Search results for: deep neural image models

Authors: Tomoko Yaginuma, Rosa Cabecinhas

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Recently, the studies of the images about Japan and/or the Japanese people have been done in a Japanese language education context since the number of the students of Japanese as a Foreign Language (JFL) has been increasing worldwide, including in Portugal. It has been claimed that one of the reasons for this increase is the current popularity of Japanese pop-culture, namely anime (Japanese animations) and manga (Japanese visual novels), among young students. In the present study, the images about Japan and the Japanese held by JFL students in Portugal were examined by a questionnaire survey. The JFL students in higher education in Portugal (N=296) were asked to answer, among the other questions, their degree of agreement (using a Likert scale) with 24 pre-defined descriptions about the Japanese, which appear as relevant in a qualitative pilot study conducted before. The results show that the image of Japanese people by Portuguese JFL students is stressed around four dimensions: 1) diligence, 2) kindness, 3) conservativeness and 4) innovativeness. The students considered anime was the main source of information about the Japanese people and culture and anime was also strongly associated with the students’ interests in learning Japanese language.

Keywords: anime, cultural studies, images about Japan and Japanese people, Portugal

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Authors: Sinuhé Perea Puente

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In several physics systems the whole can be obtained as an exact copy of each of its parts, which facilitates the study of a complex system by looking carefully at its elements, separately. Reducionism offers simplified models which makes the problems easier, but “there’s plenty of room...at the mesoscopic scale”. Here we present a tour for two of its representants: Berry phase and skyrmions, studying some of its basic definitions and properties, and two cases in which both arise together, to finish constraining the scale for our mesoscopic system in the quest of quantum skyrmions, discovering which properties are conserved and which others may be destroyed.

Keywords: condensed mattter, quantum physics, skyrmions, topological defects

Procedia PDF Downloads 123

Authors: Yeo Kyeong Lee, Ji Yeon Kang, Eun Mi Ryu, Hee Sun Kim, Yeong Soo Shin

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The objective of this paper is an investigation of the effects of the thickness and axial loading during a fire test on the load-bearing capacity of a fire-damaged normal-strength concrete wall. Two factors are attributed to the temperature distributions in the concrete members and are mainly obtained through numerous experiments. Toward this goal, three wall specimens of different thicknesses are heated for 2 h according to the ISO-standard heating curve, and the temperature distributions through the thicknesses are measured using thermocouples. In addition, two wall specimens are heated for 2 h while simultaneously being subjected to a constant axial loading at their top sections. The test results show that the temperature distribution during the fire test depends on wall thickness and axial load during the fire test. After the fire tests, the specimens are cured for one month, followed by the loading testing. The heated specimens are compared with three unheated specimens to investigate the residual load-bearing capacities. The fire-damaged walls show a minor difference of the load-bearing capacity regarding the axial loading, whereas a significant difference became evident regarding the wall thickness. To validate the experiment results, finite element models are generated for which the material properties that are obtained for the experiment are subject to elevated temperatures, and the analytical results show sound agreements with the experiment results. The analytical method based on validated thought experimental results is applied to generate the fire-damaged walls with 2,800 mm high considering the buckling effect: typical story height of residual buildings in Korea. The models for structural analyses generated to deformation shape after thermal analysis. The load-bearing capacity of the fire-damaged walls with pin supports at both ends does not significantly depend on the wall thickness, the reason for it is restraint of pinned ends. The difference of the load-bearing capacity of fire-damaged walls as axial load during the fire is within approximately 5 %.

Keywords: normal-strength concrete wall, wall thickness, axial-load ratio, slenderness ratio, fire test, residual strength, finite element analysis

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Authors: Arunima Shukla, Vikas Almadi, Devesh Jaiswal, Sunil Saini, Bhusan S. Patil

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Lightning protection consists of three main parts; mainly air termination system, down conductor, and earth termination system. Earth termination system is the most important part as earth is the sink and source of charges. Therefore, even when the charges are captured and delivered to the ground, and an easy path is not provided to the charges, earth termination system would lead to problems. Soil has significantly different resistivities ranging from 10 Ωm for wet organic soil to 10000 Ωm for bedrock. Different methods have been discussed and used conventionally such as deep-ground-well method and altering the length of the rod. Those methods are not considered economical. Therefore, it was a general practice to use charcoal along with salt to reduce the soil resistivity. Bentonite is worldwide acceptable material, that had led our interest towards study of bentonite at first. It was concluded that bentonite is a clay which is non-corrosive, environment friendly. Whereas bentonite is suitable only when there is moisture present in the soil, as in the absence of moisture, cracks will appear on the surface which will provide an open passage to the air, resulting into increase in the resistivity. Furthermore, bentonite without moisture does not have enough bonding property, moisture retention, conductivity, and non-leachability. Therefore, bentonite was used along with the other backfill material to overcome the dependency of bentonite on moisture. Different experiments were performed to get the best ratio of bentonite and carbon backfill. It was concluded that properties will highly depend on the quantity of bentonite and carbon-based backfill material.

