Search results for: multiple criteria decision making (MCDM)

Authors: Hamid Mohammadi Makerani

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In recent years, “Bottom-up Planning Approach" has been widely accepted and expanded from planning theorists. Citizen participation becomes more important in decision-making in informal settlements. Many of previous projects and strategies due to ignorance of citizen participation, have been failed facing with informal settlements and in some cases lead physical expansion of these neighbourhoods. According to recent experiences, the new participatory approach was in somehow successful. This paper focuses on local experiences in Iran. A considerable amount of people live in informal settlements in Iran. With the previous methods, the government could not solve the problems of these settlements. It is time to examine new methods such as empowerment of the local citizens and involve them to solve the current physical, social, and economic problems. The paper aims to address the previous and new strategies facing with informal settlements, the conditions under which citizens could be involved in planning process, limits and potentials of this process, the main actors and issues and finally motivations that are able to promote citizen participation. Documentary studies, observation, interview and questionnaire have been used to achieve the above mentioned objectives. Nearly 80 percent of responder in Saadi Community are ready to participate in regularising their neighbourhoods, if pre-conditions of citizen involvement are being provided. These pre-conditions include kind of problem and its severity, the importance of issue, existence of a short-term solution, etc. Moreover, confirmation of dweller-s ownership can promote the citizen engagement in participatory projects.

Keywords: Bottom-up Planning, Citizen Participation, Informal Settlements, Local Resources.

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Authors: T. Chaiechi, N. Stoeckl

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Scarcity of resources for biodiversity conservation gives rise to the need of strategic investment with priorities given to the cost of conservation. While the literature provides abundant methodological options for biodiversity conservation; estimating true cost of conservation remains abstract and simplistic, without recognising dynamic nature of the cost. Some recent works demonstrate the prominence of economic theory to inform biodiversity decisions, particularly on the costs and benefits of biodiversity however, the integration of the concept of true cost into biodiversity actions and planning are very slow to come by, and specially on a farm level. Conservation planning studies often use area as a proxy for costs neglecting different land values as well as protected areas. These literature consider only heterogeneous benefits while land costs are considered homogenous. Analysis with the assumption of cost homogeneity results in biased estimation; since not only it doesn’t address the true total cost of biodiversity actions and plans, but also it fails to screen out lands that are more (or less) expensive and/or difficult (or more suitable) for biodiversity conservation purposes, hindering validity and comparability of the results. Economies of scope” is one of the other most neglected aspects in conservation literature. The concept of economies of scope introduces the existence of cost complementarities within a multiple output production system and it suggests a lower cost during the concurrent production of multiple outputs by a given farm. If there are, indeed, economies of scope then simplistic representation of costs will tend to overestimate the true cost of conservation leading to suboptimal outcomes. The aim of this paper, therefore, is to provide first road review of the various theoretical ways in which economies of scope are likely to occur of how they might occur in conservation. Consequently, the paper addresses gaps that have to be filled in future analysis.

Keywords: Cost, biodiversity conservation, Multi-output production systems, Empirical techniques.

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Authors: Ma. Rosario Concepcion O. Ang, Luis Caezar Ian K. Panganiban, Charmyne B. Mamador, Oliver Dan G. De Luna, Michael D. Bausas, Joselito P. Cruz

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PhilSHORE is a multi-site, multi-device and multicriteria decision support tool designed to support the development of tidal current energy in the Philippines. Its platform is based on Geographic Information Systems (GIS) which allows for the collection, storage, processing, analyses and display of geospatial data. Combining GIS tools with open source web development applications, PhilSHORE becomes a webGIS-based marine spatial planning tool. To date, PhilSHORE displays output maps and graphs of power and energy density, site suitability and site-device analysis. It enables stakeholders and the public easy access to the results of tidal current energy resource assessments and site suitability analyses. Results of the initial development show that PhilSHORE is a promising decision support tool for ORE project developments.

