Search results for: coverage probability

Authors: Weber A. R. Souza, Andre A. N. Dantas, Marcio A. Medeiros, Rafaella F. Costa

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The erosive processes are natural phenomena that cause changes in the soil continuously due to the actions of natural erosive agents and their speed can be intensified or retarded by factors such as climate, inclination, type of matrix rock, vegetation and anthropic activities, the latter being very relevant in occupied areas without planning and urban infrastructure. Inadequate housing sites associated with an inefficient urban drainage network and lack of vegetation cover potentiate the erosive processes that, over time, are gaining alarming proportions, as is the case of the erosion in Planaltina in Federal district, a Brazilian state in the central west. Thus, the aim of this work was to compare the use of Vetiver grass and Alfalfa as vegetation cover to slope protection. For that, a study was carried out in the scientific literature about the improvement of the soil properties provided by them and verification of the safety factor through the simulation of slopes with different heights and inclination using SLOPE / W software. The Vetiver grass presented little more satisfactory results than the Alfalfa, but these obtained results slightly closer to that of the vetiver grass in less time of planting.

Keywords: erosive processes, planting, slope protection, vegetation cover

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Authors: Nicula Valentin, Andrei Virginia

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Nowadays, the individual plays a central role in the state’s architecture. This is why the subjective dimension of the security represents a key concept in risk assessment. The paper’s scope is to emphasize the discrepancy between expert and lay evaluations of national security hazards, which is caused by key factors like emotions, personal experience, knowledge and media. Therefore, we have chosen to apply, using these two different groups of respondents, the Q-sort method, which reveals individual beliefs, attitudes, preferences hidden behind the subjects’ own way of prioritizing the risks they are confronted with. Our study’s conclusions are meant to unveil significant indicators needed to be taken into consideration by a state’s leadership in order to understand the social perception of national security hazards, to communicate better with the public opinion and prevent or mitigate the overestimation of the severity or probability of these dangers.

Keywords: risk perception, Q-sort method, national security hazards, individual beliefs

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Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

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Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

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Authors: Jing Zhang, Jie Chen

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In this paper, we deal with the optimal I/O point location in an automated parking system. In this system, the S/R machine (storage and retrieve machine) travels independently in vertical and horizontal directions. Based on the characteristics of the parking system and the basic principle of AS/RS system (Automated Storage and Retrieval System), we obtain the continuous model in units of time. For the single command cycle using the randomized storage policy, we calculate the probability density function for the system travel time and thus we develop the travel time model. And we confirm that the travel time model shows a good performance by comparing with discrete case. Finally in this part, we establish the optimal model by minimizing the expected travel time model and it is shown that the optimal location of the I/O point is located at the middle of the left-hand above corner.

Keywords: parking system, optimal location, response time, S/R machine

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Authors: Jadwiga Królikowska, Andrzej Królikowski, Jarosław Bajer

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The work delineates the threats of maladjustment of the capacity of rain canals, designed and built in the early 20th century, in connection to heavy rainfall, especially in summer. This is the cause of the so called 'urban floods.' It directly relates to fierce raise of paving in the cities. Resolving this problem requires a change in philosophy of draining the rainfall by wider use of retention, infiltration and usage of rainwater. In systemic approach to managing the safety of urban drainage systems the risk, which is directly connected to safety failures, has been accepted as a measure. The risk level defines the probability of occurrence of losses grater than the ones forecast for a given time frame. The procedure of risk modelling, enabling its numeric analysis by using appropriate weights, is a significant issue in this paper.

Keywords: drainage system, urban areas, risk measurement, systemic approach

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Authors: Ravipa Rojasavachai, Li Yang

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Working from home has become a global phenomenon after the coronavirus outbreak, and most employees have a choice to choose between working from home or the office. In this paper, we examine the demographics and socio-economics factors influencing individuals’ decision to choose working from home rather than the office before and after the coronavirus outbreak based on Australian household data. We find that all factors impact the working from home choice before the coronavirus outbreak, but the number of children turns to an uninfluenced factor on individuals’ choices after the outbreak. We also find that female employees have a higher probability of choosing to work from home after the coronavirus outbreak. This is because they have less concern for their career opportunities and higher wage premium of working from home due to the changing in cultural norms and advanced working from home technologies in companies after the coronavirus outbreak.

