units, homeland security, military operations, public transportation securities such as airports, metro and railway stations due to its harmful effect on the human population. In this work, an electrochemical genosensor array that allows simultaneous detection of different biowarfare agents within an integrated microsystem that provides an easy handling of the technology which combines a microfluidics setup with a multiplexing genosensor array has been developed and optimised for the following targets: Bacillus anthracis, Brucella abortis and melitensis, Bacteriophage lambda, Francisella tularensis, Burkholderia mallei and pseudomallei, Coxiella burnetii, Yersinia pestis, and Bacillus thuringiensis. The electrode array was modified via co-immobilisation of a 1:100 (mol/mol) mixture of a thiolated probe and an oligoethyleneglycol-terminated monopodal thiol. PCR products from these relevant biowarfare agents were detected reproducibly through a sandwich assay format with the target hybridised between a surface immobilised probe into the electrode and a horseradish peroxidase-labelled secondary reporter probe, which provided an enzyme based electrochemical signal. The potential of the designed microsystem for multiplexed genosensor detection and cross-reactivity studies over potential interfering DNA sequences has demonstrated high selectivity using the developed platform producing high-throughput.

Keywords: biowarfare agents, genosensors, multipled detection, microsystem

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Authors: Kulwinder Singh Mann

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The innovative features of information system, known as Radiology Information System (RIS), for electronic medical records has shown a good impact in the hospital. The objective is to help and make their work easier; such as for a physician to access the patient’s data and for a patient to check their bill transparently. The interoperability of RIS with the other intra-hospital information systems it interacts with, dealing with the compatibility and open architecture issues, are accomplished by two novel mechanisms. The first one is the particular message handling system that is applied for the exchange of information, according to the Health Level Seven (HL7) protocol’s specifications and serves the transfer of medical and administrative data among the RIS applications and data store unit. The second one implements the translation of information between the formats that HL7 and Digital Imaging and Communication in Medicine (DICOM) protocols specify, providing the communication between RIS and Picture and Archive Communication System (PACS) which is used for the increasing incorporation of modern medical imaging equipment.

Keywords: RIS, PACS, HIS, HL7, DICOM, messaging service, interoperability, digital images

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Authors: T. Garba, Y. Y. Babanyara, T. O. Quddus, A. K. Mukatari

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Human activities make environmental parameters in order to keep on changing globally. While some changes are necessary and beneficial to flora and fauna, others have serious consequences threatening the survival of their natural habitat if these changes are not properly monitored and mitigated. In-situ assessments are characterized by many challenges due to the absence of time series data and sometimes areas to be observed or monitored are inaccessible. Satellites Remote Sensing provide us with the digital images of same geographic areas within a pre-defined interval. This makes it possible to monitor and detect changes of environmental phenomena. This paper, therefore, reviewed the commonly use changes detection techniques globally such as image differencing, image rationing, image regression, vegetation index difference, change vector analysis, principal components analysis, multidate classification, post-classification comparison, and visual interpretation. The paper concludes by suggesting the use of more than one technique.

Keywords: environmental phenomena, change detection, monitor, techniques

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Authors: Hang Yang, Jichao Li, Kewei Yang, Tianyang Lei

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Multivariate time series anomaly detection is a significant research topic in the field of data mining, encompassing a wide range of applications across various industrial sectors such as traffic roads, financial logistics, and corporate production. The inherent spatial dependencies and temporal characteristics present in multivariate time series introduce challenges to the anomaly detection task. Previous studies have typically been based on the assumption that all variables belong to the same spatial hierarchy, neglecting the multi-level spatial relationships. To address this challenge, this paper proposes a multi-scale spatial and unified temporal feature fusion network, denoted as MSUT-Net, for multivariate time series anomaly detection. The proposed model employs a multi-level modeling approach, incorporating both temporal and spatial modules. The spatial module is designed to capture the spatial characteristics of multivariate time series data, utilizing an adaptive graph structure learning model to identify the multi-level spatial relationships between data variables and their attributes. The temporal module consists of a unified temporal processing module, which is tasked with capturing the temporal features of multivariate time series. This module is capable of simultaneously identifying temporal dependencies among different variables. Extensive testing on multiple publicly available datasets confirms that MSUT-Net achieves superior performance on the majority of datasets. Our method is able to model and accurately detect systems data with multi-level spatial relationships from a spatial-temporal perspective, providing a novel perspective for anomaly detection analysis.

