Search results for: contractors selection

Authors: Kalu Ram Meena, Aditi Kar Gangopadhyay, Satrajit Mandal

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Two normal populations with different means and same variance are considered, where the variance is known. The population with the smaller sample mean is selected. Various estimators are constructed for the mean of the selected normal population. Finally, they are compared with respect to the bias and MSE risks by the mehod of Monte-Carlo simulation and their performances are analysed with the help of graphs.

Keywords: Estimation after selection, Brewster-Zidek technique.

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Authors: Muhammad Aqil, Ichiro Kita, Akira Yano, Nishiyama Soichi

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This paper presents an alternate approach that uses artificial neural network to simulate the flood level dynamics in a river basin. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach and evolving graphical feature and can be adopted for any similar situation to predict the flood level. The main data processing includes the gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood level data, to train/test the model using various inputs and to visualize results. The program code consists of a set of files, which can as well be modified to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The running results indicate that the decision support system applied to the flood level seems to have reached encouraging results for the river basin under examination. The comparison of the model predictions with the observed data was satisfactory, where the model is able to forecast the flood level up to 5 hours in advance with reasonable prediction accuracy. Finally, this program may also serve as a tool for real-time flood monitoring and process control.

Keywords: Decision Support System, Neural Network, Flood Level

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Authors: S. M. Seyedhosseini, A. Makui, M. Ghadami

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Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.

Keywords: Case based reasoning, Genetic algorithm, Groupdecision making, Product management.

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Authors: Zs. J. Becze, Á. Krivián, M. Sárvári

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Hybrid selection and the application of hybrid specific production technologies are important in terms of the increase of the yield and crop safety of maize. The main explanation for this is climate change, since weather extremes are going on and seem to accelerate in Hungary too.

The biological bases, the selection of appropriate hybrids will be of greater importance in the future. The issue of the adaptability of hybrids will be considerably appreciated. Its good agronomical traits and stress bearing against climatic factors and agrotechnical elements (e.g. different types of herbicides) will be important. There have been examples of 3-4 consecutive droughty years in the past decades, e.g. 1992-1993-1994 or 2009-2011-2012, which made the results of crop production critical. Irrigation cannot be the solution for the problem since currently only the 2% of the arable land is irrigated. Temperatures exceeding the multi-year average are characteristic mainly to the July and August in Hungary, which significantly increase the soil surface evaporation, thus further enhance water shortage. In terms of the yield and crop safety of maize, the weather of these two months is crucial, since the extreme high temperature in July decreases the viability of the pollen and the pistil of maize, decreases the extent of fertilization and makes grain-filling tardy. Consequently, yield and crop safety decrease.

Keywords: Abiotic factors, drought, nutrition content, yield.

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: Computer vision, deep learning, object detection, semiconductor.

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Authors: Seyhan Karaçavuş, Bülent Yılmaz, Ömer Kayaaltı, Semra İçer, Arzu Taşdemir, Oğuzhan Ayyıldız, Kübra Eset, Eser Kaya

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In this study, our goal was to perform tumor staging and subtype determination automatically using different texture analysis approaches for a very common cancer type, i.e., non-small cell lung carcinoma (NSCLC). Especially, we introduced a texture analysis approach, called Law’s texture filter, to be used in this context for the first time. The 18F-FDG PET images of 42 patients with NSCLC were evaluated. The number of patients for each tumor stage, i.e., I-II, III or IV, was 14. The patients had ~45% adenocarcinoma (ADC) and ~55% squamous cell carcinoma (SqCCs). MATLAB technical computing language was employed in the extraction of 51 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), and Laws’ texture filters. The feature selection method employed was the sequential forward selection (SFS). Selected textural features were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). In the automatic classification of tumor stage, the accuracy was approximately 59.5% with k-NN classifier (k=3) and 69% with SVM (with one versus one paradigm), using 5 features. In the automatic classification of tumor subtype, the accuracy was around 92.7% with SVM one vs. one. Texture analysis of FDG-PET images might be used, in addition to metabolic parameters as an objective tool to assess tumor histopathological characteristics and in automatic classification of tumor stage and subtype.

Keywords: Cancer stage, cancer cell type, non-small cell lung carcinoma, PET, texture analysis.

