Search results for: spatial and temporal data

Authors: Francisco M. Silva

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Technology is evolving, creating an impact on our everyday lives and the telehealth industry. Telehealth encapsulates the provision of healthcare services and information via a technological approach. There are several benefits of using web-based methods to provide healthcare help. Nonetheless, few health and psychological help approaches combine this method with wearable sensors. This paper aims to create an online platform for users to receive self-care help and information using wearable sensors. In addition, researchers developing a similar project obtain a solid foundation as a reference. This study provides descriptions and analyses of the software and hardware architecture. Exhibits and explains a heart rate dynamic and efficient algorithm that continuously calculates the desired sensors' values. Presents diagrams that illustrate the website deployment process and the webserver means of handling the sensors' data. The goal is to create a working project using Arduino compatible hardware. Heart rate sensors send their data values to an online platform. A microcontroller board uses an algorithm to calculate the sensor heart rate values and outputs it to a web server. The platform visualizes the sensor's data, summarizes it in a report, and creates alerts for the user. Results showed a solid project structure and communication from the hardware and software. The web server displays the conveyed heart rate sensor's data on the online platform, presenting observations and evaluations.

Keywords: Arduino, heart rate BPM, microcontroller board, telehealth, wearable sensors, web-based healthcare

Procedia PDF Downloads 126

Authors: Runglaksamee Rodkam

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The purpose of this research was to study the influence of accountants’ potential performance on their working process, a case study of Government Savings Banks in the northeast of Thailand. The independent variables included accounting knowledge, accounting skill, accounting value, accounting ethics, and accounting attitude, while the dependent variable included the success of the working process. A total of 155 accountants working for Government Savings Banks were selected by random sampling. A questionnaire was used as a tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analyses. The findings revealed that the majority of accountants were female with an age between 35-40 years old. Most of the respondents had an undergraduate degree with ten years of experience. Moreover, the factors of accounting knowledge, accounting skill, accounting a value and accounting ethics and accounting attitude were rated at a high level. The findings from regression analysis of observation data revealed a causal relationship in that the observation data could explain at least 51 percent of the success in the accountants’ working process.

Keywords: influence, potential performance, success, working process

Procedia PDF Downloads 256

Authors: Ahmed El-Banbi, Ahmed El-Maraghi

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PVT properties are needed as input data in all reservoir, production, and surface facilities engineering calculations. In the absence of PVT reports on valid reservoir fluid samples, engineers rely on PVT correlations to generate the required PVT data. The accuracy of PVT correlations varies, and no correlation group has been found to provide accurate results for all oil types. The effect of inaccurate PVT data can be significant in engineering calculations and is well documented in the literature. Bubble point pressure can sometimes be obtained from external sources. In this paper, we show how to utilize the known bubble point pressure to improve the accuracy of calculated PVT properties from correlations. We conducted a systematic study using around 250 reservoir oil samples to quantify the effect of pre-knowledge of bubble point pressure. The samples spanned a wide range of oils, from very volatile oils to black oils and all the way to low-GOR oils. A method for shifting both undersaturated and saturated sections of the PVT properties curves to the correct bubble point is explained. Seven PVT correlation families were used in this study. All PVT properties (e.g., solution gas-oil ratio, formation volume factor, density, viscosity, and compressibility) were calculated using the correct bubble point pressure and the correlation estimated bubble point pressure. Comparisons between the calculated PVT properties and actual laboratory-measured values were made. It was found that pre-knowledge of bubble point pressure and using the shifting technique presented in the paper improved the correlation-estimated values by 10% to more than 30%. The most improvement was seen in the solution gas-oil ratio and formation volume factor.

