Search results for: multiple scales

Authors: Richa Shri, Varinder Singh, Kundan Singh Bora, Abhishek Bhanot, Rahul Kumar, Amit Kumar, Ravinder Kaur

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The term ‘neuroprotection’ means preserving/salvaging function and structure of neurons. Neuroprotection is an adjunctive treatment option for neurodegenerative disorders. Oxidative stress is considered a major culprit in neurodegenerative disorders; hence, management strategies include use of antioxidants. Our search for a neuroprotective agent began with Allium cepa L. or onions, (family Amaryllidaceae) - a potent antioxidant. We have investigated the neuroprotective potential of onions in experimental models of ischemic stroke, diabetic neuropathy, neuropathic pain, and dementia. In pre and post-ischemic stroke model, the methanol extract of outer scales of onion bulbs (MEOS) prevented memory loss and motor in-coordination; reduced oxidative stress and cerebral infarct size. This also prevented and ameliorated diabetic neuropathy in mice. The MEOS was fractionated to yield a flavonoid rich fraction (FRF) that successfully reversed ischemia-reperfusion induced neuronal damage, thereby demonstrating that the flavonoids are responsible for the activity. The FRF effectively ameliorated chronic constriction induced neuropathic pain in rats. The FRF was subjected to bioactivity-guided fractionated. It was seen that FRF is more effective as compared to the isolated components probably due to synergism among the constituents (i.e., quercetin and quercetin glucosides) in the FRF. The outer scales of onion bulbs have great potential for prevention as well as for treatment of neuronal disorders. Red onions, with higher amounts of flavonoids as compared to the white onions, produced more significant neuroprotection. Thus, the standardized FRF from the waste material of a commonly used vegetable, especially the red variety, may be developed as a valuable neuroprotective agent.

Keywords: Allium cepa, antioxidant activity, flavonoid rich fraction, neuroprotection

Procedia PDF Downloads 152

Authors: Ishak Suleiman, Ahmad Kamsani Samingan, Yeoh Chun Yeow, Abdul Aziz Bin Abdul Rahman

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In this paper, we evaluate the benefits of distributed 4x4 MIMO LTE downlink systems compared to that of the co-located 4x4 MIMO LTE downlink system. The performance evaluation was carried out experimentally by using Wireless Open-Access Research Platform (WARP), where the comparison between the 4x4 MIMO LTE transmission downlink system in distributed and co-located techniques was examined. The measured Error Vector Magnitude (EVM) results showed that the distributed technique achieved better system performance compared to the co-located arrangement.

Keywords: multiple-input-multiple-output (MIMO), distributed MIMO, co-located MIMO, LTE

Procedia PDF Downloads 423

Authors: Arezou Hajhashemi, Karim Asgari, Masoud Etemadifar, Maryam Keyvani, Ali Hekmatnia

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Multiple Sclerosis (MS) is one of the most prevalent demyelinating diseases in CNS. As in other chronic cerebral diseases, impairment in cognitive functioning and in memory is popular. Because of the inflammatory and demyelinating nature of the disease, the localization of plaques in different parts of the Prefrontal and Limbic System, may lead to memorial symptoms. This investigation was intended to study relationship between frequency of plaques and memorial symptoms arising from dysfunction limbic system and prefrontal of patients with MS. The sample was selected randomly from patients with MS with memory problem, who have been referred to Isfahan Multiple Sclerosis Society. Brain System Test and Memory Test was administered to the sample, and their MRI's were analyzed by specialist in order to indentify two different parts of plaques. The data was analyzed by SPSS. The results showed that there were significant relationship between MS plaques and prefrontal's dysfunction and memorial symptom related to prefrontal area; however, there were no significant relationship between MS plaques and limbic system's dysfunction and memorial symptoms related to limbic system area. The results of this study suggest that memorial symptoms due to injury regions of the brain have the most significant relationship to prefrontal. Better judgment about these results needs more studies in future.

Keywords: multiple sclerosis, magnetic image, brain injury, behavior disorder

Procedia PDF Downloads 514

Authors: Ming-Jong Tsai, T. M. Wu, R. C. Chu

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The purpose of this study is to develop an Advanced linear calibration Technique for air flow sensing by using CTA-based Hot wire Anemometry. It contains a host PC with Human Machine Interface, a wind tunnel, a wind speed controller, an automatic data acquisition module, and nonlinear calibration model. To improve the fitting error by using single fitting polynomial, this study proposes a Multiple three-order Polynomial Fitting Method (MPFM) for fitting the non-linear output of a CTA-based Hot wire Anemometry. The CTA-based anemometer with built-in fitting parameters is installed in the wind tunnel, and the wind speed is controlled by the PC-based controller. The Hot-Wire anemometer's thermistor resistance change is converted into a voltage signal or temperature differences, and then sent to the PC through a DAQ card. After completion measurements of original signal, the Multiple polynomial mathematical coefficients can be automatically calculated, and then sent into the micro-processor in the Hot-Wire anemometer. Finally, the corrected Hot-Wire anemometer is verified for the linearity, the repeatability, error percentage, and the system outputs quality control reports.

