Search results for: statistical tools
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7698

Search results for: statistical tools

7488 On Mathematical Modelling and Optimization of Emerging Trends Processes in Advanced Manufacturing

Authors: Agarana Michael C., Akinlabi Esther T., Pule Kholopane

Abstract:

Innovation in manufacturing process technologies and associated product design affects the prospects for manufacturing today and in near future. In this study some theoretical methods, useful as tools in advanced manufacturing, are considered. In particular, some basic Mathematical, Operational Research, Heuristic, and Statistical techniques are discussed. These techniques/methods are very handy in many areas of advanced manufacturing processes, including process planning optimization, modelling and analysis. Generally the production rate requires the application of Mathematical methods. The Emerging Trends Processes in Advanced Manufacturing can be enhanced by using Mathematical Modelling and Optimization techniques.

Keywords: mathematical modelling, optimization, emerging trends, advanced manufacturing

Procedia PDF Downloads 299
7487 Crashworthiness Optimization of an Automotive Front Bumper in Composite Material

Authors: S. Boria

Abstract:

In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: composite material, crashworthiness, finite element analysis, optimization

Procedia PDF Downloads 256
7486 Packet Analysis in Network Forensics: Insights, Tools, and Case Study

Authors: Dalal Nasser Fathi, Amal Saud Al-Mutairi, Mada Hamed Al-Towairqi, Enas Fawzi Khairallah

Abstract:

Network forensics is essential for investigating cyber incidents and detecting malicious activities by analyzing network traffic, with a focus on packet and protocol data. This process involves capturing, filtering, and examining network data to identify patterns and signs of attacks. Packet analysis, a core technique in this field, provides insights into the origins of data, the protocols used, and any suspicious payloads, which aids in detecting malicious activity. This paper explores network forensics, providing guidance for the analyst on what to look for and identifying attack sites guided by the seven layers of the OSI model. Additionally, it explains the most commonly used tools in network forensics and demonstrates a practical example using Wireshark.

Keywords: network forensic, packet analysis, Wireshark tools, forensic investigation, digital evidence

Procedia PDF Downloads 8
7485 Forecasting the Influences of Information and Communication Technology on the Structural Changes of Japanese Industrial Sectors: A Study Using Statistical Analysis

Authors: Ubaidillah Zuhdi, Shunsuke Mori, Kazuhisa Kamegai

Abstract:

The purpose of this study is to forecast the influences of Information and Communication Technology (ICT) on the structural changes of Japanese economies based on Leontief Input-Output (IO) coefficients. This study establishes a statistical analysis to predict the future interrelationships among industries. We employ the Constrained Multivariate Regression (CMR) model to analyze the historical changes of input-output coefficients. Statistical significance of the model is then tested by Likelihood Ratio Test (LRT). In our model, ICT is represented by two explanatory variables, i.e. computers (including main parts and accessories) and telecommunications equipment. A previous study, which analyzed the influences of these variables on the structural changes of Japanese industrial sectors from 1985-2005, concluded that these variables had significant influences on the changes in the business circumstances of Japanese commerce, business services and office supplies, and personal services sectors. The projected future Japanese economic structure based on the above forecast generates the differentiated direct and indirect outcomes of ICT penetration.

Keywords: forecast, ICT, industrial structural changes, statistical analysis

Procedia PDF Downloads 375
7484 Improving Automotive Efficiency through Lean Management Tools: A Case Study

Authors: Raed El-Khalil, Hussein Zeaiter

Abstract:

Managing and improving efficiency in the current highly competitive global automotive industry demands that companies adopt leaner and more flexible systems. During the past 20 years the domestic automotive industry in North America has been focusing on establishing new management strategies in order to meet market demands. 98The lean management process also known as Toyota Manufacturing Process (TPS) or lean manufacturing encompasses tools and techniques that were established in order to provide the best quality product with the fastest lead time at the lowest cost. The following paper presents a study that focused on improving labor efficiency at one of the Big Three (Ford, GM, Chrysler LLC) domestic automotive facility in North America. The objective of the study was to utilize several lean management tools in order to optimize the efficiency and utilization levels at the “Pre-Marriage” chassis area in a truck manufacturing and assembly facility. Utilizing three different lean tools (i.e. Standardization of work, 7 Wastes, and 5S) this research was able to improve efficiency by 51%, utilization by 246%, and reduce operations by 14%. The return on investment calculated based on the improvements made was 284%.