Keywords: PVT data, PVT properties, PVT correlations, bubble point pressure

Procedia PDF Downloads 63

Authors: Hlaing Zaw Oo, N. Kostromina, V. Osipchik, T. Kravchenko, K. Yakovleva

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The process of modification of ed-20 epoxy resin synthesized by vinyl-containing compounds is considered. It is shown that the introduction of vinyl-containing compounds into the composition based on epoxy resin ED-20 allows adjusting the technological and operational characteristics of the binder. For improvement of the properties of epoxy resin, following modifiers were selected: polyvinylformalethyl, polyvinyl butyral and composition of linear and aromatic amines (Аramine) as a hardener. Now the big range of hardeners of epoxy resins exists that allows varying technological properties of compositions, and also thermophysical and strength indicators. The nature of the aramin type hardener has a significant impact on the spatial parameters of the mesh, glass transition temperature, and strength characteristics. Epoxy composite materials based on ED-20 modified with polyvinyl butyral were obtained and investigated. It is shown that the composition of resins based on derivatives of polyvinyl butyral and ED-20 allows obtaining composite materials with a higher complex of deformation-strength, adhesion and thermal properties, better water resistance, frost resistance, chemical resistance, and impact strength. The magnitude of the effect depends on the chemical structure, temperature and curing time. In the area of concentrations, where the effect of composite synergy is appearing, the values of strength and stiffness significantly exceed the similar parameters of the individual components of the mixture. The polymer-polymer compositions form their class of materials with diverse specific properties that ensure their competitive application. Coatings with high performance under cyclic loading have been obtained based on epoxy oligomers modified with vinyl-containing compounds.

Keywords: epoxy resins, modification, vinyl-containing compounds, deformation, strength properties

Procedia PDF Downloads 112

Authors: Khlood F. Salman, Richard Zoucha, Hani Nawafleh

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Introduction: Jordan ranks the fourth highest breast cancer prevalence after Lebanon, Bahrain, and Kuwait. Considerable evidence showed that cultural, ethnic, and economic differences influence a woman’s practice to early detection and prevention of breast cancer. Objectives: To understand women’s health beliefs and values in relation to early detection of breast cancer; and to explore the impact of these beliefs on their decisions regarding reluctance or acceptance of early detection measures such as mammogram screening. Design: A qualitative focused ethnography was used to collect data for this study. Settings: The study was conducted in the second largest city surrounded by a large rural area in Ma’an- Jordan. Participants: A total of twenty seven women, with no history of breast cancer, between the ages of 18 and older, who had prior health experience with health providers, and were willing to share elements of personal health beliefs related to breast health within the larger cultural context. The participants were recruited using the snowball method and words of mouth. Data collection and analysis: A short questionnaire was designed to collect data related to socio demographic status (SDQ) from all participants. A Semi-structured interviews guide was used to elicit data through interviews with the informants. Nvivo10 a data manager was utilized to assist with data analysis. Leininger’s four phases of qualitative data analysis was used as a guide for the data analysis. The phases used to analyze the data included: 1) Collecting and documenting raw data, 2) Identifying of descriptors and categories according to the domains of inquiry and research questions. Emic and etic data is coded for similarities and differences, 3) Identifying patterns and contextual analysis, discover saturation of ideas and recurrent patterns, and 4) Identifying themes and theoretical formulations and recommendations. Findings: Three major themes were emerged within the cultural and religious context; 1. Fear, denial, embarrassment and lack of knowledge were common perceptions of Ma’anis’ women regarding breast health and screening mammography, 2. Health care professionals in Jordan were not quick to offer information and education about breast cancer and screening, and 3. Willingness to learn about breast health and cancer prevention. Conclusion: The study indicated the disparities between the infrastructure and resourcing in rural and urban areas of Jordan, knowledge deficit related to breast cancer, and lack of education about breast health may impact women’s decision to go for a mammogram screening. Cultural beliefs, fear, embarrassments as well as providers lack of focus on breast health were significant contributors against practicing breast health. Health providers and policy makers should provide resources for the establishment health education programs regarding breast cancer early detection and mammography screening. Nurses should play a major role in delivering health education about breast health in general and breast cancer in particular. A culturally appropriate health awareness messages can be used in creating educational programs which can be employed at the national levels.

Keywords: breast health, beliefs, cultural context, ethnography, mammogram screening

Procedia PDF Downloads 298

Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

Procedia PDF Downloads 380

Authors: Vishwa Joshi

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The study of mood recognition in the field of music has gained a lot of momentum in the recent years with machine learning and data mining techniques and many audio features contributing considerably to analyze and identify the relation of mood plus music. In this paper we consider the same idea forward and come up with making an effort to build a system for automatic recognition of mood underlying the audio song’s clips by mining their audio features and have evaluated several data classification algorithms in order to learn, train and test the model describing the moods of these audio songs and developed an open source framework. Before classification, Preprocessing and Feature Extraction phase is necessary for removing noise and gathering features respectively.

