Search results for: Spatial Data Analyses

Authors: Lucas Wilman Crispim, Patrícia Hallack, Maikel Ballester

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This work aims at modeling electric discharges in gas mixtures. The mathematical model mimics the ignition process in a commercial spark-plug when a high voltage is applied to the plug terminals. A longitudinal unidimensional Cartesian domain is chosen for the simulation region. Energy and mass transfer are considered for a macroscopic fluid representation, while energy transfer in molecular collisions and chemical reactions are contemplated at microscopic level. The macroscopic model is represented by a set of uncoupled partial differential equations. Microscopic effects are studied within a discrete model for electronic and molecular collisions in the frame of ZDPlasKin, a plasma modeling numerical tool. The BOLSIG+ solver is employed in solving the electronic Boltzmann equation. An operator splitting technique is used to separate microscopic and macroscopic models. The simulation gas is a mixture of atomic Argon neutral, excited and ionized. Spatial and temporal evolution of such species and temperature are presented and discussed.

Keywords: CFD, electronic discharge, ignition, spark plug

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Authors: Ahmad Shayeq Azizi, Yuji Toda

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In Afghanistan, floods are the most frequent and recurrent events among other natural disasters. On the other hand, lack of monitoring data is a severe problem, which increases the difficulty of making the appropriate flood countermeasures of flood forecasting. This study is carried out to simulate the flood inundation in Harirud River Basin by application of distributed hydrological model, Integrated Flood Analysis System (IFAS) and 2D hydrodynamic model, International River Interface Cooperative (iRIC) based on satellite rainfall combined with historical peak discharge and global accessed data. The results of the simulation can predict the inundation area, depth and velocity, and the hardware countermeasures such as the impact of levee installation can be discussed by using the present method. The methodology proposed in this study is suitable for the area where hydrological and geographical data including river survey data are poorly observed.

Keywords: distributed hydrological model, flood inundation, hydrodynamic model, ungauged basins

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Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk

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The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.

Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression

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Authors: Wai Yan Shih, Sau Man Wong, Wing Chung Chang, Wai Chi Chan

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Background: Late-life depression is associated with significant consequences. Although symptomatic reduction is achievable through pharmacological interventions, older adults are more vulnerable to the side effects than their younger counterparts. In addition, drugs do not address underlying cognitive dysfunctions such as rumination and reduced autobiographical memory specificity (AMS), both shown to be maladaptive coping styles that are associated with a poorer prognosis in depression. Considering how aging is accompanied by cognitive, psychological and physical changes, the interplay of these age-related factors may potentially aggravate and interfere with these depressive cognitive dysfunctions in late-life depression. Special care should, therefore, be drawn to ensure these cognitive dysfunctions are adequately addressed. Aim: This randomized controlled trial aims to examine the effect of mindfulness-based cognitive therapy (MBCT) on depressed older adults, and whether the potential benefits of MBCT are mediated by improvements in rumination and AMS. Method: Fifty-seven participants with an average age of 70 years old were recruited from multiple elderly centers and online mailing lists. Participants were assessed with: (1) Hamilton depression scale, (2) ruminative response scale, (3) autobiographical memory test, (4) mindful attention awareness scale, and (5) Montreal cognitive assessment. Eligible participants with mild to moderate depressive symptoms and normal cognitive functioning were randomly allocated to an 8-week MBCT group or active control group consisting of a low-intensity exercise program and health education. Post-intervention assessments were conducted after the 8-week program. Ethics approval was given by the Institutional Review Board of the University of Hong Kong/Hospital Authority. Results: Mixed-factorials ANOVAs demonstrated significant time x group interaction effects for depressive symptoms, AMS, and dispositional mindfulness. A marginally significant interaction effect was found for rumination. Simple effect analyses revealed a significant reduction in depressive symptoms for the both the MBCT group (mean difference = 7.1, p = .000), and control group (mean difference = 2.7, p = .023). However, only participants in the MBCT group demonstrated improvements in rumination, AMS, and dispositional mindfulness. Bootstrapping-based mediation analyses showed that the effect of MBCT in alleviating depressive symptoms was only mediated by the reduction in rumination. Conclusions: The findings support the use of MBCT as an effective intervention for depressed older adults, considering the improvements in depressive symptoms, rumination, AMS and dispositional mindfulness despite their age. Reduction in ruminative tendencies plays a major role in the cognitive mechanism of MBCT.

