Search results for: ground motion modeling

Authors: Xilu Liu, Ameen Farooq

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Beijing has several compact residential housing settings in many of its urban districts. The study in this paper reveals that urban compactness, as predictor of density, may carry an altogether different meaning in the developing world when compared to the U.S for achieving objectives of urban sustainability. Recent urban design studies in the U.S are debating for compact and mixed-use higher density housing to achieve sustainable and energy efficient living environments. While the concept of urban compactness is widely accepted as an approach in modern architectural and urban design fields, this belief may not directly carry well into all areas within cities of developing countries. Beijing’s technology-driven economy, with its historic and rich cultural heritage and a highly speculated real-estate market, extends its urban boundaries into multiple compact urban settings of varying scales and densities. The accelerated pace of migration from the countryside for better opportunities has led to unsustainable and uncontrolled buildups in order to meet the growing population demand within and outside of the urban center. This unwarranted compactness in certain urban zones has produced an unhealthy physical density with serious environmental and ecological challenging basic living conditions. In addition, crowding, traffic congestion, pollution and limited housing surrounding this compactness is a threat to public health. Several residential blocks in close proximity to each other were found quite compacted, or ill-planned, with residential sites due to lack of proper planning in Beijing. Most of them at first sight appear to be compact and dense but further analytical studies revealed that what appear to be dense actually are not as dense as to make a good case that could serve as the corner stone of sustainability and energy efficiency. This study considered several factors including floor area ratio (FAR), ground coverage (GSI), open space ratio (OSR) as indicators in analyzing urban compactness as a predictor of density. The findings suggest that these measures, influencing the density of residential sites under study, were much smaller in density than expected given their compact adjacencies. Further analysis revealed that several residential housing appear to support the notion of density in its compact layout but are actually compacted due to unregulated planning marred by lack of proper urban design standards, policies and guidelines specific to their urban context and condition.

Keywords: Beijing, density, sustainability, urban compactness

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Authors: Jihad Daba, Jean-Pierre Dubois

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Multi path fading noise degrades the performance of cellular communication, most notably in femto- and pico-cells in 3G and 4G systems. When the wireless channel consists of a small number of scattering paths, the statistics of fading noise is not analytically tractable and poses a serious challenge to developing closed canonical forms that can be analysed and used in the design of efficient and optimal receivers. In this context, noise is multiplicative and is referred to as stochastically local fading. In many analytical investigation of multiplicative noise, the exponential or Gamma statistics are invoked. More recent advances by the author of this paper have utilized a Poisson modulated and weighted generalized Laguerre polynomials with controlling parameters and uncorrelated noise assumptions. In this paper, we investigate the statistics of multi-diversity stochastically local area fading channel when the channel consists of randomly distributed Rayleigh and Rician scattering centers with a coherent specular Nakagami-distributed line of sight component and an underlying doubly stochastic Poisson process driven by a lognormal intensity. These combined statistics form a unifying triply stochastic filtered marked Poisson point process model.

Keywords: cellular communication, femto and pico-cells, stochastically local area fading channel, triply stochastic filtered marked Poisson point process

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Authors: Yu-Chi Chou

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The purpose of this study was to establish a logical path of an instructional model of empathy and social regulation, providing feasibility evidence on the model implementation in students with autism spectrum disorder (ASD). This newly developed Emotional Bug-Out Bag (BoB) curriculum was designed to enhance the empathy and socially shared regulation of students with ASD. The BoB model encompassed three instructional phases of basic theory lessons (BTL), action plan practices (APP), and final theory practices (FTP) during implementation. Besides, a learning flow (teacher-directed instruction, student self-directed problem-solving, group-based task completion, group-based reflection) was infused into the progress of instructional phases to deliberately promote the social regulatory process in group-working activities. A total of 23 junior high school students with ASD were implemented with the BoB curriculum. To examine the logical path for model implementation, data was collected from the participating students’ self-report scores on the learning nodes and understanding questions. Path analysis using structural equation modeling (SEM) was utilized for analyzing scores on 10 learning nodes and 41 understanding questions through the three phases of the BoB model. Results showed (a) all participants progressed throughout the implementation of the BoB model, and (b) the models of learning nodes and phases were positive and significant as expected, confirming the hypothesized logic path of this curriculum.

Keywords: autism spectrum disorder, empathy, regulation, socially shared regulation

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Authors: Tuba Kizilirmak

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Distinct properties of porous metamaterials have been largely processed for biomedicine requiring a three-dimensional (3D) porous structure engaged with fine mechanical features, biodegradation ability, and biocompatibility. Applications of metamaterials are (i) porous orthopedic and dental implants; (ii) in vitro cell culture of metamaterials and bone regeneration of metamaterials in vivo; (iii) macro-, micro, and nano-level porous metamaterials for sensors, diagnosis, and drug delivery. There are some specific properties to design metamaterials for tissue engineering. These are surface to volume ratio, pore size, and interconnection degrees are selected to control cell behavior and bone ingrowth. In this study, additive manufacturing technique selective laser melting will be used to print the scaffolds. Selective Laser Melting prints the 3D components according to designed 3D CAD models and manufactured materials, adding layers progressively by layer. This study aims to design metamaterials with Ti6Al4V material, which gives benefit in respect of mechanical and biological properties. Ti6Al4V scaffolds will support cell attachment by conferring a suitable area for cell adhesion. This study will control the osteoblast cell attachment on Ti6Al4V scaffolds after the determination of optimum stiffness and other mechanical properties which are close to mechanical properties of bone. Before we produce the samples, we will use a modeling technique to simulate the mechanical behavior of samples. These samples include different lattice models with varying amounts of porosity and density.

