Search results for: channel estimation
Commenced in January 2007
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Edition: International
Paper Count: 3043

Search results for: channel estimation

133 A Versatile Data Processing Package for Ground-Based Synthetic Aperture Radar Deformation Monitoring

Authors: Zheng Wang, Zhenhong Li, Jon Mills

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Ground-based synthetic aperture radar (GBSAR) represents a powerful remote sensing tool for deformation monitoring towards various geohazards, e.g. landslides, mudflows, avalanches, infrastructure failures, and the subsidence of residential areas. Unlike spaceborne SAR with a fixed revisit period, GBSAR data can be acquired with an adjustable temporal resolution through either continuous or discontinuous operation. However, challenges arise from processing high temporal-resolution continuous GBSAR data, including the extreme cost of computational random-access-memory (RAM), the delay of displacement maps, and the loss of temporal evolution. Moreover, repositioning errors between discontinuous campaigns impede the accurate measurement of surface displacements. Therefore, a versatile package with two complete chains is developed in this study in order to process both continuous and discontinuous GBSAR data and address the aforementioned issues. The first chain is based on a small-baseline subset concept and it processes continuous GBSAR images unit by unit. Images within a window form a basic unit. By taking this strategy, the RAM requirement is reduced to only one unit of images and the chain can theoretically process an infinite number of images. The evolution of surface displacements can be detected as it keeps temporarily-coherent pixels which are present only in some certain units but not in the whole observation period. The chain supports real-time processing of the continuous data and the delay of creating displacement maps can be shortened without waiting for the entire dataset. The other chain aims to measure deformation between discontinuous campaigns. Temporal averaging is carried out on a stack of images in a single campaign in order to improve the signal-to-noise ratio of discontinuous data and minimise the loss of coherence. The temporal-averaged images are then processed by a particular interferometry procedure integrated with advanced interferometric SAR algorithms such as robust coherence estimation, non-local filtering, and selection of partially-coherent pixels. Experiments are conducted using both synthetic and real-world GBSAR data. Displacement time series at the level of a few sub-millimetres are achieved in several applications (e.g. a coastal cliff, a sand dune, a bridge, and a residential area), indicating the feasibility of the developed GBSAR data processing package for deformation monitoring of a wide range of scientific and practical applications.

Keywords: ground-based synthetic aperture radar, interferometry, small baseline subset algorithm, deformation monitoring

Procedia PDF Downloads 134
132 Regional Disparities in Microfinance Distribution: Evidence from Indian States

Authors: Sunil Sangwan, Narayan Chandra Nayak

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Over the last few decades, Indian banking system has achieved remarkable growth in its credit volume. However, one of the most disturbing facts about this growth is the uneven distribution of financial services across regions. Having witnessed limited success from all the earlier efforts towards financial inclusion targeting the rural poor and the underprivileged, provision of microfinance, of late, has emerged as a supplementary mechanism. There are two prominent modes of microfinance distribution in India namely Bank-SHG linkage (SBLP) and private Microfinance Institutions (MFIs). Ironically, such efforts also seem to have failed to achieve the desired targets as the microfinance services have witnessed skewed distribution across the states of the country. This study attempts to make a comparative analysis of the geographical skew of the SBLP and MFI in India and examine the factors influencing their regional distribution. The results indicate that microfinance services are largely concentrated in the southern region, accounting for about 50% of all microfinance clients and 49% of all microfinance loan portfolios. This is distantly followed by an eastern region where client outreach is close to 25% only. The north-eastern, northern, central, and western regions lag far behind in microfinance sectors, accounting for only 4%, 4%, 10%, and 7 % client outreach respectively. The penetration of SHGs is equally skewed, with the southern region accounting for 46% of client outreach and 70% of loan portfolios followed by an eastern region with 21% of client outreach and 13% of the loan portfolio. Contrarily, north-eastern, northern, central, western and eastern regions account for 5%, 5%, 10%, and 13% of client outreach and 3%, 3%, 7%, and 4% of loan portfolios respectively. The study examines the impact of literacy rate, rural poverty, population density, primary sector share, non-farm activities, loan default behavior and bank penetration on the microfinance penetration. The study is limited to 17 major states of the country over the period 2008-2014. The results of the GMM estimation indicate the significant positive impact of literacy rate, non-farm activities and population density on microfinance penetration across the states, while the rise in loan default seems to deter it. Rural poverty shows the significant negative impact on the spread of SBLP, while it has a positive impact on MFI penetration, hence indicating the policy of exclusion being adhered to by the formal financial system especially towards the poor. However, MFIs seem to be working as substitute mechanisms to banks to fill the gap. The findings of the study are a pointer towards enhancing financial literacy, non-farm activities, rural bank penetration and containing loan default for achieving greater microfinance prevalence.

Keywords: bank penetration, literacy rate, microfinance, primary sector share, rural non-farm activities, rural poverty

Procedia PDF Downloads 211
131 Lean Comic GAN (LC-GAN): a Light-Weight GAN Architecture Leveraging Factorized Convolution and Teacher Forcing Distillation Style Loss Aimed to Capture Two Dimensional Animated Filtered Still Shots Using Mobile Phone Camera and Edge Devices

Authors: Kaustav Mukherjee

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In this paper we propose a Neural Style Transfer solution whereby we have created a Lightweight Separable Convolution Kernel Based GAN Architecture (SC-GAN) which will very useful for designing filter for Mobile Phone Cameras and also Edge Devices which will convert any image to its 2D ANIMATED COMIC STYLE Movies like HEMAN, SUPERMAN, JUNGLE-BOOK. This will help the 2D animation artist by relieving to create new characters from real life person's images without having to go for endless hours of manual labour drawing each and every pose of a cartoon. It can even be used to create scenes from real life images.This will reduce a huge amount of turn around time to make 2D animated movies and decrease cost in terms of manpower and time. In addition to that being extreme light-weight it can be used as camera filters capable of taking Comic Style Shots using mobile phone camera or edge device cameras like Raspberry Pi 4,NVIDIA Jetson NANO etc. Existing Methods like CartoonGAN with the model size close to 170 MB is too heavy weight for mobile phones and edge devices due to their scarcity in resources. Compared to the current state of the art our proposed method which has a total model size of 31 MB which clearly makes it ideal and ultra-efficient for designing of camera filters on low resource devices like mobile phones, tablets and edge devices running OS or RTOS. .Owing to use of high resolution input and usage of bigger convolution kernel size it produces richer resolution Comic-Style Pictures implementation with 6 times lesser number of parameters and with just 25 extra epoch trained on a dataset of less than 1000 which breaks the myth that all GAN need mammoth amount of data. Our network reduces the density of the Gan architecture by using Depthwise Separable Convolution which does the convolution operation on each of the RGB channels separately then we use a Point-Wise Convolution to bring back the network into required channel number using 1 by 1 kernel.This reduces the number of parameters substantially and makes it extreme light-weight and suitable for mobile phones and edge devices. The architecture mentioned in the present paper make use of Parameterised Batch Normalization Goodfellow etc al. (Deep Learning OPTIMIZATION FOR TRAINING DEEP MODELS page 320) which makes the network to use the advantage of Batch Norm for easier training while maintaining the non-linear feature capture by inducing the learnable parameters

Keywords: comic stylisation from camera image using GAN, creating 2D animated movie style custom stickers from images, depth-wise separable convolutional neural network for light-weight GAN architecture for EDGE devices, GAN architecture for 2D animated cartoonizing neural style, neural style transfer for edge, model distilation, perceptual loss

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130 Comparative Vector Susceptibility for Dengue Virus and Their Co-Infection in A. aegypti and A. albopictus