Keywords: GIS, Site Suitability Analysis, Tidal Current Energy Resource Assessment, WebGIS.

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Authors: Chanoknart Mayusoh

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In most of apparel creation, the designer usually uses standard pattern as a fundamental of pattern making. In the design of each kind of apparel, standard pattern is starting point of production. The importance of standard pattern is that it is able to have the apparel fits to general people. Therefore, standard pattern is standardized to be the same. Regardless which type of apparel, its standard pattern will have similar production. Anyhow, the author sees that the apparel design, regardless for which type of apparel, has to stick on the standard pattern as a fundamental of apparel design and this seems to be a limitation of apparel design without any designing alternative being developed. In the research on the creation of contemporary apparel Inspired by the sofa’s pattern structure in Vimanmek Mansion. The author has applied the pattern of the sofa and armchair to be the principle in the apparel design, instead of standard pattern, to create new form of structures and shapes making the contemporary apparel becomes more interesting and different than previous, can be used in daily life, as well as being a new alternative for apparel design. Those who are interesting in such idea can apply and develop it to be more variety further.

Keywords: Contemporary Apparel, Sofa’s Pattern, Armchair’s Pattern, Vimanmek Mansion.

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Authors: Kuen-Ming Shu, Jyun-Wei Chen

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Encapsulated O-rings are specifically designed to address the problem of sealing the most hostile chemicals and extreme temperature applications. Ultrasonic vibration hot embossing and ultrasonic welding techniques provide a fast and reliable method to fabricate encapsulated O-ring. This paper performs the design and analysis method of the acoustic horns with double extrusion to process tube double side flange simultaneously. The paper deals with study through Finite Element Method (FEM) of ultrasonic stepped horn used to process a capsulated O-ring, the theoretical dimensions of horns, and their natural frequencies and amplitudes are obtained through the simulations of COMOSOL software. Furthermore, real horns were fabricated, tested and verified to proof the practical utility of these horns. 

Keywords: Encapsulated O-rings, ultrasonic vibration hot embossing, flange making, acoustic horn, finite element analysis.

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Authors: Francesco Ruscio, Paolo Paoletti, Jens Thomas, Paul Myers, Sebastiano Fichera

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This paper presents the development of a low-cost monitoring system for a hydroponic urban vertical farm, enabling its automation and a quantitative assessment of the farm performance. Urban farming has seen increasing interest in the last decade thanks to the development of energy efficient and affordable LED lights; however, the optimal configuration of such systems (i.e. amount of nutrients, light-on time, ambient temperature etc.) is mostly based on the farmers’ experience and empirical guidelines. Moreover, even if simple, the maintenance of such systems is labor intensive as it requires water to be topped-up periodically, mixing of the nutrients etc. To unlock the full potential of urban farming, a quantitative understanding of the role that each variable plays in the growth of the plants is needed, together with a higher degree of automation. The low-cost monitoring system proposed in this paper is a step toward filling this knowledge and technological gap, as it enables collection of sensor data related to water and air temperature, water level, humidity, pressure, light intensity, pH and electric conductivity without requiring any human intervention. More sensors and actuators can also easily be added thanks to the modular design of the proposed platform. Data can be accessed remotely via a simple web interface. The proposed platform can be used both for quantitatively optimizing the setup of the farms and for automating some of the most labor-intensive maintenance activities. Moreover, such monitoring system can also potentially be used for high-level decision making, once enough data are collected.

Keywords: Automation, hydroponics, internet of things, monitoring system, urban farming.