Keywords: lean manufacturing, standardized work, operation efficiency, utilization

Procedia PDF Downloads 522
7483 An Adjusted Network Information Criterion for Model Selection in Statistical Neural Network Models

Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

Abstract:

In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

Procedia PDF Downloads 570
7482 The Effect of Mobile Technology Use in Education: A Meta-Analysis Study

Authors: Şirin Küçük, Ayşe Kök, İsmail Şahin

Abstract:

Mobile devices are very popular and useful tools for assisting people in daily life. With the advancement of mobile technologies, the issue of mobile learning has been widely investigated in education. Many researches consider that it is important to integrate pedagogical and technical strengths of mobile technology into learning environments. For this reason, the purpose of this research is to examine the effect of mobile technology use in education with meta-analysis method. Meta-analysis is a statistical technique which combines the findings of independent studies in a specific subject. In this respect, the articles will be examined by searching the databases for researches which are conducted between 2005 and 2014. It is expected that the results of this research will contribute to future research related to mobile technology use in education.

Keywords: mobile learning, meta-analysis, mobile technology, education

Procedia PDF Downloads 721
7481 Next Generation Radiation Risk Assessment and Prediction Tools Generation Applying AI-Machine (Deep) Learning Algorithms

Authors: Selim M. Khan

Abstract:

Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

Procedia PDF Downloads 98
7480 The Development of a Cyber Violence Measurement Tool for Youths: A Multi-Reporting of Ecological Factors

Authors: Jong-Hyo Park, Eunyoung Choi, Jae-Yeon Lim, Seon-Suk Lee, Yeong-Rong Koo, Ji-Ung Kwon, Kyung-Sung Kim, Jong-Ik Lee, Juhan Park, Hyun-Kyu Lee, Won-Kyoung Oh, Jisang Lee, Jiwon Choe

Abstract:

Due to COVID-19, cyber violence among youths has soared as they spend more time online than before. In contrast to the deepening concerns, measurement tools that can assess the vulnerability of cyber violence in individual youths still need to be supplemented. The measurement tools lack consideration of various factors related to cyber violence among youths. Most of the tools are self-report questionnaires, and these adolescents' self-report questionnaire forms can underestimate the harmful behavior and overestimate the damage experience. Therefore, this study aims to develop a multi-report measurement tool for youths that can reliably measure individuals' ecological factors related to cyber violence. The literature review explored factors related to cyber violence, and the questions were constructed. The face validity of the questions was confirmed by conducting focus group interviews. Exploratory and confirmatory factor analyses (N=671) were also conducted for statistical validation. This study developed a multi-report measurement tool for cyber violence with 161 questions, consisting of six domains: online behavior, cyber violence awareness, victimization-perpetration-witness experience, coping efficacy (individuals, peers, teachers, and parents), psychological characteristics, and pro-social capabilities. In addition to self-report from a youth respondent, this measurement tool includes peers, teachers, and parents reporting for the respondent. It is possible to reliably measure the ecological factors of individual youths who are vulnerable or highly resistant to cyber violence. In schools, teachers could refer to the measurement results for guiding students, better understanding their cyber violence conditions, and assessing their pro-social capabilities. With the measurement results, teachers and police officers could detect perpetrators or victims and intervene immediately. In addition, this measurement tool could analyze the effects of the prevention and intervention programs for cyber violence and draw appropriate suggestions.

Keywords: adolescents, cyber violence, cyber violence measurement tool, measurement tool, multi-report measurement tool, youths

Procedia PDF Downloads 101
7479 Preparation of Wireless Networks and Security; Challenges in Efficient Accession of Encrypted Data in Healthcare

Authors: M. Zayoud, S. Oueida, S. Ionescu, P. AbiChar

Abstract:

Background: Wireless sensor network is encompassed of diversified tools of information technology, which is widely applied in a range of domains, including military surveillance, weather forecasting, and earthquake forecasting. Strengthened grounds are always developed for wireless sensor networks, which usually emerges security issues during professional application. Thus, essential technological tools are necessary to be assessed for secure aggregation of data. Moreover, such practices have to be incorporated in the healthcare practices that shall be serving in the best of the mutual interest Objective: Aggregation of encrypted data has been assessed through homomorphic stream cipher to assure its effectiveness along with providing the optimum solutions to the field of healthcare. Methods: An experimental design has been incorporated, which utilized newly developed cipher along with CPU-constrained devices. Modular additions have also been employed to evaluate the nature of aggregated data. The processes of homomorphic stream cipher have been highlighted through different sensors and modular additions. Results: Homomorphic stream cipher has been recognized as simple and secure process, which has allowed efficient aggregation of encrypted data. In addition, the application has led its way to the improvisation of the healthcare practices. Statistical values can be easily computed through the aggregation on the basis of selected cipher. Sensed data in accordance with variance, mean, and standard deviation has also been computed through the selected tool. Conclusion: It can be concluded that homomorphic stream cipher can be an ideal tool for appropriate aggregation of data. Alongside, it shall also provide the best solutions to the healthcare sector.

Keywords: aggregation, cipher, homomorphic stream, encryption

Procedia PDF Downloads 262
7478 Information Technology Approaches to Literature Text Analysis

Authors: Ayse Tarhan, Mustafa Ilkan, Mohammad Karimzadeh

Abstract:

Science was considered as part of philosophy in ancient Greece. By the nineteenth century, it was understood that philosophy was very inclusive and that social and human sciences such as literature, history, and psychology should be separated and perceived as an autonomous branch of science. The computer was also first seen as a tool of mathematical science. Over time, computer science has grown by encompassing every area in which technology exists, and its growth compelled the division of computer science into different disciplines, just as philosophy had been divided into different branches of science. Now there is almost no branch of science in which computers are not used. One of the newer autonomous disciplines of computer science is digital humanities, and one of the areas of digital humanities is literature. The material of literature is words, and thanks to the software tools created using computer programming languages, data that a literature researcher would need months to complete, can be achieved quickly and objectively. In this article, three different tools that literary researchers can use in their work will be introduced. These studies were created with the computer programming languages Python and R and brought to the world of literature. The purpose of introducing the aforementioned studies is to set an example for the development of special tools or programs on Ottoman language and literature in the future and to support such initiatives. The first example to be introduced is the Stylometry tool developed with the R language. The other is The Metrical Tool, which is used to measure data in poems and was developed with Python. The latest literature analysis tool in this article is Voyant Tools, which is a multifunctional and easy-to-use tool.

Keywords: DH, literature, information technologies, stylometry, the metrical tool, voyant tools

Procedia PDF Downloads 153
7477 Investigating Visual Statistical Learning during Aging Using the Eye-Tracking Method

Authors: Zahra Kazemi Saleh, Bénédicte Poulin-Charronnat, Annie Vinter

Abstract:

This study examines the effects of aging on visual statistical learning, using eye-tracking techniques to investigate this cognitive phenomenon. Visual statistical learning is a fundamental brain function that enables the automatic and implicit recognition, processing, and internalization of environmental patterns over time. Some previous research has suggested the robustness of this learning mechanism throughout the aging process, underscoring its importance in the context of education and rehabilitation for the elderly. The study included three distinct groups of participants, including 21 young adults (Mage: 19.73), 20 young-old adults (Mage: 67.22), and 17 old-old adults (Mage: 79.34). Participants were exposed to a series of 12 arbitrary black shapes organized into 6 pairs, each with different spatial configurations and orientations (horizontal, vertical, and oblique). These pairs were not explicitly revealed to the participants, who were instructed to passively observe 144 grids presented sequentially on the screen for a total duration of 7 min. In the subsequent test phase, participants performed a two-alternative forced-choice task in which they had to identify the most familiar pair from 48 trials, each consisting of a base pair and a non-base pair. Behavioral analysis using t-tests revealed notable findings. The mean score for the first group was significantly above chance, indicating the presence of visual statistical learning. Similarly, the second group also performed significantly above chance, confirming the persistence of visual statistical learning in young-old adults. Conversely, the third group, consisting of old-old adults, showed a mean score that was not significantly above chance. This lack of statistical learning in the old-old adult group suggests a decline in this cognitive ability with age. Preliminary eye-tracking results showed a decrease in the number and duration of fixations during the exposure phase for all groups. The main difference was that older participants focused more often on empty cases than younger participants, likely due to a decline in the ability to ignore irrelevant information, resulting in a decrease in statistical learning performance.