Authors: Monika Soni, Chandra Bhattacharya, Siraj Ahmed Ahmed, Prafulla Dutta

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Dengue is now a globally important arboviral disease. Extensive vector surveillance has already established A.aegypti as a primary vector, but A.albopictus is now accelerating the situation through gradual adaptation to human surroundings. Global destabilization and gradual climatic shift with rising in temperature have significantly expanded the geographic range of these species These versatile vectors also host Chikungunya, Zika, and yellow fever virus. Biggest challenge faced by endemic countries now is upsurge in co-infection reported with multiple serotypes and virus co-circulation. To foster vector control interventions and mitigate disease burden, there is surge for knowledge on vector susceptibility and viral tolerance in response to multiple infections. To address our understanding on transmission dynamics and reproductive fitness, both the vectors were exposed to single and dual combinations of all four dengue serotypes by artificial feeding and followed up to third generation. Artificial feeding observed significant difference in feeding rate for both the species where A.albopictus was poor artificial feeder (35-50%) compared to A.aegypti (95-97%) Robust sequential screening of viral antigen in mosquitoes was followed by Dengue NS1 ELISA, RT-PCR and Quantitative PCR. To observe viral dissemination in different mosquito tissues Indirect immunofluorescence assay was performed. Result showed that both the vectors were infected initially with all dengue(1-4)serotypes and its co-infection (D1 and D2, D1 and D3, D1 and D4, D2 and D4) combinations. In case of DENV-2 there was significant difference in the peak titer observed at 16th day post infection. But when exposed to dual infections A.aegypti supported all combinations of virus where A.albopictus only continued single infections in successive days. There was a significant negative effect on the fecundity and fertility of both the vectors compared to control (PANOVA < 0.001). In case of dengue 2 infected mosquito, fecundity in parent generation was significantly higher (PBonferroni < 0.001) for A.albopicus compare to A.aegypti but there was a complete loss of fecundity from second to third generation for A.albopictus. It was observed that A.aegypti becomes infected with multiple serotypes frequently even at low viral titres compared to A.albopictus. Possible reason for this could be the presence of wolbachia infection in A.albopictus or mosquito innate immune response, small RNA interference etc. Based on the observations it could be anticipated that transovarial transmission may not be an important phenomenon for clinical disease outcome, due to the absence of viral positivity by third generation. Also, Dengue NS1 ELISA can be used for preliminary viral detection in mosquitoes as more than 90% of the samples were found positive compared to RT-PCR and viral load estimation.

Keywords: co-infection, dengue, reproductive fitness, viral quantification

Procedia PDF Downloads 178
129 Soybean Seed Composition Prediction From Standing Crops Using Planet Scope Satellite Imagery and Machine Learning

Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

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128 Religious Capital and Entrepreneurial Behavior in Small Businesses: The Importance of Entrepreneurial Creativity

Authors: Waleed Omri

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With the growth of the small business sector in emerging markets, developing a better understanding of what drives 'day-to-day' entrepreneurial activities has become an important issue for academicians and practitioners. Innovation, as an entrepreneurial behavior, revolves around individuals who creatively engage in new organizational efforts. In a similar vein, the innovation behaviors and processes at the organizational member level are central to any corporate entrepreneurship strategy. Despite the broadly acknowledged importance of entrepreneurship and innovation at the individual level in the establishment of successful ventures, the literature lacks evidence on how entrepreneurs can effectively harness their skills and knowledge in the workplace. The existing literature illustrates that religion can impact the day-to-day work behavior of entrepreneurs, managers, and employees. Religious beliefs and practices could affect daily entrepreneurial activities by fostering mental abilities and traits such as creativity, intelligence, and self-efficacy. In the present study, we define religious capital as a set of personal and intangible resources, skills, and competencies that emanate from an individual’s religious values, beliefs, practices, and experiences and may be used to increase the quality of economic activities. Religious beliefs and practices give individuals a religious satisfaction, which can lead them to perform better in the workplace. In addition, religious ethics and practices have been linked to various positive employee outcomes in terms of organizational change, job satisfaction, and entrepreneurial intensity. As investigations of their consequences beyond direct task performance are still scarce, we explore if religious capital plays a role in entrepreneurs’ innovative behavior. In sum, this study explores the determinants of individual entrepreneurial behavior by investigating the relationship between religious capital and entrepreneurs’ innovative behavior in the context of small businesses. To further explain and clarify the religious capital-innovative behavior link, the present study proposes a model to examine the mediating role of entrepreneurial creativity. We use both Islamic work ethics (IWE) and Islamic religious practices (IRP) to measure Islamic religious capital. We use structural equation modeling with a robust maximum likelihood estimation to analyze data gathered from 289 Tunisian small businesses and to explore the relationships among the above-described variables. In line with the theory of planned behavior, only religious work ethics are found to increase the innovative behavior of small businesses’ owner-managers. Our findings also clearly demonstrate that the connection between religious capital-related variables and innovative behavior is better understood if the influence of entrepreneurial creativity, as a mediating variable of the aforementioned relationship, is taken into account. By incorporating both religious capital and entrepreneurial creativity into the innovative behavior analysis, this study provides several important practical implications for promoting innovation process in small businesses.

Keywords: entrepreneurial behavior, small business, religion, creativity

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127 Effect of Vitrification on Embryos Euploidy Obtained from Thawed Oocytes

Authors: Natalia Buderatskaya, Igor Ilyin, Julia Gontar, Sergey Lavrynenko, Olga Parnitskaya, Ekaterina Ilyina, Eduard Kapustin, Yana Lakhno

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Introduction: It is known that cryopreservation of oocytes has peculiar features due to the complex structure of the oocyte. One of the most important features is that mature oocytes contain meiotic division spindle which is very sensitive even to the slightest variation in temperature. Thus, the main objective of this study is to analyse the resulting euploid embryos obtained from thawed oocytes in comparison with the data of preimplantation genetic screening (PGS) in fresh embryo cycles. Material and Methods: The study was conducted at 'Medical Centre IGR' from January to July 2016. Data were analysed for 908 donor oocytes obtained in 67 cycles of assisted reproductive technologies (ART), of which 693 oocytes were used in the 51 'fresh' cycles (group A), and 215 oocytes - 16 ART programs with vitrification female gametes (group B). The average age of donors in the groups match 27.3±2.9 and 27.8±6.6 years. Stimulation of superovulation was conducted the standard way. Vitrification was performed in 1-2 hours after transvaginal puncture and thawing of oocytes were carried out in accordance with the standard protocol of Cryotech (Japan). Manipulation ICSI was performed 4-5 hours after transvaginal follicle puncture for fresh oocytes, or after defrosting - for vitrified female gametes. For the PGS, an embryonic biopsy was done on the third or on the fifth day after fertilization. Diagnostic procedures were performed using fluorescence in situ hybridization with the study of such chromosomes as 13, 16, 18, 21, 22, X, Y. Only morphologically quality blastocysts were used for the transfer, the estimation of which corresponded to the Gardner criteria. The statistical hypotheses were done using the criteria t, x^2 at a significance levels p<0.05, p<0.01, p<0.001. Results: The mean number of mature oocytes per cycle in group A was 13.58±6.65 and in group B - 13.44±6.68 oocytes for patient. The survival of oocytes after thawing totaled 95.3% (n=205), which indicates a highly effective quality of performed vitrification. The proportion of zygotes in the group A corresponded to 91.1%(n=631), in the group B – 80.5%(n=165), which shows statistically significant difference between the groups (p<0.001) and explained by non-viable oocytes elimination after vitrification. This is confirmed by the fact that on the fifth day of embryos development a statistically significant difference in the number of blastocysts was absent (p>0.05), and constituted respectively 61.6%(n=389) and 63.0%(n=104) in the groups. For the PGS performing 250 embryos analyzed in the group A and 72 embryos - in the group B. The results showed that euploidy in the studied chromosomes were 40.0%(n=100) embryos in the group A and 41.7% (n=30) - in the group B, which shows no statistical significant difference (p>0.05). The indicators of clinical pregnancies in the groups amounted to 64.7% (22 pregnancies per 34 embryo transfers) and 61.5% (8 pregnancies per 13 embryo transfers) respectively, and also had no significant difference between the groups (p>0.05). Conclusions: The results showed that the vitrification does not affect the resulting euploid embryos in assisted reproductive technologies and are not reflected in their morphological characteristics in ART programs.