Keywords: additive manufacturing, titanium lattices, metamaterials, porous metals

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Authors: Chumki Payun, Bidisha Som

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The Mising language, spoken by the Mising community in Assam, belongs to the Tibeto-Burman family of languages. This is one of the smaller languages of the region and is facing endangerment due to the dominance of the larger languages, like Assamese. The language is spoken in close in-group scenarios and is gradually losing ground to the dominant languages, partly also due to the education setup where schools use only dominant languages. While there are a number of factors for the current contemporary status of the language, and those can be studied using sociolinguistic tools, the current work aims to contribute to the understanding of language attrition through language processing in order to establish if the effect of second language dominance is more than mere ‘usage’ patterns and has an impact on cognitive strategies. When bilingualism spreads widely in society and results in a language shift, speakers perform people often do better in their second language (L2) than in their first language (L1) across a variety of task settings, in both comprehension and production tasks. This phenomenon was investigated in the case of Mising-Assamese bilinguals, using a picture naming task, in two districts of Jorhat and Tinsukia in Assam, where the relative dominance of L2 is slightly different. This explorative study aimed to investigate if the L2 dominance is visible in their performance and also if the pattern is different in the two different places, thus pointing to the degree of language loss in this case. The findings would have implications for native language education, as education in one’s mother tongue can help reverse the effect of language attrition helping preserve the traditional knowledge system. The hypothesis was that due to the dominance of the L2, subjects’ performance in the task would be better in Assamese than that of Missing. The experiment: Mising-Assamese bilingual participants (age ranges 21-31; N= 20 each from both districts) had to perform a picture naming task in which participants were shown pictures of familiar objects and asked to name them in four scenarios: (a) only in Mising; (b) only in Assamese; (c) a cued mix block: an auditory cue determines the language in which to name the object, and (d) non-cued mix block: participants are not given any specific language cues, but instructed to name the pictures in whichever language they feel most comfortable. The experiment was designed and executed using E-prime 3.0 and was conducted responses were recorded using the help of a Chronos response box and was recorded with the help of a recorder. Preliminary analysis reveals the presence of dominance of L2 over L1. The paper will present a comparison of the response latency, error analysis, and switch cost in L1 and L2 and explain the same from the perspective of language attrition.

Keywords: bilingualism, language attrition, language processing, Mising language.

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Authors: Muhammad Abdullah, Salman Iqbal, Mamoona Rasheed

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Social identity among people is an important source of pride and self-esteem, consequently, people struggle to preserve a positive perception of their groups and collectives. The purpose of this paper is to explain the process of social identification and to highlight the underlying causal factors of social identity among employees. There is a little research about how the social identity of employees is shaped in Pakistan’s organizational culture. This study is based on social identity theory. This study uses Systems’ approach as a research methodology. The feedback loop approach is applied to explain the underlying key elements of employee behavior that collectively form social identity among social groups in corporate arena. The findings of this study reveal that effective, evaluative and cognitive components of an individual’s personality are associated with the social identification. The system dynamic feedback loop approach has revealed the underlying structure that is associated with social identity, social group formation, and effective component proved to be the most associated factor. This may also enable to understand how social groups become stable and individuals act according to the group requirements. The value of this paper lies in the understanding gained about the underlying key factors that play a crucial role in social group formation in organizations. It may help to understand the rationale behind how employees socially categorize themselves within organizations. It may also help to design effective and more cohesive teams for better operations and long-term results. This may help to share knowledge among employees as well. The underlying structure behind the social identification is highlighted with the help of system modeling.

Keywords: affective commitment, cognitive commitment, evaluated commitment, system thinking

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Authors: Mallikarjunachari Gangapuram

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The design of stimuli-responsive hydrogel nanocomposite thin films is gaining significant attention in these days due to its wide variety of applications. Soft microrobots, drug delivery, biosensors, regenerative medicine, bacterial adhesion, energy storage and wound dressing are few advanced applications in different fields. In this research work, the nanomechanical properties of composite thin films of 20 microns were tuned by applying homogeneous external DC, and AC magnetic fields of magnitudes 0.05 T and 0.1 T. Polyvinyl alcohol (PVA) used as a matrix material and elliptical hematite nanoparticles (ratio of the length of the major axis to the length of the minor axis is 140.59 ± 1.072 nm/52.84 ± 1.072 nm) used as filler materials to prepare the nanocomposite thin films. Both quasi-static nanoindentation, Nano Dynamic Mechanical Analysis (Nano-DMA) tests were performed to characterize the viscoelastic properties of PVA, PVA+Hematite (0.1% wt, 2% wt and 4% wt) nanocomposites. Different properties such as storage modulus, loss modulus, hardness, and Er/H were carefully analyzed. The increase in storage modulus, hardness, Er/H and a decrease in loss modulus were observed with increasing concentration and DC magnetic field followed by AC magnetic field. Contact angle and ATR-FTIR experiments were conducted to understand the molecular mechanisms such as hydrogen bond formation, crosslinking density, and particle-particle interactions. This systematic study is helpful in design and modeling of magnetic responsive hydrogel nanocomposite thin films for biomedical applications.

Keywords: hematite, hydrogel, nanoindentation, nano-DMA

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Authors: Mohamad Najari, Gilbert Grondin, Marwan El-Rich

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Design trucks in standard codes are selected based on the amount of damage they cause on structures-specifically bridges- and roads to represent the real traffic loads. Some limited numbers of trucks are run on a bridge one at a time and the damage on the bridge is recorded for each truck. One design track is also run on the same bridge “n” times -“n” is the number of trucks used previously- to calculate the damage of the design truck on the same bridge. To make these damages equal a reduction factor is needed for that specific design truck in the codes. As the limited number of trucks cannot be the exact representative of real traffic through the life of the structure, these reduction factors are not accurately calculated and they should be modified accordingly. Started on July 2004, the vehicle load data were collected in six weigh in motion (WIM) sites owned by Alberta Transportation for eight consecutive years. This database includes more than 200 million trucks. Having these data gives the opportunity to compare the effect of any standard fatigue trucks weigh and the real traffic load on the fatigue life of the bridges which leads to a modification for the fatigue truck factor in the code. To calculate the damage for each truck, the truck is run on the bridge, moment history of the detail under study is recorded, stress range cycles are counted, and then damage is calculated using available S-N curves. A 2000 lines FORTRAN code has been developed to perform the analysis and calculate the damages of the trucks in the database for all eight fatigue categories according to Canadian Institute of Steel Construction (CSA S-16). Stress cycles are counted using rain flow counting method. The modification factors for design truck (CL-625) are calculated for two different bridge configurations and ten span lengths varying from 1 m to 200 m. The two considered bridge configurations are single-span bridge and four span bridge. This was found to be sufficient and representative for a simply supported span, positive moment in end spans of bridges with two or more spans, positive moment in interior spans of three or more spans, and the negative moment at an interior support of multi-span bridges. The moment history of the mid span is recorded for single-span bridge and, exterior positive moment, interior positive moment, and support negative moment are recorded for four span bridge. The influence lines are expressed by a polynomial expression obtained from a regression analysis of the influence lines obtained from SAP2000. It is found that for design truck (CL-625) fatigue truck factor is varying from 0.35 to 0.55 depending on span lengths and bridge configuration. The detail results will be presented in the upcoming papers. This code can be used for any design trucks available in standard codes.