Keywords: work from home, telework, remote working, COVID-19, pandemic, wage

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Authors: Nareenad Panbun

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The objective is to study the knowledge utilization from the participants of the announcer training program by National Broadcasting and Telecommunications Commission (NBTC). This study is a quantitative research based on surveys and self-answering questionnaires. The population of this study is 100 participants randomly chosen by non-probability sampling method. The results have shown that most of the participants were satisfied with the topics of general knowledge about the broadcasting and television business for 37 people representing 37%, followed by the topics of broadcasting techniques. The legal issues, consumer rights, television business ethics, and credibility of the media are, in addition to the media's role and responsibilities in society, the use of language for successful communication. Therefore, the communication language skills are the most important for all of the trainees and will also build up the image of the broadcasting center.

Keywords: announcer training program, participant, requirements announced, theory of utilization

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Authors: Illyas Md Isa, Sharifah Norain Mohd Sharif, Norhayati Hashima

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A mercury(II) sensor was developed by using multi-walled carbon nanotubes (MWCNTs) paste electrode modified with Zn/Al layered double hydroxide-3(4-methoxyphenyl)propionate nanocomposite (Zn/Al-HMPP). The optimum conditions by cyclic voltammetry were observed at electrode composition 2.5% (w/w) of Zn/Al-HMPP/MWCNTs, 0.4 M potassium chloride, pH 4.0, and scan rate of 100 mVs-1. The sensor exhibited wide linear range from 1x10-3 M to 1x10-7 M Hg2+ and 1x10-7 M to 1x10-9 M Hg2+, with a detection limit of 1x10-10 M Hg2+. The high sensitivity of the proposed electrode towards Hg(II) was confirmed by double potential-step chronocoulometry which indicated these values; diffusion coefficient 1.5445 x 10-9 cm2 s-1, surface charge 524.5 µC s-½ and surface coverage 4.41 x 10-2 mol cm-2. The presence of 25-fold concentration of most metal ions had no influence on the anodic peak current. With characteristics such as high sensitivity, selectivity and repeatability the electrode was then proposed as the appropriate alternative for the determination of mercury(II).

Keywords: cyclic voltammetry, mercury(II), modified carbon paste electrode, nanocomposite

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Authors: Salim Çalışkan, Hakan Akyüz

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Digital image correlation has been accustomed as a versatile and efficient method for measuring displacements on the article surfaces by comparing reference subsets in undeformed images with the define target subset in the distorted image. The theoretical model points out that the accuracy of the digital image correlation displacement data can be exactly anticipated based on the divergence of the image noise and the sum of the squares of the subset intensity gradients. The digital image correlation procedure locates each subset of the original image in the distorted image. The software then determines the displacement values of the centers of the subassemblies, providing the complete displacement measures. In this paper, the effect of the speckle distribution and its effect on displacements measured out plane displacement data as a function of the size of the subset was investigated. Nine groups of speckle patterns were used in this study: samples are sprayed randomly by pre-manufactured patterns of three different hole diameters, each with three coverage ratios, on a computer numerical control punch press. The resulting displacement values, referenced at the center of the subset, are evaluated based on the average of the displacements of the pixel’s interior the subset.

Keywords: digital image correlation, speckle pattern, experimental mechanics, tensile test, aluminum alloy

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Authors: Davood Shishebori, Mohammad Saber Fallah Nezhad, Sina Seifi

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In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.

Keywords: MDS sampling plan, RGS plan, sampling plan for resubmitted lots, process capability index (PCI), average sample number (ASN), Bayesian approach

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Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

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The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

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Authors: Illyas Md Isa, Sharifah Norain Mohd Sharif, Norhayati Hashim

Abstract:

A mercury(II) sensor was developed by using multi-walled carbon nano tubes (MWCNTs) paste electrode modified with Zn/Al layered double hydroxide-3(4-methoxyphenyl) propionate nano composite (Zn/Al-HMPP). The optimum conditions by cyclic voltammetry were observed at electrode composition 2.5% (w/w) of Zn/Al-HMPP/MWCNTs, 0.4 M potassium chloride, pH 4.0, and scan rate of 100 mVs-1. The sensor exhibited wide linear range from 1x10-3 M to 1x10-7 M Hg2+ and 1x10-7 M to 1x10-9 M Hg2+, with a detection limit of 1 x 10-10 M Hg2+. The high sensitivity of the proposed electrode towards Hg(II) was confirmed by double potential-step chronocoulometry which indicated these values; diffusion coefficient 1.5445 x 10-9 cm2 s-1, surface charge 524.5 µC s-½ and surface coverage 4.41 x 10-2 mol cm-2. The presence of 25-fold concentration of most metal ions had no influence on the anodic peak current. With characteristics such as high sensitivity, selectivity and repeatability the electrode was then proposed as the appropriate alternative for the determination of mercury.

Keywords: Cyclic voltammetry, Mercury(II), Modified carbon paste electrode, Nanocomposite

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Authors: Jaeyoung Lee, Minji Je

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Objectives: In adolescence, adolescents are curious about sex, but sexual experience before becoming an adult can cause the risk of high probability of sexually transmitted infection. Therefore, it is very important to prevent sexually transmitted infections so that adolescents can grow in healthy and upright way. Adolescent females, especially, have sexual behavior distinguished from that of male adolescents. Protecting female adolescents’ reproductive health is even more important since it is directly related to the childbirth of the next generation. This study, thus, investigated the predictors of sexually transmitted infection in adolescent females with sexual experiences based on the National Health Statistics in Korea. Methods: This study was conducted based on the National Health Statistics in Korea. The 11th Korea Youth Behavior Web-based Survey in 2016 was conducted in the type of anonymous self-reported survey in order to find out the health behavior of adolescents. The target recruitment group was middle and high school students nationwide as of April 2016, and 65,528 students from a total of 800 middle and high schools participated. The study was conducted in 537 female high school students (Grades 10–12) among them. The collected data were analyzed as complex sampling design using SPSS statistics 22. The strata, cluster, weight, and finite population correction provided by Korea Center for Disease Control & Prevention (KCDC) were reflected to constitute complex sample design files, which were used in the statistical analysis. The analysis methods included Rao-Scott chi-square test, complex samples general linear model, and complex samples multiple logistic regression analysis. Results: Out of 537 female adolescents, 11.9% (53 adolescents) had experiences of venereal infection. The predictors for venereal infection of the subjects were ‘age at first intercourse’ and ‘sexual intercourse after drinking’. The sexually transmitted infection of the subjects was decreased by 0.31 times (p=.006, 95%CI=0.13-0.71) for middle school students and 0.13 times (p<.001, 95%CI=0.05-0.32) for high school students whereas the age of the first sexual experience was under elementary school age. In addition, the sexually transmitted infection of the subjects was 3.54 times (p < .001, 95%CI=1.76-7.14) increased when they have experience of sexual relation after drinking alcohol, compared to those without the experience of sexual relation after drinking alcohol. Conclusions: The female adolescents had high probability of sexually transmitted infection if their age for the first sexual experience was low. Therefore, the female adolescents who start sexual experience earlier shall have practical sex education appropriate for their developmental stage. In addition, since the sexually transmitted infection increases, if they have sexual relations after drinking alcohol, the consideration for prevention of alcohol use or intervention of sex education shall be required. When health education intervention is conducted for health promotion for female adolescents in the future, it is necessary to reflect the result of this study.

Keywords: adolescent, coitus, female, sexually transmitted diseases

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Authors: Afaf Alharbi, Qianni Zhang

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The identification of malignant tissue in histopathological slides holds significant importance in both clinical settings and pathology research. This paper introduces a methodology aimed at automatically categorizing cancerous tissue through the utilization of a multiple-instance learning framework. This framework is specifically developed to acquire knowledge of the Bernoulli distribution of the bag label probability by employing neural networks. Furthermore, we put forward a neural network based permutation-invariant aggregation operator, equivalent to attention mechanisms, which is applied to the multi-instance learning network. Through empirical evaluation of an openly available colon cancer histopathology dataset, we provide evidence that our approach surpasses various conventional deep learning methods.