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Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom

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The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. Previous work established that the Ward-style artificial neural network (ANN) is a suitable tool for developing such models. The current research focused on developing ANN models with reduced average prediction error by increasing the number of distinct observations used in training, adding additional input terms that describe the date of an observation, increasing the duration of prior weather data included in each observation, and reexamining the number of hidden nodes used in the network. Models were created to predict air temperature at hourly intervals from one to 12 hours ahead. Each ANN model, consisting of a network architecture and set of associated parameters, was evaluated by instantiating and training 30 networks and calculating the mean absolute error (MAE) of the resulting networks for some set of input patterns. The inclusion of seasonal input terms, up to 24 hours of prior weather information, and a larger number of processing nodes were some of the improvements that reduced average prediction error compared to previous research across all horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or 12.5%, less than the previous model. Prediction MAEs eight and 12 hours ahead improved by 0.17°C and 0.16°C, respectively, improvements of 7.4% and 5.9% over the existing model at these horizons. Networks instantiating the same model but with different initial random weights often led to different prediction errors. These results strongly suggest that ANN model developers should consider instantiating and training multiple networks with different initial weights to establish preferred model parameters.

Keywords: Decision support systems, frost protection, fruit, time-series prediction, weather modeling

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Authors: Dennys Robson Girardi, Hugo Bulegon, Claudia Maria Moro Barra

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Leprosy is an infectious disease caused by Mycobacterium Leprae, this disease, generally, compromises the neural fibers, leading to the development of disability. Disabilities are changes that limit daily activities or social life of a normal individual. When comes to leprosy, the study of disability considered the functional limitation (physical disabilities), the limitation of activity and social participation, which are measured respectively by the scales: EHF, SALSA and PARTICIPATION SCALE. The objective of this work is to propose an on-line monitoring of leprosy patients, which is based on information scales EHF, SALSA and PARTICIPATION SCALE. It is expected that the proposed system is applied in monitoring the patient during treatment and after healing therapy of the disease. The correlations that the system is between the scales create a variety of information, presented the state of the patient and full of changes or reductions in disability. The system provides reports with information from each of the scales and the relationships that exist between them. This way, health professionals, with access to patient information, can intervene with techniques for the Prevention of Disability. Through the automated scale, the system shows the level of the patient and allows the patient, or the responsible, to take a preventive measure. With an online system, it is possible take the assessments and monitor patients from anywhere.

Keywords: Leprosy, Medical Informatics, Decision SupportSystem, Disability.

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Authors: Zhen Peng, Baifeng Wu

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Modern computing technology enters the era of parallel computing with the trend of sustainable and scalable parallelism. Single Instruction Multiple Data (SIMD) is an important way to go along with the trend. It is able to gather more and more computing ability by increasing the number of processor cores without the need of modifying the program. Meanwhile, in the field of scientific computing and engineering design, many computation intensive applications are facing the challenge of increasingly large amount of data. Data parallel computing will be an important way to further improve the performance of these applications. In this paper, we take the accurate collision detection in building information modeling as an example. We demonstrate a model for constructing a data parallel algorithm. According to the model, a complex object is decomposed into the sets of simple objects; collision detection among complex objects is converted into those among simple objects. The resulting algorithm is a typical SIMD algorithm, and its advantages in parallelism and scalability is unparalleled in respect to the traditional algorithms.

Keywords: Data parallelism, collision detection, single instruction multiple data, building information modeling, continuous scalability.

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Authors: Miguel A. Gómez , Enrique Hilario , Francisco J. Alvarez , Elena Gastiasoro , Antonia Alvarez, Juan L. Larrabe

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Total liquid ventilation can support gas exchange in animal models of lung injury. Clinical application awaits further technical improvements and performance verification. Our aim was to develop a liquid ventilator, able to deliver accurate tidal volumes, and a computerized system for measuring lung mechanics. The computer-assisted, piston-driven respirator controlled ventilatory parameters that were displayed and modified on a real-time basis. Pressure and temperature transducers along with a lineal displacement controller provided the necessary signals to calculate lung mechanics. Ten newborn lambs (<6 days old) with respiratory failure induced by lung lavage, were monitored using the system. Electromechanical, hydraulic and data acquisition/analysis components of the ventilator were developed and tested in animals with respiratory failure. All pulmonary signals were collected synchronized in time, displayed in real-time, and archived on digital media. The total mean error (due to transducers, A/D conversion, amplifiers, etc.) was less than 5% compared to calibrated signals. Improvements in gas exchange and lung mechanics were observed during liquid ventilation, without impairment of cardiovascular profiles. The total liquid ventilator maintained accurate control of tidal volumes and the sequencing of inspiration/expiration. The computerized system demonstrated its ability to monitor in vivo lung mechanics, providing valuable data for early decision-making.

