Search results for: complexity ontology

Authors: Erica Siqueira, Adriana Bin, Rachel Stefanuto

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The paper aims to identify and to discuss the impact and results of ex-ante, mid-term and ex-post evaluation initiatives in Brazilian Social Enterprises from the point of view of the entrepreneurs and investors, highlighting the processes involved in these activities and their aftereffects. The study was conducted using a descriptive methodology, primarily qualitative. A multiple-case study was used, and, for that, semi-structured interviews were conducted with ten entrepreneurs in the (i) social finance, (ii) education, (iii) health, (iv) citizenship and (v) green tech fields, as well as three representatives of various impact investments, which are (i) venture capital, (ii) loan and (iii) equity interest areas. Convenience (non-probabilistic) sampling was adopted to select both businesses and investors, who voluntarily contributed to the research. The evaluation is still incipient in most of the studied business cases. Some stand out by adopting well-known methodologies like Global Impact Investing Report System (GIIRS), but still, have a lot to improve in several aspects. Most of these enterprises use nonexperimental research conducted by their own employees, which is ordinarily not understood as 'golden standard' to some authors in the area. Nevertheless, from the entrepreneur point of view, it is possible to identify that most of them including those routines in some extent in their day-by-day activities, despite the difficulty they have of the business in general. In turn, the investors do not have overall directions to establish evaluation initiatives in respective enterprises; they are funding. There is a mechanism of trust, and this is, usually, enough to prove the impact for all stakeholders. The work concludes that there is a large gap between what the literature states in regard to what should be the best practices in these businesses and what the enterprises really do. The evaluation initiatives must be included in some extension in all enterprises in order to confirm social impact that they realize. Here it is recommended the development and adoption of more flexible evaluation mechanisms that consider the complexity involved in these businesses’ routines. The reflections of the research also suggest important implications for the field of Social Enterprises, whose practices are far from what the theory preaches. It highlights the risk of the legitimacy of these enterprises that identify themselves as 'social impact', sometimes without the proper proof based on causality data. Consequently, this makes the field of social entrepreneurship fragile and susceptible to questioning, weakening the ecosystem as a whole. In this way, the top priorities of these enterprises must be handled together with the results and impact measurement activities. Likewise, it is recommended to perform further investigations that consider the trade-offs between impact versus profit. In addition, research about gender, the entrepreneur motivation to call themselves as Social Enterprises, and the possible unintended consequences from these businesses also should be investigated.

Keywords: evaluation practices, impact, results, social enterprise, social entrepreneurship ecosystem

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Authors: M. Kharrat, G. Moreau, Z. Aboura

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The latest advances in the weaving industry, combined with increasingly sophisticated means of materials processing, have made it possible to produce complex 3D composite structures. Mainly used in aeronautics, composite materials with 3D architecture offer better mechanical properties than 2D reinforced composites. Nevertheless, these materials require a good understanding of their behavior. Because of the complexity of such materials, the damage mechanisms are multiple, and the scenario of their appearance and evolution depends on the nature of the exerted solicitations. The AE technique is a well-established tool for discriminating between the damage mechanisms. Suitable sensors are used during the mechanical test to monitor the structural health of the material. Relevant AE-features are then extracted from the recorded signals, followed by a data analysis using pattern recognition techniques. In order to better understand the damage scenarios of interlock composite materials, a multi-instrumentation was set-up in this work for tracking damage initiation and development, especially in the vicinity of the first significant damage, called macro-damage. The deployed instrumentation includes video-microscopy, Digital Image Correlation, Acoustic Emission (AE) and micro-tomography. In this study, a multi-variable AE data analysis approach was developed for the discrimination between the different signal classes representing the different emission sources during testing. An unsupervised classification technique was adopted to perform AE data clustering without a priori knowledge. The multi-instrumentation and the clustered data served to label the different signal families and to build a learning database. This latter is useful to construct a supervised classifier that can be used for automatic recognition of the AE signals. Several materials with different ingredients were tested under various solicitations in order to feed and enrich the learning database. The methodology presented in this work was useful to refine the damage threshold for the new generation materials. The damage mechanisms around this threshold were highlighted. The obtained signal classes were assigned to the different mechanisms. The isolation of a 'noise' class makes it possible to discriminate between the signals emitted by damages without resorting to spatial filtering or increasing the AE detection threshold. The approach was validated on different material configurations. For the same material and the same type of solicitation, the identified classes are reproducible and little disturbed. The supervised classifier constructed based on the learning database was able to predict the labels of the classified signals.

Keywords: acoustic emission, classifier, damage mechanisms, first damage threshold, interlock composite materials, pattern recognition

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Authors: Zheng Yuxun

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This review critically assesses the advancements and prospective developments in defect detection methodologies within the semiconductor industry, an essential domain that significantly affects the operational efficiency and reliability of electronic components. As semiconductor devices continue to decrease in size and increase in complexity, the precision and efficacy of defect detection strategies become increasingly critical. Tracing the evolution from traditional manual inspections to the adoption of advanced technologies employing automated vision systems, artificial intelligence (AI), and machine learning (ML), the paper highlights the significance of precise defect detection in semiconductor manufacturing by discussing various defect types, such as crystallographic errors, surface anomalies, and chemical impurities, which profoundly influence the functionality and durability of semiconductor devices, underscoring the necessity for their precise identification. The narrative transitions to the technological evolution in defect detection, depicting a shift from rudimentary methods like optical microscopy and basic electronic tests to more sophisticated techniques including electron microscopy, X-ray imaging, and infrared spectroscopy. The incorporation of AI and ML marks a pivotal advancement towards more adaptive, accurate, and expedited defect detection mechanisms. The paper addresses current challenges, particularly the constraints imposed by the diminutive scale of contemporary semiconductor devices, the elevated costs associated with advanced imaging technologies, and the demand for rapid processing that aligns with mass production standards. A critical gap is identified between the capabilities of existing technologies and the industry's requirements, especially concerning scalability and processing velocities. Future research directions are proposed to bridge these gaps, suggesting enhancements in the computational efficiency of AI algorithms, the development of novel materials to improve imaging contrast in defect detection, and the seamless integration of these systems into semiconductor production lines. By offering a synthesis of existing technologies and forecasting upcoming trends, this review aims to foster the dialogue and development of more effective defect detection methods, thereby facilitating the production of more dependable and robust semiconductor devices. This thorough analysis not only elucidates the current technological landscape but also paves the way for forthcoming innovations in semiconductor defect detection.

Keywords: semiconductor defect detection, artificial intelligence in semiconductor manufacturing, machine learning applications, technological evolution in defect analysis

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Authors: E. Menga, S. Hernandez

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Finite Element Models (FEMs) are widely used in order to study and predict the dynamic properties of structures and usually, the prediction can be obtained with much more accuracy in the case of a single component than in the case of assemblies. Especially for structural dynamics studies, in the low and middle frequency range, most complex FEMs can be seen as assemblies made by linear components joined together at interfaces. From a modelling and computational point of view, these types of joints can be seen as localized sources of stiffness and damping and can be modelled as lumped spring/damper elements, most of time, characterized by nonlinear constitutive laws. On the other side, most of FE programs are able to run nonlinear analysis in time-domain. They treat the whole structure as nonlinear, even if there is one nonlinear degree of freedom (DOF) out of thousands of linear ones, making the analysis unnecessarily expensive from a computational point of view. In this work, a methodology in order to obtain the nonlinear frequency response of structures, whose nonlinearities can be considered as localized sources, is presented. The work extends the well-known Structural Dynamic Modification Method (SDMM) to a nonlinear set of modifications, and allows getting the Nonlinear Frequency Response Functions (NLFRFs), through an ‘updating’ process of the Linear Frequency Response Functions (LFRFs). A brief summary of the analytical concepts is given, starting from the linear formulation and understanding what the implications of the nonlinear one, are. The response of the system is formulated in both: time and frequency domain. First the Modal Database is extracted and the linear response is calculated. Secondly the nonlinear response is obtained thru the NL SDMM, by updating the underlying linear behavior of the system. The methodology, implemented in MATLAB, has been successfully applied to estimate the nonlinear frequency response of two systems. The first one is a two DOFs spring-mass-damper system, and the second example takes into account a full aircraft FE Model. In spite of the different levels of complexity, both examples show the reliability and effectiveness of the method. The results highlight a feasible and robust procedure, which allows a quick estimation of the effect of localized nonlinearities on the dynamic behavior. The method is particularly powerful when most of the FE Model can be considered as acting linearly and the nonlinear behavior is restricted to few degrees of freedom. The procedure is very attractive from a computational point of view because the FEM needs to be run just once, which allows faster nonlinear sensitivity analysis and easier implementation of optimization procedures for the calibration of nonlinear models.

