Search results for: satellite solar panel deployment mechanism

Authors: Sara Rejeb, Catherine Duveau, Tabea Rebafka

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To monitor the production process of turbofan aircraft engines, multiple measurements of various geometrical parameters are systematically recorded on manufactured parts. Engine parts are subject to extremely high standards as they can impact the performance of the engine. Therefore, it is essential to analyze these databases to better understand the influence of the different parameters on the engine's performance. Self-organizing maps are unsupervised neural networks which achieve two tasks simultaneously: they visualize high-dimensional data by projection onto a 2-dimensional map and provide clustering of the data. This technique has become very popular for data exploration since it provides easily interpretable results and a meaningful global view of the data. As such, self-organizing maps are usually applied to aircraft engine condition monitoring. As databases in this field are huge and complex, they naturally contain multiple missing entries for various reasons. The classical Kohonen algorithm to compute self-organizing maps is conceived for complete data only. A naive approach to deal with partially observed data consists in deleting items or variables with missing entries. However, this requires a sufficient number of complete individuals to be fairly representative of the population; otherwise, deletion leads to a considerable loss of information. Moreover, deletion can also induce bias in the analysis results. Alternatively, one can first apply a common imputation method to create a complete dataset and then apply the Kohonen algorithm. However, the choice of the imputation method may have a strong impact on the resulting self-organizing map. Our approach is to address simultaneously the two problems of computing a self-organizing map and imputing missing values, as these tasks are not independent. In this work, we propose an extension of self-organizing maps for partially observed data, referred to as missSOM. First, we introduce a criterion to be optimized, that aims at defining simultaneously the best self-organizing map and the best imputations for the missing entries. As such, missSOM is also an imputation method for missing values. To minimize the criterion, we propose an iterative algorithm that alternates the learning of a self-organizing map and the imputation of missing values. Moreover, we develop an accelerated version of the algorithm by entwining the iterations of the Kohonen algorithm with the updates of the imputed values. This method is efficiently implemented in R and will soon be released on CRAN. Compared to the standard Kohonen algorithm, it does not come with any additional cost in terms of computing time. Numerical experiments illustrate that missSOM performs well in terms of both clustering and imputation compared to the state of the art. In particular, it turns out that missSOM is robust to the missingness mechanism, which is in contrast to many imputation methods that are appropriate for only a single mechanism. This is an important property of missSOM as, in practice, the missingness mechanism is often unknown. An application to measurements on one type of part is also provided and shows the practical interest of missSOM.

Keywords: imputation method of missing data, partially observed data, robustness to missingness mechanism, self-organizing maps

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Authors: Daria Grechishnikova, Maria Poptsova

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Transposable elements play an important role in the evolution of various species from bacteria to human. Long Interspersed Nuclear Elements (LINEs) and Short Interspersed Nuclear Elements (SINEs) are two major classes of retrotransposons that occupy a considerable part of any genome and their copy numbers can range form several hundreds to a million. Both LINEs and SINEs multiply through a copy-and-paste mechanism. LINEs encode proteins, which make them capable of self-propagation while SINEs are parasitic and require the machinery of LINEs to multiply. The mechanisms how LINE and SINE RNA is recognized by the LINE-encoded reverse transcriptase (RT) remain unclear. For some SINE-LINE pairs, it was shown that they share a common 3’-end with a stem-loop structure. Majority of the SINE-LINE pairs do not have a common 3’-end. Recently we have shown that in the human genome Alu-L1 pairs have structurally similar stem-loop structure at the 3’-end. Here we extended our analysis to a wide range of species and analyzed LINEs from 161 different species from Repbase and 217 SINE sequences from SINEBase. It appeared that all of the analyzed sequences contained stem-loop structures at the 3’-end. Here we conclude that it is very likely that a common evolutionary mechanism of transposon RNA recognition requires the presence of stem-loop structures at their 3’-end.

Keywords: LINE, SINE, mechanisms of retrotransposition, retrotransposons, stem-loop, stem-loop structures, transposons

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Authors: Hasan Vural

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Turkey is a favorable country to produce a great variety of agricultural products because of her different geographic and climatic conditions which have been used to divide the country into four main and seven sub regions. This classification into seven regions traditionally has been used in order to data collection and publication especially related with agricultural production. Afterwards, nine agricultural regions were considered. Recently, the governmental body which is responsible of data collection and dissemination (Turkish Institute of Statistics-TIS) has used 12 classes which include 11 sub regions and Istanbul province. This study aims to evaluate these classification efforts based on the acreage of ten main crops in a ten years time period (1996-2005). The panel data grouped in 11 subregions has been evaluated by cluster and multivariate statistical methods. It was concluded that from the agricultural production point of view, it will be rather meaningful to consider three main and eight sub-agricultural regions throughout the country.

