Search results for: raw complex data
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 28319

Search results for: raw complex data

27059 5-[Aryloxypyridyl (or Nitrophenyl)]-4H-1,2,4-Triazoles as Flexible Benzodiazepine Analogs: Synthesis, Receptor Binding Affinity and the Lipophilicity-Dependent Anti-Seizure Onset of Action

Authors: Latifeh Navidpour, Shabnam Shabani, Alireza Heidari, Manouchehr Bashiri, Azadeh Ebrahim-Habibi, Soraya Shahhosseini, Hamed Shafaroodi, Sayyed Abbas Tabatabai, Mahsa Toolabi

Abstract:

A new series of 5-(2-aryloxy-4-nitrophenyl)-4H-1,2,4-triazoles and 5-(2-aryloxy-3-pyridyl)-4H-1,2,4-triazoles, possessing C-3 thio or alkylthio substituents, was synthesized and evaluated for their benzodiazepine receptor affinity and anti-seizure activity. These analogues revealed similar to significantly superior affinity to GABAA/ benzodiazepine receptor complex (IC50 values of 0.04–4.1 nM), relative to diazepam as the reference drug (IC50 value of 2.4 nM). To determine the onset of anti-seizure activity, the time-dependent effectiveness of i.p. administration of compounds on pentylenetetrazole induced seizure threshold was studied and a very good relationship was observed between the lipophilicity (cLogP) and onset of action of studied analogues (r2 = 0.964). The minimum effective dose of the compounds, determined at the time the analogues showed their highest activity, was demonstrated to be 0.025–0.1 mg/kg, relative to diazepam (0.025 mg/kg).

Keywords: 1, 2, 4-triazole, flexible benzodiazepines, GABAA/bezodiazepine receptor complex, onset of action, PTZ induced seizure threshold

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27058 WiFi Data Offloading: Bundling Method in a Canvas Business Model

Authors: Majid Mokhtarnia, Alireza Amini

Abstract:

Mobile operators deal with increasing in the data traffic as a critical issue. As a result, a vital responsibility of the operators is to deal with such a trend in order to create added values. This paper addresses a bundling method in a Canvas business model in a WiFi Data Offloading (WDO) strategy by which some elements of the model may be affected. In the proposed method, it is supposed to sell a number of data packages for subscribers in which there are some packages with a free given volume of data-offloaded WiFi complimentary. The paper on hands analyses this method in the views of attractiveness and profitability. The results demonstrate that the quality of implementation of the WDO strongly affects the final result and helps the decision maker to make the best one.

Keywords: bundling, canvas business model, telecommunication, WiFi data offloading

Procedia PDF Downloads 193
27057 Experimental and Numerical Analysis of Mustafa Paşa Mosque in Skopje

Authors: Ozden Saygili, Eser Cakti

Abstract:

The masonry building stock in Istanbul and in other cities of Turkey are exposed to significant earthquake hazard. Determination of the safety of masonry structures against earthquakes is a complex challenge. This study deals with experimental tests and non-linear dynamic analysis of masonry structures modeled through discrete element method. The 1:10 scale model of Mustafa Paşa Mosque was constructed and the data were obtained from the sensors on it during its testing on the shake table. The results were used in the calibration/validation of the numerical model created on the basis of the 1:10 scale model built for shake table testing. 3D distinct element model was developed that represents the linear and nonlinear behavior of the shake table model as closely as possible during experimental tests. Results of numerical analyses with those from the experimental program were compared and discussed.

Keywords: dynamic analysis, non-linear modeling, shake table tests, masonry

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27056 Distributed Perceptually Important Point Identification for Time Series Data Mining

Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung

Abstract:

In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.

Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining

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27055 Effects of Training on Self-Efficacy, Competence, and Target Complaints of Dementia Family Support Program Facilitators

Authors: Myonghwa Park, Eun Jeong Choi

Abstract:

Persons with dementia living at home have complex caregiving demands, which can be significant sources of stress for the family caregivers. Thus, the dementia family support program facilitators struggle to provide various health and social services, facing diverse challenges. The purpose of this study was to research the effects of training program for the dementia family support program facilitators on self-efficacy, competence, and target complaints concerning operating their program. We created a training program with systematic contents, which was composed of 10 sessions and we provided the program for the facilitators. The participants were 32 people at 28 community dementia support centers who manage dementia family support programs and they completed quantitative and qualitative self-report questionnaire before and after participating in the training program. For analyzing the data, descriptive statistics were used and with a paired t-test, pretest and posttest scores of self-efficacy, competence, and target complaints were analyzed. We used Statistical Package for the Social Sciences (SPSS) statistics (Version 21) to analyze the data. The average age of the participants was 39.6 years old and the 84.4% of participants were nurses. There were statistically meaningful increases in facilitators’ self-efficacy scores (t = -4.45, p < .001) and competence scores (t = -2.133, p = 0.041) after participating in training program and operating their own dementia family support program. Also, the facilitators’ difficulties in conducting their dementia family support program were decreased which was assessed with target complaints. Especially, the facilitators’ lack of dementia expertise and experience was decreased statistically significantly (t = 3.520, p = 0.002). Findings provided evidence of the benefits of the training program for facilitators to enhance managing dementia family support program by improving the facilitators’ self-efficacy and competence and decreasing their difficulties regarding operating their program.