Keywords: frequency response, nonlinear dynamics, structural dynamic modification, softening effect, rubber

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Authors: Tingwei Shu, Dong Zhou, Chengjun Guo

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Semantic communication is an emerging form of communication that realize intelligent communication by extracting semantic information of data at the source and transmitting it, and recovering the data at the receiving end. It can effectively solve the problem of data transmission under the situation of large data volume, low SNR and restricted bandwidth. With the development of Deep Learning, semantic communication further matures and is gradually applied in the fields of the Internet of Things, Uumanned Air Vehicle cluster communication, remote sensing scenarios, etc. We propose an improved semantic communication system for the situation where the data volume is huge and the spectrum resources are limited during the transmission of remote sensing images. At the transmitting, we need to extract the semantic information of remote sensing images, but there are some problems. The traditional semantic communication system based on Convolutional Neural Network cannot take into account the global semantic information and local semantic information of the image, which results in less-than-ideal image recovery at the receiving end. Therefore, we adopt the improved vision-Transformer-based structure as the semantic encoder instead of the mainstream one using CNN to extract the image semantic features. In this paper, we first perform pre-processing operations on remote sensing images to improve the resolution of the images in order to obtain images with more semantic information. We use wavelet transform to decompose the image into high-frequency and low-frequency components, perform bilinear interpolation on the high-frequency components and bicubic interpolation on the low-frequency components, and finally perform wavelet inverse transform to obtain the preprocessed image. We adopt the improved Vision-Transformer structure as the semantic coder to extract and transmit the semantic information of remote sensing images. The Vision-Transformer structure can better train the huge data volume and extract better image semantic features, and adopt the multi-layer self-attention mechanism to better capture the correlation between semantic features and reduce redundant features. Secondly, to improve the coding efficiency, we reduce the quadratic complexity of the self-attentive mechanism itself to linear so as to improve the image data processing speed of the model. We conducted experimental simulations on the RSOD dataset and compared the designed system with a semantic communication system based on CNN and image coding methods such as BGP and JPEG to verify that the method can effectively alleviate the problem of excessive data volume and improve the performance of image data communication.

Keywords: semantic communication, transformer, wavelet transform, data processing

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Authors: Matjaž Šraml, Marko Renčelj, Tomaž Tollazzi, Chiara Gruden

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Road safety is a worldwide issue with numerous and heterogeneous factors influencing it. On the side, driver state – comprising distraction/inattention, fatigue, drowsiness, extreme emotions, and socio-cultural factors highly affect road safety. On the other side, the vehicle state has an important role in mitigating (or not) the road risk. Finally, the road environment is still one of the main determinants of road safety, defining driving task complexity. At the same time, thanks to technological development, a lot of detailed data is easily available, creating opportunities for the detection of driver state, vehicle characteristics and road conditions and, consequently, for the design of ad hoc interventions aimed at improving driver performance, increase awareness and mitigate road risks. This is the challenge faced by the i-DREAMS project. i-DREAMS, which stands for a smart Driver and Road Environment Assessment and Monitoring System, is a 3-year project funded by the European Union’s Horizon 2020 research and innovation program. It aims to set up a platform to define, develop, test and validate a ‘Safety Tolerance Zone’ to prevent drivers from getting too close to the boundaries of unsafe operation by mitigating risks in real-time and after the trip. After the definition and development of the Safety Tolerance Zone concept and the concretization of the same in an Advanced driver-assistance system (ADAS) platform, the system was tested firstly for 2 months in a driving simulator environment in 5 different countries. After that, naturalistic driving studies started for a 10-month period (comprising a 1-month pilot study, 3-month baseline study and 6 months study implementing interventions). Currently, the project team has approved a common evaluation approach, and it is developing the assessment of the usage and outcomes of the i-DREAMS system, which is turning positive insights. The i-DREAMS consortium consists of 13 partners, 7 engineering universities and research groups, 4 industry partners and 2 partners (European Transport Safety Council - ETSC - and POLIS cities and regions for transport innovation) closely linked to transport safety stakeholders, covering 8 different countries altogether.

Keywords: advanced driver assistant systems, driving simulator, safety tolerance zone, traffic safety

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Authors: Mwehe Mathenge, Ben G. J. S. Sonneveld, Jacqueline E. W. Broerse

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Smallholder farmers are important drivers of agriculture productivity, food security, and poverty reduction in Sub-Saharan Africa. However, they are faced with myriad challenges in their efforts at participating in agribusiness markets. How the geographic explicit factors existing at the local level interact to impede smallholder farmers' decision to participates (or not) in agribusiness markets is not well understood. Deconstructing the spatial complexity of the local environment could provide a deeper insight into how geographically explicit determinants promote or impede resource-poor smallholder farmers from participating in agribusiness. This paper’s objective was to identify, map, and analyze local spatial autocorrelation in factors that impede poor smallholders from participating in agribusiness markets. Data were collected using geocoded researcher-administered survey questionnaires from 392 households in Western Kenya. Three spatial statistics methods in geographic information system (GIS) were used to analyze data -Global Moran’s I, Cluster and Outliers Analysis (Anselin Local Moran’s I), and geographically weighted regression. The results of Global Moran’s I reveal the presence of spatial patterns in the dataset that was not caused by spatial randomness of data. Subsequently, Anselin Local Moran’s I result identified spatially and statistically significant local spatial clustering (hot spots and cold spots) in factors hindering smallholder participation. Finally, the geographically weighted regression results unearthed those specific geographic explicit factors impeding market participation in the study area. The results confirm that geographically explicit factors are indispensable in influencing the smallholder farming decisions, and policymakers should take cognizance of them. Additionally, this research demonstrated how geospatial explicit analysis conducted at the local level, using geographically disaggregated data, could help in identifying households and localities where the most impoverished and resource-poor smallholder households reside. In designing spatially targeted interventions, policymakers could benefit from geospatial analysis methods in understanding complex geographic factors and processes that interact to influence smallholder farmers' decision-making processes and choices.

Keywords: agribusiness markets, GIS, smallholder farmers, spatial statistics, disaggregated spatial data

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Authors: Ju-Hong Lee, Ching-Wei Liao

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An adaptive array beamformer is designed for automatically preserving the desired signals while cancelling interference and noise. Providing robustness against model mismatches and tracking possible environment changes calls for robust adaptive beamforming techniques. The design criterion yields the well-known generalized sidelobe canceller (GSC) beamformer. In practice, the knowledge of the desired steering vector can be imprecise, which often occurs due to estimation errors in the DOA of the desired signal or imperfect array calibration. In these situations, the SOI is considered as interference, and the performance of the GSC beamformer is known to degrade. This undesired behavior results in a reduction of the array output signal-to-interference plus-noise-ratio (SINR). Therefore, it is worth developing robust techniques to deal with the problem due to local scattering environments. As to the implementation of adaptive beamforming, the required computational complexity is enormous when the array beamformer is equipped with massive antenna array sensors. To alleviate this difficulty, a generalized sidelobe canceller (GSC) with partially adaptivity for less adaptive degrees of freedom and faster adaptive response has been proposed in the literature. Unfortunately, it has been shown that the conventional GSC-based adaptive beamformers are usually very sensitive to the mismatch problems due to local scattering situations. In this paper, we present an effective GSC-based beamformer against the mismatch problems mentioned above. The proposed GSC-based array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. We utilize the predefined steering vector and a presumed angle tolerance range to carry out the required estimation for obtaining an appropriate steering vector. A matrix associated with the direction vector of signal sources is first created. Then projection matrices related to the matrix are generated and are utilized to iteratively estimate the actual direction vector of the desired signal. As a result, the quiescent weight vector and the required signal blocking matrix required for performing adaptive beamforming can be easily found. By utilizing the proposed GSC-based beamformer, we find that the performance degradation due to the considered local scattering environments can be effectively mitigated. To further enhance the beamforming performance, a signal subspace projection matrix is also introduced into the proposed GSC-based beamformer. Several computer simulation examples show that the proposed GSC-based beamformer outperforms the existing robust techniques.

