Search results for: data interpolating empirical orthogonal function

Authors: Samantha A. Cintron, Janet Pierce, Mihaela E. Sardiu, Diane Mahoney, Jill Peltzer, Bhanu Gupta, Qiuhua Shen

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High output heart failure (HOHF) is characterized a high output state resulting from an underlying disease process and is commonly caused by obesity. As obesity levels increase, more individuals will be at risk for obesity-related HOHF. However, the underlying pathophysiologic mechanisms of obesity-related HOHF are not well understood and need further research. The aim of the study was to describe the differences in leukocyte transcriptomes of morbidly obese patients with HOHF and those with non-HOHF. In this cross-sectional study, the study team collected blood samples, demographics, and clinical data of six patients with morbid obesity and HOHF and six patients with morbid obesity and non-HOHF. The study team isolated the peripheral blood leukocyte RNA and applied stranded total RNA sequencing. Differential gene expression was calculated, and Ingenuity Pathway Analysis software was used to interpret the canonical pathways, functional changes, upstream regulators, and mechanistic and causal networks that were associated with the significantly different leukocyte transcriptomes. The study team identified 116 differentially expressed genes; 114 were upregulated, and 2 were downregulated in the HOHF group (Benjamini-Hochberg adjusted p-value ≤ 0.05 and log2(fold-change) of ±1). The differentially expressed genes were involved with cell proliferation, mitochondrial function, erythropoiesis, erythrocyte stability, and apoptosis. The top upregulated canonical pathways associated with differentially expressed genes were autophagy, adenosine monophosphate-activated protein kinase signaling, and senescence pathways. Upstream regulator GATA Binding Protein 1 (GATA1) and a network associated with nuclear factor kappa-light chain-enhancer of activated B cells (NF-kB) were also identified based on the different leukocyte transcriptomes of morbidly obese patients with HOHF and non-HOHF. To the author’s best knowledge, this is the first study that reported the differential gene expression in patients with obesity-related HOHF and demonstrated the unique pathophysiologic mechanisms underlying the disease. Further research is needed to determine the role of cellular function and maintenance, inflammation, and iron homeostasis in obesity-related HOHF.

Keywords: cardiac output, heart failure, obesity, transcriptomics

Procedia PDF Downloads 39

Authors: Christina Tay

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This paper investigates the impact of Information and Communication Technology (ICT) on bilateral trade in goods. Empirical analysis is performed on the United States and 34 partnering countries from 2000 to 2013. Our econometric model fits the data well, explaining 52% of the variation in trade flows for goods trade, 53.2% of the variation in trade flows for goods export and 48% of the variation in trade flows for goods import. For every 10% increase in fixed broadband Internet subscribers per 100 people increases, goods trade by 7.9% and for every 5% increase in fixed broadband Internet subscribers per 100 people, goods export increases by 11%. For every 1% increase in fixed telephone line penetration per 100 people, goods trade increases by 26.3%, goods export increases by 24.4% and goods import increases by 24.8%. For every 1% increase in mobile-cellular telephone subscriptions, goods trade decreases by 29.6% and goods export decreases by 27.1%, whilst for every 0.01% increase in mobile-cellular telephone subscriptions, goods import decreases by 34.3%. For every 1% increase in the percentage of population who used the Internet from any location in the last 12 months Internet, goods trade increases by 32.5%, goods export increases by 38.9%, goods import increases by 33%. All our trade determinants as well as our ICT variables have significances on goods exports for the US. We can also draw from our study that the US relies more rather heavily on ICT for its goods export compared to goods import.

Keywords: bilateral trade, fixed broadband, fixed telephone, goods trade, information and communicative technologies, Internet, mobile-cellular phone

Procedia PDF Downloads 277

Authors: Victor Breux, Jérôme Boutet, Alain Goret, Viviane Cattin

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Early detection of anomalies in data centers is important to reduce downtimes and the costs of periodic maintenance. However, there is little research on this topic and even fewer on the fusion of sensor data for the detection of abnormal events. The goal of this paper is to propose a method for anomaly detection in data centers by combining sensor data (temperature, humidity, power) and deep learning models. The model described in the paper uses one autoencoder per sensor to reconstruct the inputs. The auto-encoders contain Long-Short Term Memory (LSTM) layers and are trained using the normal samples of the relevant sensors selected by correlation analysis. The difference signal between the input and its reconstruction is then used to classify the samples using feature extraction and a random forest classifier. The data measured by the sensors of a data center between January 2019 and May 2020 are used to train the model, while the data between June 2020 and May 2021 are used to assess it. Performances of the model are assessed a posteriori through F1-score by comparing detected anomalies with the data center’s history. The proposed model outperforms the state-of-the-art reconstruction method, which uses only one autoencoder taking multivariate sequences and detects an anomaly with a threshold on the reconstruction error, with an F1-score of 83.60% compared to 24.16%.

Keywords: anomaly detection, autoencoder, data centers, deep learning

Procedia PDF Downloads 179

Authors: Mingbao Chen, Mingli Zhao

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The coastal zone is the intersection of land and sea system, and also is the connecting zone of the two economic systems of land and sea. In the world, all countries attach great importance to the coastal zone management and the coastal zone economy. In China, the government has developed a number of related coastal management policies and institutional, such as marine functional zoning, main function zoning, integrated coastal zone management, to ensure the sustainable utilization of the coastal zone and promote the development of coastal economic. However, in practice, the effect is not satisfactory. This paper analyses the coastal areas of coastal zone management on coastal economic growth contribution based on coastal areas economic development data with the 2007-2015 in China, which uses the method of the evaluation index system of coastal zone management institutional efficiency. The results show that the coastal zone management institutional objectives are not clear, and the institutional has high repeatability. At the same time, over management of coastal zone leads to low economic efficiency because the government management boundary is blurred.

