Search results for: architecture conservation

Authors: Mokhlisur Rahman

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Ocean inhibits one of the most complex ecosystems on the planet that regulates the earth's climate and weather by providing us with compatible weather to live. Ocean provides food by extending various ways of lifestyles that are dependent on it, transportation by accommodating the world's biggest carriers, recreation by offering its beauty in many moods, and home to countless species. At the essence of receiving various forms of entertainment, consumers choose to be close to the ocean while performing many fun activities. Which, at some point, upsets the stomach of the ocean by threatening marine life and the environment. Consumers throw the waste into the ocean after using it. Most of them are plastics that float over the ocean and turn into thousands of micro pieces that are hard to observe with the naked eye but easily eaten by the sea species. Eventually, that conflicts with the natural consumption process of any living species, making them sick. This information is not known by most consumers who go to the sea or seashores occasionally to spend time, nor is it widely discussed, which creates an information gap among consumers. However, advertising is a powerful tool to educate people about ocean pollution. This abstract analyzes three major ocean-saving advertisement campaigns that use innovative and advanced technology to get maximum exposure. The study collects data from the selected campaigns' websites and retrieves all available content related to messages, videos, and images. First, the SeaLegacy campaign uses stunning images to create awareness among the people; they use social media content, videos, and other educational content. They create content and strategies to build an emotional connection among the consumers that encourage them to move on an action. All the messages in their campaign empower consumers by using powerful words. Second, Ocean Conservancy Campaign uses social media marketing, events, and educational content to protect the ocean from various pollutants, including plastics, climate change, and overfishing. They use powerful images and videos of marine life. Their mission is to create evidence-based solutions toward a healthy ocean. Their message includes the message regarding the local communities along with the sea species. Third, ocean clean-up is a campaign that applies strategies using innovative technologies to remove plastic waste from the ocean. They use social media, digital, and email marketing to reach people and raise awareness. They also use images and videos to evoke an emotional response to take action. These tree advertisements use realistic images, powerful words, and the presence of living species in the imagery presentation, which are eye-catching and can grow emotional connection among the consumers. Identifying the effectiveness of the messages these advertisements carry and their strategies highlights the knowledge gap of mass people between real pollution and its consequences, making the message more accessible to the mass of people. This study aims to provide insights into the effectiveness of ocean-saving advertisement campaigns and their impact on the public's awareness of ocean conservation. The findings from this study help shape future campaigns.

Keywords: advertising-campaign, content-creation, images ocean-saving technology, videos

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Authors: Francesco Lubrano, Fabrizio Bertone, Federico Stirano

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Modern societies strongly depend on Critical Infrastructures (CI). Hospitals, power supplies, water supplies, telecommunications are just few examples of CIs that provide vital functions to societies. CIs like hospitals are very complex environments, characterized by a huge number of cyber and physical systems that are becoming increasingly integrated. Ensuring a high level of security within such critical infrastructure requires a deep knowledge of vulnerabilities, threats, and potential attacks that may occur, as well as defence and prevention or mitigation strategies. The possibility to remotely monitor and control almost everything is pushing the adoption of network-connected devices. This implicitly introduces new threats and potential vulnerabilities, posing a risk, especially to those devices connected to the Internet. Modern medical devices used in hospitals are not an exception and are more and more being connected to enhance their functionalities and easing the management. Moreover, hospitals are environments with high flows of people, that are difficult to monitor and can somehow easily have access to the same places used by the staff, potentially creating damages. It is therefore clear that physical and cyber threats should be considered, analysed, and treated together as cyber-physical threats. This means that an integrated approach is required. SAFECARE, an integrated cyber-physical security solution, tries to respond to the presented issues within healthcare infrastructures. The challenge is to bring together the most advanced technologies from the physical and cyber security spheres, to achieve a global optimum for systemic security and for the management of combined cyber and physical threats and incidents and their interconnections. Moreover, potential impacts and cascading effects are evaluated through impact propagation models that rely on modular ontologies and a rule-based engine. Indeed, SAFECARE architecture foresees i) a macroblock related to cyber security field, where innovative tools are deployed to monitor network traffic, systems and medical devices; ii) a physical security macroblock, where video management systems are coupled with access control management, building management systems and innovative AI algorithms to detect behavior anomalies; iii) an integration system that collects all the incoming incidents, simulating their potential cascading effects, providing alerts and updated information regarding assets availability.

Keywords: cyber security, defence strategies, impact propagation, integrated security, physical security

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Authors: Adel Edwar Waheeb Louka

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Purpose AI-driven solutions are at the forefront of many pathology and medical imaging methods. Using algorithms designed to better the experience of medical professionals within their respective fields, the efficiency and accuracy of diagnosis can improve. In particular, X-rays are a fast and relatively inexpensive test that can diagnose diseases. In recent years, X-rays have not been widely used to detect and diagnose COVID-19. The under use of Xrays is mainly due to the low diagnostic accuracy and confounding with pneumonia, another respiratory disease. However, research in this field has expressed a possibility that artificial neural networks can successfully diagnose COVID-19 with high accuracy. Models and Data The dataset used is the COVID-19 Radiography Database. This dataset includes images and masks of chest X-rays under the labels of COVID-19, normal, and pneumonia. The classification model developed uses an autoencoder and a pre-trained convolutional neural network (DenseNet201) to provide transfer learning to the model. The model then uses a deep neural network to finalize the feature extraction and predict the diagnosis for the input image. This model was trained on 4035 images and validated on 807 separate images from the ones used for training. The images used to train the classification model include an important feature: the pictures are cropped beforehand to eliminate distractions when training the model. The image segmentation model uses an improved U-Net architecture. This model is used to extract the lung mask from the chest X-ray image. The model is trained on 8577 images and validated on a validation split of 20%. These models are calculated using the external dataset for validation. The models’ accuracy, precision, recall, f1-score, IOU, and loss are calculated. Results The classification model achieved an accuracy of 97.65% and a loss of 0.1234 when differentiating COVID19-infected, pneumonia-infected, and normal lung X-rays. The segmentation model achieved an accuracy of 97.31% and an IOU of 0.928. Conclusion The models proposed can detect COVID-19, pneumonia, and normal lungs with high accuracy and derive the lung mask from a chest X-ray with similarly high accuracy. The hope is for these models to elevate the experience of medical professionals and provide insight into the future of the methods used.

Keywords: artificial intelligence, convolutional neural networks, deeplearning, image processing, machine learningSarapin, intraarticular, chronic knee pain, osteoarthritisFNS, trauma, hip, neck femur fracture, minimally invasive surgery

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Authors: Natarajan Ramasamy, Gurulingamurthy Haralur, Ramesh Nivarthu, Nikhil Kumar Singha

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Elastomers are polymeric materials with varied backbone architectures ranging from linear to dendrimeric structures and wide varieties of monomeric repeat units. These elastomers show strongly viscous and weakly elastic when it is not cross-linked. But when crosslinked, based on the extent the properties of these elastomers can range from highly flexible to highly stiff nature. Lightly cross-linked systems are well studied and reported. Understanding the nature of highly cross-linked rubber based upon chemical structure and architecture is critical for varieties of applications. One of the critical parameters is cross-link density. In the current work, we have studied the highly cross-linked state of linear, lightly branched to star-shaped branched elastomers and determined the cross-linked density by using different models. Change in hardness, shift in Tg, change in modulus and swelling behavior were measured experimentally as a function of the extent of curing. These properties were analyzed using varied models to determine cross-link density. We used hardness measurements to examine cure time. Hardness to the extent of curing relationship is determined. It is well known that micromechanical transitions like Tg and storage modulus are related to the extent of crosslinking. The Tg of the elastomer in different crosslinked state was determined by DMA, and based on plateau modulus the crosslink density is estimated by using Nielsen’s model. Usually for lightly crosslinked systems, based on equilibrium swelling ratio in solvent the cross link density is estimated by using Flory–Rhener model. When it comes to highly crosslinked system, Flory-Rhener model is not valid because of smaller chain length. So models based on the assumption of polymer as a Non-Gaussian chain like 1) Helmis–Heinrich–Straube (HHS) model, 2) Gloria M.gusler and Yoram Cohen Model, 3) Barbara D. Barr-Howell and Nikolaos A. Peppas model is used for estimating crosslink density. In this work, correction factors are determined to the existing models and based upon it structure-property relationship of highly crosslinked elastomers was studied.