Keywords: adaptive antenna beamforming, local scattering, signal blocking, steering mismatch

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Authors: Qiyao Han, Xianhai Meng

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Urban infrastructures refer to the fundamental facilities and systems that serve cities. Due to the global climate change and human activities in recent years, many urban areas around the world are facing enormous challenges from natural and man-made disasters, like flood, earthquake and terrorist attack. For this reason, urban resilience to disasters has attracted increasing attention from researchers and practitioners. Given the complexity of infrastructure systems and the uncertainty of disasters, this paper suggests that studies of resilience could focus on urban functional sustainability (in social, economic and environmental dimensions) supported by infrastructure systems under disturbance. It is supposed that urban infrastructure systems with high resilience should be able to reconfigure themselves without significant declines in critical functions (services), such as primary productivity, hydrological cycles, social relations and economic prosperity. Despite that some methods have been developed to integrate the resilience and sustainability of individual infrastructure components, more work is needed to enable system-level integration. This research presents a conceptual analysis framework for integrating resilience and sustainability based on fractal theory. It is believed that the ability of an ecological system to maintain structure and function in face of disturbance and to reorganize following disturbance-driven change is largely dependent on its self-similar and hierarchical fractal structure, in which cross-scale resilience is produced by the replication of ecosystem processes dominating at different levels. Urban infrastructure systems are analogous to ecological systems because they are interconnected, complex and adaptive, are comprised of interconnected components, and exhibit characteristic scaling properties. Therefore, analyzing resilience of ecological system provides a better understanding about the dynamics and interactions of infrastructure systems. This paper discusses fractal characteristics of ecosystem resilience, reviews literature related to system-level infrastructure resilience, identifies resilience criteria associated with sustainability dimensions, and develops a conceptual analysis framework. Exploration of the relevance of identified criteria to fractal characteristics reveals that there is a great potential to analyze infrastructure systems based on fractal. In the conceptual analysis framework, it is proposed that in order to be resilient, urban infrastructure system needs to be capable of “maintaining” and “reorganizing” multi-scale critical functions under disasters. Finally, the paper identifies areas where further research efforts are needed.

Keywords: fractal, urban infrastructure, sustainability, system-level resilience

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Authors: Madhuka G. P. D. Udantha, Gihan V. Dias, Surangika Ranathunga

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Today Websites contain very interesting applications. But there are only few methodologies to analyze User navigations through the Websites and formulating if the Website is put to correct use. The web logs are only used if some major attack or malfunctioning occurs. Web Logs contain lot interesting dealings on users in the system. Analyzing web logs has become a challenge due to the huge log volume. Finding interesting patterns is not as easy as it is due to size, distribution and importance of minor details of each log. Web logs contain very important data of user and site which are not been put to good use. Retrieving interesting information from logs gives an idea of what the users need, group users according to their various needs and improve site to build an effective and efficient site. The model we built is able to detect attacks or malfunctioning of the system and anomaly detection. Logs will be more complex as volume of traffic and the size and complexity of web site grows. Unsupervised techniques are used in this solution which is fully automated. Expert knowledge is only used in validation. In our approach first clean and purify the logs to bring them to a common platform with a standard format and structure. After cleaning module web session builder is executed. It outputs two files, Web Sessions file and Indexed URLs file. The Indexed URLs file contains the list of URLs accessed and their indices. Web Sessions file lists down the indices of each web session. Then DBSCAN and EM Algorithms are used iteratively and recursively to get the best clustering results of the web sessions. Using homogeneity, completeness, V-measure, intra and inter cluster distance and silhouette coefficient as parameters these algorithms self-evaluate themselves to input better parametric values to run the algorithms. If a cluster is found to be too large then micro-clustering is used. Using Cluster Signature Module the clusters are annotated with a unique signature called finger-print. In this module each cluster is fed to Associative Rule Learning Module. If it outputs confidence and support as value 1 for an access sequence it would be a potential signature for the cluster. Then the access sequence occurrences are checked in other clusters. If it is found to be unique for the cluster considered then the cluster is annotated with the signature. These signatures are used in anomaly detection, prevent cyber attacks, real-time dashboards that visualize users, accessing web pages, predict actions of users and various other applications in Finance, University Websites, News and Media Websites etc.

Keywords: anomaly detection, clustering, pattern recognition, web sessions

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Authors: Christian Ihwiwhu, Nnamdi Obioha, Udeme John, Edward Bobade, Oghenerunor Bekibele, Adedeji Awujoola, Ibi-Ada Itotoi

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Understanding the complexity in the distribution of hydrocarbon in a simple structure with flow baffles and connectivity issues is critical in targeting and developing the remaining pay in a mature asset. Subtle facies changes (heterogeneity) can have a drastic impact on reservoir fluids movement, and this can be crucial to identifying sweet spots in mature fields. This study aims to evaluate selected reservoirs in Ovhor Field, Niger Delta, Nigeria, with the objective of optimising production from the field by targeting undeveloped oil reserves, bypassed pay, and gaining an improved understanding of the selected reservoirs to increase the company’s reservoir limits. The task at the Ovhor field is complicated by poor stratigraphic seismic resolution over the field. 3-D geological (sedimentology and stratigraphy) interpretation, use of results from quantitative interpretation, and proper understanding of production data have been used in recognizing flow baffles and undeveloped compartments in the field. The full field 3-D model has been constructed in such a way as to capture heterogeneities and the various compartments in the field to aid the proper simulation of fluid flow in the field for future production prediction, proper history matching and design of good trajectories to adequately target undeveloped oil in the field. Reservoir property models (porosity, permeability, and net-to-gross) have been constructed by biasing log interpreted properties to a defined environment of deposition model whose interpretation captures the heterogeneities expected in the studied reservoirs. At least, two scenarios have been modelled for most of the studied reservoirs to capture the range of uncertainties we are dealing with. The total original oil in-place volume for the four reservoirs studied is 157 MMstb. The cumulative oil and gas production from the selected reservoirs are 67.64 MMstb and 9.76 Bscf respectively, with current production rate of about 7035 bopd and 4.38 MMscf/d (as at 31/08/2019). Dynamic simulation and production forecast on the 4 reservoirs gave an undeveloped reserve of about 3.82 MMstb from two (2) identified oil restoration activities. These activities include side-tracking and re-perforation of existing wells. This integrated approach led to the identification of bypassed oil in some areas of the selected reservoirs and an improved understanding of the studied reservoirs. New wells have/are being drilled now to test the results of our studies, and the results are very confirmatory and satisfying.

Keywords: facies, flow baffle, bypassed pay, heterogeneities, history matching, reservoir limit

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Authors: Tengku Sepora Tengku Mahadi

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Where the speed of book writing lags behind the high need for such material for tertiary studies, translation offers a way to enhance the equilibrium in this demand-supply equation. Nevertheless, translation is confronted by obstacles that threaten its effectiveness. The primary challenge to the production of efficient translations may well be related to the text-type and in terms of its complexity. A text that is intricately written with unique rhetorical devices, subject-matter foundation and cultural references will undoubtedly challenge the translator. Longer time and greater effort would be the consequence. To understand these text-related challenges, the present paper set out to analyze a lawbook entitled Learning the Law by David Melinkoff. The book is chosen because it has often been used as a textbook or for reference in many law courses in the United Kingdom and has seen over thirteen editions; therefore, it can be said to be a worthy book for studies in law. Another reason is the existence of a ready translation in Malay. Reference to this translation enables confirmation to some extent of the potential problems that might occur in its translation. Understanding the organization and the language of the book will help translators to prepare themselves better for the task. They can anticipate the research and time that may be needed to produce an effective translation. Another premise here is that this text-type implies certain ways of writing and organization. Accordingly, it seems practicable to adopt the functional theory of language as suggested by Michael Halliday as its theoretical framework. Concepts of the context of culture, the context of situation and measures of the field, tenor and mode form the instruments for analysis. Additional examples from similar materials can also be used to validate the findings. Some interesting findings include the presence of several other text-types or sub-text-types in the book and the dependence on literary discourse and devices to capture the meanings better or add color to the dry field of law. In addition, many elements of culture can be seen, for example, the use of familiar alternatives, allusions, and even terminology and references that date back to various periods of time and languages. Also found are parts which discuss origins of words and terms that may be relevant to readers within the United Kingdom but make little sense to readers of the book in other languages. In conclusion, the textual analysis in terms of its functions and the linguistic and textual devices used to achieve them can then be applied as a guide to determine the effectiveness of the translation that is produced.