Keywords: data mining, industrial system, multivariate time series, anomaly detection

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Authors: Chung-Yuan Huang, Yu-Hsiang Fu, Chuen-Tsai Sun

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Community detection represents an important data-mining tool for analyzing and understanding real-world complex network structures and functions. We believe that at least four criteria determine the appropriateness of a community detection algorithm: (a) it produces useable normalized mutual information (NMI) and modularity results for social networks, (b) it overcomes resolution limitation problems associated with synthetic networks, (c) it produces good NMI results and performance efficiency for Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks, and (d) it produces good modularity and performance efficiency for large-scale real-world complex networks. To our knowledge, no existing community detection algorithm meets all four criteria. In this paper, we describe a simple hierarchical arc-merging (HAM) algorithm that uses network topologies and rule-based arc-merging strategies to identify community structures that satisfy the criteria. We used five well-studied social network datasets and eight sets of LFR benchmark networks to validate the ground-truth community correctness of HAM, eight large-scale real-world complex networks to measure its performance efficiency, and two synthetic networks to determine its susceptibility to resolution limitation problems. Our results indicate that the proposed HAM algorithm is capable of providing satisfactory performance efficiency and that HAM-identified communities were close to ground-truth communities in social and LFR benchmark networks while overcoming resolution limitation problems.

Keywords: complex network, social network, community detection, network hierarchy

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Authors: Arwa Alzughaibi

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Human Motion detection is a challenging task due to a number of factors including variable appearance, posture and a wide range of illumination conditions and background. So, the first need of such a model is a reliable feature set that can discriminate between a human and a non-human form with a fair amount of confidence even under difficult conditions. By having richer representations, the classification task becomes easier and improved results can be achieved. The Aim of this paper is to investigate the reliable and accurate human motion detection models that are able to detect the human motions accurately under varying illumination levels and backgrounds. Different sets of features are tried and tested including Histogram of Oriented Gradients (HOG), Deformable Parts Model (DPM), Local Decorrelated Channel Feature (LDCF) and Aggregate Channel Feature (ACF). However, we propose an efficient and reliable human motion detection approach by combining Histogram of oriented gradients (HOG) and local phase quantization (LPQ) as the feature set, and implementing search pruning algorithm based on optical flow to reduce the number of false positive. Experimental results show the effectiveness of combining local phase quantization descriptor and the histogram of gradient to perform perfectly well for a large range of illumination conditions and backgrounds than the state-of-the-art human detectors. Areaunder th ROC Curve (AUC) of the proposed method achieved 0.781 for UCF dataset and 0.826 for CDW dataset which indicates that it performs comparably better than HOG, DPM, LDCF and ACF methods.

Keywords: human motion detection, histograms of oriented gradient, local phase quantization, local phase quantization

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Authors: Mohammad K. Parvez, Ahmed H. Arbab, Mohammed S. Al-Dosari, Adnan J. Al-Rehaily