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Authors: M. Kouhirostamkolaei, M. Kouhirostami, M. Sam, J. Woo, A. T. Asutosh, J. Li, C. Kibert

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Construction is one of the most energy consumed activities in the urban environment that results in a significant amount of greenhouse gas emissions around the world. Thus, the impact of the construction industry on global warming is undeniable. Thus, reducing building energy consumption and mitigating carbon production can slow the rate of global warming. The purpose of this study is to determine the amount of energy consumption and carbon dioxide production during the operation phase and the impact of using new shells on energy saving and carbon footprint. Therefore, a residential building with a re-enforced concrete structure is selected in Babolsar, Iran. DesignBuilder software has been used for one year of building operation to calculate the amount of carbon dioxide production and energy consumption in the operation phase of the building. The primary results show the building use 61750 kWh of energy each year. Computer simulation analyzes the effect of changing building shells -using XPS polystyrene and new electrochromic windows- as well as changing the type of lighting on energy consumption reduction and subsequent carbon dioxide production. The results show that the amount of energy and carbon production during building operation has been reduced by approximately 70% by applying the proposed changes. The changes reduce CO₂e to 11345 kg CO₂/yr. The result of this study helps designers and engineers to consider material selection’s process as one of the most important stages of design for improving energy performance of buildings.

Keywords: Construction materials, green construction, energy simulation, carbon footprint, energy saving, concrete structure, DesignBuilder.

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Authors: Zayed Freah Zeadat

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The wellbeing of urban dwellers is strongly associated with the quality and quantity of green infrastructure. Nevertheless, urban green infrastructure is still lagging in many Arab cities, and Jordan is no exception. The capital city of Jordan, Amman, is becoming more urban dense with limited green spaces. The unplanned urban growth in Amman has caused several environmental problems such as urban heat islands, air pollution and lack of green spaces. This study aims to investigate the most suitable drivers to leverage the implementation of urban green infrastructure in Jordan through qualitative and quantitative analysis. The qualitative research includes an extensive literature review to discuss the most common drivers used internationally to promote urban green infrastructure implementation in the literature. The quantitative study employs a questionnaire survey to rank the suitability of each driver. Consultants, contractors and policymakers were invited to fill the research questionnaire according to their judgments and opinions. Relative Importance Index has been used to calculate the weighted average of all drivers and the Kruskal-Wallis test to check the degree of agreement among groups. This study finds that research participants agreed that indirect financial incentives (i.e., tax reductions, reduction in stormwater utility fee, reduction of interest rate, density bonus etc.) are the most effective incentive policy whilst granting sustainability certificate policy is the least effective driver to ensure widespread of UGI is elements in Jordan.

Keywords: sustainable development, urban green infrastructure, relative importance index, urban Jordan

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Authors: Manal Mhada, BrahimEzzahiri, Ouafae Benlhabib

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Seventy-nine accessions, including two local wild species (Chenopodium album and C. murale) and several cultivated quinoa lines developed through recurrent selection in Morocco were screened for their resistance against Peronospora farinose, the causal agent of downy mildew disease. The method of artificial inoculation on detached healthy leaves taken from the middle stage of the plant was used. Screened accessions showed different levels of quantitative resistance to downy mildew as they were scored through the calculation of their area under disease progress curve and their two resistance components, the incubation period and the latent period. Significant differences were found between accessions regarding the three criteria (Incubation Period, Latent Period and Area Under Diseases Progress Curve). Accessions M2a and S938/1 were ranked resistant as they showed the longest Incubation Period (7 days) and Latent Period (12 days) and the lowest area under diseases progress curve (4). Therefore, M24 is the most susceptible accession as it has presented the highest area under diseases progress curve (34.5) and the shortest Incubation Period (1 day) and Latent Period (3 days). In parallel to this evaluation approach, the accession resistance was confirmed under the field conditions through natural infection by using the tree-leaf method. The high correlation found between detached leaf inoculation method and field screening under natural infection allows us to use this laboratory technique with sureness in further selection works.

Keywords: Detached leaf inoculation, Downy mildew, Field screening, Quinoa.

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Authors: Hossein Ahmadi, Ogholgol Nazari

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The necessity of grading and sequencing tasks has led to the development of different criteria in this regard. However, appropriateness of these criteria in different situations is less discussed. This paper attempts to shed more light on the priority of different criteria in relation with different factors including learners, teachers, educational, and cultural factors.