Keywords: flow rate sensing, hot wire, constant temperature anemometry (CTA), linear calibration, multiple three-order polynomial fitting method (MPFM), temperature compensation

Procedia PDF Downloads 416

Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

Procedia PDF Downloads 87

Authors: Jaehong Yu, Seoung Bum Kim

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Clustering analysis can facilitate the extraction of intrinsic patterns in a dataset and reveal its natural groupings without requiring class information. For effective clustering analysis in high dimensional datasets, unsupervised dimensionality reduction is an important task. Unsupervised dimensionality reduction can generally be achieved by feature extraction or feature selection. In many situations, feature selection methods are more appropriate than feature extraction methods because of their clear interpretation with respect to the original features. The unsupervised feature selection can be categorized as feature subset selection and feature ranking method, and we focused on unsupervised feature ranking methods which evaluate the features based on their importance scores. Recently, several unsupervised feature ranking methods were developed based on ensemble approaches to achieve their higher accuracy and stability. However, most of the ensemble-based feature ranking methods require the true number of clusters. Furthermore, these algorithms evaluate the feature importance depending on the ensemble clustering solution, and they produce undesirable evaluation results if the clustering solutions are inaccurate. To address these limitations, we proposed an ensemble-based feature ranking method with random subspace and multiple-k ensemble (FRRM). The proposed FRRM algorithm evaluates the importance of each feature with the random subspace ensemble, and all evaluation results are combined with the ensemble importance scores. Moreover, FRRM does not require the determination of the true number of clusters in advance through the use of the multiple-k ensemble idea. Experiments on various benchmark datasets were conducted to examine the properties of the proposed FRRM algorithm and to compare its performance with that of existing feature ranking methods. The experimental results demonstrated that the proposed FRRM outperformed the competitors.

Keywords: clustering analysis, multiple-k ensemble, random subspace-based feature evaluation, unsupervised feature ranking

Procedia PDF Downloads 339

Authors: L. Tonia, I. Daglis, W. Kurth

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The sound of the universe creates an affinity with the sounds of music. The analysis of the sound of space focuses on the existence of a tone material, the microstructure and macrostructure, and the form of the sound through the signals recorded during the flight of the spacecraft Van Allen Probes and Cassini’s mission. The sound becomes from the frequencies that belong to electromagnetic waves. Plasma Wave Science Instrument and Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) recorded the signals from space. A transformation of that signals to audio gave the opportunity to study and analyze the sound. Due to the fact that the musical tone pitch has a frequency and every electromagnetic wave produces a frequency too, the creation of a musical score, which appears as the sound of space, can give information about the form, the symmetry, and the harmony of the sound. The conversion of space radio emissions to audio provides a number of tone pitches corresponding to the original frequencies. Through the process of these sounds, we have the opportunity to present a music score that “composed” from space. In this score, we can see some basic features associated with the music form, the structure, the tone center of music material, the construction and deconstruction of the sound. The structure, which was built through a harmonic world, includes tone centers, major and minor scales, sequences of chords, and types of cadences. The form of the sound represents the symmetry of a spiral movement not only in micro-structural but also to macro-structural shape. Multiple glissando sounds in linear and polyphonic process of the sound, founded in magnetic fields around Earth, Saturn, and Jupiter, but also a spiral movement appeared on the spectrogram of the sound. Whistles, Auroral Kilometric Radiations, and Chorus emissions reveal movements similar to musical excerpts of works by contemporary composers like Sofia Gubaidulina, Iannis Xenakis, EinojuhamiRautavara.

Keywords: space sound analysis, spiral, space music, analysis

Procedia PDF Downloads 177

Authors: Lin Zhang

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Neighborhood redevelopment is vital to improve residents’ living environment, and there has been a national neighborhood micro-redevelopment initiative in China since 2020, which is largely different from the previous large-scale demolition and reconstruction projects. Yet, few studies systematically examine the new interactions of multiple actors in this initiative. China’s neighborhood (micro-) redevelopment is a kind of governance network, and the complexity perspective could reflect the dynamic nature of multiple actors and their relationships in governance networks. In order to better understand the fundamental shifts of governance networks in China’s neighborhood micro-redevelopment, this paper adopted a theoretical framework of complexity in governance networks and analyzed the new governance networks of neighborhood micro-redevelopment projects in Haikou accordingly.