Keywords: aging, eye tracking, implicit learning, visual statistical learning

Procedia PDF Downloads 78
7476 Solar Photovoltaic Pumping and Water Treatment Tools: A Case Study in Ethiopian Village

Authors: Corinna Barraco, Ornella Salimbene

Abstract:

This research involves the Ethiopian locality of Jeldi (North Africa), an area particularly affected by water shortage and in which the pumping and treatment of drinking water are extremely sensitive issues. The study aims to develop and apply low-cost tools for the design of solar water pumping and water purification systems in a not developed country. Consequently, two technical tools have been implemented in Excel i) Solar photovoltaic Pumping (Spv-P) ii) Water treatment (Wt). The Spv-P tool was applied to the existing well (depth 110 [m], dynamic water level 90 [m], static water level 53 [m], well yield 0.1728 [m³h⁻¹]) in the Jeldi area, where estimated water demand is about 50 [m3d-1]. Through the application of the tool, it was designed the water extraction system of the well, obtaining the number of pumps and solar panels necessary for water pumping from the well of Jeldi. Instead, the second tool Wt has been applied in the subsequent phase of extracted water treatment. According to the chemical-physical parameters of the water, Wt returns as output the type of purification treatment(s) necessary to potable the extracted water. In the case of the well of Jeldi, the tool identified a high criticality regarding the turbidity parameter (12 [NTU] vs 5 [NTU]), and a medium criticality regarding the exceeding limits of sodium concentration (234 [mg/L Na⁺] vs 200 [mg/L Na⁺]) and ammonia (0.64 [mg/L NH³-N] vs 0.5 [mg/L NH³-N]). To complete these tools, two specific manuals are provided for the users. The joint use of the two tools would help reduce problems related to access to water resources compared to the current situation and represents a simplified solution for the design of pumping systems and analysis of purification treatments to be performed in undeveloped countries.

Keywords: drinking water, Ethiopia, treatments, water pumping

Procedia PDF Downloads 158
7475 A Study on Big Data Analytics, Applications and Challenges

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, Healthcare, and business intelligence contain voluminous and incremental data, which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organization's decision-making strategy can be enhanced using big data analytics and applying different machine learning techniques and statistical tools on such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates on various frameworks in the process of Analysis using different machine-learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 85
7474 A Study on Big Data Analytics, Applications, and Challenges

Authors: Chhavi Rana

Abstract:

The aim of the paper is to highlight the existing development in the field of big data analytics. Applications like bioinformatics, smart infrastructure projects, healthcare, and business intelligence contain voluminous and incremental data which is hard to organise and analyse and can be dealt with using the framework and model in this field of study. An organisation decision-making strategy can be enhanced by using big data analytics and applying different machine learning techniques and statistical tools to such complex data sets that will consequently make better things for society. This paper reviews the current state of the art in this field of study as well as different application domains of big data analytics. It also elaborates various frameworks in the process of analysis using different machine learning techniques. Finally, the paper concludes by stating different challenges and issues raised in existing research.

Keywords: big data, big data analytics, machine learning, review

Procedia PDF Downloads 95
7473 Nonstationarity Modeling of Economic and Financial Time Series

Authors: C. Slim

Abstract:

Traditional techniques for analyzing time series are based on the notion of stationarity of phenomena under study, but in reality most economic and financial series do not verify this hypothesis, which implies the implementation of specific tools for the detection of such behavior. In this paper, we study nonstationary non-seasonal time series tests in a non-exhaustive manner. We formalize the problem of nonstationary processes with numerical simulations and take stock of their statistical characteristics. The theoretical aspects of some of the most common unit root tests will be discussed. We detail the specification of the tests, showing the advantages and disadvantages of each. The empirical study focuses on the application of these tests to the exchange rate (USD/TND) and the Consumer Price Index (CPI) in Tunisia, in order to compare the Power of these tests with the characteristics of the series.