Keywords: bridge, fatigue, fatigue design truck, rain flow analysis, FORTRAN

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Authors: Ali Mashayekh, Mahdiye Khorasani, Thomas Weyh

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The tendency to use the Battery-Electric vehicle (BEV) for the low and medium driving range or even high driving range has been growing more and more. As a result, higher safety, reliability, and durability of the battery pack as a component of electric vehicles, which has a great share of cost and weight of the final product, are the topics to be considered and investigated. Battery aging can be considered as the predominant factor regarding the reliability and durability of BEV. To better understand the aging process, offline battery characterization has been widely used, which is time-consuming and needs very expensive infrastructures. This paper presents the substitute method for the conventional battery characterization methods, which is based on battery Modular Multilevel Management (BM3). According to this Topology, the battery cells can be drained and charged concerning their capacity, which allows varying battery pack structures. Due to the integration of the power electronics, the output voltage of the battery pack is no longer fixed but can be dynamically adjusted in small steps. In other words, each cell can have three different states, namely series, parallel, and bypass in connection with the neighbor cells. With the help of MATLAB/Simulink and by using the BM3 modules, the battery string model is created. This model allows us to switch two cells with the different SoC as parallel, which results in the internal balancing of the cells. But if the parallel switching lasts just for a couple of ms, we can have a perturbation pulse which can stimulate the cells out of the relaxation phase. With the help of modeling the voltage response pulse of the battery, it would be possible to characterize the cell. The Online EIS method, which is discussed in this paper, can be a robust substitute for the conventional battery characterization methods.

Keywords: battery characterization, SoH estimation, RLS, BEV

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Authors: Sidi M. A. Ghaly, Mohammad O. Khan, Mohammed Shalaby, Khaled A. Al-Snaie

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Electrical capacitance tomography (ECT) is a valuable, non-invasive technique used to monitor multiphase flow processes, especially within industrial pipelines. This study focuses on the design, testing, and performance comparison of ECT sensors configured with 8, 12, and 16 electrodes, aiming to evaluate their effectiveness in imaging accuracy, resolution, and sensitivity. Each sensor configuration was designed to capture the spatial permittivity distribution within a pipeline cross-section, enabling visualization of phase distribution and flow characteristics such as oil and water interactions. The sensor designs were implemented and tested in closed pipes to assess their response to varying flow regimes. Capacitance data collected from each electrode configuration were reconstructed into cross-sectional images, enabling a comparison of image resolution, noise levels, and computational demands. Results indicate that the 16-electrode configuration yields higher image resolution and sensitivity to phase boundaries compared to the 8- and 12-electrode setups, making it more suitable for complex flow visualization. However, the 8 and 12-electrode sensors demonstrated advantages in processing speed and lower computational requirements. This comparative analysis provides critical insights into optimizing ECT sensor design based on specific industrial requirements, from high-resolution imaging to real-time monitoring needs.

Keywords: capacitance tomography, modeling, simulation, electrode, permittivity, fluid dynamics, imaging sensitivity measurement

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Authors: Vishwanath Pethri Kamath, Jayantha Gowda Sarapanahalli, Vishal Mishra, Siddhesh Balwant Bandgar

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Recognition of emotional information is essential in any form of communication. Growing HCI (Human-Computer Interaction) in recent times indicates the importance of understanding of emotions expressed and becomes crucial for improving the system or the interaction itself. In this research work, textual data for emotion recognition is used. The text being the least expressive amongst the multimodal resources poses various challenges such as contextual information and also sequential nature of the language construction. In this research work, the proposal is made for a neural architecture to resolve not less than 8 emotions from textual data sources derived from multiple datasets using google pre-trained word2vec word embeddings and a Multi-head attention-based bidirectional LSTM model with a one-vs-all Multi-Level Classification. The emotions targeted in this research are Anger, Disgust, Fear, Guilt, Joy, Sadness, Shame, and Surprise. Textual data from multiple datasets were used for this research work such as ISEAR, Go Emotions, Affect datasets for creating the emotions’ dataset. Data samples overlap or conflicts were considered with careful preprocessing. Our results show a significant improvement with the modeling architecture and as good as 10 points improvement in recognizing some emotions.

Keywords: text emotion recognition, bidirectional LSTM, multi-head attention, multi-level classification, google word2vec word embeddings

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Authors: Nkemjika Chinenye-Kanu, Mamdud Hossain, Ghazi Droubi

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Prediction of multiphase flow induced forces, void fraction and pressure is crucial at both design and operating stages of practical energy and process pipe systems. In this study, transient numerical simulations of upward slug-churn flow through a vertical 90-degree elbow have been conducted. The volume of fluid (VOF) method was used to model the two-phase flows while the K-epsilon Reynolds-Averaged Navier-Stokes (RANS) equations were used to model turbulence in the flows. The simulation results were validated using experimental results. Void fraction signal, peak frequency and maximum magnitude of void fraction fluctuation of the slug-churn flow validation case studies compared well with experimental results. The x and y direction force fluctuation signals at the elbow control volume were obtained by carrying out force balance calculations using the directly extracted time domain signals of flow properties through the control volume in the numerical simulation. The computed force signal compared well with experiment for the slug and churn flow validation case studies. Hence, the present numerical simulation technique was able to predict the behaviours of the one-way flow induced forces and void fraction fluctuations.