Keywords: neighborhood redevelopment, governance, networks, Haikou

Procedia PDF Downloads 89

Authors: Agostinho Antunes

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The completion of the human genome sequencing in 2003 opened a new perspective into the importance of whole genome sequencing projects, and currently multiple species are having their genomes completed sequenced, from simple organisms, such as bacteria, to more complex taxa, such as mammals. This voluminous sequencing data generated across multiple organisms provides also the framework to better understand the genetic makeup of such species and related ones, allowing to explore the genetic changes underlining the evolution of diverse phenotypic traits. Here, recent results from our group retrieved from comparative evolutionary genomic analyses of selected marine animal species will be considered to exemplify how gene novelty and gene enhancement by positive selection might have been determinant in the success of adaptive radiations into diverse habitats and lifestyles.

Keywords: marine genomics, evolutionary bioinformatics, human genome sequencing, genomic analyses

Procedia PDF Downloads 611

Authors: J. K. Karapetyan

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In this paper seismological-statistical analysis of actual instrumental data on the main tremor of the Great Japan earthquake 11.03.2011 is implemented for finding out the dependence between maximal values of peak ground accelerations (PGA) and epicentric distances. A number of peculiarities of manifestation of accelerations' maximum values at the interval of long epicentric distances are revealed which do not correspond with current scales of seismic intensity.

Keywords: earthquakes, instrumental records, seismic hazard, Japan

Procedia PDF Downloads 365

Authors: Eui-Hak Lee, Jae-Hyun Ro, Hyoung-Kyu Song

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In internet of things (IoT) system, the communication scheme with reliability and low power is required to connect a terminal. Cooperative communication can achieve reliability and lower power than multiple-input multiple-output (MIMO) system. Cooperative communication increases the reliability with low power, but decreases a throughput. It has a weak point that the communication throughput is decreased. In this paper, a novel scheme is proposed to increase the communication throughput. The novel scheme is a transmission structure that increases transmission rate. And a decoding scheme according to the novel transmission structure is proposed. Simulation results show that the proposed scheme increases the throughput without bit error rate (BER) performance degradation.

Keywords: cooperative communication, IoT, STBC, transmission rate

Procedia PDF Downloads 396

Authors: Maria A. Castillo H., Andres R. Leandro, Jose F. Bienvenido B.

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In 2015, Guatemala officially adopted the Sustainable Development Goals (SDG) according to the 2030 Agenda agreed by the United Nations Organization. In 2016, these objectives and goals were reviewed, and the National Priorities were established within the K'atún 2032 National Development Plan. In 2019 and 2021, progress was evaluated with 120 defined indicators, and the need to improve quality and availability of statistical data necessary for the analysis of sustainability indicators was detected, so the values to be reached in 2024 and 2032 were adjusted. The need for greater agricultural technology is one of the priorities established within SDG 2 "Zero Hunger". Within this area, protected agricultural production provides greater productivity throughout the year, reduces the use of chemical products to control pests and diseases, reduces the negative impact of climate and improves product quality. During the crisis caused by Covid-19, there was an increase in exports of fruits and vegetables produced in greenhouses from Guatemala. However, this information has not been considered in the 2021 revision of the Plan. The objective of this study is to evaluate the information available on Greenhouse Agricultural Production and its integration into the Sustainability Indicators for Guatemala. This study was carried out in four phases: 1. Analysis of the Goals established for SDG 2 and the indicators included in the K'atún Plan. 2. Analysis of Environmental, Social and Economic Indicator Models. 3. Definition of territorial levels in 2 geographic scales: Departments and Municipalities. 4. Diagnosis of the available data on technological agricultural production with emphasis on Greenhouses at the 2 geographical scales. A summary of the results is presented for each phase and finally some recommendations for future research are added. The main contribution of this work is to improve the available data that allow the incorporation of some agricultural technology indicators in the established goals, to evaluate their impact on Food Security and Nutrition, Employment and Investment, Poverty, the use of Water and Natural Resources, and to provide a methodology applicable to other production models and other geographical areas.

Keywords: greenhouses, protected agriculture, sustainable indicators, Guatemala, sustainability, SDG

Procedia PDF Downloads 85

Authors: Estela Macedo Alves

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This paper is an overview on public policy analysis focused on the study of Brazilian public policy making process. The methodology is based on the review of some theories on the subject, linking them to Brazilian reality. The study presents basic policy analysis concepts, such as policy, polity and politics. It is emphasized John Kingdon's Multiple Stream Model, because of its clarifying aspects concerning public policies formulation process in democratic countries. In this path it was possible to establish interpretations on environmental public policies in Brazil and understand its methods, instead of presenting only a case study. At the end, it is possible to connect theory with Brazilian reality, identifying negative and positive points of its political processes and structure.