Keywords: backfill material, bentonite, grounding material, low resistivity

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Authors: Jing Jiang, Wenhuan XU, Lei Zhang, Shiyi Zhang, Tongli Wang

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Climate data quality significantly affects the reliability of ecological modeling. In the Asia Pacific (AP) region, low-quality climate data hinders ecological modeling. ClimateAP, a software developed in 2017, generates high-quality climate data for the AP region, benefiting researchers in forestry and agriculture. However, its adoption remains limited. This study aims to confirm the validity of biologically relevant variable data generated by ClimateAP during the normal climate period through comparison with the currently available gridded data. Climate data from 2,366 weather stations were used to evaluate the prediction accuracy of ClimateAP in comparison with the commonly used gridded data from WorldClim1.4. Univariate regressions were applied to 48 monthly biologically relevant variables, and the relationship between the observational data and the predictions made by ClimateAP and WorldClim was evaluated using Adjusted R-Squared and Root Mean Squared Error (RMSE). Locations were categorized into mountainous and flat landforms, considering elevation, slope, ruggedness, and Topographic Position Index. Univariate regressions were then applied to all biologically relevant variables for each landform category. Random Forest (RF) models were implemented for the climatic niche modeling of Cunninghamia lanceolata. A comparative analysis of the prediction accuracies of RF models constructed with distinct climate data sources was conducted to evaluate their relative effectiveness. Biologically relevant variables were obtained from three unpublished Chinese meteorological datasets. ClimateAPv3.0 and WorldClim predictions were obtained from weather station coordinates and WorldClim1.4 rasters, respectively, for the normal climate period of 1961-1990. Occurrence data for Cunninghamia lanceolata came from integrated biodiversity databases with 3,745 unique points. ClimateAP explains a minimum of 94.74%, 97.77%, 96.89%, and 94.40% of monthly maximum, minimum, average temperature, and precipitation variances, respectively. It outperforms WorldClim in 37 biologically relevant variables with lower RMSE values. ClimateAP achieves higher R-squared values for the 12 monthly minimum temperature variables and consistently higher Adjusted R-squared values across all landforms for precipitation. ClimateAP's temperature data yields lower Adjusted R-squared values than gridded data in high-elevation, rugged, and mountainous areas but achieves higher values in mid-slope drainages, plains, open slopes, and upper slopes. Using ClimateAP improves the prediction accuracy of tree occurrence from 77.90% to 82.77%. The biologically relevant climate data produced by ClimateAP is validated based on evaluations using observations from weather stations. The use of ClimateAP leads to an improvement in data quality, especially in non-mountainous regions. The results also suggest that using biologically relevant variables generated by ClimateAP can slightly enhance climatic niche modeling for tree species, offering a better understanding of tree species adaptation and resilience compared to using gridded data.

Keywords: climate data validation, data quality, Asia pacific climate, climatic niche modeling, random forest models, tree species

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Authors: Nicole Merkle, Stefan Zander

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Ambient Assisted Living (AAL) describes a technological and methodological stack of (e.g. formal model-theoretic semantics, rule-based reasoning and machine learning), different aspects regarding the behavior, activities and characteristics of humans. Hence, a semantic representation of the user environment and its relevant elements are required in order to allow assistive agents to recognize situations and deduce appropriate actions. Furthermore, the user and his/her characteristics (e.g. physical, cognitive, preferences) need to be represented with a high degree of expressiveness in order to allow software agents a precise evaluation of the users’ context models. The correct interpretation of these context models highly depends on temporal, spatial circumstances as well as individual user preferences. In most AAL approaches, model representations of real world situations represent the current state of a universe of discourse at a given point in time by neglecting transitions between a set of states. However, the AAL domain currently lacks sufficient approaches that contemplate on the dynamic adaptions of context-related representations. Semantic representations of relevant real-world excerpts (e.g. user activities) help cognitive, rule-based agents to reason and make decisions in order to help users in appropriate tasks and situations. Furthermore, rules and reasoning on semantic models are not sufficient for handling uncertainty and fuzzy situations. A certain situation can require different (re-)actions in order to achieve the best results with respect to the user and his/her needs. But what is the best result? To answer this question, we need to consider that every smart agent requires to achieve an objective, but this objective is mostly defined by domain experts who can also fail in their estimation of what is desired by the user and what not. Hence, a smart agent has to be able to learn from context history data and estimate or predict what is most likely in certain contexts. Furthermore, different agents with contrary objectives can cause collisions as their actions influence the user’s context and constituting conditions in unintended or uncontrolled ways. We present an approach for dynamically updating a semantic model with respect to the current user context that allows flexibility of the software agents and enhances their conformance in order to improve the user experience. The presented approach adapts rules by learning sensor evidence and user actions using probabilistic reasoning approaches, based on given expert knowledge. The semantic domain model consists basically of device-, service- and user profile representations. In this paper, we present how this semantic domain model can be used in order to compute the probability of matching rules and actions. We apply this probability estimation to compare the current domain model representation with the computed one in order to adapt the formal semantic representation. Our approach aims at minimizing the likelihood of unintended interferences in order to eliminate conflicts and unpredictable side-effects by updating pre-defined expert knowledge according to the most probable context representation. This enables agents to adapt to dynamic changes in the environment which enhances the provision of adequate assistance and affects positively the user satisfaction.