Keywords: computational fluid dynamics, flow induced vibration, slug-churn flow, void fraction and force fluctuation

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Authors: Fangzheng Li, Xiong Li

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Significant differences in urban greening have occurred in Chinese cities, which accompanied with China's rapid urbanization. However, few studies focused on the spatial differentiation of urban greening in China with large amounts of data. The spatial differentiation pattern, spatial correlation characteristics and the distribution shape of urban green space ratio, urban green coverage rate and public green area per capita were calculated and analyzed, using Global and Local Moran's I using data from 289 cities in 2014. We employed Spatial Lag Model and Spatial Error Model to assess the impacts of urbanization process on urban greening of China. Then we used Geographically Weighted Regression to estimate the spatial variations of the impacts. The results showed: 1. a significant spatial dependence and heterogeneity existed in urban greening values, and the differentiation patterns were featured by the administrative grade and the spatial agglomeration simultaneously; 2. it revealed that urbanization has a negative correlation with urban greening in Chinese cities. Among the indices, the the proportion of secondary industry, urbanization rate, population and the scale of urban land use has significant negative correlation with the urban greening of China. Automobile density and per capita Gross Domestic Product has no significant impact. The results of GWR modeling showed that the relationship between urbanization and urban greening was not constant in space. Further, the local parameter estimates suggested significant spatial variation in the impacts of various urbanization factors on urban greening.

Keywords: China’s urbanization, geographically weighted regression, spatial differentiation pattern, urban greening

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Authors: Isaac Mugume, Charles Basalirwa, Daniel Waiswa, Mary Nsabagwa, Triphonia Jacob Ngailo, Joachim Reuder, Sch¨attler Ulrich, Musa Semujju

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The Numerical weather prediction (NWP) models are considered powerful tools for guiding quantitative rainfall prediction. A couple of NWP models exist and are used at many operational weather prediction centers. This study considers two models namely the Consortium for Small–scale Modeling (COSMO) model and the Weather Research and Forecasting (WRF) model. It compares the models’ ability to predict rainfall over Uganda for the period 21st April 2013 to 10th May 2013 using the root mean square (RMSE) and the mean error (ME). In comparing the performance of the models, this study assesses their ability to predict light rainfall events and extreme rainfall events. All the experiments used the default parameterization configurations and with same horizontal resolution (7 Km). The results show that COSMO model had a tendency of largely predicting no rain which explained its under–prediction. The COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly (p = 0.014) higher magnitude of error compared to the WRF model (RMSE: 11.86; ME: -1.09). However the COSMO model (RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light rainfall events. All the models under–predicted extreme rainfall events with the COSMO model (RMSE: 43.63; ME: -39.58) presenting significantly higher error magnitudes than the WRF model (RMSE: 35.14; ME: -26.95). This study recommends additional diagnosis of the models’ treatment of deep convection over the tropics.

Keywords: comparative performance, the COSMO model, the WRF model, light rainfall events, extreme rainfall events

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Authors: Reza Nematirad, Anil Pahwa, Balasubramaniam Natarajan

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Time series data consist of successive data points collected over a period of time. Accurate prediction of future values is essential for informed decision-making in several real-world applications, including electricity load demand forecasting, lifetime estimation of industrial machinery, traffic planning, weather prediction, and the stock market. Due to their critical relevance and wide application, there has been considerable interest in time series forecasting in recent years. However, the proliferation of sensors and IoT devices, real-time monitoring systems, and high-frequency trading data introduce significant intricate temporal variations, rapid changes, noise, and non-linearities, making time series forecasting more challenging. Classical methods such as Autoregressive integrated moving average (ARIMA) and Exponential Smoothing aim to extract pre-defined temporal variations, such as trends and seasonality. While these methods are effective for capturing well-defined seasonal patterns and trends, they often struggle with more complex, non-linear patterns present in real-world time series data. In recent years, deep learning has made significant contributions to time series forecasting. Recurrent Neural Networks (RNNs) and their variants, such as Long short-term memory (LSTMs) and Gated Recurrent Units (GRUs), have been widely adopted for modeling sequential data. However, they often suffer from the locality, making it difficult to capture local trends and rapid fluctuations. Convolutional Neural Networks (CNNs), particularly Temporal Convolutional Networks (TCNs), leverage convolutional layers to capture temporal dependencies by applying convolutional filters along the temporal dimension. Despite their advantages, TCNs struggle with capturing relationships between distant time points due to the locality of one-dimensional convolution kernels. Transformers have revolutionized time series forecasting with their powerful attention mechanisms, effectively capturing long-term dependencies and relationships between distant time points. However, the attention mechanism may struggle to discern dependencies directly from scattered time points due to intricate temporal patterns. Lastly, Multi-Layer Perceptrons (MLPs) have also been employed, with models like N-BEATS and LightTS demonstrating success. Despite this, MLPs often face high volatility and computational complexity challenges in long-horizon forecasting. To address intricate temporal variations in time series data, this study introduces Times2D, a novel framework that parallelly integrates 2D spectrogram and derivative heatmap techniques. The spectrogram focuses on the frequency domain, capturing periodicity, while the derivative patterns emphasize the time domain, highlighting sharp fluctuations and turning points. This 2D transformation enables the utilization of powerful computer vision techniques to capture various intricate temporal variations. To evaluate the performance of Times2D, extensive experiments were conducted on standard time series datasets and compared with various state-of-the-art algorithms, including DLinear (2023), TimesNet (2023), Non-stationary Transformer (2022), PatchTST (2023), N-HiTS (2023), Crossformer (2023), MICN (2023), LightTS (2022), FEDformer (2022), FiLM (2022), SCINet (2022a), Autoformer (2021), and Informer (2021) under the same modeling conditions. The initial results demonstrated that Times2D achieves consistent state-of-the-art performance in both short-term and long-term forecasting tasks. Furthermore, the generality of the Times2D framework allows it to be applied to various tasks such as time series imputation, clustering, classification, and anomaly detection, offering potential benefits in any domain that involves sequential data analysis.

Keywords: derivative patterns, spectrogram, time series forecasting, times2D, 2D representation

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Authors: Chin-Pin, Chen, Shi-Chi, Shiao, Ting-Hao, Lin

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Current industry is facing the rapid development of new technology in the world and fierce changes of economic environment in the society so that the industry development trend gradually does not focus on labor, but leads the industry and the academic circle with innovation and creativity. The development trend in machinery industry presents the same situation. Based on the aim of Creativity White Paper, Ministry of Education in Taiwan promotes and develops various creativity contests to cope with the industry trend. Domestic students and enterprises have good performance on domestic and international creativity contests in recent years. There must be important creative elements in such creative works to win the award among so many works. Literature review and in-depth interview with five creativity contest awarded instructors are first proceeded to conclude 15 machinery creative elements, which are further compared with the creative elements of machinery awarded creative works in past five years to understand the relationship between awarded works and creative elements. The statistical analysis results show that IDEA (Industrial Design Excellence Award) contains the most creative elements among four major international creativity contests. That is, most creativity review focuses on creative elements that are comparatively stricter. Concerning the groups participating in creativity contests, enterprises consider more creative elements of the creative works than other two elements for contests. From such contest works, creative elements of “replacement or improvement”, “convenience”, and “modeling” present higher significance. It is expected that the above findings could provide domestic colleges and universities with reference for participating in creativity related contests in the future.