Keywords: Brazilian policies, environmental public policy, multiple stream model, public policy analysis

Procedia PDF Downloads 408

Authors: R. R. Ramsheeja, R. Sreeraj

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For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

Procedia PDF Downloads 509

Authors: Lemuel David

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This study aims to investigate The Impact of Tax Policies on Small Business Growth in Developing Countries: A Case Study of Montserrado Mount County, Republic of Liberia. Businesses in Liberia are crucial for job creation and the economic empowerment of its citizens, especially in Grand Cape Mount County where they provide 95% of all jobs and support local capital formation. However, many businesses face challenges that lead to premature closure, including tax-related issues such as multiple taxations and high tax burdens. This research aims to examine the effects of various taxation on business survival in Grand Cape Mount County. The study employed a survey research design with a population of 50 and a sample size of 74. Data was collected using a self-administered questionnaire and analyzed quantitatively with simple percentages, and the research hypotheses were tested with ANOVA. The study findings revealed that multiple taxations hurts business survival, and the relationship between business size and its ability to pay taxes is significant. Therefore, the study recommends that the government of Liberia should create uniform tax policies that support business development in Grand Cape Mount County, and consider the size of businesses when formulating tax policies.

Keywords: multiple taxations, businesses, mortality, growth

Procedia PDF Downloads 74

Authors: Anurag Saxena, Alkesh Agrawal, Dinesh Kumar

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The next generation mobile communication systems i.e. fourth generation (4G) was developed to accommodate the quality of service and required data rate. This project focuses on multiple access technique proposed in 4G communication systems. It is attempted to demonstrate the IDMA (Interleave Division Multiple Access) technology. The basic principle of IDMA is that interleaver is different for each user whereas CDMA employs different signatures. IDMA inherits many advantages of CDMA such as robust against fading, easy cell planning; dynamic channel sharing and IDMA increase the spectral efficiency and reduce the receiver complexity. In this, performance of IDMA is analyzed using QC-LDPC coding scheme further it is compared with LDPC coding and at last BER is calculated and plotted in MATLAB.

Keywords: 4G, QC-LDPC, CDMA, IDMA

Procedia PDF Downloads 323

Authors: Athena Daniilidou, Maria Platsidou

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Recently developed scales addressed -specifically- teachers’ resilience. Although they profited from the field, they do not include some of the critical protective factors of teachers’ resilience identified in the literature. To address this limitation, we aimed at designing a more comprehensive scale for measuring teachers' resilience which encompasses various personal and environmental protective factors. To this end, two studies were carried out. In Study 1, 407 primary school teachers were tested with the new scale, the Teachers’ Protective Factors of Resilience Scale (TPFRS). Similar scales, such as the Multidimensional Teachers’ Resilience Scale and the Teachers’ Resilience Scale), were used to test the convergent validity, while the Maslach Burnout Inventory and the Teachers’ Sense of Efficacy Scale was used to assess the discriminant validity of the new scale. The factorial structure of the TPFRS was checked with confirmatory factor analysis and a good fit of the model to the data was found. Next, item response theory analysis using a two-parameter model (2PL) was applied to check the items within each factor. It revealed that 9 items did not fit the corresponding factors well and they were removed. The final version of the TPFRS includes 29 items, which assess six protective factors of teachers’ resilience: values and beliefs (5 items, α=.88), emotional and behavioral adequacy (6 items, α=.74), physical well-being (3 items, α=.68), relationships within the school environment, (6 items, α=.73) relationships outside the school environment (5 items, α=.84), and the legislative framework of education (4 items, α=.83). Results show that it presents a satisfactory convergent and discriminant validity. Study 2, in which 964 primary and secondary school teachers were tested, confirmed the factorial structure of the TPFRS as well as its discriminant validity, which was tested with the Schutte Emotional Intelligence Scale-Short Form. In conclusion, our results confirmed that the TPFRS is a valid instrument for assessing teachers' protective factors of resilience and it can be safely used in future research and interventions in the teaching profession. In conclusion, our results showed that the TPFRS is a new multi-dimensional instrument valid for assessing teachers' protective factors of resilience and it can be safely used in future research and interventions in the teaching profession.

