Search results for: thin layer chromatography-flame ionization detection

Authors: Edward K. Boahen, Brunel E. Bouya-Moko, Changda Wang

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The major threat to online social network (OSN) users is account compromisation. Spammers now spread malicious messages by exploiting the trust relationship established between account owners and their friends. The challenge in detecting a compromised account by service providers is validating the trusted relationship established between the account owners, their friends, and the spammers. Another challenge is the increase in required human interaction with the feature selection. Research available on supervised learning (machine learning) has limitations with the feature selection and accounts that cannot be profiled, like application programming interface (API). Therefore, this paper discusses the various behaviours of the OSN users and the current approaches in detecting a compromised OSN account, emphasizing its limitations and challenges. We propose a deep learning approach that addresses and resolve the constraints faced by the previous schemes. We detailed our proposed optimized nonsymmetric deep auto-encoder (OPT_NDAE) for unsupervised feature learning, which reduces the required human interaction levels in the selection and extraction of features. We evaluated our proposed classifier using the NSL-KDD and KDDCUP'99 datasets in a graphical user interface enabled Weka application. The results obtained indicate that our proposed approach outperformed most of the traditional schemes in OSN compromised account detection with an accuracy rate of 99.86%.

Keywords: computer security, network security, online social network, account compromisation

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Authors: Hendradi Hardhienata, Tony Sumaryada, Sri Setyaningsih

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Current progress in the field of nonlinear optics has enabled precise surface characterization in semiconductor materials. Nonlinear optical techniques are favorable due to their nondestructive measurement and ability to work in nonvacuum and ambient conditions. The advance of the bond hyperpolarizability models opens a wide range of nanoscale surface investigation including the possibility to detect molecular orientation at the surface of silicon and zincblende semiconductors, investigation of electric field induced second harmonic fields at the semiconductor interface, detection of surface impurities, and very recently, study surface defects such as twin boundary in wurtzite semiconductors. In this work, we show using nonlinear optical techniques, e.g. nonlinear bond models how arbitrary polarization of the incoming electric field in Rotational Anisotropy Spectroscopy experiments can provide more information regarding the origin of the nonlinear sources in zincblende and wurtzite semiconductor structure. In addition, using hyperpolarizability consideration, we describe how the nonlinear susceptibility tensor describing SHG can be well modelled using only few parameter because of the symmetry of the bonds. We also show how the third harmonic intensity feature shows considerable changes when the incoming field polarization angle is changed from s-polarized to p-polarized. We also propose a method how to investigate surface reconstruction and defects in wurtzite and zincblende structure at the nanoscale level.

Keywords: surface characterization, bond model, rotational anisotropy spectroscopy, effective hyperpolarizability

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Authors: Chetan Gupta, Ramesh Gupta

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Unmanned aerial vehicles, of all sizes, are prime targets of the wing morphing concept as their lightweight structures demand high aerodynamic stability while traversing unsteady atmospheric conditions. In this research study, a hybrid morphing technology is developed to aid the trailing edge of the aircraft wing to alter its camber as a monolithic element rather than functioning as conventional appendages like flaps. Kinematic tailoring, actuation techniques involving shape memory alloys (SMA), piezoelectrics – individually fall short of providing a simplistic solution to the conundrum of morphing aircraft wings. On the other hand, the feature of negligible hysteresis while actuating using compliant mechanisms has shown higher levels of applicability and deliverability in morphing wings of even large aircrafts. This research paper delves into designing a wing section model with a periodic, multi-stable compliant structure requiring lower orders of topological optimization. The design is sub-divided into three smaller domains with external hyperelastic connections to achieve deflections ranging from -15° to +15° at the trailing edge of the wing. To facilitate this functioning, a hybrid actuation system by combining the larger bandwidth feature of piezoelectric macro-fibre composites and relatively higher work densities of shape memory alloy wires are used. Finite element analysis is applied to optimize piezoelectric actuation of the internal compliant structure. A coupled fluid-surface interaction analysis is conducted on the wing section during morphing to study the development of the velocity boundary layer at low Reynold’s numbers of airflow.

Keywords: compliant mechanism, hybrid morphing, piezoelectrics, shape memory alloys

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Authors: Mohamed Ahmed Abdelmawla

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Calling to achieve Millennium Development Goals (MDGs) engaged with agriculture, i.e. poverty alleviation targets, human resources involved in agricultural sectors with special emphasis on irrigation must receive wealth of practical experience and training. Increased food production, including staple food, is needed to overcome the present and future threats to food security. This should happen within a framework of sustainable management of natural resources, elimination of unsustainable methods of production and poverty reduction (i.e. axes of modernization). A didactic tool to confirm the task of wise and maximum utility is the best management and accurate measurement, as major requisites for modernization process. The key component to modernization as a warranted goal is adhering great attention to management and measurement issues via capacity building. As such, this paper stressed the issues of discharge management and measurement by Field Outlet Pipes (FOP) for selected ones within the Gezira Scheme, where randomly nine FOPs were selected as representative locations. These FOPs extended along the Gezira Main Canal at Kilo 57 areas in the South up to Kilo 194 in the North. The following steps were followed during the field data collection and measurements: For each selected FOP, a 90 v- notch thin plate weir was placed in such away that the water was directed to pass only through the notch. An optical survey level was used to measure the water head of the notch and FOP. Both calculated discharge rates as measured by the v – notch, denoted as [Qc], and the adopted discharges given by (MOIWR), denoted as [Qa], are tackled for the average of three replicated readings undertaken at each location. The study revealed that the FOP overestimates and sometimes underestimates the discharges. This is attributed to the fact that the original design specifications were not fulfilled or met at present conditions where water is allowed to flow day and night with high head fluctuation, knowing that the FOP is non modular structure, i.e. the flow depends on both levels upstream and downstream and confirmed by the results of this study. It is convenient and formative to quantify the discharge in FOP with weirs or Parshall flumes. Cropping calendar should be clearly determined and agreed upon before the beginning of the season in accordance and consistency with the Sudan Gezira Board (SGB) and Ministry of Irrigation and Water Resources. As such, the water indenting should be based on actual Crop Water Requirements (CWRs), not on rules of thumb (420 m3/feddan, irrespective of crop or time of season).