Keywords: stationarity, unit root tests, economic time series, ADF tests

Procedia PDF Downloads 423
7472 Employer Learning, Statistical Discrimination and University Prestige

Authors: Paola Bordon, Breno Braga

Abstract:

This paper investigates whether firms use university prestige to statistically discriminate among college graduates. The test is based on the employer learning literature which suggests that if firms use a characteristic for statistical discrimination, this variable should become less important for earnings as a worker gains labor market experience. In this framework, we use a regression discontinuity design to estimate a 19% wage premium for recent graduates of two of the most selective universities in Chile. However, we find that this premium decreases by 3 percentage points per year of labor market experience. These results suggest that employers use college selectivity as a signal of workers' quality when they leave school. However, as workers reveal their productivity throughout their careers, they become rewarded based on their true quality rather than the prestige of their college.

Keywords: employer learning, statistical discrimination, college returns, college selectivity

Procedia PDF Downloads 581
7471 Statistical Manufacturing Cell/Process Qualification Sample Size Optimization

Authors: Angad Arora

Abstract:

In production operations/manufacturing, a cell or line is typically a bunch of similar machines (computer numerical control (CNCs), advanced cutting, 3D printing or special purpose machines. For qualifying a typical manufacturing line /cell / new process, Ideally, we need a sample of parts that can be flown through the process and then we make a judgment on the health of the line/cell. However, with huge volumes and mass production scope, such as in the mobile phone industry, for example, the actual cells or lines can go in thousands and to qualify each one of them with statistical confidence means utilizing samples that are very large and eventually add to product /manufacturing cost + huge waste if the parts are not intended to be customer shipped. To solve this, we come up with 2 steps statistical approach. We start with a small sample size and then objectively evaluate whether the process needs additional samples or not. For example, if a process is producing bad parts and we saw those samples early, then there is a high chance that the process will not meet the desired yield and there is no point in keeping adding more samples. We used this hypothesis and came up with 2 steps binomial testing approach. Further, we also prove through results that we can achieve an 18-25% reduction in samples while keeping the same statistical confidence.

Keywords: statistics, data science, manufacturing process qualification, production planning

Procedia PDF Downloads 98
7470 An Approach Based on Statistics and Multi-Resolution Representation to Classify Mammograms

Authors: Nebi Gedik

Abstract:

One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: wave atom transform, statistical features, multi-resolution representation, mammogram

Procedia PDF Downloads 223
7469 The Metacognition Levels of Students: A Research School of Physical Education and Sports at Anadolu University

Authors: Dilek Yalız Solmaz

Abstract:

Meta-cognition is an important factor for educating conscious individuals who are aware of their cognitive processes. With this respect, the purposes of this article is to find out the perceived metacognition level of Physical Education and Sports School students at Anadolu University and to identify whether metacognition levels display significant differences in terms of various variables. 416 Anadolu University Physical Education and Sports School students were formed the research universe. "The Meta-Cognitions Questionnaire (MCQ-30)" developed by Cartwright-Hatton and Wells and later developed the 30-item short form (MCQ-30) was used. The MCQ-30 which was adapted into Turkish by Tosun and Irak is a four-point agreement scale. In the data analysis, arithmethic mean, standard deviation, t-test and ANOVA were used. There is no statistical difference between mean scores of uncontrollableness and danger, cognitive awareness, cognitive confidence and the positive beliefs of girls and boys students. There is a statistical difference between mean scores of the need to control thinking. There is no statistical difference according to departments of students between mean scores of uncontrollableness and danger, cognitive awareness, cognitive confidence, need to control thinking and the positive beliefs. There is no statistical difference according to grade level of students between mean scores of the positive beliefs, cognitive confidence and need to control thinking. There is a statistical difference between mean scores of uncontrollableness and danger and cognitive awareness.

Keywords: meta cognition, physical education, sports school students, thinking

Procedia PDF Downloads 383
7468 Sustainability of High-Rise Affordable Housing: Critical Issues in Applying Green Building Rating Tools

Authors: Poh Im. Lim, Hillary Yee Qin. Tan

Abstract:

Nowadays, going green has become a trend, and being emphasized in the construction industry. In Malaysia, there are several green rating tools available in the industry and among these, GBI and GreenRE are considered as the most common tools adopted for residential buildings. However, being green is not equal to or making something sustainable. Being sustainable is to take economic, environmental and social aspects into consideration. This is particularly essential in the affordable housing sector as the end-users belong to lower-income and places importance on many socio-economic needs beyond the environmental criteria. This paper discusses the arguments in proposing a sustainability framework that is tailor-made for high-rise affordable housing. In-depth interviews and observation mapping methods were used in gathering inputs from the end-users, non-governmental organisations (NGOs) as well as the professionals. ‘Bottom-up’ approach was applied in this research to show the significance of participation from the local community in the decision-making process. The proposed sustainability framework illustrates the discrepancies between user priorities and what the industry is providing. The outcome of this research suggests that integrating sustainability into high-rise affordable housing is achievable and beneficial to the industry, society, and the environment.