Keywords: mindfulness-based cognitive therapy, depression, older adults, rumination, autobiographical memory specificity

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Authors: Matej Komanec, Jan Bohata, Stanislav Zvanovec, Tomas Nemecek, Jan Broucek, Josef Beran

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With the exponential growth of social networks, video streaming and increasing demands on data rates, the number of newly built data centers rises proportionately. The data centers, however, have to adjust to the rapidly increased amount of data that has to be processed. For this purpose, multi-mode (MM) fiber based infrastructures are often employed. It stems from the fact, the connections in data centers are typically realized within a short distance, and the application of MM fibers and components considerably reduces costs. On the other hand, the usage of MM components brings specific requirements for installation service conditions. Moreover, it has to be taken into account that MM fiber components have a higher production tolerance for parameters like core and cladding diameters, eccentricity, etc. Due to the high demands for the reliability of data center components, the determination of properly excited optical field inside the MM fiber core belongs to the key parameters while designing such an MM optical system architecture. Appropriately excited mode field of the MM fiber provides optimal power budget in connections, leads to the decrease of insertion losses (IL) and achieves effective modal bandwidth (EMB). The main parameter, in this case, is the encircled flux (EF), which should be properly defined for variable optical sources and consequent different mode-field distribution. In this paper, we present detailed investigation and measurements of the mode field distribution for short MM links purposed in particular for data centers with the emphasis on reliability and safety. These measurements are essential for large MM network design. The various scenarios, containing different fibers and connectors, were tested in terms of IL and mode-field distribution to reveal potential challenges. Furthermore, we focused on estimation of particular defects and errors, which can realistically occur like eccentricity, connector shifting or dust, were simulated and measured, and their dependence to EF statistics and functionality of data center infrastructure was evaluated. The experimental tests were performed at two wavelengths, commonly used in MM networks, of 850 nm and 1310 nm to verify EF statistics. Finally, we provide recommendations for data center systems and networks, using OM3 and OM4 MM fiber connections.

Keywords: optical fiber, multi-mode, data centers, encircled flux

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Authors: Eun Hak Lee, Young-Hyun Seo, Hosuk Shin, Seung-Young Kho

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Among traffic crashes, driving under the influence (DUI) of alcohol is the most dangerous behavior in Seoul, South Korea. In 2016 alone 40 deaths occurred on of 2,857 cases of DUI. Since DUI is one of the major factors in increasing the severity of crashes, the intensive management of DUI required to reduce traffic crash deaths and the crash damages. This study aims to investigate the relationship between DUI and traffic safety in order to establish countermeasures for traffic safety improvement. The analysis was conducted on the habitual drivers who drove under the influence. Information of habitual drivers is matched to crash data and fine data. The descriptive statistics on data used in this study, which consists of driver license acquisition, traffic fine, and crash data provided by the Korean National Police Agency, are described. The drivers under the influence are classified by statistically significant criteria, such as driver’s age, license type, driving experience, and crash reasons. With the results of the analysis, we propose some countermeasures to enhance traffic safety.