Keywords: euploid embryos, preimplantation genetic screening, thawing oocytes, vitrification

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126 Correlation Between Different Radiological Findings and Histopathological diagnosis of Breast Diseases: Retrospective Review Conducted Over Sixth Years in King Fahad University Hospital in Eastern Province, Saudi Arabia

Authors: Sadeem Aljamaan, Reem Hariri, Rahaf Alghamdi, Batool Alotaibi, Batool Alsenan, Lama Althunayyan, Areej Alnemer

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The aim of this study is to correlate between radiological findings and histopathological results in regard to the breast imaging-reporting and data system scores, size of breast masses, molecular subtypes and suspicious radiological features, as well as to assess the concordance rate in histological grade between core biopsy and surgical excision among breast cancer patients, followed by analyzing the change of concordance rate in relation to neoadjuvant chemotherapy in a Saudi population. A retrospective review was conducted over 6-year period (2017-2022) on all breast core biopsies of women preceded by radiological investigation. Chi-squared test (χ2) was performed on qualitative data, the Mann-Whitney test for quantitative non-parametric variables, and the Kappa test for grade agreement. A total of 641 cases were included. Ultrasound, mammography, and magnetic resonance imaging demonstrated diagnostic accuracies of 85%, 77.9% and 86.9%; respectively. magnetic resonance imaging manifested the highest sensitivity (72.2%), and the lowest was for ultrasound (61%). Concordance in tumor size with final excisions was best in magnetic resonance imaging, while mammography demonstrated a higher tendency of overestimation (41.9%), and ultrasound showed the highest underestimation (67.7%). The association between basal-like molecular subtypes and the breast imaging-reporting and data system score 5 classifications was statistically significant only for magnetic resonance imaging (p=0.04). Luminal subtypes demonstrated a significantly higher percentage of speculation in mammography. Breast imaging-reporting and data system score 4 manifested a substantial number of benign pathologies in all the 3 modalities. A fair concordance rate (k= 0.212 & 0.379) was demonstrated between excision and the preceding core biopsy grading with and without neoadjuvant therapy, respectively. The results demonstrated a down-grading in cases post-neoadjuvant therapy. In cases who did not receive neoadjuvant therapy, underestimation of tumor grade in biopsy was evident. In summary, magnetic resonance imaging had the highest sensitivity, specificity, positive predictive value and accuracy of both diagnosis and estimation of tumor size. Mammography demonstrated better sensitivity than ultrasound and had the highest negative predictive value, but ultrasound had better specificity, positive predictive value and accuracy. Therefore, the combination of different modalities is advantageous. The concordance rate of core biopsy grading with excision was not impacted by neoadjuvant therapy.

Keywords: breast cancer, mammography, MRI, neoadjuvant, pathology, US

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125 Coming Closer to Communities of Practice through Situated Learning: The Case Study of Polish-English, English-Polish Undergraduate BA Level Language for Specific Purposes of Translation Class

Authors: Marta Lisowska

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The growing trend of market specialization imposes upon translators the need for proficiency in the working knowledge of specialist discourse. The notion of specialization differs from a broad general category to a highly specialized narrow field. The specialised discourse is used in the channel of communication based upon distinctive features typical for communities of practice whose co-existence is codified and hermetically locked against outsiders. Consequently, any translator deprived of professional discourse competence and social skills is incapable of providing competent translation product from source language into target language. In this paper, we report on research that explores the pedagogical practices aiming to bridge the dichotomy between the professionals and the specialist translators, while accounting for the reality of the world of professional communities entered by undergraduates on two levels: the text-based generic, and the social one. Drawing from the functional social constructivist approach, seen here as situated learning, this paper reports on the case of English-Polish, Polish-English undergraduate BA Level LSP of law translation class run in line with the simulated classroom-based and the reality-based (apprenticeship) approach. This blended method serves the purpose of introducing the young trainees to the professional world. The research provides new insights into how the LSP translation undergraduates become legitimized through discursive and social participation and engagement. The undergraduates, situated peripherally at the outset, experience their own transformation towards becoming members of these professional groups. With subjective evaluation, the trainees take a stance on this dual mode class and development of their skills. Comparing and contrasting their own work done in line with two models of translation teaching: authentic and near-authentic, the undergraduates answer research questions devised by a questionnaire survey The responses take us closer to how students feel about their LSP translation competence development. The major findings show how the trainees perceive the benefits and hardships of their functional translation class. In terms of skills, they related to communication as the most enhanced one; they highly valued the fact of being ‘exposed’ to a variety of texts (cf. multi literalism), team work, learning how to schedule work, IT skills boost and the ability to learn how to work individually. Another finding indicates that students struggled most with specialized language, and co-working with other students. The short-term research shows the momentum when the undergraduate LSP translation trainees entered the path of transformation i.e. gained consciousness of ‘how it is’ to be a participant-translator of real-life communities of practice, gaining pragmatic dint of the social and linguistic skills understood here as discursive competence (text > genre > discourse > professional practice). The undergraduates need to be aware of the work they have to do and challenges they are to face before arriving at the expert level of professional translation competence.

Keywords: communities of practice in LSP translation teaching, learning LSP translation as situated experience, peripheral participation, professional discourse for LSP translation teaching, professional translation competence

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124 DSF Elements in High-Rise Timber Buildings

Authors: Miroslav Premrov, Andrej Štrukelj, Erika Kozem Šilih

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The utilization of prefabricated timber-wall elements with double glazing, called as double-skin façade element (DSF), represents an innovative structural approach in the context of new high-rise timber construction, simultaneously combining sustainable solutions with improved energy efficiency and living quality. In addition to the minimum energy needs of buildings, the design of modern buildings is also increasingly focused on the optimal indoor comfort, in particular on sufficient natural light indoors. An optimally energy-designed building with an optimal layout of glazed areas around the building envelope represents a great potential in modern timber construction. Usually, all these transparent façade elements, because of energy benefits, are primary asymmetrical oriented and if they are considered as non-resisting against a horizontal load impact, a strong torsion effects in the building can appear. The problem of structural stability against a strong horizontal load impact of such modern timber buildings especially increase in a case of high-rise structures where additional bracing elements have to be used. In such a case, special diagonal bracing systems or other bracing solutions with common timber wall elements have to be incorporated into the structure of the building to satisfy all prescribed resisting requirements given by the standards. However, all such structural solutions are usually not environmentally friendly and also not contribute to an improved living comfort, or they are not accepted by the architects at all. Consequently, it is a special need to develop innovative load-bearing timber-glass wall elements which are in the same time environmentally friendly, can increase internal comfort in the building, but are also load-bearing. The new developed load-bearing DSF elements can be a good answer on all these requirements. Timber-glass façade elements DSF wall elements consist of two transparent layers, thermal-insulated three-layered glass pane on the internal side and an additional single-layered glass pane on the external side of the wall. The both panes are separated by an air channel which can be of any dimensions and can have a significant influence on the thermal insulation or acoustic response of such a wall element. Most already published studies on DSF elements primarily deal only with energy and LCA solutions and do not address any structural problems. In previous studies according to experimental analysis and mathematical modeling it was already presented a possible benefit of such load-bearing DSF elements, especially comparing with previously developed load-bearing single-skin timber wall elements, but they were not applicate yet in any high-rise timber structure. Therefore, in the presented study specially selected 10-storey prefabricated timber building constructed in a cross-laminated timber (CLT) structural wall system is analyzed using the developed DSF elements in a sense to increase a structural lateral stability of the whole building. The results evidently highlight the importance the load-bearing DSF elements, as their incorporation can have a significant impact on the overall behavior of the structure through their influence on the stiffness properties. Taking these considerations into account is crucial to ensure compliance with seismic design codes and to improve the structural resilience of high-rise timber buildings.

Keywords: glass, high-rise buildings, numerical analysis, timber

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123 Hydraulic Headloss in Plastic Drainage Pipes at Full and Partially Full Flow

Authors: Velitchko G. Tzatchkov, Petronilo E. Cortes-Mejia, J. Manuel Rodriguez-Varela, Jesus Figueroa-Vazquez

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Hydraulic headloss, expressed by the values of friction factor f and Manning’s coefficient n, is an important parameter in designing drainage pipes. Their values normally are taken from manufacturer recommendations, many times without sufficient experimental support. To our knowledge, currently there is no standard procedure for hydraulically testing such pipes. As a result of research carried out at the Mexican Institute of Water Technology, a laboratory testing procedure was proposed and applied on 6 and 12 inches diameter polyvinyl chloride (PVC) and high-density dual wall polyethylene pipe (HDPE) drainage pipes. While the PVC pipe is characterized by naturally smooth interior and exterior walls, the dual wall HDPE pipe has corrugated exterior wall and, although considered smooth, a slightly wavy interior wall. The pipes were tested at full and partially full pipe flow conditions. The tests for full pipe flow were carried out on a 31.47 m long pipe at flow velocities between 0.11 and 4.61 m/s. Water was supplied by gravity from a 10 m-high tank in some of the tests, and from a 3.20 m-high tank in the rest of the tests. Pressure was measured independently with piezometer readings and pressure transducers. The flow rate was measured by an ultrasonic meter. For the partially full pipe flow the pipe was placed inside an existing 49.63 m long zero slope (horizontal) channel. The flow depth was measured by piezometers located along the pipe, for flow rates between 2.84 and 35.65 L/s, measured by a rectangular weir. The observed flow profiles were then compared to computer generated theoretical gradually varied flow profiles for different Manning’s n values. It was found that Manning’s n, that normally is assumed constant for a given pipe material, is in fact dependent on flow velocity and pipe diameter for full pipe flow, and on flow depth for partially full pipe flow. Contrary to the expected higher values of n and f for the HDPE pipe, virtually the same values were obtained for the smooth interior wall PVC pipe and the slightly wavy interior wall HDPE pipe. The explanation of this fact was found in Henry Morris’ theory for smooth turbulent conduit flow over isolated roughness elements. Following Morris, three categories of the flow regimes are possible in a rough conduit: isolated roughness (or semi smooth turbulent) flow, wake interference (or hyper turbulent) flow, and skimming (or quasi-smooth) flow. Isolated roughness flow is characterized by friction drag turbulence over the wall between the roughness elements, independent vortex generation, and dissipation around each roughness element. In this regime, the wake and vortex generation zones at each element develop and dissipate before attaining the next element. The longitudinal spacing of the roughness elements and their height are important influencing agents. Given the slightly wavy form of the HDPE pipe interior wall, the flow for this type of pipe belongs to this category. Based on that theory, an equation for the hydraulic friction factor was obtained. The obtained coefficient values are going to be used in the Mexican design standards.