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We investigated ex vivo and in vivo antioxidative and hepatoprotective effect of Aerva javanica. Total ethanol extract of A. javanica aerial parts was prepared, and tested on DCFH-toxicated HepG2 cell in CCl4-injured Wistar rats. MTT-assay was used to determine cell viability, and serum biochemical markers of liver injury as well as histopathology were performed. In vitro DPPH and β-carotene free-radical scavenging assay and phytochemical screening of the extract was done. Furthermore, A. javanica total extract was standardized and validated by HPTLC method. While DCFH-injured cells were recovered to about 56.7% by 100 microg/ml of the extract, a 200 microg/ml dose resulted in hepatocytes recovery by about 90.2%. Oral administration of the extract (100 and 200 mg/kg.bw/day) significantly normalized the serum SGOT, SGPT, GGT, ALP, bilirubin, cholesterol, HDL, LDL, VLDL, TG and MDA levels, including tissue NP-SH and TP in CCl4-injured rats. In addition, the histopathology of dissected liver also revealed that A. javanica cured the tissue lesion compared to reference drug, Silymarin. In vitro assays revealed strong free-radical scavenging ability of the extract and presence of alkaloids, flavonoids, tannins, sterols and saponins where Rutin, a well-known antioxidant flavonoid was identified. Our finding therefore, suggests the therapeutic potential of A. javanica in various liver diseases. However, isolation of the active principles, their mechanism of action and other therapeutic contribution remain to be addressed.

Keywords: Aerva javanica, antioxidant, hepatoprotection, rutin

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Authors: Mohamed Khalifa Zayet, Salma Belal Eiid, Mushira Mohamed Dahaba

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Introduction: Malignant tumors may not be easily detected by traditional radiographic techniques especially in an anatomically complex area like maxillofacial region. At the same time, the advent of biological functional MRI was a significant footstep in the diagnostic imaging field. Objective: The purpose of this study was to define the malignant metabolic profile of maxillofacial lesions using diffusion MRI and magnetic resonance spectroscopy, as adjunctive aids for diagnosing of such lesions. Subjects and Methods: Twenty-one patients with twenty-two lesions were enrolled in this study. Both morphological and functional MRI scans were performed, where T1, T2 weighted images, diffusion-weighted MRI with four apparent diffusion coefficient (ADC) maps were constructed for analysis, and magnetic resonance spectroscopy with qualitative and semi-quantitative analyses of choline and lactate peaks were applied. Then, all patients underwent incisional or excisional biopsies within two weeks from MR scans. Results: Statistical analysis revealed that not all the parameters had the same diagnostic performance, where lactate had the highest areas under the curve (AUC) of 0.9 and choline was the lowest with insignificant diagnostic value. The best cut-off value suggested for lactate was 0.125, where any lesion above this value is supposed to be malignant with 90 % sensitivity and 83.3 % specificity. Despite that ADC maps had comparable AUCs still, the statistical measure that had the final say was the interpretation of likelihood ratio. As expected, lactate again showed the best combination of positive and negative likelihood ratios, whereas for the maps, ADC map with 500 and 1000 b-values showed the best realistic combination of likelihood ratios, however, with lower sensitivity and specificity than lactate. Conclusion: Diffusion weighted imaging and magnetic resonance spectroscopy are state-of-art in the diagnostic arena and they manifested themselves as key players in the differentiation process of orofacial tumors. The complete biological profile of malignancy can be decoded as low ADC values, high choline and/or high lactate, whereas that of benign entities can be translated as high ADC values, low choline and no lactate.

Keywords: diffusion magnetic resonance imaging, magnetic resonance spectroscopy, malignant tumors, maxillofacial