Keywords: functional theory of language, lawbook text-type, rhetorical devices, culture

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Authors: Yitian Ren, Liyin Shen, Tao Zhou, Xiao Li

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The past urbanization process in China has brought out series of problems, the Chinese government has then positioned small towns in essential roles for implementing the strategy 'The National New-type Urbanization Plan (2014-2020)'. As the connector and transfer station of cities and countryside, small towns are important force to narrow the gap between urban and rural area, and to achieve the mission of new-type urbanization in China. The sustainable development of small towns plays crucial role because cities are not capable enough to absorb the surplus rural population. Nevertheless, there are various types of barriers hindering the sustainable development of small towns, which led to the limited development of small towns and has presented a bottleneck in Chinese urbanization process. Therefore, this paper makes deep understanding of these barriers, thus effective actions can be taken to address them. And this paper chooses the perspective of Southwest China (refers to Sichuan province, Yunnan province, Guizhou province, Chongqing Municipality City and Tibet Autonomous Region), cause the urbanization rate in Southwest China is far behind the average urbanization level of the nation and the number of small towns accounts for a great proportion in mainland China, also the characteristics of small towns in Southwest China are distinct. This paper investigates the barriers of sustainable development of small towns which located in Southwest China by using the content analysis method, combing with the field work and interviews in sample small towns, then identified and concludes 18 barriers into four dimensions, namely, institutional barriers, economic barriers, social barriers and ecological barriers. Based on the research above, questionnaire survey and data analysis are implemented, thus the key barriers hinder the sustainable development of small towns in Southwest China are identified by using fuzzy set theory, those barriers are, lack of independent financial power, lack of construction land index, financial channels limitation, single industrial structure, topography variety and complexity, which mainly belongs to institutional barriers and economic barriers. In conclusion part, policy suggestions are come up with to improve the politic and institutional environment of small town development, also the market mechanism are supposed to be introduced to the development process of small towns, which can effectively overcome the economic barriers, promote the sustainable development of small towns, accelerate the in-situ urbanization by absorbing peasants in nearby villages, and achieve the mission of new-type urbanization in China from the perspective of people-oriented.

Keywords: barrier analysis, sustainable development, small town, Southwest China

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Authors: P. Vindin, R. Cordier, N. J. Wilson, H. Lee

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Engagement in community-based activities such as education, employment, and social relationships can improve the quality of life for individuals with Autism Spectrum Disorder (ASD). Community mobility is vital to attaining independence for individuals with ASD. Learning to drive and gaining a driver’s license is a critical link to community mobility; however, for individuals with ASD acquiring safe driving skills can be a challenging process. Issues related to anxiety, executive function, and social communication may affect driving behaviours. Driving training and education aimed at addressing barriers faced by learner drivers with ASD can help them improve their driving performance. A multi-site randomized controlled trial (RCT) was conducted to evaluate the effectiveness of an autism-specific driving training intervention for improving the on-road driving performance of learner drivers with ASD. The intervention was delivered via a training manual and interactive website consisting of five modules covering varying driving environments starting with a focus on off-road preparations and progressing through basic to complex driving skill mastery. Seventy-two learner drivers with ASD aged 16 to 35 were randomized using a blinded group allocation procedure into either the intervention or control group. The intervention group received 10 driving lessons with the instructors trained in the use of an autism-specific driving training protocol, whereas the control group received 10 driving lessons as usual. Learner drivers completed a pre- and post-observation drive using a standardized driving route to measure driving performance using the Driving Performance Checklist (DPC). They also completed anxiety, executive function, and social responsiveness measures. The findings showed that there were significant improvements in driving performance for both the intervention (d = 1.02) and the control group (d = 1.15). However, the differences were not significant between groups (p = 0.614) or study sites (p = 0.842). None of the potential moderator variables (anxiety, cognition, social responsiveness, and driving instructor experience) influenced driving performance. This study is an important step toward improving community mobility for individuals with ASD showing that an autism-specific driving training intervention can improve the driving performance of leaner drivers with ASD. It also highlighted the complexity of conducting a multi-site design even when sites were matched according to geography and traffic conditions. Driving instructors also need more and clearer information on how to communicate with learner drivers with restricted verbal expression.

Keywords: autism spectrum disorder, community mobility, driving training, transportation

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Authors: Jing Nan

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The air breakdown voltage in compact circuit breakers is a critical factor in the design and reliability of electrical distribution systems. This voltage determines the threshold at which the air insulation between conductors will fail or 'break down,' leading to an arc. This phenomenon is highly sensitive to the conditions within the breaker, such as the temperature and the distance between electrodes. Typically, air breakdown voltage models have been reliable for predicting failure under standard operational temperatures. However, in conditions post-arcing, where temperatures can soar above 2000K, these models face challenges due to the complex physics of ionization and electron behaviour at such high-energy states. Building upon the foundational understanding that the breakdown mechanism is initiated by free electrons and propelled by electric fields, which lead to ionization and, potentially, to avalanche or streamer formation, we acknowledge the complexity introduced by high-temperature environments. Recognizing the limitations of existing experimental data, a notable research gap exists in the accurate prediction of breakdown voltage at elevated temperatures, typically observed post-arcing, where temperatures exceed 2000K.To bridge this knowledge gap, we present a method that integrates gap distance and high-temperature effects into air breakdown voltage assessment. The proposed model is grounded in the physics of ionization, accounting for the dynamic behaviour of free electrons which, under intense electric fields at elevated temperatures, lead to thermal ionization and potentially reach the threshold for streamer formation as Meek's criterion. Employing the Saha equation, our model calculates equilibrium electron densities, adapting to the atmospheric pressure and the hot temperature regions indicative of post-arc temperature conditions. Our model is rigorously validated against established experimental data, demonstrating substantial improvements in predicting air breakdown voltage in the high-temperature regime. This work significantly improves the predictive power for air breakdown voltage under conditions that closely mimic operational stressors in compact circuit breakers. Looking ahead, the proposed methods are poised for further exploration in alternative insulating media, like SF6, enhancing the model's utility for a broader range of insulation technologies and contributing to the future of high-temperature electrical insulation research.