Keywords: drainage plastic pipes, hydraulic headloss, hydraulic friction factor, Manning’s n

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122 Voluntary Disclosure Of Sustainability Information In Malaysian Federal-level Statutory Bodies

Authors: Siti Zabedah Saidin, Aidi Ahmi, Azharudin Ali, Wan Norhayati Wan Ahmad

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In today's increasingly complex and interconnected world, the concept of sustainability has transcended mere corporate social responsibility, evolving into a fundamental driver of organizational behaviour and disclosure. This content analysis study delves into the Malaysian federal-level statutory bodies’ annual report for the year 2021, aiming to elucidate the extent of sustainability disclosures within the non-financial sections of these reports. The escalating global emphasis on sustainability has prompted organizations to embrace transparency as a means to demonstrate their commitment to environmental, social, and governance (ESG) considerations. Voluntary sustainability disclosure has emerged as a crucial channel through which organizations communicate their efforts, initiatives, and impacts in these areas, thereby fostering trust and accountability with stakeholders. The study aims to identify and examine the types of sustainability information disclosed voluntarily by the federal-level statutory bodies, concentrating on the non-financial sections of the annual reports. To achieve this, the study adopts a simplified disclosure index, a pragmatic tool that quantifies the extent of sustainability reporting in a standardized manner. Using convenience sampling, the study selects a sample of annual reports from the federal-level statutory bodies in Malaysia, as provided on their respective websites. The content analysis is centred on the non-financial sections of these reports, allowing for an in-depth exploration of sustainability disclosures. The findings of the study present the extent to which Malaysian federal-level statutory bodies embrace sustainability reporting. Through thorough content analysis, the study uncovered diverse dimensions of sustainability information, encompassing environmental impact assessments, social engagement endeavours, and governance frameworks. This reveals a deliberate effort by these bodies to encapsulate their holistic organizational contributions and challenges, transcending traditional financial metrics. This research contributes to the existing literature by providing insights into the evolving landscape of sustainability disclosure practices among Malaysian federal-level statutory bodies. The findings underline the proactive nature of these bodies in voluntarily sharing sustainability-related information, reflecting their recognition of the interconnectedness between organizational success and societal well-being. Furthermore, the study underscores the potential influence of regulatory guidelines and societal expectations in shaping the extent and nature of voluntary sustainability disclosures. Organizations are not merely responding to regulatory mandates but are actively aligning with global sustainability goals and stakeholder expectations. As organizations continue to navigate the intricate web of stakeholder expectations and sustainability imperatives, this study enriches the discourse surrounding transparency and sustainability reporting. The analysis emphasizes the important role of non-financial disclosures in portraying a holistic organizational narrative. In an era where stakeholders demand accountability, and the interconnectedness of global challenges necessitates collaborative action, the voluntary disclosure of sustainability information stands as a testament to the commitment of Malaysian federal-level statutory bodies in shaping a more sustainable future.

Keywords: voluntary disclosure, sustainability information, annual report, federal-level statutory body

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121 On Stochastic Models for Fine-Scale Rainfall Based on Doubly Stochastic Poisson Processes

Authors: Nadarajah I. Ramesh

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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

Procedia PDF Downloads 255
120 Experimental Investigation of Absorbent Regeneration Techniques to Lower the Cost of Combined CO₂ and SO₂ Capture Process

Authors: Bharti Garg, Ashleigh Cousins, Pauline Pearson, Vincent Verheyen, Paul Feron

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The presence of SO₂ in power plant flue gases makes flue gas desulfurization (FGD) an essential requirement prior to post combustion CO₂ (PCC) removal facilities. Although most of the power plants worldwide deploy FGD in order to comply with environmental regulations, generally the achieved SO₂ levels are not sufficiently low for the flue gases to enter the PCC unit. The SO₂ level in the flue gases needs to be less than 10 ppm to effectively operate the PCC installation. The existing FGD units alone cannot bring down the SO₂ levels to or below 10 ppm as required for CO₂ capture. It might require an additional scrubber along with the existing FGD unit to bring the SO₂ to the desired levels. The absence of FGD units in Australian power plants brings an additional challenge. SO₂ concentrations in Australian power station flue gas emissions are in the range of 100-600 ppm. This imposes a serious barrier on the implementation of standard PCC technologies in Australia. CSIRO’s developed CS-Cap process is a unique solution to capture SO₂ and CO₂ in a single column with single absorbent which can potentially bring cost-effectiveness to the commercial deployment of carbon capture in Australia, by removing the need for FGD. Estimated savings of removing SO₂ through a similar process as CS-Cap is around 200 MMUSD for a 500 MW Australian power plant. Pilot plant trials conducted to generate the proof of concept resulted in 100% removal of SO₂ from flue gas without utilising standard limestone-based FGD. In this work, removal of absorbed sulfur from aqueous amine absorbents generated in the pilot plant trials has been investigated by reactive crystallisation and thermal reclamation. More than 95% of the aqueous amines can be reclaimed back from the sulfur loaded absorbent via reactive crystallisation. However, the recovery of amines through thermal reclamation is limited and depends on the sulfur loading on the spent absorbent. The initial experimental work revealed that reactive crystallisation is a better fit for CS-Cap’s sulfur-rich absorbent especially when it is also capable of generating K₂SO₄ crystals of highly saleable quality ~ 99%. Initial cost estimation carried on both the technologies resulted in almost similar capital expenditure; however, the operating cost is considerably higher in thermal reclaimer than that in crystalliser. The experimental data generated in the laboratory from both the regeneration techniques have been used to generate the simulation model in Aspen Plus. The simulation model illustrates the economic benefits which could be gained by removing flue gas desulfurization prior to standard PCC unit and replacing it with a CS-Cap absorber column co-capturing CO₂ and SO₂, and it's absorbent regeneration system which would be either reactive crystallisation or thermal reclamation.

Keywords: combined capture, cost analysis, crystallisation, CS-Cap, flue gas desulfurisation, regeneration, sulfur, thermal reclamation

Procedia PDF Downloads 100
119 Agent-Based Modeling Investigating Self-Organization in Open, Non-equilibrium Thermodynamic Systems

Authors: Georgi Y. Georgiev, Matthew Brouillet

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This research applies the power of agent-based modeling to a pivotal question at the intersection of biology, computer science, physics, and complex systems theory about the self-organization processes in open, complex, non-equilibrium thermodynamic systems. Central to this investigation is the principle of Maximum Entropy Production (MEP). This principle suggests that such systems evolve toward states that optimize entropy production, leading to the formation of structured environments. It is hypothesized that guided by the least action principle, open thermodynamic systems identify and follow the shortest paths to transmit energy and matter, resulting in maximal entropy production, internal structure formation, and a decrease in internal entropy. Concurrently, it is predicted that there will be an increase in system information as more information is required to describe the developing structure. To test this, an agent-based model is developed simulating an ant colony's formation of a path between a food source and its nest. Utilizing the Netlogo software for modeling and Python for data analysis and visualization, self-organization is quantified by calculating the decrease in system entropy based on the potential states and distribution of the ants within the simulated environment. External entropy production is also evaluated for information increase and efficiency improvements in the system's action. Simulations demonstrated that the system begins at maximal entropy, which decreases as the ants form paths over time. A range of system behaviors contingent upon the number of ants are observed. Notably, no path formation occurred with fewer than five ants, whereas clear paths were established by 200 ants, and saturation of path formation and entropy state was reached at populations exceeding 1000 ants. This analytical approach identified the inflection point marking the transition from disorder to order and computed the slope at this point. Combined with extrapolation to the final path entropy, these parameters yield important insights into the eventual entropy state of the system and the timeframe for its establishment, enabling the estimation of the self-organization rate. This study provides a novel perspective on the exploration of self-organization in thermodynamic systems, establishing a correlation between internal entropy decrease rate and external entropy production rate. Moreover, it presents a flexible framework for assessing the impact of external factors like changes in world size, path obstacles, and friction. Overall, this research offers a robust, replicable model for studying self-organization processes in any open thermodynamic system. As such, it provides a foundation for further in-depth exploration of the complex behaviors of these systems and contributes to the development of more efficient self-organizing systems across various scientific fields.