Keywords: machinery, creative elements, creativity contest, creativity works

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Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino

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In order to reduce numerical computations in the nonlinear dynamic analysis of seismically base-isolated structures, a Mixed Explicit-Implicit time integration Method (MEIM) has been proposed. Adopting the explicit conditionally stable central difference method to compute the nonlinear response of the base isolation system, and the implicit unconditionally stable Newmark’s constant average acceleration method to determine the superstructure linear response, the proposed MEIM, which is conditionally stable due to the use of the central difference method, allows to avoid the iterative procedure generally required by conventional monolithic solution approaches within each time step of the analysis. The main aim of this paper is to investigate the stability and computational efficiency of the MEIM when employed to perform the nonlinear time history analysis of base-isolated structures with sliding bearings. Indeed, in this case, the critical time step could become smaller than the one used to define accurately the earthquake excitation due to the very high initial stiffness values of such devices. The numerical results obtained from nonlinear dynamic analyses of a base-isolated structure with a friction pendulum bearing system, performed by using the proposed MEIM, are compared to those obtained adopting a conventional monolithic solution approach, i.e. the implicit unconditionally stable Newmark’s constant acceleration method employed in conjunction with the iterative pseudo-force procedure. According to the numerical results, in the presented numerical application, the MEIM does not have stability problems being the critical time step larger than the ground acceleration one despite of the high initial stiffness of the friction pendulum bearings. In addition, compared to the conventional monolithic solution approach, the proposed algorithm preserves its computational efficiency even when it is adopted to perform the nonlinear dynamic analysis using a smaller time step.

Keywords: base isolation, computational efficiency, mixed explicit-implicit method, partitioned solution approach, stability

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Authors: Mansour Eslami, Fereshte Habibi

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Limb length discrepancy (LLD), or anisomeric, is defined as a condition in which paired limbs are noticeably unequal. Individuals with LLD during walking use compensatory mechanisms to dynamically lengthen the short limb and shorten the long limb to minimize the displacement of the body center of mass and consequently reduce body energy expenditure. Due to the compensatory movements created, LLD greater than 1 cm increases the odds of creating lumbar problems and hip and knee osteoarthritis. Insoles are non-surgical therapies that are recommended to improve the walking pattern, pain and create greater symmetry between the two lower limbs. However, it is not yet clear what effect insoles have on the variables related to injuries during walking. The aim of the present study was to evaluate the effect of internal and external heel lift insoles on pelvic kinematic in sagittal and frontal planes and lower extremity joint moments in individuals with mild leg length discrepancy during the stance phase of walking. Biomechanical data of twenty-eight men with structural leg length discrepancy of 10-25 mm were collected while they walked under three conditions: shoes without insole (SH), with internal heel lift insoles (IHLI) in shoes, and with external heal lift insole (EHLI). The tests were performed for both short and long legs. The pelvic kinematic and joint moment were measured with a motion capture system and force plate. Five walking trials were performed for each condition. The average value of five successful trials was used for further statistical analysis. Repeated measures ANCOVA with Bonferroni post hoc test were used for between-group comparisons (p ≤ 0.05). In both internal and external heel lift insoles (IHLI, EHLI), there was a significant decrease in the peak values of lateral and anterior pelvic tilts of the long leg, hip, and knee moments of a long leg and ankle moment of short leg (p ≤ 0.05). Furthermore, significant increases in peak values of lateral and anterior pelvic tilt of short leg in IHLI and EHLI were observed as compared to Shoe (SH) condition (p ≤ 0.01). In addition, a significant difference was observed between the IHLI and EHLI conditions in peak anterior pelvic tilt of long leg and plantar flexor moment of short leg (p=0.04; p= 0.04 respectively). Our findings indicate that both IHLI and EHLI can play an important role in controlling excessive pelvic movements in the sagittal and frontal planes in individuals with mild LLD during walking. Furthermore, the EHLI may have a better effect in preventing musculoskeletal injuries compared to the IHLI.

Keywords: kinematic, leg length discrepancy, shoe insole, walking

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Authors: Ivana Čavlina Tomašević, Višnjica Vučetić, Maja Telišman Prtenjak, Barbara Malečić

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The Split wildfire on the mid-Adriatic Coast in July 2017 is one of the most severe wildfires in Croatian history, given the size and unexpected fire behavior, and it is used in this research as a case study to run the Weather Research and Forecasting Spread Fire (WRF SFIRE) model. This coupled fire-atmosphere model was successfully run for the first time ever for one Croatian wildfire case. Verification of coupled simulations was possible by using the detailed reconstruction of the Split wildfire. Specifically, precise information on ignition time and location, together with mapped fire progressions and spotting within the first 30 hours of the wildfire, was used for both – to initialize simulations and to evaluate the model’s ability to simulate fire’s propagation and final fire scar. The preliminary simulations were obtained using high-resolution vegetation and topography data for the fire area, additionally interpolated to fire grid spacing at 33.3 m. The results demonstrated that the WRF SFIRE model has the ability to work with real data from Croatia and produce adequate results for forecasting fire spread. As the model in its setup has the ability to include and exclude the energy fluxes between the fire and the atmosphere, this was used to investigate possible fire-atmosphere interactions during the Split wildfire. Finally, successfully coupled simulations provided the first numerical evidence that a wildfire from the Adriatic coast region can modify the dynamical structure of the surrounding atmosphere, which agrees with observations from fire grounds. This study has demonstrated that the WRF SFIRE model has the potential for operational application in Croatia with more accurate fire predictions in the future, which could be accomplished by inserting the higher-resolution input data into the model without interpolation. Possible uses for fire management in Croatia include prediction of fire spread and intensity that may vary under changing weather conditions, available fuels and topography, planning effective and safe deployment of ground and aerial firefighting forces, preventing wildland-urban interface fires, effective planning of evacuation routes etc. In addition, the WRF SFIRE model results from this research demonstrated that the model is important for fire weather research and education purposes in order to better understand this hazardous phenomenon that occurs in Croatia.

