Search results for: structural vulnerability detection

Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

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Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: color overlapping windows, image stitching, leukocyte detection, white blood cell detection

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Authors: Maria Del Mar Maira Vidal, Alvaro Briales

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In this paper, we will conduct an analysis of the results of the I+D+i research project “New types of socio-existential vulnerability, support and care in Spain” (VULSOCU) (2016-20). This project had the objective to analyze the new types of vulnerability that are the result of the combination of several factors as the economic crisis, the unemployment, the transformations of the Welfare State, the individualization, etc. We have, therefore, analyzed the way that Spanish long-term unemployed over 45 years experience vulnerability and its consequences on their lives. We have focused on long-term unemployed over 45 that had previously developed stable career paths and have been looking for a job for two years or more. In order to carry out this analysis, we will try to break the dichotomy between the social and the individual, between the socio-historical and the subjectivity, to overcome some of the limits of the research on unemployment. The fieldwork consisted of more than ten focus groups and fifty in-depth interviews. The work and life ethics completely changed at the turn of the nineteenth and twentieth centuries. In the nineteenth century, companies had trouble maintaining their staff, but in the 21st century, unemployed workers feel that they are useless people. Workers value themselves if they have a job. This unveils that labor is a comprehensive social relationship in capitalist societies. In general, unemployed workers are not able to analyze their unemployment as a social problem. They analyze their unemployment as an individual problem. They blame themselves for their unemployment; instead of taking into account that there are millions of unemployed, they talk about themselves as if they were on their own. And the problems caused by unemployment are explained as psychological problems and are medicalized. Anyway, it is important to highlight that this is the result of an ideology and a social relationship that is part of our historical time.

Keywords: life ethics, work ethics, unemployment, unemployed over 45 years old

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Authors: Moustapha H. Ibrahim, Dahir Abdourahman

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This document presents a short-circuit fault detection process in a photovoltaic (PV) system. The proposed method is developed in MATLAB/Simulink. It determines whatever the size of the installation number of the short circuit module. The proposed algorithm indicates the presence or absence of an abnormality on the power of the PV system through measures of hourly global irradiation, power output, and ambient temperature. In case a fault is detected, it displays the number of modules in a short circuit. This fault detection method has been successfully tested on two different PV installations.

Keywords: PV system, short-circuit, fault detection, modelling, MATLAB-Simulink

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Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

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Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

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Authors: M. Khouil, N. Saber, M. Mestari

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In this paper, a different architecture of a collision detection neural network (DCNN) is developed. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons, linear and threshold logic, which simplified the actual implementation of all the networks proposed. The study of the collision detection is divided into two sections, the collision between a point and a polyhedron and then the collision between two convex polyhedra. The aim of this research is to determine through the AMAXNET network a mini maximum point in a fixed time, which allows us to detect the presence of a potential collision.

Keywords: collision identification, fixed time, convex polyhedra, neural network, AMAXNET

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Authors: Sriraman Kothuri, Komal Teja Mattupalli

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In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.

Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm

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Authors: Jae Moon Im, Kwang Bok Shin, Sang Woo Lee

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In this paper, evaluation of structural integrity for composite lattice structure was conducted by compressive test. Composite lattice structure was manufactured by carbon fiber using filament winding method. In order to evaluate the structural integrity of composite lattice structure, compressive test was done using anti-buckling fixture. The delamination occurred 84 Tons of compressive load. It was found that composite lattice structure satisfied the design requirements.

Keywords: composite material, compressive test, lattice structure, structural integrity

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Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

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A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

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Authors: Natalya G. Filimonova, Mariya G. Ozerova, Irina N. Ermakova

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The long-term strategy of the economic development of Russia up to 2030 is based on the concept of sustainable growth. The determining factor of such development is complex changes in the economic system which may be achieved by making progressive changes in its structure. The structural changes determine the character and the direction of economic development, as well as they include all elements of this system without exception, and their regulated character ensures the most rapid aim achievement. This article has discussed the industrial structure of the agriculture in Russia. With the use of the system of indexes, the article has determined the directions, intensity, and speed of structural shifts. The influence of structural changes on agricultural production development has been found out. It is noticed that the changes in the industrial structure are synchronized with the changes in the organisation and economic structure. Efficiency assessment of structural changes allowed to trace the efficiency of structural changes and elaborate the main directions for agricultural policy improvement.

