Search results for: traditional scheduling algorithms

Authors: Zafer Yüce, Paşa Yayla, Alev Taşkın

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There are heaps of analytical methods to estimate the crack growth life of a component. Soft computing methods have an increasing trend in predicting fatigue life. Their ability to build complex relationships and capability to handle huge amounts of data are motivating researchers and industry professionals to employ them for challenging problems. This study focuses on soft computing methods, especially random forest regressors and artificial neural networks with hyperparameter optimization algorithms such as grid search and random grid search, to estimate the crack growth life of an aircraft wing splice joint under variable amplitude loading. TensorFlow and Scikit-learn libraries of Python are used to build the machine learning models for this study. The material considered in this work is 7050-T7451 aluminum, which is commonly preferred as a structural element in the aerospace industry, and regarding the crack type; corner crack is used. A finite element model is built for the joint to calculate fastener loads and stresses on the structure. Since finite element model results are validated with analytical calculations, findings of the finite element model are fed to AFGROW software to calculate analytical crack growth lives. Based on Fighter Aircraft Loading Standard for Fatigue (FALSTAFF), 90 unique fatigue loading spectra are developed for various load levels, and then, these spectrums are utilized as inputs to the artificial neural network and random forest regression models for predicting crack growth life. Finally, the crack growth life predictions of the machine learning models are compared with analytical calculations. According to the findings, a good correlation is observed between analytical and predicted crack growth lives.

Keywords: aircraft, fatigue, joint, life, optimization, prediction.

Procedia PDF Downloads 175

Authors: Xian Chen

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In recent years, the tendency that the decline of material and social vitality of old city in China becomes more and more serious. Nowadays, transformation and renewal of the old city have become a hot topic in urban research. The traditional mode of large-scale promotion has been criticized. Thus, exploration of new ways to update the city turns to be a necessity on the way of sustainable urban development. Pocket Park is a small city open space, its location choose is based on abandoned or idle lands on urban structure, is scattered or hidden in corner of the urban. It has a great significance on improving the old city environment. Based on the theory of ‘pocket park’, this paper summarizes the successful experience of domestic and foreign practice, and discusses the update strategies which are suitable for China's national conditions according to the characteristics and predicament of the old city in China. The main methods and results are as follows: 1)Based on the conception of ‘pocket park’, though describing the research status in domestic and foreign, summarizing the experience which is worth learning and existing problems. 2) From the analysis of ‘pocket park’ function, general design principles and types of the deep-seated difficulties in renewal the old city and the possibility of the application of ‘pocket park’,the varied implementation of ‘pocket park’ form are established, and application value in the old city renewal are summed up. 3) It can’t be denied that pocket park plays an irreplaceable role in solving the recession and renewing the vitality of the old city. Anymore, It is recommended to develop corresponding supportive development policies.

Keywords: sustainable development, strategy, old city renewal, pocket park

Procedia PDF Downloads 350

Authors: Abubakar Samaila

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Pastoralism has been an old practice in the Sahel region of west Africa. In recent years, pastoralists in Nigeria have increasingly been migrating on seasonal transhumance southward from the neighboring countries, especially Niger Republic, in search of better grazing conditions due to mainly, climate change. This has increased pressure on farm lands which instigate farmer-herder conflicts. These conflicts occur mainly between farmers and pastoralists but also between pastoralist groups themselves. However, there has been a shift in these conflicts recently to involve traditional institutions and, in some cases, the local authorities along the borderlands. The involvement of local institutions in the conflict has created an incentive to local actors, particularly pastoralcommunity-based groups, in responding to these violent threats. As pastoralists are mobile, these conflicts became difficult to contain and, thus, spill across borders. Consequently, the conflict has now transformed into an urbanized regional conflicts that involve some major cities along the Nigeria-Niger borderlands; Sokoto, Zamfara, and Katsina on the Nigerian side andDosso, Tahoa andMaradi in Niger republic. These areas are now experiencing unprecedented growing wave of violence that have become complex and escalates into a hydra-social conflict. The aim of this research is to investigate how the fluidities of Nigeria-Niger borderland intensified armed conflicts between the local pastoral organizations and sedentary populationspreading to some urban cities along the borderlands. The paper further suggests alternative approaches towards addressing the perennial crisis in African borderlands.

Keywords: pastoralism, climate change, conflict, nigeria, niger, borderlands

Procedia PDF Downloads 92

Authors: V. Ayishwarya Bharathi, S. M. Hasker, J. Indhu, M. Mohamed Azarudeen, G. Gowthami, R. Vinoth Rajan, N. Vijayarangan

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Identification of water quality conditions in a river system based on limited observations is an essential task for meeting the goals of environmental management. The traditional method of water quality testing is to collect samples manually and then send to laboratory for analysis. However, it has been unable to meet the demands of water quality monitoring today. So a set of automatic measurement and reporting system of water quality has been developed. In this project specifies Water quality parameters collected by multi-parameter water quality probe are transmitted to data processing and monitoring center through GPRS wireless communication network of mobile. The multi parameter sensor is directly placed above the water level. The monitoring center consists of GPRS and micro-controller which monitor the data. The collected data can be monitor at any instant of time. In the pollution control board they will monitor the water quality sensor data in computer using Visual Basic Software. The system collects, transmits and processes water quality parameters automatically, so production efficiency and economy benefit are improved greatly. GPRS technology can achieve well within the complex environment of poor water quality non-monitored, and more specifically applicable to the collection point, data transmission automatically generate the field of water analysis equipment data transmission and monitoring.