Keywords: green building rating tools, high-rise affordable housing, sustainability framework, sustainable development

Procedia PDF Downloads 141
7467 Exploring the Spatial Characteristics of Mortality Map: A Statistical Area Perspective

Authors: Jung-Hong Hong, Jing-Cen Yang, Cai-Yu Ou

Abstract:

The analysis of geographic inequality heavily relies on the use of location-enabled statistical data and quantitative measures to present the spatial patterns of the selected phenomena and analyze their differences. To protect the privacy of individual instance and link to administrative units, point-based datasets are spatially aggregated to area-based statistical datasets, where only the overall status for the selected levels of spatial units is used for decision making. The partition of the spatial units thus has dominant influence on the outcomes of the analyzed results, well known as the Modifiable Areal Unit Problem (MAUP). A new spatial reference framework, the Taiwan Geographical Statistical Classification (TGSC), was recently introduced in Taiwan based on the spatial partition principles of homogeneous consideration of the number of population and households. Comparing to the outcomes of the traditional township units, TGSC provides additional levels of spatial units with finer granularity for presenting spatial phenomena and enables domain experts to select appropriate dissemination level for publishing statistical data. This paper compares the results of respectively using TGSC and township unit on the mortality data and examines the spatial characteristics of their outcomes. For the mortality data between the period of January 1st, 2008 and December 31st, 2010 of the Taitung County, the all-cause age-standardized death rate (ASDR) ranges from 571 to 1757 per 100,000 persons, whereas the 2nd dissemination area (TGSC) shows greater variation, ranged from 0 to 2222 per 100,000. The finer granularity of spatial units of TGSC clearly provides better outcomes for identifying and evaluating the geographic inequality and can be further analyzed with the statistical measures from other perspectives (e.g., population, area, environment.). The management and analysis of the statistical data referring to the TGSC in this research is strongly supported by the use of Geographic Information System (GIS) technology. An integrated workflow that consists of the tasks of the processing of death certificates, the geocoding of street address, the quality assurance of geocoded results, the automatic calculation of statistic measures, the standardized encoding of measures and the geo-visualization of statistical outcomes is developed. This paper also introduces a set of auxiliary measures from a geographic distribution perspective to further examine the hidden spatial characteristics of mortality data and justify the analyzed results. With the common statistical area framework like TGSC, the preliminary results demonstrate promising potential for developing a web-based statistical service that can effectively access domain statistical data and present the analyzed outcomes in meaningful ways to avoid wrong decision making.

Keywords: mortality map, spatial patterns, statistical area, variation

Procedia PDF Downloads 260
7466 Methodology for Obtaining Static Alignment Model

Authors: Lely A. Luengas, Pedro R. Vizcaya, Giovanni Sánchez

Abstract:

In this paper, a methodology is presented to obtain the Static Alignment Model for any transtibial amputee person. The proposed methodology starts from experimental data collected on the Hospital Militar Central, Bogotá, Colombia. The effects of transtibial prosthesis malalignment on amputees were measured in terms of joint angles, center of pressure (COP) and weight distribution. Some statistical tools are used to obtain the model parameters. Mathematical predictive models of prosthetic alignment were created. The proposed models are validated in amputees and finding promising results for the prosthesis Static Alignment. Static alignment process is unique to each subject; nevertheless the proposed methodology can be used in each transtibial amputee.