Keywords: management, measurement, MDGs, modernization

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Authors: David Oluwole Moses, Odeyemi Adebowale Toba, Olawale Adetunji Kola

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Candida auris, an emerging fungus, has been reported in more than 30 countries around the world since its first detection in 2009. Due to its several virulence factors, resistance to antifungals, and persistence in hospital settings, Candida auris has been reported to cause treatment-failure infections. This study was therefore carried out to determine the incidence of Candida auris in a tertiary hospital in Ekiti State, Nigeria. In this study, a total of 115 samples were screened for Candida species using cultural and molecular methods. The carriage of virulence factors and antifungal resistance among C. auris was detected using standard microbiological methods. Candida species isolated from the samples were 15 (30.0%) in clinical samples and 22 (33.85%) in hospital equipment screened. Non-albicans Candida accounted for 3 (20%) and 8 (36.36%) among the isolates from the clinical samples and equipment, respectively. Only five of the non-albicans Candida isolates were C. auris. All the isolates produced biofilm, gelatinase, and hemolysin, while none produced germ tubes. Two of the isolates were resistant to all the antifungals tested. Also, all the isolates were resistant to fluconazole and itraconazole. Nystatin appeared to be the most effective among the tested antifungals. The isolation of Candida auris is being reported for the second time in Nigeria, further confirming that the fungus has spread beyond Lagos and Ibadan, where it was first reported. The extent of the spread of the nosocomial fungus needed to be further investigated and curtailed in Nigeria before its outbreak in healthcare facilities.

Keywords: candida auris, virulence factors, antifungals, pathogen, hospital, infection

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Authors: Othman M. Hakami, Abdul Jabbar Al-Rajab

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Occurrence of heavy metals in water resources increased in the recent years albeit at low concentrations. Lead (PbII) is among the most important inorganic pollutants in ground and surface water. However, removal of this toxic metal efficiently from water is of public and scientific concern. In this study, we developed a rapid and efficient removal method of lead from water using chitosan/magnetite nanoparticles. A simple and effective process has been used to prepare chitosan/magnetite nanoparticles (NPs) (CS/Mag NPs) with effect on saturation magnetization value; the particles were strongly responsive to an external magnetic field making separation from solution possible in less than 2 minutes using a permanent magnet and the total Fe in solution was below the detection limit of ICP-OES (<0.19 mg L-1). The hydrodynamic particle size distribution increased from an average diameter of ~60 nm for Fe3O4 NPs to ~75 nm after chitosan coating. The feasibility of the prepared NPs for the adsorption and desorption of Pb(II) from water were evaluated using Chitosan/Magnetite NPs which showed a high removal efficiency for Pb(II) uptake, with 90% of Pb(II) removed during the first 5 minutes and equilibrium in less than 10 minutes. Maximum adsorption capacities for Pb(II) occurred at pH 6.0 and under room temperature were as high as 85.5 mg g-1, according to Langmuir isotherm model. Desorption of adsorbed Pb on CS/Mag NPs was evaluated using deionized water at different pH values ranged from 1 to 7 which was an effective eluent and did not result the destruction of NPs, then, they could subsequently be reused without any loss of their activity in further adsorption tests. Overall, our results showed the high efficiency of chitosan/magnetite nanoparticles (NPs) in lead removal from water in controlled conditions, and further studies should be realized in real field conditions.

Keywords: chitosan, magnetite, water, treatment

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Authors: Jianghao Hu, Hongyu Wang

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The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

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Authors: Saad M. Darwish, Magda M. Madbouly, Murad B. Khorsheed

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Sign Languages (SL) are the most accomplished forms of gestural communication. Therefore, their automatic analysis is a real challenge, which is interestingly implied to their lexical and syntactic organization levels. Hidden Markov models (HMM’s) have been used prominently and successfully in speech recognition and, more recently, in handwriting recognition. Consequently, they seem ideal for visual recognition of complex, structured hand gestures such as are found in sign language. In this paper, several results concerning static hand gesture recognition using an algorithm based on Type-2 Fuzzy HMM (T2FHMM) are presented. The features used as observables in the training as well as in the recognition phases are based on Singular Value Decomposition (SVD). SVD is an extension of Eigen decomposition to suit non-square matrices to reduce multi attribute hand gesture data to feature vectors. SVD optimally exposes the geometric structure of a matrix. In our approach, we replace the basic HMM arithmetic operators by some adequate Type-2 fuzzy operators that permits us to relax the additive constraint of probability measures. Therefore, T2FHMMs are able to handle both random and fuzzy uncertainties existing universally in the sequential data. Experimental results show that T2FHMMs can effectively handle noise and dialect uncertainties in hand signals besides a better classification performance than the classical HMMs. The recognition rate of the proposed system is 100% for uniform hand images and 86.21% for cluttered hand images.