Keywords: multiparameter sensor, GPRS, visual basic software, RS232

Procedia PDF Downloads 412

Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

Procedia PDF Downloads 141

Authors: Mengping Cheng, John Everatt, Alison Arrow, Amanda Denston

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Based on the available evidence, Chinese heritage language learners have a basic level of Chinese language proficiency with lower capability in literacy compared to speaking. Low levels of literacy are likely related to the lack of reading activities in current textbook-based pedagogy used in Chinese community schools. The present study aims to use Reading to Learn pedagogy which is a top-down language learning model and test the effectiveness of Reading to Learn on Chinese heritage learners’ written vocabulary acquisition. A quasi-experiment with the pre-test/post-test non-equivalent group design was conducted. The experimental group received Reading to Learn instructions and the control group had traditional textbook-based instructions. Participants were given Chinese characters tasks (a recognize-and-read task and a listen-and-point task), vocabulary tasks (a receptive vocabulary task and a productive vocabulary task) and a sentence cloze test in pre-tests and post-tests. Data collection is in progress and results will be available shortly. If the results show more improvement of Chinese written vocabulary in the experimental group than in the control group, it will be recommended that Reading to Learn pedagogy is valuable to be used to maintain and develop Chinese heritage language literacy.

Keywords: Chinese heritage language, experimental research, Reading to Learn pedagogy, vocabulary acquisition

Procedia PDF Downloads 154

Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

Procedia PDF Downloads 161

Authors: J. Bahrawi, M. Elhag

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Estimation of evapotranspiration is always a major component in water resources management. Traditional techniques of calculating daily evapotranspiration based on field measurements are valid only for local scales. Earth observation satellite sensors are thus used to overcome difficulties in obtaining daily evapotranspiration measurements on regional scale. The Surface Energy Balance System (SEBS) model was adopted to estimate daily evapotranspiration and relative evaporation along with other land surface energy fluxes. The model requires agro-climatic data that improve the model outputs. Advance Along Track Scanning Radiometer (AATSR) and Medium Spectral Resolution Imaging Spectrometer (MERIS) imageries were used to estimate the daily evapotranspiration and relative evaporation over the entire Nile Delta region in Egypt supported by meteorological data collected from six different weather stations located within the study area. Daily evapotranspiration maps derived from SEBS model show a strong agreement with actual ground-truth data taken from 92 points uniformly distributed all over the study area. Moreover, daily evapotranspiration and relative evaporation are strongly correlated. The reliable estimation of daily evapotranspiration supports the decision makers to review the current land use practices in terms of water management, while enabling them to propose proper land use changes.

Keywords: daily evapotranspiration, relative evaporation, SEBS, AATSR, MERIS, Nile Delta

Procedia PDF Downloads 259

Authors: Hung-Yuan Chang, Wen-Lung Chiang, Kuo-Liang Wu, Chen-Tsung Lin

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National Space Organization (NSPO) has completed in 2014 the development of a space-borne GPS receiver, including design, manufacture, comprehensive functional test, environmental qualification test and so on. The main performance of this receiver include 8-meter positioning accuracy, 0.05 m/sec speed-accuracy, the longest 90 seconds of cold start time, and up to 15g high dynamic scenario. The receiver will be integrated in the autonomous FORMOSAT-7 NSPO-Built satellite scheduled to be launched in 2019 to execute pre-defined scientific missions. The flight model of this receiver manufactured in early 2015 will pass comprehensive functional tests and environmental acceptance tests, etc., which are expected to be completed by the end of 2015. The space-borne GPS receiver is a pure software design in which all GPS baseband signal processing are executed by a digital signal processor (DSP), currently only 50% of its throughput being used. In response to the booming global navigation satellite systems, NSPO will gradually expand this receiver to become a multi-mode, multi-band, high-precision navigation receiver, and even a science payload, such as the reflectometry receiver of a global navigation satellite system. The fundamental purpose of this extension study is to port some software algorithms such as signal acquisition and correlation, reused code and large amount of computation load to the FPGA whose processor is responsible for operational control, navigation solution, and orbit propagation and so on. Due to the development and evolution of the FPGA is pretty fast, the new system architecture upgraded via an FPGA should be able to achieve the goal of being a multi-mode, multi-band high-precision navigation receiver, or scientific receiver. Finally, the results of tests show that the new system architecture not only retains the original overall performance, but also sets aside more resources available for future expansion possibility. This paper will explain the detailed DSP/FPGA architecture, development, test results, and the goals of next development stage of this receiver.