Keywords: information theory, prediction model, prosthetic alignment, transtibial prosthesis

Procedia PDF Downloads 257
7465 Direct Translation vs. Pivot Language Translation for Persian-Spanish Low-Resourced Statistical Machine Translation System

Authors: Benyamin Ahmadnia, Javier Serrano

Abstract:

In this paper we compare two different approaches for translating from Persian to Spanish, as a language pair with scarce parallel corpus. The first approach involves direct transfer using an statistical machine translation system, which is available for this language pair. The second approach involves translation through English, as a pivot language, which has more translation resources and more advanced translation systems available. The results show that, it is possible to achieve better translation quality using English as a pivot language in either approach outperforms direct translation from Persian to Spanish. Our best result is the pivot system which scores higher than direct translation by (1.12) BLEU points.

Keywords: statistical machine translation, direct translation approach, pivot language translation approach, parallel corpus

Procedia PDF Downloads 488
7464 On the Development of Medical Additive Manufacturing in Egypt

Authors: Khalid Abdelghany

Abstract:

Additive Manufacturing (AM) is the manufacturing technology that is used to fabricate fast products direct from CAD models in very short time and with minimum operation steps. Jointly with the advancement in medical computer modeling, AM proved to be a very efficient tool to help physicians, orthopedic surgeons and dentists design and fabricate patient-tailored surgical guides, templates and customized implants from the patient’s CT / MRI images. AM jointly with computer-assisted designing/computer-assisted manufacturing (CAD/CAM) technology have enabled medical practitioners to tailor physical models in a patient-and purpose-specific fashion and helped to design and manufacture of templates, appliances and devices with a high range of accuracy using biocompatible materials. In developing countries, there are some technical and financial limitations of implementing such advanced tools as an essential portion of medical applications. CMRDI institute in Egypt has been working in the field of Medical Additive Manufacturing since 2003 and has assisted in the recovery of hundreds of poor patients using these advanced tools. This paper focuses on the surgical and dental use of 3D printing technology in Egypt as a developing country. The presented case studies have been designed and processed using the software tools and additive manufacturing machines in CMRDI through cooperative engineering and medical works. Results showed that the implementation of the additive manufacturing tools in developed countries is successful and could be economical comparing to long treatment plans.

Keywords: additive manufacturing, dental and orthopeadic stents, patient specific surgical tools, titanium implants

Procedia PDF Downloads 315
7463 Analysis of the Engineering Judgement Influence on the Selection of Geotechnical Parameters Characteristic Values

Authors: K. Ivandic, F. Dodigovic, D. Stuhec, S. Strelec

Abstract:

A characteristic value of certain geotechnical parameter results from an engineering assessment. Its selection has to be based on technical principles and standards of engineering practice. It has been shown that the results of engineering assessment of different authors for the same problem and input data are significantly dispersed. A survey was conducted in which participants had to estimate the force that causes a 10 cm displacement at the top of a axially in-situ compressed pile. Fifty experts from all over the world took part in it. The lowest estimated force value was 42% and the highest was 133% of measured force resulting from a mentioned static pile load test. These extreme values result in significantly different technical solutions to the same engineering task. In case of selecting a characteristic value of a geotechnical parameter the importance of the influence of an engineering assessment can be reduced by using statistical methods. An informative annex of Eurocode 1 prescribes the method of selecting the characteristic values of material properties. This is followed by Eurocode 7 with certain specificities linked to selecting characteristic values of geotechnical parameters. The paper shows the procedure of selecting characteristic values of a geotechnical parameter by using a statistical method with different initial conditions. The aim of the paper is to quantify an engineering assessment in the example of determining a characteristic value of a specific geotechnical parameter. It is assumed that this assessment is a random variable and that its statistical features will be determined. For this purpose, a survey research was conducted among relevant experts from the field of geotechnical engineering. Conclusively, the results of the survey and the application of statistical method were compared.

Keywords: characteristic values, engineering judgement, Eurocode 7, statistical methods

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7462 Assessment of Vocational Rehabilitation of Visually Impaired Persons in Poultry Farming at Blind Center, Ogbomoso

Authors: Modupe C. Alasa

Abstract:

One of the major parameters for ensuring a country’s economic growth and development is the extent to which the citizens are involved in agriculture. The general objective of this study is to determine the assessment of vocational rehabilitation of visually impaired persons in poultry farming at blind center, Ogbomoso, Nigeria. A total number of 70 students will be selected randomly through the use of structured questionnaire out of the total number of students which is 120. Data will be collected from the farmers’ personal characteristics and other specific objectives related to the work. The results will be analyzed with the use of simple statistical tools as frequency, percentage, means and standard deviations. Conclusion and recommendations will be suggested based on result findings of the study.