Keywords: agricultural region, factorial analysis, cluster analysis,

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Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

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Authors: Laurent Maurin, Mervi Toivanen

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This paper estimates euro area banks’ internal target capital ratios and investigates whether banks’ adjustment to the targets have an impact on credit supply and holding of securities during the financial crisis in 2005-2011. Using data on listed banks and country-specific macro-variables a partial adjustment model is estimated in a panel context. The results indicate, firstly, that an increase in the riskiness of banks’ balance sheets influences positively on the target capital ratios. Secondly, the adjustment towards higher equilibrium capital ratios has a significant impact on banks’ assets. The impact is found to be more size-able on security holdings than on loans, thereby suggesting a pecking order.

Keywords: Euro area, capital ratios, credit supply, partial adjustment model

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Authors: Anton S. Perin, Vladimir M. Shandarov

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Compensation for the nonlinear diffraction of narrow laser beams with wavelength of 532 and the formation of photonic waveguides and waveguide circuits due to the contribution of pyroelectric effect to the nonlinear response of lithium niobate crystal have been experimentally demonstrated. Complete compensation for the linear and nonlinear diffraction broadening of light beams is obtained upon uniform heating of an undoped sample from room temperature to 55 degrees Celsius. An analysis of the light-field distribution patterns and the corresponding intensity distribution profiles allowed us to estimate the spacing for the channel waveguides. The observed behavior of bright soliton beams may be caused by their coherent interaction, which manifests itself in repulsion for anti-phase light fields and in attraction for in-phase light fields. The experimental results of this study showed a fundamental possibility of forming optically complex waveguide structures in lithium niobate crystals with pyroelectric mechanism of nonlinear response. The topology of these structures is determined by the light field distribution on the input face of crystalline sample. The optical induction of channel waveguide elements by interacting spatial solitons makes it possible to design optical systems with a more complex topology and a possibility of their dynamic reconfiguration.

Keywords: self-action, soliton, lithium niobate, piroliton, photorefractive effect, pyroelectric effect

Procedia PDF Downloads 160

Authors: Sukhwinder K. Bhullar, M. B. G. Jun

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The developments in biomedical industry have demanded the development of biocompatible, high performance materials to meet higher engineering specifications. The general requirements of such materials are to provide a combination of high stiffness and strength with significant weight savings, resistance to corrosion, chemical resistance, low maintenance, and reduced costs. Auxetic materials which come under the category of smart materials offer huge potential through measured enhancements in mechanical properties. Unique deformation mechanism, providing cushioning on indentation, automatically adjustable with its strength and thickness in response to forces and having memory returns to its neutral state on dissipation of stresses make them good candidate in biomedical industry. As simple extension and compression of tissues is of fundamental importance in biomechanics, therefore, to study the elastic behaviour of auxetic soft tissues implant is targeted in this paper. Therefore development and characterization of auxetic soft tissue implant is studied in this paper. This represents a real life configuration where soft tissue such as meniscus in knee replacement, ligaments and tendons often are taken as transversely isotropic. Further, as composition of alternating polydisperse blocks of soft and stiff segments combined with excellent biocompatibility make polyurethanes one of the most promising synthetic biomaterials. Hence selecting auxetic polyurathylene foam functional characterization is performed and compared with conventional polyurathylene foam.

Keywords: auxetic materials, deformation mechanism, enhanced mechanical properties, soft tissues

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Authors: Pascal François Faye, Baye Mor Sall, Bineta Dembele, Jeanne Ana Awa Faye

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In agriculture, estimating crop yields is key to improving productivity and decision-making processes such as financial market forecasting and addressing food security issues. The main objective of this paper is to have tools to predict and improve the accuracy of crop yield forecasts using machine learning (ML) algorithms such as CART , KNN and SVM . We developed a mobile app and a web app that uses these algorithms for practical use by farmers. The tests show that our system (collection and deployment architecture, web application and mobile application) is operational and validates empirical knowledge on agro-climatic parameters in addition to proactive decision-making support. The experimental results obtained on the agricultural data, the performance of the ML algorithms are compared using cross-validation in order to identify the most effective ones following the agricultural data. The proposed applications demonstrate that the proposed approach is effective in predicting crop yields and provides timely and accurate responses to farmers for decision support.

Keywords: prediction, machine learning, artificial intelligence, digital agriculture

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Authors: F. Pagliara, F. Mauriello

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The objective of this paper is to investigate the relationship between the increase of accessibility brought by high speed rail (HSR) systems and the tourism market in Italy. The impacts of HSR projects on tourism can be quantified in different ways. In this manuscript, an empirical analysis has been carried out with the aid of a dataset containing information both on tourism and transport for 99 Italian provinces during the 2006-2016 period. Panel data regression models have been considered, since they allow modelling a wide variety of correlation patterns. Results show that HSR has an impact on the choice of a given destination for Italian tourists while the presence of a second level hub mainly affects foreign tourists. Attraction variables are also significant for both categories and the variables concerning security, such as number of crimes registered in a given destination, have a negative impact on the choice of a destination.