Keywords: space-borne, GPS receiver, DSP, FPGA, multi-mode multi-band

Procedia PDF Downloads 369

Authors: Berhane Gebreslassie

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Conventional commericial buildings are among the highest unwisely consumes enormous amount of energy and as consequence produce significant amount Carbon Dioxide (CO2). Traditional/conventional buildings have been built for years without consideration being given to their impact on the global warming issues as well as their CO2 contributions. Since 1973, simulation of Green Building (GB) for Energy Efficiency started and many countries in particular the US showed a positive response to minimize the usage of energy in respect to reducing the CO2 emission. As a consequence many software companies developed their own unique building energy efficiency simulation software, interfacing interoperability with Building Information Modeling (BIM). The last decade has witnessed very rapid growing number of researches on GB energy efficiency system. However, the study also indicates that the results of current GB simulation are not yet satisfactory to meet the objectives of GB. In addition most of these previous studies are unlikely excluded the studies of ultimate building energy efficiencies simulation. The aim of this project is to meet the objectives of GB by design, modeling and simulation of building ultimate energy efficiencies system. This research project presents multi-level, L-shape office building in which every particular part of the building materials has been tested for energy efficiency. An overall of 78.62% energy is saved, approaching to NetZero energy saving. Furthermore, the building is implements with distributed energy resources like renewable energies and integrating with Smart Building Automation System (SBAS) for controlling and monitoring energy usage.

Keywords: ultimate energy saving, optimum energy saving, green building, sustainable materials and renewable energy

Procedia PDF Downloads 275

Authors: E. Kharaishvili, G. Erkomaishvili, M. Chavleishvili

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The paper evaluates the natural and resource potential of agriculture, a traditional sector for Georgia. It is concluded that despite favorable conditions the rate of development of the sector is lower compared to other sectors of the economy, self-sufficiency rate for locally produced agricultural products is low; on average, import of food is 4 times higher compared to export, and the country faces considerable challenges in this regard. Tendencies of self-sufficiency rates are studied, and it is concluded that the indicators of export and import of agro-food products increase in accordance with the tendency of increasing production in agricultural sector. The paper substantiates stimulating impact of international trade on agricultural development. Two alternative strategies are assessed in this respect: 1) export stimulation, and 2) import replacement strategies. It is concluded that significant tendencies are observed in agro-food sector of Georgia; in particular, productivity is low; import volume significantly exceeds the export volume. It is considered that the growth of export will allow Georgia to overcome limited opportunities of local market and encourage increasing competitiveness. Various tools of economic policy are suggested for achieving these goals; in particular to subsidize export, optimize trade barriers, manage exchange rates effectively, offer special financial services, provide insurance for export, etc.

Keywords: agro-food sector, trend of production, export stimulation, economic policy

Procedia PDF Downloads 206

Authors: Dina Zakeri, Ali Aminzad

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Multimedia-assisted teaching results in eliminating traditional training barriers, facilitating the cognition process and upgrading learning outcomes. This study attempted to examine the effects of implementing multimedia on teaching technical translation model and on the technical text translation ability of Iranian students of translation. To fulfill the purpose of the study, a total of forty-six learners were selected out of fifty-seven participants in a higher education center in Tehran based on their scores in Preliminary English Test (PET) and were divided randomly into the experimental and control groups. Prior to the treatment, a technical text translation questionnaire was devised and then approved and validated by three assistant professors of technical fields and three assistant professors of Teaching English as a Foreign Language (TEFL) at the university. This questionnaire was administered as a pretest to both groups. Control and experimental groups were trained for five successive weeks using identical course books but with a different lesson plan that allowed employing multimedia for the experimental group only. The devised and approved questionnaire was administered as a posttest to both groups at the end of the instruction. A multivariate ANOVA was run to compare the two groups’ means on the PET, pretest and posttest. The results showed the rejection of all null hypotheses of the study and revealed that multimedia significantly improved technical text translation ability of the learners.

Keywords: multimedia, multimedia-mediated teaching, technical translation model, technical text, translation ability

Procedia PDF Downloads 129

Authors: Nidhal Mgadmi, Abdelhafidh Othmani

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This article examines the causal relationship between stock indices and cryptocurrencies during the current war between Russia and Ukraine. The econometric investigation runs from February 24, 2022, to April 12, 2023, focusing on seven stock market indices (S&P500, DAX, CAC40, Nikkei, TSX, MOEX, and PFTS) and seven cryptocurrencies (Bitcoin, Ethereum, Litcoin, Dash, Ripple, DigiByte and XEM). In this article, we try to understand how investors react to fluctuations in financial assets to seek safe havens in cryptocurrencies. We used dynamic causality to detect a possible causal relationship in the short term and seven models to estimate the long-term relationship between cryptocurrencies and financial assets. The causal relationship between financial market indexes and cryptocurrency coins in the short run indicates that three famous cryptocurrencies (BITCOIN, ETHEREUM, RIPPLE) and the two digital assets with minor popularity (XEM, Digibyte) are impacted by the German, Russian, and Ukrainian stock markets. In the long run, we found a positive and significate effect of the American, Canadian, French, and Ukrainian stock market indexes on Bitcoin. Thus, the stability of the traditional financial markets during the current war period can be explained on the one hand by investors’ fears of an unstable business climate, and on the other hand, by speculators’ sentiment towards new electronic products, which are perceived as hedging instruments and a safe haven in the face of the conflict between Ukraine and Russia.