Keywords: assessment, impair, poultry, rehabilitation, vocational

Procedia PDF Downloads 256
7461 A Simulated Scenario of WikiGIS to Support the Iteration and Traceability Management of the Geodesign Process

Authors: Wided Batita, Stéphane Roche, Claude Caron

Abstract:

Geodesign is an emergent term related to a new and complex process. Hence, it needs to rethink tools, technologies and platforms in order to efficiently achieve its goals. A few tools have emerged since 2010 such as CommunityViz, GeoPlanner, etc. In the era of Web 2.0 and collaboration, WikiGIS has been proposed as a new category of tools. In this paper, we present WikiGIS functionalities dealing mainly with the iteration and traceability management to support the collaboration of the Geodesign process. Actually, WikiGIS is built on GeoWeb 2.0 technologies —and primarily on wiki— and aims at managing the tracking of participants’ editing. This paper focuses on a simplified simulation to illustrate the strength of WikiGIS in the management of traceability and in the access to history in a Geodesign process. Indeed, a cartographic user interface has been implemented, and then a hypothetical use case has been imagined as proof of concept.

Keywords: geodesign, history, traceability, tracking of participants’ editing, WikiGIS

Procedia PDF Downloads 249
7460 Self-Efficacy Perceptions of Pre-Service Art and Music Teachers towards the Use of Information and Communication Technologies

Authors: Agah Tugrul Korucu

Abstract:

Information and communication technologies have become an important part of our daily lives with significant investments in technology in the 21st century. Individuals are more willing to design and implement computer-related activities, and they are the main component of computer self-efficacy and self-efficacy related to the fact that the increase in information technology, with operations in parallel with these activities more successful. The Self-efficacy level is a significant factor which determines how individuals act in events, situations and difficult processes. It is observed that individuals with higher self-efficacy perception of computers who encounter problems related to computer use overcome them more easily. Therefore, this study aimed to examine self-efficacy perceptions of pre-service art and music teachers towards the use of information and communication technologies in terms of different variables. Research group consists of 60 pre-service teachers who are studying at Necmettin Erbakan University Ahmet Keleşoğlu Faculty of Education Art and Music department. As data collection tool of the study; “personal information form” developed by the researcher and used to collect demographic data and "the perception scale related to self-efficacy of informational technology" are used. The scale is 5-point Likert-type scale. It consists of 27 items. The Kaiser-Meyer-Olkin (KMO) sample compliance value is found 0.959. The Cronbach alpha reliability coefficient of the scale is found to be 0.97. computer-based statistical software package (SPSS 21.0) is used in order to analyze the data collected by data collection tools; descriptive statistics, t-test, analysis of variance are used as statistical techniques.

Keywords: self-efficacy perceptions, teacher candidate, information and communication technologies, art teacher

Procedia PDF Downloads 326
7459 The Influence of Size on Fused Silica Strength: A Multi-Method Study

Authors: Şeyma Saliha Fidan, Rahmi Ünal

Abstract:

Ceramic materials exhibit inherently brittle behavior, primarily attributed to the presence of flaws that severely restrict their applicability as structural elements under tensile loading. This brittleness necessitates special attention in the design of ceramic components, with a particular focus on appropriately addressing stress distribution. Among the most commonly used uniaxial testing methods to evaluate the mechanical behavior of ceramics are three-point bending and four-point bending tests. Each of these methods induces a unique stress distribution within the specimen. Using Weibull theory and its fundamental assumptions, it is possible to account for the different stress fields produced by each testing method and compare the resulting strength data. This comparison is based on the concept of effective volume or area. In this study, slip-cast fused silica ceramics were selected as the material of interest. The study aims to apply Weibull statistical theory to various testing methods, integrating statistical tools and finite element method (FEM) simulations. A validated FEM-based approach was developed to determine the effective volumes of the specimens. The effective volume values obtained through analytical and numerical methods were compared, and the stress fields generated by different testing methods were evaluated based on Weibull theory. Moreover, the effective volume calculation procedure derived from numerical analysis methods has been adapted for use in complex test geometries and various loading conditions.

Keywords: ceramic, fused silica, effective volume, Weibull analysis, finite element method

Procedia PDF Downloads 6