Keywords: air breakdown voltage, high-temperature insulation, compact circuit breakers, electrical discharge, saha equation

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Authors: Soroush Pakniyat-Jahromi, Jessica Bucciarelli, Souparno Mitra, Neda Motamedi, Ralph Amazan, Samuel Rothman, Jose Tiburcio, Douglas Reich, Vicente Liz

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Violence is defined as an act of physical force that is intended to cause harm and may lead to physical and/or psychological damage. Violence toward healthcare workers (HCWs) is more common in psychiatric settings, emergency departments, and nursing homes; however, healthcare workers in medical setting are not spared from such events. Workplace violence has a huge burden in the healthcare industry and has a major impact on the physical and mental wellbeing of staff. The purpose of this study is to compare the prevalence of patient agitation and violence in medical-surgical settings in BronxCare Hospital (BCH) Bronx, New York, one year before and during the COVID-19 pandemic. Data collection occurred between June 2021 and August 2021, while the sampling time was from 2019 to 2021. The data were separated into two separate time categories: pre-COVID-19 (03/2019-03/2020) and COVID-19 (03/2020-03/2021). We created frequency tables for 19 variables. We used a chi-square test to determine a variable's statistical significance. We tested all variables against “restraint type”, determining if a patient was violent or became violent enough to restrain. The restraint types were “chemical”, “physical”, or both. This analysis was also used to determine if there was a statistical difference between the pre-COVID-19 and COVID-19 timeframes. Our data shows that there was an increase in incidents of violence in COVID-19 era (03/2020-03/2021), with total of 194 (62.8%) reported events, compared to pre COVID-19 era (03/2019-03/2020) with 115 (37.2%) events (p: 0.01). Our final analysis, completed using a chi-square test, determined the difference in violence in patients between pre-COVID-19 and COVID-19 era. We then tested the violence marker against restraint type. The result was statistically significant (p: 0.01). This is the first paper to systematically review the prevalence of violence in medical-surgical units in a hospital in New York, pre COVID-19 and during the COVID-19 era. Our data is in line with the global trend of increased prevalence of patient agitation and violence in medical settings during the COVID-19 pandemic. Violence and its management is a challenge in healthcare settings, and the COVID-19 pandemic has brought to bear a complexity of circumstances, which may have increased its incidence. It is important to identify and teach healthcare workers the best preventive approaches in dealing with patient agitation, to decrease the number of restraints in medical settings, and to create a less restrictive environment to deliver care.

Keywords: COVID-19 pandemic, patient agitation, restraints, violence

Procedia PDF Downloads 113

Authors: Shankha Pratim Bhattacharya

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In general building repair and renovation projects are minor in nature. It requires less attention as the primary cost involvement is relatively small. Although the building repair and maintenance projects look simple, it involves much complexity during execution. Many of the present research indicate that few uncertain situations are usually linked with maintenance projects. Those may not be read properly in the planning stage of the projects, and finally, lead to time overrun. Building repair and maintenance become essential and periodical after commissioning of the building. In Institutional buildings, the regular maintenance projects also include addition –alteration, modification activities. Increase in the student admission, new departments, and sections, new laboratories and workshops, up gradation of existing laboratories are very common in the institutional buildings in the developing nations like India. The project becomes very critical because it undergoes space problem, architectural design issues, structural modification, etc. One of the prime factors in the institutional building maintenance and modification project is the time constraint. Mostly it required being executed a specific non-work time period. The present research considered only the institutional buildings of the Eastern part of India to analyse the repair and maintenance project delay. A general survey was conducted among the technical institutes to find the causes and corresponding nature of construction delay factors. Five technical institutes are considered in the present study with repair, renovation, modification and extension type of projects. Construction delay factors are categorically subdivided into four groups namely, material, manpower (works), Contract and Site. The survey data are collected for the nature of delay responsible for a specific project and the absolute amount of delay through proposed and actual duration of work. In the first stage of the paper, a relative importance index (RII) is proposed for the delay factors. The occurrence of the delay factors is also judged by its frequency-severity nature. Finally, the delay factors are then rated and linked with the type of work. In the second stage, a regression analysis is executed to establish an empirical relationship between the actual time of a project and the percentage of delay. It also indicates the impact of the factors for delay responsibility. Ultimately, the present paper makes an effort to identify the critical delay factors for the repair and renovation type project in the Eastern Indian Institutional building.

Keywords: delay factor, institutional building, maintenance, relative importance index, regression analysis, repair

Procedia PDF Downloads 232

Authors: Iyad Jadalhaq, Mohammed El Hadi El Maknouzi

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The place of Islamic law in the legal system of the UAE is best understood by introducing a differentiation between its role as a formal source of law and its influence as a material source of law. What this differentiation helps clarify is that the corpus of Islamic law constitutes a much deeper influence on adjudication, law-making and the legal profession in the UAE, than it might appear at first sight, by considering its formal position in the division of labor between courts, or legislative lists of sources of law. This paper aims to examine the role of Shariah in the UAE private law system by determining the comprehensiveness of Sharia in the legal system as a whole, and not in a limited way related to it as a source of law according to Article 1 of the Civil Transactions Law. Turning to the role of the Shariah as a formal source of law, it is useful to start from Article 1 of the UAE Civil Code. This provision lays out the formal hierarchy of sources of UAE private law, these being legislation, Islamic law, and custom. Hence, when deciding a civil dispute, a judge should first refer to positive legislation in force in the UAE. Lacking the rule to cover the case before him/her, the judge ought then to refer directly to Islamic law. If the matter lacks regulation in Islamic law, only then may the judge appeal to custom. Accordingly, in connection to civil transactions, Shariah is presented here, formally, as the second source of law. Still, Shariah law addresses many other issues beyond civil transactions, including matters of morals, worship, and belief. However, in Article 1 of the UAE Civil Code, the reference to Islamic law ought to be understood as limited to the rules it lays out for civil transactions. There are four main sets of courts in the judicial systems of the UAE, whose competence is based on whether a dispute touches upon civil and commercial transactions, criminal offenses, personal statuses, or labor relations. This sectorial and multi-tiered organization of courts as a whole constitutes an institutional development compatible with the long-standing affirmation in the Shariah of the legitimacy of the judiciary. Indeed, Islamic law authorizes the governing authorities to organize the judiciary, including by allocating specific types of cases to particular kinds of judges depending on the value of the case, or by assigning judges to a specific place in which they are to exercise their jurisdictional function. In view of this, the contemporary organization of courts in the UAE can be regarded as an organic adaptation, aligned with Shariah rules on the assignment of jurisdictional authority, to the growing complexity of modern society. Therefore, we can conclude to the comprehensive role of Shariah in the entire legal system of the United Arab Emirates, including legislation, a judicial system, institutional, and administrative work.

Keywords: Islamic jurisprudence, Shariah, UAE civil code, UAE private law

Procedia PDF Downloads 100

Authors: Sara A. Ben Lashihar

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The heritage building information modelling (HBIM) of the historical masonry buildings has expanded lately to meet the urgent needs for conservation and structural analysis. The masonry structures are unique features for ancient building architectures worldwide that have special cultural, spiritual, and historical significance. However, there is a research gap regarding the reliability of the HBIM modeling process of these structures. The HBIM modeling process of the masonry structures faces significant challenges due to the inherent complexity and uniqueness of their structural systems. Most of these processes are based on tracing the point clouds and rarely follow documents, archival records, or direct observation. The results of these techniques are highly abstracted models where the accuracy does not exceed LOD 200. The masonry assemblages, especially curved elements such as arches, vaults, and domes, are generally modeled with standard BIM components or in-place models, and the brick textures are graphically input. Hence, future investigation is necessary to establish a methodology to generate automatically parametric masonry components. These components are developed algorithmically according to mathematical and geometric accuracy and the validity of the survey data. The main aim of this paper is to provide a comprehensive review of the state of the art of the existing researches and papers that have been conducted on the HBIM modeling of the masonry structural elements and the latest approaches to achieve parametric models that have both the visual fidelity and high geometric accuracy. The paper reviewed more than 800 articles, proceedings papers, and book chapters focused on "HBIM and Masonry" keywords from 2017 to 2021. The studies were downloaded from well-known, trusted bibliographic databases such as Web of Science, Scopus, Dimensions, and Lens. As a starting point, a scientometric analysis was carried out using VOSViewer software. This software extracts the main keywords in these studies to retrieve the relevant works. It also calculates the strength of the relationships between these keywords. Subsequently, an in-depth qualitative review followed the studies with the highest frequency of occurrence and the strongest links with the topic, according to the VOSViewer's results. The qualitative review focused on the latest approaches and the future suggestions proposed in these researches. The findings of this paper can serve as a valuable reference for researchers, and BIM specialists, to make more accurate and reliable HBIM models for historic masonry buildings.