Keywords: tourists, overnights, high speed rail, attractions, security

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Authors: Anastasia Schnitzer, Oliver Rehren

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Mental health has become an increasingly important topic in society in recent years, not least due to the challenges posed by the corona pandemic. Along with this, the public has become more and more aware that a lack of enlightenment and proper coping mechanisms may result in a notable risk to develop mental disorders. Yet, there are still many biases against those affected, which are further connected to issues of stigmatization and societal exclusion. One of the main strategies to combat these forms of prejudice and stigma is to induce intergroup contact. More specifically, the Intergroup Contact Theory states engaging in certain types of contact with members of marginalized groups may be an effective way to improve attitudes towards these groups. However, due to the persistent prejudice and stigmatization, affected individuals often do not dare to speak openly about their mental disorders, so that intergroup contact often goes unnoticed. As a result, many people only experience conscious contact with individuals with a mental disorder through media. As an analogy to the Intergroup Contact Theory, the Parasocial Contact Hypothesis proposes that repeatedly being exposed to positive media representations of outgroup members can lead to a reduction of negative prejudices and attitudes towards this outgroup. While there is a growing body of research on the merit of this mechanism, measurements often only consist of 'positive' or 'negative' parasocial contact conditions (or examine the valence or quality of the previous contact with the outgroup); meanwhile, more specific conditions are often neglected. The current study aims to tackle this shortcoming. By scrutinizing the potential of contemporary series as a narrative framework of high quality, we strive to elucidate more detailed aspects of beneficial parasocial contact -for the sake of reducing prejudice and stigma towards individuals with mental disorders. Thus, a two-factorial between-subject online panel study with three measurement points was conducted (N = 95). Participants were randomly assigned to one of two groups, having to watch episodes of either a series with a narrative framework of high (Quality-TV) or low quality (Continental-TV), with one-week interval in-between the episodes. Suitable series were determined with the help of a pretest. Prejudice and stigma towards people with mental disorders were measured at the beginning of the study, before and after each episode, and in a final follow-up one week after the last two episodes. Additionally, parasocial interaction (PSI), quality of contact (QoC), and transportation were measured several times. Based on these data, multivariate multilevel analyses were performed in R using the lavaan package. Latent growth models showed moderate to high increases in QoC and PSI as well as small to moderate decreases in stigma and prejudice over time. Multilevel path analysis with individual and group levels further revealed that a qualitative narrative framework leads to a higher quality of contact experience, which then leads to lower prejudice and stigma, with effects ranging from moderate to high.

Keywords: prejudice, quality of contact, parasocial contact, narrative framework

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Authors: Laura Rodrigues Carmona, Maria José Chambel, Vânia Sofia Carvalho

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Background: In peacekeeping operations, military personnel are often exposed to the same traumatic stress factors found during conventional war and may also be subject to the physical risks and psychological stressors associated with posttraumatic stress disorder (PTSD). Objectives: To discuss the prevalence of PTSD among peacekeepers as well as the risks of and protective factors against this disorder and its comorbidities and/or consequences. Methods: A systematic literature search was performed with relevant keywords, and 53 articles were identified for this review. Results and conclusions: Military personnel deployed in peacekeeping operations have a higher prevalence of PTSD than nonmilitary personnel, a prevalence similar to that of military personnel deployed in war situations. Concerning the salient risk factors, the contextual factors are highlighted, and in regard to the protective factors, the individual factors are highlighted. This study thus demonstrates that there are factors in which the role of the military is essential, via both its selection and monitoring of peacekeepers during and after their deployment, to protect deployed personnel’s mental health.

Keywords: peacekeepers, peacekeeping, military, PTSD, post-traumatic stress disorder, posttraumatic stress disorder

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Authors: Teboho J. Mosikari, Johannes T. Tsoku, Diteboho L. Xaba

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The increase of capital mobility across emerging economies has become an interesting topic for many economic policy makers. The current study tests the validity of Feldstein–Horioka puzzle for 5 BRICS countries. The sample period of the study runs from 2001 to 2014. The study uses the following parameter estimates well known as the Fully Modified OLS (FMOLS), and Dynamic OLS (DOLS). The results of the study show that investment and savings are cointegrated in the long run. The parameters estimated using FMOLS and DOLS are 0.85 and 0.74, respectively. These results imply that policy makers within BRICS countries have to consider flexible monetary and fiscal policy instruments to influence the mobility of capital with the bloc.