Keywords: Criteria, Grading, Sequencing, Language learning tasks.

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Authors: Lingzhi Li, Jiankun Zhang, Tiantian Gu

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Hazard management that can prevent fatal accidents and property losses is a fundamental process during the buildings’ construction stage. However, due to lack of safety supervision resources and operational pressures, the conduction of hazard management is poor and ineffective in China. In order to improve the quality of construction safety management, it is critical to explore the use of information technologies to ensure that the process of hazard management is efficient and effective. After exploring the existing problems of construction hazard management in China, this paper develops the griddization management model for construction hazard management. First, following the knowledge grid infrastructure, the griddization computing infrastructure for construction hazards management is designed which includes five layers: resource entity layer, information management layer, task management layer, knowledge transformation layer and application layer. This infrastructure will be as the technical support for realizing grid management. Second, this study divides the construction hazards into grids through city level, district level and construction site level according to grid principles. Last, a griddization management process including hazard identification, assessment and control is developed. Meanwhile, all stakeholders of construction safety management, such as owners, contractors, supervision organizations and government departments, should take the corresponding responsibilities in this process. Finally, a case study based on actual construction hazard identification, assessment and control is used to validate the effectiveness and efficiency of the proposed griddization management model. The advantage of this designed model is to realize information sharing and cooperative management between various safety management departments.

Keywords: Construction hazard, grid management, griddization computing, process.

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Authors: C. Ardil

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Fuzzy set theory and its extensions (intuitionistic fuzzy sets, picture fuzzy sets, and neutrosophic sets) have been widely used to address imprecision and uncertainty in complex decision-making. However, they may struggle with inherent indeterminacy and inconsistency in real-world situations. This study introduces uncertainty sets as a promising alternative, offering a structured framework for incorporating both types of uncertainty into decision-making processes.This work explores the theoretical foundations and applications of uncertainty sets. A novel decision-making algorithm based on uncertainty set-based proximity measures is developed and demonstrated through a practical application: selecting the most suitable stealth combat aircraft.

The results highlight the effectiveness of uncertainty sets in ranking alternatives under uncertainty. Uncertainty sets offer several advantages, including structured uncertainty representation, robust ranking mechanisms, and enhanced decision-making capabilities due to their ability to account for ambiguity.Future research directions are also outlined, including comparative analysis with existing MCDM methods under uncertainty, sensitivity analysis to assess the robustness of rankings,and broader application to various MCDM problems with diverse complexities. By exploring these avenues, uncertainty sets can be further established as a valuable tool for navigating uncertainty in complex decision-making scenarios.

Keywords: Uncertainty set, stealth combat aircraft selection multiple criteria decision-making analysis, MCDM, uncertainty proximity analysis

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Authors: Maia Kukhaleishvili, Ekaterine Bulauri, Iveta Megrelishvili, Tamar Shamatava, Tamar Chipashvili

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Plant viruses can cause loss of yield and quality in a lot of important crops. Symptoms of pathogens are variable depending on the cultivars and virus strain. Selection of resistant potato varieties would reduce the risk of virus transmission and significant economic impact. Other way to avoid reduced harvest yields is regular potato seed production sampling and testing for viral infection. The aim of this study was to determine the occurrence and distribution of viral diseases according potato cultivars for further selection of virus-free material in Georgia. During the summer 2015- 2016, 5 potato cultivars (Sante, Laura, Jelly, Red Sonia, Anushka) at 5 different farms located in Akhalkalaki were tested for 6 different potato viruses: Potato virus A (PVA), Potato virus M (PVM), Potato virus S (PVS), Potato virus X (PVX), Potato virus Y (PVY) and potato leaf roll virus (PLRV). A serological method, Double Antibody Sandwich-Enzyme linked Immunosorbent Assay (DASELISA) was used at the laboratory to analyze the results. The result showed that PVY (21.4%) and PLRV (19.7%) virus presence in collected samples was relatively high compared to others. Researched potato cultivars except Jelly and Laura were infected by PVY with different concentrations. PLRV was found only in three potato cultivars (Sante, Jelly, Red Sonia) and PVM virus (3.12%) was characterized with low prevalence. PVX, PVA and PVS virus infection was not reported. It would be noted that 7.9% of samples were containing PVY/PLRV mix infection. Based on the results it can be concluded that PVY and PLRV infections are dominant in all research cultivars. Therefore significant yield losses are expected. Systematic, long-term control of potato viral infection, especially seed-potatoes, must be regarded as the most important factor to increase seed productivity.