Keywords: HBIM, masonry, structure, modeling, automatic, approach, parametric

Procedia PDF Downloads 142

Authors: Marcin Stasiulewicz, Sebastian Filipkowski, Aneta Panuszko

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Background: The hallmark of neurodegenerative diseases, including Alzheimer's and Parkinson's diseases, is an aggregation of the abnormal forms of peptides and proteins. Water is essential to functioning biomolecules, and it is one of the key factors influencing protein folding and misfolding. However, the hydration studies of proteins are complicated due to the complexity of protein systems. The use of model compounds can facilitate the interpretation of results involving larger systems. Objectives: The goal of the research was to characterize the properties of the hydration water surrounding the two three-residue K peptide fragments INS (Isoleucine - Asparagine - Serine) and NSR (Asparagine - Serine - Arginine). Methods: Fourier-transform infrared spectra of aqueous solutions of the tripeptides were recorded on Nicolet 8700 spectrometer (Thermo Electron Co.) Measurements were carried out at 25°C for varying molality of solute. To remove oscillation couplings from water spectra and, consequently, obtain narrow O-D semi-heavy water bands (HDO), the isotopic dilution method of HDO in H₂O was used. The difference spectra method allowed us to isolate the tripeptide-affected HDO spectrum. Results: The structural and energetic properties of water affected by the tripeptides were compared to the properties of pure water. The shift of the values of the gravity center of bands (related to the mean energy of water hydrogen bonds) towards lower values with respect to the ones corresponding to pure water suggests that the energy of hydrogen bonds between water molecules surrounding tripeptides is higher than in pure water. A comparison of the values of the mean oxygen-oxygen distances in water affected by tripeptides and pure water indicates that water-water hydrogen bonds are shorter in the presence of these tripeptides. The analysis of differences in oxygen-oxygen distance distributions between the tripeptide-affected water and pure water indicates that around the tripeptides, the contribution of water molecules with the mean energy of hydrogen bonds decreases, and simultaneously the contribution of strong hydrogen bonds increases. Conclusions: It was found that hydrogen bonds between water molecules in the hydration sphere of tripeptides are shorter and stronger than in pure water. It means that in the presence of the tested tripeptides, the structure of water is strengthened compared to pure water. Moreover, it has been shown that in the vicinity of the Asparagine - Serine - Arginine, water forms stronger and shorter hydrogen bonds. Acknowledgments: This work was funded by the National Science Centre, Poland (grant 2017/26/D/NZ1/00497).

Keywords: amyloids, K-peptide, hydration, FTIR spectroscopy

Procedia PDF Downloads 157

Authors: Vinayak Malhotra, Samanyu Raina, Ajinkya Vajurkar

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Enhancing the rocket efficiency by controlling the external factors in solid rockets motors has been an active area of research for most of the terrestrial and extra-terrestrial system operations. Appreciable work has been done, but the complexity of the problem has prevented thorough understanding due to heterogenous heat and mass transfer. On record, severe issues have surfaced amounting to irreplaceable loss of mankind, instruments, facilities, and huge amount of money being invested every year. The coupled effect of an external heat source and external heat sink is an aspect yet to be articulated in combustion. Better understanding of this coupled phenomenon will induce higher safety standards, efficient missions, reduced hazard risks, with better designing, validation, and testing. The experiment will help in understanding the coupled effect of an external heat sink and heat source on the burning process, contributing in better combustion and fire safety, which are very important for efficient and safer rocket flights and space missions. Safety is the most prevalent issue in rockets, which assisted by poor combustion efficiency, emphasizes research efforts to evolve superior rockets. This signifies real, engineering, scientific, practical, systems and applications. One potential application is Solid Rocket Motors (S.R.M). The study may help in: (i) Understanding the effect on efficiency of core engines due to the primary boosters if considered as source, (ii) Choosing suitable heat sink materials for space missions so as to vary the efficiency of the solid rocket depending on the mission, (iii) Giving an idea about how the preheating of the successive stage due to previous stage acting as a source may affect the mission. The present work governs the temperature (resultant) and thus the heat transfer which is expected to be non-linear because of heterogeneous heat and mass transfer. The study will deepen the understanding of controlled inter-energy conversions and the coupled effect of external source/sink(s) surrounding the burning fuel eventually leading to better combustion thus, better propulsion. The work is motivated by the need to have enhanced fire safety and better rocket efficiency. The specific objective of the work is to understand the coupled effect of external heat source and sink on propellant burning and to investigate the role of key controlling parameters. Results as of now indicate that there exists a singularity in the coupled effect. The dominance of the external heat sink and heat source decides the relative rocket flight in Solid Rocket Motors (S.R.M).

Keywords: coupled effect, heat transfer, sink, solid rocket motors, source

Procedia PDF Downloads 199

Authors: Guoyu Wang, Meilian Zhang, Chunhui LI, Bing Ren

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In recent decades, a variety of floating structures have played a crucial role in ocean and marine engineering, such as ships, offshore platforms, floating breakwaters, fish farms, floating airports, etc. It is common for floating structures to suffer from loadings under waves, and the responses of the structures mounted in marine environments have a significant relation to the wave impacts. The interaction between surface waves and floating structures is one of the important issues in ship or marine structure design to increase performance and efficiency. With the progress of computational fluid dynamics, a number of numerical models based on the NS equations in the time domain have been developed to explore the above problem, such as the finite difference method or the finite volume method. Those traditional numerical simulation techniques for moving bodies are grid-based, which may encounter some difficulties when treating a large free surface deformation and a moving boundary. In these models, the moving structures in a Lagrangian formulation need to be appropriately described in grids, and the special treatment of the moving boundary is inevitable. Nevertheless, in the mesh-based models, the movement of the grid near the structure or the communication between the moving Lagrangian structure and Eulerian meshes will increase the algorithm complexity. Fortunately, these challenges can be avoided by the meshless particle methods. In the present study, a moving particle semi-implicit model is explored for the numerical simulation of fluid–structure interaction with surface flows, especially for coupling of fluid and moving rigid body. The equivalent momentum transfer method is proposed and derived for the coupling of fluid and rigid moving body. The structure is discretized into a group of solid particles, which are assumed as fluid particles involved in solving the NS equation altogether with the surrounding fluid particles. The momentum conservation is ensured by the transfer from those fluid particles to the corresponding solid particles. Then, the position of the solid particles is updated to keep the initial shape of the structure. Using the proposed method, the motions of a free-floating body in regular waves are numerically studied. The wave surface evaluation and the dynamic response of the floating body are presented. There is good agreement when the numerical results, such as the sway, heave, and roll of the floating body, are compared with the experimental and other numerical data. It is demonstrated that the presented MPS model is effective for the numerical simulation of fluid-structure interaction.

Keywords: floating body, fluid structure interaction, MPS, particle method, waves

Procedia PDF Downloads 48

Authors: Hamza Benzerrouk, Alexander Nebylov

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In classical GNSS/INS integration designs, the loosely coupled approach uses the GNSS derived position and the velocity as the measurements vector. This design is suboptimal from the standpoint of preventing GNSSoutliers/outages. The tightly coupled GPS/INS navigation filter mixes the GNSS pseudo range and inertial measurements and obtains the vehicle navigation state as the final navigation solution. The ultra‐tightly coupled GNSS/INS design combines the I (inphase) and Q(quadrature) accumulator outputs in the GNSS receiver signal tracking loops and the INS navigation filter function intoa single Kalman filter variant (EKF, UKF, SPKF, CKF and HCKF). As mentioned, EKF and UKF are the most used nonlinear filters in the literature and are well adapted to inertial navigation state estimation when integrated with GNSS signal outputs. In this paper, it is proposed to move a step forward with more accurate filters and modern approaches called Cubature and High Degree cubature Kalman Filtering methods, on the basis of previous results solving the state estimation based on INS/GNSS integration, Cubature Kalman Filter (CKF) and High Degree Cubature Kalman Filter with (HCKF) are the references for the recent developed generalized Cubature rule based Kalman Filter (GCKF). High degree cubature rules are the kernel of the new solution for more accurate estimation with less computational complexity compared with the Gauss-Hermite Quadrature (GHQKF). Gauss-Hermite Kalman Filter GHKF which is not selected in this work because of its limited real-time implementation in high-dimensional state-spaces. In ultra tightly or a deeply coupled GNSS/INS system is dynamics EKF is used with transition matrix factorization together with GNSS block processing which is well described in the paper and assumes available the intermediary frequency IF by using a correlator samples with a rate of 500 Hz in the presented approach. GNSS (GPS+GLONASS) measurements are assumed available and modern SPKF with Cubature Kalman Filter (CKF) are compared with new versions of CKF called high order CKF based on Spherical-radial cubature rules developed at the fifth order in this work. Estimation accuracy of the high degree CKF is supposed to be comparative to GHKF, results of state estimation are then observed and discussed for different initialization parameters. Results show more accurate navigation state estimation and more robust GNSS receiver when Ultra Tightly Coupled approach applied based on High Degree Cubature Kalman Filter.