Keywords: dynamic mechanical analysis, glass transition temperature, parts per hundred grams of rubber, crosslink density, number of networks per unit volume of elastomer

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Authors: Babatunde Kolawole

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This paper embarks on an exploration of the compelling interplay between documentary filmmaking and activism, delving into their symbiotic relationship and profound impact on advocacy and social justice causes. Through an in-depth analysis of diverse case studies, it seeks to illuminate the instances where documentary films have emerged as potent tools for effecting social change and advancing the principles of justice. This research underscores the vital role played by documentary filmmakers in harnessing the medium's unique capacity to engage, educate, and mobilize audiences while advocating for societal transformation. The primary focus of this study is on a selection of compelling case studies spanning various topics and causes, each exemplifying the marriage between documentary filmmaking and activism. These case studies encompass a broad spectrum of subjects, from environmental conservation and climate change to civil rights movements and human rights struggles. By examining these real-world instances, this paper endeavors to provide a comprehensive understanding of the strategies, challenges, and ethical considerations that underpin the practice of documentary filmmaking as a form of activism. Throughout the paper, it becomes evident that the potency of documentary filmmaking lies in its ability to blend artistry with social impact. The selected case studies vividly demonstrate how documentary filmmakers, armed with cameras and a passion for change, have emerged as critical agents of societal transformation. Whether it be exposing environmental atrocities, shedding light on systemic inequalities, or giving voice to marginalized communities, these documentaries have played a pivotal role in pushing the boundaries of advocacy and social justice. One of the key themes explored in this paper is the evolving nature of documentary filmmaking as a tool for activism. It delves into the shift from traditional observational documentaries to more participatory and immersive approaches, highlighting the dynamic ways in which filmmakers engage with their subjects and audiences. This evolution is exemplified in case studies where filmmakers have collaborated with the communities they document, fostering a sense of agency and empowerment among those whose stories are being told. Furthermore, this research underscores the ethical considerations inherent in the intersection of documentary filmmaking and activism. It scrutinizes questions surrounding representation, objectivity, and the responsibility of filmmakers in portraying complex social issues. By dissecting ethical dilemmas faced by documentary filmmakers in these case studies, this paper encourages a critical examination of the ethical boundaries and obligations in the realm of advocacy-driven filmmaking. In conclusion, this paper aims to shed light on the remarkable potential of documentary filmmaking as a catalyst for activism and social justice. Through the lens of compelling case studies, it illustrates the transformative power of the medium in effecting change, amplifying underrepresented voices, and mobilizing global audiences. It is hoped that this research will not only inform the discourse on documentary activism but also inspire filmmakers, scholars, and advocates to continue leveraging the cinematic art form as a formidable force for a more just and equitable world.

Keywords: film, filmmaker, documentary, human right

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Authors: Muhammad Khairi bin Sulaiman

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The utilization of Building Information Modelling (BIM) in the construction industry has provided an opportunity for designers in the Architecture, Engineering and Construction (AEC) industry to proceed from the conventional method of using manual drafting to a way that creates alternative designs quickly, produces more accurate, reliable and consistent outputs. By using BIM Software, designers can create digital content that manipulates the use of data using the parametric model of BIM. With BIM software, more alternative designs can be created quickly and design problems can be explored further to produce a better design faster than conventional design methods. Generally, BIM is used as a documentation mechanism and has not been fully explored and utilised its capabilities as a design tool. Relative to the current issue, Modular Coordination (MC) design as a sustainable design practice is encouraged since MC design will reduce material wastage through standard dimensioning, pre-fabrication, repetitive, modular construction and components. However, MC design involves a complex process of rules and dimensions. Therefore, a tool is needed to make this process easier. Since the parameters in BIM can easily be manipulated to follow MC rules and dimensioning, thus, the integration of BIM software with MC design is proposed for architects during the design stage. With this tool, there will be an improvement in acceptance and practice in the application of MC design effectively. Consequently, this study will analyse and explore the function and customization of BIM objects and the capability of BIM software to expedite the application of MC design during the design stage for architects. With this application, architects will be able to create building models and locate objects within reference modular grids that adhere to MC rules and dimensions. The parametric modeling capabilities of BIM will also act as a visual tool that will further enhance the automation of the 3-Dimensional space planning modeling process. (Method) The study will first analyze and explore the parametric modeling capabilities of rule-based BIM objects, which eventually customize a reference grid within the rules and dimensioning of MC. Eventually, the approach will further enhance the architect's overall design process and enable architects to automate complex modeling, which was nearly impossible before. A prototype using a residential quarter will be modeled. A set of reference grids guided by specific MC rules and dimensions will be used to develop a variety of space planning and configuration. With the use of the design, the tool will expedite the design process and encourage the use of MC Design in the construction industry.

Keywords: building information modeling, modular coordination, space planning, customization, BIM application, MC space planning

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Authors: Aliaksandr Shuba, Max Welch Guerra, Martin Pekar

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The research is dedicated to the Historiography of European urbanism in the 20th century with its critical analysis of transnational oriented sources in Slavic languages. The goal of this research was to give an overview of Slavic sources on this subject. In the research, historians, who wrote in influential historiographies on architecture and urbanism in the 20th century history in Slavic languages from Eastern, Central and South-eastern Europe, are analysed. The analysis of historiographies in Slavic languages includes diverse sources from around Europe with authors, who examined European Urbanism in the 20th century through a global prism of or their own perspectives. The main publications are from the second half of the 20th century and the early 21st century with Soviet and Post-Soviet discourses. The necessity to analyse Slavic sources was a result of historiography of urbanism establishment as a discipline in the 20th century and by the USSR, Czechslovak, and Yugoslavian academics, who created strong historiographic bases for a development of their urban historiographic schools for wide studies and analysis of architectural and urban ideas and projects with their history in the early 1970s. That is analyzed in this research within Slavic publications, which often have different perspectives and discourses to Anglo-Saxon, and these bibliographic sources can bring a diversity of new ideas in contemporary academic discourse of the European urban historiography. The publications in Slavic languages are analyzed according to the following aspects: where, when, which types, by whom, and to whom the sources were written. The critical analysis of essential sources on the Historiography of European urbanism in the 20th century with an accomplishment through their comparison and interpretation. The authors’ autonomy is analysed as a central point, along with the influence of the Communist Party and state control on the interpretation of the history of urbanism in Central, Eastern and South-eastern Europe with the main dominant topics and ideas from the second half of the 20th century. Cross-national Slavic Historiographic sources and their perspectives are compared to the main transnational Anglo-Saxon Historiographic topics as some of the dominant subjects are hypothetically similar and others have more local or national oriented directions. Some of the dominant subjects, topics, and subtopics are hypothetically similar, while the others have more local or national oriented directions because of the authors’ autonomy and influences of the Communist Party with the state control in Slavic Socialists countries that were illustrated in this research.