Keywords: Diseases, infection, potato, virus.

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Authors: R. B. Ibrahim, M. S. Argungu, I. M. Mungadi

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It is obvious in this present time, internet has become an indispensable part of human life since its inception. The Internet has provided diverse opportunities to make life so easy for human beings, through the adoption of various channels. Among these channels are email, internet banking, video conferencing, and the like. Email is one of the easiest means of communication hugely accepted among individuals and organizations globally. But over decades the security integrity of this platform has been challenged with malicious activities like Phishing. Email phishing is designed by phishers to fool the recipient into handing over sensitive personal information such as passwords, credit card numbers, account credentials, social security numbers, etc. This activity has caused a lot of financial damage to email users globally which has resulted in bankruptcy, sudden death of victims, and other health-related sicknesses. Although many methods have been proposed to detect email phishing, in this research, the results of multiple machine-learning methods for predicting email phishing have been compared with the use of filter-wrapper feature selection. It is worth noting that all three models performed substantially but one outperformed the other. The dataset used for these models is obtained from Kaggle online data repository, while three classifiers: decision tree, Naïve Bayes, and Logistic regression are ensemble (Bagging) respectively. Results from the study show that the Decision Tree (CART) bagging ensemble recorded the highest accuracy of 98.13% using PEF (Phishing Essential Features). This result further demonstrates the dependability of the proposed model.

Keywords: Ensemble, hybrid, filter-wrapper, phishing.

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Authors: A. Mansour Khaki, A. E. Forouhid, S. Hemmati, M. Rahnamay-Naeini

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In this article we research on the drivers’ behavior at intersections. Some significant behaviors are chosen and designed a questionnaire which was about 2 pages. In this questionnaire, samples were being asked to answer by checking the box. The answers have been from always to never. This questionnaire related to our selection’s behaviors. Finally it has been resulted that most of aggressive behaviors were being common in them. Also it has been suggested some solutions for each of them.

Keywords: Driver, behavior, intersection, study.

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Authors: Yu-Cheng Lin

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Construction project control attempts to obtain real-time information and effectively enhance dynamic control and management via information sharing and analysis among project participants to eliminate construction conflicts and project delays. However, survey results for Taiwan indicate that construction commercial project management software is not widely accepted for subcontractors and suppliers. To solve the project communications problems among participants, this study presents a novel system called the Construction Dynamic Teams Communication Management (Con-DTCM) system for small-to-medium sized subcontractors and suppliers in Taiwanese Construction industry, and demonstrates that the Con-DTCM system responds to the most recent project information efficiently and enhances management of project teams (general contractor, suppliers and subcontractors) through web-based environment. Web-based technology effectively enhances information sharing during construction project management, and generates cost savings via the Internet. The main unique characteristic of the proposed Con-DTCM system is extremely user friendly and easily design compared with current commercial project management applications. The Con-DTCM system is applied to a case study of construction of a building project in Taiwan to confirm the proposed methodology and demonstrate the effectiveness of information sharing during the construction phase. The advantages of the Con-DTCM system are in improving project control and management efficiency for general contractors, and in providing dynamic project tracking and management, which enables subcontractors and suppliers to acquire the most recent project-related information. Furthermore, this study presents and implements a generic system architecture.

Keywords: Construction project management, Information System, Portal, Web, Small-to-medium enterprises.

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Authors: Buket Metin

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Buildings cause a variety of loads on the environment due to activities performed at each stage of the building life cycle. Construction is the first stage that affects both the natural and built environments at different steps of the process, which can be defined as transportation of materials within the construction site, formation and preparation of materials on-site and the application of materials to realize the building subsystems. All of these steps require the use of technology, which varies based on the facilities that contractors and subcontractors have. Hence, environmental consequences of the construction process should be tackled by focusing on construction technology options used in every step of the process. This paper presents an environmental decision-making model for assessing on-site performances of subcontractors based on the construction technology options which they can supply. First, construction technologies, which constitute information, tools and methods, are classified. Then, environmental performance criteria are set forth related to resource consumption, ecosystem quality, and human health issues. Finally, the model is developed based on the relationships between the construction technology components and the environmental performance criteria. The Fuzzy Analytical Hierarchy Process (FAHP) method is used for weighting the environmental performance criteria according to environmental priorities of decision-maker(s), while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used for ranking on-site environmental performances of subcontractors using quantitative data related to the construction technology components. Thus, the model aims to provide an insight to decision-maker(s) about the environmental consequences of the construction process and to provide an opportunity to improve the overall environmental performance of construction sites.