Keywords: driving under influence, traffic safety, traffic crash, traffic fine

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Authors: J. Wicks

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Aim: To develop a simple methodology to allow collected heart rate (HR) data from inexpensive wearable devices to be expressed in a suitable format (METs) to quantitate occupational (and recreational) activity. Introduction: Assessment of occupational activity is commonly done by utilizing questionnaires in combination with prescribed MET levels of a vast range of previously measured activities. However for any individual the intensity of performing a specific activity can vary significantly. Ideally objective measurement of individual activity is preferred. Though there are a wide range of HR recording devices there is a distinct lack methodology to allow processing of collected data to quantitate energy expenditure (EE). The HR index equation expresses METs in relation to relative HR i.e. the ratio of activity HR to resting HR. The use of this equation provides a simple utility for objective measurement of EE. Methods: During a typical occupational work period of approximately 8 hours HR data was recorded using a Polar RS 400 wrist monitor. Recorded data was downloaded to a Windows PC and non HR data was stripped from the ASCII file using ‘Notepad’. The HR data was exported to a spread sheet program and sorted by HR range into a histogram format. Three HRs were determined, namely a resting HR (the HR delimiting the lowest 30 minutes of recorded data), a mean HR and a peak HR (the HR delimiting the highest 30 minutes of recorded data). HR indices were calculated (mean index equals mean HR/rest HR and peak index equals peak HR/rest HR) with mean and peak indices being converted to METs using the HR index equation. Conclusion: Inexpensive HR recording devices can be utilized to make reasonable estimates of occupational (or recreational) EE suitable for large scale demographic screening by utilizing the HR index equation. The intrinsic value of the HR index equation is that it is independent of factors that influence absolute HR, namely fitness, smoking and beta-blockade.

Keywords: energy expenditure, heart rate histograms, heart rate index, occupational activity

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Authors: Weisi Guo

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It is well established that there may be running correlations in sequential exam marks due to students sitting in the order of course registration patterns. As such, a random and non-sequential sampling of exam marks is a standard recommended practice. Here, the paper examines a large number of exam data stretching several years across different modules to see the degree to which it is true. Using the real mark distribution as a generative process, it was found that random simulated data had no more sequential randomness than the real data. That is to say, the running correlations that one often observes are statistically identical to chance. Digging deeper, it was found that some high running correlations have students that indeed share a common course history and make similar mistakes. However, at the statistical scale of a module question, the combined effect is statistically similar to the random shuffling of papers. As such, there may not be the need to take random samples for marks, but it still remains good practice to mark papers in a random sequence to reduce the repetitive marking bias and errors.

Keywords: data analysis, empirical study, exams, marking

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Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. While it is recognized that SOC predictors vary significantly when derived from remote sensing data and environmental variables, identifying the specific parameters most suitable for accurately estimating SOC in diverse agricultural areas remains a challenge. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors' impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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Authors: Anu Malhotra, Rahul Malhotra

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This review paper is focused on achievement ability analysis of perspective teachers and students of technical education of Haryana. It is well known that women have higher verbal achievement, while men have higher achievement in non-verbal and scientific achievement. Chi-square analyses were performed to evaluate the effect of information and communication technology tools on the scientific, verbal and non-verbal achievement of the controlled and uncontrolled group of 204 students of Haryana. The computed value of expected count, which is more than 5, shows that there is a significant improvement in achievement ability of students of the controlled group when compared to the uncontrolled group. The research analyzes that the Information and communication technology tools play an important role in enhancing student’s achievement.

Keywords: achievement, ICT, perspective teacher, verbal achievement

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Authors: Kihyon Kwon, Hyun T. Park, Gil Y. Chung, Sang-Hoon Lee

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This paper focuses on assessing sloshing-induced overflow of the seismically-isolated nuclear tanks based on Fluid-Structure Interaction (FSI) analysis. Typically, fluid motion in the seismically-isolated nuclear tank systems may be rather amplified and even overflowed under earthquake. Sloshing-induced overflow in those structures has to be reliably assessed and predicted since it can often cause critical damages to humans and environments. FSI analysis is herein performed to compute the total cumulative overflowed water volume more accurately, by coupling ANSYS with CFX for structural and fluid analyses, respectively. The approach is illustrated on a nuclear liquid storage tank, Spent Fuel Pool (SFP), forgiven conditions under consideration: different liquid levels, Peak Ground Accelerations (PGAs), and post earthquakes.