Keywords: Feldstein and Horioka puzzle, saving and investment, panel models, BRICS countries

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Authors: Rahime Hülya Öztürk

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Along with the development of globalization, the relationship between economic, politic and commercial behaviors became unlimited. The liberalization of capital has many advantages for countries, but it also has some disadvantages. In these disadvantages the most important one is corruption. Especially in Developing Countries and Underdeveloped countries, corruption is very extensive. Corruption causes inefficient use of resources and promotes income inequality. Especially in the transition period of economies corruption increases and sometimes governments don’t interfere. To fight against corruption domestic and international measures are taken. Corruption is an economic problem, but it also has social and moral effects. The aim of this study is to define the relationship between corruption and income in Independent Turkish State. In the first part of the study, the concept of corruption is examined. In the second part of the study, information about The Independent Turkish Republic is given. In the third part of the study, country’s relationship between corruption and income is analyzed with panel data analysis.

Keywords: corruption, income, independent Turkish Republic, distribution of income

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Authors: Michael I. Okereke, Ambrose I. Akpoyomare

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This paper presents a numerical study of the impact mechanic of metallic and sandwich structures incorporate with blast resistance enhancements. The study focuses on structures that have been exposed to improvised explosives devices (IEDs) attacks. The results show numerical conclusions on mechanisms to ensure blast resistance enhancement for the applications studied in this work. The work has identified optimal panel configuration both in geometry and configurations to ensure optimal blast resistance response to such IEDs discharges. Findings from this work will drive improvements in especially military and civilian vehicles in countries where blast attacks on vehicular occupants are quite rampant like Pakistan and Afghanistan.

Keywords: blast resistance, blast enhancement, explosives, material behavior

Procedia PDF Downloads 367

Authors: Qinglu Wu, Anna Wai-Man Choi, Peilian Chi

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Gratitude is one individual strength that not only facilitates the mental health, but also fosters the relationship satisfaction in the romantic relationship. In terms of moral effect theory and stress-and-coping theory of forgiveness, present study not only investigated the association between grateful disposition and relationship satisfaction, but also explored the mechanism by comprehensively examining the potential mediating roles of three profiles of forgiveness (trait forgivingness, decisional forgiveness, emotional forgiveness), another character strength that highly related to the gratitude and relationship satisfaction. Structural equation modeling was used to conduct the multiple mediator model with a sample of 103 Chinese college students in dating relationship (39 male students and 64 female students, Mage = 19.41, SD = 1.34). Findings displayed that both gratitude and relationship satisfaction positively correlated with decisional forgiveness and emotional forgiveness. Emotional forgiveness was the only mediator, and it completely mediated the relationship between gratitude and relationship satisfaction. Gratitude was helpful in enhancing individuals’ perception of satisfaction in romantic relationship through replacing negative emotions toward partners with positive ones after transgression in daily life. It highlighted the function of emotional forgiveness in personal healing and peaceful state, which is important to the perception of satisfaction in relationship. Findings not only suggested gratitude could provide a stability for forgiveness, but also the mechanism of prosocial responses or positive psychological processes on relationship satisfaction. The significant roles of gratitude and emotional forgiveness could be emphasized in the intervention working on the romantic relationship development or reconciliation.

Keywords: decisional forgiveness, emotional forgiveness, gratitude, relationship satisfaction, trait forgivingness

Procedia PDF Downloads 262

Authors: Samira Karimi-Mansoub, Rahem Abri

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Currently, users expect high quality and personalized information from search results. To satisfy user’s needs, personalized approaches to web search have been proposed. These approaches can provide the most appropriate answer for user’s needs by using user context and incorporating information about query provided by combining search technologies. To carry out personalized web search, there is a need to make different techniques on whole of user search process. There are the number of possible deployment of personalized approaches such as personalized web search, personalized recommendation, personalized summarization and filtering systems and etc. but the common feature of all approaches in various domains is that user modeling is utilized to provide personalized information from the Web. So the most important work in personalized approaches is user model mining. User modeling applications and technologies can be used in various domains depending on how the user collected information may be extracted. In addition to, the used techniques to create user model is also different in each of these applications. Since in the previous studies, there was not a complete survey in this field, our purpose is to present a survey on applications and techniques of user modeling from the viewpoint of improvement in search results by considering the existing literature and researches.

Keywords: filtering systems, personalized web search, user modeling, user search behavior

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Authors: Sumbal Riaz, Sardar-un-Nisa, Mehreen Sirshar

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5G - The 5th generation of mobile phone and data communication standards is the next edge of innovation for whole mobile industry. 5G is Real Wireless World System and it will provide a totally wireless communication system all over the world without limitations. 5G uses many 4g technologies and it will hit the market in 2020. This research is the comprehensive survey on the quality parameters of 5G technology.5G provide High performance, Interoperability, easy roaming, fully converged services, friendly interface and scalability at low cost. To meet the traffic demands in future fifth generation wireless communications systems will include i) higher densification of heterogeneous networks with massive deployment of small base stations supporting various Radio Access Technologies (RATs), ii) use of massive Multiple Input Multiple Output (MIMO) arrays, iii) use of millimetre Wave spectrum where larger wider frequency bands are available, iv) direct device to device (D2D) communication, v) simultaneous transmission and reception, vi) cognitive radio technology.