Keywords: GNSS, INS, Kalman filtering, ultra tight integration

Procedia PDF Downloads 261

Authors: Cesar Vazquez-Gonzalez, Sophie Avila-Foucat, Leonardo Ortiz-Lozano, Patricia Moreno-Casasola, Alejandro Granados-Barba

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In the last twenty years, academic and scientific literature has been focused on understanding the processes and factors of coastal social-ecological systems vulnerability and resilience. Some scholars argue that resilience and vulnerability are isolated concepts due to their epistemological origin, while others note the existence of a strong resilience-vulnerability relationship. Here we present an ordinal logistic regression model based on the analytical framework about dynamic resilience-vulnerability interaction along adaptive cycle of complex systems and disasters process phases (during, recovery and learning). In this way, we demonstrate that 1) during the disturbance, absorptive capacity (resilience as a core of attributes) and external response capacity explain the probability of households capitals to diminish the damage, and exposure sets the thresholds about the amount of disturbance that households can absorb, 2) at recovery, absorptive capacity and external response capacity explain the probability of households capitals to recovery faster (resilience as an outcome) from damage, and 3) at learning, adaptive capacity (resilience as a core of attributes) explains the probability of households adaptation measures based on the enhancement of physical capital. As a result, during the disturbance phase, exposure has the greatest weight in the probability of capital’s damage, and households with absorptive and external response capacity elements absorbed the impact of floods in comparison with households without these elements. At the recovery phase, households with absorptive and external response capacity showed a faster recovery on their capital; however, the damage sets the thresholds of recovery time. More importantly, diversity in financial capital increases the probability of recovering other capital, but it becomes a liability so that the probability of recovering the household finances in a longer time increases. At learning-reorganizing phase, adaptation (modifications to the house) increases the probability of having less damage on physical capital; however, it is not very relevant. As conclusion, resilience is an outcome but also core of attributes that interacts with vulnerability along the adaptive cycle and disaster process phases. Absorptive capacity can diminish the damage experienced by floods; however, when exposure overcomes thresholds, both absorptive and external response capacity are not enough. In the same way, absorptive and external response capacity diminish the recovery time of capital, but the damage sets the thresholds in where households are not capable of recovering their capital.

Keywords: absorptive capacity, adaptive capacity, capital, floods, recovery-learning, social-ecological systems

Procedia PDF Downloads 109

Authors: Suneet Jagdev

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The development of the original Bauhaus occurred at a time in the beginning of the 20th century when the industrialization of Germany had reached a climax. The cities were a reflection of the new living conditions of an industrialized society. The Bauhaus can be interpreted as an ambitious attempt to find appropriate answers to the challenges by using architecture-urban development and design. The core elements of the conviction of the day were the belief in the necessary crossing of boundaries between the various disciplines and courage to experiment for a better solution. Even after 100 years, the situation in our cities is shaped by similar complexity. The urban consequences of developments are difficult to estimate and to predict. The paper critically reflected on the central aspects of the history of the Bauhaus and its role in bringing the modernism in India by comparative studies of the methodology adopted by the artists and designer in both the countries. The paper talked in detail about how the Bauhaus Exhibition in 1922 offered Indian artists a new weapon of anti-colonial resistance. The original Bauhaus fought its aesthetic and political battles in the context of economic instability and the rise of German fascism. The Indians had access to dominant global languages and in a particular English. The availability of print media and a vibrant indigenous intellectual culture provided Indian people a tool to accept technology while denying both its dominant role in culture and the inevitability of only one form of modernism. The indigenous was thus less an engagement with their culture as in the West than a tool of anti-colonial struggle. We have shown how the Indian people used Bauhaus as a critique of colonialism itself through an undermining of its typical modes of representation and as a means of incorporating the Indian desire for spirituality into art and as providing the cultural basis for a non-materialistic and anti-industrial form of what we might now term development. The paper reflected how through painting the Bauhaus entered the artistic consciousness of the sub-continent not only for its stylistic and technical innovations but as a tool for a critical and even utopian modernism that could challenge both the hegemony of academic and orientalist art and as the bearer of a transnational avant-garde as much political as it was artistic, and as such the basis of a non-Eurocentric but genuinely cosmopolitan alternative to the hierarchies of oppression and domination that had long bound India and were at that moment rising once again to a tragic crescendo in Europe. We have talked about how the Bauhaus of today can offer an innovative orientation towards discourse around architecture and design.

Keywords: anti-colonial struggle, art over architecture, Bauhaus exhibition of 1922, industrialization

Procedia PDF Downloads 223

Authors: Sathwik Sarvadevabhatla Kasyap, Kostas Senetakis

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The mechanical behavior of geological materials is very complex, and this complexity is related to the discrete nature of soils and rocks. Characteristics of a material at the grain scale such as particle size and shape, surface roughness and morphology, and particle contact interface are critical to evaluate and better understand the behavior of discrete materials. This study investigates experimentally the micro-mechanical behavior of quartz sand grains with emphasis on the influence of the presence of microparticles in their contact region. The outputs of the study provide some fundamental insights on the contact mechanics behavior of artificially coated grains and can provide useful input parameters in the discrete element modeling (DEM) of soils. In nature, the contact interfaces between real soil grains are commonly observed with microparticles. This is usually the case of sand-silt and sand-clay mixtures, where the finer particles may create a coating on the surface of the coarser grains, altering in this way the micro-, and thus the macro-scale response of geological materials. In this study, the micro-mechanical behavior of Leighton Buzzard Sand (LBS) quartz grains, with interference of different microparticles at their contact interfaces is studied in the laboratory using an advanced custom-built inter-particle loading apparatus. Special techniques were adopted to develop the coating on the surfaces of the quartz sand grains so that to establish repeatability of the coating technique. The characterization of the microstructure of coated particles on their surfaces was based on element composition analyses, microscopic images, surface roughness measurements, and single particle crushing strength tests. The mechanical responses such as normal and tangential load – displacement behavior, tangential stiffness behavior, and normal contact behavior under cyclic loading were studied. The behavior of coated LBS particles is compared among different classes of them and with pure LBS (i.e. surface cleaned to remove any microparticles). The damage on the surface of the particles was analyzed using microscopic images. Extended displacements in both normal and tangential directions were observed for coated LBS particles due to the plastic nature of the coating material and this varied with the variation of the amount of coating. The tangential displacement required to reach steady state was delayed due to the presence of microparticles in the contact region of grains under shearing. Increased tangential loads and coefficient of friction were observed for the coated grains in comparison to the uncoated quartz grains.