Keywords: attention multiple instance learning, MIL and transfer learning, histopathological slides, cancer tissue classification

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Authors: Sahil Imtiyaz

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One of the biggest challenges has emerged from the ever-expanding, dynamic, and instantaneously changing space-Big Data; and to find a data point and inherit wisdom to this space is a hard task. In this paper, we reduce the space of big data in Hamiltonian formalism that is in concordance with Ising Model. For this formulation, we simulate the system using dye laser in FORTRAN and analyse the dynamics of the data point in energy well of rhodium atom. After mapping the photon intensity and pulse width with energy and potential we concluded that as we increase the energy there is also increase in probability of tunnelling up to some point and then it starts decreasing and then shows a randomizing behaviour. It is due to decoherence with the environment and hence there is a loss of ‘quantumness’. This interprets the efficiency parameter and the extent of quantum evolution. The results are strongly encouraging in favour of the use of ‘Topological Property’ as a source of information instead of the qubit.

Keywords: big data, optimization, quantum evolution, hamiltonian, dye laser, fermionic computations

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Authors: Faiza Manzoor

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The main purpose of this study is to examine the socioeconomic and institutional determinants that affect farmers' probability of agricultural technology adoption. Primary survey data was gathered from 350 small household farmers of developing economies, and the empirical analysis was completed by exploiting a logit and probit model. The outcomes of this research emphasize that socioeconomic factors such as farmers' age, education level, and farm size impact farmers' behavior in adopting digital farming technology. The results show that cooperative membership and institutional characteristics such as access to credit and extension services have also affected small farmers' use and adoption of agricultural technologies. Digitalization also helps farmers by increasing their understanding and improving their decision-making abilities. Some policy implications and future directions are discussed.

Keywords: digital agriculture technologies, socioeconomics, institutional, developing economies

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Authors: Mostafa Gamal, Hoda K. Mohamed, Islam El-Maddah, Ali Hamdi

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In recent years, many digital documents on the web have been created due to the rapid growth of ’social applications’ communities or ’Data-intensive applications’. The evolution of online-based multimedia data poses new challenges in storing and querying large amounts of data for online recommender systems. Graph data models have been shown to be more efficient than relational data models for processing complex data. This paper will explain the key differences between graph and relational databases, their strengths and weaknesses, and why using graph databases is the best technology for building a realtime recommendation system. Also, The paper will discuss several similarity metrics algorithms that can be used to compute a similarity score of pairs of nodes based on their neighbourhoods or their properties. Finally, the paper will discover how NLP strategies offer the premise to improve the accuracy and coverage of realtime recommendations by extracting the information from the stored unstructured knowledge, which makes up the bulk of the world’s data to enrich the graph database with this information. As the size and number of data items are increasing rapidly, the proposed system should meet current and future needs.

Keywords: graph databases, NLP, recommendation systems, similarity metrics

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Authors: D. P. Rollinson, B. J. Dilley, P. G. Ryan

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The white-chinned petrel (Procellaria aequinoctialis) is the seabird species most commonly killed by Southern Hemisphere longline fisheries. Despite the importance of diving ability for mitigating longline bycatch, little is known of this species’ diving behaviour. We obtained data from temperature–depth recorders from nine white-chinned petrels breeding on Marion Island, southwestern Indian Ocean, during the late incubation and chickrearing period. Maximum dive depth (16 m) was slightly deeper than the previous estimate (13 m), but varied considerably among individuals (range 2–16 m). Males dived deeper than females, and birds feeding chicks dived deeper than incubating birds, but dive rate did not differ between the sexes. Time of day had no significant effect on dive depth or rate. Our findings will help to improve the design and performance of mitigation measures aimed at reducing seabird bycatch in longline fisheries, such as the calculation of minimum line sink rates and optimum aerial coverage of bird-scaring lines.

Keywords: dive depth, dive duration, temperature–depth recorders, seabirds, bird-scaring lines

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Authors: Kailash C. Madan

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We study the steady state behaviour of a batch arrival single server queue in which the first service with general service times is compulsory and the second service with general service times is optional. We term such a two phase service as generalized Coxian-2 service. Just after completion of a service the server must take a vacation of random length of time with general vacation times. We obtain steady state probability generating functions for the queue size as well as the steady state mean queue size at a random epoch of time in explicit and closed forms. Some particular cases of interest including some known results have been derived.