Keywords: 5G, 5th generation, innovation, standard, wireless communication

Procedia PDF Downloads 440

Authors: C. Hamamura, V. Gialluca

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Much of the Eclectricity Distributors has about 70% of its electricity interruptions arising from cause "trees", alone or associated with wind and rain and with or without falling branch and / or trees. This contributes inexorably and significantly to outages, resulting in high costs as compensation in addition to the operation and maintenance costs. On the other hand, there is little data structure and solutions to better organize the trees pruning plan effectively, minimizing costs and environmentally friendly. This work describes the development of an algorithm to provide data of trees associated to power grid. The method is accomplished on several steps using satellite imagery and geographically vectorized grid. A sliding window like approach is performed to seek the area around the grid. The proposed method counted 764 trees on a patch of the grid, which was very close to the 738 trees counted manually. The trees data was used as a part of a larger project that implements a system to optimize tree pruning plan.

Keywords: image pattern recognition, trees pruning, trees recognition, neural network

Procedia PDF Downloads 495

Authors: Hui-Hsin Huang, Sheng-Tung Huang, Chi-Ming Lee, Chiao-Han Yen, Chun-Mao Lin

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At initiation stage, there are no symptoms at initiation stage; however, at late stage, patients suffer symptoms as soon as ovarian cancer metastasis. Moreover, ovarian cancer cells are resistant to some anti-ovarian cancer drugs in clinical. Thus, it is very important to find an effective treatment for resistant ovarian cancer. Anthraquinone derivatives are able to induce DNA damage and lead to cell apoptosis, so several derivatives have been used for clinical application. Therefore, to explore more effective anti-ovarian cancer drugs, this study investigates the mechanism of three new anthraquinone compounds bearing different functional groups to camptothecin-resistance ovarian cell line A2780R2000. Cell viability was determined by MTT assay after treating A2780R2000 with the three new anthraquinone compounds. The results indicated that IC50 values are 33.44μM (Compound I), 25.77μM (Compound II) and 24.59μM (Compound III). Next, through cell cycle analysis, the results demonstrated that three new anthraquinone compounds not only induced A2780R2000 cell cycle arrest at early stage but also apoptosis at late stage. Besides, through apoptosis assay, the results indicated new anthraquinone compound induced apoptosis at late stage. Furthermore, the results of western blot show that the three new anthraquinone compounds lead to A2780R2000 apoptosis through intrinsic pathway. Theses results suggested that three new anthraquinone compounds may be potential new drugs for clinical cancer treatment in the future.

Keywords: anthraquinone, camptothecin, resistance, ovarian cancer

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Authors: Szu-Hua Wang, Yi-Wen Chen

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Urban ecosystems are complex coupled human-environment systems. They contain abundant natural resources for producing natural assets and attract urban assets to consume natural resources for urban development. Urban ecosystems provide several ecosystem services, including provisioning services, regulating services, cultural services, and supporting services. Rapid global climate change makes urban ecosystems and their ecosystem services encountering various natural disasters. Lots of natural disasters have occurred around the world under the constant changes in the frequency and intensity of extreme weather events in the past two decades. In Taiwan, hydrological disasters have been paid more attention due to the potential high sensitivity of Taiwan’s cities to climate change, and it impacts. However, climate change not only causes extreme weather events directly but also affects the interactions among human, ecosystem services and their dynamic feedback processes indirectly. Therefore, this study adopts a systematic method, solar energy synthesis, based on the concept of the eco-energy analysis. The Taipei area, the most densely populated area in Taiwan, is selected as the study area. The changes of ecosystem services between 2015 and Typhoon Soudelor have been compared in order to investigate the impacts of extreme precipitation events on ecosystem services. The results show that the forest areas are the largest contributions of energy to ecosystem services in the Taipei area generally. Different soil textures of different subsystem have various upper limits of water contents or substances. The major contribution of ecosystem services of the study area is natural hazard regulation provided by the surface water resources areas. During the period of Typhoon Soudelor, the freshwater supply in the forest areas had become the main contribution. Erosion control services were the main ecosystem service affected by Typhoon Soudelor. The second and third main ecosystem services were hydrologic regulation and food supply. Due to the interactions among ecosystem services, fresh water supply, water purification, and waste treatment had been affected severely.