Keywords: institutional overlap, over management, coastal zone management, coastal zone economy

Procedia PDF Downloads 370

Authors: Rosy Joseph

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From an algebraic point of view, Semirings provide the most natural generalization of group theory and ring theory. In the absence of additive inverse in a semiring, one had to impose a weaker condition on the semiring, i.e., the additive cancellative law to study interesting structural properties. In many practical situations, fuzzy numbers are used to model imprecise observations derived from uncertain measurements or linguistic assessments. In this connection, a special class of fuzzy numbers whose shape is symmetric with respect to a vertical line called the symmetric fuzzy numbers i.e., for α ∈ (0, 1] the α − cuts will have a constant mid-point and the upper end of the interval will be a non-increasing function of α, the lower end will be the image of this function, is suitable. Based on this description, arithmetic operations and a ranking technique to order the symmetric fuzzy numbers were dealt with in detail. Wherein it was observed that the structure of the class of symmetric fuzzy numbers forms a commutative semigroup with cancellative property. Also, it forms a multiplicative monoid satisfying sub-distributive property.In this paper, we introduce the algebraic structure, sub-distributive semiring and discuss its various properties viz., ideals and prime ideals of sub-distributive semiring, sub-distributive ring of difference etc. in detail. Symmetric fuzzy numbers are visualized as an illustration.

Keywords: semirings, subdistributive ring of difference, subdistributive semiring, symmetric fuzzy numbers

Procedia PDF Downloads 197

Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

Procedia PDF Downloads 179

Authors: Babek Erdebilli

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The aim of this study is to develop and describe a new methodology for the Multi-Criteria Decision-Making (MCDM) problem using IFE (Elimination Et Choix Traduisant La Realite (ELECTRE) model. The proposed models enable Decision-Makers (DMs) on the assessment and use Intuitionistic Fuzzy Numbers (IFN). A numerical example is provided to demonstrate and clarify the proposed analysis procedure. Also, an empirical experiment is conducted to validation the effectiveness.

Keywords: multi-criteria decision-making, IFE, DM’s, fuzzy electre model

Procedia PDF Downloads 632

Authors: Eun Jae Ko, In Young Sung, Eui Soo Joeng

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Cognitive impairment is commonly encountered problem in children with various clinical diseases, including Down syndrome, autism spectrum disorder, brain injury, and others. Cognitive impairment limits participation in education and society, and this further hinders development in cognition. However, young children with cognitive impairment tend not to respond well to traditional cognitive treatments, therefore alternative treatment choices are need. As a cognitive training program, touch screen technology can easily be applied to very young children by involving visual and auditory support. Injini was developed as tablet computer based cognitive rehabilitation program for young children or individuals with severe cognitive impairment, which targeted on cognitive ages of 18 to 36 months. The aim of this study was to evaluate the efficacy of a tablet computer based cognitive rehabilitation program (Injini) for children with cognitive impairment. 38 children between cognitive ages of 18 to 36 months confirmed by cognitive evaluations were recruited and randomly assigned to the intervention group (n=20) and the control group (n=18). The intervention group received tablet computer based cognitive rehabilitation program (Injini) for 30 minutes per session, twice a week, over a period of 12 weeks, in addition to the traditional rehabilitation program. The control group received traditional rehabilitation program only. Mental score of Bayley Scales of Infant Development II (BSID II), Pediatric Evaluation of Disability Inventory (PEDI), Laboratory Temperament Assessment Battery (Lab-TAB), Early Childhood Behavior Questionnaire (ECBQ), and Goal Attainment Scale (GAS) were evaluated before and after 12 weeks of therapeutic intervention. When comparing the baseline characteristics, there was no significant difference between the two groups in the measurements of cognitive function. After 12 weeks of treatment, both group showed improvements in all measurements. However, in comparison of improvements after treatment, the intervention group showed more improvements in the mental score of BSID II, social function domain of PEDI, observation domain of Lab-TAB, and GAS, as compared to the control group. Application of the tablet computer based cognitive rehabilitation program (Injini) would be beneficial for improvement of cognitive function in young children with cognitive impairment.

Keywords: cognitive therapy, computer-assisted therapy, early intervention, tablets

Procedia PDF Downloads 270

Authors: K. Zehouani, I. Oldal

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Purpose: In the human knee joint, degenerative joint disease may happen with time. The standard treatment of this disease is the total knee replacement through prosthesis implanting. The reason lies in the fact that this phenomenon causes different material abrasion as compare to pure sliding or rolling alone. This study focuses on developing a knee prosthesis geometry, which fulfills the mechanical and kinematical requirements. Method: The MSC ADAMS program is used to describe the rotation of the human knee joint as a function of flexion, and to investigate how the flexion and rotation movement changes between the condyles of a multi-body model of the knee prosthesis as a function of flexion angle (in the functional arc of the knee (20-120º)). Moreover, the multi-body model with identical boundary conditions is constituted, and the numerical simulations are carried out using the MSC ADAMS program system. Results: It is concluded that the use of the multi-body model reduces time and cost since it does not need to manufacture the tibia and the femur as it requires for the knee prosthesis of the test machine. Moreover, without measuring or by dispensing with a test machine for the knee prosthesis geometry, approximation of the results of our model to a human knee is carried out directly. Conclusion: The pattern obtained by the multi-body model provides an insight for future experimental tests related to the rotation and flexion of the knee joint concerning the actual average and friction load.