Keywords: hand gesture recognition, hand detection, type-2 fuzzy logic, hidden Markov Model

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Authors: Alokananda Ghosh, Shraban Sarkar

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The study aims to identify suitable sites for new hospitals with critical obstetric care facilities in Birbhum, one of the vulnerable and underserved districts of Eastern India, considering six main and 14 sub-criteria, using GIS-based Analytic Hierarchy Process (AHP) and Multi-Attribute Utility Theory (MAUT) approach. The criteria were identified through field surveys and previous literature. After collecting expert decisions, a pairwise comparison matrix was prepared using the Saaty scale to calculate the weights through AHP. On the contrary, objective weighting methods, i.e., Entropy and Criteria Importance through Interaction Correlation (CRITIC), were used to perform the MAUT. Finally, suitability maps were prepared by weighted sum analysis. Sensitivity analyses of AHP were performed to explore the effect of dominant criteria. Results from AHP reveal that ‘maternal death in transit’ followed by ‘accessibility and connectivity’, ‘maternal health care service (MHCS) coverage gap’ were three important criteria with comparatively higher weighted values. Whereas ‘accessibility and connectivity’ and ‘maternal death in transit’ were observed to have more imprint in entropy and CRITIC, respectively. While comparing the predictive suitable classes of these three models with the layer of existing hospitals, except Entropy-MAUT, the other two are pointing towards the left-over underserved areas of existing facilities. Only 43%-67% of existing hospitals were in the moderate to lower suitable class. Therefore, the results of the predictive models might bring valuable input in future planning.

Keywords: hospital site suitability, analytic hierarchy process, multi-attribute utility theory, entropy, criteria importance through interaction correlation, multi-criteria decision analysis

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Authors: Beng Yew Low, Cher Liang Cha, Cheng Yong Teoh

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Due to a lack of continual assessment or grade related data, identifying first-year engineering students in a polytechnic education at risk of failing is challenging. Our experience over the years tells us that there is no strong correlation between having good entry grades in Mathematics and the Sciences and excelling in hardcore engineering subjects. Hence, identifying students at risk of failure cannot be on the basis of entry grades in Mathematics and the Sciences alone. These factors compound the difficulty of early identification and intervention. This paper describes the development of a predictive analytics model in the early detection of students at risk of failing and evaluates its effectiveness. Data from continual assessments conducted in term one, supplemented by data of student psychological profiles such as interests and study habits, were used. Three classification techniques, namely Logistic Regression, K Nearest Neighbour, and Random Forest, were used in our predictive model. Based on our findings, Random Forest was determined to be the strongest predictor with an Area Under the Curve (AUC) value of 0.994. Correspondingly, the Accuracy, Precision, Recall, and F-Score were also highest among these three classifiers. Using this Random Forest Classification technique, students at risk of failure could be identified at the end of term one. They could then be assigned to a Learning Support Programme at the beginning of term two. This paper gathers the results of our findings. It also proposes further improvements that can be made to the model.

Keywords: continual assessment, predictive analytics, random forest, student psychological profile

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Authors: Maysoon Khalil Askar

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The delineation of possible areas of corrosion along the external face of an underground oil pipeline in Trunk line of Al- Garraf oil field was investigated using the horizontal electrical resistivity profiling technique and study the contribution of pH, Moisture Content in Soil and Presence chlorides, sulfates and total dissolve salts in soil and water. The test sites represent a physical and chemical properties of soils. The hydrogen-ion concentration of soil and groundwater range from 7.2 to 9.6, and the resistivity values of the soil along the pipeline were obtained using the YH302B model resistivity meter having values between 1588 and 720 Ohm-cm. the chloride concentration in soil and groundwater is high (more than 1000 ppm), total soulable salt is more than 5000 ppm, and sulphate range from 0.17% and 0.98% in soil and more than 600 ppm in groundwater. The soil is poor aeration, the soil texture is fine (clay and silt soil), the water content is high (the groundwater is close to surface), the chloride and sulphate is high in the soil and groundwater, the total soulable salt is high in ground water and finally the soil electric resistivity is low that the soil is very corrosive and there is the possibility of the pipeline failure. These methods applied in the study are quick, economic and efficient for detecting along buried pipelines which need to be protected. Routine electrical geophysical investigations along buried oil pipelines should be undertaken for the early detection and prevention of pipeline failure with its attendant environmental, human and economic consequences.

Keywords: soil resistivity, corrosion, cathodic protection, chloride concentration, water content

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Authors: B. Nageshwar Rao

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Urinary tract infection (UTI) represents the most commonly acquired bacterial infection worldwide, with substantial morbidity, mortality, and economic burden. The objective of the study is to characterize the microbial profiles of uropathogenic in the obstetric population by RTPCR. Study design: An observational cross-sectional study was performed at a single tertiary health care hospital among 50 pregnant women with UTIs, including asymptomatic and symptomatic patients attending the outpatient department and inpatient department of Obstetrics and Gynaecology.Methods: Serotyping and genes detection of various uropathogens were studied using RTPCR. Pulse filed gel electrophoresis methods were used to determine the various genetic profiles. Results: The present study shows that CsgD protein, involved in biofilm formation in Escherichia coli, VIM1, IMP1 genes for Klebsiella were identified by using the RTPCR method. Our results showed that the prevalence of VIM1 and IMP1 genes and CsgD protein in E.coli showed a significant relationship between strong biofilm formation, and this may be due to the prevalence of specific genes. Finally, the genetic identification of RTPCR results for both bacteria was correlated with each other and concluded that the above uropathogens were common isolates in producing Biofilm in the pregnant woman suffering from urinary tract infection in our hospital observational study.