Keywords: music, mood, features, classification

Procedia PDF Downloads 500

Authors: Soha A. Bahanshal, Vaibhav Verdhan, Bayong Kim

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Graduation rates at six-year colleges are becoming a more essential indicator for incoming fresh students and for university rankings. Predicting student graduation is extremely beneficial to schools and has a huge potential for targeted intervention. It is important for educational institutions since it enables the development of strategic plans that will assist or improve students' performance in achieving their degrees on time (GOT). A first step and a helping hand in extracting useful information from these data and gaining insights into the prediction of students' progress and performance is offered by machine learning techniques. Data analysis and visualization techniques are applied to understand and interpret the data. The data used for the analysis contains students who have graduated in 6 years in the academic year 2017-2018 for science majors. This analysis can be used to predict the graduation of students in the next academic year. Different Predictive modelings such as logistic regression, decision trees, support vector machines, Random Forest, Naïve Bayes, and KNeighborsClassifier are applied to predict whether a student will graduate. These classifiers were evaluated with k folds of 5. The performance of these classifiers was compared based on accuracy measurement. The results indicated that Ensemble Classifier achieves better accuracy, about 91.12%. This GOT prediction model would hopefully be useful to university administration and academics in developing measures for assisting and boosting students' academic performance and ensuring they graduate on time.

Keywords: prediction, decision trees, machine learning, support vector machine, ensemble model, student graduation, GOT graduate on time

Procedia PDF Downloads 73

Authors: Naila Nasreen, Dianchen Lu

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This paper explores the dynamical behavior of the (2+1)-dimensional Boussinesq equation, which is a nonlinear water wave equation and is used to model wave packets in dispersive media with weak nonlinearity. This equation depicts how long wave made in shallow water propagates due to the influence of gravity. The (2+1)- dimensional Boussinesq equation combines the two-way propagation of the classical Boussinesq equation with the dependence on a second spatial variable, as that occurs in the two-dimensional Kadomstev- Petviashvili equation. This equation provides a description of head- on collision of oblique waves and it possesses some interesting properties. The governing model is discussed by the assistance of Ricatti equation mapping method, a relatively integration tool. The solutions have been extracted in different forms the solitary wave solutions as well as hyperbolic and periodic solutions. Moreover, the sensitivity analysis is demonstrated for the designed dynamical structural system’s wave profiles, where the soliton wave velocity and wave number parameters regulate the water wave singularity. In addition to being helpful for elucidating nonlinear partial differential equations, the method in use gives previously extracted solutions and extracts fresh exact solutions. Assuming the right values for the parameters, various graph in different shapes are sketched to provide information about the visual format of the earned results. This paper’s findings support the efficacy of the approach taken in enhancing nonlinear dynamical behavior. We believe this research will be of interest to a wide variety of engineers that work with engineering models. Findings show the effectiveness simplicity, and generalizability of the chosen computational approach, even when applied to complicated systems in a variety of fields, especially in ocean engineering.

Keywords: (2+1)-dimensional Boussinesq equation, solitary wave solutions, Ricatti equation mapping approach, nonlinear phenomena

Procedia PDF Downloads 101

Authors: Syed Basit Ali Shah Bukhari, Yan Qiang, Saad Abdul Rauf, Syed Saqlaina Bukhari

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Text Classification is the methodology to classify any given text into the respective category from a given set of categories. It is highly important and vital to use proper set of pre-processing , feature selection and classification techniques to achieve this purpose. In this paper we have used different ensemble techniques along with variance in feature selection parameters to see the change in overall accuracy of the result and also on some other individual class based features which include precision value of each individual category of the text. After subjecting our data through pre-processing and feature selection techniques , different individual classifiers were tested first and after that classifiers were combined to form ensembles to increase their accuracy. Later we also studied the impact of decreasing the classification categories on over all accuracy of data. Text classification is highly used in sentiment analysis on social media sites such as twitter for realizing people’s opinions about any cause or it is also used to analyze customer’s reviews about certain products or services. Opinion mining is a vital task in data mining and text categorization is a back-bone to opinion mining.

Keywords: Natural Language Processing, Ensemble Classifier, Bagging Classifier, AdaBoost

Procedia PDF Downloads 232

Authors: Zahra Amirhosseini, Mahtab Nameni

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The aim of this study was to investigate the relationship between growth, beta, and Company's cash. We calculate cash as dependent variable and growth opportunity and beta as independent variables. This study was based on an analysis of panel data. Population of the study is the companies which listed in Tehran Stock exchange and a financial data of 215 companies during the period 2010 to 2015 have been selected as the sample through systematic sampling. The results of the first hypothesis showed there is a significant relationship between growth opportunities cash holdings. Also according to the analysis done in the second hypothesis, we determined that there is an inverse relation between company risk and cash holdings.