Keywords: meteorology, agrometeorology, fire weather, wildfires, couple fire-atmosphere model

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Authors: James Beauchemin

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Research indicates that college students are experiencing mental health challenges of greater severity, and an increased number of students are seeking help. Contributing to the compromised wellness of the college student population are the prevalence of unhealthy lifestyle habits and behaviors such as alcohol consumption, tobacco use, dietary concerns, risky sexual behaviors, and lack of physical activity. Alternative approaches are needed for this population that emphasize prevention and holistic lifestyle change that mitigate mental health and wellness challenges and alleviate strain on campus resources. This presentation will introduce a Solution-Focused Wellness (SFW) intervention model and examine wellness domains solution-focused strategies to promote personal well-being, and provide supporting research from multiple studies that illustrate intervention effectiveness with a collegiate population. Given the subjective and personal nature of wellness, a therapeutic approach that provides the opportunity for individuals to conceptualize and operationalize wellness themselves is critical to facilitating lasting wellness-based change. Solution-Focused Brief Therapy (SFBT) is a strength-based modality defined by its emphasis on constructing solutions rather than focusing on problems and the assumption that clients have the resources and capacity to change. SFBT has demonstrated effectiveness as a brief therapeutic intervention with the college population in groups and related to health and wellness. By integrating SFBT strategies with personal wellness, a brief intervention was developed to support college students in establishing lifestyles trends consistent with their conceptualizations of wellness. Research supports the effectiveness of a SFW model in improving college student wellness in both face-to-face and web-based formats. Outcomes of controlled and longitudinal studies will be presented, demonstrating significant improvements in perceptions of stress, life satisfaction, happiness, mental health, well-being, and resilience. Overall, there is compelling evidence that utilization of a Solution-Focused Brief Therapy approach with college students can help to improve personal wellness and establish healthy lifestyle trends, providing an effective prevention-focused strategy for college counseling centers and wellness centers to employ. Primary research objectives include: 1)establish an evidence-based approach to facilitating wellness pro motion among the college student population, 2) examine the effectiveness of a Solution-Focused Wellness (SFW) intervention model in decreasing stress, improving personal wellness, mental health, life satisfaction, and resiliency,3) investigate intervention impacts over time (e.g. 6-week post-intervention), and 4) demonstrate SFW intervention utility in wellness promotion and associated outcomes when compared with no-treatment control, and alternative intervention approaches.

Keywords: wellness, college students, solution-focused, prevention

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Authors: Birhanu Betela Warssamo

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Background: There is limited evidence on the prevalence and risk factors for hepatitis C virus (HCV) infection among waste handlers in the Sidama region, Ethiopia; however, this knowledge is necessary for the effective prevention of HCV infection in the region. Methods: A cross-sectional study was conducted among randomly selected waste collectors from October 2021 to 30 July 2022 in different public hospitals in the Sidama region of Ethiopia. Serum samples were collected from participants and screened for anti-HCV using a rapid immunochromatography assay. Socio-demographic and risk factor information of waste handlers was gathered by pretested and well-structured questionnaires. The generalized linear model (GLM) was conducted using R software, and P-value < 0.05 was declared statistically significant. Results: From a total of 282 participating waste handlers, 16 (5.7%) (95% CI, 4.2 – 8.7) were infected with the hepatitis C virus. The educational status of waste handlers was the significant demographic variable that was associated with the hepatitis C virus (AOR = 0.055; 95% CI = 0.012 – 0.248; P = 0.000). More married waste handlers, 12 (75%), were HCV positive than unmarried, 4 (25%) and married waste handlers were 2.051 times (OR = 2.051, 95%CI = 0.644 –6.527, P = 0.295) more prone to HCV infection, compared to unmarried, which was statistically insignificant. The GLM showed that exposure to blood (OR = 8.26; 95% CI = 1.878–10.925; P = 0.037), multiple sexual partners (AOR = 3.63; 95% CI = 2.751–5.808; P = 0.001), sharp injury (AOR = 2.77; 95% CI = 2.327–3.173; P = 0.036), not using PPE (AOR = 0.77; 95% CI = 0.032–0.937; P = 0.001), contact with jaundiced patient (AOR = 3.65; 95% CI = 1.093–4.368; P = 0 .0048) and unprotected sex (AOR = 11.91; 95% CI = 5.847–16.854; P = 0.001) remained statistically significantly associated with HCV positivity. Conclusions: The study revealed that there was a high prevalence of hepatitis C virus infection among waste handlers in the Sidama region, Ethiopia. This demonstrated that there is an urgent need to increase preventative efforts and strategic policy orientations to control the spread of the hepatitis C virus.

Keywords: Hepatitis C virus, risk factors, waste handlers, prevalence, Sidama Ethiopia

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Authors: Mateusz Bilski, Jakub Klas, Emilia Kowalczyk, Sylwia Koziej, Katarzyna Kulszo, Ludmiła Grzybowska- Szatkowska