Keywords: biofilms, Klebsiella, E.coli, urinary tract infection

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Authors: Yogesh Karunakar, Praveen Kandaswamy

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Mother’s milk provides the most superior source of nutrition to a child. There is no other substitute to the mother’s milk. Postpartum secretions like breast milk can be analyzed on the go for testing the presence of any harmful pathogen before a mother can feed the child or donate the milk for the milk bank. Since breast feeding is one of the main causes for transmission of diseases to the newborn, it is mandatory to test the secretions. In this paper, we describe the detection of pathogens like E-coli, Human Immunodeficiency Virus (HIV), Hepatitis B (HBV), Hepatitis C (HCV), Cytomegalovirus (CMV), Zika and Ebola virus through an innovative method, in which we are developing a unique chip for testing the mother’s milk sample. The chip will contain an antibody specific to the target pathogen that will show a color change if there are enough pathogens present in the fluid that will be considered dangerous. A smart-phone camera will then be acquiring the image of the strip and using various image processing techniques we will detect the color development due to antigen antibody interaction within 5 minutes, thereby not adding to any delay, before the newborn is fed or prior to the collection of the milk for the milk bank. If the target pathogen comes positive through this method, then the health care provider can provide adequate treatment to bring down the number of pathogens. This will reduce the postpartum related mortality and morbidity which arises due to feeding infectious breast milk to own child.

Keywords: postpartum, fluids, camera, HIV, HCV, CMV, Zika, Ebola, smart-phones, breast milk, pathogens, image processing techniques

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Authors: Behnaz Moradijamei, Michael Higgins

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Identifying community structure is a critical task in analyzing social media data sets often modeled by networks. Statistical models such as the stochastic block model have proven to explain the structure of communities in real-world network data. In this work, we develop a goodness-of-fit test to examine community structure's existence by using a distinguishing property in networks: cyclic structures are more prevalent within communities than across them. To better understand how communities are shaped by the cyclic structure of the network rather than just the number of edges, we introduce a novel method for deciding on the existence of communities. We utilize these structures by using renewal non-backtracking random walk (RNBRW) to the existing goodness-of-fit test. RNBRW is an important variant of random walk in which the walk is prohibited from returning back to a node in exactly two steps and terminates and restarts once it completes a cycle. We investigate the use of RNBRW to improve the performance of existing goodness-of-fit tests for community detection algorithms based on the spectral properties of the adjacency matrix. Our proposed test on community structure is based on the probability distribution of eigenvalues of the normalized retracing probability matrix derived by RNBRW. We attempt to make the best use of asymptotic results on such a distribution when there is no community structure, i.e., asymptotic distribution under the null hypothesis. Moreover, we provide a theoretical foundation for our statistic by obtaining the true mean and a tight lower bound for RNBRW edge weights variance.

Keywords: hypothesis testing, RNBRW, network inference, community structure

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Authors: Luca Collini, Michele Antolotti, Diego Schiavi

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At present, complex geometries within production time shrinkage, rapidly increasing demand, and high-quality standard requirement make the non-destructive (ND) control of additively manufactured components indispensable means. On the other hand, a technology gap and the lack of standards regulating the methods and the acceptance criteria indicate the NDT of these components a stimulating field to be still fully explored. Up to date, penetrant testing, acoustic wave, tomography, radiography, and semi-automated ultrasound methods have been tested on metal powder based products so far. External defects, distortion, surface porosity, roughness, texture, internal porosity, and inclusions are the typical defects in the focus of testing. Detection of density and layers compactness are also been tried on stainless steels by the ultrasonic scattering method. In this work, the authors want to present and discuss the radiographic and the ultrasound ND testing on additively manufactured Ti₆Al₄V and inconel parts obtained by the selective laser melting (SLM) technology. In order to test the possibilities given by the radiographic method, both X-Rays and γ-Rays are tried on a set of specifically designed specimens realized by the SLM. The specimens contain a family of defectology, which represent the most commonly found, as cracks and lack of fusion. The tests are also applied to real parts of various complexity and thickness. A set of practical indications and of acceptance criteria is finally drawn.

Keywords: non-destructive testing, selective laser melting, radiography, UT method

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Authors: Mustafa Taskin, Ozgur Demir, M. Mert Serveren

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The precise study of the impact of underwater explosions on structures is of great importance in the design and engineering calculations of floating structures, especially those used for military purposes, as well as power generation facilities such as offshore platforms that can become a target in case of war. Considering that ship and submarine structures are mostly curved surfaces, it is extremely important and interesting to examine the destructive effects of underwater explosions on curvilinear surfaces. In this study, geometric nonlinear dynamic analysis of cylindrical composite sandwich shells subjected to instantaneous pressure load is performed. The instantaneous pressure load is defined as an underwater explosion and the effects of the liquid medium are taken into account. There are equations in the literature for pressure due to underwater explosions, but these equations have been obtained for flat plates. For this reason, the instantaneous pressure load equations are arranged to be suitable for curvilinear structures before proceeding with the analyses. Fluid-solid interaction is defined by using Taylor's Plate Theory. The lower and upper layers of the cylindrical composite sandwich shell are modeled as composite laminate and the middle layer consists of soft core. The geometric nonlinear dynamic equations of the shell are obtained by Hamilton's principle, taken into account the von Kàrmàn theory of large displacements. Then, time dependent geometric nonlinear equations of motion are solved with the help of generalized differential quadrature method (GDQM) and dynamic behavior of cylindrical composite sandwich shells exposed to underwater explosion is investigated. An algorithm that can work parametrically for the solution has been developed within the scope of the study.