Keywords: Construction process, construction technology, decision making, environmental performance, subcontractors.

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Authors: Isao Taguchi, Yasuo Sugai

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This paper proposes an efficient learning method for the layered neural networks based on the selection of training data and input characteristics of an output layer unit. Comparing to recent neural networks; pulse neural networks, quantum neuro computation, etc, the multilayer network is widely used due to its simple structure. When learning objects are complicated, the problems, such as unsuccessful learning or a significant time required in learning, remain unsolved. Focusing on the input data during the learning stage, we undertook an experiment to identify the data that makes large errors and interferes with the learning process. Our method devides the learning process into several stages. In general, input characteristics to an output layer unit show oscillation during learning process for complicated problems. The multi-stage learning method proposes by the authors for the function approximation problems of classifying learning data in a phased manner, focusing on their learnabilities prior to learning in the multi layered neural network, and demonstrates validity of the multi-stage learning method. Specifically, this paper verifies by computer experiments that both of learning accuracy and learning time are improved of the BP method as a learning rule of the multi-stage learning method. In learning, oscillatory phenomena of a learning curve serve an important role in learning performance. The authors also discuss the occurrence mechanisms of oscillatory phenomena in learning. Furthermore, the authors discuss the reasons that errors of some data remain large value even after learning, observing behaviors during learning.

Keywords: data selection, function approximation problem, multistage leaning, neural network, voluntary oscillation.

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Authors: Nachawit Tikul

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This study aimed to determine low-income housing adaptations for flooding, which causes living problems and housing damage, and the results from improvement. Three low-income settlements in Chiang Mai which experienced different flood types, i.e. flash floods in Samukeepattana, drainage floods in Bansanku, and river floods in Kampangam, were chosen for the study. Almost all of the residents improved their houses to protect the property from flood damage by changing building materials to flood damage resistant materials for walls, floors, and other parts of the structure that were below the base of annual flood elevation. They could only build some parts of their own homes, so hiring skilled workers or contractors was still important. Building materials which have no need for any special tools and are easy to access and use for construction, as well as low cost, are selected for construction. The residents in the three slums faced living problems for only a short time and were able to cope with them. This may be due to the location of the three slums near the city where assistance is readily available. But the housing and the existence in the slums can endure only the regular floods and residence still have problems in unusual floods, which have been experienced 1-2 times during the past 10 years. The residents accept the need for evacuations and prepare for them. When faced with extreme floods, residence have evacuated to the nearest safe place such as schools and public building, and come back to repair the houses after the flood. These are the distinguishing characteristics of low-income living which can withstand serious situations due to the simple lifestyle. Therefore, preparation of living areas for use during severe floods and encouraging production of affordable flood resistant materials should be areas of concern when formulating disaster assistance policies for low income people.

Keywords: Flooding, low-income settlement, housing, adaptation.

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Authors: Mehdi Ghayoumi

Abstract:

We have applied new accelerated algorithm for linear discriminate analysis (LDA) in face recognition with support vector machine. The new algorithm has the advantage of optimal selection of the step size. The gradient descent method and new algorithm has been implemented in software and evaluated on the Yale face database B. The eigenfaces of these approaches have been used to training a KNN. Recognition rate with new algorithm is compared with gradient.

Keywords: lda, adaptive, svm, face recognition.

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Authors: Saisundar. S., I Made Darmayuda, Zhou Jun, Krishna Mainali, Simon Ng Sheung Yan, Eran Ofek

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This paper compares the recent transformerless ACDC power converter architectures and provides an assessment of each. A prototype of one of the transformerless AC-DC converter architecture is also presented depicting the feasibility of a small form factor, power supply design. In this paper component selection guidelines to achieve high efficiency AC-DC power conversion are also discussed.

Keywords: AC-DC converter, digitally controlled, switched mode power supply, transformerless.