Keywords: causality, stock indices, cryptocurrency, war, Russia, Ukraine

Procedia PDF Downloads 67

Authors: Cecilia Jatu, Adventino

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Gedangsari is located in Gunungkidul, Yogyakarta Province, which has several criteria to be used as a new geosite object. The research area is located in the southern mountain zone of Java, composed of 5 rock formations with Oligocene up to Middle Miocene age. The purpose of this study is to reveal the potential of geotourism and the geoheritage to be proposed as a new geosite and to make a geosite map of Gedangsari. The research method used is descriptive data collection and which includes quantitative geological data collection, geotourism, and heritage sites, then supported by petrographic analysis, geological structure, geological mapping, and SWOT analysis. The geological data proved that Gedangsari consists of igneous rock (intrusion), pyroclastic rock, and sediment rock. This condition caused many varieties and particular geomorphological platform. Geotourism that include in Gedangsari are Luweng Sampang Canyon, Gedangsari Bouma Sequence, Watugajah Columnar Joint, Gedangsari Marine Fan Sediment, and Tegalrejo Waterfall. There is also Tegalrejo Village, which can be considered as geoheritage site because of its culture and batik traditional cloth. The results of the SWOT analysis, Gedangsari geosite must be developed and appropriately promoted in order to improve the existence. The development of geosite area will have a significant impact that improve the economic growth of the surrounding community and can be used by the government as base information for sustainable development. In addition, the making of an educational map about the geological conditions and geotourism location of the Gedangsari geosite can increase the people's knowledge about Gedangsari.

Keywords: Gedangsari, geoheritage, geotourism, geosite

Procedia PDF Downloads 122

Authors: Sixing Chen, Shuai Yang

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Online celebrity business, also known as Internet celebrity business (or Wanghong business in Chinese), is an emerging relational C2C business model, and an alternative to traditional C2C transactional business models. There are already millions of these consumers, and this number is growing. In this model, consumer purchase decisions are driven by recommendations and endorsements in videos posted online by celebrities. The purpose of this paper is to determine the relational constructs within consumer relationships in the Internet celebrity business model and to investigate relationships between the constructs and consumer purchase intention. A questionnaire-based study was conducted with consumers who had an awareness of, or prior purchase experience with online celebrities. The results of exploratory factor analysis (EFA) and multiple regression analysis revealed three valid relational constructs: product experience sharing, lifestyle association, and real-time interaction. This study indicated that these constructs had the direct effect on consumer preference and purchase intention. The findings of this study provide insight into a business model in which online shopping is driven by celebrities. They suggest that online celebrities should pay more attention to product experience sharing, life style association and real-time interaction for managing their product promotions. These are the most salient factors with respect to the relational constructs identified in this study.

Keywords: customer relationship, customer to customer, Internet celebrity, online celebrity, online marketing, purchase intention

Procedia PDF Downloads 318

Authors: Abed Hannane, Rouag Noureddine

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The present study aims to evaluate the association of fresh garlic (Allium sativum L.) and storage at 4°C in preserving the microbiological, nutritional, and sanitary quality of Merguez-type sausages prepared and sold locally from meat offal. The analysis focused on the evaluation of the microbiological quality of fifteen samples randomly taken from several butcheries in the wilaya of BBA, eastern Algeria. The bacteriological analysis revealed the presence of 6.88.10⁵ CFU/g of total aerobic bacteria, 5.39.10⁵ CFU/g of total coliforms, 2.23.10⁵ CFU/g of fecal coliforms, 2.43.103 CFU/g of Escherichia coli and 1.8.10⁵ CFU/g of coagulase-positive staphylococci, values higher than Algerian standards. The addition of fresh garlic as an antibacterial preservative at concentrations of 0.06, 0.12, 0.18, and 0.24 g/g to ground beef samples and stored in the refrigerator at 4°C for 15 days. The addition of garlic to Merguez made it possible to significantly reduce the presence of different bacterial groups during their refrigerated storage, compared to untreated meat, bringing it below the standards defined in the matter. Thus, the use of garlic as a food additive at a concentration of 0.12 g/g was sufficient to obtain levels according to Algerian standards equal to 1.8.10⁴ CFU/g of total aerobic bacteria, 9.48.10³ CFU/ g of total coliforms, 3.68.10³ UFC/g fecal coliforms, 4.56.10² UFC/g of E.coli 2.39.10⁴ UFC/g of coagulase-positive staphylococci. It is clear that thanks to the addition of garlic to Merguez, the sanitary quality has been improved by reducing the aerobic bacterial load and increasing the shelf life at 4°C.