Keywords: cylindrical composite sandwich shells, generalized differential quadrature method, geometric nonlinear dynamic analysis, underwater explosion

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Authors: Sahar Ehsani, David James, Vernon Hodge

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In this experimental study, total selenium in solution was measured with Graphite Furnace Atomic Absorption Spectroscopy, GFAAS, then chemical reactions with sodium borohydride were used to reduce selenite to hydrogen selenide. Hydrogen selenide was then stripped from the solution by purging the solution with nitrogen gas. Since the two main speciations in oxic waters are usually selenite, Se(IV) and selenate, Se(VI), it was assumed that after Se(IV) is removed, the remaining total selenium was Se(VI). Total selenium measured after stripping gave Se(VI) concentration, and the difference of total selenium measured before and after stripping gave Se(IV) concentration. An additional step of reducing Se(VI) to Se(IV) was performed by boiling the stripped solution under acidic conditions, then removing Se(IV) by a chemical reaction with sodium borohydride. This additional procedure of removing Se(VI) from the solution is useful in rare cases where the water sample is reducing and contains selenide speciation. In this study, once Se(IV) and Se(VI) were both removed from the water sample, the remaining total selenium concentration was zero. The method was tested to determine Se(IV) and Se(VI) in both purified water and synthetic irrigation water spiked with Se(IV) and Se(VI). Average recovery of spiked samples of diluted synthetic irrigation water was 99% for Se(IV) and 97% for Se(VI). Detection limits of the method were 0.11 µg L⁻¹ and 0.32 µg L⁻¹ for Se(IV) and Se(VI), respectively.

Keywords: Analytical Method, Graphite Furnace Atomic Absorption Spectroscopy, Selenate, Selenite, Selenium Speciations

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Authors: Chris Neale, Jenny Roe, Peter Aspinall, Sara Tilley, Steve Cinderby, Panos Mavros, Richard Coyne, Neil Thin, Catharine Ward Thompson

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This research directly assesses older people’s neural activation in response to walking through a changing urban environment, as measured by electroencephalography (EEG). As the global urban population is predicted to grow, there is a need to understand the role that the urban environment may play on the health of its older inhabitants. There is a large body of evidence suggesting green space has a beneficial restorative effect, but this effect remains largely understudied in both older people and by using a neuroimaging assessment. For this study, participants aged 65 years and over were required to walk between a busy urban built environment and a green urban environment, in a counterbalanced design, wearing an Emotiv EEG headset to record real-time neural responses to place. Here we report on the outputs for these responses derived from both the proprietary Affectiv Suite software, which creates emotional parameters with a real time value assigned to them, as well as the raw EEG output focusing on alpha and beta changes, associated with changes in relaxation and attention respectively. Each walk lasted around fifteen minutes and was undertaken at the natural walking pace of the participant. The two walking environments were compared using a form of high dimensional correlated component regression (CCR) on difference data between the urban busy and urban green spaces. For the Emotiv parameters, results showed that levels of ‘engagement’ increased in the urban green space (with a subsequent decrease in the urban busy built space) whereas levels of ‘excitement’ increased in the urban busy environment (with a subsequent decrease in the urban green space). In the raw data, low beta (13 – 19 Hz) increased in the urban busy space with a subsequent decrease shown in the green space, similar to the pattern shown with the ‘excitement’ result. Alpha activity (9 – 13 Hz) shows a correlation with low beta, but not with dependent change in the regression model. This suggests that alpha is acting as a suppressor variable. These results suggest that there are neural signatures associated with the experience of urban spaces which may reflect the age of the cohort or the spatiality of the settings themselves. These are shown both in the outputs of the proprietary software as well as the raw EEG output. Built busy urban spaces appear to induce neural activity associated with vigilance and low level stress, while this effect is ameliorated in the urban green space, potentially suggesting a beneficial effect on attentional capacity in urban green space in this participant group. The interaction between low beta and alpha requires further investigation, in particular the role of alpha in this relationship.

Keywords: ageing, EEG, green space, urban space

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

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The assessment of disease levels in crop fields is an important and time-consuming task that generally relies on expert knowledge of trained individuals. Image classification in agriculture problems historically has been based on classical machine learning strategies that make use of hand-engineered features in the top of a classification algorithm. This approach tends to not produce results with high accuracy and generalization to the classes classified by the system when the nature of the elements has a significant variability. The advent of deep convolutional neural networks has revolutionized the field of machine learning, especially in computer vision tasks. These networks have great resourcefulness of learning and have been applied successfully to image classification and object detection tasks in the last years. The objective of this work was to propose a new method based on deep learning convolutional neural networks towards the task of disease level monitoring. Common RGB images of winter wheat were obtained during a growing season. Five categories of disease levels presence were produced, in collaboration with agronomists, for the algorithm classification. Disease level tasks performed by experts provided ground truth data for the disease score of the same winter wheat plots were RGB images were acquired. The system had an overall accuracy of 84% on the discrimination of the disease level classes.