Keywords: ambient intelligence, machine learning, semantic web, software agents

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Authors: Nomin-Erdene Erdenetsogt, Tseedulam Khuut, Batsaikhan Tserenpil, Bayarsaikhan Enkhee

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As the framework of 60 years of development of Astronomical and Geophysical science in modern Mongolia, various geophysical methods (electrical tomography, ground-penetrating radar, and high-resolution reflection seismic profiles) were used to image an active fault in-depth range between few decimeters to few tens meters. An active fault was fractured by an earthquake magnitude 7.6 during 1967. After geophysical investigations, trench excavations were done at the sites to expose the fault surfaces. The complex geophysical survey in the Mogod fault, Bulgan region of central Mongolia shows an interpretable reflection arrivals range of < 5 m to 50 m with the potential for increased resolution. Reflection profiles were used to help interpret the significance of neotectonic surface deformation at earthquake active fault. The interpreted profiles show a range of shallow fault structures and provide subsurface evidence with support of paleoseismologic trenching photos, electrical surveys.

Keywords: Mogod fault, geophysics, seismic processing, seismic reflection survey

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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A considerable area of Algerian lands are threatened by the phenomenon of wind erosion. For a long time, wind erosion and its associated harmful effects on the natural environment have posed a serious threat, especially in the arid regions of the country. In recent years, as a result of increases in the irrational exploitation of natural resources (fodder) and extensive land clearing, wind erosion has particularly accentuated. The extent of degradation in the arid region of the Algerian Mécheriadepartment generated a new situation characterized by the reduction of vegetation cover, the decrease of land productivity, as well as sand encroachment on urban development zones. In this study, we attempt to investigate the potential of remote sensing and geographic information systems for detecting the spatial dynamics of the ancient dune cords based on the numerical processing of PlanetScope PSB.SB sensors images by September 29, 2021. As a second step, we prospect the use of a multi-scale geographic object-based image analysis (GEOBIA) approach to segment the high spatial resolution images acquired on heterogeneous surfaces that vary according to human influence on the environment. We have used the fractal net evolution approach (FNEA) algorithm to segment images (Baatz&Schäpe, 2000). Multispectral data, a digital terrain model layer, ground truth data, a normalized difference vegetation index (NDVI) layer, and a first-order texture (entropy) layer were used to segment the multispectral images at three segmentation scales, with an emphasis on accurately delineating the boundaries and components of the sand accumulation areas (Dune, dunes fields, nebka, and barkhane). It is important to note that each auxiliary data contributed to improve the segmentation at different scales. The silted areas were classified using a nearest neighbor approach over the Naâma area using imagery. The classification of silted areas was successfully achieved over all study areas with an accuracy greater than 85%, although the results suggest that, overall, a higher degree of landscape heterogeneity may have a negative effect on segmentation and classification. Some areas suffered from the greatest over-segmentation and lowest mapping accuracy (Kappa: 0.79), which was partially attributed to confounding a greater proportion of mixed siltation classes from both sandy areas and bare ground patches. This research has demonstrated a technique based on very high-resolution images for mapping sanded and degraded areas using GEOBIA, which can be applied to the study of other lands in the steppe areas of the northern countries of the African continent.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Hemant Kumar, R. N. K. Sharma, A. P. Krishna

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The study has been carried out on the Saranda in Jharkhand and a part of Odisha state. Geospatial data of Hyperion, a remote sensing satellite, have been used. This study has used a wide variety of patterns related to image processing to enhance and extract the mining class of Fe and Mn ores.Landsat-8, OLI sensor data have also been used to correctly explore related minerals. In this way, various processes have been applied to increase the mineralogy class and comparative evaluation with related frequency done. The Hyperion dataset for hyperspectral remote sensing has been specifically verified as an effective tool for mineral or rock information extraction within the band range of shortwave infrared used. The abundant spatial and spectral information contained in hyperspectral images enables the differentiation of different objects of any object into targeted applications for exploration such as exploration detection, mining.

Keywords: Hyperion, hyperspectral, sensor, Landsat-8

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Authors: Supaporn Prajongjai, Pannarungsri Inpayoung

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This research attempts to explore the perception and satisfaction of international tourists toward Thai economy, politics and Bangkok attributes. Due to tourism industry provides a high rate of revenue for Thailand, and the outcome from this business drives every section of Thailand such as business, residents’ living level. Unfortunately, some incidents in the country, such as some turmoil, have ruined the city’s image which obviously impacts to the tourism industry, the major source of revenue. The size of this research was 400 international tourists who visit Bangkok, Thailand during the 1st – 20th March 2009 and age between 20 – 65 years. The results reveal that tourists satisfy with all of Bangkok’s attributes including general attractions, heritage attraction, maintenance factors and cultural attraction. Also, tourists’ perception toward Thai politics is significantly related to their satisfaction of Bangkok’s attributes, but their perception toward Thai economy is not significantly correlated to their satisfaction of Bangkok’s attributes.