Keywords: European urbanism, historiography, different perspectives, 20th century

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Authors: Volker Landersheim, Daria Manushyna, Thinh Pham, Dai-Duong Tran, Thomas Geury, Omar Hegazy, Steven Wilkins

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Air pollution is one of the emerging problems in our society. Targets of reduction of CO₂ emissions address low-carbon and resource-efficient transport. (Plug-in) hybrid electric propulsion concepts offer the possibility to reduce total cost of ownership (TCO) and emissions for public transport vehicles (e.g., bus application). In this context, typically, diesel engines are used to form the hybrid propulsion system of the vehicle. Though the technological development of diesel engines experience major advantages, some challenges such as the high amount of particle emissions remain relevant. Gaseous fuels (i.e., compressed natural gases (CNGs) or liquefied petroleum gases (LPGs) represent an attractive alternative to diesel because of their composition. In the framework of the research project 'Optimised Real-world Cost-Competitive Modular Hybrid Architecture' (ORCA), which was funded by the EU, two different hybrid-electric propulsion concepts have been investigated: one using a diesel engine as internal combustion engine and one using CNG as fuel. The aim of the current study is to analyze specific benefits for the aforementioned hybrid propulsion systems for predefined driving scenarios with regard to emissions and total cost of ownership in bus application. Engine models based on experimental data for diesel and CNG were developed. For the purpose of designing optimal energy management strategies for each propulsion system, maps-driven or quasi-static models for specific engine types are used in the simulation framework. An analogous modelling approach has been chosen to represent emissions. This paper compares the two concepts regarding their CO₂ and NOx emissions. This comparison is performed for relevant bus missions (urban, suburban, with and without zero-emission zone) and with different energy management strategies. In addition to the emissions, also the downsizing potential of the combustion engine has been analysed to minimize the powertrain TCO (pTCO) for plug-in hybrid electric buses. The results of the performed analyses show that the hybrid vehicle concept using the CNG engine shows advantages both with respect to emissions as well as to pTCO. The pTCO is 10% lower, CO₂ emissions are 13% lower, and the NOx emissions are more than 50% lower than with the diesel combustion engine. These results are consistent across all usage profiles under investigation.

Keywords: bus transport, emissions, hybrid propulsion, pTCO, CNG

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Authors: V. Vsevolozhskaia

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Since 1990, energy-efficient development concepts have constituted both a turning point in civil engineering and a challenge for an environmentally friendly future. Energy and water currently play an essential role in the sustainable economic growth of the world in general and Russia in particular: the efficiency of the water supply system is the second most important parameter for energy consumption according to the British assessment method, while the water-energy nexus has been identified as a focus for accelerating sustainable growth and developing effective, innovative solutions. The activities considered in this study were aimed at organizing and executing the renovation of the property in residential buildings located in St. Petersburg, specifically buildings with local or federal historical heritage status under the control of the St. Petersburg Committee for the State Inspection and Protection of Historic and Cultural Monuments (KGIOP) and UNESCO. Even after reconstruction, these buildings still fall into energy efficiency class D. Russian Government Resolution No. 87 on the structure and required content of project documentation contains a section entitled ‘Measures to ensure compliance with energy efficiency and equipment requirements for buildings, structures, and constructions with energy metering devices’. Mention is made of the need to install collectors and meters, which only calculate energy, neglecting the main purpose: to make buildings more energy-efficient, potentially even energy efficiency class A. The least-explored aspects of energy-efficient technology in the Russian Federation remain the water balance and the possibility of implementing rain and meltwater collection systems. These modern technologies are used exclusively for new buildings due to a lack of government directive to create project documentation during the planning of major renovations and reconstruction that would include the collection and reuse of rainwater. Energy-efficient technology for rain and meltwater collection is currently applied only to new buildings, even though research has proved that using rainwater is safe and offers a huge step forward in terms of eco-efficiency analysis and water innovation. Where conservation is mandatory, making changes to protected sites is prohibited. In most cases, the protected site is the cultural heritage building itself, including the main walls and roof. However, the installation of a second water supply system and collection of rainwater would not affect the protected building itself. Water efficiency in St. Petersburg is currently considered only from the point of view of the installation that regulates the flow of the pipeline shutoff valves. The development of technical guidelines for the use of grey- and/or rainwater to meet the needs of residential buildings during reconstruction or renovation is not yet complete. The ideas for water treatment, collection and distribution systems presented in this study should be taken into consideration during the reconstruction or renovation of residential cultural heritage buildings under the protection of KGIOP and UNESCO. The methodology applied also has the potential to be extended to other cultural heritage sites in northern countries and lands with an average annual rainfall of over 600 mm to cover average toilet-flush needs.

Keywords: cultural heritage, energy efficiency, renovation, rainwater collection, reconstruction, water management, water supply

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Authors: Andrei Bejan, Luminita Marin, Dalila Belei

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Phenothiazine with electron-rich nitrogen and sulfur heteroatoms has a high electron-donating ability which promotes a good conjugation and therefore low band-gap with consequences upon charge carrier mobility improving and shifting of light emission in visible domain. Moreover, its non-planar butterfly conformation inhibits molecular aggregation and thus preserves quite well the fluorescence quantum yield in solid state compared to solution. Therefore phenothiazine and its derivatives are promising hole transport materials for use in organic electronic and optoelectronic devices as light emitting diodes, photovoltaic cells, integrated circuit sensors or driving circuits for large area display devices. The objective of this paper was to obtain a series of new phenothiazine derivatives by introduction of different electron withdrawing substituents as formyl, carboxyl and cyanoacryl units in order to create a push pull system which has potential to improve the electronic and optical properties. Bromine atom was used as electrono-donor moiety to extend furthermore the existing conjugation. The understudy compounds were structural characterized by FTIR and 1H-NMR spectroscopy and single crystal X-ray diffraction. Besides, the single crystal X-ray diffraction brought information regarding the supramolecular architecture of the compounds. Photophysical properties were monitored by UV-vis and photoluminescence spectroscopy, while the electrochemical behavior was established by cyclic voltammetry. The absorption maxima of the studied compounds vary in a large range (322-455 nm), reflecting the different electronic delocalization degree, depending by the substituent nature. In a similar manner, the emission spectra reveal different color of emitted light, a red shift being evident for the groups with higher electron withdrawing ability. The emitted light is pure and saturated for the compounds containing strong withdrawing formyl or cyanoacryl units and reach the highest quantum yield of 71% for the compound containing bromine and cyanoacrilic units. Electrochemical study show reversible oxidative and reduction processes for all the compounds and a close correlation of the HOMO-LUMO band gap with substituent nature. All these findings suggest the obtained compounds as promising materials for optoelectronic devices.

Keywords: electrochemical properties, phenothiazine derivatives, photoluminescence, quantum yield

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Authors: C. Sancho Salvatierra, J. M. Martinez Nieto, R. García Gonzalez-Gordon, M. I. Martinez Bellido

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Introduction: Nature could act as an asset for human health protecting against possible diseases and promoting the state of both physical and mental health. Goals: This paper aims to determine which natural elements present evidence that show positive influence on human health, on which particular aspects and how. It also aims to determine the best biomarkers to measure such influence. Method: A systematic literature review was carried out. First, a general free text search was performed in databases, such as Scopus, PubMed or PsychInfo. Secondly, a specific search was performed combining keywords in order of increasing complexity. Also the Snowballing technique was used and it was consulted in the CSIC’s (The Spanish National Research Council). Databases: Of the 130 articles obtained and reviewed, 80 referred to natural elements that influenced health. These 80 articles were classified and tabulated according to the nature elements found, the health aspects studied, the health measurement parameters used and the measurement techniques used. In this classification the results of the studies were codified according to whether they were positive, negative or neutral both for the elements of nature and for the aspects of health studied. Finally, the results of the 80 selected studies were summarized and categorized according to the elements of nature that showed the greatest positive influence on health and the biomarkers that had shown greater reliability to measure said influence. Results: Of the 80 articles studied, 24 (30.0%) were reviews and 56 (70.0%) were original research articles. Among the 24 reviews, 18 (75%) found positive results of natural elements on health, and 6 (25%) both positive and negative effects. Of the 56 original articles, 47 (83.9%) showed positive results, 3 (5.4%) both positive and negative, 4 (7.1%) negative effects, and 2 (3.6%) found no effects. The results reflect positive effects of different elements of nature on the following pathologies: diabetes, high blood pressure, stress, attention deficit hyperactivity disorder, psychotic, anxiety and affective disorders. They also show positive effects on the following areas: immune system, social interaction, recovery after illness, mood, decreased aggressiveness, concentrated attention, cognitive performance, restful sleep, vitality and sense of well-being. Among the elements of nature studied, those that show the greatest positive influence on health are forest immersion, natural views, daylight, outdoor physical activity, active transport, vegetation biodiversity, natural sounds and the green residences. As for the biomarkers used that show greater reliability to measure the effects of natural elements are the levels of cortisol (both in blood and saliva), vitamin D levels, serotonin and melatonin, blood pressure, heart rate, muscle tension and skin conductance. Conclusions: Nature is an asset for health, well-being and quality of life. Awareness programs, education and health promotion are needed based on the elements that nature brings us, which in turn generate proactive attitudes in the population towards the protection and conservation of nature. The studies related to this subject in Spain are very scarce. Aknowledgements. This study has been promoted and partially financed by the Environmental Foundation Jaime González-Gordon.