Keywords: crop disease assessment, deep learning, precision agriculture, residual neural networks

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Authors: Jae-Il Jeong, Hoon-Jae Park, Jung-Woo Cho, Yang-Gon Kim, Jin-Young Park, Joo-Young Oh, Si-Geun Choi, Seock-Sam Kim, Young Tae Cho, Chan Gyu Kim, Jong-Hyoung Kim

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Bearing component has strongly required to decrease vibration and wear to achieve high durability and life time. In the industry field, bearing durability is improved by surface treatment on the bearing surface by centrifugal casting or gravity casting production method. However, this manufacturing method has caused problems such as long processing time, defect rate, and health harmful effect. To solve this problem, there is a laser cladding deposition treatment, which provides fast processing and food adhesion. Therefore, optimum conditions of white metal laser deposition should be studied to minimize bearing contact axis wear using laser cladding techniques. In this study, we deposit a soft white metal layer on SCM440, which is mainly used for shaft and bolt. On laser deposition process, the laser power and powder feed rate and laser head speed factors are controlled to find out the optimal conditions. We also measure hardness using micro Vickers, analyze FE-SEM (Field Emission Scanning Electron Microscope) and EDS (Energy Dispersive Spectroscopy) to study the mechanical properties and surface characteristics with various parameters change. Furthermore, this paper suggests the optimum condition of laser cladding deposition to apply in industrial fields. This work was supported by the Industrial Innovation Project of the Korea Evaluation Institute of Industrial Technology (KEIT) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (Research no. 10051653).

Keywords: laser deposition, bearing, white metal, mechanical properties

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Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: Mst Ilme Faridatul, Bo Wu

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Multi-temporal urban land cover mapping is of paramount importance for monitoring urban sprawl and managing the ecological environment. For diversified urban activities, it is challenging to map land covers in a complex urban environment. Spectral indices have proved to be effective for mapping urban land covers. To improve multi-temporal urban land cover classification and mapping, we evaluate the performance of three spectral indices, e.g. modified normalized difference bare-land index (MNDBI), tasseled cap water and vegetation index (TCWVI) and shadow index (ShDI). The MNDBI is developed to evaluate its performance of enhancing urban impervious areas by separating bare lands. A tasseled cap index, TCWVI is developed to evaluate its competence to detect vegetation and water simultaneously. The ShDI is developed to maximize the spectral difference between shadows of skyscrapers and water and enhance water detection. First, this paper presents a comparative analysis of three spectral indices using Landsat Enhanced Thematic Mapper (ETM), Thematic Mapper (TM) and Operational Land Imager (OLI) data. Second, optimized thresholds of the spectral indices are imputed to classify land covers, and finally, their performance of enhancing multi-temporal urban land cover mapping is assessed. The results indicate that the spectral indices are competent to enhance multi-temporal urban land cover mapping and achieves an overall classification accuracy of 93-96%.

Keywords: land cover, mapping, multi-temporal, spectral indices

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Authors: Arab M., Ait Abdallah M., Zeraoulia N., Boumaza H., Aoutia M., Griene L., Ait Abdelkader B.,

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breast and ovarian cancer are respectively the first and fourth leading causes of cancer among women in Algeria. A family story of cancer in the most important risk factor, and in most cases of families with breast and /or ovarian cancer, the pattern of cancer family can be attributed to mutation in BRCA1/2genes. objectibes: the aim of our study in to investigate the spectrum of BRCA1/2 germiline mutation in familial breast and /or ovarian cancer and to determine the prevalence and the nature of BRCA1/2mutation in Algeria methods: we deremined the prevalence of BRCA1/2 mutation within a cohort of 161 probands selected according the eisinger score double stranded sanger sequencing of all coding exons of BRCA1/2including flanking intronic region were performed results: we identified a total of 23 distinct deleterious mutations (class5) 12 differents mutations in BRCA1(52%) and 11 in BRCA2(48%). 78% (18/23) were protein truncating and 22%(5/23) missens mutations.3 novel deleterious mutations have been identified, which have not been described in public mutation database. one new mutation were found in two unrelated patients. the overall mutation detection rate in our study is 28,5%(46/161).more over, an UVS c7783 located in BRCA2 is found in two unrelated probands and segregate in the 02 families/ conclusion: our results sugget of large spectrum of BRCA1/2 mutation in Algerian breast/ovarian cancer family. The nature and prevalence of BRCA1/2mutation in algerian families are ongoing in a larger study, 80 probands are to day under investigation. This study which may therefore identify the genetic particularity of Algerian breast /ovarian cancer.