Keywords: biomechanics, knee joint, rotation, flexion, kinematics, MSC ADAMS

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Authors: Pavel H. Llamocca, Victoria Lopez

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The main objective of our work is the comparative analysis of environmental data from Open Data bases, belonging to different governments. This means that you have to integrate data from various different sources. Nowadays, many governments have the intention of publishing thousands of data sets for people and organizations to use them. In this way, the quantity of applications based on Open Data is increasing. However each government has its own procedures to publish its data, and it causes a variety of formats of data sets because there are no international standards to specify the formats of the data sets from Open Data bases. Due to this variety of formats, we must build a data integration process that is able to put together all kind of formats. There are some software tools developed in order to give support to the integration process, e.g. Data Tamer, Data Wrangler. The problem with these tools is that they need data scientist interaction to take part in the integration process as a final step. In our case we don’t want to depend on a data scientist, because environmental data are usually similar and these processes can be automated by programming. The main idea of our tool is to build Hadoop procedures adapted to data sources per each government in order to achieve an automated integration. Our work focus in environment data like temperature, energy consumption, air quality, solar radiation, speeds of wind, etc. Since 2 years, the government of Madrid is publishing its Open Data bases relative to environment indicators in real time. In the same way, other governments have published Open Data sets relative to the environment (like Andalucia or Bilbao). But all of those data sets have different formats and our solution is able to integrate all of them, furthermore it allows the user to make and visualize some analysis over the real-time data. Once the integration task is done, all the data from any government has the same format and the analysis process can be initiated in a computational better way. So the tool presented in this work has two goals: 1. Integration process; and 2. Graphic and analytic interface. As a first approach, the integration process was developed using Java and Oracle and the graphic and analytic interface with Java (jsp). However, in order to open our software tool, as second approach, we also developed an implementation with R language as mature open source technology. R is a really powerful open source programming language that allows us to process and analyze a huge amount of data with high performance. There are also some R libraries for the building of a graphic interface like shiny. A performance comparison between both implementations was made and no significant differences were found. In addition, our work provides with an Official Real-Time Integrated Data Set about Environment Data in Spain to any developer in order that they can build their own applications.

Keywords: open data, R language, data integration, environmental data

Procedia PDF Downloads 300

Authors: Samira Akdader-Oudahmane, Assia Kamel, Lynda Lakabi, Michael Bruce Zimmermann, Zohra Hamouli-Said, Djamila Meskine

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Background: Iodine is a trace element whose adequate intakes are essential during pregnancy to promote the correct growth and development of the fetus. Iodine deficiency is the cause of several disorders in foetal development, and thyroid disorders during pregnancy are associated with an increased risk of miscarriage or premature birth. The aim of this study was to assess the iodine status and thyroid function of pregnant women (PW) in northern Algeria. Methods: Healthy PW were recruited from an urban area (Algiers). Spot urine and venous blood samples were collected to assess iodine status (urinary iodine concentration, UIC) and serum thyroid hormones (TSH, FT4), and anti-thyroid peroxidase antibodies (TPO-Ab) concentrations. Results: The median UIC for the PW (n=172) in Algiers was 246,74µg/L, 244,68 µg/L, and 220,63µg/L, respectively, during the first, second, and third trimesters of pregnancy. Mean TSH and FT4 concentrations were within reference ranges in all groups of women. Among PW, 72.7%, 75.4%, and 75.5% in the first, second and third trimester were TPO-Ab+. Among PW, 14%, 10%, and 10% in the first, second and third trimester, respectively, with TPO -Ab+ had subclinical hypothyroidism. An analysis of the variations in the levels of the serum parameters (FT4, TSH and anti-TPO antibodies) was analyzed according to the UIC intervals admitted and show that these marker are predictive of thyroid function. Conclusion: In northern Algeria, median UICs indicate iodine sufficiency in PW. About 75% of PW are TPO-Ab+ and the prevalence of subclinical hypothyroidism is high.

Keywords: thyroid, pregnant woman, urinary iodine, subclinical hypothyroidism

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Authors: Gebremeskel Hagos Gebremedhin, Feng Chong, Heyan Huang

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Software system is the combination of architecture and organized components to accomplish a specific function or set of functions. A good software architecture facilitates application system development, promotes achievement of functional requirements, and supports system reconfiguration. We describe three studies demonstrating the utility of our architecture in the subdomain of mobile office robots and identify software engineering principles embodied in the architecture. The main aim of this paper is to analyze prove architecture design and automatic re-architecting using machine learning. Intelligence software architecture and automatic re-architecting process is reorganizing in to more suitable one of the software organizational structure system using the user access dataset for creating relationship among the components of the system. The 3-step approach of data mining was used to analyze effective recovery, transformation and implantation with the use of clustering algorithm. Therefore, automatic re-architecting without changing the source code is possible to solve the software complexity problem and system software reuse.

Keywords: intelligence, software architecture, re-architecting, software reuse, High level design

Procedia PDF Downloads 104

Authors: Steven R. Lawyer, Tereza Prihodova, Katerina Prihodova

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Delay discounting (DD) is one of the most frequently used behavioral-economic measures of impulsive choice, but there are few cross-cultural comparisons of discounting, and to the best of our knowledge, none compare patterns of DD across different commodities or compare real and hypothetical rewards across cultures. The purpose of this study was to compare patterns of DD for both real and hypothetical money and cigarettes among participants in the USA and the Czech Republic. Adult smokers from the United States and the Czech Republic completed standard measures of DD for hypothetical and real money (~$10USD) and cigarettes (1 pack, or 20 cigarettes). Contrary to data from the USA sample, Czech Republic participants discounted the value of real money steeper than hypothetical money, though this could be related to the relatively poor fit of the hyperbolic decay function to DD for hypothetical money in the Czech sample. These findings suggest that there might be cultural differences in delay discounting that warrant further attention.