Keywords: antimicrobial effect, garlic, sausage, storage

Procedia PDF Downloads 100

Authors: Yessi Rahmawati, Andiga Kusuma Nur Ichsan, Fitria Nur Anggraeni

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Climate change is one of the focus studies that many researchers focus on in the present world, either in the emerging countries or developed countries which is one of the main pillars on Sustainable Development Goals (SDGs). There is on-going discussion that climate change can affect natural disaster, namely drought, storm, flood, and many others; and also the impact on human life. East Java is the best performances and has economic potential that should be utilized. Despite the economic performance and high agriculture productivity, East Java has the highest number of people under the poverty line. The present study is to measuring the contribution of drought and productivity of agriculture to the poverty in East Java, Indonesia, using spatial econometrics analysis. The authors collect data from 2008 – 2015 from Indonesia’s Ministry of Agriculture, Natural Disaster Management Agency (BNPB), and Official Statistic (BPS). First, the result shows the existence of spatial autocorrelation between drought and poverty. Second, the present research confirms that there is strong relationship between drought and poverty. the majority of farmer in East Java are still relies on the rainfall and traditional irrigation system. When the drought strikes, mostly the farmer will lose their income; make them become more vulnerable household, and trap them into poverty line. The present research will give empirical studies regarding drought and poverty in the academics world.

Keywords: SDGs, drought, poverty, Indonesia, spatial econometrics, spatial autocorrelation

Procedia PDF Downloads 154

Authors: Alexander Rincón Ruiz

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This article is based on an exhaustive review and interdisciplinary effort spanning three years. It involved interviews, dialogues, discussion panels, and collective work on various visions of bio-economy in Colombia. The dialogue included government institutions, universities, local communities, activist groups, research institutes, the productive sector, and politicians, integrating perspectives such as Latin American environmental thought, complexity theory, modern visions, local worldviews (Afro-Colombian, indigenous, peasant), decoloniality, political ecology, ecological economics, and environmental economies. This work highlighted the need to redefine the traditional bio-economy concept, typically focused on markets and biotechnology, and to revisit the original idea of a bio-economy as an ‘economy for life’. In a country as diverse as Colombia—both biophysically and in its varied relationships with the territory—this redefinition is crucial. It emphasizes alternative logics of well-being related to resilience, care, and cooperation, reflecting Indigenous, Afro-Colombian, and peasant worldviews. This article is significant for proposing, for the first time, a viable approach to diverse and alternative economies for life tailored to the Colombian context. It represents not only academic work but also a political commitment to inclusion and plurality, aligning with the Colombian context and potentially extendable to other regions.

Keywords: ecological economics, decoloniality, complexity, Biodiversity

Procedia PDF Downloads 34

Authors: Nirmal Kumar Verma, Pallavi Jha

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Generation of the electromagnetic radiation oscillating at the frequencies in the terahertz range by propagation of two-color laser pulses in plasma is an active area of research due to its potential applications in various areas, including security screening, material characterization, and spectroscopic techniques. Due to nonionizing nature and the ability to penetrate several millimeters, THz radiation is suitable for diagnosis of cancerous cells. Traditional THz emitters like optically active crystals, when irradiated with high power laser radiation, are subject to material breakdown and hence low conversion efficiencies. This problem is not encountered in laser-plasma based THz radiation sources. The present paper is devoted to the study of the enhanced electromagnetic radiation generation by propagation of two-color, linearly polarized laser pulses through the magnetized plasma. The two lasers pulse orthogonally polarized are co-propagating along the same direction. The direction of the external magnetic field is such that one of the two laser pulses propagates in the ordinary mode, while the other pulse propagates in the extraordinary mode through the homogeneous plasma. A transverse electromagnetic wave with frequency in the THz range is generated due to the presence of the static magnetic field. It is observed that larger amplitude terahertz can be generated by mixing of ordinary and extraordinary modes of two-color laser pulses as compared with a single laser pulse propagating in the extraordinary mode.

Keywords: two-color laser pulses, electromagnetic radiation, magnetized plasma, ordinary and extraordinary modes

Procedia PDF Downloads 285

Authors: Philipp Galkin

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Government policy is a critical factor in the understanding of energy markets. Regardless, it is rarely approached systematically from a research perspective. Gaining a precise understanding of what policies exist, their intended outcomes, geographical extent, duration, evolution, etc. would enable the research community to answer a variety of questions that, for now, are either oversimplified or ignored. Policy, on its surface, also seems a rather unstructured and qualitative undertaking. There may be quantitative components, but incorporating the concept of policy analysis into quantitative analysis remains a challenge. The KAPSARC Energy Policy Database (KEPD) is intended to address these two energy policy research limitations. Our approach is to represent policies within a quantitative library of the specific policy measures contained within a set of legal documents. Each of these measures is recorded into the database as a single entry characterized by a set of qualitative and quantitative attributes. Initially, we have focused on the major laws at the national level that regulate coal in China. However, KAPSARC is engaged in various efforts to apply this methodology to other energy policy domains. To ensure scalability and sustainability of our project, we are exploring semantic processing using automated computer algorithms. Automated coding can provide a more convenient input data for human coders and serve as a quality control option. Our initial findings suggest that the methodology utilized in KEPD could be applied to any set of energy policies. It also provides a convenient tool to facilitate understanding in the energy policy realm enabling the researcher to quickly identify, summarize, and digest policy documents and specific policy measures. The KEPD captures a wide range of information about each individual policy contained within a single policy document. This enables a variety of analyses, such as structural comparison of policy documents, tracing policy evolution, stakeholder analysis, and exploring interdependencies of policies and their attributes with exogenous datasets using statistical tools. The usability and broad range of research implications suggest a need for the continued expansion of the KEPD to encompass a larger scope of policy documents across geographies and energy sectors.