Keywords: growth, beta, liquidity, company

Procedia PDF Downloads 395

Authors: Diana Codat

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Tweets' analysis is part of text mining. Each document is a written text. It's possible to apply the usual text search techniques, in particular by switching to the bag-of-words representation. But the tweets induce peculiarities. Some may enrich the analysis. Thus, their length is calibrated (at least as far as public messages are concerned), special characters make it possible to identify authors (@) and themes (#), the tweet and retweet mechanisms make it possible to follow the diffusion of the information. Conversely, other characteristics may disrupt the analyzes. Because space is limited, authors often use abbreviations, emoticons to express feelings, and they do not pay much attention to spelling. All this creates noise that can complicate the task. The tweets carry a lot of potentially interesting information. Their exploitation is one of the main axes of the analysis of the social networks. We show how to access Twitter-related messages. We will initiate a study of the properties of the tweets, and we will follow up on the exploitation of the content of the messages. We will work under R with the package 'twitteR'. The study of tweets is a strong focus of analysis of social networks because Twitter has become an important vector of communication. This example shows that it is easy to initiate an analysis from data extracted directly online. The data preparation phase is of great importance.

Keywords: data mining, language R, social networks, Twitter

Procedia PDF Downloads 184

Authors: Fu-Pei Hsiao, Fung-Chung Tu, Chien-Kuo Chiu

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In this work, to develop a method for detailed assesses of post-earthquake seismic performance for RC buildings in Taiwan, experimental data for several column specimens with various failure modes (flexural failure, flexural-shear failure, and shear failure) are used to derive reduction factors of seismic capacity for specified damage states. According to the damage states of RC columns and their corresponding seismic reduction factors suggested by experimental data, this work applies the detailed seismic performance assessment method to identify the seismic capacity of earthquake-damaged RC buildings. Additionally, a post-earthquake emergent assessment procedure is proposed that can provide the data needed for decision about earthquake-damaged buildings in a region with high seismic hazard. Finally, three actual earthquake-damaged school buildings in Taiwan are used as a case study to demonstrate application of the proposed assessment method.

Keywords: seismic assessment, seismic reduction factor, residual seismic ratio, post-earthquake, reinforced concrete, building

Procedia PDF Downloads 400

Authors: Basiliyos Tilahun Betru, Charles Awono Onana, Bernabe Batchakui

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Recommender systems have become increasingly popular in recent years, and are utilized in numerous areas. Nowadays many web services provide several information for users and recommender systems have been developed as critical element of these web applications to predict choice of preference and provide significant recommendations. With the help of the advantage of deep learning in modeling different types of data and due to the dynamic change of user preference, building a deep model can better understand users demand and further improve quality of recommendation. In this paper, deep neural network models for recommender system are evaluated. Most of deep neural network models in recommender system focus on the classical collaborative filtering user-item setting. Deep learning models demonstrated high level features of complex data can be learned instead of using metadata which can significantly improve accuracy of recommendation. Even though deep learning poses a great impact in various areas, applying the model to a recommender system have not been fully exploited and still a lot of improvements can be done both in collaborative and content-based approach while considering different contextual factors.

Keywords: big data, decision making, deep learning, recommender system

Procedia PDF Downloads 479

Authors: Nirupama Sam

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COVID-19, the greatest pandemic since the turn of the century, presents several issues for urban planners, the most significant of which is determining appropriate mitigation techniques for creating pandemic-friendly and resilient public spaces. The study is conducted in four stages. The first stage consisted of literature reviews to examine the evolution and transformation of public spaces during pandemics throughout history and the role of public spaces during pandemic outbreaks. The second stage is to determine the factors that influence the success of public spaces, which was accomplished by an analysis of current literature and case studies. The influencing factors are categorized under comfort and images, uses and activity, access and linkages, and sociability. The third stage is to establish the priority of identified factors for which a questionnaire survey of stakeholders is conducted and analyzing of certain factors with the help of GIS tools. COVID-19 has been in effect in India for the last two years. Kerala has the highest daily COVID-19 prevalence due to its high population density, making it more susceptible to viral outbreaks. Despite all preventive measures taken against COVID-19, Kerala remains the worst-affected state in the country. Finally, two live case studies of the hardest-hit localities, namely Subhash bose park and Napier Museum park in the Ernakulam and Trivandrum districts of Kerala, respectively, were chosen as study areas for the survey. The responses to the questionnaire were analyzed using SPSS for determining the weights of the influencing factors. The spatial success of the selected case studies was examined using the GIS interpolation model. Following the overall assessment, the fourth stage is to develop strategies and guidelines for planning public spaces to make them more efficient and robust, which further leads to improved quality, safety and resilience to future pandemics.