Keywords: competence, dementia, facilitator, family, self-efficacy, training

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27054 Heavy Sulphide Material Characterization of Grasberg Block Cave Mine, Mimika, Papua: Implication for Tunnel Development and Mill Issue

Authors: Cahya Wimar Wicaksono, Reynara Davin Chen, Alvian Kristianto Santoso

Abstract:

Grasberg Cu-Au ore deposit as one of the biggest porphyry deposits located in Papua Province, Indonesia produced by several intrusion that restricted by Heavy Sulphide Zone (HSZ) in peripheral. HSZ is the rock that becomes the contact between Grassberg Igneous Complex (GIC) with sedimentary and igneous rock outside, which is rich in sulphide minerals such as pyrite ± pyrrhotite. This research is to obtain the characteristic of HSZ based on geotechnical, geochemical and mineralogy aspect and those implication for daily mining operational activities. Method used in this research are geological and alteration mapping, core logging, FAA (Fire Assay Analysis), AAS (Atomic absorption spectroscopy), RQD (Rock Quality Designation) and rock water content. Data generated from methods among RQD data, mineral composition and grade, lithological and structural geology distribution in research area. The mapping data show that HSZ material characteristics divided into three type based on rocks association, there are near igneous rocks, sedimentary rocks and on HSZ area. And also divided based on its location, north and south part of research area. HSZ material characteristic consist of rock which rich of pyrite ± pyrrhotite, and RQD range valued about 25%-100%. Pyrite ± pyrrhotite which outcropped will react with H₂O and O₂ resulting acid that generates corrosive effect on steel wire and rockbolt. Whereas, pyrite precipitation proses in HSZ forming combustible H₂S gas which is harmful during blasting activities. Furthermore, the impact of H₂S gas in blasting activities is forming poison gas SO₂. Although HSZ high grade Cu-Au, however those high grade Cu-Au rich in sulphide components which is affected in flotation milling process. Pyrite ± pyrrhotite in HSZ will chemically react with Cu-Au that will settle in milling process instead of floating.

Keywords: combustible, corrosive, heavy sulphide zone, pyrite ± pyrrhotite

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27053 Analysing Techniques for Fusing Multimodal Data in Predictive Scenarios Using Convolutional Neural Networks

Authors: Philipp Ruf, Massiwa Chabbi, Christoph Reich, Djaffar Ould-Abdeslam

Abstract:

In recent years, convolutional neural networks (CNN) have demonstrated high performance in image analysis, but oftentimes, there is only structured data available regarding a specific problem. By interpreting structured data as images, CNNs can effectively learn and extract valuable insights from tabular data, leading to improved predictive accuracy and uncovering hidden patterns that may not be apparent in traditional structured data analysis. In applying a single neural network for analyzing multimodal data, e.g., both structured and unstructured information, significant advantages in terms of time complexity and energy efficiency can be achieved. Converting structured data into images and merging them with existing visual material offers a promising solution for applying CNN in multimodal datasets, as they often occur in a medical context. By employing suitable preprocessing techniques, structured data is transformed into image representations, where the respective features are expressed as different formations of colors and shapes. In an additional step, these representations are fused with existing images to incorporate both types of information. This final image is finally analyzed using a CNN.

Keywords: CNN, image processing, tabular data, mixed dataset, data transformation, multimodal fusion

Procedia PDF Downloads 116
27052 Material Chemistry Level Deformation and Failure in Cementitious Materials

Authors: Ram V. Mohan, John Rivas-Murillo, Ahmed Mohamed, Wayne D. Hodo

Abstract:

Cementitious materials, an excellent example of highly complex, heterogeneous material systems, are cement-based systems that include cement paste, mortar, and concrete that are heavily used in civil infrastructure; though commonly used are one of the most complex in terms of the material morphology and structure than most materials, for example, crystalline metals. Processes and features occurring at the nanometer sized morphological structures affect the performance, deformation/failure behavior at larger length scales. In addition, cementitious materials undergo chemical and morphological changes gaining strength during the transient hydration process. Hydration in cement is a very complex process creating complex microstructures and the associated molecular structures that vary with hydration. A fundamental understanding can be gained through multi-scale level modeling for the behavior and properties of cementitious materials starting from the material chemistry level atomistic scale to further explore their role and the manifested effects at larger length and engineering scales. This predictive modeling enables the understanding, and studying the influence of material chemistry level changes and nanomaterial additives on the expected resultant material characteristics and deformation behavior. Atomistic-molecular dynamic level modeling is required to couple material science to engineering mechanics. Starting at the molecular level a comprehensive description of the material’s chemistry is required to understand the fundamental properties that govern behavior occurring across each relevant length scale. Material chemistry level models and molecular dynamics modeling and simulations are employed in our work to describe the molecular-level chemistry features of calcium-silicate-hydrate (CSH), one of the key hydrated constituents of cement paste, their associated deformation and failure. The molecular level atomic structure for CSH can be represented by Jennite mineral structure. Jennite has been widely accepted by researchers and is typically used to represent the molecular structure of the CSH gel formed during the hydration of cement clinkers. This paper will focus on our recent work on the shear and compressive deformation and failure behavior of CSH represented by Jennite mineral structure that has been widely accepted by researchers and is typically used to represent the molecular structure of CSH formed during the hydration of cement clinkers. The deformation and failure behavior under shear and compression loading deformation in traditional hydrated CSH; effect of material chemistry changes on the predicted stress-strain behavior, transition from linear to non-linear behavior and identify the on-set of failure based on material chemistry structures of CSH Jennite and changes in its chemistry structure will be discussed.

Keywords: cementitious materials, deformation, failure, material chemistry modeling

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27051 Reliability and Validity of a Portable Inertial Sensor and Pressure Mat System for Measuring Dynamic Balance Parameters during Stepping

Authors: Emily Rowe

Abstract:

Introduction: Balance assessments can be used to help evaluate a person’s risk of falls, determine causes of balance deficits and inform intervention decisions. It is widely accepted that instrumented quantitative analysis can be more reliable and specific than semi-qualitative ordinal scales or itemised scoring methods. However, the uptake of quantitative methods is hindered by expense, lack of portability, and set-up requirements. During stepping, foot placement is actively coordinated with the body centre of mass (COM) kinematics during pre-initiation. Based on this, the potential to use COM velocity just prior to foot off and foot placement error as an outcome measure of dynamic balance is currently being explored using complex 3D motion capture. Inertial sensors and pressure mats might be more practical technologies for measuring these parameters in clinical settings. Objective: The aim of this study was to test the criterion validity and test-retest reliability of a synchronised inertial sensor and pressure mat-based approach to measure foot placement error and COM velocity while stepping. Methods: Trials were held with 15 healthy participants who each attended for two sessions. The trial task was to step onto one of 4 targets (2 for each foot) multiple times in a random, unpredictable order. The stepping target was cued using an auditory prompt and electroluminescent panel illumination. Data was collected using 3D motion capture and a combined inertial sensor-pressure mat system simultaneously in both sessions. To assess the reliability of each system, ICC estimates and their 95% confident intervals were calculated based on a mean-rating (k = 2), absolute-agreement, 2-way mixed-effects model. To test the criterion validity of the combined inertial sensor-pressure mat system against the motion capture system multi-factorial two-way repeated measures ANOVAs were carried out. Results: It was found that foot placement error was not reliably measured between sessions by either system (ICC 95% CIs; motion capture: 0 to >0.87 and pressure mat: <0.53 to >0.90). This could be due to genuine within-subject variability given the nature of the stepping task and brings into question the suitability of average foot placement error as an outcome measure. Additionally, results suggest the pressure mat is not a valid measure of this parameter since it was statistically significantly different from and much less precise than the motion capture system (p=0.003). The inertial sensor was found to be a moderately reliable (ICC 95% CIs >0.46 to >0.95) but not valid measure for anteroposterior and mediolateral COM velocities (AP velocity: p=0.000, ML velocity target 1 to 4: p=0.734, 0.001, 0.000 & 0.376). However, it is thought that with further development, the COM velocity measure validity could be improved. Possible options which could be investigated include whether there is an effect of inertial sensor placement with respect to pelvic marker placement or implementing more complex methods of data processing to manage inherent accelerometer and gyroscope limitations. Conclusion: The pressure mat is not a suitable alternative for measuring foot placement errors. The inertial sensors have the potential for measuring COM velocity; however, further development work is needed.