Keywords: delay discounting, temporal discounting, cigarette smoking, real rewards, hypothetical rewards

Procedia PDF Downloads 172

Authors: Ahmed Moustapha Mfokeu

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Agri-food VSEs in Cameroon are facing a succession of crises, lack of security, particularly in the Far North, South West, and North West regions, the consequences of the Covid 19 crisis, and the war in Ukraine . These multiple crises have benefited the reception of the prices of the raw materials. Moreover, the exacerbation of competitive pressures is driven by the technological acceleration of productive systems in emerging countries which increase the demands imposed on the markets. The Cameroonian VSE must therefore be able to meet the new challenges of international competition, especially through innovation. The objective of this research is to contribute to the knowledge of the effects of innovation on the performance of very small agribusinesses in Cameroon. On the methodological level, the data were provided from a sample of 153 companies in the cities of Douala and Yaoundé. This research uses structural equation models with latent variables. The main results show that there is a positive and significant link between innovation and the performance of very small agri-food companies, so if it is important for entrepreneurs to encourage and practice innovation, it is also necessary to make them understand and make them like this aspect in their strategic function.

Keywords: innovation, performance, very small enterprise, agrifood

Procedia PDF Downloads 90

Authors: Meera Tandan, Mohan Timilsina, Martin Cormican, Akke Vellinga

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Background: In general practice, many infections are treated empirically without microbiological confirmation. Understanding susceptibility of antimicrobials during empirical prescribing can be helpful to reduce inappropriate prescribing. This study aims to apply a prediction model using a decision tree approach to predict the antimicrobial resistance (AMR) of urinary tract infections (UTI) based on non-clinical features of patients over 65 years. Decision tree models are a novel idea to predict the outcome of AMR at an initial stage. Method: Data was extracted from the database of the microbiological laboratory of the University Hospitals Galway on all antimicrobial susceptibility testing (AST) of urine specimens from patients over the age of 65 from January 2011 to December 2014. The primary endpoint was resistance to common antimicrobials (Nitrofurantoin, trimethoprim, ciprofloxacin, co-amoxiclav and amoxicillin) used to treat UTI. A classification and regression tree (CART) model was generated with the outcome ‘resistant infection’. The importance of each predictor (the number of previous samples, age, gender, location (nursing home, hospital, community) and causative agent) on antimicrobial resistance was estimated. Sensitivity, specificity, negative predictive (NPV) and positive predictive (PPV) values were used to evaluate the performance of the model. Seventy-five percent (75%) of the data were used as a training set and validation of the model was performed with the remaining 25% of the dataset. Results: A total of 9805 UTI patients over 65 years had their urine sample submitted for AST at least once over the four years. E.coli, Klebsiella, Proteus species were the most commonly identified pathogens among the UTI patients without catheter whereas Sertia, Staphylococcus aureus; Enterobacter was common with the catheter. The validated CART model shows slight differences in the sensitivity, specificity, PPV and NPV in between the models with and without the causative organisms. The sensitivity, specificity, PPV and NPV for the model with non-clinical predictors was between 74% and 88% depending on the antimicrobial. Conclusion: The CART models developed using non-clinical predictors have good performance when predicting antimicrobial resistance. These models predict which antimicrobial may be the most appropriate based on non-clinical factors. Other CART models, prospective data collection and validation and an increasing number of non-clinical factors will improve model performance. The presented model provides an alternative approach to decision making on antimicrobial prescribing for UTIs in older patients.

Keywords: antimicrobial resistance, urinary tract infection, prediction, decision tree

Procedia PDF Downloads 243

Authors: Lu Si, Jie Yu, Shasha Li, Jun Ma, Lei Luo, Qingbo Wu, Yongqi Ma, Zhengji Liu

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Instance selection (IS) technique is used to reduce the data size to improve the performance of data mining methods. Recently, to process very large data set, several proposed methods divide the training set into some disjoint subsets and apply IS algorithms independently to each subset. In this paper, we analyze the limitation of these methods and give our viewpoint about how to divide and conquer in IS procedure. Then, based on fast condensed nearest neighbor (FCNN) rule, we propose a large data sets instance selection method with MapReduce framework. Besides ensuring the prediction accuracy and reduction rate, it has two desirable properties: First, it reduces the work load in the aggregation node; Second and most important, it produces the same result with the sequential version, which other parallel methods cannot achieve. We evaluate the performance of FCNN-MR on one small data set and two large data sets. The experimental results show that it is effective and practical.

Keywords: instance selection, data reduction, MapReduce, kNN

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Authors: Marcelo Araujo da Nóbrega, Ariel Moura Vilas Boas

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This study aims to characterize the physicochemical aspects of the soils of southeastern Chapada Diamantina - Bahia related to the phytophysiognomies of this area, rupestrian field, small savanna (savanna fields), small dense savanna (savanna fields), savanna (Cerrado), dry thorny forest (Caatinga), dry thorny forest/savanna, scrub (Carrasco - ecotone), forest island (seasonal semi-deciduous forest - Capão) and seasonal semi-deciduous forest. To achieve the research objective, soil samples were collected in each plant formation and analyzed in the soil laboratory of ESALQ - USP in order to identify soil fertility through the determination of pH, organic matter, phosphorus, potassium, calcium, magnesium, potential acidity, sum of bases, cation exchange capacity and base saturation. The composition of soil particles was also checked; that is, the texture, step made in the terrestrial ecosystems laboratory of the Department of Ecology of USP and in the soil laboratory of ESALQ. Another important factor also studied was to show the variations in the vegetation cover in the region as a function of soil moisture in the different existing physiographic environments. Another study carried out was a comparison between the average soil moisture data with precipitation data from three locations with very different phytophysiognomies. The soils found in this part of Bahia can be classified into 5 classes, with a predominance of oxisols. All of these classes have a great diversity of physical and chemical properties, as can be seen in photographs and in particle size and fertility analyzes. The deepest soils are located in the Central Pediplano of Chapada Diamantina where the dirty field, the clean field, the executioner and the semideciduous seasonal forest (Capão) are located, and the shallower soils were found in the rupestrian field, dry thorny forest, and savanna fields, the latter located on a hillside. As for the variations in water in the region's soil, the data indicate that there were large spatial variations in humidity in both the rainy and dry periods.