Keywords: Russian agricultural sectors, sectoral structure, organizational and economic structure, structural changes

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Authors: Zdenek Silar, Martin Dobrovolny

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This article deals with the obstacle detection on a railway crossing (clearance detection). Detection is based on the optical flow estimation and classification of the flow vectors by K-means clustering algorithm. For classification of passing vehicles is used optical flow direction determination. The optical flow estimation is based on a modified Lucas-Kanade method.

Keywords: background estimation, direction of optical flow, K-means clustering, objects detection, railway crossing monitoring, velocity vectors

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Authors: Ma Lei-Lei, Zhou You

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Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

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Authors: Geraldine G. Granados Vazquez

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Every human being is exposed to the risk of dying; wherein some of them are more susceptible than others depending on the cause. Therefore, the cause could be the hazard to die that a group or individual has, making this irreversible damage the condition of vulnerability. Risk is a dynamic concept; which means that it depends on the environmental, social, economic and political conditions. Thus vulnerability may only be evaluated in terms of relative parameters. This research is focusing specifically on building a model that evaluate the risk or propensity of death in past urban societies in connection with the everyday life of individuals, considering that death can be a consequence of two coexisting issues: hazard and the deterioration of the resistance to destruction. One of the most important discussions in bioarchaeology refers to health and life conditions in ancient groups; the researchers are looking for more flexible models that evaluate these topics. In that way, this research proposes a theoretical-methodological model that assess the vulnerability of death in past urban groups. This model pretends to be useful to evaluate the risk of death, considering their sociohistorical context, and their intrinsic biological features. This theoretical and methodological model, propose four areas to assess vulnerability. The first three areas use statistical methods or quantitative analysis. While the last and fourth area, which corresponds to the embodiment, is based on qualitative analysis. The four areas and their techniques proposed are a) Demographic dynamics. From the distribution of age at the time of death, the analysis of mortality will be performed using life tables. From here, four aspects may be inferred: population structure, fertility, mortality-survival, and productivity-migration, b) Frailty. Selective mortality and heterogeneity in frailty can be assessed through the relationship between characteristics and the age at death. There are two indicators used in contemporary populations to evaluate stress: height and linear enamel hypoplasias. Height estimates may account for the individual’s nutrition and health history in specific groups; while enamel hypoplasias are an account of the individual’s first years of life, c) Inequality. Space reflects various sectors of society, also in ancient cities. In general terms, the spatial analysis uses measures of association to show the relationship between frail variables and space, d) Embodiment. The story of everyone leaves some evidence on the body, even in the bones. That led us to think about the dynamic individual's relations in terms of time and space; consequently, the micro analysis of persons will assess vulnerability from the everyday life, where the symbolic meaning also plays a major role. In sum, using some Mesoamerica examples, as study cases, this research demonstrates that not only the intrinsic characteristics related to the age and sex of individuals are conducive to vulnerability, but also the social and historical context that determines their state of frailty before death. An attenuating factor for past groups is that some basic aspects –such as the role they played in everyday life– escape our comprehension, and are still under discussion.

Keywords: bioarchaeology, frailty, Mesoamerica, vulnerability

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Authors: Ujjal Chattaraj, P. C. Dasbebartta, S. Bhuyan

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This paper aims to propose a method to detect the action of the driver’s eyes, using the concept of face detection. There are three major key contributing methods which can rapidly process the framework of the facial image and hence produce results which further can program the reactions of the vehicles as pre-programmed for the traffic safety. This paper compares and analyses the methods on the basis of their reaction time and their ability to deal with fluctuating images of the driver. The program used in this study is simple and efficient, built using the AdaBoost learning algorithm. Through this program, the system would be able to discard background regions and focus on the face-like regions. The results are analyzed on a common computer which makes it feasible for the end users. The application domain of this experiment is quite wide, such as detection of drowsiness or influence of alcohols in drivers or detection for the case of identification.