Keywords: health, green areas, nature, well-being

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Authors: Domenica Bona

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Colin Chant and David Goodman argue that historians of Chinese pre-industrial cities tend to underestimate revolutions and overestimate cyclic patterns: periods of peace and prosperity in the earl part of each d nast , followed b peasants’ rebellions and upheavals. Boyd described these cyclic patterns as part of the background of Chinese town planning and architecture. Thus old ideals of city planning-square plan, southward orientation and a palace along the central axis - are revived again and again in the ascendant phases of several d nastic c cles (e.g. Chang’an, Kaifen, and Beijing). Along this line of thought, m paper questions the relationship between the “magic square rule” and modern Chinese urban- planning. As a matter of fact, the classical theme of “cosmic Taoist urbanism” is still a reference for planning cities and new urban developments, whenever there is the intention to express nationalist ideals and “cultural straightforwardness.” Besides, some case studies can be related to “modern d nasties”: the first Republic under the Kuo Min Tang, the red People’s Republic and the post-Maoist open country of Deng Xiao Ping. Considering the project for the new capital of Nanjing in the Thirties, Beijing’s Tianan Men area in the ifties, and Shenzhen’s utian CBD in late 20th century, I argue that cyclic patterns are still in place, though with deformations related to westernization, private interests and lack of spirituality. How far new Chinese cities are - or simply seem to be - westernized? Symbolism, invisible frameworks, repeating features and behavioural patterns make urban China just “superficiall” western. This can be well noticed in cities previousl occupied b foreigners, like Hong Kong, or in newly founded ones, like Shenzhen, where both Asians and non-Asian people can feel the gender-shift from New-York-like landscapes to something else. Current planning in main metropolitan areas shows a blurred relationship between public policies and private investments: two levels of decisions and actions, one addressing the larger scale and infrastructures, the other concerning the micro scale and development of single plots. While zoning is instrumental in this process, master plans are often laid out over a very poor cartography, so much that any relation between the formal characters of new cities and the centuries-old structure of the related territory gets lost.

Keywords: China, contemporary cities, cultural heritage, shenzhen, urban planning

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Authors: Esshili Awatef, Manitz Marie-Pierre, Eßlinger Manuela, Gerhardt Alexandra, Plümper Jennifer, Wachholz Simone, Friebe Astrid, Juckel Georg

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Maternal immune activation (MIA) resulting from maternal viral infection during pregnancy is a known risk factor for schizophrenia. The neural mechanisms by which maternal infections increase the risk for schizophrenia remain unknown, although the prevailing hypothesis argues that an activation of the maternal immune system induces changes in the maternal-fetal environment that might interact with fetal brain development. It may lead to an activation of fetal microglia inducing long-lasting functional changes of these cells. Based on post-mortem analysis showing an increased number of activated microglial cells in patients with schizophrenia, it can be hypothesized that these cells contribute to disease pathogenesis and may actively be involved in gray matter loss observed in such patients. In the present study, we hypothesize that prenatal treatment with the inflammatory agent Poly(I:C) during embryogenesis at contributes to microglial activation in the offspring, which may, therefore, represent a contributing factor to the pathogenesis of schizophrenia and underlines the need for new pharmacological treatment options. Pregnant rats were treated with intraperitoneal injections a single dose of Poly(I:C) or saline on gestation day 17. Brains of control and Poly(I:C) offspring, were removed and into 20-μm-thick coronal sections were cut by using a Cryostat. Brain slices were fixed and immunostained with ba1 antibody. Subsequently, Iba1-immunoreactivity was detected using a secondary antibody, goat anti-rabbit. The sections were viewed and photographed under microscope. The immunohistochemical analysis revealed increases in microglia cell number in the prefrontal cortex, in offspring of poly(I:C) treated-rats as compared to the controls injected with NaCl. However, no significant differences were observed in microglia activation in the cerebellum among the groups. Prenatal immune challenge with Poly(I:C) was able to induce long-lasting changes in the offspring brains. This lead to a higher activation of microglia cells in the prefrontal cortex, a brain region critical for many higher brain functions, including working memory and cognitive flexibility. which might be implicated in possible changes in cortical neuropil architecture in schizophrenia. Further studies will be needed to clarify the association between microglial cells activation and schizophrenia-related behavioral alterations.

Keywords: Microglia, neuroinflammation, PolyI:C, schizophrenia

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Authors: Eiman Kattan, Hong Wei

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In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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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

Procedia PDF Downloads 135

Authors: Donghyun Lee, Cam Nguyen

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Multi-band systems offer a great deal of benefit in modern communication and radar systems. In particular, multi-band antenna-array radar systems with their extended frequency diversity provide numerous advantages in detection, identification, locating and tracking a wide range of targets, including enhanced detection coverage, accurate target location, reduced survey time and cost, increased resolution, improved reliability and target information. An accurate calibration is a critical issue in antenna array systems. The amplitude and phase errors in multi-band and multi-polarization antenna array transceivers result in inaccurate target detection, deteriorated resolution and reduced reliability. Furthermore, the digital beam former without the RF domain phase-shifting is less immune to unfiltered interference signals, which can lead to receiver saturation in array systems. Therefore, implementing integrated front-end architecture, which can support calibration function with low insertion and filtering function from the farthest end of an array transceiver is of great interest. We report a dual K/Ka-band T/R/Calibration switch module with quasi-elliptic dual-bandpass filtering function implementing a Q-enhanced metamaterial transmission line. A unique dual-band frequency response is incorporated in the reception and calibration path of the proposed switch module utilizing the composite right/left-handed meta material transmission line coupled with a Colpitts-style negative generation circuit. The fabricated fully integrated T/R/Calibration switch module in 0.18-μm BiCMOS technology exhibits insertion loss of 4.9-12.3 dB and isolation of more than 45 dB in the reception, transmission and calibration mode of operation. In the reception and calibration mode, the dual-band frequency response centered at 24.5 and 35 GHz exhibits out-of-band rejection of more than 30 dB compared to the pass bands below 10.5 GHz and above 59.5 GHz. The rejection between the pass bands reaches more than 50 dB. In all modes of operation, the IP1-dB is between 4 and 11 dBm. Acknowledgement: This paper was made possible by NPRP grant # 6-241-2-102 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.

Keywords: microwaves, millimeter waves, T/R switch, wireless communications, wireless communications

Procedia PDF Downloads 142

Authors: Kuniaki Kudo, Raviraj Solanki, Kaushal Patel, Yash Virani

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This research mainly concerns optimizing UI test automation for large-scale web applications. The test target application is the HHAexchange homecare management WEB application that seamlessly connects providers, state Medicaid programs, managed care organizations (MCOs), and caregivers through one platform with large-scale functionalities. This study focuses on user interface automation testing for the WEB application. The quality assurance team must execute many manual users interface test cases in the development process to confirm no regression bugs. The team automated 346 test cases; the UI automation test execution time was over 17 hours. The business requirement was reducing the execution time to release high-quality products quickly, and the quality assurance automation team modernized the test automation framework to optimize the execution time. The base of the WEB UI automation test environment is Selenium, and the test code is written in Python. Adopting a compilation language to write test code leads to an inefficient flow when introducing scalability into a traditional test automation environment. In order to efficiently introduce scalability into Test Automation, a scripting language was adopted. The scalability implementation is mainly implemented with AWS's serverless technology, an elastic container service. The definition of scalability here is the ability to automatically set up computers to test automation and increase or decrease the number of computers running those tests. This means the scalable mechanism can help test cases run parallelly. Then test execution time is dramatically decreased. Also, introducing scalable test automation is for more than just reducing test execution time. There is a possibility that some challenging bugs are detected by introducing scalable test automation, such as race conditions, Etc. since test cases can be executed at same timing. If API and Unit tests are implemented, the test strategies can be adopted more efficiently for this scalability testing. However, in WEB applications, as a practical matter, API and Unit testing cannot cover 100% functional testing since they do not reach front-end codes. This study applied a scalable UI automation testing strategy to the large-scale homecare management system. It confirmed the optimization of the test case execution time and the detection of a challenging bug. This study first describes the detailed architecture of the scalable test automation environment, then describes the actual performance reduction time and an example of challenging issue detection.