Keywords: international tourists' perception, tourists' satisfactions, Thai economy, tourism destination

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Authors: Mario Belseran

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The issue of climate change become world attention where one of them increase in air temperature due to greenhouse gas emissions. This climate change is caused by gases in the atmosphere, one of which is CO2. DKI Jakarta as the capital has a dense population with a variety of existing land use. Land use that is dominated by settlements resulting in fewer green space, which functions to absorb atmospheric CO2. Image interpretation SPOT-7 is used to determine the greenness level of vegetation on a green space using the vegetation index NDVI, EVI, GNDVI and OSAVI. Measuring the diameter and height of trees were also performed to obtain the value of biomass that will be used as the CO2 absorption value. The CO2 absorption value that spread in Jakarta are classified into three classes: high, medium, and low. The distribution pattern of CO2 absorption value at green space in Jakarta dominance in the medium class with the distribution pattern is located in South Jakarta, East Jakarta, North Jakarta and West Jakarta. The distribution pattern of green space in Jakarta scattered randomly and more dominate in East Jakarta and South Jakarta

Keywords: carbon dioxide, DKI Jakarta, green space, SPOT-7, vegetation index

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Authors: Anthony J. Kondracki, Bonzo I. Reddick, Jennifer L. Barkin

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We sought to examine the association of maternal Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and treponema pallidum (TP) (syphilis) infections with preterm birth (PTB) (<37 weeks gestation), low birth weight (LBW) (<2500 grams) and prenatal care (PNC) attendance. This cross-sectional study was based on data drawn from the 2020 United States National Center for Health Statistics (NCHS) Natality File. We estimated the prevalence of all births, early/late PTBs, moderately/very LBW, and the distribution of sexually transmitted infections (STIs) according to maternal characteristics in the sample. In multivariable logistic regression models, we examined adjusted odds ratios (aORs) and their corresponding 95% confidence intervals (CIs) of PTB and LBW subcategories in the association with maternal/infant characteristics, PNC status, and maternal CT, NG, and TP infections. In separate logistic regression models, we assessed the risk of these newborn outcomes stratified by PNC status. Adjustments were made for race/ethnicity, age, education, marital status, health insurance, liveborn parity, previous preterm birth, gestational hypertension, gestational diabetes, PNC status, smoking, and infant sex. Additionally, in a sensitivity analysis, we assessed the association with early, full, and late term births and the potential impact of unmeasured confounding using the E-value. CT (1.8%) was most prevalent STI in pregnancy, followed by NG (0.3%), and TP (0.1%). Non-Hispanic Black women, 20-24 years old, with a high school education, and on Medicaid had the highest rate of STIs. Around 96.6% of women reported receiving PNC and about 60.0% initiated PNC early in pregnancy. PTB and LBW were strongly associated with NG infection (12.2% and 12.1%, respectively) and late initiation/no PNC (8.5% and 7.6%, respectively), and ≤10 prenatal visits received (13.1% and 10.3%, respectively). The odds of PTB and LBW were 2.5- to 3-foldhigher for each STI among women who received ≤10 prenatal visits than >10 visits. Adequate prenatal care utilization and timely screening and treatment of maternal STIs can substantially reduce the burden of adverse newborn outcomes.

Keywords: low birthweight, prenatal care, preterm birth, sexually transmitted infections

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Authors: Sergio Haram Sarmiento, Arcady Ponosov

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Based on appropriate multivariate statistical methodology, we suggest a generic framework for efficient parameter estimation for ordinary differential equations and the corresponding nonlinear models. In this framework classical linear regression strategies is refined into a nonlinear regression by a locally linear modelling technique (known as metamodelling). The approach identifies those latent variables of the given model that accumulate most information about it among all approximations of the same dimension. The method is applied to several benchmark problems, in particular, to the so-called ”power-law systems”, being non-linear differential equations typically used in Biochemical System Theory.

Keywords: principal component analysis, generalized law of mass action, parameter estimation, metamodels

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Authors: Steven Woods

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The use of Corporate Social Responsibility Statements has become ubiquitous in society. The appeal to consumers by being a well-behaved social entity has become a strategy not just to ensure brand loyalty but also to further larger scale projects of corporate interests. Specifically, the use of CSR to position corporations as good planetary citizens involves not just self-promotion but also a way of transferring responsibility from systems to individuals. By using techniques labeled as “greenwashing” and emphasizing ethical consumption choices as the solution, corporations present themselves as good members of the community and pursuing sustainability. Ultimately, the primary function of Corporate Social Responsibility statements is to maintain the economic status quo of ongoing growth and consumption while presenting and environmentally progressive image to the public, as well as reassuring them corporate behavior is superior to government intervention. By analyzing the communication techniques utilized through content analysis of specific examples, along with an analysis of the frames of meaning constructed in the CSR statements, the practices of Corporate Responsibility and Sustainability will be addressed from an ethical perspective.