Keywords: AdaBoost learning algorithm, face detection, framework, traffic safety

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Authors: Samra Naz, Aneeqa Ahmed, Qurat-ul-ain Mubarak, Irum Nausheen

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Driver safety systems protect driver from accidents by sensing signs of drowsiness. The paper proposes a technique which can detect the signs of drowsiness and make corresponding decisions to make the driver alert. This paper presents a technique in which the driver will be continuously monitored by a camera and his eyes, head and mouth movements will be observed. If the drowsiness signs are detected on the basis of these three movements under the predefined criteria, driver will be declared as sleepy and he will get alert with the help of alarms. Three robust techniques of drowsiness detection are combined together to make a robust system that can prevent form accident.

Keywords: drowsiness, eye closure, fatigue detection, yawn detection

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Authors: A. Moawad, K. C. Yao, A. Mansour, R. Gautier

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The detecting of an occupied frequency band is a major issue in cognitive radio systems. The detection process becomes difficult if the signal occupying the band of interest has faded amplitude due to multipath effects. These effects make it hard for an occupying user to be detected. This work mitigates the missed-detection problem in the context of cognitive radio in frequency-selective fading channel by proposing blind channel estimation method that is based on scattering transform. By initially applying conventional energy detection, the missed-detection probability is evaluated, and if it is greater than or equal to 50%, channel estimation is applied on the received signal followed by channel equalization to reduce the channel effects. In the proposed channel estimator, we modify the Morlet wavelet by using its first derivative for better frequency resolution. A mathematical description of the modified function and its frequency resolution is formulated in this work. The improved frequency resolution is required to follow the spectral variation of the channel. The channel estimation error is evaluated in the mean-square sense for different channel settings, and energy detection is applied to the equalized received signal. The simulation results show improvement in reducing the missed-detection probability as compared to the detection based on principal component analysis. This improvement is achieved at the expense of increased estimator complexity, which depends on the number of wavelet filters as related to the channel taps. Also, the detection performance shows an improvement in detection probability for low signal-to-noise scenarios over principal component analysis- based energy detection.

Keywords: channel estimation, cognitive radio, scattering transform, spectrum sensing

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Authors: Ionel D. Craiu, Mihai Nedelcu

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Thin-walled cylinders are often used by the offshore industry as columns of floating installations. Based on observed strains, the inverse Finite Element Method (iFEM) may rebuild the deformation of structures. Structural Health Monitoring uses this approach extensively. However, the number of in-situ strain gauges is what determines how accurate it is, and for shell structures with complicated deformation, this number can easily become too high for practical use. Any thin-walled beam member's complicated deformation can be modeled by the Generalized Beam Theory (GBT) as a linear combination of pre-specified cross-section deformation modes. GBT uses bar finite elements as opposed to shell finite elements. This paper proposes an iFEM/GBT formulation for the shape sensing of thin-walled cylinders based on these benefits. This method significantly reduces the number of strain gauges compared to using the traditional inverse-shell finite elements. Using numerical simulations, dent damage detection is achieved by comparing the strain distributions of the undamaged and damaged members. The effect of noise on strain measurements is also investigated.

Keywords: damage detection, generalized beam theory, inverse finite element method, shape sensing

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Authors: Hong Yu, Ion Matei

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Carbon fiber reinforced composites (CFRP) used as aircraft structure are subject to lightning strike, putting structural integrity under risk. Indirect damage may occur after a lightning strike where the internal structure can be damaged due to excessive heat induced by lightning current, while the surface of the structures remains intact. Three damage modes may be observed after a lightning strike: fiber breakage, inter-ply delamination and intra-ply cracks. The assessment of internal damage states in composite is challenging due to complicated microstructure, inherent uncertainties, and existence of multiple damage modes. In this work, a model based approach is adopted to diagnose faults in carbon composites after lighting strikes. A resistor network model is implemented to relate the overall electrical and thermal conduction behavior under simulated lightning current waveform to the intrinsic temperature dependent material properties, microstructure and degradation of materials. A fault detection and identification (FDI) module utilizes the physics based model and a particle filtering algorithm to identify damage mode as well as calculate the probability of structural failure. Extensive simulation results are provided to substantiate the proposed fault diagnosis methodology with both single fault and multiple faults cases. The approach is also demonstrated on transient resistance data collected from a IM7/Epoxy laminate under simulated lightning strike.