Procedia PDF Downloads 171

Authors: Syed Farooq Adil, Merajuddinkhan, Mujeeb Khan, Hamad Z. Alkhathlan

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Phytochemicals from plant extracts belong to an important source of natural products which have demonstrated excellent cytotoxic activities. However, plants of different origins exhibit diverse chemical compositions and bioactivities. Therefore, the discovery of plants based new anticancer agents from different parts of the world is always challenging. In this study, methanolic extracts of different parts of 11 plants from Saudi Arabia have been tested in vitro for their anticancer potential on human liver cancer cell line (HepG2). Particularly, for this study, plants from Asteraceae, Resedaceae, and Polygonaceae families were chosen on the basis of locally available ethnobotanical data and their medicinal properties. Among 12 tested extract samples, three samples obtained from Artemisia monosperma stem, Ochradenus baccatus aerial parts, and Pulicaria glutinosa stem have demonstrated interesting cytotoxic activities with a cell viability of 29.3%, 28.4% and 24.2%, respectively. Whereas, four plant extracts including Calendula arvensis aerial parts, Scorzonera musilii whole plant, A. monosperma leaves show moderate anticancer properties bearing a cell viability ranging from 11.9 to 16.7%. The remaining extracts have shown poor cytotoxic activities. Subsequently, GC-MS analysis of methanolic extracts of the four most active plants extracts such as C. comosum, O. baccatus, P. glutinosa and A. monosperma detected the presence of 41 phytomolecules. Among which 3-(4-hydroxyphenyl) propionitrile (1), 8,11-octadecadiynoic acid methyl ester (2), 6,7-dimethoxycoumarin (3), and 1-(2-hydroxyphenyl) ethenone (4) were found to be the lead compounds of C. comosum, O. baccatus P. glutinosa and A. monosperma, respectively.

Keywords: medicinal plants, asteraceae, polygonaceae, hepg2

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Authors: S. Korkut, M. S. Kilic, E. Erhan

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In order to detect and quantify the phenolic contents of a wastewater with biosensors, two working electrodes based on modified Poly (Pyrrole) films were fabricated. Enzyme horseradish peroxidase was used as biomolecule of the prepared electrodes. Various phenolics were tested at the biosensor. Phenol detection was realized by electrochemical reduction of quinones produced by enzymatic activity. Analytical parameters were calculated and the results were compared with each other.

Keywords: carbon nanotube, phenol biosensor, polypyrrole, poly (glutaraldehyde)

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Authors: A. Nachour, L. Ouzizi, Y. Aoura

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Recent developments on multi-agent system have brought a new research field on image processing. Several algorithms are used simultaneously and improved in deferent applications while new methods are investigated. This paper presents a new automatic method for edge detection using several agents and many different actions. The proposed multi-agent system is based on parallel agents that locally perceive their environment, that is to say, pixels and additional environmental information. This environment is built using Vector Field Convolution that attract free agent to the edges. Problems of partial, hidden or edges linking are solved with the cooperation between agents. The presented method was implemented and evaluated using several examples on different synthetic and medical images. The obtained experimental results suggest that this approach confirm the efficiency and accuracy of detected edge.

Keywords: edge detection, medical MRImages, multi-agent systems, vector field convolution

Procedia PDF Downloads 391

Authors: Lucja Rodzik, Joanna Lewandowska-Lancucka, Michal Szuwarzynski, Krzysztof Szczubialka, Maria Nowakowska

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The analysis of nucleobases is of great importance for bioscience since their abnormal concentration in body fluids suggests the deficiency and mutation of the immune system, and it is considered to be an important parameter for diagnosis of various diseases. The presented conjugate meets the need for development of the effective, selective and highly sensitive sensor for nucleobase/nucleoside detection. The novel, highly fluorescent cadmium telluride quantum dots (CdTe QDs) functionalized with thymine and stabilized with thioglycolic acid (TGA) conjugates has been developed and thoroughly characterized. Successful formation of the material was confirmed by elemental analysis, and UV–Vis fluorescence and FTIR spectroscopies. The crystalline structure of the obtained product was characterized with X-ray diffraction (XRD) method. The composition of CdTe QDs and their thymine conjugate was also examined using X-ray photoelectron spectroscopy (XPS). The size of the CdTe-thymine was 3-6 nm as demonstrated using atomic force microscopy (AFM) and high resolution transmission electron microscopy (HRTEM) imaging. The plasmon resonance fluorescence band at 540 nm on excitation at 351 nm was observed for these nanoparticles. The intensity of this band increased with the increase in the amount of conjugated thymine with no shift in its position. Based on the fluorescence measurements, it was found that the CdTe-thymine conjugate interacted efficiently and selectively not only with adenine, a nucleobase complementary to thymine, but also with nucleosides and adenine-containing modified nucleosides, i.e., 5′-deoxy-5′-(methylthio)adenosine (MTA) and 2’-O-methyladenosine, the urinary tumor markers which allow monitoring of the disease progression. The applicability of the CdTe-thymine sensor for the real sample analysis was also investigated in simulated urine conditions. High sensitivity and selectivity of CdTe-thymine fluorescence towards adenine, adenosine and modified adenosine suggest that obtained conjugate can be potentially useful for development of the biosensor for complementary nucleobase/nucleoside detection.