Keywords: immature lamb, perfluorocarbon, pressure-limited, total liquid ventilation, ventilator; volume-controlled

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Authors: G. Martino, F. Silva, E. Marchal

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The control over delivered iron ore blend characteristics is one of the most important aspects of the mining business. The iron ore price is a function of its composition, which is the outcome of the beneficiation process. So, end-to-end integrated planning of mine operations can reduce risks of penalties on the iron ore price. In a standard iron mining company, the production chain is composed of mining, ore beneficiation, and client supply. When mine planning and client supply decisions are made uncoordinated, the beneficiation plant struggles to deliver the best blend possible. Technological improvements in several fields allowed bridging the gap between departments and boosting integrated decision-making processes. Clusterization and classification algorithms over historical production data generate reasonable previsions for quality and volume of iron ore produced for each pile of run-of-mine (ROM) processed. Mathematical modeling can use those deterministic relations to propose iron ore blends that better-fit specifications within a delivery schedule. Additionally, a model capable of representing the whole production chain can clearly compare the overall impact of different decisions in the process. This study shows how flexibilization combined with a planning optimization model between the mine and the ore beneficiation processes can reduce risks of out of specification deliveries. The model capabilities are illustrated on a hypothetical iron ore mine with magnetic separation process. Finally, this study shows ways of cost reduction or profit increase by optimizing process indicators across the production chain and integrating the different plannings with the sales decisions.

Keywords: Clusterization and classification algorithms, integrated planning, optimization, mathematical modeling, penalty minimization.

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Authors: Gonzalo Rubio, Eusebio Valero, Sven Lanzan

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The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations. As a results of this, Computational Fluid Dynamic (CFD) solvers are widely used in the aeronautical field. These solvers require the correct selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on the proper choice of these parameters. In this paper we create an expert system capable of making an accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver. Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time required for the convergence of a CFD solver.

Keywords: Artificial Neural Network, Computational Fluid Dynamics, Optimization

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Authors: Abdi T. Abdalla, Justinian Anatory

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This paper investigates the possibility of improving throughputs of some Media Access Controls protocols such as ALOHA, slotted ALOHA and Carrier Sense Multiple Access with Collision Avoidance with the aim of increasing the performance of Powerline access networks. In this investigation, the real Powerline network topology in Tanzania located in Dar es Salaam City, Kariakoo area was used as a case study. During this investigation, Wireshark Network Protocol Analyzer was used to analyze data traffic of similar existing network for projection purpose and then the data were simulated using MATLAB. This paper proposed and analyzed three improvement techniques based on collision domain, packet length and combination of the two. From the results, it was found that the throughput of Carrier Sense Multiple Access with Collision Avoidance protocol improved noticeably while ALOHA and slotted ALOHA showed insignificant changes especially when the hybrid techniques were employed.

Keywords: Access Network, ALOHA, Broadband Powerline Communication, Slotted ALOHA, CSMA/CA and MAC Protocols.