Keywords: China, energy policy, policy analysis, policy database

Procedia PDF Downloads 323

Authors: Mohsen Azarmjoo, Mehdi Mehdizadeh Koupaei, Maryam Mehdizadeh Koupaei, Asghar Mahdlouei Azar

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The increasing prevalence of wireless networks in our daily lives has made them indispensable. The aim of this research is to investigate the management of information transfer in wireless networks and the integration of renewable solar energy resources in a residential building. The focus is on the transmission of electricity and information through wireless networks, as well as the utilization of sensors and wireless fire alarm systems. The research employs a descriptive approach to examine the transmission of electricity and information on a wireless network with electric and optical telephone lines. It also investigates the transmission of signals from sensors and wireless fire alarm systems via radio waves. The methodology includes a detailed analysis of security, comfort conditions, and costs related to the utilization of wireless networks and renewable solar energy resources. The study reveals that it is feasible to transmit electricity on a network cable using two pairs of network cables without the need for separate power cabling. Additionally, the integration of renewable solar energy systems in residential buildings can reduce dependence on traditional energy carriers. The use of sensors and wireless remote information processing can enhance the safety and efficiency of energy usage in buildings and the surrounding spaces.

Keywords: renewable energy, intelligentization, wireless sensors, fire alarm system

Procedia PDF Downloads 54

Authors: Djeddi Khaled, Houssou Hind, Miloudi Abdellatif, Rabah Siham

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In the field of veterinary medicine, there is a growing application of artificial intelligence (AI) for diagnosing bovine mastitis, a prevalent inflammatory disease in dairy cattle. AI technologies, such as automated milking systems, have streamlined the assessment of key metrics crucial for managing cow health during milking and identifying prevalent diseases, including mastitis. These automated milking systems empower farmers to implement automatic mastitis detection by analyzing indicators like milk yield, electrical conductivity, fat, protein, lactose, blood content in the milk, and milk flow rate. Furthermore, reports highlight the integration of somatic cell count (SCC), thermal infrared thermography, and diverse systems utilizing statistical models and machine learning techniques, including artificial neural networks, to enhance the overall efficiency and accuracy of mastitis detection. According to a review of 15 publications, machine learning technology can predict the risk and detect mastitis in cattle with an accuracy ranging from 87.62% to 98.10% and sensitivity and specificity ranging from 84.62% to 99.4% and 81.25% to 98.8%, respectively. Additionally, machine learning algorithms and microarray meta-analysis are utilized to identify mastitis genes in dairy cattle, providing insights into the underlying functional modules of mastitis disease. Moreover, AI applications can assist in developing predictive models that anticipate the likelihood of mastitis outbreaks based on factors such as environmental conditions, herd management practices, and animal health history. This proactive approach supports farmers in implementing preventive measures and optimizing herd health. By harnessing the power of artificial intelligence, the diagnosis of bovine mastitis can be significantly improved, enabling more effective management strategies and ultimately enhancing the health and productivity of dairy cattle. The integration of artificial intelligence presents valuable opportunities for the precise and early detection of mastitis, providing substantial benefits to the dairy industry.

Keywords: artificial insemination, automatic milking system, cattle, machine learning, mastitis

Procedia PDF Downloads 65

Authors: A. Babaei Zarch, S. Kianbakht, H. Fallah Huseini, P. Changaei, A. Mirjalili, J. Salehi

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Background: Malva Sylvestris L. has antioxidant property and is widely used in the traditional medicine to treat gastrointestinal, respiratory, skin and urological disorders. Objective: In this study the protective effect of Malva Sylvestris against sodium fluoride-induced nephrotoxicity in rat were evaluated. Methods: The Malva Sylvestris flower extract was prepared and injected intraperitoneally at the doses of 100, 200, 400 mg/kg/day to group of rats ( 10 in each group) for 1 week and subsequently 600 ppm sodium fluoride was added to the rats drinking water for 1 additional week. After these steps, the rats’ serum levels of urea, creatinine, reduced glutathione, catalase and malondialdehyde were determined. The histopathologies of the rats’ kidneys were also studied. Results: Sodium fluoride administration increased levels of BUN, creatinine glutathione, catalase activity and decreased malondialdehyde indicating induction of nephrotoxicity in rats. Malva Sylvestris extract pretreatment significantly decreased the BUN and creatinine levels (P<0.05). Moreover, the levels of catalase and glutathione were increased by Malva, and this increase were also statistically significant (P<0.05). All three doses of Malva extract decreased the malondialdehyde level, but it was significant only for the doses of 200 and 400 mg/kg/day (P<0.05). Histopathological findings also showed protective effect of Malva against renal damage induced by sodium fluoride. Conclusion: The results suggest that Malva Sylvestris has protective effect against sodium fluoride-induced nephrotoxicity maybe mediated by its antioxidant property.