Keywords: urban design, public space, covid-19, post-pandemic, public spaces

Procedia PDF Downloads 137

Authors: R. Venkatesan, A. Sabari

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Developments of social networking internet scenario are recommended for the requirements of scalable, authentic, secure group communication model like multicasting. Multicasting is an inter network service that offers efficient delivery of data from a source to multiple destinations. Even though multicast has been very successful at providing an efficient and best-effort data delivery service for huge groups, it verified complex process to expand other features to multicast in a scalable way. Separately, the requirement for secure electronic information had become gradually more apparent. Since multicast applications are deployed for mainstream purpose the need to secure multicast communications will become significant.

Keywords: multicasting, scalability, security, social network

Procedia PDF Downloads 292

Authors: Rusnardi Rahmat Putra, Junji Kiyono, Aiko Furukawa

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Several powerful earthquakes have struck Padang during recent years, one of the largest of which was an M 7.6 event that occurred on September 30, 2009 and caused more than 1000 casualties. Following the event, we conducted a 12-site microtremor array investigation to gain a representative determination of the soil condition of subsurface structures in Padang. From the dispersion curve of array observations, the central business district of Padang corresponds to relatively soft soil condition with Vs30 less than 400 m/s. because only one accelerometer existed, we simulated the 2009 Padang earthquake to obtain peak ground acceleration for all sites in Padang city. By considering the damage data of the 2009 Padang earthquake, we produced seismic risk vulnerability estimation of non-engineered houses for rock, medium and soft soil condition. We estimated the loss ratio based on the ground response, seismic hazard of Padang and the existing damaged to non-engineered structure houses due to Padang earthquake in 2009 data for several return periods of earthquake events.

Keywords: profile, Padang earthquake, microtremor array, seismic vulnerability

Procedia PDF Downloads 410

Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

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Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

Procedia PDF Downloads 131

Authors: Kumar Sambhav Pandey, Anamika Singh

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The continuous researches in the field of computer architecture basically aims at accelerating the computational speed and to gain enhanced performance. In this era, the superscalar, sub-scalar concept has not gained enough attention for improving the computation performance. In this paper, we have presented a sub-scalar approach to utilize the parallelism present with in the data while processing. The main idea is to split the data into individual smaller entities and these entities are processed with a defined known set of instructions. This sub-scalar approach to the MIPS architecture can bring out significant improvement in the computational speedup. MIPS-I is the basic design taken in consideration for the development of sub-scalar MIPS64 for increasing the instruction level parallelism (ILP) and resource utilization.

Keywords: dataword, MIPS, processor, sub-scalar

Procedia PDF Downloads 545

Authors: Hernando Santamaría-García, Sandra Báez, Pablo Reyes, José Santamaría-García, Diana Matallana, Adolfo García, Agustín Ibañez

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The study of moral emotions (i.e., Schadenfreude and envy) is critical to understand the ecological complexity of everyday interactions between cognitive, affective, and social cognition processes. Most previous studies in this area have used correlational imaging techniques and framed Schadenfreude and envy as monolithic domains. Here, we profit from a relevant neurodegeneration model to disentangle the brain regions engaged in three dimensions of Schadenfreude and envy: deservingness, morality, and legality. We tested 20 patients with behavioral variant frontotemporal dementia (bvFTD), 24 patients with Alzheimer’s disease (AD), as a contrastive neurodegeneration model, and 20 healthy controls on a novel task highlighting each of these dimensions in scenarios eliciting Schadenfreude and envy. Compared with the AD and control groups, bvFTD patients obtained significantly higher scores on all dimensions for both emotions. Interestingly, the legal dimension for both envy and Schadenfreude elicited higher emotional scores than the deservingness and moral dimensions. Furthermore, correlational analyses in bvFTD showed that higher envy and Schadenfreude scores were associated with greater deficits in social cognition, inhibitory control, and behavior. Brain anatomy findings (restricted to bvFTD and controls) confirmed differences in how these groups process each dimension. Schadenfreude was associated with the ventral striatum in all subjects. Also, in bvFTD patients, increased Schadenfreude across dimensions was negatively correlated with regions supporting social-value rewards, mentalizing, and social cognition (frontal pole, temporal pole, angular gyrus and precuneus). In all subjects, all dimensions of envy positively correlated with the volume of the anterior cingulate cortex, a region involved in processing unfair social comparisons. By contrast, in bvFTD patients, the intensified experience of envy across all dimensions was negatively correlated with a set of areas subserving social cognition, including the prefrontal cortex, the parahippocampus, and the amygdala. Together, the present results provide the first lesion-based evidence for the multidimensional nature of the emotional experiences of envy and Schadenfreude. Moreover, this is the first demonstration of a selective exacerbation of envy and Schadenfreude in bvFTD patients, probably triggered by atrophy to social cognition networks. Our results offer new insights into the mechanisms subserving complex emotions and moral cognition in neurodegeneration, paving the way for groundbreaking research on their interaction with other cognitive, social, and emotional processes.