Keywords: aws, elastic container service, scalability, serverless, ui automation test

Procedia PDF Downloads 69

Authors: Mohamed Malek Khenissi, Mohamed Montassar Ben Slama, Anis Belhaj Mohamed, Moncef Saidi

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Northern Tunisia is well known by its different and complex structural and geological zones that have been the result of a geodynamic history that extends from the early Mesozoic era to the actual period. One of these zones is the salt province, where the Halokinesis process is manifested by a number of NE/SW salt structures such as Jebel Ech-Cheid which represents masses of materials characterized by a high plasticity and low density. The salt masses extrusions that have been developed due to an extension that started from the late Triassic to late Cretaceous. The evolution of salt bodies within sedimentary basins have not only contributed to modify the architecture of the basin, but it also has certain geochemical effects which touch mainly source rocks that surround it. It has been demonstrated that the presence of salt structures within sedimentary basins can influence its temperature distribution and thermal history. Moreover, it has been creating heat flux anomalies that may affect the maturity of organic matter and the timing of hydrocarbon generation. Field samples of the Bahloul source rock (Cenomanan-Tunonian) were collected from different sights from all around Ech Cheid salt structure and evaluated using Rock-eval pyrolysis and GC/MS techniques in order to assess the degree of maturity evolution and the heat flux anomalies in the different zones analyze. The Total organic Carbon (TOC) values range between 1 to 9% and the (Tmax) ranges between 424 and 445°C, also the distribution of the source rock biomarkers both saturated and aromatic changes in a regular fashions with increasing maturity and this are shown in the chromatography results such as Ts/(Ts+Tm) ratios, 22S/(22S+22R) values for C31 homohopanes, ββ/(ββ+αα)20R and 20S/(20S+20R) ratios for C29 steranes which gives a consistent maturity indications and assessment of the field samples. These analyses are carried to interpret the maturity evolution and the heat flux around Ech Cheid salt structure through the geological history. These analyses also aim to demonstrate that the salt structure can have a direct effect on the geothermal gradient of the basin and on the maturity of the Bahloul Formation source rock. The organic matter has reached different stages of thermal maturity, but delineate a general increasing maturity trend. Our study confirms that the J. Ech Cheid salt body have on the first hand: a huge influence on the local distribution of anoxic depocentre at least within Cenomanian-Turonian time. In the second hand, the thermal anomaly near the salt mass has affected the maturity of Bahloul Formation.

Keywords: Bahloul formation, depocentre, GC/MS, rock-eval

Procedia PDF Downloads 220

Authors: Ashok Kumar, Parveen Parveen

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India is bestowed with an extremely high population of plant species with medicinal value and even has two biodiversity hotspots. Indian systems of medicine including Ayurveda, Siddha and Unani have historically been serving humankind across the world since time immemorial. About 1500 plant species have well been documented in Ayurvedic Nighantus as official medicinal plants. Additionally, several hundred species of plants are being routinely used as medicines by local people especially tribes living in and around forests. The natural resources for medicinal plants have unscientifically been over-exploited forcing rapid depletion in their genetic diversity. Moreover, renewed global interest in herbal medicines may even lead to additional depletion of medicinal plant wealth of the country, as about 95% collection of medicinal plants for pharmaceutical preparation is being carried out from natural forests. On the other hand, huge export market of medicinal and aromatic plants needs to be seriously tapped for enhancing inflow of foreign currency. Asparagus racemosus Willd., a member of family Liliaceae, is one of thirty-two plant species that have been identified as priority species for cultivation and conservation by the National Medicinal Plant Board (NMPB), Government of India. Though attention is being focused on standardization of agro-techniques and extraction methods, little has been designed on genetic improvement and selection of desired types with higher root production and saponin content, a basic ingredient of medicinal value. The saponin not only improves defense mechanisms and controls diabetes but the roots of this species promote secretion of breast milk, improved lost body weight and considered as an aphrodisiac. There is ample scope for genetic improvement of this species for enhancing productivity substantially, qualitatively and quantitatively. It is emphasized to select desired genotypes with sufficient genetic diversity for important economic traits. Hybridization between two genetically divergent genotypes could result in the synthesis of new F1 hybrids consisting of useful traits of both the parents. The evaluation of twenty seed sources of Asparagus racemosus assembled different geographical locations of India revelled high degree of variability for traits of economic importance. The maximum genotypic and phenotypic variance was observed for shoot height among shoot related traits and for root length among root related traits. The shoot height, genotypic variance, phenotypic variance, genotypic coefficient of variance, the phenotypic coefficient of variance was recorded to be 231.80, 3924.80, 61.26 and 1037.32, respectively, where those of the root length were 9.55, 16.80, 23.46 and 41.27, respectively. The maximum genetic advance and genetic gain were obtained for shoot height among shoot-related traits and root length among root-related traits. Index values were developed for all seed sources based on the four most important traits, and Panthnagar (Uttrakhand), Jodhpur (Rajasthan), Dehradun (Uttarakhand), Chandigarh (Punjab), Jammu (Jammu & Kashmir) and Solan (Himachal Pradesh) were found to be promising seed sources.

Keywords: asparagus, genetic, genotypes, variance

Procedia PDF Downloads 108

Authors: Hülya Torun, Ondřej Novák, Jaromír Mikulík, Miroslav Strnad, Faik A. Ayaz

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World climate is changing. Millions of people in the world still face chronic undernourishment for conducting a healthy life and the world’s population is growing steadily. To meet this growing demand, agriculture and food systems must adapt to the adverse effects of climate change and become more resilient, productive and sustainable. From this perspective, to determine tolerant cultivars for undesirable environmental conditions will be necessary food production for sustainable development. Among abiotic stresses, soil salinity is one of the most detrimental global fact restricting plant sources. Development of salt-tolerant lines is required in order to increase the crop productivity and quality in salt-treated lands. Therefore, the objective of this study was to investigate the morphological and physiological responses of barley cultivars accessions to salinity stress by NaCl. For this purpose, it was aimed to determine the crosstalk between some endogenous phytohormones and exogenous salicylic acid (SA) in two different vegetative parts (leaves and roots) of barley (Hordeum vulgare L.; Poaceae; 2n=14; Ince-04) which is detected salt-tolerant. The effects of SA on growth parameters, leaf relative water content (RWC), endogenous phytohormones; including indole-3-acetic acid (IAA), cytokinins (CKs), abscisic acid (ABA), jasmonic acid (JA) and ethylene were investigated in barley cultivars under salinity stress. SA was applied to 17-day-old seedlings of barley in two different ways including before (pre-treated for 24 h) and simultaneously with NaCl stress treatment. NaCl (0, 150, 300 mM) exposure in the hydrophonic system was associated with a rapid decrease in growth parameters and RWC, which is an indicator of plant water status, resulted in a strong up-regulation of ABA as a stress indicator. Roots were more dramatically affected than leaves. Water conservation in 150 mM NaCl treated-barley plants did not change, but decreased in 300 mM NaCl treated plants. Pre- and simultaneously treatment of SA did not significantly alter growth parameters and RWC. ABA, JA and ethylene are known to be related with stress. In the present work, ethylene also increased, similarly to ABA, but not with the same intensity. While ABA and ethylene increased by the increment of salt concentrations, JA levels rapidly decreased especially in roots. Both pre- and simultaneously SA applications alleviated salt-induced decreases in 300 mM NaCl resulted in the increment of ABA levels. CKs and IAA are related to cell growth and development. At high salinity (300 mM NaCl), CKs (cZ+cZR) contents increased in both vegetative organs while IAA levels stayed at the same level with control groups. However, IAA increased and cZ+cZR rapidly decreased in leaves of barley plants with SA treatments before salt applications (in pre- SA treated groups). Simultaneously application of SA decreased CKs levels in both leaves and roots of the cultivar. Due to increasing concentrations of NaCl in association with decreasing ABA, JA and ethylene content and increments in CKs and IAA were recorded with SA treatments. As results of the study, in view of all the phytohormones that we tested, exogenous SA induced greater tolerance to salinity particularly when applied before salinity stress.