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Authors: Indunil Jayatilake, Warna Karunasena, Weena Lokuge

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An Australian manufacturer has fabricated an innovative GFRP sandwich panel made from E-glass fiber skin and a modified phenolic core for structural applications. Debonding, which refers to separation of skin from the core material in composite sandwiches, is one of the most common types of damage in composites. The presence of debonding is of great concern because it not only severely affects the stiffness but also modifies the dynamic behaviour of the structure. Generally it is seen that the majority of research carried out has been concerned about the delamination of laminated structures whereas skin-core debonding has received relatively minor attention. Furthermore it is observed that research done on composite slabs having multiple skin-core debonding is very limited. To address this gap, a comprehensive research investigating dynamic behaviour of composite panels with single and multiple debonding is presented. The study uses finite-element modelling and analyses for investigating the influence of debonding on free vibration behaviour of single and multilayer composite sandwich panels. A broad parametric investigation has been carried out by varying debonding locations, debonding sizes and support conditions of the panels in view of both single and multiple debonding. Numerical models were developed with Strand7 finite element package by innovatively selecting the suitable elements to diligently represent their actual behavior. Three-dimensional finite element models were employed to simulate the physically real situation as close as possible, with the use of an experimentally and numerically validated finite element model. Comparative results and conclusions based on the analyses are presented. For similar extents and locations of debonding, the effect of debonding on natural frequencies appears greatly dependent on the end conditions of the panel, giving greater decrease in natural frequency when the panels are more restrained. Some modes are more sensitive to debonding and this sensitivity seems to be related to their vibration mode shapes. The fundamental mode seems generally the least sensitive mode to debonding with respect to the variation in free vibration characteristics. The results indicate the effectiveness of the developed three dimensional finite element models in assessing debonding damage in composite sandwich panels.

Keywords: Debonding, free vibration behaviour, GFRP sandwich panels, three dimensional finite element modelling.

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Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

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Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, KL divergence, quickest change detection, time series data.

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Authors: Ab. Rashid M.F.F., Gan S.Y., Muhammad N.Y.

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Surface roughness (Ra) is one of the most important requirements in machining process. In order to obtain better surface roughness, the proper setting of cutting parameters is crucial before the process take place. This research presents the development of mathematical model for surface roughness prediction before milling process in order to evaluate the fitness of machining parameters; spindle speed, feed rate and depth of cut. 84 samples were run in this study by using FANUC CNC Milling α-Τ14ιE. Those samples were randomly divided into two data sets- the training sets (m=60) and testing sets(m=24). ANOVA analysis showed that at least one of the population regression coefficients was not zero. Multiple Regression Method was used to determine the correlation between a criterion variable and a combination of predictor variables. It was established that the surface roughness is most influenced by the feed rate. By using Multiple Regression Method equation, the average percentage deviation of the testing set was 9.8% and 9.7% for training data set. This showed that the statistical model could predict the surface roughness with about 90.2% accuracy of the testing data set and 90.3% accuracy of the training data set.

Keywords: Surface roughness, regression analysis.

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Authors: D. Kliaugaitė, J. K, Staniškis

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In this study tree types of multilayer gas barrier plastic packaging films were compared using life cycle assessment as a tool for resource efficient and environmentally low-impact materials selection. The first type of multilayer packaging film (PET-AlOx/LDPE) consists of polyethylene terephthalate with barrier layer AlOx (PET-AlOx) and low density polyethylene (LDPE). The second type of polymer film (PET/PE-EVOH-PE) is made of polyethylene terephthalate (PET) and co-extrusion film PE-EVOH-PE as barrier layer. And the third one type of multilayer packaging film (PET-PVOH/LDPE) is formed from polyethylene terephthalate with barrier layer PVOH (PET-PVOH) and low density polyethylene (LDPE).

All of analyzed packaging has significant impact to resource depletion, because of raw materials extraction and energy use and production of different kind of plastics. Nevertheless the impact generated during life cycle of functional unit of II type of packaging (PET/PE-EVOH-PE) was about 25% lower than impact generated by I type (PET-AlOx/LDPE) and III type (PET-PVOH/LDPE) of packaging.

Result revealed that the contribution of different gas barrier type to the overall environmental problem of packaging is not significant. The impact are mostly generated by using energy and materials during raw material extraction and production of different plastic materials as plastic polymers material as PE, LDPE and PET, but not gas barrier materials as AlOx, PVOH and EVOH.