Keywords: corporate social responsibility, ethics, greenwashing, sustainability

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Authors: Nan KANG, Pierre Coddet, Hanlin Liao, Christian Coddet

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In this study, the almost dense eutectic Al-12Si alloys were fabricated by selective laser melting (SLM) from the powder mixture of pure Aluminum and pure Silicon, which show the mean particle sizes of 30 μm and 5μm respectively, under the argon environment. The image analysis shows that the highest value of relative density (95 %) was measured for the part obtained at the laser power of 280 W. X ray diffraction (XRD), Optical microscope (OM) and scanning electron microscope (SEM) equipped with X-ray energy dispersive spectroscopy (EDS) were employed to determine the microstructures of the SLM-processed Al-Si alloy, which illustrate that the SLM samples present the ultra-fine microstructure. The XRD results indicate that no clearly phase transformation happened during the SLM process. Additionally, the vaporization behavior of Aluminum was detected for the parts obtained at high laser power. Besides, the maximum microhardness value, about 95 Hv, was measured for the samples obtained at laser power of 280 W, and which shows the highest wear resistance.

Keywords: al-Si alloy, selective laser melting, wear behavior, microstructure

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Authors: Jihene Jebeniani

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We proposed an approach combining both the techniques of experimental economy and the flexibility of discrete choice models in order to test the loss aversion. Our main objective was to test the loss aversion of the Cumulative Prospect Theory (CPT). We developed an experimental laboratory in the context of the financial investments that aimed to analyze the attitude towards the risk of the investors. The study uses the lotteries and is basing on econometric modeling. The estimated model was the ordered probit.

Keywords: risk aversion, behavioral finance, experimental economic, lotteries, cumulative prospect theory

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Authors: Achim Kampker, Heiner H. Heimes, Mathias Ordung, Christoph Lienemann, Ansgar Hollah, Nemanja Sarovic

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Electric cars with their fast innovation cycles and their disruptive character offer a high degree of freedom regarding innovative design for remanufacturing. Remanufacturing increases not only the resource but also the economic efficiency by a prolonged product life time. The reduced power train wear of electric cars combined with high manufacturing costs for batteries allow new business models and even second life applications. Modular and intermountable designed battery packs enable the replacement of defective or outdated battery cells, allow additional cost savings and a prolongation of life time. This paper discusses opportunities for future remanufacturing value chains of electric cars and their battery components and how to address their potentials with elaborate designs. Based on a brief overview of implemented remanufacturing structures in different industries, opportunities of transferability are evaluated. In addition to an analysis of current and upcoming challenges, promising perspectives for a sustainable electric car circular economy enabled by design for remanufacturing are deduced. Two mathematical models describe the feasibility of pursuing a circular economy of lithium ion batteries and evaluate remanufacturing in terms of sustainability and economic efficiency. Taking into consideration not only labor and material cost but also capital costs for equipment and factory facilities to support the remanufacturing process, cost benefit analysis prognosticate that a remanufacturing battery can be produced more cost-efficiently. The ecological benefits were calculated on a broad database from different research projects which focus on the recycling, the second use and the assembly of lithium ion batteries. The results of this calculations show a significant improvement by remanufacturing in all relevant factors especially in the consumption of resources and greenhouse warming potential. Exemplarily suitable design guidelines for future remanufacturing lithium ion batteries, which consider modularity, interfaces and disassembly, are used to illustrate the findings. For one guideline, potential cost improvements were calculated and upcoming challenges are pointed out.

Keywords: circular economy, electric mobility, lithium ion batteries, remanufacturing

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Authors: Mahalakshmi Vivekanandan S.

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As per the recent changes happening in the global policies, climate-related changes and the impact it causes across every sector are viewed as green swan events – in essence, climate-related changes can often happen and lead to risk and a lot of uncertainty, but needs to be mitigated instead of considering them as black swan events. This brings about a question on how this risk can be computed so that the financial institutions can plan to mitigate it. Climate-related changes impact all risk types – credit risk, market risk, operational risk, liquidity risk, reputational risk and other risk types. And the models required to compute this has to consider the different industrial needs of the counterparty, as well as the factors that are contributing to this – be it in the form of different risk drivers, or the different transmission channels or the different approaches and the granular form of data availability. This brings out the suggestion that the climate-related changes, though it affects Pillar I risks, will be a Pillar II risk. This has to be modeled specifically based on the financial institution’s actual exposure to different industries instead of generalizing the risk charge. And this will have to be considered as the additional capital to be met by the financial institution in addition to their Pillar I risks, as well as the existing Pillar II risks. In this paper, the author presents a risk assessment framework to model and assess climate change risks - for both credit and market risks. This framework helps in assessing the different scenarios and how the different transition risks affect the risk associated with the different parties. This research paper delves into the topic of the increase in the concentration of greenhouse gases that in turn cause global warming. It then considers the various scenarios of having the different risk drivers impacting the Credit and market risk of an institution by understanding the transmission channels and also considering the transition risk. The paper then focuses on the industry that’s fast seeing a disruption: the automobile industry. The paper uses the framework to show how the climate changes and the change to the relevant policies have impacted the entire financial institution. Appropriate statistical models for forecasting, anomaly detection and scenario modeling are built to demonstrate how the framework can be used by the relevant agencies to understand their financial risks. The paper also focuses on the climate risk calculation for the Pillar II Capital calculations and how it will make sense for the bank to maintain this in addition to their regular Pillar I and Pillar II capital.