Keywords: Barley, Hordeum vulgare, phytohormones, salicylic acid, salinity

Procedia PDF Downloads 201

Authors: Ercan Kızılay, Mustafa Demi̇rel, Selçuk Coşkun

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Railway signaling systems consist of vital products that regulate railway traffic and provide safe route arrangements and maneuvers of trains. SIL 4 signal lamps are produced by many manufacturers today. There is a need for systems that enable these signal lamps to be controlled by commands from the interlocking. These systems should act as fail-safe and give error indications to the interlocking system when an unexpected situation occurs for the safe operation of railway systems from the RAMS perspective. In the past, driving and proving the lamp in relay-based systems was typically done via signaling relays. Today, the proving of lamps is done by comparing the current values read over the return circuit, the lower and upper threshold values. The purpose is an analog electronic object controller with the possibility of easy integration with vital systems and the signal lamp itself. During the study, the EN50126 standard approach was considered, and the concept, definition, risk analysis, requirements, architecture, design, and prototyping were performed throughout this study. FMEA (Failure Modes and Effects Analysis) and FTA (Fault Tree) Analysis) have been used for safety analysis in accordance with EN 50129. Concerning these analyzes, the 1oo2D reactive fail-safe hardware design of a controller has been researched. Electromagnetic compatibility (EMC) effects on the functional safety of equipment, insulation coordination, and over-voltage protection were discussed during hardware design according to EN 50124 and EN 50122 standards. As vital equipment for railway signaling, railway signal object controllers should be developed according to EN 50126 and EN 50129 standards which identify the steps and requirements of the development in accordance with the SIL 4(Safety Integrity Level) target. In conclusion of this study, an analog railway signal object controller, which takes command from the interlocking system, is processed in driver cards. Driver cards arrange the voltage level according to desired visibility by means of semiconductors. Additionally, prover cards evaluate the current upper and lower thresholds. Evaluated values are processed via logic gates which are composed as 1oo2D by means of analog electronic technologies. This logic evaluates the voltage level of the lamp and mitigates the risks of undue dimming.

Keywords: object controller, railway electronic, analog electronic, safety, railway signal

Procedia PDF Downloads 71

Authors: Mishak Rahul, Naveen Kumar, Bharath Kumar

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Conceived as a high-end engine to revolutionise sustainable agri-food production, the intelligent crop circle (ICC) aims to incorporate the Internet of Things (IoT), blockchain technology and artificial intelligence (AI) to bolster resource efficiency and prevent waste, increase the volume of production and bring about sustainable solutions with long-term ecosystem conservation as the guiding principle. The operating principle of the ICC relies on bringing together multidisciplinary bottom-up collaborations between producers, researchers and consumers. Key elements of the framework include IoT-based smart sensors for sensing soil moisture, temperature, humidity, nutrient and air quality, which provide short-interval and timely data; blockchain technology for data storage on a private chain, which maintains data integrity, traceability and transparency; and AI-based predictive analysis, which actively predicts resource utilisation, plant growth and environment. This data and AI insights are built into the ICC platform, which uses the resulting DSS (Decision Support System) outlined as help in decision making, delivered through an easy-touse mobile app or web-based interface. Farmers are assumed to use such a decision-making aid behind the power of the logic informed by the data pool. Building on existing data available in the farm management systems, the ICC platform is easily interoperable with other IoT devices. ICC facilitates connections and information sharing in real-time between users, including farmers, researchers and industrial partners, enabling them to cooperate in farming innovation and knowledge exchange. Moreover, ICC supports sustainable practice in agriculture by integrating gamification techniques to stimulate farm adopters, deploying VR technologies to model and visualise 3D farm environments and farm conditions, framing the field scenarios using VR headsets and Real-Time 3D engines, and leveraging edge technologies to facilitate secure and fast communication and collaboration between users involved. And through allowing blockchain-based marketplaces, ICC offers traceability from farm to fork – that is: from producer to consumer. It empowers informed decision-making through tailor-made recommendations generated by means of AI-driven analysis and technology democratisation, enabling small-scale and resource-limited farmers to get their voice heard. It connects with traditional knowledge, brings together multi-stakeholder interactions as well as establishes a participatory ecosystem to incentivise continuous growth and development towards more sustainable agro-ecological food systems. This integrated approach leverages the power of emerging technologies to provide sustainable solutions for a resilient food system, ensuring sustainable agriculture worldwide.

Keywords: blockchain, internet of things, artificial intelligence, decision support system, virtual reality, gamification, traceability, sustainable agriculture

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Authors: S. Arias

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New housing developments and the technological changes that this implies, adapt the styles of living of its residents, as well as new family structures and forms of work due to the particular needs of a specific group of people which involves different techniques of dealing with, organize, equip and use a particular territory. Currently, own their own space is increasingly important and the cities are faced with the challenge of providing the opportunity for such demands, as well as energy, water and waste removal necessary in the process of construction and occupation of new human settlements. Until the day of today, not has failed to give full response to these demands and needs, resulting in cities that grow without control, badly used land, avenues and congested streets. Buildings and dwellings have an important impact on the environment and on the health of the people, therefore environmental quality associated with the comfort of humans to the sustainable development of natural resources. Applied to architecture, this concept involves the incorporation of new technologies in all the constructive process of a dwelling, changing customs of developers and users, what must be a greater effort in planning energy savings and thus reducing the emissions Greenhouse Gases (GHG) depending on the geographical location where it is planned to develop. Since the techniques of occupation of the territory are not the same everywhere, must take into account that these depend on the geographical, social, political, economic and climatic-environmental circumstances of place, which in modified according to the degree of development reached. In the analysis that must be undertaken to check the degree of sustainability of the place, it is necessary to make estimates of the energy used in artificial air conditioning and lighting. In the same way is required to diagnose the availability and distribution of the water resources used for hygiene and for the cooling of artificially air-conditioned spaces, as well as the waste resulting from these technological processes. Based on the results obtained through the different stages of the analysis, it is possible to perform an energy audit in the process of proposing recommendations of sustainability in architectural spaces in search of energy saving, rational use of water and natural resources optimization. The above can be carried out through the development of a sustainable building code in develop technical recommendations to the regional characteristics of each study site. These codes would seek to build bases to promote a building regulations applicable to new human settlements looking for is generated at the same time quality, protection and safety in them. This building regulation must be consistent with other regulations both national and municipal and State, such as the laws of human settlements, urban development and zoning regulations.