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Background: Liver metastases are a common complication of primary solid tumors and sig-nificantly reduce patient survival. In the era of increasing diagnosis of oligometastatic disease and oligoprogression, methods of local treatment of metastases, i.e. MDT, are becoming more important. Implementation of such treatment can be considered for liver metastases, which are a common complication of primary solid tumors and significantly reduce patient survival. To date, the mainstay of treatment for oligometastatic disease has been surgical resection, but not all patients qualify for the procedure. As an alternative to surgical resection, radiotherapy techniques have become available, including stereotactic body radiation therapy (SBRT) or high-dose interstitial brachytherapy (iBT). iBT is an invasive method that emits very high doses of radiation from the inside of the tumor to the outside. This technique provides better tumor coverage than SBRT while having little impact on surrounding healthy tissue and elim-inates some concerns involving respiratory motion. Methods: We conducted a systematic re-view of the scientific literature on the use of brachytherapy in the treatment of liver metasta-ses from 2018 - 2023 using PubMed and ResearchGate browsers according to PRISMA rules. Results: From 111 articles, 18 publications containing information on 729 patients with liver metastases were selected. iBT has been shown to provide high rates of tumor control. Among 14 patients with 54 unresectable RCC liver metastases, after iBT LTC was 92.6% during a median follow-up of 10.2 months, PFS was 3.4 months. In analysis of 167 patients after treatment with a single fractional dose of 15-25 Gy with brachytherapy at 6- and 12-month follow-up, LRFS rates of 88,4-88.7% and 70.7 - 71,5%, PFS of 78.1 and 53.8%, and OS of 92.3 - 96.7% and 76,3% - 79.6%, respectively, were achieved. No serious complications were observed in all patients. Distant intrahepatic progression occurred later in patients with unre-sectable liver metastases after brachytherapy (PFS: 19.80 months) than in HCC patients (PFS: 13.50 months). A significant difference in LRFS between CRC patients (84.1% vs. 50.6%) and other histologies (92.4% vs. 92.4%) was noted, suggesting a higher treatment dose is necessary for CRC patients. The average target dose for metastatic colorectal cancer was 40 - 60 Gy (compared to 100 - 250 Gy for HCC). To better assess sensitivity to therapy and pre-dict side effects, it has been suggested that humoral mediators be evaluated. It was also shown that baseline levels of TNF-α, MCP-1 and VEGF, as well as NGF and CX3CL corre-lated with both tumor volume and radiation-induced liver damage, one of the most serious complications of iBT, indicating their potential role as biomarkers of therapy outcome. Con-clusions: The use of brachytherapy methods in the treatment of liver metastases of various cancers appears to be an interesting and relatively safe therapeutic method alternative to sur-gery. An important challenge remains the selection of an appropriate brachytherapy method and radiation dose for the corresponding initial tumor type from which the metastasis origi-nated.

Keywords: liver metastases, brachytherapy, CT-HDRBT, iBT

Procedia PDF Downloads 113

Authors: Jiashu Shen

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Objectives: Spirometry is a basic reference for health evaluation which is widely used in clinical. Previous reference of spirometry is not applicable because of drastic changes of social and natural circumstance in China. A new reference values for the spirometry of the Chinese population is extremely needed. Method: Spirometric reference value was established using the statistical modeling method Generalized Additive Models for Location, Scale and Shape for forced expiratory volume in 1 s (FEV1), forced vital capacity (FVC), FEV1/FVC, and maximal mid-expiratory flow (MMEF). Results: Data from 236,606 healthy non-smokers aged 4–90 years was collected from the MJ Health Check database. Spirometry equations for FEV1, FVC, MMEF, and FEV1/FVC were established, including the predicted values and lower limits of normal (LLNs) by sex. The predictive equations that were developed for the spirometric results elaborated the relationship between spirometry and age, and they eliminated the effects of height as a variable. Most previous predictive equations for Chinese spirometry were significantly overestimated (to be exact, with mean differences of 22.21% in FEV1 and 31.39% in FVC for males, along with differences of 26.93% in FEV1 and 35.76% in FVC for females) or underestimated (with mean differences of -5.81% in MMEF and -14.56% in FEV1/FVC for males, along with a difference of -14.54% in FEV1/FVC for females) the results of lung function measurements as found in this study. Through cross-validation, our equations were established as having good fit, and the means of the measured value and the estimated value were compared, with good results. Conclusions: Our study updates the spirometric reference equations for Chinese people of all ages and provides comprehensive values for both physical examination and clinical diagnosis.

Keywords: Chinese, GAMLSS model, reference values, spirometry

Procedia PDF Downloads 133

Authors: Ora Geiger

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Reading is a cognitive process of deciphering visual signs to produce meaning. During the reading process, written information of symbols and signs is received in the person’s eye and processed in the brain. This definition is relevant to both the reading of letters and the reading of musical notation. But while the letters of the alphabet are signs determined arbitrarily, notes are recorded systematically on a staff, with the location of each note on the staff indicating its relative pitch. In this paper, the researcher specifies the characteristics of alphabet reading in comparison to musical notation reading, and discusses the question whether a person diagnosed with dyslexia will necessarily have difficulty in reading musical notes. Dyslexia is a learning disorder that makes it difficult to acquire alphabet-reading skills due to difficulties expressed in the identification of letters, spelling, and other language deciphering skills. In order to read, one must be able to connect a symbol with a sound and to join the sounds into words. A person who has dyslexia finds it difficult to translate a graphic symbol into the sound that it represents. When teaching reading to children diagnosed with dyslexia, the multi-sensory approach, supporting the activation and involvement of most of the senses in the learning process, has been found to be particularly effective. According to this approach, when most senses participate in the reading learning process, it becomes more effective. During years of experience, the researcher, who is a music specialist, has been following the music reading learning process of elementary school age students, some of them diagnosed with Dyslexia, while studying to play soprano (descant) recorder. She argues that learning music reading while studying to play a musical instrument is a multi-sensory experience by its nature. The senses involved are: sight, hearing, touch, and the kinesthetic sense (motion), which provides the brain with information on the relative positions of the body. In this way, the learner experiences simultaneously visual, auditory, tactile, and kinesthetic impressions. The researcher concludes that there should be no contra-indication for teaching standard music reading to children with dyslexia if an appropriate process is offered. This conclusion is based on two main characteristics of music reading: (1) musical notation system is a systematic, logical, relative set of symbols written on a staff; and (2) music reading learning connected with playing a musical instrument is by its nature a multi-sensory activity since it combines sight, hearing, touch, and movement. This paper describes music reading teaching procedures and provides unique teaching methods that have been found to be effective for students who were diagnosed with Dyslexia. It provides theoretical explanations in addition to guidelines for music education practices.