Keywords: FSI analysis, seismically-isolated nuclear tank system, sloshing-induced overflow

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Authors: Ágoston Nagy

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This paper introduces a method of using unsupervised machine learning to visualize the feature space of a dataset in 2D, in order to find most characteristic segments in the set. After dimension reduction, users can select clusters by manual drawing. Selected clusters are recorded into a data model that is used for later predictions, based on realtime data. Predictions are made with supervised learning, using Gesture Recognition Toolkit. The paper introduces two example applications: a semantic audio organizer for analyzing incoming sounds, and a gesture database organizer where gestural data (recorded by a Leap motion) is visualized for further manipulation.

Keywords: gesture recognition, machine learning, real-time interaction, visualization

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Authors: Sourabh Yaduvanshi, Varsha Namdeo, Namrata Yaduvanshi

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This study delves into the design and development intricacies of crafting detailed 2D bar charts via d3.js, recognizing its limitations in generating 3D visuals within the Document Object Model (DOM). The study combines three.js with d3.js, facilitating a smooth evolution from 2D to immersive 3D representations. This fusion epitomizes the synergy between front-end technologies, expanding horizons in data visualization. Beyond technical expertise, it symbolizes a creative convergence, pushing boundaries in visual representation. The abstract illuminates methodologies, unraveling the intricate integration of this fusion and guiding enthusiasts. It narrates a compelling story of transcending 2D constraints, propelling data visualization into captivating three-dimensional realms, and igniting creativity in front-end visualization endeavors.

Keywords: design, development, front-end technologies, visualization

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Authors: K. Tejasri, K. Suvarna Vani, S. Prathyusha, S. Ramya

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Proteins are chained sequences of amino acids which are brought together by the peptide bonds. Many varying formations of the chains are possible due to multiple combinations of amino acids and rotation in numerous positions along the chain. Protein structure prediction is one of the crucial goals worked towards by the members of bioinformatics and theoretical chemistry backgrounds. Among the four different structure levels in proteins, we emphasize mainly the secondary level structure. Generally, the secondary protein basically comprises alpha-helix and beta-sheets. Multi-class classification problem of data with disparity is truly a challenge to overcome and has to be addressed for the beta strands. Imbalanced data distribution constitutes a couple of the classes of data having very limited training samples collated with other classes. The secondary structure data is extracted from the protein primary sequence, and the beta-strands are predicted using suitable machine learning algorithms.

Keywords: proteins, secondary structure elements, beta-sheets, beta-strands, alpha-helices, machine learning algorithms

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Authors: Sudeshna Sengupta

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Women’s work lives weave a complex fabric of myriad work relations and complex structures. Lives, when seen from the lens of work, is a saga of conjugated oppression by intertwined structures that are vertically and horizontally interwoven in a very complex manner. Women interact with multiple institutions through their work. The interactions and interplay of institutions shape their organization of work. They intersperse productive work with reproductive work, unpaid economic activities with unpaid care work, and all kinds of activities with leisure and self-care. The proposed paper intends to understand how women working as home-based workers in the National Capital Region (NCR) of India are organizing their everyday work, and how the organization of work is influenced by the interplay of structures. Situating itself in a multidisciplinary theoretical framework, this paper brings out how the gendering of work is playing out in the political, economic and social domain and shaping the work-life within the family, and in the paid workspace. The paper will use a primary data source, which is qualitative in nature. It will comprise 15 qualitative interviews of women home-based workers from the National Capital Region. The research uses a life history approach. The sampling was purposive using snowballing as a method. The dataset is part of the primary data (qualitative) collected for the ongoing Ph.D. work in Gender Studies at Ambedkar University Delhi. The home-based workers interviewed were in “non-factory” wage relations based on piece rates with flexible working hours. Their workplaces were their own homes with no spatial divide between living spaces and workspaces. Home-based workers were recognized as a group in the domain of labor economics in the 1980s. When menial work was cheaper than machine work, the capital owners preferred to outsource work as home-based work to women. These production spaces are fragmented and the identity of gender is created within labor processes to favor material accumulation. Both the employers and employees acknowledged the material gain of the capital owner when work was subcontracted to women at home. Simultaneously the market reinforced women’s reproductive role by conforming to patriarchal ideology. The contractors played an important role in implementing localized control on workers and also in finding workers for fragmented, gendered production processes. Their presence helped the employers in bringing together multiple forms of oppression that ranged from creating a structure to flout laws by creating shadow employers. It created an intertwined social and economic structure as well as a workspace where the line between productive and reproductive work gets blurred. The state invisibilized itself either by keeping the sector out of the domain of laws or by not implementing its own laws regulating working conditions or social security. It allowed the local hierarchy to function and define localized working conditions. The productive reproductive continuum reveals a labor control that influenced both the productive and reproductive work of women.