Keywords: Bahia, Brazil, chapada diamantina, phytophysiognomies, soils

Procedia PDF Downloads 127

Authors: Pi Hsia Liang

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The rise of Facebook, Twitter, and other social networks significantly changes in interconnections between people, enhancing the process of information dissemination and amplify the influence of that information. Therefore, to develop informational efficiency or signaling equilibrium type of information environment among social networks, without adverse selection effects, becomes an important issue. Thus, someone may post a piece of intentional information in relation to personal interest for trying to create marginal influence. Therefore, economists are seeking to establish theories of informational efficiency under social network environment in order to resolve adverse selection issues. Reputation could be one of the important factors in the process of creating informational efficiency. Additionally, investors how to process green information, or information of corporate social responsibility is a very important study. This study essentially employs experimental study for examining how investors use stock relevant green information in Facebook and various Taiwan local networks. Facebook, and blogs of Money DJ, Technews and cnYES, respectively, are the primary sites for this examination that also allow to differentiate effects between Facebook and other local social networks. Questionnaire is developed for such an experimental testing. Note that questionnaire allows this study to group, for example, decision frequency and length of time duration focusing on social networks that are used for discriminating investor type and competence of informed investor. This study selects 500 investors that can be separated into two respective 250 samples as the control group and 250 samples in such an experimental. The quantity of sample investor sufficiently results in statistic significance of this experimental study. The empirical results of this study can be used for explaining how financial information in relation to corporate social responsibility would be disseminated in social websites. Therefore, we can lead to better interpretation of price/earnings relationship type of study and empirical studies of green information usefulness or informational efficiency Note that the above mentioned empirical studies did not exist any social network and annual report of corporate social responsibility. This study expects to find the results that both network degree and network cluster significantly affected green information dissemination frequency. In other words, investors with more connections and with high clustered connections might exert a greater influence on their green information dissemination process. The preferred users of financial social networks could make better stock decision that could amplify effects of green information. In addition, Facebook would be more influential than other local Taiwan financial social networks, although Facebook is not a specialized financial social network. In other words, the popularity and reputation effects of Facebook significantly contribute to usefulness of green information and influence of green information. Third, it has a better chance to find rumor or cheating information in local Taiwan financial social networks than Facebook. In other words, Facebook possesses reputation effect, or a better informational efficiency. Or, even though Taiwan local financial social networks have marginal informational effects on stock price, because of shortage of informational efficiency or monitoring system, information could be a tool for those whom owning superior information.

Keywords: network effect on financial services, informational efficiency theory, social networks, social websites

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Authors: Laura N. Bolivar T.

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The tourism importance for regional development is mainly highlighted by the collaborative, cooperating and competitive relationships of the involved agents. The fostering of associativity processes, in particular, the cluster approach emphasizes the beneficial outcomes from the concentration of enterprises, where innovation and entrepreneurship flourish and shape the dynamics for tourism empowerment. Considering the department of Huila, it is located in the south-west of Colombia and holds the biggest coffee production in the country, although it barely contributes to the national GDP. Hence, its economic development strategy is looking for more dynamism and Huila could be consolidated as a leading destination for cultural, ecological and heritage tourism, if at least the public policy making processes for the tourism management of La Tatacoa Desert, San Agustin Park and Bambuco’s National Festival, were implemented in a more efficient manner. In this order of ideas, this study attempts to address the potential restrictions and beneficial factors for the consolidation of the tourism sector of Huila-Colombia as a cluster and how could it impact its regional development. Therefore, a set of theoretical frameworks such as the Tourism Routes Approach, the Tourism Breeding Environment, the Community-based Tourism Method, among others, but also a collection of international experiences describing tourism clustering processes and most outstanding problematics, is analyzed to draw up learning points, structure of proceedings and success-driven factors to be contrasted with the local characteristics in Huila, as the region under study. This characterization involves primary and secondary information collection methods and comprises the South American and Colombian context together with the identification of involved actors and their roles, main interactions among them, major tourism products and their infrastructure, the visitors’ perspective on the situation and a recap of the related needs and benefits regarding the host community. Considering the umbrella concepts, the theoretical and the empirical approaches, and their comparison with the local specificities of the tourism sector in Huila, an array of shortcomings is analytically constructed and a series of guidelines are proposed as a way to overcome them and simultaneously, raise economic development and positively impact Huila’s well-being. This non-exhaustive bundle of guidelines is focused on fostering cooperating linkages in the actors’ network, dealing with Information and Communication Technologies’ innovations, reinforcing the supporting infrastructure, promoting the destinations considering the less known places as well, designing an information system enabling the tourism network to assess the situation based on reliable data, increasing competitiveness, developing participative public policy-making processes and empowering the host community about the touristic richness. According to this, cluster dynamics would drive the tourism sector to meet articulation and joint effort, then involved agents and local particularities would be adequately assisted to cope with the current changing environment of globalization and competition.