Keywords: complexity, self-organization, agent based modelling, efficiency

Procedia PDF Downloads 43
118 Application of 2D Electrical Resistivity Tomographic Imaging Technique to Study Climate Induced Landslide and Slope Stability through the Analysis of Factor of Safety: A Case Study in Ooty Area, Tamil Nadu, India

Authors: S. Maniruzzaman, N. Ramanujam, Qazi Akhter Rasool, Swapan Kumar Biswas, P. Prasad, Chandrakanta Ojha

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Landslide is one of the major natural disasters in South Asian countries. Applying 2D Electrical Resistivity Tomographic Imaging estimation of geometry, thickness, and depth of failure zone of the landslide can be made. Landslide is a pertinent problem in Nilgris plateau next to Himalaya. Nilgris range consists of hard Archean metamorphic rocks. Intense weathering prevailed during the Pre-Cambrian time had deformed the rocks up to 45m depth. The landslides are dominant in the southern and eastern part of plateau of is comparatively smaller than the northern drainage basins, as it has low density of drainage; coarse texture permitted the more of infiltration of rainwater, whereas in the northern part of the plateau entombed with high density of drainage pattern and fine texture with less infiltration than run off, and low to the susceptible to landslide. To get comprehensive information about the landslide zone 2D Electrical Resistivity Tomographic imaging study with CRM 500 Resistivity meter are used in Coonoor– Mettupalyam sector of Nilgiris plateau. To calculate Factor of Safety the infinite slope model of Brunsden and Prior is used. Factor of Safety can be expressed (FS) as the ratio of resisting forces to disturbing forces. If FS < 1 disturbing forces are larger than resisting forces and failure may occur. The geotechnical parameters of soil samples are calculated on the basis upon the apparent resistivity values for litho units of measured from 2D ERT image of the landslide zone. Relationship between friction angles for various soil properties is established by simple regression analysis from apparent resistivity data. Increase of water content in slide zone reduces the effectiveness of the shearing resistance and increase the sliding movement. Time-lapse resistivity changes to slope failure is determined through geophysical Factor of Safety which depends on resistivity and site topography. This ERT technique infers soil property at variable depths in wider areas. This approach to retrieve the soil property and overcomes the limit of the point of information provided by rain gauges and porous probes. Monitoring of slope stability without altering soil structure through the ERT technique is non-invasive with low cost. In landslide prone area an automated Electrical Resistivity Tomographic Imaging system should be installed permanently with electrode networks to monitor the hydraulic precursors to monitor landslide movement.

Keywords: 2D ERT, landslide, safety factor, slope stability

Procedia PDF Downloads 288
117 Fuzzy Availability Analysis of a Battery Production System

Authors: Merve Uzuner Sahin, Kumru D. Atalay, Berna Dengiz

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In today’s competitive market, there are many alternative products that can be used in similar manner and purpose. Therefore, the utility of the product is an important issue for the preferability of the brand. This utility could be measured in terms of its functionality, durability, reliability. These all are affected by the system capabilities. Reliability is an important system design criteria for the manufacturers to be able to have high availability. Availability is the probability that a system (or a component) is operating properly to its function at a specific point in time or a specific period of times. System availability provides valuable input to estimate the production rate for the company to realize the production plan. When considering only the corrective maintenance downtime of the system, mean time between failure (MTBF) and mean time to repair (MTTR) are used to obtain system availability. Also, the MTBF and MTTR values are important measures to improve system performance by adopting suitable maintenance strategies for reliability engineers and practitioners working in a system. Failure and repair time probability distributions of each component in the system should be known for the conventional availability analysis. However, generally, companies do not have statistics or quality control departments to store such a large amount of data. Real events or situations are defined deterministically instead of using stochastic data for the complete description of real systems. A fuzzy set is an alternative theory which is used to analyze the uncertainty and vagueness in real systems. The aim of this study is to present a novel approach to compute system availability using representation of MTBF and MTTR in fuzzy numbers. Based on the experience in the system, it is decided to choose 3 different spread of MTBF and MTTR such as 15%, 20% and 25% to obtain lower and upper limits of the fuzzy numbers. To the best of our knowledge, the proposed method is the first application that is used fuzzy MTBF and fuzzy MTTR for fuzzy system availability estimation. This method is easy to apply in any repairable production system by practitioners working in industry. It is provided that the reliability engineers/managers/practitioners could analyze the system performance in a more consistent and logical manner based on fuzzy availability. This paper presents a real case study of a repairable multi-stage production line in lead-acid battery production factory in Turkey. The following is focusing on the considered wet-charging battery process which has a higher production level than the other types of battery. In this system, system components could exist only in two states, working or failed, and it is assumed that when a component in the system fails, it becomes as good as new after repair. Instead of classical methods, using fuzzy set theory and obtaining intervals for these measures would be very useful for system managers, practitioners to analyze system qualifications to find better results for their working conditions. Thus, much more detailed information about system characteristics is obtained.

Keywords: availability analysis, battery production system, fuzzy sets, triangular fuzzy numbers (TFNs)

Procedia PDF Downloads 195
116 Potential of Aerodynamic Feature on Monitoring Multilayer Rough Surfaces

Authors: Ibtissem Hosni, Lilia Bennaceur Farah, Saber Mohamed Naceur

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In order to assess the water availability in the soil, it is crucial to have information about soil distributed moisture content; this parameter helps to understand the effect of humidity on the exchange between soil, plant cover and atmosphere in addition to fully understanding the surface processes and the hydrological cycle. On the other hand, aerodynamic roughness length is a surface parameter that scales the vertical profile of the horizontal component of the wind speed and characterizes the surface ability to absorb the momentum of the airflow. In numerous applications of the surface hydrology and meteorology, aerodynamic roughness length is an important parameter for estimating momentum, heat and mass exchange between the soil surface and atmosphere. It is important on this side, to consider the atmosphere factors impact in general, and the natural erosion in particular, in the process of soil evolution and its characterization and prediction of its physical parameters. The study of the induced movements by the wind over soil vegetated surface, either spaced plants or plant cover, is motivated by significant research efforts in agronomy and biology. The known major problem in this side concerns crop damage by wind, which presents a booming field of research. Obviously, most models of soil surface require information about the aerodynamic roughness length and its temporal and spatial variability. We have used a bi-dimensional multi-scale (2D MLS) roughness description where the surface is considered as a superposition of a finite number of one-dimensional Gaussian processes each one having a spatial scale using the wavelet transform and the Mallat algorithm to describe natural surface roughness. We have introduced multi-layer aspect of the humidity of the soil surface, to take into account a volume component in the problem of backscattering radar signal. As humidity increases, the dielectric constant of the soil-water mixture increases and this change is detected by microwave sensors. Nevertheless, many existing models in the field of radar imagery, cannot be applied directly on areas covered with vegetation due to the vegetation backscattering. Thus, the radar response corresponds to the combined signature of the vegetation layer and the layer of soil surface. Therefore, the key issue of the numerical estimation of soil moisture is to separate the two contributions and calculate both scattering behaviors of the two layers by defining the scattering of the vegetation and the soil blow. This paper presents a synergistic methodology, and it is for estimating roughness and soil moisture from C-band radar measurements. The methodology adequately represents a microwave/optical model which has been used to calculate the scattering behavior of the aerodynamic vegetation-covered area by defining the scattering of the vegetation and the soil below.