The LCA results could be useful in different decision-making processes, for selecting resource efficient and environmentally low-impact materials.

Keywords: Polymer packaging, life cycle assessment, resource efficiency.

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Authors: F. Fabeil Noor, Roslinah Mahmud, Janice L. H. Nga, Rasid Mail

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In Malaysia, particularly in Sabah, the government has been promoting entrepreneurship among rural people to encourage them to earn their living by making good use of the diverse natural resources and local cultures of Sabah. Nevertheless, despite the government’s aim to encourage more local community in rural area to involve in entrepreneurship, the involvement of community in entrepreneurial activity is still low. It is crucial to identify the factors stimulate (or prevent) the involvement of rural community in Sabah in entrepreneurial activity. Therefore, this study tries to investigate the personal and contextual factors that may have impact on decision to start a business among the local community in Mantanani Island. In addition, this study also aims to identify the perceived benefits they receive from entrepreneurial activity. A structured face-to-face interview was conducted with 61 local communities in Mantanani Island. Data analysis revealed that passion, personal skills and self-confidence are the significant internal factors to entrepreneurial activity, whereas access to finance, labour and infrastructure are the significant external factors that are found to influence entrepreneurship. In terms of perceived rewards they received from taking up small business, it was found that respondents are predominantly agreed that entrepreneurship offers financial benefit than non-financial. In addition, this study also offers several suggestions for entrepreneurship development in Mantanani Island and it is hoped that this study may help the related agency to develop effective support policies in order to encourage more people in rural area to involve in entrepreneurship.

Keywords: Entrepreneurship, motivation, perceived rewards, rural community.

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Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

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Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as physiological vital signs, images and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful to influence the judgement of clinical sentiment in ICU clinical notes. This paper presents two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of a clinical transformer model that can reliably predict clinical sentiment for notes of COVID patients in ICU. We train the model on clinical notes for COVID-19 patients, ones not previously seen by Bio_ClinicalBERT or Bio_Discharge_Summary_BERT. The model which was based on Bio_ClinicalBERT achieves higher predictive accuracy than the one based on Bio_Discharge_Summary_BERT (Acc 93.33%, AUC 0.98, and Precision 0.96). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and Precision 0.92).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation.

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Authors: Zhila Safari, Ali Ashrafizadeh, Najaf Hedayat

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Thermodynamics characterization Sesame oil extraction by Acetone, Hexane and Benzene has been evaluated. The 120 hours experimental Data were described by a simple mathematical model. According to the simulation results and the essential criteria, Acetone is superior to other solvents but under certain conditions where oil extraction takes place Hexane is superior catalyst.

Keywords: Liquid-solid extraction, seed oil, ThermodynamicStudy.

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Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

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Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: Dynamic modeling, missing data, multiple imputation, physiological measures.

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Authors: P. V. S. Mascarenhas, B. C. P. Albuquerque, D. J. F. Campos, L. L. Almeida, V. R. Domingues, L. C. S. M. Ozelim

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Retaining slope structures are increasingly considered in geotechnical engineering projects due to extensive urban cities growth. These kinds of engineering constructions may present instabilities over the time and may require reinforcement or even rebuilding of the structure. In this context, statistical analysis is an important tool for decision making regarding retaining structures. This study approaches the failure probability of the construction of a retaining wall over the debris of an old and collapsed one. The new solution’s extension length will be of approximately 350 m and will be located over the margins of the Lake Paranoá, Brasilia, in the capital of Brazil. The building process must also account for the utilization of the ruins as a caisson. A series of in situ and laboratory experiments defined local soil strength parameters. A Standard Penetration Test (SPT) defined the in situ soil stratigraphy. Also, the parameters obtained were verified using soil data from a collection of masters and doctoral works from the University of Brasília, which is similar to the local soil. Initial studies show that the concrete wall is the proper solution for this case, taking into account the technical, economic and deterministic analysis. On the other hand, in order to better analyze the statistical significance of the factor-of-safety factors obtained, a Monte Carlo analysis was performed for the concrete wall and two more initial solutions. A comparison between the statistical and risk results generated for the different solutions indicated that a Gabion solution would better fit the financial and technical feasibility of the project.