Keywords: ecosystem, extreme precipitation events, ecosystem services, solar energy synthesis

Procedia PDF Downloads 140

Authors: Özlem Erzurumlu, Nazan Oskay, Ece Melek

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Knitting which is one of the textile manufacturing techniques is manufactured by using the system of single yarn. Knitting wares consisting of loops structurally have flexible structures. Knitting can be shaped and given volume easily due to increasing or decreasing the number of loops, being manufactured in circular form and its flexible structure. While the knitting wares are basically being manufactured to meet the requirements, it takes its place in the art field overflowing outside of industrial production later. Textile artist ensures his ideas to convert into artistic product by using textiles and non-textiles with aesthetic concerns and creative impulses. When textile crafts are observed at the present time we see that knitting technique has an extensive area of use such as sculpture, panel, installation art and performing art. It is examined how the knitting technique is used in textile crafts observing patterns obtained by this technique in textile crafts in this study.

Keywords: art, textile, knitting art, textile crafts

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Authors: Robel Habtemariam

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Globally, wind energy and photovoltaics (PV) solar energy are among the leading renewable energy sources (RES) in terms of installed capacity. In order to increase the contribution of RES to the power supply system, large scale energy integration is required, mainly due to wind energy and PV. In this paper, an investigation has been made on the electrical power supply systems of Taiwan and Greece in order to integrate high level of wind and photovoltaic (PV) to increase the penetration of renewable energy resources. Currently, both countries heavily depend on fossil fuels to meet the demand and to generate adequate electricity. Therefore, this study is carried out to look into the two cases power supply system by developing a methodology that includes major power units. To address the analysis, an approach for simulation of power systems is formulated and applied. The simulation is based on the non-dynamic analysis of the electrical system. This simulation results in calculating the energy contribution of different types of power units; namely the wind, PV, non-flexible and flexible power units. The calculation is done for three different scenarios (2020, 2030, & 2050), where the first two scenarios are based on national targets and scenario 2050 is a reflection of ambitious global targets. By 2030 in Taiwan, the input of the power units is evaluated as 4.3% (wind), 3.7% (PV), 65.2 (non-flexible), 25.3% (flexible), and 1.5% belongs to hydropower plants. In Greece, much higher renewable energy contribution is observed for the same scenario with 21.7% (wind), 14.3% (PV), 38.7% (non-flexible), 14.9% (flexible), and 10.3% (hydro). Moreover, it examines the ability of the power systems to deal with the variable nature of the wind and PV generation. For this reason, an investigation has also been done on the use of the combined wind power with pumped storage systems (WPS) to enable the system to exploit the curtailed wind energy & surplus PV and thus increase the wind and PV installed capacity and replace the peak supply by conventional power units. Results show that the feasibility of pumped storage can be justified in the high scenario (that is the scenario of 2050) of RES integration especially in the case of Greece.

Keywords: large scale energy integration, photovoltaics solar energy, pumped storage systems, renewable energy sources

Procedia PDF Downloads 274

Authors: Solanki Ravirajsinh, Kudo Kuniaki, Sharma Ankit, Devi Sherine, Kuboshima Misaki, Tachi Shuntaro

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In software development life cycles, the absence of scalable CI/CD significantly impacts organizations, leading to increased overall maintenance costs, prolonged release delivery times, heightened manual efforts, and difficulties in meeting tight deadlines. Implementing CI/CD with standard serverless technologies using cloud services overcomes all the above-mentioned issues and helps organizations improve efficiency and faster delivery without the need to manage server maintenance and capacity. By integrating scalable CI/CD with scalable automation testing, productivity, quality, and agility are enhanced while reducing the need for repetitive work and manual efforts. Implementing scalable CI/CD for development using cloud services like ECS (Container Management Service), AWS Fargate, ECR (to store Docker images with all dependencies), Serverless Computing (serverless virtual machines), Cloud Log (for monitoring errors and logs), Security Groups (for inside/outside access to the application), Docker Containerization (Docker-based images and container techniques), Jenkins (CI/CD build management tool), and code management tools (GitHub, Bitbucket, AWS CodeCommit) can efficiently handle the demands of diverse development environments and are capable of accommodating dynamic workloads, increasing efficiency for faster delivery with good quality. CI/CD pipelines encourage collaboration among development, operations, and quality assurance teams by providing a centralized platform for automated testing, deployment, and monitoring. Scalable CI/CD streamlines the development process by automatically fetching the latest code from the repository every time the process starts, building the application based on the branches, testing the application using a scalable automation testing framework, and deploying the builds. Developers can focus more on writing code and less on managing infrastructure as it scales based on the need. Serverless CI/CD eliminates the need to manage and maintain traditional CI/CD infrastructure, such as servers and build agents, reducing operational overhead and allowing teams to allocate resources more efficiently. Scalable CI/CD adjusts the application's scale according to usage, thereby alleviating concerns about scalability, maintenance costs, and resource needs. Creating scalable automation testing using cloud services (ECR, ECS Fargate, Docker, EFS, Serverless Computing) helps organizations run more than 500 test cases in parallel, aiding in the detection of race conditions, performance issues, and reducing execution time. Scalable CI/CD offers flexibility, dynamically adjusting to varying workloads and demands, allowing teams to scale resources up or down as needed. It optimizes costs by only paying for the resources as they are used and increases reliability. Scalable CI/CD pipelines employ automated testing and validation processes to detect and prevent errors early in the development cycle.