Keywords: CdTe quantum dots, conjugate, sensor, thymine

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Authors: Retno Supriyanti, Ahmad Chuzaeri, Yogi Ramadhani, A. Haris Budi Widodo

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The use of ultrasonography in the medical world has been very popular including the diagnosis of pregnancy. In determining pregnancy, ultrasonography has many roles, such as to check the position of the fetus, abnormal pregnancy, fetal age and others. Unfortunately, all these things still need to analyze the role of the obstetrician in the sense of image raised by ultrasonography. One of the most striking is the determination of gestational age. Usually, it is done by measuring the length of the fetus manually by obstetricians. In this study, we developed a computer-aided diagnosis for the determination of gestational age by measuring the length of the fetus automatically using edge detection method and image morphology. Results showed that the system is sufficiently accurate in determining the gestational age based image processing.

Keywords: computer aided diagnosis, gestational age, and diameter of uterus, length of fetus, edge detection method, morphology image

Procedia PDF Downloads 294

Authors: Alden Boby, Dane Brown, James Connan

Abstract:

Character recognition is a well-researched topic across disciplines. Regardless, creating a solution that can cater to multiple situations is still challenging. Vehicle licence plates lack an international standard, meaning that different countries and regions have their own licence plate format. A problem that arises from this is that the typefaces and designs from different regions make it difficult to create a solution that can cater to a wide range of licence plates. The main issue concerning detection is the character recognition stage. This paper aims to create an object detection-based character recognition model trained on a custom dataset that consists of typefaces of licence plates from various regions. Given that characters have featured consistently maintained across an array of fonts, YOLO can be trained to recognise characters based on these features, which may provide better performance than OCR methods such as Tesseract OCR.

Keywords: computer vision, character recognition, licence plate recognition, object detection

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Authors: Niloofar Yousefi, Marie Alaghband, Ivan Garibay

Abstract:

With the increase of credit card usage, the volume of credit card misuse also has significantly increased, which may cause appreciable financial losses for both credit card holders and financial organizations issuing credit cards. As a result, financial organizations are working hard on developing and deploying credit card fraud detection methods, in order to adapt to ever-evolving, increasingly sophisticated defrauding strategies and identifying illicit transactions as quickly as possible to protect themselves and their customers. Compounding on the complex nature of such adverse strategies, credit card fraudulent activities are rare events compared to the number of legitimate transactions. Hence, the challenge to develop fraud detection that are accurate and efficient is substantially intensified and, as a consequence, credit card fraud detection has lately become a very active area of research. In this work, we provide a survey of current techniques most relevant to the problem of credit card fraud detection. We carry out our survey in two main parts. In the first part, we focus on studies utilizing classical machine learning models, which mostly employ traditional transnational features to make fraud predictions. These models typically rely on some static physical characteristics, such as what the user knows (knowledge-based method), or what he/she has access to (object-based method). In the second part of our survey, we review more advanced techniques of user authentication, which use behavioral biometrics to identify an individual based on his/her unique behavior while he/she is interacting with his/her electronic devices. These approaches rely on how people behave (instead of what they do), which cannot be easily forged. By providing an overview of current approaches and the results reported in the literature, this survey aims to drive the future research agenda for the community in order to develop more accurate, reliable and scalable models of credit card fraud detection.

Keywords: Credit Card Fraud Detection, User Authentication, Behavioral Biometrics, Machine Learning, Literature Survey

Procedia PDF Downloads 121