Keywords: batch arrivals, compound Poisson process, generalized Coxian-2 service, steady state

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Authors: Ihsane Modhaffar

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Fiber orientation is essential for the physical properties of composite materials. The theoretical parameters of a given reinforcement are usually known and widely used to predict the behavior of the material. In this work, we propose an image processing approach to estimate true principal directions and fiber orientation during injection molding processes of short fiber reinforced thermoplastics. Generally, a group of fibers are described in terms of probability distribution function or orientation tensor. Numerical techniques for the prediction of fiber orientation are also considered for concentrated situations. The flow was considered to be incompressible, and behave as Newtonian fluid containing suspensions of short-fibers. The governing equations, of this problem are: the continuity, the momentum and the energy. The obtained results were compared to available experimental findings. A good agreement between the numerical results and the experimental data was achieved.

Keywords: injection, composites, short-fiber reinforced thermoplastics, fiber orientation, incompressible fluid, numerical simulation

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Authors: Mohammad Abdullah-Al-Wadud

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In the current era of automation and artificial intelligence, different systems have been increasingly keeping on depending on decision-making capabilities of machines. Such systems/applications may range from simple classifiers to sophisticated surveillance systems based on traditional sensors and related equipment which are becoming more common in the internet of things (IoT) paradigm. However, the available data for such problems are usually imprecise and incomplete, which leads to uncertainty in decisions made based on traditional probability-based classifiers. This requires a robust fusion framework to combine the available information sources with some degree of certainty. The theory of evidence can provide with such a method for combining evidence from different (may be unreliable) sources/observers. This talk will address the employment of the Dempster-Shafer Theory of evidence in some practical applications.

Keywords: decision making, dempster-shafer theory, evidence fusion, incomplete data, uncertainty

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Authors: Mohamed Othmani, Yassine Khlifi

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This paper presents a technique for compact three dimensional (3D) object model reconstruction using wavelet networks. It consists to transform an input surface vertices into signals,and uses wavelet network parameters for signal approximations. To prove this, we use a wavelet network architecture founded on several mother wavelet families. POLYnomials WindOwed with Gaussians (POLYWOG) wavelet families are used to maximize the probability to select the best wavelets which ensure the good generalization of the network. To achieve a better reconstruction, the network is trained several iterations to optimize the wavelet network parameters until the error criterion is small enough. Experimental results will shown that our proposed technique can effectively reconstruct an irregular 3D object models when using the optimized wavelet network parameters. We will prove that an accurateness reconstruction depends on the best choice of the mother wavelets.

Keywords: 3d object, optimization, parametrization, polywog wavelets, reconstruction, wavelet networks

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Authors: M. Movahedi Rad

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In this study, a general approach to the reliability based limit analysis of laterally loaded piles is presented. In engineering practice, the uncertainties play a very important role. The aim of this study is to evaluate the lateral load capacity of free head and fixed-head long pile when the plastic limit analysis is considered. In addition to the plastic limit analysis to control the plastic behaviour of the structure, uncertain bound on the complementary strain energy of the residual forces is also applied. This bound has a significant effect for the load parameter. The solution to reliability-based problems is obtained by a computer program which is governed by the reliability index calculation.

Keywords: reliability, laterally loaded pile, residual strain energy, probability, limit analysis

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Authors: Natnicha Hasoontree

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The purpose of this paper was to study the relationship between brand value and perceived brand quality of television viewers in Bangkok towards the television business in Thailand. The population included television viewers in Bangkok, Thailand. A probability sampling technique was performed to get a sample group that included 500 respondents. Taro Yamane technique was utilized to get a proper sample size. A five Likert scale questionnaire was designed specifically to investigate brand value and perceived brand quality from the perspectives of television viewers in Bangkok. The findings implied that consumers in Bangkok attached a high importance towards the brand equity of television companies that comprised brand ability, brand reputation, brand credibility, and business ethics. Perceived brand quality received high rank in all aspects.