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Authors: Akram Mahdaviparsa, Tamera McCuen, Vahideh Karimimansoob

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Fire service is responsible for protecting life, assets, and natural resources from fire and other hazardous incidents. Search and rescue in unfamiliar buildings is a vital part of firefighters’ responsibilities. Providing firefighters with precise building information in an easy-to-understand format is a potential solution for mitigating the negative consequences of fire hazards. The negative effect of insufficient knowledge about a building’s indoor environment impedes firefighters’ capabilities and leads to lost property. A data rich building information modeling (BIM) is a potentially useful source in three-dimensional (3D) visualization and data/information storage for fire emergency response. Therefore, this research’s purpose is prioritizing the required information for firefighters from the most important information to the least important. A survey was carried out with firefighters working in the Norman Fire Department to obtain the importance of each building information item. The results show that “the location of exit doors, windows, corridors, elevators, and stairs”, “material of building elements”, and “building data” are the three most important information specified by firefighters. The results also implied that the 2D model of architectural, structural and way finding is more understandable in comparison with the 3D model, while the 3D model of MEP system could convey more information than the 2D model. Furthermore, color in visualization can help firefighters to understand the building information easier and quicker. Sufficient internal consistency of all responses was proven through developing the Pearson Correlation Matrix and obtaining Cronbach’s alpha of 0.916. Therefore, the results of this study are reliable and could be applied to the population.

Keywords: BIM, building fire response, ranking, visualization.

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Authors: T. O. Olwal, K. Djouani, B. J. van Wyk, Y. Hamam, P. Siarry

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Multi-Radio Multi-Channel Wireless Mesh Networks (MRMC-WMNs) operate at the backbone to access and route high volumes of traffic simultaneously. Such roles demand high network capacity, and long “online" time at the expense of accelerated transmission energy depletion and poor connectivity. This is the problem of transmission power control. Numerous power control methods for wireless networks are in literature. However, contributions towards MRMC configurations still face many challenges worth considering. In this paper, an energy-efficient power selection protocol called PMMUP is suggested at the Link-Layer. This protocol first divides the MRMC-WMN into a set of unified channel graphs (UCGs). A UCG consists of multiple radios interconnected to each other via a common wireless channel. In each UCG, a stochastic linear quadratic cost function is formulated. Each user minimizes this cost function consisting of trade-off between the size of unification states and the control action. Unification state variables come from independent UCGs and higher layers of the protocol stack. The PMMUP coordinates power optimizations at the network interface cards (NICs) of wireless mesh routers. The proposed PMMUP based algorithm converges fast analytically with a linear rate. Performance evaluations through simulations confirm the efficacy of the proposed dynamic power control.

Keywords: Effective band inference based power control algorithm (EBIA), Power Selection MRMC Unification Protocol (PMMUP), MRMC State unification Variable Prediction (MRSUP), Wireless Mesh Networks (WMNs).

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Authors: Wei Liu, Xionghui Zhou, Qiang Niu, Yunhao Ni

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3D part library is an ideal approach to reuse the existing design and thus facilitates the modeling process, which will enhance the efficiency. In this paper, we implemented the thought on the SolidWorks platform. The system supports the functions of type and parameter selection, 3D template driving and part assembly. Finally, BOM is exported in Excel format. Experiment shows that our method can satisfy the requirement of die and mold designers.

Keywords: Intelligent, SolidWorks, automatic assembly, part library.

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Authors: Alan Walsh, Peter Walker, Michael Ellis

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There is a real danger that both practitioners and researchers considering risks associated with megaprojects ignore or underestimate the impacts of cultural risk. The paper investigates the potential impacts of a failure to achieve cultural unity between the principal actors executing a megaproject. The principle relationships include the relationships between the principle Contractors and the project stakeholders or the project stakeholders and their principle advisors, Western Consultants. This study confirms that cultural dissonance between these parties can delay or disrupt the megaproject execution and examines why cultural issues should be prioritized as a significant risk factor in megaproject delivery. This paper addresses the practical impacts and potential mitigation measures, which may reduce cultural dissonance for a megaproject's delivery. This information is retrieved from on-going case studies in live infrastructure megaprojects in Europe and the Middle East's GCC states, from Western Consultants' perspective. The collaborating researchers each have at least 30 years of construction experience and are engaged in architecture, project management and contracts management, dealing with megaprojects in Europe or the GCC. After examining the cultural interfaces they have observed during the execution of megaprojects, they conclude that globally, culture significantly influences their efficient delivery. The study finds that cultural risk is ever-present, where different nationalities co-manage megaprojects and that cultural conflict poses a real threat to the timely delivery of megaprojects. The study indicates that the higher the cultural distance between the principal actors, the more pronounced the risk, with the risk of cultural dissonance more prominent in GCC megaprojects. The findings support a more culturally aware and cohesive team approach and recommend cross-cultural training to mitigate the effects of cultural disparity.