Keywords: achieve parallel execution, cloud services, scalable automation testing, scalable continuous integration and deployment

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Authors: Sandesh Achar

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Artificial intelligence is being increasingly incorporated into many applications across various sectors such as health, education, security, and agriculture. Recently, there has been rapid development in cloud computing technology, resulting in AI’s implementation into cloud computing to enhance and optimize the technology service rendered. The deployment of AI in cloud-based applications has brought about autonomous computing, whereby systems achieve stated results without human intervention. Despite the amount of research into autonomous computing, work incorporating AI/ML into cloud computing to enhance its performance and resource allocation remain a fundamental challenge. This paper highlights different manifestations, roles, trends, and challenges related to AI-based cloud computing models. This work reviews and highlights excellent investigations and progress in the domain. Future directions are suggested for leveraging AI/ML in next-generation computing for emerging computing paradigms such as cloud environments. Adopting AI-based algorithms and techniques to increase operational efficiency, cost savings, automation, reducing energy consumption and solving complex cloud computing issues are the major findings outlined in this paper.

Keywords: artificial intelligence, cloud computing, deep learning, machine learning, internet of things

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Authors: Shafqat Ullah Khan, Ammar Nasir

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Using planar antenna array (PAA) in radars, Broadcasting, satellite antennas, and sonar for the detection of targets, Helps provide instant beam pattern control. High flexibility and Adaptability are achieved by multiple beam steering by using a Planar array and are particularly needed in real-life Sanrio’s where the need arises for several high-directivity beams. Faulty sensors in planar arrays generate asymmetry, which leads to service degradation, radiation pattern distortion, and increased levels of sidelobe. The POA, a nature-inspired optimization algorithm, accurately determines faulty sensors within an array, enhancing the reliability and performance of planar array antennas through extensive simulations and experiments. The analysis was done for different types of faults in 7 x 7 and 8 x 8 planar arrays in MATLAB.

Keywords: Planar antenna array, , Pelican optimisation Algorithm, , Faculty sensor, Antenna arrays

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Authors: Kang Huang, Wanting Zhou, Shiwei Yuan, Lei Li

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Since information technology develops rapidly, the security issue has become an increasingly critical for computer system. In particular, as cloud computing and the Internet of Things (IoT) continue to gain widespread adoption, computer systems need to new security threats and attacks. The Root of Trust (RoT) is the foundation for providing basic trusted computing, which is used to verify the security and trustworthiness of other components. Design a reliable Root of Trust and guarantee its own security are essential for improving the overall security and credibility of computer systems. In this paper, we discuss the implementation of self-security technology based on the RISC-V Root of Trust at the hardware level. To effectively safeguard the security of the Root of Trust, researches on security safeguard technology on the Root of Trust have been studied. At first, a lightweight and secure boot framework is proposed as a secure mechanism. Secondly, two kinds of memory protection mechanism are built to against memory attacks. Moreover, hardware implementation of proposed method has been also investigated. A series of experiments and tests have been carried on to verify to effectiveness of the proposed method. The experimental results demonstrated that the proposed approach is effective in verifying the integrity of the Root of Trust’s own boot rom, user instructions, and data, ensuring authenticity and enabling the secure boot of the Root of Trust’s own system. Additionally, our approach provides memory protection against certain types of memory attacks, such as cache leaks and tampering, and ensures the security of root-of-trust sensitive information, including keys.

Keywords: root of trust, secure boot, memory protection, hardware security

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Authors: Yaseen Muhammad, Zhenxia Zhao, Zhangfa Tong

Abstract:

A key problem with hydrodesulfurization (HDS) process of fuel oils is the application of severe operating conditions. In this study, we proposed the catalytic HDS of dibenzothiophene (DBT) integrated with ionic liquids (ILs) application at mild temperature and pressure over low loaded (0.5 wt.%) Pd promoted Co-Mo@Al₂O₃ and Ni-Mo@Al₂O₃ catalysts. Among the thirteen ILs tested, [BMIM]BF₄, [(CH₃)₄N]Cl, [EMIM]AlCl₄, and [(C₈H₁₇)(C₃H₇)₃P]Br enhanced the catalytic HDS efficiency while the latest ranked the top of activity list as confirmed by DFT studies as well. Experimental results revealed that Pd incorporation greatly enhanced the HDS activity of classical Co or Ni based catalysts. At mild optimized experimental conditions of 1 MPa H₂ pressure, 120 oC, IL:oil ratio of 1:3 and 4 h reaction time, the % DBT conversion (21 %) by Ni-Mo@Al₂O₃ was enhanced to 69 % (over Pd-Ni-Mo@ Al₂O₃) using [(C₈H₁₇) (C₃H₇)₃P]Br. The fresh and spent catalysts were characterized for textural properties using XPS, SEM, EDX, XRD and BET surface area techniques. An overall catalytic HDS activity followed the order of: Pd-Ni-Mo@Al₂O₃ > Pd-Co-Mo@Al₂O₃ > Ni-Mo@Al₂O₃ > Co-Mo@Al₂O₃. [(C₈H₁₇) (C₃H₇)₃P]Br.could be recycled four times with minimal decrease in HDS activity. Reaction products were analyzed by GC-MS which helped in proposing reaction mechanism for the IL coupled HDS process. The present approach attributed to its cost-effective nature, ease of operation with less mechanical requirements in terms of mild operating conditions, and high efficiency could be deemed as an alternative approach for the HDS of DBT on industrial level applications.