Keywords: resilience, protective factors, teachers, item response theory

Procedia PDF Downloads 99

Authors: Sameerah A. Al-Hariri Al-Zahrani

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The current study aims at getting acquainted with the impact of the use of some multiple intelligence-based teaching strategies on developing moral intelligence and inferential jurisprudential thinking among secondary school female students. The study has endeavored to answer the following questions: What is the impact of the use of some multiple intelligence-based teaching strategies on developing inferential jurisprudential thinking and moral intelligence among first-year secondary school female students? In the frame of this main research question, the study seeks to answer the following sub-questions: (i) What are the inferential jurisprudential thinking skills among first-year secondary school female students? (ii) What are the components of moral intelligence among first year secondary school female students? (iii) What is the impact of the use of some multiple intelligence‐based teaching strategies (such as the strategies of analyzing values, modeling, Socratic discussion, collaborative learning, peer collaboration, collective stories, building emotional moments, role play, one-minute observation) on moral intelligence among first-year secondary school female students? (iv) What is the impact of the use of some multiple intelligence‐based teaching strategies (such as the strategies of analyzing values, modeling, Socratic discussion, collaborative learning, peer collaboration, collective stories, building emotional moments, role play, one-minute observation) on developing the capacity for inferential jurisprudential thinking of juristic rules among first-year secondary school female students? The study has used the descriptive-analytical methodology in surveying, analyzing, and reviewing the literature on previous studies in order to benefit from them in building the tools of the study and the materials of experimental treatment. The study has also used the experimental method to study the impact of the independent variable (multiple intelligence strategies) on the two dependent variables (moral intelligence and inferential jurisprudential thinking) in first-year secondary school female students’ learning. The sample of the study is made up of 70 female students that have been divided into two groups: an experimental group consisting of 35 students who have been taught through multiple intelligence strategies, and a control group consisting of the other 35 students who have been taught normally. The two tools of the study (inferential jurisprudential thinking test and moral intelligence scale) have been implemented on the two groups as a pre-test. The female researcher taught the experimental group and implemented the two tools of the study. After the experiment, which lasted eight weeks, was over, the study showed the following results: (i) The existence of significant statistical differences (0.05) between the mean average of the control group and that of the experimental group in the inferential jurisprudential thinking test (recognition of the evidence of jurisprudential rule, recognition of the motive for the jurisprudential rule, jurisprudential inferencing, analogical jurisprudence) in favor of the experimental group. (ii) The existence of significant statistical differences (0.05) between the mean average of the control group and that of the experimental group in the components of the moral intelligence scale (sympathy, conscience, moral wisdom, tolerance, justice, respect) in favor of the experimental group. The study has, thus, demonstrated the impact of the use of some multiple intelligence-based teaching strategies on developing moral intelligence and inferential jurisprudential thinking.

Keywords: moral intelligence, teaching, inferential jurisprudential thinking, secondary school

Procedia PDF Downloads 159

Authors: Poonam Yadav, Dong Bok Lee

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Isothermal oxidation at 800°C for 50h and Cyclic oxidation at 600°C and 800°C for 40h of Pure Ti and Ti64 were performed in a muffle furnace. In Cyclic oxidation, massive scale spallation occurred, and the oxide scale cracks and peels off were observed at high temperature, it represents oxide scale that formed during cyclic oxidation was spalled out owing to stresses due to thermal shock generated during repetitive oxidation and subsequent cooling. The thickness of scale is larger in cyclic oxidation than the isothermal case. This is due to inward diffusion of oxygen through oxide scales and/or pores and cracks in cyclic oxidation.

Keywords: cyclic, diffusion, isothermal, cyclic

Procedia PDF Downloads 919

Authors: Frederico Fialho Teixeira, Islam Mashaly, Maryam Shafiei, Jurij Karlovsek

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The ubiquity of data gathering and smart technologies, advancements in virtual technologies, and the development of the internet of things (IoT) have created urgent demands for the development of frameworks and efficient workflows for data collection, visualisation, and analysis. Digital twin, in different scales of the city into the building, allows for bringing together data from different sources to generate fundamental and illuminating insights for the management of current facilities and the lifecycle of amenities as well as improvement of the performance of current and future designs. Over the past two decades, there has been growing interest in the topic of digital twin and their applications in city and building scales. Most such studies look at the urban environment through a homogeneous or generalist lens and lack specificity in particular characteristics or identities, which define an urban university campus. Bridging this knowledge gap, this paper offers a framework for developing a digital twin for a university campus that, with some modifications, could provide insights for any large-scale digital twin settings like towns and cities. It showcases how currently unused data could be purposefully combined, interpolated and visualised for producing analysis-ready data (such as flood or energy simulations or functional and occupancy maps), highlighting the potential applications of such a framework for campus planning and policymaking. The research integrates campus-level data layers into one spatial information repository and casts light on critical data clusters for the digital twin at the campus level. The paper also seeks to raise insightful and directive questions on how digital twin for campus can be extrapolated to city-scale digital twin. The outcomes of the paper, thus, inform future projects for the development of large-scale digital twin as well as urban and architectural researchers on potential applications of digital twin in future design, management, and sustainable planning, to predict problems, calculate risks, decrease management costs, and improve performance.