Keywords: informal sector, paid work, women workers, labor processes

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Authors: Chougrani Fadela, Cheriguene Abderrahim

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Fifty three strains of thermophilic and mesophilic lactic acid bacteria were isolated from the ewe’s milk. Identification reveals the presence of nineteen strains (36%) of Lactobacillus sp., seventeen strains (32%) of Lactococcus sp., nine strains (17%) of Streptococcus thermophilus and eight strains (15%) of Leuconostoc sp. The strains were characterized for their technological properties. A high diversity of properties among the studied strains was demonstrated. On the basis of technological characteristics, two strains (Lactobacillus bulgaricus and Streptococcus thermophilus) were screened with respect to their acid and flavour production for the preparation of a natural yogurt and compared to a commercial starter cultures. Sensorial analyses revealed that the product manufactured on the basis of the isolated strains have a cohesiveness and adhesiveness corresponding to standard products. The pH and the acidity recorded are also within accepted levels during all the period of conservation.

Keywords: Lactobacillus bulgaricus, Streptococcus thermophilus, yoghurt, cohesiveness, adhesiveness, Algerian ewe’s milk

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Authors: Abdu Umar Adamu, Maimuna Ibrahim

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In this present work, a locally used medicinal plant, namely: Aspillia kotschyi belonging to the Compositae family, was extracted using methanolic and petroleum ether 60-80OC. The extracts were subjected to microwave plasma Atomic Emission Spectroscopy (MPES) to determine the following metals Se, Ag, Fe, Cu, Ni, As, Co, Mn, and Al. From the result, Ag, Cu, Ni, and Co are of very negligible concentrations in the plant extract. However, Seleniun is found to be 0.530 (mg/kg) in the plant methanolic extract. Iron, on the other hand, was found to be 3.712 (mg/kg) in the plant extract. Arsenic was found to be 0.506 and 1.301 (mg/kg) in both methanolic and petroleum spirit extracts of the plant material. The concentration of aluminium was found to be of the range of 3.050mg/kg in the plant. Functional group analysis of the plant extracts was also carried out using Fourier transform infrared (FTIR) spectroscopy which showed the presence of some functional groups. The results of this study suggest some merit in the popular use of the plant in herbal medicine.

Keywords: Aspillia kotschyi, functional group, FTIR, MPES

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Authors: Bharat P. Modi, Jayesh M. Patel

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Mobile Internet is acting as a major source of data. As the number of web pages continues to grow the Mobile web provides the data miners with just the right ingredients for extracting information. In order to cater to this growing need, a special term called Mobile Web mining was coined. Mobile Web mining makes use of data mining techniques and deciphers potentially useful information from web data. Web Usage mining deals with understanding the behavior of users by making use of Mobile Web Access Logs that are generated on the server while the user is accessing the website. A Web access log comprises of various entries like the name of the user, his IP address, a number of bytes transferred time-stamp etc. A variety of Log Analyzer tools exists which help in analyzing various things like users navigational pattern, the part of the website the users are mostly interested in etc. The present paper makes use of such log analyzer tool called Mobile Web Log Expert for ascertaining the behavior of users who access an astrology website. It also provides a comparative study between a few log analyzer tools available.