Keywords: dynamic balance, inertial sensors, portable, pressure mat, reliability, stepping, validity, wearables

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27050 Determination of Poisson’s Ratio and Elastic Modulus of Compression Textile Materials

Authors: Chongyang Ye, Rong Liu

Abstract:

Compression textiles such as compression stockings (CSs) have been extensively applied for the prevention and treatment of chronic venous insufficiency of lower extremities. The involvement of multiple mechanical factors such as interface pressure, frictional force, and elastic materials make the interactions between lower limb and CSs to be complex. Determination of Poisson’s ratio and elastic moduli of CS materials are critical for constructing finite element (FE) modeling to numerically simulate a complex interactive system of CS and lower limb. In this study, a mixed approach, including an analytic model based on the orthotropic Hooke’s Law and experimental study (uniaxial tension testing and pure shear testing), has been proposed to determine Young’s modulus, Poisson’s ratio, and shear modulus of CS fabrics. The results indicated a linear relationship existing between the stress and strain properties of the studied CS samples under controlled stretch ratios (< 100%). The newly proposed method and the determined key mechanical properties of elastic orthotropic CS fabrics facilitate FE modeling for analyzing in-depth the effects of compression material design on their resultant biomechanical function in compression therapy.

Keywords: elastic compression stockings, Young’s modulus, Poisson’s ratio, shear modulus, mechanical analysis

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27049 Knowledge Discovery and Data Mining Techniques in Textile Industry

Authors: Filiz Ersoz, Taner Ersoz, Erkin Guler

Abstract:

This paper addresses the issues and technique for textile industry using data mining techniques. Data mining has been applied to the stitching of garments products that were obtained from a textile company. Data mining techniques were applied to the data obtained from the CHAID algorithm, CART algorithm, Regression Analysis and, Artificial Neural Networks. Classification technique based analyses were used while data mining and decision model about the production per person and variables affecting about production were found by this method. In the study, the results show that as the daily working time increases, the production per person also decreases. In addition, the relationship between total daily working and production per person shows a negative result and the production per person show the highest and negative relationship.

Keywords: data mining, textile production, decision trees, classification

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27048 Assessment of cellulase and xylanase Production by chryseobacterium sp. Isolated from Decaying Biomass in Alice, Eastern Cape, South Africa

Authors: A. Nkohla, U. Nwodo, L. V. Mabinya, A. I. Okoh

Abstract:

A potential source for low-cost production of value added products is the utilization of lignocellulosic materials. However, the huddle needing breaching would be the dismantlement of the complex lignocellulosic structure as to free sugar base therein. the current lignocellosic material treatment process is expensive and not eco-friendly hence, the advocacy for enzyme based technique which is both cheap and eco-friendly is highly imperative. Consequently, this study aimed at the screening of cellulose and xylan degrading bacterial strain isolated from decaying sawdust samples. This isolate showed high activity for cellulase and xylanase when grown on carboxymethyl cellulose and birtchwood xylan as the sole carbon source respectively. The 16S rDNA nucleotide sequence of the isolate showed 98% similarity with that of Chryseobacterium taichungense thus, it was identified as a Chryseobacterium sp. Optimum culture conditions for cellulase and xylanase production were medium pH 6, incubation temperature of 25 °C at 50 rpm and medium pH 6, incubation temperature of 25 °C at 150 rpm respectively. The high enzyme activity obtained from this bacterial strain portends it as a good candidate for industrial use in the degradation of complex biomass for value added products.

Keywords: lignocellulosic material, chryseobacterium sp., submerged fermentation, cellulase, xylanase

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27047 Gaits Stability Analysis for a Pneumatic Quadruped Robot Using Reinforcement Learning

Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

Abstract:

Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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27046 The Syllable Structure and Syllable Processes in Suhwa Arabic: An Autosegmental Analysis

Authors: Muhammad Yaqub Olatunde

Abstract:

Arabic linguistic science is redirecting its focus towards the analysis and description of social, regional, and temporal varieties of social, regional, and temporal varieties in order to show how they vary in pronunciation, vocabulary, and grammar. This is not to say that the traditional Arabic linguists did not mention scores of dialectical variations but such works focused on the geographical boundaries of the Arabic speaking countries. There is need for a comprehensive survey of various Arabic dialects within the boundary of Arabic speaking countries and outside showing both the similarities and differences of linguistic and extra linguistic elements. This study therefore examines the syllable structure and process in noun and verb in the shuwa Arabic dialect speaking in North East Nigeria [mainly in Borno state]. The work seeks to establish the facts about this phenomenon, using auto- segmental analysis. These facts are compared, where necessary; using possible alternative analysis, with what operate in other related dialects within and outside Arabic speaking countries. The interaction between epenthesis and germination in the language also generate an interesting issue. The paper then conclude that syllable structure and process in the language need to recognize the existence of complex onset and a complex rhyme producing a consonant cluster in the former and a closed syllable in the letter. This emerges as result of resyllabification, which is motivated by these processes.