Keywords: BRCA1/2 mutations, hereditary breast cancer, algerian women, prvalence

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Authors: K. Sridhar Reddy, M. Amaranatha Reddy, Nilanjan Mitra

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Short paneled concrete pavement (SPCP) with shorter panel size can be an alternative to the conventional jointed plain concrete pavements (JPCP) at the same cost as the asphalt pavements with all the advantages of concrete pavement with reduced thickness, less chance of mid-slab cracking and or dowel bar locking so common in JPCP. Cast-in-situ short concrete panels (short slabs) laid on a strong foundation consisting of a dry lean concrete base (DLC), and cement treated subbase (CTSB) will reduce the thickness of the concrete slab to the order of 180 mm to 220 mm, whereas JPCP was with 280 mm for the same traffic. During the construction of SPCP test sections on two Indian National Highways (NH), it was observed that the joints remain uncracked after a year of traffic. The undoweled and uncracked joints load transfer variability and joint behavior are of interest with anticipation on its long-term performance of the SPCP. To investigate the effects of undoweled and uncracked joints on short slabs, the present study was conducted. A multilayer linear elastic analysis using 3D finite element package for different panel sizes with different thicknesses resting on different types of solid elastic foundation with and without temperature gradient was developed. Surface deflections were obtained from 3D FE model and validated with measured field deflections from falling weight deflectometer (FWD) test. Stress analysis indicates that flexural stresses in short slabs are decreased with a decrease in panel size and increase in thickness. Detailed evaluation of stress analysis with the effects of curling behavior, the stiffness of the base layer and a variable degree of load transfer, is underway.

Keywords: joint behavior, short slabs, uncracked joints, undoweled joints, 3D numerical simulation

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Authors: S. Zhang, L. Zhang, X. Chen

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Due to the large uncertainty on the mechanical properties of FRP (fibre reinforced plastic), the reliability evaluation of FRP structures are currently receiving much attention in industry. However, possible statistical correlation between ply mechanical properties has been so far overlooked, and they are mostly assumed to be independent random variables. In this study, the statistical correlation between ply mechanical properties of uni-directional and plain weave composite is firstly analyzed by a combination of Monte-Carlo simulation and finite element modeling of the FRP unit cell. Large linear correlation coefficients between the in-plane mechanical properties are observed, and the correlation coefficients are heavily dependent on the uncertainty of the fibre volume ratio. It is also observed that the correlation coefficients related to Poisson’s ratio are negative while others are positive. To experimentally achieve the statistical correlation coefficients between in-plane mechanical properties of FRP, all concerned in-plane mechanical properties of the same specimen needs to be known. In-plane shear modulus of FRP is experimentally derived by the approach suggested in the ASTM standard D5379M. Tensile tests are conducted using the same specimens used for the shear test, and due to non-uniform tensile deformation a modification factor is derived by a finite element modeling. Digital image correlation is adopted to characterize the specimen non-uniform deformation. The preliminary experimental results show a good agreement with the numerical analysis on the statistical correlation. Then, failure probability of laminate plates is calculated in cases considering and not considering the statistical correlation, using the Monte-Carlo and Markov Chain Monte-Carlo methods, respectively. The results highlight the importance of accounting for the statistical correlation between ply mechanical properties to achieve accurate failure probability of laminate plates. Furthermore, it is found that for the multi-layer laminate plate, the statistical correlation between the ply elastic properties significantly affects the laminate reliability while the effect of statistical correlation between the ply strength is minimal.

Keywords: failure probability, FRP, reliability, statistical correlation

Procedia PDF Downloads 153

Authors: Hong Li, Haiyang Yu, Shiqing Cheng, Nai Cao, Zhiliang Shi

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Unconventional resources have gradually become the main direction for oil and gas exploration and development. However, the productivity of gas wells, the level of water production, and the seepage law in tight fractured gas reservoirs are very different. These are the reasons why production prediction is so difficult. Firstly, a three-dimensional multi-scale fracture and multiphase mathematical model based on an embedded discrete fracture model (EDFM) is established. And the material balance method is used to calculate the water body multiple according to the production performance characteristics of water-producing gas well. This will help construct a 'virtual water body'. Based on these, this paper presents a numerical simulation process that can adapt to different production modes of gas wells. The research results show that fractures have a double-sided effect. The positive side is that it can increase the initial production capacity, but the negative side is that it can connect to the water body, which will lead to the gas production drop and the water production rise both rapidly, showing a 'scissor-like' characteristic. It is worth noting that fractures with different angles have different abilities to connect with the water body. The higher the angle of gas well development, the earlier the water maybe break through. When the reservoir is a single layer, there may be a stable production period without water before the fractures connect with the water body. Once connected, a 'scissors shape' will appear. If the reservoir has multiple layers, the gas and water will produce at the same time. The above gas-water relationship can be matched with the gas well production date of the Xujiahe gas reservoir in the Sichuan Basin. This method is used to predict the productivity of a well with hydraulic fractures in this gas reservoir, and the prediction results are in agreement with on-site production data by more than 90%. It shows that this research idea has great potential in the productivity prediction of water-producing gas wells. Early prediction results are of great significance to guide the design of development plans.