Keywords: mobile web access logs, web usage mining, web server, log analyzer

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Authors: Huy Q. Tran, Bac V. Nguyen, Choonghyun Kang, Jungwon Huh

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Jumbo container crane is an important part of port structures that needs to be designed properly, even when the port locates in low seismicity zone such as in Korea. In this paper, 30 artificial ground motions derived from the elastic response spectra of Korean Building Code (2005) are used for time history analysis. It is found that the uplift might not occur in this analysis when the crane locates in the low seismic zone. Therefore, a selection of a pinned or a gap element for base supporting has not much effect on the determination of the total base shear. The relationships between the total base shear and peak ground acceleration (PGA) and the relationships between the portal drift and the PGA are proposed in this study.

Keywords: jumbo container crane, portal drift, time history analysis, total base shear

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Authors: Aaron Aboshio

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Numerical study of the static response of homogeneous clay stratum considering a wide range of cohesion and subject to foundation loads is presented. The linear elastic–perfectly plastic constitutive relation with the von Mises yield criterion were utilised to develop a numerically cost effective finite element model for the soil while imposing a rigid body constrain to the foundation footing. From the analyses carried out, estimate of the bearing capacity factor, Nc as well as the ultimate load-carrying capacities of these soils, effect of cohesion on foundation settlements, stress fields and failure propagation were obtained. These are consistent with other findings in the literature and hence can be a useful guide in design of safe foundations in clay soils for buildings and other structure.

Keywords: bearing capacity factors, finite element method, safe bearing pressure, structure-soil interaction

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Authors: Behzad Shahizare, N. Nik-Ghazali, Kannan M. Munisamy, Seyedsaeed Tabatabaeikia

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The main objective of this study is to clarify the effect of the adjustable outlet guide vane (OGV) on the axial fan. Three-dimensional Numerical study was performed to analyze the effect of adjustable guide vane for improving the airflow rate in axial fans. Grid independence test was done between five different meshes in order to choose the reliable mesh. In flow analyses, Reynolds averaged Navier-Stokes (RANS) equations was solved using three types of turbulence models named k-ɛ, k-ω and k-ω SST. The aerodynamic performances of the fan and guide vane were evaluated. Numerical method was validated by comparing with experimental test according to AMECA 210 standard. Results showed that, by using the adjustable guide vane the airflow rate is increased around 3% to 6 %. The maximum enhancement of the airflow rate was achieved when pressure was 374pa.

Keywords: axial fan, adjustable guide vane, CFD, turbo machinery

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Authors: Jun Liu, Feihang Zhou, Gungyi Wang

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This paper expounds on the direct-driven PMSG wind power system control strategy, and analyses the stability conditions of the system. The direct-driven PMSG wind power system may generate the intense mechanical vibration, when wind speed changes dramatically. This paper proposes a new type of torque control strategy, which increases the system damping effectively, mitigates mechanical vibration of the system, and enhances the stability conditions of the system. The simulation results verify the reliability of the new torque control strategy.

Keywords: damping, direct-driven PMSG wind power system, mechanical vibration, torque control

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Authors: Hanna Gulema, Meaza Demissie, Alemayehu Worku, Tesfaye Assebe Yadeta, Yemane Berhane

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Background: In patriarchal societies, female caregivers decide on food allocation within a family based on prevailing gender and age norms, which may lead to inequality that does not favor young adolescent girls. This study evaluated the effect of a community-based social norm intervention involving female caregivers in West Hararghe, Ethiopia. The intervention was engaging female caregivers along with other adult influential community members to deliberate and act on food allocation social norms in a process referred to as Social Analysis and Action (SAA). Method: We used data from a large quasi-experimental study to compare family eating practices between those who participated in the Social Analyses and Action intervention and those who did not. The respondents were female caregivers in households with young adolescent girls (ages 13 and 14 years). The study’s outcome was the practice of family eating together from the same dish. The difference in difference (DID) analysis with the Mixed effect logistic regression model was used to examine the effect of the intervention. Result: The results showed improved family eating practices in both groups, but the improvement was greater in the intervention group. The DID analysis showed an 11.99 percentage points greater improvement in the intervention arm than in the control arm. The mixed-effect regression produced an adjusted odds ratio of 2.08 (95% CI [1.06–4.09]) after controlling selected covariates, p-value 0.033. Conclusions: The involvement of influential adult community members significantly improves the family practice of eating together in households where adolescent girls are present in our study. The intervention has great potential to minimize household food allocation inequalities and thus improve the nutritional status of young adolescents. Further studies are necessary to evaluate the effectiveness of the intervention in different social norm contexts to formulate policy and guidelines for scale-up.