Keywords: innovative strategy, local development, network of tourism actors, tourism cluster

Procedia PDF Downloads 129

Authors: Trevor Toy, Josef Langerman

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Around a quarter of the world’s data is generated by financial with an estimated 708.5 billion global non-cash transactions reached between 2018 and. And with Open Banking still a rapidly developing concept within the financial industry, there is an opportunity to create a secure mechanism for connecting its stakeholders to openly, legitimately and consensually share the data required to enable it. Integration and data sharing of anonymised transactional data are still operated in silos and centralised between the large corporate entities in the ecosystem that have the resources to do so. Smaller fintechs generating data and businesses looking to consume data are largely excluded from the process. Therefore there is a growing demand for accessible transactional data for analytical purposes and also to support the rapid global adoption of Open Banking. The following research has provided a solution framework that aims to provide a secure decentralised marketplace for 1.) data providers to list their transactional data, 2.) data consumers to find and access that data, and 3.) data subjects (the individuals making the transactions that generate the data) to manage and sell the data that relates to themselves. The platform also provides an integrated system for downstream transactional-related data from merchants, enriching the data product available to build a comprehensive view of a data subject’s spending habits. A robust and sustainable data market can be developed by providing a more accessible mechanism for data producers to monetise their data investments and encouraging data subjects to share their data through the same financial incentives. At the centre of the platform is the market mechanism that connects the data providers and their data subjects to the data consumers. This core component of the platform is developed on a decentralised blockchain contract with a market layer that manages transaction, user, pricing, payment, tagging, contract, control, and lineage features that pertain to the user interactions on the platform. One of the platform’s key features is enabling the participation and management of personal data by the individuals from whom the data is being generated. This framework developed a proof-of-concept on the Etheruem blockchain base where an individual can securely manage access to their own personal data and that individual’s identifiable relationship to the card-based transaction data provided by financial institutions. This gives data consumers access to a complete view of transactional spending behaviour in correlation to key demographic information. This platform solution can ultimately support the growth, prosperity, and development of economies, businesses, communities, and individuals by providing accessible and relevant transactional data for big data analytics and open banking.

Keywords: big data markets, open banking, blockchain, personal data management

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Authors: A. Bere, H. G. Sithuba, K. Kyei, C. Sigauke

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We employ a discrete logit survival model to investigate the risk factors for early alcohol intake among students at two tertiary institutions in Thohoyandou, South Africa. Data were collected from a sample of 744 students using a self-administered questionnaire. Significant covariates were arrived at through a regularization algorithm implemented using the glmmLasso package. The tuning parameter was determined using a five-fold cross-validation algorithm. The baseline hazard was modelled as a smooth function of time through the use of spline functions. The results show that the hazard of initial alcohol intake peaks at the age of about 16 years and that at any given time, being of a male gender, prior use of other drugs, having drinking peers, having experienced negative life events and physical abuse are associated with a higher risk of alcohol intake debut.

Keywords: cross-validation, discrete hazard model, LASSO, smooth baseline hazard

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Authors: K. Julia Rose Mary, Victor Arokia Doss

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Electrical and chemical stimulations up-regulate phosphorylaion of CREB, a transcriptional factor that induces its target gene production for memory consolidation and Late Long-Term Potentiation (L-LTP) in CA1 region of the hippocampus. L-LTP requires complex interactions among second-messenger signaling cascade molecules such as cAMP, CAMKII, CAMKIV, MAPK, RSK, PKA, all of which converge to phosphorylate CREB which along with CBP induces the transcription of target genes involved in memory consolidation. A differential equation based model for L-LTP representing stimulus-mediated activation of downstream mediators which confirms the steep, supralinear stimulus-response effects of activation and inhibition was used. The same was extended to accommodate the inhibitory effect of the Inducible cAMP Early Repressor (ICER). ICER is the natural inducible CREB antagonist represses CRE-Mediated gene transcription involved in long-term plasticity for learning and memory. After verifying the sensitivity and robustness of the model, we had simulated it with various empirical levels of repressor concentration to analyse their effect on the gene induction. The model appears to predict the regulatory dynamics of repression on the L-LTP and agrees with the experimental values. The flux data obtained in the simulations demonstrate various aspects of equilibrium between the gene induction and repression.

Keywords: CREB, L-LTP, mathematical modeling, simulation

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Authors: Shameka Stanford

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This presentation will discuss how cognitive and communication disorders in the areas of executive functioning, receptive and expressive language can impact the problem-solving and decision making of individuals with such impairments. More specifically, this presentation will discuss approaches the legal defense team of capital case lawyers can add to their experience when servicing individuals who have a history of educational decline, special education, and limited intervention and treatment. The objective of the research is to explore and identify the correlations between impaired executive function skills and decision making and competency for individuals facing death penalty charges. To conduct this research, experimental design, randomized sampling, qualitative analysis was employed. This research contributes to the legal and criminal justice system related to how they view, defend, and characterize, and judge individuals with documented cognitive and communication disorders who are eligible for capital case charges. More importantly, this research contributes to the increased ability of death penalty lawyers to successfully defend clients with a history of academic difficulty, special education, and documented disorders that impact educational progress and academic success.