Keywords: malva sylvestris, nephrotoxicity, sodium fluoride, rat

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Authors: Ahmed Abdulghani Taha, Mohammad Abdulghani Taha

Abstract:

This study aims at being acquainted with the using the body fat percentage (%BF) with body Mass Index (BMI) as input parameters in fuzzy logic decision support system to predict properly the lifted weight for students at weightlifting class lift according to his abilities instead of traditional manner. The sample included 53 male students (age = 21.38 ± 0.71 yrs, height (Hgt) = 173.17 ± 5.28 cm, body weight (BW) = 70.34 ± 7.87.6 kg, Body mass index (BMI) 23.42 ± 2.06 kg.m-2, fat mass (FM) = 9.96 ± 3.15 kg and fat percentage (% BF) = 13.98 ± 3.51 %.) experienced the weightlifting class as a credit and has variance at BW, Hgt and BMI and FM. BMI and % BF were taken as input parameters in FUZZY logic whereas the output parameter was the lifted weight (LW). There were statistical differences between LW values before and after using fuzzy logic (Diff 3.55± 2.21, P > 0.001). The percentages of the LW categories proposed by fuzzy logic were 3.77% of students to lift 1.0 fold of their bodies; 50.94% of students to lift 0.95 fold of their bodies; 33.96% of students to lift 0.9 fold of their bodies; 3.77% of students to lift 0.85 fold of their bodies and 7.55% of students to lift 0.8 fold of their bodies. The study concluded that the characteristic changes in body composition experienced by students when undergoing weightlifting could be utilized side by side with the Fuzzy logic decision support system to determine the proper workloads consistent with the abilities of students.

Keywords: fuzzy logic, body mass index, body fat percentage, weightlifting

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Authors: Leila Najeh

Abstract:

This study investigates the motivational factors influencing Tunisian university students learning English through online platforms. Using a mixed-methods approach, data were collected from 112 undergraduate students of English across universities in Tunisia. The study employed an online questionnaire to measure intrinsic and extrinsic motivation, incorporating the Learning Motivation Questionnaire (FFLLM-Q) developed by Gonzales in 2001 and semi-structured interviews to explore students’ perspectives on their online learning experiences. Quantitative analysis revealed a significant correlation between intrinsic motivation and interactive features such as gamification and adaptive content delivery, while extrinsic motivation was strongly linked to career aspirations and academic requirements. Qualitative findings highlighted challenges such as limited interaction with peers and teachers, technical constraints, and a lack of immediate feedback as demotivating factors. Participants expressed a preference for blended learning models, combining the flexibility of online education with the collaborative environment of traditional classrooms. This study underscores the need for tailored online learning solutions to enhance the motivational landscape for Tunisian students, emphasizing the importance of culturally relevant content, accessible platforms, and supportive learning communities. Further research is recommended to evaluate the long-term impact of these interventions on language proficiency and learner autonomy.

Keywords: motivational factor, online foreign language learnig, tunsian students of english, online learning platforms

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Authors: Jinsong Zhao, Lin Zhao

Abstract:

Shenzhen, one of the fastest growing cities in the world, has been building a global ocean central city since 2017, facing many challenges, especially how to innovate new legal regimes to meet the future demands of the development of global shipping. First, the current legal regime of bills of lading as a document of title was established by English law in the 18th century but limited to the period of marine transportation from port of loading to port of discharge (namely, port to port). The e-commerce era is asking for such a function to be extended from port to port to door to door. Secondly, the function of the port has also been upgraded from the traditional loading and unloading of goods to a much wider area, such as being custody of warehousing goods for its mortgage bank, and therefore its legal status is changing, so it is necessary to amend the law of ports and harbours and innovate the rights and responsibilities of the port under its new role as the custody. Thirdly, the development of new marine energy has made more and more offshore floating wind power and floating photovoltaic devices face new legal issues such as legal status, nationality and ownership registration, mortgage, maritime lien, and possessory lien. Fourthly, the jurisdiction of the above issues, as well as conflicts of law and the applicable law, are also questions pending answers. This paper will discuss these issues of private international law, especially the innovation of new legal regimes with an aim to solve the above problems.

Keywords: maritime law, bills of lading, e-commerce, port law, marine clean energy

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Authors: Mehrdad Shafiei Dizaji, Hoda Azari

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The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data prediction, akin to advancements in medical imaging for tracking tumor progression in the human body. This research presents a detailed development framework for a specialized PINN model proficient at interpreting and forecasting GPR data, much like how medical imaging models predict tumor behavior. By harnessing the synergy between deep learning algorithms and the physical laws governing subsurface structures—or, in medical terms, human tissues—the model effectively embeds the physics of electromagnetic wave propagation into its architecture. This ensures that predictions not only align with fundamental physical principles but also mirror the precision needed in medical diagnostics for detecting and monitoring tumors. The suggested deep learning structure comprises three components: a CNN, a spatial feature channel attention (SFCA) mechanism, and ConvLSTM, along with temporal feature frame attention (TFFA) modules. The attention mechanism computes channel attention and temporal attention weights using self-adaptation, thereby fine-tuning the visual and temporal feature responses to extract the most pertinent and significant visual and temporal features. By integrating physics directly into the neural network, our model has shown enhanced accuracy in forecasting GPR data. This improvement is vital for conducting effective assessments of bridge deck conditions and other evaluations related to civil infrastructure. The use of Physics-Informed Neural Networks (PINNs) has demonstrated the potential to transform the field of Non-Destructive Evaluation (NDE) by enhancing the precision of infrastructure deterioration predictions. Moreover, it offers a deeper insight into the fundamental mechanisms of deterioration, viewed through the prism of physics-based models.