Keywords: capital calculation, climate risk, credit risk, pillar ii risk, scenario modeling

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Authors: Joshua Kim Schimpf, Kyun Doo Kim, Jaseok Heo

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In this study, the droplet behavior of under horizontal stratified flow regime for air and water flow in horizontal pipe experiments from a 0.24 m, 0.095 m, and 0.0486 m size diameter pipe are examined. The effects of gravity, pipe diameter, and turbulent diffusion on droplet deposition are considered. Models for droplet entrainment and deposition are proposed that considers developing length. Validation for experimental data dedicated from the REGARD, CEA and Williams, University of Illinois, experiment were performed using SPACE (Safety and Performance Analysis Code for Nuclear Power Plants).

Keywords: droplet, entrainment, deposition, horizontal

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Authors: Anna Avramenko, Heikki Haario

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This paper reports the development and application of a 2D depth-averaged model. The main goal of this contribution is to apply the depth averaged equations to a wind park model in which the treatment of the geometry, introduced on the mathematical model by the mass and momentum source terms. The depth-averaged model will be used in future to find the optimal position of wind turbines in the wind park. K-E and 2D LES turbulence models were consider in this article. 2D CFD simulations for one hill was done to check the depth-averaged model in practise.

Keywords: depth-averaged equations, numerical modeling, CFD, wind park model

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Authors: Abdulatif Abdulsalam, Mohamed Shaban

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This paper introduces interfacing and replication of electronic tools based on the MATLAB/ SIMULINK mock-up package. Mock-up components contain dc-dc converters, power issue rectifiers, motivation machines, dc gear, synchronous gear, and more entire systems. Power issue rectifier model includes solid state device models. The tools are the clear-cut structure and mock-up of complex energetic systems connecting with power electronic machines.

Keywords: power electronics, machine, MATLAB, simulink

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Authors: M. N. Islam, B. Boswell, Y. R. Ginting

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The influence of canned cycles and cutting parameters on hole quality in cryogenic drilling has been investigated experimentally and analytically. A three-level, three-parameter experiment was conducted by using the design-of-experiment methodology. The three levels of independent input parameters were the following: for canned cycles—a chip-breaking canned cycle (G73), a spot drilling canned cycle (G81), and a deep hole canned cycle (G83); for feed rates—0.2, 0.3, and 0.4 mm/rev; and for cutting speeds—60, 75, and 100 m/min. The selected work and tool materials were aluminum 6061-6T and high-speed steel (HSS), respectively. For cryogenic cooling, liquid nitrogen (LN2) was used and was applied externally. The measured output parameters were the three widely used quality characteristics of drilled holes—diameter error, circularity, and surface roughness. Pareto ANOVA was applied for analyzing the results. The findings revealed that the canned cycle has a significant effect on diameter error (contribution ratio 44.09%) and small effects on circularity and surface finish (contribution ratio 7.25% and 6.60%, respectively). The best results for the dimensional accuracy and surface roughness were achieved by G81. G73 produced the best circularity results; however, for dimensional accuracy, it was the worst level.

Keywords: circularity, diameter error, drilling canned cycle, pareto ANOVA, surface roughness

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Authors: Weiming Hu, Xu Li, Xiaonan Li, Zhong Xu, Li Yuan, Xuan Dong

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Maneuver decision-making plays a critical role in high-performance intelligent driving. This paper proposes a risk assessment-based decision-making network (RADMN) to address the problem of driving strategy for the commercial vehicle. RADMN integrates two networks, aiming at identifying the risk degree of collision and rollover and providing decisions to ensure the effectiveness and reliability of driving strategy. In the risk assessment module, risk degrees of the backward collision, forward collision and rollover are quantified for hazard recognition. In the decision module, a deep reinforcement learning based on multi-objective optimization (DRL-MOO) algorithm is designed, which comprehensively considers the risk degree and motion states of each traffic participant. To evaluate the performance of the proposed framework, Prescan/Simulink joint simulation was conducted in highway scenarios. Experimental results validate the effectiveness and reliability of the proposed RADMN. The output driving strategy can guarantee the safety and provide key technical support for the realization of autonomous driving of commercial vehicles.

Keywords: decision-making strategy, risk assessment, multi-objective optimization, commercial vehicle

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Authors: V. K. Arora, Suraj Prakash

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Pile foundations are provided to transfer the vertical and horizontal loads of superstructures like high rise buildings, bridges, offshore structures etc. to the deep strata in the soil. These vertical and horizontal loads are due to the loads coming from the superstructure and wind, water thrust, earthquake, and earth pressure, respectively. In a pile foundation, piles are used in groups. Vertical piles in a group of piles are more efficient to take vertical loads as compared to horizontal loads and when the horizontal load per pile exceeds the bearing capacity of the vertical piles in that case batter piles are used with vertical piles because batter piles can take more lateral loads than vertical piles. In this paper, a model study was conducted on three vertical pile group with single positive and negative battered pile subjected to lateral loads. The batter angle for battered piles was ±35◦ with the vertical axis. Piles were spaced at 2.5d (d=diameter of pile) to each other. The soil used for model test was cohesionless soil. Lateral loads were applied in three stages on all the pile groups individually and it was found that under the repeated action of lateral loading, the deflection of the piles increased under the same loading. After comparing the results, it was found that the pile group with positive batter pile fails at 28 kgf and the pile group with negative batter pile fails at 24 kgf so it shows that positive battered piles are stronger than the negative battered piles.