Keywords: carbon composite, fault detection, fault identification, particle filter

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Authors: Muhammad Irfan

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The rise of radicalization within Islam has spawned a new era of global terror. The battlefield Successes of ISIS and the Taliban are fuelled by an ideological war waged, largely and successfully, in the media arena. This research will examine how Islamic extremist groups are using media modalities and populist narratives to influence migrant Muslim populations in Europe towards extremism. In 2014, ISIS shocked the world in exporting horrifically graphic forms of violence on social media. Their Muslim support base was largely disgusted and reviled. In response, they reconfigured their narrative by introducing populist 'hooks', astutely portraying the Muslim populous as oppressed and exploited by unjust, corrupt autocratic regimes and Western power structures. Within this crucible of real and perceived oppression, hundreds of thousands of the most desperate, vulnerable and abused migrants left their homelands, risking their lives in the hope of finding peace, justice, and prosperity in Europe. Instead, many encountered social stigmatization, detention and/or discrimination for being illegal migrants, for lacking resources and for simply being Muslim. This research will examine how Islamic extremist groups are exploiting the disenfranchisement of these migrant populations and using populist messaging on social media to influence them towards violent extremism. ISIS, in particular, formulates specific encoded messages for newly-arriving Muslims in Europe, preying upon their vulnerability. Violence is posited, as a populist response, to the tyranny of European oppression. This research will analyze the factors and indicators which propel Muslim migrants along the spectrum from resilience to violence extremism. Expected outcomes are identification of factors which influence vulnerability towards violent extremism; an early-warning detection framework; predictive analysis models; and de-radicalization frameworks. This research will provide valuable tools (practical and policy level) for European governments, security stakeholders, communities, policy-makers, and educators; it is anticipated to contribute to a de-escalation of Islamic extremism globally.

Keywords: populism, radicalization, de-radicalization, social media, ISIS, Taliban, shariah, jihad, Islam, Europe, political communication, terrorism, migrants, refugees, extremism, global terror, predictive analysis, early warning detection, models, strategic communication, populist narratives, Islamic extremism

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Authors: Muhammad Rosli Abdullah, Noor Hasmiza Harun

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A microorganism detection system has a potential to be used with the advancement in a biosensor development. The detection system requires an optical sensing system, microfluidic device and biological reagent. Although, the biosensors are available in the market, a label free and a lab-on-chip approach will promote a flexible solution. As a preliminary study of microorganism detection, three mechanisms such as Total Internal Reflection (TIR), Micro Fluidic Channel (MFC) and magnetic-electric field propagation were study and simulated. The objective are to identify the TIR angle, MFC parabolic flow and the wavelength for the microorganism detection. The simulation result indicates that evanescent wave is achieved when TIR angle > 42°, the corner and centre of a parabolic velocity are 0.02 m/s and 0.06 m/s respectively, and a higher energy distribution of a perfect electromagnetic scattering with dipole resonance radiation occurs at 500 nm. This simulation is beneficial to determine the components of the microorganism detection system that does not rely on classical microbiological, immunological and genetic methods which are laborious, time-consuming procedures and confined to specialized laboratories with expensive instrumentation equipment.

Keywords: microorganism, microfluidic, total internal reflection, lab on chip

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Authors: Vijaya Yuvaram Singh V M, Kameshwar Rao J V

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The challenge with development of neural network based methods for medical is the availability of data. Anatomical landmark detection in the medical domain is a process to find points on the x-ray scan report of the patient. Most of the time this task is done manually by trained professionals as it requires precision and domain knowledge. Traditionally object detection based methods are used for landmark detection. Here, we utilize reinforcement learning and query based method to train a single agent capable of detecting multiple landmarks. A deep Q network agent is trained to detect single and multiple landmarks present on hip and shoulder from x-ray scan of a patient. Here a single agent is trained to find multiple landmark making it superior to having individual agents per landmark. For the initial study, five images of different patients are used as the environment and tested the agents performance on two unseen images.