Keywords: aerodynamic, bi-dimensional, vegetation, synergistic

Procedia PDF Downloads 244
115 Screening of Osteoporosis in Aging Populations

Authors: Massimiliano Panella, Sara Bortoluzzi, Sophia Russotto, Daniele Nicolini, Carmela Rinaldi

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Osteoporosis affects more than 200 million people worldwide. About 75% of osteoporosis cases are undiagnosed or diagnosed only when a bone fracture occurs. Since osteoporosis related fractures are significant determinants of the burden of disease and health and social costs of aging populations, we believe that this is the early identification and treatment of high-risk patients should be a priority in actual healthcare systems. Screening for osteoporosis by dual energy x-ray absorptiometry (DEXA) is not cost-effective for general population. An alternative is pulse-echo ultrasound (PEUS) because of the minor costs. To this end, we developed an early detection program for osteoporosis with PEUS, and we evaluated is possible impact and sustainability. We conducted a cross-sectional study including 1,050 people in Italy. Subjects with >1 major or >2 minor risk factors for osteoporosis were invited to PEUS bone mass density (BMD) measurement at the proximal tibia. Based on BMD values, subjects were classified as healthy subjects (BMD>0.783 g/cm²) and pathological including subjects with suspected osteopenia (0.783≤BMD>0.719 g/cm²) or osteoporosis (BMD ≤ 0.719 g/cm²). The responder rate was 60.4% (634/1050). According to the risk, PEUS scan was recommended to 436 people, of whom 300 (mean age 45.2, 81% women) accepted to participate. We identified 240 (80%) healthy and 60 (20%) pathological subjects (47 osteopenic and 13 osteoporotic). We observed a significant association between high risk people and reduced bone density (p=0.043) with increased risks for female gender, older ages, and menopause (p<0.01). The yearly cost of the screening program was 8,242 euros. With actual Italian fracture incidence rates in osteoporotic patients, we can reasonably expect in 20 years that at least 6 fractures will occur in our sample. If we consider that the mean costs per fracture in Italy is today 16,785 euros, we can estimate a theoretical cost of 100,710 euros. According to literature, we can assume that the early treatment of osteoporosis could avoid 24,170 euros of such costs. If we add the actual yearly cost of the treatments to the cost of our program and we compare this final amount of 11,682 euros to the avoidable costs of fractures (24,170 euros) we can measure a possible positive benefits/costs ratio of 2.07. As a major outcome, our study let us to early identify 60 people with a significant bone loss that were not aware of their condition. This diagnostic anticipation constitutes an important element of value for the project, both for the patients, for the preventable negative outcomes caused by the fractures, and for the society in general, because of the related avoidable costs. Therefore, based on our finding, we believe that the PEUS based screening performed could be a cost-effective approach to early identify osteoporosis. However, our study has some major limitations. In fact, in our study the economic analysis is based on theoretical scenarios, thus specific studies are needed for a better estimation of the possible benefits and costs of our program.

Keywords: osteoporosis, prevention, public health, screening

Procedia PDF Downloads 99
114 Deep Learning for SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 45
113 Ecological Planning Method of Reclamation Area Based on Ecological Management of Spartina Alterniflora: A Case Study of Xihu Harbor in Xiangshan County

Authors: Dong Yue, Hua Chen

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The study region Xihu Harbor in Xiangshan County, Ningbo City is located in the central coast of Zhejiang Province. Concerning the wave dispating issue, Ningbo government firstly introduced Spartina alterniflora in 1980s. In the 1990s, S. alterniflora spread so rapidly thus a ‘grassland’ in the sea has been created nowadays. It has become the most important invasive plant of China’s coastal tidal flats. Although S. alterniflora had some ecological and economic functions, it has also brought series of hazards. It has ecological hazards on many aspects, including biomass and biodiversity, hydrodynamic force and sedimentation process, nutrient cycling of tidal flat, succession sequence of soil and plants and so on. On engineering, it courses problems of poor drainage and channel blocking. On economy, the hazard mainly reflected in the threat on aquaculture industry. The purpose of this study is to explore an ecological, feasible and economical way to manage Spartina alterniflora and use the land formed by it, taking Xihu Harbor in Xiangshan County as a case. Comparison method, mathematical modeling, qualitative and quantitative analysis are utilized to proceed the study. Main outcomes are as follows. By comparing a series of S. alterniflora managing methods which include the combination of mechanical cutting and hydraulic reclamation, waterlogging, herbicide and biological substitution from three standpoints – ecology, engineering and economy. It is inferred that the combination of mechanical cutting and hydraulic reclamation is among the top rank of S. alternifora managing methods. The combination of mechanical cutting and hydraulic reclamation means using large-scale mechanical equipment like large screw seagoing dredger to excavate the S. alterniflora with root and mud together. Then the mix of mud and grass was blown off nearby coastal tidal zone transported by pipelines, which can cushion the silt of tidal zone to form a land. However, as man-made land by coast, the reclamation area’s ecological sensitivity is quite high and will face high possibility of flood threat. Therefore, the reclamation area has many reasonability requirements, including ones on location, specific scope, water surface rate, direction of main watercourse, site of water-gate, the ratio of ecological land to urban construction land. These requirements all became important basis when the planning was being made. The water system planning, green space system planning, road structure and land use all need to accommodate the ecological requests. Besides, the profits from the formed land is the managing project’s source of funding, so how to utilize land efficiently is another considered point in the planning. It is concluded that by aiming at managing a large area of S. alterniflora, the combination of mechanical cutting and hydraulic reclamation is an ecological, feasible and economical method. The planning of reclamation area should fully respect the natural environment and possible disasters. Then the planning which makes land use efficient, reasonable, ecological will promote the development of the area’s city construction.

Keywords: ecological management, ecological planning method, reclamation area, Spartina alternifora, Xihu harbor

Procedia PDF Downloads 289
112 Microgrid Design Under Optimal Control With Batch Reinforcement Learning

Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

Procedia PDF Downloads 94
111 The Effect of the Precursor Powder Size on the Electrical and Sensor Characteristics of Fully Stabilized Zirconia-Based Solid Electrolytes

Authors: Olga Yu Kurapova, Alexander V. Shorokhov, Vladimir G. Konakov

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Nowadays, due to their exceptional anion conductivity at high temperatures cubic zirconia solid solutions, stabilized by rare-earth and alkaline-earth metal oxides, are widely used as a solid electrolyte (SE) materials in different electrochemical devices such as gas sensors, oxygen pumps, solid oxide fuel cells (SOFC), etc. Nowadays the intensive studies are carried out in a field of novel fully stabilized zirconia based SE development. The use of precursor powders for SE manufacturing allows predetermining the microstructure, electrical and sensor characteristics of zirconia based ceramics used as SE. Thus the goal of the present work was the investigation of the effect of precursor powder size on the electrical and sensor characteristics of fully stabilized zirconia-based solid electrolytes with compositions of 0,08Y2O3∙0,92ZrO2 (YSZ), 0,06Ce2O3∙ 0,06Y2O3∙0,88ZrO2 and 0,09Ce2O3∙0,06Y2O3-0,85ZrO2. The synthesis of precursors powders with different mean particle size was performed by sol-gel synthesis in the form of reversed co-precipitation from aqueous solutions. The cakes were washed until the neutral pH and pan-dried at 110 °С. Also, YSZ ceramics was obtained by conventional solid state synthesis including milling into a planetary mill. Then the powder was cold pressed into the pellets with a diameter of 7.2 and ~4 mm thickness at P ~16 kg/cm2 and then hydrostatically pressed. The pellets were annealed at 1600 °С for 2 hours. The phase composition of as-synthesized SE was investigated by X-Ray photoelectron spectroscopy ESCA (spectrometer ESCA-5400, PHI) X-ray diffraction analysis - XRD (Shimadzu XRD-6000). Following galvanic cell О2 (РО2(1)), Pt | SE | Pt, (РО2(2) = 0.21 atm) was used for SE sensor properties investigation. The value of РО2(1) was set by mixing of O2 and N2 in the defined proportions with the accuracy of  5%. The temperature was measured by Pt/Pt-10% Rh thermocouple, The cell electromotive force (EMF) measurement was carried out with ± 0.1 mV accuracy. During the operation at the constant temperature, reproducibility was better than 5 mV. Asymmetric potential measured for all SE appeared to be negligible. It was shown that the resistivity of YSZ ceramics decreases in about two times upon the mean agglomerates decrease from 200-250 to 40 nm. It is likely due to the both surface and bulk resistivity decrease in grains. So the overall decrease of grain size in ceramic SE results in the significant decrease of the total ceramics resistivity allowing sensor operation at lower temperatures. For the SE manufactured the estimation of oxygen ion transfer number tion was carried out in the range 600-800 °С. YSZ ceramics manufactured from powders with the mean particle size 40-140 nm, shows the highest values i.e. 0.97-0.98. SE manufactured from precursors with the mean particle size 40-140 nm shows higher sensor characteristic i.e. temperature and oxygen concentration EMF dependencies, EMF (ENernst - Ereal), tion, response time, then ceramics, manufactured by conventional solid state synthesis.