Keywords: vertical piles, positive battered piles, negative battered piles, cohesionless soil, lateral loads, model test

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Authors: Jatesh Kathpalia, Subhash Chander

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Violence against women has spread into a global epidemic. This has debilitating effect over the performance of women. Due to deep-rooted values, traditional Indian culture women fear the consequences of reporting violence and declare an unwillingness to subject themselves to the shame of being identified as battered women. Main interest was to study types of domestic violence which women face and to encourage them to report the matter. The study involved understanding the nature, extent and types of domestic violence. Two hundred rural women respondents were selected at random, interview schedule was prepared, and victims afflicted with domestic violence were identified. Data were collected and analyzed for different forms of domestic violence faced by women. 60% of the respondents faced domestic violence in different forms. Out of 120 women who were affected, 92.5% faced emotional, 90.8% faced verbal, 49.1% faced economic and 58.3% faced physical violence. 45.0% faced violence within three months of the marriage. Out of these, only 6.6% reported the violence to the police. Frequently faced forms of violence were slapping (27.1%), beating (24.3%) and starvation (25.7%). Number of women who were not allowed to spend money of their own stood at 30.5%. About 50% victims of emotional violence were facing constant criticism by their in-laws. Significant association was found between age, education and socio-economic status of the respondents and domestic violence. Rural women in Haryana face grave problem of domestic violence which need to be curbed for improving condition of women in society.

Keywords: domestic violence against women, economic, emotional, physical and verbal violence, marriage, rural women

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Authors: Ayadi Aya, Ghorbel Oussama, M. Obeid Abdulfattah, Abid Mohamed

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Nowadays, many wireless sensor networks have been distributed in the real world to collect valuable raw sensed data. The challenge is to extract high-level knowledge from this huge amount of data. However, the identification of outliers can lead to the discovery of useful and meaningful knowledge. In the field of wireless sensor networks, an outlier is defined as a measurement that deviates from the normal behavior of sensed data. Many detection techniques of outliers in WSNs have been extensively studied in the past decade and have focused on classic based algorithms. These techniques identify outlier in the real transaction dataset. This survey aims at providing a structured and comprehensive overview of the existing researches on classification based outlier detection techniques as applicable to WSNs. Thus, we have identified key hypotheses, which are used by these approaches to differentiate between normal and outlier behavior. In addition, this paper tries to provide an easier and a succinct understanding of the classification based techniques. Furthermore, we identified the advantages and disadvantages of different classification based techniques and we presented a comparative guide with useful paradigms for promoting outliers detection research in various WSN applications and suggested further opportunities for future research.

Keywords: bayesian networks, classification-based approaches, KPCA, neural networks, one-class SVM, outlier detection, wireless sensor networks

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Authors: Juzhong Tan, William Kerr

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Roasting is one critical procedure in chocolate processing, where special favors are developed, moisture content is decreased, and better processing properties are developed. Therefore, determination of roasting degree of cocoa bean is important for chocolate manufacturers to ensure the quality of chocolate products, and it also decides the commercial value of cocoa beans collected from cocoa farmers. The roasting degree of cocoa beans currently relies on human specialists, who sometimes are biased, and chemical analysis, which take long time and are inaccessible to many manufacturers and farmers. In this study, a self-made electronic nose system consists of gas sensors (TGS 800 and 2000 series) was used to detecting the gas generated by cocoa beans with a different roasting degree (0min, 20min, 30min, and 40min) and the signals collected by gas sensors were used to train a three-layers ANN. Chemical analysis of the graded beans was operated by traditional GC-MS system and the contents of volatile chemical compounds were used to train another ANN as a reference to electronic nosed signals trained ANN. Both trained ANN were used to predict cocoa beans with a different roasting degree for validation. The best accuracy of grading achieved by electronic nose signals trained ANN (using signals from TGS 813 826 820 880 830 2620 2602 2610) turned out to be 96.7%, however, the GC trained ANN got the accuracy of 83.8%.

Keywords: artificial neutron network, cocoa bean, electronic nose, roasting

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Authors: John M. Lyne, K. Andrea Scott

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In fluid dynamics, direct numerical simulations (DNS) of turbulent flows require large amounts of nodes to appropriately resolve all scales of energy transfer. Due to the size of these databases, sharing these datasets amongst the academic community is a challenge. Recent work has been done to investigate the use of super-resolution to enable database sharing, where a low-resolution flow field is super-resolved to high resolutions using a neural network. Recently, Generative Adversarial Networks (GAN) have grown in popularity with impressive results in the generation of faces, landscapes, and more. This work investigates the generation of unique high-resolution channel flow velocity fields from a low-dimensional latent space using a GAN. The training objective of the GAN is to generate samples in which the distribution of the generated samplesis ideally indistinguishable from the distribution of the training data. In this study, the network is trained using samples drawn from a statistically stationary channel flow at a Reynolds number of 560. Results show that the turbulent statistics and energy spectra of the generated flow fields are within reasonable agreement with those of the DNS data, demonstrating that GANscan produce the intricate multi-scale phenomena of turbulence.