Keywords: social cognition, moral emotions, neuroimaging, frontotemporal dementia

Procedia PDF Downloads 291

Authors: Vinod Chovvayil Panengal

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The idea of secularism in India has taken a different direction after independence when religion became a reason for a great divide in, otherwise harmonious society. Since then the religious spaces became protected and more sacred and not shared. However, there is a larger threat on beliefs, rituals, and the spirituality of these religions in the form of technology, tourism and globalization. In a way, they weaken the importance of religion from our society over a period of time. The importance of religion to a sense of place has been overlooked or diminished. Religion provides symbolic meaning to places which distinguishes certain physical environments from otherwise similar ones. The rapid transformation of urban spaces, eliminating the territorial differences of sense, spirit and identity have started creating urban centers rooting out this genre of unique urban spaces from our cities. Indian cities, with a strong identity created by rich and colorful overlays of culture through its evolution, have been threatened by this de-territorialization. This paper enquires the relationship of the symbol of the identity and religiosity of a place, through spatial form, rituals and activity, and accommodating the technology and the changing social structure within the bounds of that relationship. The subjects for this enquiry are Sufism and the Sufi city- Ajmer. The internal transformations in the ideologies of Islam and Sufism and the changes in the society surround it triggered the phenomena of de- territorialization. The need for establishing a symbiotic relationship between the spiritual content and the social life, through the manifestation of space, time and activity derived from this concern on abated territory of Sufism inside the city. Redirecting transformation catalyst such as tourism, technology, etc, towards the improvement of physical and social conditions, preservation of the heritage and the expansion of the notional idea of religion over the city will help to re- territorialize city as a Sufi city.

Keywords: sense of place, religion, Islam, identity

Procedia PDF Downloads 273

Authors: Dipti Govil, Nidhi Khosla

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Couple-level reports of contraception are important as wives and husbands may give different reports about contraceptive use. Using matched couple-data (N=62910), from India's NFHS–IV (2015-16), this paper examines concordance in spousal reports of current contraceptive use and its differentials. Reporting of contraceptive use was higher among wives (59%) than husbands (25%). Concordance was low; 16.5% of couples reported the use of the same method, while 21% reported the use of any method. There existed a huge denial from husbands on the use of female sterilization. Reconstruction of contraceptive use among men increased concordance by 10%. Multivariate analysis shows that concordance was low in urban and Southern India, among younger women and women with lower wealth-index. Men's control over household decision-making and negative attitudes towards contraception were associated with a lower concordance. Findings highlight the importance of using couple-level data to estimate contraceptive prevalence, the role of education programs to inculcate positive attitudes towards contraception, fostering gender equality, and involving men into family planning efforts. The results also raise the issue of data quality as the questions were asked differently from men and women, which might have contributed to wide discordance.

Keywords: concordance, contraceptive use, couple, female sterilisation, India

Procedia PDF Downloads 129

Authors: Mohammad A. Al-Madi, Nagham A. Al-Madi, Fanan A. Al-Madi

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The current concept of the technology of cloud computing libraries has been increasing where users can store their data in a virtual space and can be retrieved from anywhere whilst using the network. By using cloud computing technology, industries and individuals save money, time, and space. Moreover, data and information about libraries can be placed in the cloud. This paper discusses the meaning of cloud computing along with its types. Further, the focus has been given to the application of cloud computing in modern libraries. Additionally, the advantages of cloud computing and the areas in which cloud computing be applied with current usage are discussed. Finally, the present situation of the Jordanian libraries is considered and discussed in further detail.

Keywords: cloud computing, community cloud, hybrid cloud, private cloud, public cloud

Procedia PDF Downloads 221

Authors: Farhad Imanshoar

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The regime or equilibrium geometry of alluvial rivers remains a topic of fundamental scientific and engineering interest. There are several approaches to analyze the problem, namely: empirical formulas, semi-theoretical methods and rational (extreme) procedures. However, none of them is widely accepted at present, due to lack of knowledge of some physical processes associated with channel formation and the simplification hypotheses imposed in order to reduce the high quantity of involved variables. The study presented in this paper shows a new approach to estimate stable width and depth of sand-bed rivers by using developed stream power equation (DSPE). At first, a new procedure based on theoretical analysis and by considering DSPE and ultimate sediment concentration were developed. Then, experimental data for regime condition in sand-bed rivers (flow depth, flow width, sediment feed rate for several cases) were gathered. Finally, the results of this research (regime equations) are compared with the field data and other regime equations. A good agreement was observed between the field data and the values resulted from developed regime equation.