Keywords: cognitive impairments, communication disorders, death penalty, executive function

Procedia PDF Downloads 142

Authors: Hassan Karimi, Fred Piercy, Ruoxi Chen, Ana L. Jaramillo-Sierra, Wei-Ning Chang, Manjushree Palit, Catherine Martosudarmo, Angelito Antonio

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Background: The two psychotherapy camps, the randomized clinical trials (RCTs) and the common factors model, have competitively claimed specific explanations for therapy effectiveness. Recently, scholars called for empirical evidence to show the role of common factors in therapeutic outcome in marriage and family therapy. Purpose: This cross-national study aims to explore how clinicians, across different nations and theoretical orientations, attribute the contribution of common factors to therapy outcome. Method: A brief common factors questionnaire (CFQ-with a Cronbach’s Alpha, 0.77) was developed and administered in seven nations. A series of statistical analyses (paired-samples t-test, independent sample t-test, ANOVA) were conducted: to compare clinicians perceived contribution of total common factors versus model-specific factors, to compare each pair of common factors’ categories, and to compare clinicians from collectivistic nations versus clinicians from individualistic nation. Results: Clinicians across seven nations attributed 86% to common factors versus 14% to model-specific factors. Clinicians attributed 34% of therapeutic change to client’s factors, 26% to therapist’s factors, 26% to relationship factors, and 14% to model-specific techniques. The ANOVA test indicated each of the three categories of common factors (client 34%, therapist 26%, relationship 26%) showed higher contribution in therapeutic outcome than the category of model specific factors (techniques 14%). Clinicians with psychology degree attributed more contribution to model-specific factors than clinicians with MFT and counseling degrees who attributed more contribution to client factors. Clinicians from collectivistic nations attributed larger contributions to therapist’s factors (M=28.96, SD=12.75) than the US clinicians (M=23.22, SD=7.73). The US clinicians attributed a larger contribution to client’s factors (M=39.02, SD=1504) than clinicians from the collectivistic nations (M=28.71, SD=15.74). Conclusion: The findings indicate clinicians across the globe attributed more than two thirds of therapeutic change to CFs, which emphasize the training of the common factors model in the field. CFs, like model-specific factors, vary in their contribution to therapy outcome in relation to specific client, therapist, problem, treatment model, and sociocultural context. Sociocultural expectations and norms should be considered as a context in which both CFs and model-specific factors function toward therapeutic goals. Clinicians need to foster a cultural competency specifically regarding the divergent ways that CFs can be activated due to specific sociocultural values.

Keywords: common factors, model-specific factors, cross-national survey, therapist cultural competency, enhancing therapist efficacy

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Authors: Dmitriy Kuptsov

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Tree data structures, such as binary or in general k-ary trees, are essential in computer science. The applications of these data structures can range from data search and retrieval to sorting and ranking algorithms. Naive implementations of these data structures can consume prohibitively large volumes of random access memory limiting their applicability in certain solutions. Thus, in these cases, more advanced representation of these data structures is essential. In this paper we present the design of the compact version of ternary tree data structure and demonstrate the results for the experimental evaluation using static dictionary problem. We compare these results with the results for binary and regular ternary trees. The conducted evaluation study shows that our design, in the best case, consumes up to 12 times less memory (for the dictionary used in our experimental evaluation) than a regular ternary tree and in certain configuration shows performance comparable to regular ternary trees. We have evaluated the performance of the algorithms using both 32 and 64 bit operating systems.

Keywords: algorithms, data structures, succinct ternary tree, per- formance evaluation

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Authors: Kamal Ray, Tapati Bhattacharya

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Private use of public office for private gain could be a tentative definition of corruption and most distasteful event of corruption is that it is not there, nor that it is pervasive, but it is socially acknowledged in the global economy, especially in the developing nations. We attempted to assess the interrelationship between the Corruption perception index (CPI) and the principal components of governance indicators as per World Bank like Control of Corruption (CC), rule of law (RL), regulatory quality (RQ) and government effectiveness (GE). Our empirical investigation concentrates upon the degree of reflection of governance indicators upon the CPI in order to single out the most powerful corruption-generating indicator in the selected countries. We have collected time series data on above governance indicators such as CC, RL, RQ and GE of the selected eleven countries from the year of 1996 to 2012 from World Bank data set. The countries are USA, UK, France, Germany, Greece, China, India, Japan, Thailand, Brazil, and South Africa. Corruption Perception Index (CPI) of the countries mentioned above for the period of 1996 to 2012is also collected. Graphical method of simple line diagram against the time series data on CPI is applied for quick view for the relative positions of different trend lines of different nations. The correlation coefficient is enough to assess primarily the degree and direction of association between the variables as we get the numerical data on governance indicators of the selected countries. The tool of Granger Causality Test (1969) is taken into account for investigating causal relationships between the variables, cause and effect to speak of. We do not need to verify stationary test as length of time series is short. Linear regression is taken as a tool for quantification of a change in explained variables due to change in explanatory variable in respect of governance vis a vis corruption. A bilateral positive causal link between CPI and CC is noticed in UK, index-value of CC increases by 1.59 units as CPI increases by one unit and CPI rises by 0.39 units as CC rises by one unit, and hence it has a multiplier effect so far as reduction in corruption is concerned in UK. GE causes strongly to the reduction of corruption in UK. In France, RQ is observed to be a most powerful indicator in reducing corruption whereas it is second most powerful indicator after GE in reducing of corruption in Japan. Governance-indicator like GE plays an important role to push down the corruption in Japan. In China and India, GE is proactive as well as influencing indicator to curb corruption. The inverse relationship between RL and CPI in Thailand indicates that ongoing machineries related to RL is not complementary to the reduction of corruption. The state machineries of CC in S. Africa are highly relevant to reduce the volume of corruption. In Greece, the variations of CPI positively influence the variations of CC and the indicator like GE is effective in controlling corruption as reflected by CPI. All the governance-indicators selected so far have failed to arrest their state level corruptions in USA, Germany and Brazil.