Keywords: Cultural risk underestimation, cultural distance, megaproject characteristics, megaproject execution.

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Authors: C. M. De Marco Muscat-Fenech, A. M. Grech La Rosa

Abstract:

Although a lot of importance has been given to resistance analysis for various vessel types, explicit guidelines applied to multihull vessels have not been clearly defined.  The purpose of this investigation is to highlight the importance of the vessel’s layout in terms of three axes, the transverse (separation), the longitudinal (stagger) and the vertical (draught) with respect to resistance analysis. When a vessel has the potential to experience less resistance at a particular range of speeds a vast selection of opportunities are made available for both the commercial and leisure market.

Keywords: Multihull, Reistance, Trimaran.

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Authors: Emre Kara, Şura Karakuzu, Ahmet F. Geylan, Metehan Demir, Kadir Koç, Halil Aykul

Abstract:

The material selection in the design of the sandwich structures is very crucial aspect because of the positive or negative influences of the base materials to the mechanical properties of the entire panel. In the literature, it was presented that the selection of the skin and core materials plays very important role on the behavior of the sandwich. Beside this, the use of the correct adhesive can make the whole structure to show better mechanical results and behavior. In the present work, the static three-point bending tests were performed on the sandwiches having an aluminum alloy foam core, the skins made of three different types of fabrics and two different commercial adhesives (flexible polyurethane and toughened epoxy based) at different values of support span distances by aiming the analyses of their flexural performance in terms of absorbed energy, peak force values and collapse mechanisms. The main results of the flexural loading are: force-displacement curves obtained after the bending tests, peak force and absorbed energy values, collapse mechanisms and adhesion quality. The experimental results presented that the sandwiches with epoxy based toughened adhesive and the skins made of S-Glass Woven fabrics indicated the best adhesion quality and mechanical properties. The sandwiches with toughened adhesive exhibited higher peak force and energy absorption values compared to the sandwiches with flexible adhesive. The use of these sandwich structures can lead to a weight reduction of the transport vehicles, providing an adequate structural strength under operating conditions.

Keywords: Adhesive and adhesion, Aluminum foam, Bending, Collapse mechanisms.

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Authors: Milena Gojny-Zbierowska

Abstract:

In the last decades, psychological tests have been gaining in popularity as a method used for evaluating personnel, and they bring consulting companies solid profits rising by up to 10% each year. The market is offering a growing range of tools for the assessment of personality. Tests are used in organizations mainly in the recruitment and selection of staff. This paper is an attempt to initially diagnose the state of the use of psychological tests in Polish companies on the basis of empirical research.

Keywords: Psychological tests, personality, content analysis, NEO FFI, big five personality model.

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Authors: Jorge Cardoso

Abstract:

Semantic Web services will enable the semiautomatic and automatic annotation, advertisement, discovery, selection, composition, and execution of inter-organization business logic, making the Internet become a common global platform where organizations and individuals communicate with each other to carry out various commercial activities and to provide value-added services. There is a growing consensus that Web services alone will not be sufficient to develop valuable solutions due the degree of heterogeneity, autonomy, and distribution of the Web. This paper deals with two of the hottest R&D and technology areas currently associated with the Web – Web services and the Semantic Web. It presents the synergies that can be created between Web Services and Semantic Web technologies to provide a new generation of eservices.

Keywords: Semantic Web, Web service, Web process, WWW.

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Authors: Hirohide Ushida

Abstract:

This paper discusses an artificial mind model and its applications. The mind model is based on some theories which assert that emotion is an important function in human decision making. An artificial mind model with emotion is built, and the model is applied to action selection of autonomous agents. In three examples, the agents interact with humans and their environments. The examples show the proposed model effectively work in both virtual agents and real robots.

Keywords: Artificial mind, emotion, interactive agent, pet robot

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