Keywords: regime equations, developed stream power equation, sand-bed rivers, semi-theoretical methods

Procedia PDF Downloads 268

Authors: Mira Trebar

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Logistics processes of perishable food in the supply chain include the distribution activities and the real time temperature monitoring to fulfil the cold chain requirements. The paper presents the use of RFID (Radio Frequency Identification) technology as an identification tool of receiving and shipping activities in the cold store. At the same time, the use of RFID data loggers with temperature sensors is presented to observe and store the temperatures for the purpose of analyzing the processes and having the history data available for traceability purposes and efficient recall management.

Keywords: logistics, warehouse, RFID device, cold chain

Procedia PDF Downloads 631

Authors: Marina Shakleina, Konstantin Shaklein, Stanislav Yakiro

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The digitalization of modern human life over the last decade has facilitated the acquisition, storage, and processing of data, which are used to detect changes in consumer preferences and to improve the internal efficiency of the production process. This emerging trend has attracted academic interest in the use of big data in research. The study focuses on modeling the social comfort of the Russian population for the period 2010-2021 using big data. Big data provides enormous opportunities for understanding human interactions at the scale of society with plenty of space and time dynamics. One of the most popular big data sources is Google Trends. The methodology for assessing social comfort using big data involves several steps: 1. 574 words were selected based on the Harvard IV-4 Dictionary adjusted to fit the reality of everyday Russian life. The set of keywords was further cleansed by excluding queries consisting of verbs and words with several lexical meanings. 2. Search queries were processed to ensure comparability of results: the transformation of data to a 10-point scale, elimination of popularity peaks, detrending, and deseasoning. The proposed methodology for keyword search and Google Trends processing was implemented in the form of a script in the Python programming language. 3. Block and summary integral indicators of social comfort were constructed using the first modified principal component resulting in weighting coefficients values of block components. According to the study, social comfort is described by 12 blocks: ‘health’, ‘education’, ‘social support’, ‘financial situation’, ‘employment’, ‘housing’, ‘ethical norms’, ‘security’, ‘political stability’, ‘leisure’, ‘environment’, ‘infrastructure’. According to the model, the summary integral indicator increased by 54% and was 4.631 points; the average annual rate was 3.6%, which is higher than the rate of economic growth by 2.7 p.p. The value of the indicator describing social comfort in Russia is determined by 26% by ‘social support’, 24% by ‘education’, 12% by ‘infrastructure’, 10% by ‘leisure’, and the remaining 28% by others. Among 25% of the most popular searches, 85% are of negative nature and are mainly related to the blocks ‘security’, ‘political stability’, ‘health’, for example, ‘crime rate’, ‘vulnerability’. Among the 25% most unpopular queries, 99% of the queries were positive and mostly related to the blocks ‘ethical norms’, ‘education’, ‘employment’, for example, ‘social package’, ‘recycling’. In conclusion, the introduction of the latent category ‘social comfort’ into the scientific vocabulary deepens the theory of the quality of life of the population in terms of the study of the involvement of an individual in the society and expanding the subjective aspect of the measurements of various indicators. Integral assessment of social comfort demonstrates the overall picture of the development of the phenomenon over time and space and quantitatively evaluates ongoing socio-economic policy. The application of big data in the assessment of latent categories gives stable results, which opens up possibilities for their practical implementation.

Keywords: big data, Google trends, integral indicator, social comfort

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Authors: Ahmed El Naggar, Homyan Saleh

Abstract:

Dams are crucial for flood control, water supply, and the creation of hydroelectric power. Every dam has a water conveyance system, such as a spillway, providing the safe discharge of catastrophic floods when necessary. Spillway design has historically been investigated in laboratory research owing to the absence of suitable full-scale flow monitoring equipment and safety problems. Prototype measurements of aerated flows are urgently needed to quantify projected scale effects and provide missing validation data for design guidelines and numerical simulations. In this work, an image-based investigation of free-surface flows on a tiered spillway was undertaken at the laboratory (fixed camera installation) and prototype size (drone video) (drone footage) (drone footage). The drone videos were generated using data from citizen science. Analyses permitted the measurement of the free-surface aeration inception point, air-water surface velocities, fluctuations, and residual energy at the chute's downstream end from a remote site. The prototype observations offered full-scale proof of concept, while laboratory results were efficiently confirmed against invasive phase-detection probe data. This paper stresses the efficacy of image-based analyses at prototype spillways. It highlights how citizen science data may enable academics better understand real-world air-water flow dynamics and offers a framework for a small collection of long-missing prototype data.