Keywords: brand value, perceived brand quality, television business, television viewers

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Authors: Manthan Patel, Vinit Ahlawat, Anshh Singh Claire, Pijush Samui

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This paper focuses on the analysis of quicksand condition for a dam foundation. The quicksand condition occurs in cohesion less soil when effective stress of soil becomes zero. In a dam, the saturated sediment may appear quite solid until a sudden change in pressure or shock initiates liquefaction. This causes the sand to form a suspension and lose strength hence resulting in failure of dam. A soil profile shows different properties at different points and the values obtained are uncertain thus reliability analysis is performed. The reliability is defined as probability of safety of a system in a given environment and loading condition and it is assessed as Reliability Index. The reliability analysis of dams under quicksand condition is carried by Gaussian Process Regression (GPR). Reliability index and factor of safety relating to liquefaction of soil is analysed using GPR. The results of reliability analysis by GPR is compared to that of conventional method and it is demonstrated that on applying GPR the probabilistic analysis reduces the computational time and efforts.

Keywords: factor of safety, GPR, reliability index, quicksand

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Authors: Merve Uzuner Sahin, Kumru D. Atalay, Berna Dengiz

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In today’s competitive market, there are many alternative products that can be used in similar manner and purpose. Therefore, the utility of the product is an important issue for the preferability of the brand. This utility could be measured in terms of its functionality, durability, reliability. These all are affected by the system capabilities. Reliability is an important system design criteria for the manufacturers to be able to have high availability. Availability is the probability that a system (or a component) is operating properly to its function at a specific point in time or a specific period of times. System availability provides valuable input to estimate the production rate for the company to realize the production plan. When considering only the corrective maintenance downtime of the system, mean time between failure (MTBF) and mean time to repair (MTTR) are used to obtain system availability. Also, the MTBF and MTTR values are important measures to improve system performance by adopting suitable maintenance strategies for reliability engineers and practitioners working in a system. Failure and repair time probability distributions of each component in the system should be known for the conventional availability analysis. However, generally, companies do not have statistics or quality control departments to store such a large amount of data. Real events or situations are defined deterministically instead of using stochastic data for the complete description of real systems. A fuzzy set is an alternative theory which is used to analyze the uncertainty and vagueness in real systems. The aim of this study is to present a novel approach to compute system availability using representation of MTBF and MTTR in fuzzy numbers. Based on the experience in the system, it is decided to choose 3 different spread of MTBF and MTTR such as 15%, 20% and 25% to obtain lower and upper limits of the fuzzy numbers. To the best of our knowledge, the proposed method is the first application that is used fuzzy MTBF and fuzzy MTTR for fuzzy system availability estimation. This method is easy to apply in any repairable production system by practitioners working in industry. It is provided that the reliability engineers/managers/practitioners could analyze the system performance in a more consistent and logical manner based on fuzzy availability. This paper presents a real case study of a repairable multi-stage production line in lead-acid battery production factory in Turkey. The following is focusing on the considered wet-charging battery process which has a higher production level than the other types of battery. In this system, system components could exist only in two states, working or failed, and it is assumed that when a component in the system fails, it becomes as good as new after repair. Instead of classical methods, using fuzzy set theory and obtaining intervals for these measures would be very useful for system managers, practitioners to analyze system qualifications to find better results for their working conditions. Thus, much more detailed information about system characteristics is obtained.

Keywords: availability analysis, battery production system, fuzzy sets, triangular fuzzy numbers (TFNs)

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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In this paper, we treat a model that falls in the area of protecting targeted systems from intelligent threats including terrorism. We introduce the concept of system survivability, in the context of continuous attacks, as the probability that a system under attack will continue operation up to some fixed time t. We define a constant attack rate (CAR) process as an attack on a targeted system that follows an exponential distribution. We consider the superposition of several CAR processes. From the attacker side, we determine the optimal attack strategy that minimizes the system survivability. We also determine the optimal strengthening strategy that maximizes the system survivability under limited defensive resources. We use operations research techniques to identify optimal strategies of each antagonist. Our results may be used as interesting starting points to develop realistic protection strategies against intentional attacks.