Keywords: Arabic, dialect, linguistics, processes, resyllabification

Procedia PDF Downloads 417
27045 Investigation of Delivery of Triple Play Data in GE-PON Fiber to the Home Network

Authors: Ashima Anurag Sharma

Abstract:

Optical fiber based networks can deliver performance that can support the increasing demands for high speed connections. One of the new technologies that have emerged in recent years is Passive Optical Networks. This research paper is targeted to show the simultaneous delivery of triple play service (data, voice, and video). The comparison between various data rates is presented. It is demonstrated that as we increase the data rate, number of users to be decreases due to increase in bit error rate.

Keywords: BER, PON, TDMPON, GPON, CWDM, OLT, ONT

Procedia PDF Downloads 522
27044 Combined Orthodontic and Restorative Management of Complex Cases: Concepts and Case Reports

Authors: Awais Ali, Hesham Ali

Abstract:

The absence of teeth through either premature loss or developmental absence is a common condition with potentially severe impact on affected individuals. Management of these cases presents a clinical challenge which may be difficult to resolve given the effects of tooth loss or hypodontia over the course of a patient’s lifetime. Treatment of such cases is often best provided by a multi-disciplinary team, where the patient’s expectations and care delivery can be optimally managed. Orthodontic treatment is often used to prepare the dentition in advance of restorative replacement of missing teeth. Conversely, the placement of implants may precede the delivery of orthodontic treatment and indeed may function as an adjunctive orthodontic procedure. We discuss the use of both approaches here and illustrate their clinical implementation with two case reports. The first case demonstrates the use of fixed appliances to prepare the mouth for an opposing implant-retained complete denture. A second case demonstrates the use of implant-retained crowns to provide orthodontic anchorage in a partially dentate patient. We propose that complex cases such as these should always be planned and treated by a multi-disciplinary team in order to optimise the delivery of care, patient experience, and treatment outcome. The presented cases add to the body of evidence in this area.

Keywords: orthodontics, dental implantology, hypodontia, multi-disciplinary

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27043 Understanding the Classification of Rain Microstructure and Estimation of Z-R Relationship using a Micro Rain Radar in Tropical Region

Authors: Tomiwa, Akinyemi Clement

Abstract:

Tropical regions experience diverse and complex precipitation patterns, posing significant challenges for accurate rainfall estimation and forecasting. This study addresses the problem of effectively classifying tropical rain types and refining the Z-R (Reflectivity-Rain Rate) relationship to enhance rainfall estimation accuracy. Through a combination of remote sensing, meteorological analysis, and machine learning, the research aims to develop an advanced classification framework capable of distinguishing between different types of tropical rain based on their unique characteristics. This involves utilizing high-resolution satellite imagery, radar data, and atmospheric parameters to categorize precipitation events into distinct classes, providing a comprehensive understanding of tropical rain systems. Additionally, the study seeks to improve the Z-R relationship, a crucial aspect of rainfall estimation. One year of rainfall data was analyzed using a Micro Rain Radar (MRR) located at The Federal University of Technology Akure, Nigeria, measuring rainfall parameters from ground level to a height of 4.8 km with a vertical resolution of 0.16 km. Rain rates were classified into low (stratiform) and high (convective) based on various microstructural attributes such as rain rates, liquid water content, Drop Size Distribution (DSD), average fall speed of the drops, and radar reflectivity. By integrating diverse datasets and employing advanced statistical techniques, the study aims to enhance the precision of Z-R models, offering a more reliable means of estimating rainfall rates from radar reflectivity data. This refined Z-R relationship holds significant potential for improving our understanding of tropical rain systems and enhancing forecasting accuracy in regions prone to heavy precipitation.

Keywords: remote sensing, precipitation, drop size distribution, micro rain radar

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27042 Data Science-Based Key Factor Analysis and Risk Prediction of Diabetic

Authors: Fei Gao, Rodolfo C. Raga Jr.