Keywords: EDFM, multiphase, multilayer, water body

Procedia PDF Downloads 185

Authors: A. Abdelnasser, M. Kumral, B. Zoheir, P. Weihed, M. Budakoglu, L. Gumus

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Atud gold deposits located at the central part of the Egyptian Eastern Desert of Egypt. It represents the vein-type gold mineralization at the Arabian-Nubian Shield in North Africa. Furthermore, this Au mineralization was closely associated with intense hydrothermal alteration haloes along the NW-SE brittle-ductile shear zone at the mined area. This study reports new data about the mineral chemistry of the hydrothermal and metamorphic minerals as well as the geothermobarometry of the metamorphism and determines the paragenetic interrelationship between Au-bearing sulfides and gangue minerals in Atud gold mine by using the electron microprobe analyses (EMPA). These analyses revealed that the ore minerals associated with gold mineralization are arsenopyrite, pyrite, chalcopyrite, sphalerite, pyrrhotite, tetrahedrite and gersdorffite-cobaltite. Also, the gold is highly associated with arsenopyrite and As-bearing pyrite as well as sphalerite with an average ~70 wt.% Au (+26 wt.% Ag) whereas it occurred either as disseminated grains or along microfractures of arsenopyrite and pyrite in altered wallrocks and mineralized quartz veins. Arsenopyrite occurs as individual rhombic or prismatic zoned grains disseminated in the quartz veins and wallrock and is intergrown with euhedral arsenian pyrite (with ~2 atom % As). Pyrite is As-bearing pyrite that occurs as disseminated subhedral or anhedral zoned grains replacing by chalcopyrite in some samples. Inclusions of sphalerite and pyrrhotite are common in the large pyrite grains. Secondary minerals such as sericite, calcite, chlorite and albite are disseminated either in altered wallrocks or in quartz veins. Sericite is the main secondary and alteration mineral associated with Au-bearing sulfides and calcite. Electron microprobe data of the sericite show that its muscovite component is high in all analyzed flakes (XMs= an average 0.89) and the phengite content (Mg+Fe a.p.f.u.) varies from 0.10 to 0.55 and from 0.13 to 0.29 in wallrocks and mineralized veins respectively. Carbonate occurs either as thin veinlets or disseminated grains in the mineralized quartz vein and/or the wallrocks. It has higher amount of calcite (CaCO3) and low amount of MgCO3 as well as FeCO3 in the wallrocks relative to the quartz veins. Chlorite flakes are associated with arsenopyrite and their electron probe data revealed that they are generally Fe-rich composition (FeOt 20.64–20.10 wt.%) and their composition is clinochlore either pycnochlorite or ripidolite with Al (iv) = 2.30-2.36 pfu and 2.41-2.51 pfu and with narrow range of estimated formation temperatures are (289–295°C) and (301-312°C) for pycnochlorite and ripidolite respectively. Albite is accompanied with chlorite with an Ab content is high in all analyzed samples (Ab= 95.08-99.20).

Keywords: micro-analytical data, mineral chemistry, EMPA, Atud gold deposit, Egypt

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Authors: Younes El Khchine, Mohammed Sriti

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A parametric study has been conducted to analyse the flow around S809 airfoil of a wind turbine in order to better understand the characteristics and effects of laminar separation bubble (LSB) on aerodynamic design for maximizing wind turbine efficiency. Numerical simulations were performed at low Reynolds numbers by solving the Unsteady Reynolds Averaged Navier-Stokes (URANS) equations based on C-type structural mesh and using the γ-Reθt turbulence model. A two-dimensional study was conducted for the chord Reynolds number of 1×10⁵ and angles of attack (AoA) between 0 and 20.15 degrees. The simulation results obtained for the aerodynamic coefficients at various angles of attack (AoA) were compared with XFoil results. A sensitivity study was performed to examine the effects of Reynolds number and free-stream turbulence intensity on the location and length of the laminar separation bubble and the aerodynamic performances of wind turbines. The results show that increasing the Reynolds number leads to a delay in the laminar separation on the upper surface of the airfoil. The increase in Reynolds number leads to an accelerated transition process, and the turbulent reattachment point moves closer to the leading edge owing to an earlier reattachment of the turbulent shear layer. This leads to a considerable reduction in the length of the separation bubble as the Reynolds number is increased. The increase in the level of free-stream turbulence intensity leads to a decrease in separation bubble length and an increase in the lift coefficient while having negligible effects on the stall angle. When the AoA increased, the bubble on the suction airfoil surface was found to move upstream to the leading edge of the airfoil, that causes earlier laminar separation.

Keywords: laminar separation bubble, turbulence intensity, S809 airfoil, transition model, Reynolds number

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Authors: Vishal V. R. Nandigana, Mohammad Heiranian, Narayana R. Aluru

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Graphene material has found tremendous applications in water desalination, DNA sequencing and energy storage. Multiple nanopores are etched to create opening for water desalination and energy storage applications. The nanopores created are of the order of 3-5 nm allowing multiple ions to transport through the pore. In this paper, we present for the first time, molecular dynamics study of single ion transport, where only one ion passes through the graphene nanopore. The diameter of the graphene nanopore is of the same order as the hydration layers formed around each ion. Analogous to single electron transport resulting from ionic transport is observed for the first time. The current-voltage characteristics of such a device are similar to single electron transport in quantum dots. The current is blocked until a critical voltage, as the ions are trapped inside a hydration shell. The trapped ions have a high energy barrier compared to the applied input electrical voltage, preventing the ion to break free from the hydration shell. This region is called “Coulomb blockade region”. In this region, we observe zero transport of ions inside the nanopore. However, when the electrical voltage is beyond the critical voltage, the ion has sufficient energy to break free from the energy barrier created by the hydration shell to enter into the pore. Thus, the input voltage can control the transport of the ion inside the nanopore. The device therefore acts as a binary storage unit, storing 0 when no ion passes through the pore and storing 1 when a single ion passes through the pore. We therefore postulate that the device can be used for fluidic computing applications in chemistry and biology, mimicking a computer. Furthermore, the trapped ion stores a finite charge in the Coulomb blockade region; hence the device also acts a super capacitor.

Keywords: graphene nanomembrane, single ion transport, Coulomb blockade, nanofluidics

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Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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