Keywords: digital twin, smart campus, framework, data collection, point cloud

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Authors: Julio Jesus Salazar, Max Jesus De Lama

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The challenges of water management are aggravated by global change, which implies high complexity and associated uncertainty; water management is difficult because water networks cross domains (natural, societal, and political), scales (space, time, jurisdictional, institutional, knowledge, etc.) and levels (area: patches to global; knowledge: a specific case to generalized principles). In this context, we need to apply natural and non-natural measures to manage water and soil. The Basin Management Methodology considers multifunctional measures of natural water retention and erosion control and soil formation to protect water resources and address the challenges related to the recovery or conservation of the ecosystem, as well as natural characteristics of water bodies, to improve the quantitative status of water bodies and reduce vulnerability to floods and droughts. This method of water management focuses on the positive impacts of the chemical and ecological status of water bodies, restoration of the functioning of the ecosystem and its natural services; thus, contributing to both adaptation and mitigation of climate change. This methodology was applied in 7 interventions in the sub-basin of the Shullcas River in Huancayo-Junín-Peru, obtaining great benefits in the framework of the participation of alliances of actors and integrated planning scenarios. To implement the methodology in the sub-basin of the Shullcas River, a process called Climate Smart Territories (CST) was used; with which the variables were characterized in a highly complex space. The diagnosis was then worked using risk management and adaptation to climate change. Finally, it was concluded with the selection of alternatives and projects of this type. Therefore, the CST approach and process face the challenges of climate change through integrated, systematic, interdisciplinary and collective responses at different scales that fit the needs of ecosystems and their services that are vital to human well-being. This methodology is now replicated at the level of the Mantaro river basin, improving with other initiatives that lead to the model of a resilient basin.

Keywords: climate-smart territories, climate change, ecosystem services, natural measures, Climate Smart Territories (CST) approach

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Authors: Yuan Huang, Xiangping Chen, Xiaonan Luo

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Current software are continuously updating. The change between two versions usually involves multiple program entities (e.g., packages, classes, methods, attributes) with multiple purposes (e.g., changed requirements, bug fixing). It is hard for developers to understand which changes are made for the same purpose. Whether two changes are related is not decided by the relationship between this two entities in the program. In this paper, we summarized 4 coupling rules(16 instances) and 4 state-combination types at the class, method and attribute levels for software change. Related Change Vector (RCV) are defined based on coupling rules and state-combination types, and applied to classify related software changes by using Probabilistic Neural Network during a software updating.

Keywords: PNN, related change, state-combination, logical coupling, software entity

Procedia PDF Downloads 437

Authors: Ergham Al Bachir

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This study adopts strategic leadership (Upper Echelons) as the core theory and contextual leadership theory as the research lens. This research asks how the external context impacts strategic leadership effectiveness to achieve the outcomes in pluralistic organizations (PO). The study explores how the context influences the selection of CEOs, top management teams (TMT), and their leadership effectiveness. POs are characterized by the multiple objectives of their top management teams, divergent objectives, multiple strategies, and multiple governing authorities. The research question is explored by means of a qualitative multiple-case study focusing on healthcare, real estate, and financial services organizations. The data sources are semi-structured interviews, documents, and direct observations. The data analysis strategy is inductive and deploys thematic analysis and cross-case synthesis. The findings differentiate between national and international CEOs' delegation of authority and relationship with the Board of Directors. The findings identify the elements of the dynamic context that influence TMT and PO outcomes. The emergent hybrid strategic and contextual leadership framework shows how the different contextual factors influence strategic direction, PO context, selection of CEOs and TMT, and the outcomes in four pluralistic organizations. The study offers seven theoretical contributions to Upper Echelons, strategic leadership, and contextual leadership research. (1) The integration of two theories revealed how CEO’s impact on the organization is complementary to the contextual impact. (2) Conducting this study in the Middle East contributes to strategic leadership and contextual leadership research. (3) The demonstration of the significant contextual effects on the selection of CEOs. (4 and 5) Two contributions revealed new links between the context, the Board role, internal versus external CEOs, and national versus international CEOs. (6 and 7) This study offered two definitions: what accounts for CEO leadership effectiveness and organizational outcomes. Two methodological contributions were also identified: (1) Previous strategic leadership and Upper Echelons research are mainly quantitative, while this study adopts qualitative multiple-case research with face-to-face interviews. (2) The extrication of the CEO from the TMT advanced the data analysis in strategic leadership research. Four contributions are offered to practice: (1) The CEO's leadership effectiveness inside and outside the organization. (2) Rapid turnover of predecessor CEOs signifies the need for a strategic and contextual approach to CEOs' succession. (3) TMT composition and education impact on TMT-CEO and TMT-TMT interface. (4) Multilevel strategic contextual leadership development framework.