Keywords: reinforcement learning, medical landmark detection, multi target detection, deep neural network

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Authors: Mohd Noah A. Rahman, Afzaal H. Seyal, Norhafilah Bara

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Developing a software application using an interface with computers and peripheral devices using gestures of human body such as hand movements keeps growing in interest. A review on this hand gesture detection and recognition based on computer vision technique remains a very challenging task. This is to provide more natural, innovative and sophisticated way of non-verbal communication, such as sign language, in human computer interaction. Nevertheless, this paper explores hand detection and hand gesture recognition applying a vision based approach. The hand detection and recognition used skin color spaces such as HSV and YCrCb are applied. However, there are limitations that are needed to be considered. Almost all of skin color space models are sensitive to quickly changing or mixed lighting circumstances. There are certain restrictions in order for the hand recognition to give better results such as the distance of user’s hand to the webcam and the posture and size of the hand.

Keywords: hand detection, hand gesture, hand recognition, sign language

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Authors: Francisco Borja de Lara, Ali Ravanbakhsh, Robert F. Wimmer-Schweingruber, Lars Seimetz, Fermín Navarro

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The intense structural loads during the launch of a spacecraft represent a challenge for the space structure designers because enough resistance has to be achieved while maintaining at the same time the mass and volume within the allowable margins of the mission requirements and inside the limits of the budget project. In this conference, we present the structural analysis of the Lunar Lander Neutron Dosimetry (LND) experiment on the Chang'E4 mission, the first probe to land on the moon’s far side included in the Chinese’ Moon Exploration Program by the Chinese National Space Administration. To this target, the software Nastran/Patran has been used: a structural model in Patran and a structural analysis through Nastran have been realized. Next, the results obtained are used both for the optimization process of the spacecraft structure, and as input parameters for the model structural test campaign. In this way, the feasibility of the lunar instrument structure is demonstrated in terms of the modal modes, stresses, and random vibration and a better understanding of the structural tests design is provided by our results.

Keywords: Chang’E4, Chinese national space administration, lunar lander neutron dosimetry, nastran-patran, structural analysis

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Authors: Elise M. Shauf

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Beryllium can be found naturally in some fruits and vegetables (carrots, garden peas, kidney beans, pears) at very low concentrations, but is typically not clinically significant due to the low-level exposure and limited absorption of beryllium by the stomach and intestines. However, acute or chronic beryllium exposure can result in harmful toxic and carcinogenic biological effects. Beryllium can be both a workplace hazard and an environmental pollutant, therefore determining the presence of beryllium at trace levels can be essential to protect workers as well as the environment. Analysis of gallein, C₂₀H₁₂O₇, to determine if it is usable as a fluorescent dye for beryllium detection. The primary detection method currently in use includes hydroxybenzoquinoline sulfonates (HBQS), for which alternative indicators are desired. Unfortunately, gallein does not have the desired aspects needed as a dye for beryllium detection due to the peak shift properties.

Keywords: beryllium detection, fluorescent, gallein dye, indicator, spectroscopy

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Authors: Gichun Cha, Byoungjoon Yu, Jihwan Park, Minsoo Park, Junghyun Im, Sehwan Park, Sujung Sin, Seunghee Park

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The goal of this research is to estimate a structural shape change using terrestrial laser scanning. This study proceeds with development of data reduction and shape change estimation algorithm for large-capacity scan data. The point cloud of scan data was converted to voxel and sampled. Technique of shape estimation is studied to detect changes in structure patterns, such as skyscrapers, bridges, and tunnels based on large point cloud data. The point cloud analysis applies the octree data structure to speed up the post-processing process for change detection. The point cloud data is the relative representative value of shape information, and it used as a model for detecting point cloud changes in a data structure. Shape estimation model is to develop a technology that can detect not only normal but also immediate structural changes in the event of disasters such as earthquakes, typhoons, and fires, thereby preventing major accidents caused by aging and disasters. The study will be expected to improve the efficiency of structural health monitoring and maintenance.