Keywords: DFT simulation, GC-MS and reaction mechanism, Ionic liquid coupled HDS of DBT, low Pd loaded catalyst, mild operating condition

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Authors: Deepika Saini, Sandeep Jain, Ajay Kumar

Abstract:

The quinoline scaffold is one of the most widely studied in the discovery of derivatives with various heterocyclic moieties due to its potential antimalarial activities. In the present study, a chalcone series of quinoline derivatives clubbed with pyrazole were synthesized to evaluate their antimalarial property by in vitro schizont maturation inhibition assay against both chloroquine sensitive, 3D7 and chloroquine resistant, RKL9 strain of Plasmodium falciparum. Further, top five compounds were studied for in vivo preclinical study for antimalarial potential against P. berghei in Swiss albino mice. To understand the mechanism of synthesized analogues, they were screened computationally by molecular docking techniques. Compounds were docked into the active site of a protein receptor, Plasmodium falciparum Cysteine Protease Falcipain-2. The compounds were successfully synthesized, and structural confirmation was performed by FTIR, 1H-NMR, mass spectrometry and elemental analysis. In vitro study suggested that the compounds 5b, 5g, 5l, 5s and 5u possessed best antimalarial activity and further tested for in vivo screening. Compound 5u (CH₃ on both rings) with EC₅₀ 0.313 & 0.801 µg/ml against CQ-S & CQ-R strains of P. falciparum respectively and 78.01% suppression of parasitemia. The molecular docking studies of the compounds helped in understanding the mechanism of action against falcipain-2. The present study reveals the binding signatures of the synthesized ligands within the active site of the protein, and it explains the results from in vitro study in their EC₅₀ values and percentage parasitemia.

Keywords: antimalarial activity, chalcone, docking, quinoline

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Authors: Sadegh Abedi, Ali Yaghoubi, Hamidreza Mashatzadegan

Abstract:

This paper proposes an approach to identify key processes required by an organization in the field of knowledge management and aligning them with organizational objectives. For this purpose, first, organization’s most important non-financial objectives which are impacted by knowledge management processes are identified and then, using a quality house, are linked with knowledge management processes which are regarded as technical elements. Using this method, processes that are in need of improvement and more attention are prioritized based on their significance. This means that if a process has more influence on organization’s objectives and is in a dire situation comparing to others, is prioritized for choice and improvement. In this research process dominance is considered to be an influential element in process ranking (in addition to communication matrix). This is the reason for utilizing DEA techniques for prioritizing processes in quality house. Results of implementing the method in Khuzestan steel company represents this method’s capability of identifying key processes that require improvements in organization’s knowledge management system.

Keywords: knowledge management, organizational performance, fuzzy data, envelopment analysis

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Authors: Saurabh Satija, Munish Garg

Abstract:

Present work reports an efficient extraction method using microwaves based solvent–sample duo-heating mechanism, for the extraction of an important anti-diabetic plant Tinospora cordifolia from AYUSH system for estimation of berberine content. The process is based on simultaneous heating of sample matrix and extracting solvent under microwave energy. Methanol was used as the extracting solvent, which has excellent berberine solubilizing power and warms up under microwave attributable to its great dispersal factor. Extraction conditions like time of irradition, microwave power, solute-solvent ratio and temperature were optimized using Taguchi design and berberine was quantified using high performance thin layer chromatography. The ranked optimized parameters were microwave power (rank 1), irradiation time (rank 2) and temperature (rank 3). This kind of extraction mechanism under dual heating provided choice of extraction parameters for better precision and higher yield with significant reduction in extraction time under optimum extraction conditions. This developed extraction protocol will lead to extract higher amounts of berberine which is a major anti-diabetic moiety in Tinospora cordifolia which can lead to development of cheaper formulations of the plant Tinospora cordifolia and can help in rapid prevention of diabetes in the world.

Keywords: berberine, microwave, optimization, Taguchi

Procedia PDF Downloads 337