Keywords: oxygen sensors, precursor powders, sol-gel synthesis, stabilized zirconia ceramics

Procedia PDF Downloads 254
110 Optical Imaging Based Detection of Solder Paste in Printed Circuit Board Jet-Printing Inspection

Authors: D. Heinemann, S. Schramm, S. Knabner, D. Baumgarten

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Purpose: Applying solder paste to printed circuit boards (PCB) with stencils has been the method of choice over the past years. A new method uses a jet printer to deposit tiny droplets of solder paste through an ejector mechanism onto the board. This allows for more flexible PCB layouts with smaller components. Due to the viscosity of the solder paste, air blisters can be trapped in the cartridge. This can lead to missing solder joints or deviations in the applied solder volume. Therefore, a built-in and real-time inspection of the printing process is needed to minimize uncertainties and increase the efficiency of the process by immediate correction. The objective of the current study is the design of an optimal imaging system and the development of an automatic algorithm for the detection of applied solder joints from optical from the captured images. Methods: In a first approach, a camera module connected to a microcomputer and LED strips are employed to capture images of the printed circuit board under four different illuminations (white, red, green and blue). Subsequently, an improved system including a ring light, an objective lens, and a monochromatic camera was set up to acquire higher quality images. The obtained images can be divided into three main components: the PCB itself (i.e., the background), the reflections induced by unsoldered positions or screw holes and the solder joints. Non-uniform illumination is corrected by estimating the background using a morphological opening and subtraction from the input image. Image sharpening is applied in order to prevent error pixels in the subsequent segmentation. The intensity thresholds which divide the main components are obtained from the multimodal histogram using three probability density functions. Determining the intersections delivers proper thresholds for the segmentation. Remaining edge gradients produces small error areas which are removed by another morphological opening. For quantitative analysis of the segmentation results, the dice coefficient is used. Results: The obtained PCB images show a significant gradient in all RGB channels, resulting from ambient light. Using different lightings and color channels 12 images of a single PCB are available. A visual inspection and the investigation of 27 specific points show the best differentiation between those points using a red lighting and a green color channel. Estimating two thresholds from analyzing the multimodal histogram of the corrected images and using them for segmentation precisely extracts the solder joints. The comparison of the results to manually segmented images yield high sensitivity and specificity values. Analyzing the overall result delivers a Dice coefficient of 0.89 which varies for single object segmentations between 0.96 for a good segmented solder joints and 0.25 for single negative outliers. Conclusion: Our results demonstrate that the presented optical imaging system and the developed algorithm can robustly detect solder joints on printed circuit boards. Future work will comprise a modified lighting system which allows for more precise segmentation results using structure analysis.

Keywords: printed circuit board jet-printing, inspection, segmentation, solder paste detection

Procedia PDF Downloads 310
109 A Qualitative Study to Analyze Clinical Coders’ Decision Making Process of Adverse Drug Event Admissions

Authors: Nisa Mohan

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Clinical coding is a feasible method for estimating the national prevalence of adverse drug event (ADE) admissions. However, under-coding of ADE admissions is a limitation of this method. Whilst the under-coding will impact the accurate estimation of the actual burden of ADEs, the feasibility of the coded data in estimating the adverse drug event admissions goes much further compared to the other methods. Therefore, it is necessary to know the reasons for the under-coding in order to improve the clinical coding of ADE admissions. The ability to identify the reasons for the under-coding of ADE admissions rests on understanding the decision-making process of coding ADE admissions. Hence, the current study aimed to explore the decision-making process of clinical coders when coding cases of ADE admissions. Clinical coders from different levels of coding job such as trainee, intermediate and advanced level coders were purposefully selected for the interviews. Thirteen clinical coders were recruited from two Auckland region District Health Board hospitals for the interview study. Semi-structured, one-on-one, face-to-face interviews using open-ended questions were conducted with the selected clinical coders. Interviews were about 20 to 30 minutes long and were audio-recorded with the approval of the participants. The interview data were analysed using a general inductive approach. The interviews with the clinical coders revealed that the coders have targets to meet, and they sometimes hesitate to adhere to the coding standards. Coders deviate from the standard coding processes to make a decision. Coders avoid contacting the doctors for clarifying small doubts such as ADEs and the name of the medications because of the delay in getting a reply from the doctors. They prefer to do some research themselves or take help from their seniors and colleagues for making a decision because they can avoid a long wait to get a reply from the doctors. Coders think of ADE as a small thing. Lack of time for searching for information to confirm an ADE admission, inadequate communication with clinicians, along with coders’ belief that an ADE is a small thing may contribute to the under-coding of the ADE admissions. These findings suggest that further work is needed on interventions to improve the clinical coding of ADE admissions. Providing education to coders about the importance of ADEs, educating clinicians about the importance of clear and confirmed medical records entries, availing pharmacists’ services to improve the detection and clear documentation of ADE admissions, and including a mandatory field in the discharge summary about external causes of diseases may be useful for improving the clinical coding of ADE admissions. The findings of the research will help the policymakers to make informed decisions about the improvements. This study urges the coding policymakers, auditors, and trainers to engage with the unconscious cognitive biases and short-cuts of the clinical coders. This country-specific research conducted in New Zealand may also benefit other countries by providing insight into the clinical coding of ADE admissions and will offer guidance about where to focus changes and improvement initiatives.

Keywords: adverse drug events, clinical coders, decision making, hospital admissions

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108 Prediction of Endotracheal Tube Size in Children by Predicting Subglottic Diameter Using Ultrasonographic Measurement versus Traditional Formulas

Authors: Parul Jindal, Shubhi Singh, Priya Ramakrishnan, Shailender Raghuvanshi

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Background: Knowledge of the influence of the age of the child on laryngeal dimensions is essential for all practitioners who are dealing with paediatric airway. Choosing the correct endotracheal tube (ETT) size is a crucial step in pediatric patients because a large-sized tube may cause complications like post-extubation stridor and subglottic stenosis. On the other hand with a smaller tube, there will be increased gas flow resistance, aspiration risk, poor ventilation, inaccurate monitoring of end-tidal gases and reintubation may also be required with a different size of the tracheal tube. Recent advancement in ultrasonography (USG) techniques should now allow for accurate and descriptive evaluation of pediatric airway. Aims and objectives: This study was planned to determine the accuracy of Ultrasonography (USG) to assess the appropriate ETT size and compare it with physical indices based formulae. Methods: After obtaining approval from Institute’s Ethical and Research committee, and parental written and informed consent, the study was conducted on 100 subjects of either sex between 12-60 months of age, undergoing various elective surgeries under general anesthesia requiring endotracheal intubation. The same experienced radiologist performed ultrasonography. The transverse diameter was measured at the level of cricoids cartilage by USG. After USG, general anesthesia was administered using standard techniques followed by the institute. An experienced anesthesiologist performed the endotracheal intubations with uncuffed endotracheal tube (Portex Tracheal Tube Smiths Medical India Pvt. Ltd.) with Murphy’s eye. He was unaware of the finding of the ultrasonography. The tracheal tube was considered best fit if air leak was satisfactory at 15-20 cm H₂O of airway pressure. The obtained values were compared with the values of endotracheal tube size calculated by ultrasonography, various age, height, weight-based formulas and diameter of right and left little finger. The correlation of the size of the endotracheal tube by different modalities was done and Pearson's correlation coefficient was obtained. The comparison of the mean size of the endotracheal tube by ultrasonography and by traditional formula was done by the Friedman’s test and Wilcoxon sign-rank test. Results: The predicted tube size was equal to best fit and best determined by ultrasonography (100%) followed by comparison to left little finger (98%) and right little finger (97%) and age-based formula (95%) followed by multivariate formula (83%) and body length (81%) formula. According to Pearson`s correlation, there was a moderate correlation of best fit endotracheal tube with endotracheal tube size by age-based formula (r=0.743), body length based formula (r=0.683), right little finger based formula (r=0.587), left little finger based formula (r=0.587) and multivariate formula (r=0.741). There was a strong correlation with ultrasonography (r=0.943). Ultrasonography was the most sensitive (100%) method of prediction followed by comparison to left (98%) and right (97%) little finger and age-based formula (95%), the multivariate formula had an even lesser sensitivity (83%) whereas body length based formula was least sensitive with a sensitivity of 78%. Conclusion: USG is a reliable method of estimation of subglottic diameter and for prediction of ETT size in children.