Keywords: strategic leadership, contextual leadership, upper echelons, pluralistic organizations, cross-cultural leadership

Procedia PDF Downloads 92

Authors: Animish Jain

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This study deals with using Multiplicative Weight Update within artificial intelligence and machine learning to create models that can diagnose skin cancer using microscopic images of cancer samples. In this study, the multiplicative weight update method is used to take the predictions of multiple models to try and acquire more accurate results. Logistic Regression, Convolutional Neural Network (CNN), and Support Vector Machine Classifier (SVMC) models are employed within the Multiplicative Weight Update system. These models are trained on pictures of skin cancer from the ISIC-Archive, to look for patterns to label unseen scans as either benign or malignant. These models are utilized in a multiplicative weight update algorithm which takes into account the precision and accuracy of each model through each successive guess to apply weights to their guess. These guesses and weights are then analyzed together to try and obtain the correct predictions. The research hypothesis for this study stated that there would be a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The SVMC model had an accuracy of 77.88%. The CNN model had an accuracy of 85.30%. The Logistic Regression model had an accuracy of 79.09%. Using Multiplicative Weight Update, the algorithm received an accuracy of 72.27%. The final conclusion that was drawn was that there was a significant difference in the accuracy of the three models and the Multiplicative Weight Update system. The conclusion was made that using a CNN model would be the best option for this problem rather than a Multiplicative Weight Update system. This is due to the possibility that Multiplicative Weight Update is not effective in a binary setting where there are only two possible classifications. In a categorical setting with multiple classes and groupings, a Multiplicative Weight Update system might become more proficient as it takes into account the strengths of multiple different models to classify images into multiple categories rather than only two categories, as shown in this study. This experimentation and computer science project can help to create better algorithms and models for the future of artificial intelligence in the medical imaging field.

Keywords: artificial intelligence, machine learning, multiplicative weight update, skin cancer

Procedia PDF Downloads 79

Authors: Shun-Chang Yen, You-Lun Peng, Kuo-Ching San

Abstract:

A numerical study on a bluff-body structure with multiple holes was conducted using ANSYS Fluent computational fluid dynamics analysis. The effects of the hole number and jet inclination angles were considered under a fixed gas flow rate and nonreactive gas. The bluff body with multiple holes can transform the axial momentum into a radial and tangential momentum as well as increase the swirl number (S). The concentration distribution in the mixing of a central carbon dioxide (CO2) jet and an annular air jet was utilized to analyze the mixing efficiency. Three bluff bodies with differing hole numbers (H = 3, 6, and 12) and three jet inclination angles (θ = 45°, 60°, and 90°) were designed for analysis. The Reynolds normal stress increases with the inclination angle. The Reynolds shear stress, average turbulence intensity, and average swirl number decrease with the inclination angle. For an unsymmetrical hole configuration (i.e., H = 3), the streamline patterns exhibited an unsymmetrical flow field. The highest mixing efficiency (i.e., the lowest integral gas fraction of CO2) occurred at H = 3. Furthermore, the highest swirl number coincided with the strongest effect on the mass fraction of CO2. Therefore, an unsymmetrical hole arrangement induced a high swirl flow behind the porous disc.

Keywords: bluff body with multiple holes, computational fluid dynamics, swirl-jet flow, mixing efficiency

Procedia PDF Downloads 357

Authors: Parthiban Srinivasan

Abstract:

PubMed provides online access to the National Library of Medicine database (MEDLINE) and other publications, which contain close to 25 million scientific citations from 1865 to the present. There are close to 80 million author name instances in those close to 25 million citations. For any work of literature, a fundamental issue is to identify the individual(s) who wrote it, and conversely, to identify all of the works that belong to a given individual. Due to the lack of universal standards for name information, there are two aspects of name ambiguity: name synonymy (a single author with multiple name representations), and name homonymy (multiple authors sharing the same name representation). In this talk, we present some results from our extensive work in author name disambiguation for PubMed citations. Information will be presented on the effectiveness and shortcomings of different aspects of successful name disambiguation such as parsing, validation, standardization and normalization.

Keywords: disambiguation, normalization, parsing, PubMed

Procedia PDF Downloads 300

Authors: Soo Hong Da, Ng Zheng Yao, Burra Venkata Durga Kumar

Abstract:

The Healthcare sector is a business that consists of providing medical services, manufacturing medical equipment and drugs as well as providing medical insurance to the public. Most of the time, the data stored in the healthcare database is to be related to patient’s information which is required to be accurate when it is accessed by authorized stakeholders. In distributed systems, one important issue is concurrency in the system as it ensures the shared resources to be synchronized and remains consistent through multiple read and write operations by multiple clients. The problems of concurrency in the healthcare sector are who gets the access and how the shared data is synchronized and remains consistent when there are two or more stakeholders attempting to the shared data simultaneously. In this paper, a framework that is beneficial to distributed healthcare sector concurrent environment is proposed. In the proposed framework, four different level nodes of the database, which are national center, regional center, referral center, and local center are explained. Moreover, the frame synchronization is not symmetrical. There are two synchronization techniques, which are complete and partial synchronization operation are explained. Furthermore, when there are multiple clients accessed at the same time, synchronization types are also discussed with cases at different levels and priorities to ensure data is synchronized throughout the processes.