Keywords: terrestrial laser scanning, point cloud, shape information model, displacement measurement

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Authors: Junyou Shi, Weiwei Cui

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Testability modeling is a commonly used method in testability design and analysis of system. A dependency matrix will be obtained from testability modeling, and we will give a quantitative evaluation about fault detection and isolation. Based on the dependency matrix, we can obtain the diagnosis tree. The tree provides the procedures of the fault detection and isolation. But the dependency matrix usually includes built-in test (BIT) and manual test in fact. BIT runs the test automatically and is not limited by the procedures. The method above cannot give a more efficient diagnosis and use the advantages of the BIT. A Comprehensive method of fault detection and isolation is proposed. This method combines the advantages of the BIT and Manual test by splitting the matrix. The result of the case study shows that the method is effective.

Keywords: fault detection, fault isolation, testability modeling, BIT

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Authors: Alma Mendoza-Ponce, Rogelio Corona-Núñez, Florian Kraxner

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Mexico is a megadiverse country and it has nearly halved its natural vegetation in the last century due to agricultural and livestock expansion. Impacts of land use cover change and climate change are unevenly distributed and spatial prioritization to minimize the affectations on biodiversity is crucial. Global and national efforts for prioritizing biodiversity conservation show that ~33% to 45% of Mexico should be protected. The width of these targets makes difficult to lead resources. We use a framework based on vulnerability and irreplaceability to prioritize conservation efforts in Mexico. Vulnerability considered exposure, sensitivity and adaptive capacity under two scenarios (business as usual, BAU based, on the SSP2 and RCP 4.5 and a Green scenario, based on the SSP1 and the RCP 2.6). Exposure to land use is the magnitude of change from natural vegetation to anthropogenic covers while exposure to climate change is the difference between current and future values for both scenarios. Sensitivity was considered as the number of endemic species of terrestrial vertebrates which are critically endangered and endangered. Adaptive capacity is used as the ration between the percentage of converted area (natural to anthropogenic) and the percentage of protected area at municipality level. The results suggest that by 2050, between 11.6 and 13.9% of Mexico show vulnerability ≥ 50%, and by 2070, between 12.0 and 14.8%, in the Green and BAU scenario, respectively. From an ecosystem perspective cloud forests, followed by tropical dry forests, natural grasslands and temperate forests will be the most vulnerable (≥ 50%). Amphibians are the most threatened vertebrates; 62% of the endemic amphibians are critically endangered or endangered while 39%, 12% and 9% of the mammals, birds, and reptiles, respectively. However, the distribution of these amphibians counts for only 3.3% of the country, while mammals, birds, and reptiles in these categories represent 10%, 16% and 29% of Mexico. There are 5 municipalities out of the 2,457 that Mexico has that represent 31% of the most vulnerable areas (70%).These municipalities account for 0.05% of Mexico. This multiscale approach can be used to address resources to conservation targets as ecosystems, municipalities or species considering land use cover change, climate change and biodiversity uniqueness.

Keywords: biodiversity, climate change, land use change, Mexico, vulnerability

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Authors: Justin A. Udie, Subhes C. Bhatthacharyya, Leticia Ozawa-Meida

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The impact of climate change is severe in the Niger Delta and critical oil and gas infrastructures are vulnerable. This is partly due to lack of specific impact assessment framework to assess impact indices on both existing and new infrastructures. The purpose of this paper is to develop a framework for the assessment of climate change impact on critical oil and gas infrastructure in the region. Comparative and documentary methods as well as analysis of frameworks were used to develop a flexible, integrated and conceptual four dimensional framework underpinning; 1. Scoping – the theoretical identification of inherent climate burdens, review of exposure, adaptive capacities and delineation of critical infrastructure; 2. Vulnerability assessment – presents a systematic procedure for the assessment of infrastructure vulnerability. It provides real time re-scoping, practical need for data collection, analysis and review. Physical examination of systems is encouraged to complement the scoped data and ascertain the level of exposure to relevant climate risks in the area; 3. New infrastructure – consider infrastructures that are still at developmental level. It seeks to suggest the inclusion of flexible adaptive capacities in original design of infrastructures in line with climate threats and projections; 4. The Mainstreaming Climate Impact Assessment into government’s environmental decision making approach. Though this framework is designed specifically for the estimation of exposure, adaptive capacities and criticality of vulnerable oil and gas infrastructures in the Niger Delta to climate burdens; it is recommended for researchers and experts as a first-hand generic and practicable tool which can be used for the assessment of other infrastructures perceived as critical and vulnerable. The paper does not provide further tools that synch into the methodological approach but presents pointers upon which a pragmatic methodology can be developed.