Keywords: alphabet reading, dyslexia, multisensory teaching method, music reading, recorder playing

Procedia PDF Downloads 363

Authors: Muhammad Faizan Chinannai, Jaeseung Lee, Mohamed Hassan Gundu, Hyunchul Ju

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Fuel cell is known to be an effective renewable energy resource which is commercializing in the present era. It is really important to know about the improvement in performance even when the system faces some defects. This study was carried out to analyze the performance of the Polymer electrolyte fuel cell (PEFCs) under different operating conditions such as current density, relative humidity and Pt loadings considering defects with load changes. The purpose of this study is to analyze the response of the fuel cell system with defects in Balance of Plants (BOPs) and catalyst layer (CL) degradation by maintaining the coolant flow rate as such to preserve the cell temperature at the required level. Multi-Scale Simulation of 3D two-phase PEFC model with coolant was carried out under different load conditions. For detailed analysis and performance comparison, extensive contours of temperature, current density, water content, and relative humidity are provided. The simulation results of the different cases are compared with the reference data. Hence the response of the fuel cell stack with defects in BOP and CL degradations can be analyzed by the temperature difference between the coolant outlet and membrane electrode assembly. The results showed that the Failure of the humidifier increases High-Frequency Resistance (HFR), air flow defects and CL degradation results in the non-uniformity of current density distribution and high cathode activation overpotential, respectively.

Keywords: PEM fuel cell, fuel cell modeling, performance analysis, BOP components, current density distribution, degradation

Procedia PDF Downloads 212

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

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Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

Procedia PDF Downloads 124

Authors: Zhi Zhang, Liling Cao, Seyedbabak Momenzadeh, Lisa Davey

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Reinforced concrete (RC) flat slab-column systems are commonly used in residential or office buildings, as the flat slab provides efficient clearance resulting in more stories at a given height than regular reinforced concrete beam-slab system. Punching shear of slab-column joints is a critical component of two-way reinforced concrete flat slab design. The unbalanced moment at the joint is transferred via slab moment and shear forces. ACI 318 provides an equation to evaluate the punching shear under the design load. It is important to note that the design code considers gravity and environmental load when considering the design load combinations, while it does not consider the effect from differential foundation settlement, which may be a governing load condition for the slab design. This paper describes how prestressed reinforced concrete slab punching shear is evaluated based on ACI 318 provisions and finite element analysis. A prestressed reinforced concrete slab under differential settlements is studied using the finite element modeling methodology. The punching shear check equation is explained. The methodology to extract data for punching shear check from the finite element model is described and correlated with the corresponding code provisions. The study indicates that the finite element analysis results should be carefully reviewed and processed in order to perform accurate punching shear evaluation. Conclusions are made based on the case studies to help engineers understand the punching shear behavior in prestressed and non-prestressed reinforced concrete slabs.

Keywords: differential settlement, finite element model, prestressed reinforced concrete slab, punching shear

Procedia PDF Downloads 128

Authors: Fadzai Munyuki

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Parental divorce is one of youth's most stressful life events and is associated with long-lasting emotional and behavioral problems. Over the last few decades, research has consistently found strong associations between divorce and adverse health effects in adolescents. Parental divorce has been hypothesized to lead to psychosocial development problems, mental health challenges, internalizing and externalizing behavior problems, and low academic performance among adolescents. This is supported by the Positive youth development theory, which states that a family setup has a major role to play in adolescent development and well-being. So, the focus of this research will be to test this hypothesized process model among adolescents in five provinces in Zimbabwe. A cross-sectional study will be conducted to test this hypothesis, and 1840 (n = 1840) adolescents aged between 14 to 17 will be employed for this study. A Stress and Questionnaire scale, a Child behavior checklist scale, and an academic concept scale will be used for this study. Data analysis will be done using Structural Equations Modeling. This study has many limitations, including the lack of a 'real-time' study, a few cross-sectional studies, a lack of a thorough and validated population measure, and many studies that have been done that have focused on one variable in relation to parental divorce. Therefore, this study seeks to bridge this gap between past research and current literature by using a validated population measure, a real-time study, and combining three latent variables in this study.

Keywords: mental health, internalizing and externalizing behavior, divorce, academic achievements

Procedia PDF Downloads 77

Authors: Milica Karadžić, Lidija Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Anamarija Mandić, Aleksandar Oklješa, Andrea Nikolić, Marija Sakač, Katarina Penov Gaši

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Using chemometric approach, the relationships between the chromatographic lipophilicity and in silico molecular descriptors for twenty-nine selected steroid derivatives were studied. The chromatographic lipophilicity was predicted using artificial neural networks (ANNs) method. The most important in silico molecular descriptors were selected applying stepwise selection (SS) paired with partial least squares (PLS) method. Molecular descriptors with satisfactory variable importance in projection (VIP) values were selected for ANN modeling. The usefulness of generated models was confirmed by detailed statistical validation. High agreement between experimental and predicted values indicated that obtained models have good quality and high predictive ability. Global sensitivity analysis (GSA) confirmed the importance of each molecular descriptor used as an input variable. High-quality networks indicate a strong non-linear relationship between chromatographic lipophilicity and used in silico molecular descriptors. Applying selected molecular descriptors and generated ANNs the good prediction of chromatographic lipophilicity of the studied steroid derivatives can be obtained. This article is based upon work from COST Actions (CM1306 and CA15222), supported by COST (European Cooperation and Science and Technology).

Keywords: artificial neural networks, chemometrics, global sensitivity analysis, liquid chromatography, steroids

Procedia PDF Downloads 344

Authors: Subham Kharel, Sudha Ravindranath, A. Vidya, B. Chandrasekaran, K. Ganesha Raj, T. Shesadri

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Digitization of urban features is a tedious and time-consuming process when done manually. In addition to this problem, Indian cities have complex habitat patterns and convoluted clustering patterns, which make it even more difficult to map features. This paper makes an attempt to classify urban objects in the satellite image using object-oriented classification techniques in which various classes such as vegetation, water bodies, buildings, and shadows adjacent to the buildings were mapped semi-automatically. Building layer obtained as a result of object-oriented classification along with already available building layers was used. The main focus, however, lay in the extraction of high-rise buildings using spatial technology, digital image processing, and modeling, which would otherwise be a very difficult task to carry out manually. Results indicated a considerable rise in the total number of buildings in the city. High-rise buildings were successfully mapped using satellite imagery, spatial technology along with logical reasoning and mathematical considerations. The results clearly depict the ability of Remote Sensing and GIS to solve complex problems in urban scenarios like studying urban sprawl and identification of more complex features in an urban area like high-rise buildings and multi-dwelling units. Object-Oriented Technique has been proven to be effective and has yielded an overall efficiency of 80 percent in the classification of high-rise buildings.

Keywords: object oriented classification, shadow extraction, high-rise buildings, satellite imagery, spatial technology

Procedia PDF Downloads 154