Abstract:

This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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27041 The Gap between Curriculum, Pedagogy, and National Standards of Vietnamese English Language Teacher Education

Authors: Thi Phuong Lan Nguyen

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Vietnamese English Language Teacher Education (ELTE) has been changing a lot in response to the rapidly evolving socio-economic context requirements. The Vietnamese government assigns the Ministry of Education and Training (MOET) primary tasks to have policy changes to prepare for ELTE development in the globalization and socialization process. Many educational policies have been made to develop ELTE, however, they seem not to address the new global or social demands. The issue is that there are still significant disparities between the national policy and the institutional implementation. This study is to investigate the alignment between ELTE institutional curriculum, pedagogies, and MOET standards. This study used a mixed-method with the data sources from policy documents, a survey, and 33 interviews conducted with the lecturers and administrators from eleven Vietnamese ELTE institutions. The data have been analysed to understand the gap between policy and practice. The initial findings are (i) a low alignment of curriculum and language proficiency standards and (ii) a moderate alignment between curriculum and future-career skills standards. Many pedagogical challenges have been found. In order to address these gaps, it is necessary for the curriculum to be standards-based designed. It is also vital for professional development in order to improve the quality teaching. The study offers multiple perspectives on a complex issue. The study is meaningful not only to educational governance, but also to teaching practitioners, English language researchers, and English language learners. The significance lies in its relevance to English teaching careers across all parts of Vietnam, it yet remains relevant to ELTE in other countries teaching English as a foreign language.

Keywords: alignment, curriculum, educational policy, English language teaching, pedagogy, standards

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27040 Study of the Formation Mechanism of Dipalmitoylphosphatidylcholine Liposomes and Calcium Ion Complexes

Authors: T. Mdzinarashvili, M. Khvedelidze, E. Shekiladze, S. Chinchaladze, M. Mdzinarashvili

Abstract:

The study of the possible interaction between calcium ions and lipids is of great importance for the studies of complexes of calcium drug-carrying nanoparticles. We prepared calcium-containing complex liposomes from Dipalmitoylphosphatidylcholine (DPPC) lipids and studied their thermodynamic properties. In calorimetric studies, we determined that the phase transition temperature of these complexes is close to 420 C. It was shown that both hydrophobic and hydrophilic connections take part in the formation of calcium nanoparticles. We were interested in hydrophilic bonds represented by hydrogen bonds. We have shown that these hydrogen bonds are formed between the phospholipid heads, and the main contributor is the oxygen atoms in the phosphoric acid residues. In addition, based on the amount of heat absorbed during the breaking of hydrogen bonds formed between calcium-containing nanoparticle complexes, it can be concluded that the hydrogen atoms in the head of DPPC lipids form hydrogen bonds between P=O and P-O groups of phosphate. The energy of heat absorption measured by the calorimeter is of the order obtained by breaking the hydrogen bonds we have specified. Thus, we conclude that our approach to the model of liposome formation from lipids is correct. As for calcium atoms - due to the fact that it is present in the form of positive ions in the liposome, they will connect only with negatively charged phosphorus ions.

Keywords: DPPC, liposomes, calcium, complex nanoparticles

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27039 Investigation of the Main Trends of Tourist Expenses in Georgia

Authors: Nino Abesadze, Marine Mindorashvili, Nino Paresashvili

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The main purpose of the article is to make complex statistical analysis of tourist expenses of foreign visitors. We used mixed technique of selection that implies rules of random and proportional selection. Computer software SPSS was used to compute statistical data for corresponding analysis. Corresponding methodology of tourism statistics was implemented according to international standards. Important information was collected and grouped from the major Georgian airports. Techniques of statistical observation were prepared. A representative population of foreign visitors and a rule of selection of respondents were determined. We have a trend of growth of tourist numbers and share of tourists from post-soviet countries constantly increases. Level of satisfaction with tourist facilities and quality of service has grown, but still we have a problem of disparity between quality of service and prices. The design of tourist expenses of foreign visitors is diverse; competitiveness of tourist products of Georgian tourist companies is higher.

Keywords: tourist, expenses, methods, statistics, analysis

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27038 Big Data Analytics and Data Security in the Cloud via Fully Homomorphic Encryption

Authors: Waziri Victor Onomza, John K. Alhassan, Idris Ismaila, Noel Dogonyaro Moses

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This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute theoretical presentations in high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.

Keywords: big data analytics, security, privacy, bootstrapping, homomorphic, homomorphic encryption scheme

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27037 The Osteocutaneous Distal Tibia Turn-over Fillet Flap: A Novel Spare-parts Orthoplastic Surgery Option for Functional Below-knee Amputation

Authors: Harry Burton, Alexios Dimitrios Iliadis, Neil Jones, Aaron Saini, Nicola Bystrzonowski, Alexandros Vris, Georgios Pafitanis

Abstract:

This article portrays the authors’ experience with a complex lower limb bone and soft tissue defect, following chronic osteomyelitis and pathological fracture, which was managed by the multidisciplinary orthoplastic team. The decision for functional amputation versus limb salvage was deemed necessary, enhanced by the principles of “spares parts” in reconstructive microsurgery. This case describes a successful use of the osteocutaneous distal tibia turn-over fillet flap that allowed ‘lowering the level of the amputation’ from a through knee to the conventional level of a below-knee amputation to preserve the knee joint function. This case demonstrates the value of ‘spare-parts’ surgery principles and how these concepts refine complex orthoplastic approaches when limb salvage is not possible to enhance function. The osteocutaneous distal tibia turn-over fillet flap is a robust technique for modified BKA reconstructions that provides sufficient bone length to achieve a tough, sensate stump and functional knee joint.