Keywords: building regulations, housing, sustainability, technology

Procedia PDF Downloads 331

Authors: Gilberto Goracci, Fabio Curti

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This work presents a robust, light, and inexpensive algorithm to perform autonomous orbit determination using onboard magnetometer data in real-time. Magnetometers are low-cost and reliable sensors typically available on a spacecraft for attitude determination purposes, thus representing an interesting choice to perform real-time orbit determination without the need to add additional sensors to the spacecraft itself. Magnetic field measurements can be exploited by Extended/Unscented Kalman Filters (EKF/UKF) for orbit determination purposes to make up for GPS outages, yielding errors of a few kilometers and tens of meters per second in the position and velocity of a spacecraft, respectively. While this level of accuracy shows that Kalman filtering represents a solid baseline for autonomous orbit determination, it is not enough to provide a reliable state estimation in the absence of GPS signals. This work combines the solidity and reliability of the EKF with the versatility of a Recurrent Neural Network (RNN) architecture to further increase the precision of the state estimation. Deep learning models, in fact, can grasp nonlinear relations between the inputs, in this case, the magnetometer data and the EKF state estimations, and the targets, namely the true position, and velocity of the spacecraft. The model has been pre-trained on Sun-Synchronous orbits (SSO) up to 2126 kilometers of altitude with different initial conditions and levels of noise to cover a wide range of possible real-case scenarios. The orbits have been propagated considering J2-level dynamics, and the geomagnetic field has been modeled using the International Geomagnetic Reference Field (IGRF) coefficients up to the 13th order. The training of the module can be completed offline using the expected orbit of the spacecraft to heavily reduce the onboard computational burden. Once the spacecraft is launched, the model can use the GPS signal, if available, to fine-tune the parameters on the actual orbit onboard in real-time and work autonomously during GPS outages. In this way, the provided module shows versatility, as it can be applied to any mission operating in SSO, but at the same time, the training is completed and eventually fine-tuned, on the specific orbit, increasing performances and reliability. The results provided by this study show an increase of one order of magnitude in the precision of state estimate with respect to the use of the EKF alone. Tests on simulated and real data will be shown.

Keywords: artificial intelligence, extended Kalman filter, orbit determination, magnetic field

Procedia PDF Downloads 80

Authors: Zhijie Li, Wenhui Peng, Zelong Yuan, Jianchun Wang

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Turbulence is a complex phenomenon that plays a crucial role in various fields, such as engineering, atmospheric science, and fluid dynamics. Predicting and understanding its behavior over long time scales have been challenging tasks. Traditional methods, such as large-eddy simulation (LES), have provided valuable insights but are computationally expensive. In the past few years, machine learning methods have experienced rapid development, leading to significant improvements in computational speed. However, ensuring stable and accurate long-term predictions remains a challenging task for these methods. In this study, we introduce the implicit U-net enhanced Fourier neural operator (IU-FNO) as a solution for stable and efficient long-term predictions of the nonlinear dynamics in three-dimensional (3D) turbulence. The IU-FNO model combines implicit re-current Fourier layers to deepen the network and incorporates the U-Net architecture to accurately capture small-scale flow structures. We evaluate the performance of the IU-FNO model through extensive large-eddy simulations of three types of 3D turbulence: forced homogeneous isotropic turbulence (HIT), temporally evolving turbulent mixing layer, and decaying homogeneous isotropic turbulence. The results demonstrate that the IU-FNO model outperforms other FNO-based models, including vanilla FNO, implicit FNO (IFNO), and U-net enhanced FNO (U-FNO), as well as the dynamic Smagorinsky model (DSM), in predicting various turbulence statistics. Specifically, the IU-FNO model exhibits improved accuracy in predicting the velocity spectrum, probability density functions (PDFs) of vorticity and velocity increments, and instantaneous spatial structures of the flow field. Furthermore, the IU-FNO model addresses the stability issues encountered in long-term predictions, which were limitations of previous FNO models. In addition to its superior performance, the IU-FNO model offers faster computational speed compared to traditional large-eddy simulations using the DSM model. It also demonstrates generalization capabilities to higher Taylor-Reynolds numbers and unseen flow regimes, such as decaying turbulence. Overall, the IU-FNO model presents a promising approach for long-term dynamics prediction in 3D turbulence, providing improved accuracy, stability, and computational efficiency compared to existing methods.

Keywords: data-driven, Fourier neural operator, large eddy simulation, fluid dynamics

Procedia PDF Downloads 49

Authors: Aswathaman Vijayan, Manish Jha, Ullas Theertha

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Climate change and Global warming have become an issue for both developed and developing countries and perhaps the biggest threat to the environment. We at ITC Limited believe that a company’s performance must be measured by its Triple Bottom Line contribution to building economic, social and environmental capital. This Triple Bottom Line strategy focuses on - Embedding sustainability in business practices, Investing in social development and Adopting a low carbon growth path with a cleaner environment approach. The Agri Business Division - ILTD operates in the tobacco crop growing regions of Andhra Pradesh and Karnataka province of India. The Agri value chain of the company comprises of two distinct phases: First phase is Agricultural operations undertaken by ITC trained farmers and the second phase is Industrial operations which include marketing and processing of the agricultural produce. This research work covers the Greenhouse Gas (GHG) management strategy of ITC in the Agricultural operations undertaken by the farmers. The agriculture sector adds considerably to global GHG emissions through the use of carbon-based energies, use of fertilizers and other farming operations such as ploughing. In order to minimize the impact of farming operations on the environment, ITC has a taken a big leap in implementing system and process in reducing the GHG impact in farm value chain by partnering with the farming community. The company has undertaken a unique three-pronged approach for GHG management at the farm value chain: 1) GHG inventory at farm value chain: Different sources of GHG emission in the farm value chain were identified and quantified for the baseline year, as per the IPCC guidelines for greenhouse gas inventories. The major sources of emission identified are - emission due to nitrogenous fertilizer application during seedling production and main-field; emission due to diesel usage for farm machinery; emission due to fuel consumption and due to burning of crop residues. 2) Identification and implementation of technologies to reduce GHG emission: Various methodologies and technologies were identified for each GHG emission source and implemented at farm level. The identified methodologies are – reducing the consumption of chemical fertilizer usage at the farm through site-specific nutrient recommendation; Usage of sharp shovel for land preparation to reduce diesel consumption; implementation of energy conservation technologies to reduce fuel requirement and avoiding burning of crop residue by incorporation in the main field. These identified methodologies were implemented at farm level, and the GHG emission was quantified to understand the reduction in GHG emission. 3) Social and farm forestry for CO2 sequestration: In addition, the company encouraged social and farm forestry in the waste lands to convert it into green cover. The plantations are carried out with fast growing trees viz., Eucalyptus, Casuarina, and Subabul at the rate of 10,000 Ha of land per year. The above approach minimized considerable amount of GHG emission at the farm value chain benefiting farmers, community, and environment at a whole. In addition, the CO₂ stock created by social and farm forestry program has made the farm value chain to become environment-friendly.

Keywords: CO₂ sequestration, farm value chain, greenhouse gas, ITC limited

Procedia PDF Downloads 273

Authors: Marta Kaprzyk

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The cinema of Alejandro González Iñárritu hasn’t been subjected to a lot of detailed analysis yet, what makes it an exceptionally interesting research material. The purpose of this presentation is to discuss the significance of urban space in three films of this Mexican director, that forms Death Trilogy: ‘Amores Perros’ (2000), ‘21 Grams’ (2003) and ‘Babel’ (2006). The fact that in the aforementioned movies the urban space itself becomes an additional protagonist with its own identity, psychology and the ability to transform and affect other characters, in itself warrants for independent research and analysis. Independently, such mode of presenting urban space has another function; it enables the director to complement the rest of characters. The basis for methodology of this description of cinematographic space is to treat its visual layer as a point of departure for a detailed analysis. At the same time, the analysis itself will be supported by recognised academic theories concerning special issues, which are transformed here into essential tools necessary to describe the world (mise-en-scène) created by González Iñárritu. In ‘Amores perros’ the Mexico City serves as a scenery – a place full of contradictions- in the movie depicted as a modern conglomerate and an urban jungle, as well as a labyrinth of poverty and violence. In this work stylistic tropes can be found in an intertextual dialogue of the director with photographies of Nan Goldin and Mary Ellen Mark. The story recounted in ‘21 Grams’, the most tragic piece in the trilogy, is characterised by almost hyperrealistic sadism. It takes place in Memphis, which on the screen turns into an impersonal formation full of heterotopias described by Michel Foucault and non-places, as defined by Marc Augé in his essay. By contrast, the main urban space in ‘Babel’ is Tokio, which seems to perfectly correspond with the image of places discussed by Juhani Pallasmaa in his works concerning the reception of the architecture by ‘pathological senses’ in the modern (or, even more adequately, postmodern) world. It’s portrayed as a city full of buildings that look so surreal, that they seem to be completely unsuitable for the humans to move between them. Ultimately, the aim of this paper is to demonstrate the coherence of the manner in which González Iñárritu designs urban spaces in his Death Trilogy. In particular, the author attempts to examine the imperative role of the cities that form three specific microcosms in which the protagonists of the Mexican director live their overwhelming tragedies.