Keywords: remote sensing, aerated flows, large dams, proof of concept, dam spillways, air-water flows, prototype operation, remote sensing, inception point, optical flow, turbulence, residual energy

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Authors: Abdolamir Gatezadeh, Jamal Daghaleh

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The lifestyle of individuals is important and determinant for the status of psychological and social health. Recently, especially in developed countries, the relationship between lifestyle and mental illnesses, including depression, has attracted the attention of many people. In order to test the causal model of depression based on lifestyle with mediation of social health in the study, basic and applied methods were used in terms of objective and descriptive-field as well as the data collection. Methods: This study is a basic research type and is in the framework of correlational plans. In this study, the population includes all adults in Ahwaz city. A randomized, multistage sampling of 384 subjects was selected as the subjects. Accordingly, the data was collected and analyzed using structural equation modeling. Results: In data analysis, path analysis indicated the confirmation of the assumed model fit of research. This means that subscales lifestyle has a direct effect on depression and subscales lifestyle through the mediation of social health which in turn has an indirect effect on depression. Discussion and conclusion: According to the results of the research, the depression can be used to explain the components of the lifestyle and social health.

Keywords: depression, subscales lifestyle, social health, causal model

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Authors: Kevin Potoczny, Katsuichiro Goda

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The St. Lawrence lowlands extend from Ottawa to Quebec City and are known for large deposits of sensitive Leda clay. Leda clay deposits are responsible for many large landslides, such as the 1993 Lemieux and 2010 St. Jude (4 fatalities) landslides. Due to the large extent and sensitivity of Leda clay, regional hazard analysis for landslides is an important tool in risk management. A 2018 regional study by Farzam et al. on the susceptibility of Leda clay slopes to landslide hazard uses 1 arc second topographical data. A qualitative method known as Hazus is used to estimate susceptibility by checking for various criteria in a location and determine a susceptibility rating on a scale of 0 (no susceptibility) to 10 (very high susceptibility). These criteria are slope angle, geological group, soil wetness, and distance from waterbodies. Given the flat nature of St. Lawrence lowlands, the current assessment fails to capture local slopes, such as the St. Jude site. Additionally, the data did not allow one to analyze failure planes accurately. This study majorly improves the analysis performed by Farzam et al. in two aspects. First, regional assessment with high resolution data allows for identification of local locations that may have been previously identified as low susceptibility. This then provides the opportunity to conduct a more refined analysis on the failure plane of the slope. Slopes derived from 1 arc second data are relatively gentle (0-10 degrees) across the region; however, the 1- and 2-meter resolution 2022 HRDEM provided by NRCAN shows that short, steep slopes are present. At a regional level, 1 arc second data can underestimate the susceptibility of short, steep slopes, which can be dangerous as Leda clay landslides behave retrogressively and travel upwards into flatter terrain. At the location of the St. Jude landslide, slope differences are significant. 1 arc second data shows a maximum slope of 12.80 degrees and a mean slope of 4.72 degrees, while the HRDEM data shows a maximum slope of 56.67 degrees and a mean slope of 10.72 degrees. This equates to a difference of three susceptibility levels when the soil is dry and one susceptibility level when wet. The use of GIS software is used to create a regional susceptibility map across the St. Lawrence lowlands at 1- and 2-meter resolutions. Failure planes are necessary to differentiate between small and large landslides, which have so far been ignored in regional analysis. Leda clay failures can only retrogress as far as their failure planes, so the regional analysis must be able to transition smoothly into a more robust local analysis. It is expected that slopes within the region, once previously assessed at low susceptibility scores, contain local areas of high susceptibility. The goal is to create opportunities for local failure plane analysis to be undertaken, which has not been possible before. Due to the low resolution of previous regional analyses, any slope near a waterbody could be considered hazardous. However, high-resolution regional analysis would allow for more precise determination of hazard sites.

Keywords: hazus, high-resolution DEM, leda clay, regional analysis, susceptibility

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Authors: Binder Hans

Abstract:

Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

Procedia PDF Downloads 148