Keywords: endotracheal intubation, pediatric airway, subglottic diameter, traditional formulas, ultrasonography

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107 Deep Learning Based Polarimetric SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

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In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

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106 Mathematical Modelling of Bacterial Growth in Products of Animal Origin in Storage and Transport: Effects of Temperature, Use of Bacteriocins and pH Level

Authors: Benjamin Castillo, Luis Pastenes, Fernando Cordova

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The pathogen growth in animal source foods is a common problem in the food industry, causing monetary losses due to the spoiling of products or food intoxication outbreaks in the community. In this sense, the quality of the product is reflected by the population of deteriorating agents present in it, which are mainly bacteria. The factors which are likely associated with freshness in animal source foods are temperature and processing, storage, and transport times. However, the level of deterioration of products depends, in turn, on the characteristics of the bacterial population, causing the decomposition or spoiling, such as pH level and toxins. Knowing the growth dynamics of the agents that are involved in product contamination allows the monitoring for more efficient processing. This means better quality and reasonable costs, along with a better estimation of necessary time and temperature intervals for transport and storage in order to preserve product quality. The objective of this project is to design a secondary model that allows measuring the impact on temperature bacterial growth and the competition for pH adequacy and release of bacteriocins in order to describe such phenomenon and, thus, estimate food product half-life with the least possible risk of deterioration or spoiling. In order to achieve this objective, the authors propose an analysis of a three-dimensional ordinary differential which includes; logistic bacterial growth extended by the inhibitory action of bacteriocins including the effect of the medium pH; change in the medium pH levels through an adaptation of the Luedeking-Piret kinetic model; Bacteriocin concentration modeled similarly to pH levels. These three dimensions are being influenced by the temperature at all times. Then, this differential system is expanded, taking into consideration the variable temperature and the concentration of pulsed bacteriocins, which represent characteristics inherent of the modeling, such as transport and storage, as well as the incorporation of substances that inhibit bacterial growth. The main results lead to the fact that temperature changes in an early stage of transport increased the bacterial population significantly more than if it had increased during the final stage. On the other hand, the incorporation of bacteriocins, as in other investigations, proved to be efficient in the short and medium-term since, although the population of bacteria decreased, once the bacteriocins were depleted or degraded over time, the bacteria eventually returned to their regular growth rate. The efficacy of the bacteriocins at low temperatures decreased slightly, which equates with the fact that their natural degradation rate also decreased. In summary, the implementation of the mathematical model allowed the simulation of a set of possible bacteria present in animal based products, along with their properties, in various transport and storage situations, which led us to state that for inhibiting bacterial growth, the optimum is complementary low constant temperatures and the initial use of bacteriocins.

Keywords: bacterial growth, bacteriocins, mathematical modelling, temperature

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105 Nephroprotective Effect of Aqueous Extract of Plectranthus amboinicus (Roxb.) Leaves in Adriamycin Induced Acute Renal Failure in Wistar Rats: A Biochemical and Histopathological Assessment

Authors: Ampe Mohottige Sachinthi Sandaruwani Amarasiri, Anoja Priyadarshani Attanayake, Kamani Ayoma Perera Wijewardana Jayatilaka, Lakmini Kumari Boralugoda Mudduwa

Abstract:

The search for alternative pharmacological therapies based on natural extracts for renal failure has become an urgent need, due to paucity of effective pharmacotherapy. The current study was undertaken to evaluate the acute nephroprotective effect of aqueous leaf extract of Plectranthus amboinicus (Roxb.) (Family: Lamiaceae), a medicinal plant used in traditional Ayurvedic medicine for the management of renal diseases in Sri Lanka. The study was performed in adriamycin (ADR) induced nephrotoxic in Wistar rats. Wistar rats were randomly divided into four groups each with six rats. A single dose of ADR (20 mg/kg body wt., ip) was used for the induction of nephrotoxicity in all groups of rats except group one. The treatments were started 24 hours after induction of nephrotoxicity and continued for three days. Group one and two served as healthy and nephrotoxic control rats and were administered equivalent volumes of normal saline (0.9% NaCl) orally. Group three and four nephrotoxic rats were administered the lyophilized powder of the aqueous extract of P. amboinicus (400 mg/ kg body wt.; equivalent human therapeutic dose) and the standard drug, fosinopril sodium (0.09 mg/ kg body wt.) respectively. Urine and blood samples were collected from rats in each group at the end of the period of intervention for the estimation of selected renal parameters. H and E stained sections of the kidney tissues were examined for histopathological changes. Rats treated with the plant extract showed significant improvement in biochemical parameters and histopathological changes compared to ADR induced nephrotoxic group. The elevation of serum concentrations of creatinine and β2-microglobulin were decreased by 38%, and 66% in plant extract treated nephrotoxic rats respectively (p < 0.05). In addition, serum concentrations of total protein and albumin were significantly increased by 25% and 14% in rats treated with P. amboinicus respectively (p < 0.05). The results of β2 –microglobulin and serum total protein demonstrated a significant reduction in the elevated values in rats administered with the plant extract (400 mg/kg) compared to that of fosinopril (0.09 mg/kg). Urinary protein loss in 24hr urine samples was significantly decreased in rats treated with both fosinopril (86%) and P. ambonicus (56%) at the end of the intervention (p < 0.01). Accordingly, an attenuation of morphological destruction was observed in the H and E stained sections of the kidney with the treatments of plant extract and fosinopril. The results of the present study revealed that the aqueous leaf extract of P. amboinicus possesses significant nephroprotective activity at the equivalent therapeutic dose of 400 mg/ kg against adriamycin induced acute nephrotoxicity.

Keywords: biochemical assessment, histopathological assessment, nephroprotective activity, Plectranthus amboinicus

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104 Motives for Reshoring from China to Europe: A Hierarchical Classification of Companies

Authors: Fabienne Fel, Eric Griette

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Reshoring, whether concerning back-reshoring or near-reshoring, is a quite recent phenomenon. Despite the economic and political interest of this topic, academic research questioning determinants of reshoring remains rare. Our paper aims at contributing to fill this gap. In order to better understand the reasons for reshoring, we conducted a study among 280 French firms during spring 2016, three-quarters of which sourced, or source, in China. 105 firms in the sample have reshored all or part of their Chinese production or supply in recent years, and we aimed to establish a typology of the motives that drove them to this decision. We asked our respondents about the history of their Chinese supplies, their current reshoring strategies, and their motivations. Statistical analysis was performed with SPSS 22 and SPAD 8. Our results show that change in commercial and financial terms with China is the first motive explaining the current reshoring movement from this country (it applies to 54% of our respondents). A change in corporate strategy is the second motive (30% of our respondents); the reshoring decision follows a change in companies’ strategies (upgrading, implementation of a CSR policy, or a 'lean management' strategy). The third motive (14% of our sample) is a mere correction of the initial offshoring decision, considered as a mistake (under-estimation of hidden costs, non-quality and non-responsiveness problems). Some authors emphasize that developing a short supply chain, involving geographic proximity between design and production, gives a competitive advantage to companies wishing to offer innovative products. Admittedly 40% of our respondents indicate that this motive could have played a part in their decision to reshore, but this reason was not enough for any of them and is not an intrinsic motive leading to leaving Chinese suppliers. Having questioned our respondents about the importance given to various problems leading them to reshore, we then performed a Principal Components Analysis (PCA), associated with an Ascending Hierarchical Classification (AHC), based on Ward criterion, so as to point out more specific motivations. Three main classes of companies should be distinguished: -The 'Cost Killers' (23% of the sample), which reshore their supplies from China only because of higher procurement costs and so as to find lower costs elsewhere. -The 'Realists' (50% of the sample), giving equal weight or importance to increasing procurement costs in China and to the quality of their supplies (to a large extend). Companies being part of this class tend to take advantage of this changing environment to change their procurement strategy, seeking suppliers offering better quality and responsiveness. - The 'Voluntarists' (26% of the sample), which choose to reshore their Chinese supplies regardless of higher Chinese costs, to obtain better quality and greater responsiveness. We emphasize that if the main driver for reshoring from China is indeed higher local costs, it is should not be regarded as an exclusive motivation; 77% of the companies in the sample, are also seeking, sometimes exclusively, more reactive suppliers, liable to quality, respect for the environment and intellectual property.

Keywords: China, procurement, reshoring, strategy, supplies

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