Keywords: family eating practice, social norm intervention, adolescence girls, caregiver

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Authors: Ziwei Chen, Yujiang Gao

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The rapid urbanization has caused the massive physical space in Chinese cities to be in a state of duplication and dislocation through the rapid development, forming many daily spaces that cannot be standardized, typed, and identified, such as illegal construction. This phenomenon is known as urban spatial redundancy and is often excluded from mainstream architectural discussions because of its 'remaining' and 'excessive' derogatory label. In recent years, some practice architects have begun to pay attention to this phenomenon and tried to tap the value behind it. In this context, the author takes the redundancy phenomenon of resident space as the research object and explores the inspiration to the urban architectural renewal and the innovative residential area model, based on the urban survey of redundant living space in Hongkou District of Shanghai. On this basis, it shows that the changes accumulated in the long-term use of the building can be re-applied to the goals before the design, which is an important link and significance of the existence of an architecture.

Keywords: rapid urbanization, living space redundancy, architectural renewal, residential area model

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Authors: Vineetha Bettaiah, Heggere S. Ranganath

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This paper presents a Hierarchical Piecewise Linear Approximation (HPLA) for the representation of time series data in which the time series is treated as a curve in the time-amplitude image space. The curve is partitioned into segments by choosing perceptually important points as break points. Each segment between adjacent break points is recursively partitioned into two segments at the best point or midpoint until the error between the approximating line and the original curve becomes less than a pre-specified threshold. The HPLA representation achieves dimensionality reduction while preserving prominent local features and general shape of time series. The representation permits course-fine processing at different levels of details, allows flexible definition of similarity based on mathematical measures or general time series shape, and supports time series data mining operations including query by content, clustering and classification based on whole or subsequence similarity.

Keywords: data mining, dimensionality reduction, piecewise linear representation, time series representation

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Authors: Hary Aprianto Wijaya Siahaan, Bayu Edo Pratama

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Sea fishery's potential to become one of the nation's assets which very contributed to Indonesia's economy. This fishery potential not in spite of the availability of the chlorophyll in the territorial waters of Indonesia. The research was conducted using three methods, namely: statistics, comparative and analytical. The data used include MODIS sea temperature data imaging results in Aqua satellite with a resolution of 4 km in 2002-2015, MODIS data of chlorophyll-a imaging results in Aqua satellite with a resolution of 4 km in 2002-2015, and Imaging results data ASCAT on MetOp and NOAA satellites with 27 km resolution in 2002-2015. The results of the processing of the data show that the incidence of upwelling in the south of East Java Sea began to happen in June identified with sea surface temperature anomaly below normal, the mass of the air that moves from the East to the West, and chlorophyll-a concentrations are high. In July the region upwelling events are increasingly expanding towards the West and reached its peak in August. Chlorophyll-a concentration prediction using multiple linear regression equations demonstrate excellent results to chlorophyll-a concentrations prediction in 2002 until 2015 with the correlation of predicted chlorophyll-a concentration indicate a value of 0.8 and 0.3 with RMSE value. On the chlorophyll-a concentration prediction in 2016 indicate good results despite a decline in the value of the correlation, where the correlation of predicted chlorophyll-a concentration in the year 2016 indicate a value 0.6, but showed improvement in RMSE values with 0.2.