Keywords: cinematographic space, Death Trilogy, film Studies, González Iñárritu Alejandro, urban space

Procedia PDF Downloads 305

Authors: Ke-Jing Lee, Cheng-Jung Lee, Yu-Chi Chang, Li-Wen Wang, Yeong-Her Wang

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To avoid the cross-talk issue of only resistive random access memory (RRAM) cell, one transistor and one resistor (1T1R) architecture with a TiO₂-based RRAM cell connected with solution barium zirconate nickelate (BZN) organic thin film transistor (OTFT) device is successfully demonstrated. The OTFT were fabricated on a glass substrate. Aluminum (Al) as the gate electrode was deposited via a radio-frequency (RF) magnetron sputtering system. The barium acetate, zirconium n-propoxide, and nickel II acetylacetone were synthesized by using the sol-gel method. After the BZN solution was completely prepared using the sol-gel process, it was spin-coated onto the Al/glass substrate as the gate dielectric. The BZN layer was baked at 100 °C for 10 minutes under ambient air conditions. The pentacene thin film was thermally evaporated on the BZN layer at a deposition rate of 0.08 to 0.15 nm/s. Finally, gold (Au) electrode was deposited using an RF magnetron sputtering system and defined through shadow masks as both the source and drain. The channel length and width of the transistors were 150 and 1500 μm, respectively. As for the manufacture of 1T1R configuration, the RRAM device was fabricated directly on drain electrodes of TFT device. A simple metal/insulator/metal structure, which consisting of Al/TiO₂/Au structures, was fabricated. First, Au was deposited to be a bottom electrode of RRAM device by RF magnetron sputtering system. Then, the TiO₂ layer was deposited on Au electrode by sputtering. Finally, Al was deposited as the top electrode. The electrical performance of the BZN OTFT was studied, showing superior transfer characteristics with the low threshold voltage of −1.1 V, good saturation mobility of 5 cm²/V s, and low subthreshold swing of 400 mV/decade. The integration of the BZN OTFT and TiO₂ RRAM devices was finally completed to form 1T1R configuration with low power consumption of 1.3 μW, the low operation current of 0.5 μA, and reliable data retention. Based on the I-V characteristics, the different polarities of bipolar switching are found to be determined by the compliance current with the different distribution of the internal oxygen vacancies used in the RRAM and 1T1R devices. Also, this phenomenon can be well explained by the proposed mechanism model. It is promising to make the 1T1R possible for practical applications of low-power active matrix flat-panel displays.

Keywords: one transistor and one resistor (1T1R), organic thin-film transistor (OTFT), resistive random access memory (RRAM), sol-gel

Procedia PDF Downloads 329

Authors: Mandeep Singh Azad.Dibyendu Chakraborty, Vikas Vohra

Abstract:

Introduction: Poonch is one of the remotest districts of the Jammu and Kashmir (UT) and situated on international borders. This native poultry population in these areas is quite hardy and thrives well in adverse climatic conditions. Till date, no local breed from this area (Jammu Province) has been characterized thus present study was undertaken with the main objectives of molecular characterization of ChB6 gene in local native chicken of Poonch region located at international borders between India and Pakistan. The chicken B-cell marker (ChB6) gene has been proposed as a candidate gene in regulating B-cell development. Material and Method: RNA was isolated by Blood RNA Purification Kit (HiPura) and Trizol method from whole blood samples. Positive PCR products with size 1110 bp were selected for further purification, sequencing and analysis. The amplified PCR product was sequenced by Sangers dideoxy chain termination method. The obtained sequence of ChB6 gene of Poonchi chicken were compared by MEGAX software. BioEdit software was used to construct phylogenic tree, and Neighbor Joining method was used to infer evolutionary history. In order to compute evolutionary distance Maximum Composite Likelihood method was used. Results: The positively amplified samples of ChB6 genes were then subjected to Sanger sequencing with “Primer Walking. The sequences were then analyzed using MEGA X and BioEdit software. The sequence results were compared with other reported sequence from different breed of chicken and with other species obtained from the NCBI (National Center for Biotechnology Information). ClustalW method using MEGA X software was used for multiple sequence alignment. The sequence results of ChB6 gene of Poonchi chicken was compared with Centrocercus urophasianus, G. gallus mRNA for B6.1 protein, G. gallus mRNA for B6.2, G. gallus mRNA for B6.3, Gallus gallus B6.1, Halichoeres bivittatus, Miniopterus fuliginosus Ferringtonia patagonica, Tympanuchus phasianellus. The genetic distances were 0.2720, 0.0000, 0.0245, 0.0212, 0.0147, 1.6461, 2.2394, 2.0070 and 0.2363 for ChB6 gene of Poonchi chicken sequence with other sequences in the present study respectively. Sequencing results showed variations between different species. It was observed that AT content were higher then GC content for ChB6 gene. The lower AT content suggests less thermostable. It was observed that there was no sequence difference within the Poonchi population for ChB6 gene. The high homology within chicken population indicates the conservation of ChB6 gene. The maximum difference was observed with Miniopterus fuliginosus (Eastern bent-wing bat) followed by Ferringtonia patagonica and Halichoeres bivittatus. Conclusion: Genetic variation is the essential component for genetic improvement. The results of immune related gene Chb6 shows between population genetic variability. Therefore, further association studies of this gene with some prevalent diseases in large population would be helpful to identify disease resistant/ susceptible genotypes in the indigenous chicken population.

Keywords: ChB6, sequencing, ClustalW, genetic distance, poonchi chicken, SNP

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Authors: Despoina Mouratidis, Katia Lida Kermanidis

Abstract:

Machine translation (MT) is a very important task in Natural Language Processing (NLP). MT evaluation is crucial in MT development, as it constitutes the means to assess the success of an MT system, and also helps improve its performance. Several methods have been proposed for the evaluation of (MT) systems. Some of the most popular ones in automatic MT evaluation are score-based, such as the BLEU score, and others are based on lexical similarity or syntactic similarity between the MT outputs and the reference involving higher-level information like part of speech tagging (POS). This paper presents a language-independent machine learning framework for classifying pairwise translations. This framework uses vector representations of two machine-produced translations, one from a statistical machine translation model (SMT) and one from a neural machine translation model (NMT). The vector representations consist of automatically extracted word embeddings and string-like language-independent features. These vector representations used as an input to a multi-layer neural network (NN) that models the similarity between each MT output and the reference, as well as between the two MT outputs. To evaluate the proposed approach, a professional translation and a "ground-truth" annotation are used. The parallel corpora used are English-Greek (EN-GR) and English-Italian (EN-IT), in the educational domain and of informal genres (video lecture subtitles, course forum text, etc.) that are difficult to be reliably translated. They have tested three basic deep learning (DL) architectures to this schema: (i) fully-connected dense, (ii) Convolutional Neural Network (CNN), and (iii) Long Short-Term Memory (LSTM). Experiments show that all tested architectures achieved better results when compared against those of some of the well-known basic approaches, such as Random Forest (RF) and Support Vector Machine (SVM). Better accuracy results are obtained when LSTM layers are used in our schema. In terms of a balance between the results, better accuracy results are obtained when dense layers are used. The reason for this is that the model correctly classifies more sentences of the minority class (SMT). For a more integrated analysis of the accuracy results, a qualitative linguistic analysis is carried out. In this context, problems have been identified about some figures of speech, as the metaphors, or about certain linguistic phenomena, such as per etymology: paronyms. It is quite interesting to find out why all the classifiers led to worse accuracy results in Italian as compared to Greek, taking into account that the linguistic features employed are language independent.

Keywords: machine learning, machine translation evaluation, neural network architecture, pairwise classification

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