Keywords: resources, healthcare, concurrency, synchronization, stakeholders, database

Procedia PDF Downloads 150

Authors: Jatindranath Gain, Madhumita DasSarkar, Sudakshina Kundu

Abstract:

Quantum information is stored in states with multiple quasiparticles, which have a topological degeneracy. Topological quantum computation is concerned with two-dimensional many body systems that support excitations. Anyons are elementary building block of quantum computations. When anyons tunneling in a double-layer system can transition to an exotic non-Abelian state and produce Fibonacci anyons, which are powerful enough for universal topological quantum computation (TQC).Here the exotic behavior of Fibonacci Superlattice is studied by using analytical transfer matrix methods and hence Fibonacci anyons. This Fibonacci anyons can build a quantum computer which is very emerging and exciting field today’s in Nanophotonics and quantum computation.

Keywords: quantum computing, quasicrystals, Multiple Quantum wells (MQWs), transfer matrix method, fibonacci anyons, quantum hall effect, nanophotonics

Procedia PDF Downloads 390

Authors: A. Lubis, R. Widayanti, Z. Hikmah, A. Endaryanto, A. Harsono, A. Harianto, R. Etika, D. K. Handayani, M. Sampurna

Abstract:

Neonatal lupus erythematous (NLE) is a rare disease marked by clinical characteristic and specific maternal autoantibody. Many cutaneous, cardiac, liver, and hematological manifestations could happen with affect of one organ or multiple. In this case, both babies were premature, low birth weight (LBW), small for gestational age (SGA) and born through caesarean section from a systemic lupus erythematous (SLE) mother. In the first case, we found a baby girl with dyspnea and grunting. Chest X ray showed respiratory distress syndrome (RDS) great I and echocardiography showed small atrial septal defect (ASD) and ventricular septal defect (VSD). She also developed anemia, thrombocytopenia, elevated C-reactive protein, hypoalbuminemia, increasing coagulation factors, hyperbilirubinemia, and positive blood culture of Klebsiella pneumonia. Anti-Ro/SSA and Anti-nRNP/sm were positive. Intravenous fluid, antibiotic, transfusion of blood, thrombocyte concentrate, and fresh frozen plasma were given. The second baby, male presented with necrotic tissue on the left ear and skin rashes, erythematous macula, athropic scarring, hyperpigmentation on all of his body with various size and facial haemorrhage. He also suffered from thrombocytopenia, mild elevated transaminase enzyme, hyperbilirubinemia, anti-Ro/SSA was positive. Intravenous fluid, methyprednisolone, intravenous immunoglobulin (IVIG), blood, and thrombocyte concentrate transfution were given. Two cases of neonatal lupus erythematous had been presented. Diagnosis based on clinical presentation and maternal auto antibody on neonate. Organ involvement in NLE can occur as single or multiple manifestations.

Keywords: neonatus lupus erythematous, maternal autoantibody, clinical characteristic, multiple organ manifestation

Procedia PDF Downloads 424

Authors: Ashish Kumar, Munesh Raghuraj Varma, Nisarg Joshi, Gujjula Vishwa Teja, Srikanth Sambi, Arpit Awasthi

Abstract:

Autonomous driving vehicles are revolutionizing the transportation system of the 21st century. This has been possible due to intensive research put into making a robust, reliable, and intelligent program that can perceive and understand its environment and make decisions based on the understanding. It is a very data-intensive task with data coming from multiple sensors and the amount of data directly reflects on the performance of the system. Researchers have to design the preprocessing pipeline for different datasets with different sensor orientations and alignments before the dataset can be fed to the model. This paper proposes a solution that provides a method to unify all the data from different sources into a uniform format using the intrinsic and extrinsic parameters of the sensor used to capture the data allowing the same pipeline to use data from multiple sources at a time. This also means easy adoption of new datasets or In-house generated datasets. The solution also automates the complete deep learning pipeline from preprocessing to post-processing for various tasks allowing researchers to design multiple custom end-to-end pipelines. Thus, the solution takes care of the input and output data handling, saving the time and effort spent on it and allowing more time for model improvement.

Keywords: augmentation, autonomous driving, camera, custom end-to-end pipeline, data unification, lidar, post-processing, preprocessing

Procedia PDF Downloads 123