Keywords: satellite, sea surface temperature, upwelling, wind stress

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Authors: Majid Arvan, Peyman Beygi, Sina Rokhsati

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In-time detection of fire in buildings is of great importance. Employing intelligent methods in data processing in fire detection systems leads to a significant reduction of fire damage at lowest cost. In this paper, the raw data obtained from the fire detection sensor networks in buildings is processed by using intelligent methods based on neural networks and the likelihood of fire happening is predicted. In order to enhance the quality of system, the noise in the sensor data is reduced by analyzing wavelets and applying SVD technique. Meanwhile, the proposed neural network is trained using particle swarm optimization (PSO). In the simulation work, the data is collected from sensor network inside the room and applied to the proposed network. Then the outputs are compared with conventional MLP network. The simulation results represent the superiority of the proposed method over the conventional one.

Keywords: intelligent fire detection, neural network, particle swarm optimization, fire sensor network

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Authors: Saima Nazir, Mustansar Ali Ghazanfar, Sanay Muhammad Umar Saeed, Muhammad Awais Azam, Saad Ali Alahmari

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Terrorism is an important and challenging concern. The entire world is threatened by only few sophisticated terrorist groups and especially in Gulf Region and Pakistan, it has become extremely destructive phenomena in recent years. Predicting the pattern of attack type, attack group and target type is an intricate task. This study offers new insight on terrorist group’s attack type and its chosen target. This research paper proposes a framework for prediction of terrorist attacks using the historical data and making an association between terrorist group, their attack type and target. Analysis shows that the number of attacks per year will keep on increasing, and Al-Harmayan in Saudi Arabia, Al-Qai’da in Gulf Region and Tehreek-e-Taliban in Pakistan will remain responsible for many future terrorist attacks. Top main targets of each group will be private citizen & property, police, government and military sector under constant circumstances.

Keywords: data mining, counter terrorism, machine learning, SVM

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Authors: Merad Boudia Omar Rafik, Feham Mohammed

Abstract:

Data aggregation in wireless sensor networks (WSNs) provides a great reduction of energy consumption. The limited resources of sensor nodes make the choice of an encryption algorithm very important for providing security for data aggregation. Asymmetric cryptography involves large ciphertexts and heavy computations but solves, on the other hand, the problem of key distribution of symmetric one. The latter provides smaller ciphertexts and speed computations. Also, the recent researches have shown that achieving the end-to-end confidentiality and the end-to-end integrity at the same is a challenging task. In this paper, we propose (SA-SPKC), a novel security protocol which addresses both security services for WSNs, and where only the base station can verify the individual data and identify the malicious node. Our scheme is based on stateful public key encryption (StPKE). The latter combines the best features of both kinds of encryption along with state in order to reduce the computation overhead. Our analysis

Keywords: secure data aggregation, wireless sensor networks, elliptic curve cryptography, homomorphic encryption

Procedia PDF Downloads 286

Authors: S. S. Patil, B. U. Janugade, S. V. Patil

Abstract:

Pulsatile systems are gaining a lot of interest as they deliver the drug at the right site of action at the right time and in the right amount, thus providing spatial and temporal delivery thus increasing patient compliance. These systems are designed according to the circadian rhythm of the body. Chronotherapeutics is the discipline concerned with the delivery of drugs according to inherent activities of a disease over a certain period of time. It is becoming increasingly more evident that the specific time that patients take their medication may be even more significant than was recognized in the past. The tradition of prescribing medication at evenly spaced time intervals throughout the day, in an attempt to maintain constant drug levels throughout a 24-hour period, may be changing as researcher’s report that some medications may work better if their administration is coordinated with day-night patterns and biological rhythms. The potential benefits of chronotherapeutics have been demonstrated in the management of a number of diseases. In particular, there is a great deal of interest in how chronotherapy can particularly benefit patients suffering from allergic rhinitis, rheumatoid arthritis and related disorders, asthma, cancer, cardiovascular diseases, and peptic ulcer disease.

Keywords: pulsatile drug delivery, chronotherapeutics, circadian rhythm, asthma, chronobiology

Procedia PDF Downloads 358