Keywords: osteocutaneous flap, fillet flap, spare-parts surgery, Below knee amputation

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27036 Facial Pose Classification Using Hilbert Space Filling Curve and Multidimensional Scaling

Authors: Mekamı Hayet, Bounoua Nacer, Benabderrahmane Sidahmed, Taleb Ahmed

Abstract:

Pose estimation is an important task in computer vision. Though the majority of the existing solutions provide good accuracy results, they are often overly complex and computationally expensive. In this perspective, we propose the use of dimensionality reduction techniques to address the problem of facial pose estimation. Firstly, a face image is converted into one-dimensional time series using Hilbert space filling curve, then the approach converts these time series data to a symbolic representation. Furthermore, a distance matrix is calculated between symbolic series of an input learning dataset of images, to generate classifiers of frontal vs. profile face pose. The proposed method is evaluated with three public datasets. Experimental results have shown that our approach is able to achieve a correct classification rate exceeding 97% with K-NN algorithm.

Keywords: machine learning, pattern recognition, facial pose classification, time series

Procedia PDF Downloads 346
27035 Protecting Privacy and Data Security in Online Business

Authors: Bilquis Ferdousi

Abstract:

With the exponential growth of the online business, the threat to consumers’ privacy and data security has become a serious challenge. This literature review-based study focuses on a better understanding of those threats and what legislative measures have been taken to address those challenges. Research shows that people are increasingly involved in online business using different digital devices and platforms, although this practice varies based on age groups. The threat to consumers’ privacy and data security is a serious hindrance in developing trust among consumers in online businesses. There are some legislative measures taken at the federal and state level to protect consumers’ privacy and data security. The study was based on an extensive review of current literature on protecting consumers’ privacy and data security and legislative measures that have been taken.

Keywords: privacy, data security, legislation, online business

Procedia PDF Downloads 99
27034 Use of Two-Dimensional Hydraulics Modeling for Design of Erosion Remedy

Authors: Ayoub. El Bourtali, Abdessamed.Najine, Amrou Moussa. Benmoussa

Abstract:

One of the main goals of river engineering is river training, which is defined as controlling and predicting the behavior of a river. It is taking effective measurements to eliminate all related risks and thus improve the river system. In some rivers, the riverbed continues to erode and degrade; therefore, equilibrium will never be reached. Generally, river geometric characteristics and riverbed erosion analysis are some of the most complex but critical topics in river engineering and sediment hydraulics; riverbank erosion is the second answering process in hydrodynamics, which has a major impact on the ecological chain and socio-economic process. This study aims to integrate the new computer technology that can analyze erosion and hydraulic problems through computer simulation and modeling. Choosing the right model remains a difficult and sensitive job for field engineers. This paper makes use of the 5.0.4 version of the HEC-RAS model. The river section is adopted according to the gauged station and the proximity of the adjustment. In this work, we will demonstrate how 2D hydraulic modeling helped clarify the design and cover visuals to set up depth and velocities at riverbanks and throughout advanced structures. The hydrologic engineering center's-river analysis system (HEC-RAS) 2D model was used to create a hydraulic study of the erosion model. The geometric data were generated from the 12.5-meter x 12.5-meter resolution digital elevation model. In addition to showing eroded or overturned river sections, the model output also shows patterns of riverbank changes, which can help us reduce problems caused by erosion.

Keywords: 2D hydraulics model, erosion, floodplain, hydrodynamic, HEC-RAS, riverbed erosion, river morphology, resolution digital data, sediment

Procedia PDF Downloads 184
27033 Flowing Online Vehicle GPS Data Clustering Using a New Parallel K-Means Algorithm

Authors: Orhun Vural, Oguz Bayat, Rustu Akay, Osman N. Ucan

Abstract:

This study presents a new parallel approach clustering of GPS data. Evaluation has been made by comparing execution time of various clustering algorithms on GPS data. This paper aims to propose a parallel based on neighborhood K-means algorithm to make it faster. The proposed parallelization approach assumes that each GPS data represents a vehicle and to communicate between vehicles close to each other after vehicles are clustered. This parallelization approach has been examined on different sized continuously changing GPS data and compared with serial K-means algorithm and other serial clustering algorithms. The results demonstrated that proposed parallel K-means algorithm has been shown to work much faster than other clustering algorithms.