Keywords: contact interface, microparticles, micro-mechanical behavior, quartz sand

Procedia PDF Downloads 174

Authors: M. Gowri, E. K. Girija, V. Ganesh

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Background and Significance: Among the dental infections, inflammation and infection of the root canal are common among all age groups. Currently, the management of root canal infections involves cleaning the canal with powerful irrigants followed by intracanal medicament application. Though these treatments have been in vogue for a long time, root canal failures do occur. Treatment for root canal infections is limited due to the anatomical complexity in terms of small micrometer volumes and poor penetration of drugs. Thus, infections of the root canal seem to be a challenge that demands development of new agents that can eradicate C. albicans. Methodology: In the present study, we synthesized and screened silver-curcumin nanoparticle against Candida albicans. Detailed molecular studies were carried out with silver-curcumin nanoparticle on C. albicans pathogenicity. Morphological cell damage and antibiofilm activity of silver-curcumin nanoparticle on C. albicans was studied using scanning electron microscopy (SEM). Biochemical evidence for membrane damage was studied using flow cytometry. Further, the antifungal activity of silver-curcumin nanoparticle was evaluated in an ex vivo dentinal tubule infection model. Results: Screening data showed that silver-curcumin nanoparticle was active against C. albicans. Silver-curcumin nanoparticle exerted time kill effect and post antifungal effect. When used in combination with fluconazole or nystatin, silver-curcumin nanoparticle revealed a minimum inhibitory concentration (MIC) decrease for both drugs used. In-depth molecular studies with silver-curcumin nanoparticle on C. albicans showed that silver-curcumin nanoparticle inhibited yeast to hyphae (Y-H) conversion. Further, SEM images of C. albicans showed that silver-curcumin nanoparticle caused membrane damage and inhibited biofilm formation. Biochemical evidence for membrane damage was confirmed by increased propidium iodide (PI) uptake in flow cytometry. Further, the antifungal activity of silver-curcumin nanoparticle was evaluated in an ex vivo dentinal tubule infection model, which mimics human tooth root canal infection. Confocal laser scanning microscopy studies showed eradication of C. albicans and reduction in colony forming unit (CFU) after 24 h treatment in the infected tooth samples in this model. Conclusion: The results of this study can pave the way for developing new antifungal agents with well deciphered mechanisms of action and can be a promising antifungal agent or medicament against root canal infection.

Keywords: C. albicans, ex vivo dentine model, inhibition of biofilm formation, root canal infection, yeast to hyphae conversion inhibition

Procedia PDF Downloads 185

Authors: Z. Razi, S. M. J. Mortazavi, N. Shokrpour, Z. Shayan, F. Amiri

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Long-term exposure to low doses of ionizing radiation occurs in radiation health care workplaces. Although doses in health professions are generally very low, there are still matters of concern. The radiation safety program promotes occupational radiation safety through accurate and reliable monitoring of radiation workers in order to effectively manage radiation protection. To achieve this goal, it has become mandatory to implement health examination periodically. As a result, based on the hematological alterations, working populations with a common occupational radiation history are screened. This paper calls into question the effectiveness of blood component analysis as a screening program which is mandatory for medical radiation workers in some countries. This study details the distribution and trends of changes in blood components, including white blood cells (WBCs), red blood cells (RBCs) and platelets as well as received cumulative doses from occupational radiation exposure. This study was conducted among 199 participants and 100 control subjects at the medical imaging departments at the central hospital of Shiraz University of Medical Sciences during the years 2006–2010. Descriptive and analytical statistics, considering the P-value<0.05 as statistically significance was used for data analysis. The results of this study show that there is no significant difference between the radiation workers and controls regarding WBCs and platelet count during 4 years. Also, we have found no statistically significant difference between the two groups with respect to RBCs. Besides, no statistically significant difference was observed with respect to RBCs with regards to gender, which has been analyzed separately because of the lower reference range for normal RBCs levels in women compared to men and. Moreover, the findings confirm that in a separate evaluation between WBCs count and the personnel’s working experience and their annual exposure dose, results showed no linear correlation between the three variables. Since the hematological findings were within the range of control levels, it can be concluded that the radiation dosage (which was not more than 7.58 mSv in this study) had been too small to stimulate any quantifiable change in medical radiation worker’s blood count. Thus, use of more accurate method for screening program based on the working profile of the radiation workers and their accumulated dose is suggested. In addition, complexity of radiation-induced functions and the influence of various factors on blood count alteration should be taken into account.

Keywords: blood cell count, mandatory testing, occupational exposure, radiation

Procedia PDF Downloads 440

Authors: Temmuz Gönç Şavran

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Migration is a multidimensional and health-related concept that has important consequences for both migrants and the host society. Due to past conflicts and poor living conditions that lead to migration, the dangerous and difficult journey, and the problems they face upon arrival in the destination country, migrants are at higher risk for poor health. Health is a human right, and all societies and communities, including migrant groups, must receive adequate health care. In addition, the health of migrants must be improved to protect the health of the host society and ensure social integration. The main determinants of health are employment, income, education, good housing, and adequate nutrition. It can be said that migrants are among the most vulnerable groups in society in these respects, and migrant health is negatively affected by this situation. Rigid immigration policies or financial constraints in destination countries, the complexity and bureaucracy of health systems, the low health literacy of migrant groups, and the inadequate provision of translation services in health facilities are among the other main factors affecting migrant health. Migrants are also at risk of stigma, exclusion, detection, and deportation when seeking medical care. Based on data from a qualitative study with a descriptive case study design, this paper aims to highlight and sociologically assess the health-related problems of international migrants in Eskisehir, Turkey. The sample consists of 30 international migrants living in Eskisehir, two-thirds of whom are from Syria, Iraq, Afghanistan, and Pakistan. Those who are citizens of the Republic of Turkey are excluded from the study; otherwise, the legal status of the participants is not considered in the selection of the sample. This makes it possible to distinguish the different needs and problems of subgroups and to consider migrant health as a comprehensive concept. The research is supported by Anadolu University in Eskisehir, and data will be collected through semi-structured interviews between November 2022 and February 2023. With holistic sociology of health approach, this study considers migrant health as a comprehensive sociological concept. It aims to reveal the health-related resources and needs of the international migrant groups living in the center of Eskisehir, the problems they encounter in meeting these needs, and the strategies they use to solve these problems. The results are expected to show that the health of migrants is not only influenced by legislation but is shaped by many processes, from housing conditions to cultural habits. It is expected that the results will also raise awareness of discrimination, exclusion, marginalization, and hate speech in migrants’ access to health services.

Keywords: migrant health, sociology of health, sociology of migration, Turkey, refugees

Procedia PDF Downloads 57

Authors: Hernando Santamaría-García, Sandra Báez, Pablo Reyes, José Santamaría-García, Diana Matallana, Adolfo García, Agustín Ibañez

Abstract:

The study of moral emotions (i.e., Schadenfreude and envy) is critical to understand the ecological complexity of everyday interactions between cognitive, affective, and social cognition processes. Most previous studies in this area have used correlational imaging techniques and framed Schadenfreude and envy as monolithic domains. Here, we profit from a relevant neurodegeneration model to disentangle the brain regions engaged in three dimensions of Schadenfreude and envy: deservingness, morality, and legality. We tested 20 patients with behavioral variant frontotemporal dementia (bvFTD), 24 patients with Alzheimer’s disease (AD), as a contrastive neurodegeneration model, and 20 healthy controls on a novel task highlighting each of these dimensions in scenarios eliciting Schadenfreude and envy. Compared with the AD and control groups, bvFTD patients obtained significantly higher scores on all dimensions for both emotions. Interestingly, the legal dimension for both envy and Schadenfreude elicited higher emotional scores than the deservingness and moral dimensions. Furthermore, correlational analyses in bvFTD showed that higher envy and Schadenfreude scores were associated with greater deficits in social cognition, inhibitory control, and behavior. Brain anatomy findings (restricted to bvFTD and controls) confirmed differences in how these groups process each dimension. Schadenfreude was associated with the ventral striatum in all subjects. Also, in bvFTD patients, increased Schadenfreude across dimensions was negatively correlated with regions supporting social-value rewards, mentalizing, and social cognition (frontal pole, temporal pole, angular gyrus and precuneus). In all subjects, all dimensions of envy positively correlated with the volume of the anterior cingulate cortex, a region involved in processing unfair social comparisons. By contrast, in bvFTD patients, the intensified experience of envy across all dimensions was negatively correlated with a set of areas subserving social cognition, including the prefrontal cortex, the parahippocampus, and the amygdala. Together, the present results provide the first lesion-based evidence for the multidimensional nature of the emotional experiences of envy and Schadenfreude. Moreover, this is the first demonstration of a selective exacerbation of envy and Schadenfreude in bvFTD patients, probably triggered by atrophy to social cognition networks. Our results offer new insights into the mechanisms subserving complex emotions and moral cognition in neurodegeneration, paving the way for groundbreaking research on their interaction with other cognitive, social, and emotional processes.

Keywords: social cognition, moral emotions, neuroimaging, frontotemporal dementia

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