Keywords: corruption perception index, governance indicators, granger causality test, regression

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Authors: Khulud Alhussain, Anna Gavine, Stephen Macgillivray, Sushila Chowdhry

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Background: Estimates show that by the year 2030, mental illness will account for more than half of the global economic burden, second to non-communicable diseases. Often, the perinatal period is characterised by psychological ambivalence and a mixed anxiety-depressive condition. Maternal mental disorder is associated with perinatal anxiety and depression and affects breastfeeding behaviors. Studies also indicate that maternal mental health can considerably influence a baby's health in numerous aspects and impact the newborn health due to lack of adequate breastfeeding. However, studies reporting factors associated with breastfeeding behaviors are predominantly quantitative. Therefore, it is not clear what literature is available to understand the factors affecting breastfeeding and perinatal women’s perspectives and experiences. Aim: This review aimed to explore the perceptions and experiences of women with perinatal anxiety and depression, as well as how these experiences influence their breastfeeding behaviours. Methods: A systematic literature review of qualitative studies in line with the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ). Four electronic databases (CINAHL, PsycINFO, Embase, and Google Scholar) were explored for relevant studies using a search strategy. The search was restricted to studies published in the English language between 2000 and 2022. Findings from the literature were screened using a pre-defined screening criterion and the quality of eligible studies was appraised using the Walsh and Downe (2006) checklist. Findings were extracted and synthesised based on Braun and Clark. The review protocol was registered on PROSPERO (Ref: CRD42022319609). Result: A total of 4947 studies were identified from the four databases. Following duplicate removal and screening 16 studies met the inclusion criteria. The studies included 87 pregnant and 302 post-partum women from 12 countries. The participants were from a variety of economic, regional, and religious backgrounds, mainly from the age of 18 to 45 years old. Three main themes were identified: Barriers to breastfeeding, breastfeeding facilitators, emotional disturbance, and breastfeeding. Seven subthemes emerged from the data: expectation versus reality, uncertainly about maternal competencies, body image and breastfeeding, lack of sufficient breastfeeding support for family and caregivers’ support, influences positive breastfeeding practices, breastfeeding education, and causes of mental strain among breastfeeding women. Breastfeeding duration is affected in women with mental health disorders, irrespective of their desire to breastfeed. Conclusion: There is significant empirical evidence that breastfeeding behaviour and perinatal mental disturbance are linked. However, there is a lack of evidence to apply the findings to Saudi women due to lack of empirical qualitative information. To improve the psychological well-being of mothers, it is crucial to explore and recognise any concerns with their mental, physical, and emotional well-being. Therefore, robust research is needed so that breastfeeding intervention researchers and policymakers can focus on specifically what needs to be done to help mentally distressed perinatal women and their new-born.

Keywords: pregnancy, perinatal period, anxiety, depression, emotional disturbance, breastfeeding

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Authors: Aleksandra Aleksandrovna Filimonova, Lev Sergeevich Kazarinov, Tatyana Aleksandrovna Barbasova

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A method of effective planning and control of industrial facility energy consumption is offered. The method allows to optimally arrange the management and full control of complex production facilities in accordance with the criteria of minimal technical and economic losses at the forecasting control. The method is based on the optimal construction of the power efficiency characteristics with the prescribed accuracy. The problem of optimal designing of the forecasting model is solved on the basis of three criteria: maximizing the weighted sum of the points of forecasting with the prescribed accuracy; the solving of the problem by the standard principles at the incomplete statistic data on the basis of minimization of the regularized function; minimizing the technical and economic losses due to the forecasting errors.

Keywords: energy consumption, energy efficiency, energy management system, forecasting model, power efficiency characteristics

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Authors: Ahmed I. Alutabi, Naghmeh Dezhabad, Sudhakar Ganti

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Data centers have been growing in size and dema nd continuously in the last two decades. Planning for the deployment of resources has been shallow and always resorted to over-provisioning. Data center operators try to maximize the availability of their services by allocating multiple of the needed resources. One resource that has been wasted, with little thought, has been energy. In recent years, programmable resource allocation has paved the way to allow for more efficient and robust data centers. In this work, we examine the predictability of resource usage in a data center environment. We use a number of models that cover a wide spectrum of machine learning categories. Then we establish a framework to guarantee the client service level agreement (SLA). Our results show that using prediction can cut energy loss by up to 55%.

Keywords: machine learning, artificial intelligence, prediction, data center, resource allocation, green computing

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Authors: N. K. Chougule, G. V. Parishwad

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The pin fin heat sink is a novel heat transfer device to transfer large amount of heat through with very small temperature differences and it also possesses large uniform cooling characteristics. Pin fins are widely used as elements that provide increased cooling for electronic devices. Increasing demands regarding the performance of such devices can be observed due to the increasing heat production density of electronic components. For this reason, extensive work is being carried out to select and optimize pin fin elements for increased heat transfer. In this paper, the effects of design parameters and the optimum design parameters for a Pin-Fin heat sink (PFHS) under multi-jet impingement case with thermal performance characteristics have been investigated by using Taguchi methodology based on the L9 orthogonal arrays. Various design parameters, such as pin-fin array size, gap between nozzle exit to impingement target surface (Z/d) and air velocity are explored by numerical experiment. The average convective heat transfer coefficient is considered as the thermal performance characteristics. The analysis of variance (ANOVA) is applied to find the effect of each design parameter on the thermal performance characteristics. Then the results of confirmation test with the optimal level constitution of design parameters have obviously shown that this logic approach can effective in optimizing the PFHS with the thermal performance characteristics. The analysis of the Taguchi method reveals that, all the parameters mentioned above have equal contributions in the performance of heat sink efficiency. Experimental results are provided to validate the suitability of the proposed approach.

Keywords: Pin Fin Heat Sink (PFHS), Taguchi method, CFD, thermal performance

Procedia PDF Downloads 237