Keywords: parallel k-means algorithm, parallel clustering, clustering algorithms, clustering on flowing data

Procedia PDF Downloads 217
27032 An Analysis of Privacy and Security for Internet of Things Applications

Authors: Dhananjay Singh, M. Abdullah-Al-Wadud

Abstract:

The Internet of Things is a concept of a large scale ecosystem of wireless actuators. The actuators are defined as things in the IoT, those which contribute or produces some data to the ecosystem. However, ubiquitous data collection, data security, privacy preserving, large volume data processing, and intelligent analytics are some of the key challenges into the IoT technologies. In order to solve the security requirements, challenges and threats in the IoT, we have discussed a message authentication mechanism for IoT applications. Finally, we have discussed data encryption mechanism for messages authentication before propagating into IoT networks.

Keywords: Internet of Things (IoT), message authentication, privacy, security

Procedia PDF Downloads 378
27031 Development of Building Information Modeling in Property Industry: Beginning with Building Information Modeling Construction

Authors: B. Godefroy, D. Beladjine, K. Beddiar

Abstract:

In France, construction BIM actors commonly evoke the BIM gains for exploitation by integrating of the life cycle of a building. The standardization of level 7 of development would achieve this stage of the digital model. The householders include local public authorities, social landlords, public institutions (health and education), enterprises, facilities management companies. They have a dual role: owner and manager of their housing complex. In a context of financial constraint, the BIM of exploitation aims to control costs, make long-term investment choices, renew the portfolio and enable environmental standards to be met. It assumes a knowledge of the existing buildings, marked by its size and complexity. The information sought must be synthetic and structured, it concerns, in general, a real estate complex. We conducted a study with professionals about their concerns and ways to use it to see how householders could benefit from this development. To obtain results, we had in mind the recurring interrogation of the project management, on the needs of the operators, we tested the following stages: 1) Inculcate a minimal culture of BIM with multidisciplinary teams of the operator then by business, 2) Learn by BIM tools, the adaptation of their trade in operations, 3) Understand the place and creation of a graphic and technical database management system, determine the components of its library so their needs, 4) Identify the cross-functional interventions of its managers by business (operations, technical, information system, purchasing and legal aspects), 5) Set an internal protocol and define the BIM impact in their digital strategy. In addition, continuity of management by the integration of construction models in the operation phase raises the question of interoperability in the control of the production of IFC files in the operator’s proprietary format and the export and import processes, a solution rivaled by the traditional method of vectorization of paper plans. Companies that digitize housing complex and those in FM produce a file IFC, directly, according to their needs without recourse to the model of construction, they produce models business for the exploitation. They standardize components, equipment that are useful for coding. We observed the consequences resulting from the use of the BIM in the property industry and, made the following observations: a) The value of data prevail over the graphics, 3D is little used b) The owner must, through his organization, promote the feedback of technical management information during the design phase c) The operator's reflection on outsourcing concerns the acquisition of its information system and these services, observing the risks and costs related to their internal or external developments. This study allows us to highlight: i) The need for an internal organization of operators prior to a response to the construction management ii) The evolution towards automated methods for creating models dedicated to the exploitation, a specialization would be required iii) A review of the communication of the project management, management continuity not articulating around his building model, it must take into account the environment of the operator and reflect on its scope of action.

Keywords: information system, interoperability, models for exploitation, property industry

Procedia PDF Downloads 141
27030 Mechanical Cortical Bone Characterization with the Finite Element Method Based Inverse Method

Authors: Djamel Remache, Marie Semaan, Cécile Baron, Martine Pithioux, Patrick Chabrand, Jean-Marie Rossi, Jean-Louis Milan

Abstract:

Cortical bone is a complex multi-scale structure. Even though several works have contributed significantly to understanding its mechanical behavior, this behavior remains poorly understood. Nanoindentation testing is one of the primary testing techniques for the mechanical characterization of bone at small scales. The purpose of this study was to provide new nanoindentation data of cortical bovine bone in different directions and at different bone microstructures (osteonal, interstitial and laminar bone), and then to identify anisotropic properties of samples with FEM (finite element method) based inverse method. Experimentally and numerical results were compared. Experimental and numerical results were compared. The results compared were in good agreement.

Keywords: mechanical behavior of bone, nanoindentation, finite element analysis, inverse optimization approach

Procedia PDF Downloads 330