Keywords: physics-informed neural networks, deep learning, ground-penetrating radar (GPR), NDE, ConvLSTM, physics, data driven

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Authors: Ahmad Mohsin, Syda Fatima, Falak Nawaz, Aman Ullah Khan

Abstract:

Selection of an appropriate architectural style is vital to the success of target web service under development. The nature of architecture design and selection for service-oriented computing applications is quite different as compared to traditional software. Web Services have complex and rigorous architectural styles to choose. Due to this, selection for accurate architectural style for web services development has become a more complex decision to be made by architects. Architectural style selection is a multi-criteria decision and demands lots of experience in service oriented computing. Decision support systems are good solutions to simplify the selection process of a particular architectural style. Our research suggests a new approach using DSS for selection of architectural styles while developing a web service to cater FRs and NFRs. Our proposed DSS helps architects to select right web service architectural pattern according to the domain and non-functional requirements. In this paper, a rule base DSS has been developed using CLIPS (C Language Integrated Production System) to support decisions using multi-criteria requirements. This DSS takes architectural characteristics, domain requirements and software architect preferences for NFRs as input for different architectural styles in use today in service-oriented computing. Weighted sum model has been applied to prioritize quality attributes and domain requirements. Scores are calculated using multiple criterions to choose the final architecture style.

Keywords: software architecture, web-service, rule-based, DSS, multi-criteria requirements, quality attributes

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Authors: Gintaras Mitrulevičius

Abstract:

This text, which is based on the conference report, seeks to briefly examine the relationship between the concepts of social democracy and democratic socialism, drawing attention to the essential aspects of its development and, in particular, discussing the contradictions in the relationship between these concepts in the modern period. In the preparation of this text, such research methods as historical, historical-comparative methods were used, as well as methods of analyzing, synthesizing, and generalizing texts. The history of the use of terms in social democracy and democratic socialism shows that these terms were used alternately and almost synonymously. At the end of the 20th century, traditional social democracy was transformed into the so-called "new social democracy." Many of the new social democrats do not consider themselves democratic socialists and avoid the historically characteristic identification of social democracy with democratic socialism. It has become quite popular to believe that social democracy is a separate ideology from democratic socialism. Or that it has become a variant of the ideology of liberalism. This is a testimony to the crisis of ideological self-awareness of social democracy. Since the beginning of the 21st century, social democracy has also experienced a growing crisis of electoral support. This, among other things, led to her slight shift to the left. In this context, some social democrats are once again talking about democratic socialism. The rise of the ideas of democratic socialism in the United States was catalyzed by Bernie Sanders. But the proponents of democratic socialism in the United States have different concepts of democratic socialism. In modern Europe, democratic socialism is also spoken of by leftists of non-social democratic origin, whose understanding is different from that of democratic socialism inherent in classical social democracy. Some political scientists also single out the concepts in question. Analysis of the problem shows that there are currently several concepts of democratic socialism on the spectrum of the political left, both social-democratic and non-social-democratic.

Keywords: democratic socializm, socializm, social democracy, new social democracy, political ideologies

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Authors: Schirin Hanf, Carlos Lizandara-Pueyo, Timmo P. Emmert, Ivana Jevtovikj, Roger Gläser, Stephan A. Schunk

Abstract:

Metal alkoxides are very versatile precursors for a broad array of complex functional materials. However, metal alkoxides, especially transition metal alkoxides, tend to form oligomeric structures due to the very strong M–O–M binding motif. This fact hinders their facile application in sol-gel-processes and complicates access to complex carbonate or oxidic compounds after hydrolysis of the precursors. Therefore, the development of a synthetic alternative with the aim to grant access to carbonates and hydroxycarbonates from simple metal alkoxide precursors via hydrolysis is key to this project. Our approach involves the reaction of metal alkoxides with unsaturated isoelectronic molecules, such as carbon dioxide. Subsequently, a stoichiometric insertion of the CO₂ into the alkoxide M–O bond takes place and leads to the formation of soluble metal alkyl carbonates. This strategy is a very elegant approach to solubilize metal alkoxide precursors to make them accessible for sol-gel chemistry. After hydrolysis of the metal alkyl carbonates, crystalline metal carbonates, and hydroxycarbonates can be obtained, which were then utilized for the synthesis of Cu/Zn based bulk catalysts for methanol synthesis. Using these catalysts, a comparable catalytic activity to commercially available MeOH catalysts could be reached. Based on these results, a complement for traditional precipitation techniques, which are usually utilized for the synthesis of bulk methanol catalysts, have been found based on an alternative solubilization strategy.

Keywords: metal alkoxides, metal carbonates, metal hydroxycarbonates, CO₂ insertion, solubilization

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