Keywords: computational fluid dynamics, channel flow, turbulence, generative adversarial network

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Authors: Syue-Liang Lin, C. Allen Chang

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Luminescence imaging is an important technique used in biomedical research and clinical diagnostic applications in recent years. Concurrently, the development of NIR luminescence probes / imaging contrast agents has helped the understanding of the structural and functional properties of cells and animals. Photodynamic therapy (PDT) is used clinically to treat a wide range of medical conditions, but the therapeutic efficacy of general PDT for deeper tumor was limited by the penetration of excitation source. The tumor targeting biomedical nanomaterials UCNP@PS (upconversion nanoparticle conjugated with photosensitizer) for photodynamic therapy and near-infrared imaging of cancer will be developed in our study. Synthesis and characterization of biomedical nanomaterials were completed in this studies. The spectrum of UCNP was characterized by photoluminescence spectroscopy and the morphology was characterized by Transmission Electron Microscope (TEM). TEM and XRD analyses indicated that these nanoparticles are about 20~50 nm with hexagonal phase. NaYF₄:Ln³⁺ (Ln= Yb, Nd, Er) upconversion nanoparticles (UCNPs) with core / shell structure, synthesized by thermal decomposition method in 300°C, have the ability to emit visible light (upconversion: 540 nm, 660 nm) and near-infrared with longer wavelength (downconversion: NIR: 980 nm, 1525 nm) by absorbing 800 nm NIR laser. The information obtained from these studies would be very useful for applications of these nanomaterials for bio-luminescence imaging and photodynamic therapy of deep tumor tissue in the future.

Keywords: Near Infrared (NIR), lanthanide, core-shell structure, upconversion, theranostics

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Authors: Zahirah Dhurmeea, Iker Zudaire, Heidi Pethybridge, Emmanuel Chassot, Maria Cedras, Natacha Nikolic, Jerome Bourjea, Wendy West, Chandani Appadoo, Nathalie Bodin

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Scientific advice on the status of fish stocks relies on indicators that are based on strong assumptions on biological parameters such as condition, maturity and fecundity. Currently, information on the biology of albacore tuna, Thunnus alalunga, in the Indian Ocean is scarce. Consequently, many parameters used in stock assessment models for Indian Ocean albacore originate largely from other studied stocks or species of tuna. Inclusion of incorrect biological data in stock assessment models would lead to inappropriate estimates of stock status used by fisheries manager’s to establish future catch allowances. The reproductive biology of albacore tuna in the western Indian Ocean was examined through analysis of the sex ratio, spawning season, length-at-maturity (L50), spawning frequency, fecundity and fish condition. In addition, the total lipid content (TL) and lipid class composition in the gonads, liver and muscle tissues of female albacore during the reproductive cycle was investigated. A total of 923 female and 867 male albacore were sampled from 2013 to 2015. A bias in sex-ratio was found in favour of females with fork length (LF) <100 cm. Using histological analyses and gonadosomatic index, spawning was found to occur between 10°S and 30°S, mainly to the east of Madagascar from October to January. Large females contributed more to reproduction through their longer spawning period compared to small individuals. The L50 (mean ± standard error) of female albacore was estimated at 85.3 ± 0.7 cm LF at the vitellogenic 3 oocyte stage maturity threshold. Albacore spawn on average every 2.2 days within the spawning region and spawning months from November to January. Batch fecundity varied between 0.26 and 2.09 million eggs and the relative batch fecundity (mean  standard deviation) was estimated at 53.4 ± 23.2 oocytes g-1 of somatic-gutted weight. Depending on the maturity stage, TL in ovaries ranged from 7.5 to 577.8 mg g-1 of wet weight (ww) with different proportions of phospholipids (PL), wax esters (WE), triacylglycerol (TAG) and sterol (ST). The highest TL were observed in immature (mostly TAG and PL) and spawning capable ovaries (mostly PL, WE and TAG). Liver TL varied from 21.1 to 294.8 mg g-1 (ww) and acted as an energy (mainly TAG and PL) storage prior to reproduction when the lowest TL was observed. Muscle TL varied from 2.0 to 71.7 g-1 (ww) in mature females without a clear pattern between maturity stages, although higher values of up to 117.3 g-1 (ww) was found in immature females. TL results suggest that albacore could be viewed predominantly as a capital breeder relying mostly on lipids stored before the onset of reproduction and with little additional energy derived from feeding. This study is the first one to provide new information on the reproductive development and classification of albacore in the western Indian Ocean. The reproductive parameters will reduce uncertainty in current stock assessment models which will eventually promote sustainability of the fishery.

Keywords: condition, size-at-maturity, spawning behaviour, temperate tuna, total lipid content

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