Keywords: CAR processes, defense/attack strategies, exponential failure, survivability

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Authors: Dyah Titisari Widyastuti

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Rail-station area development that is based on the concept of TOD (Transit Oriented Development) is principally oriented to pedestrian accessibility for daily mobility. The aim of this research is elaborating how far the existing physical elements of a rail-station district could facilitate pedestrian mobility and establish a pedestrian friendly district toward implementation of a TOD concept. This research was conducted through some steps: (i) mapping the rail-station area pedestrian sidewalk and pedestrian network as well as activity nodes and transit nodes, (ii) assessing the level of pedestrian sidewalk connectivity joining trip origin and destination. The research area coverage in this case is limited to walking distance of the rail station (around 500 meters or 10-15 minutes walking). The findings of this research on the current condition of the street and pedestrian sidewalk network and connectivity, show good preference for the foot modal share (more than 50%) is achieved. Nevertheless, it depends on the distance from the trip origin to destination.

Keywords: accessibility of daily mobility, pedestrian-friendly district, rail-station district, transit oriented development

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Authors: Luis M. Ribeiro, Jorge Raposo, Ricardo Oliveira, David Caballero, Domingos X. Viegas

Abstract:

Under the scope of European project WUIWATCH a set of experimental tests on house vulnerability was performed in order to assess the resistance of selected house components during the passage of a forest fire. Among the individual elements most affected by the passage of a wildfire the windows are the ones with greater exposure. In this sense, a set of exploratory experimental tests was designed to assess some particular aspects related to the vulnerability of windows and blinds. At the same time, the importance of leaving them closed (as well as the doors inside a house) during a wild fire was explored in order to give some scientific background to guidelines for homeowners. Three sets of tests were performed: 1. Windows and blinds resistance to heat. Three types of protective blinds were tested (aluminium, PVC and wood) on 2 types of windows (single and double pane). The objective was to assess the structures resistance. 2. The influence of air flow on the transport of burning embers inside a house. A room was built to scale, and placed inside a wind tunnel, with one window and one door on opposite sides. The objective was to assess the importance of leaving an inside door opened on the probability of burning embers entering the room. 3. The influence of the dimension of openings on a window or door related to the probability of ignition inside a house. The objective was to assess the influence of different window openings in relation to the amount of burning particles that can enter a house. The main results were: 1. The purely radiative heat source provides 1.5 KW/m2 of heat impact in the structure, while the real fire generates 10 Kw/m2. When protected by the blind, the single pane window reaches 30ºC on both sides, and the double pane window has a differential of 10º from the side facing the heat (30ºC) and the opposite side (40ºC). Unprotected window constantly increases temperature until the end of the test. Window blinds reach considerably higher temperatures. PVC loses its consistency above 150ºC and melts. 2. Leaving the inside door closed results in a positive pressure differential of +1Pa from the outside to the inside, inhibiting the air flow. Opening the door in half or full reverts the pressure differential to -6 and -8 times respectively, favouring the air flow from the outside to the inside. The number of particles entering the house follows the same tendency. 3. As the bottom opening in a window increases from 0,5 cm to 4 cm the number of particles that enter the house per second also increases greatly. From 5 cm until 80cm there is no substantial increase in the number of entering particles. This set of exploratory tests proved to be an added value in supporting guidelines for home owners, regarding self-protection in WUI areas.

Keywords: forest fire, wildland urban interface, house vulnerability, house protective elements

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Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Francisco Andree Ramirez-Casas, Alondra Orozco-Gomez, Miguel Angel Sanchez-Caro, Carlos Herrera-Ventosa

Abstract:

High concentrations of particulate matter in the atmosphere pose a threat to human health, especially over areas with high concentrations of population; however, field air pollution monitoring is expensive and time-consuming. In order to achieve reduced costs and global coverage of the whole urban area, remote sensing can be used. This study evaluates PM2.5 concentrations, over the Mexico City´s metropolitan area, are estimated using atmospheric reflectance from LANDSAT 8, satellite imagery and historical PM2.5 measurements of the Automatic Environmental Monitoring Network of Mexico City (RAMA). Through the processing of the available satellite images, a preliminary model was generated to evaluate the optimal bands for the generation of the final model for Mexico City. Work on the final model continues with the results of the preliminary model. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air pollution modeling, Landsat 8, PM2.5, remote sensing

Procedia PDF Downloads 203