Keywords: adaptation, assessment, conceptual, climate, change, framework, vulnerability

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Authors: Olena Mayboroda, Angel Gonzalez Benito, Jonathan Sabate Del Rio, Marketa Svobodova, Sandra Julich, Herbert Tomaso, Ciara K. O'Sullivan, Ioanis Katakis

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DNA amplification is required for most molecular diagnostic applications but conventional PCR has disadvantages for field testing. Isothermal amplification techniques are being developed to respond to this problem. One of them is the Recombinase Polymerase Amplification (RPA) that operates at isothermal conditions without sacrificing specificity and sensitivity in easy-to-use formats. In this work RPA was used for the optical detection of solid-phase amplification of the potential biowarfare agent Yersinia pestis. Thiolated forward primers were immobilized on the surface of maleimide-activated microtitre plates for the quantitative detection of synthetic and genomic DNA, with elongation occurring only in the presence of the specific template DNA and solution phase reverse primers. Quantitative detection was achieved via the use of biotinylated reverse primers and post-amplification addition of streptavidin-HRP conjugate. The overall time of amplification and detection was less than 1 hour at a constant temperature of 37oC. Single-stranded and double-stranded DNA sequences were detected achieving detection limits of 4.04*10-13 M and 3.14*10-16 M, respectively. The system demonstrated high specificity with negligible responses to non-specific targets.

Keywords: recombinase polymerase amplification, Yersinia pestis, solid-phase detection, ELONA

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Authors: A. Boulanoir, B. Ould Bouamama, A. Debiane, N. Achour

Abstract:

The paper deals with robust Fault Detection and isolation with respect to parameter uncertainties based on linear fractional transformation form (LFT) Bond graph. The innovative interest of the proposed methodology is the use only one representation for systematic generation of robust analytical redundancy relations and adaptive residual thresholds for sensibility analysis. Furthermore, the parameter uncertainties are introduced graphically in the bond graph model. The methodology applied to the nonlinear industrial Electro-Mechanical Actuators (EMA) used in avionic systems, has determined first the structural monitorability analysis (which component can be monitored) with given instrumentation architecture with any need of complex calculation and secondly robust fault indicators for online supervision.

Keywords: bond graph (BG), electro mechanical actuators (EMA), fault detection and isolation (FDI), linear fractional transformation (LFT), mechatronic systems, parameter uncertainties, avionic system

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Authors: Komal Babbar

Abstract:

Multiuser Detection is the intelligent estimation/demodulation of transmitted bits in the presence of Multiple Access Interference. The authors have presented the Bit-error rate (BER) achieved by linear multi-user detectors: Matched filter (which treats the MAI as AWGN), Decorrelating and MMSE. In this work, authors investigate the bit error probability analysis for Matched filter, decorrelating, and MMSE. This problem arises in several practical CDMA applications where the receiver may not have full knowledge of the number of active users and their signature sequences. In particular, the behavior of MAI at the output of the Multi-user detectors (MUD) is examined under various asymptotic conditions including large signal to noise ratio; large near-far ratios; and a large number of users. In the last section Authors also shows Matlab Simulation results for Multiuser detection techniques i.e., Matched filter, Decorrelating, MMSE for 2 users and 10 users.

Keywords: code division multiple access, decorrelating, matched filter, minimum mean square detection (MMSE) detection, multiple access interference (MAI), multiuser detection (MUD)

Procedia PDF Downloads 495