Keywords: Economical analysis, probability of failure, retaining walls, statistical analysis.

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Authors: D. Tedesco, G. Feletti, P. Trucco

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The present study aims to develop a Decision Support System (DSS) to support operational decisions in Emergency Medical Service (EMS) systems regarding the assignment of medical emergency requests to Emergency Departments (ED). This problem is called “hospital selection” and concerns the definition of policies for the selection of the ED to which patients who require further treatment are transported by ambulance. The employed research methodology consists of a first phase of review of the technical-scientific literature concerning DSSs to support the EMS management and, in particular, the hospital selection decision. From the literature analysis, it emerged that current studies mainly focused on the EMS phases related to the ambulance service and consider a process that ends when the ambulance is available after completing a mission. Therefore, all the ED-related issues are excluded and considered as part of a separate process. Indeed, the most studied hospital selection policy turned out to be proximity, thus allowing to minimize the travelling time and to free-up the ambulance in the shortest possible time. The purpose of the present study consists in developing an optimization model for assigning medical emergency requests to the EDs also considering the expected time performance in the subsequent phases of the process, such as the case mix, the expected service throughput times, and the operational capacity of different EDs in hospitals. To this end, a Discrete Event Simulation (DES) model was created to compare different hospital selection policies. The model was implemented with the AnyLogic software and finally validated on a realistic case. The hospital selection policy that returned the best results was the minimization of the Time To Provider (TTP), considered as the time from the beginning of the ambulance journey to the ED at the beginning of the clinical evaluation by the doctor. Finally, two approaches were further compared: a static approach, based on a retrospective estimation of the TTP, and a dynamic approach, focused on a predictive estimation of the TTP which is determined with a constantly updated Winters forecasting model. Findings reveal that considering the minimization of TTP is the best hospital selection policy. It allows to significantly reducing service throughput times in the ED with a negligible increase in travel time. Furthermore, an immediate view of the saturation state of the ED is produced and the case mix present in the ED structures (i.e., the different triage codes) is considered, as different severity codes correspond to different service throughput times. Besides, the use of a predictive approach is certainly more reliable in terms on TTP estimation, than a retrospective approach. These considerations can support decision-makers in introducing different hospital selection policies to enhance EMSs performance.

Keywords: Emergency medical services, hospital selection, discrete event simulation, forecast model.

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Authors: Jin Hou, Xia Wang, Fang Xu, Viet Dung Nguyen, Ling Wu

Abstract:

There has been a growing interest in implementing humanoid avatars in networked virtual environment. However, most existing avatar communication systems do not take avatars- social backgrounds into consideration. This paper proposes a novel humanoid avatar animation system to represent personalities and facial emotions of avatars based on culture, profession, mood, age, taste, and so forth. We extract semantic keywords from the input text through natural language processing, and then the animations of personalized avatars are retrieved and displayed according to the order of the keywords. Our primary work is focused on giving avatars runtime instruction from multiple natural languages. Experiments with Chinese, Japanese and English input based on the prototype show that interactive avatar animations can be displayed in real time and be made available online. This system provides a more natural and interesting means of human communication, and therefore is expected to be used for cross-cultural communication, multiuser online games, and other entertainment applications.

Keywords: personalized avatar, mutiple natural luanguage processing, social backgrounds, anmimation, human computer interaction

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Authors: P. Pongsumpun

Abstract:

One of the important tropical diseases is Chikunkunya. This disease is transmitted between the human by the insect-borne virus, of the genus Alphavirus. It occurs in Africa, Asia and the Indian subcontinent. In Thailand, the incidences due to this disease are increasing every year. In this study, the transmission of this disease is studied through dynamical model analysis.

Keywords: Chikunkunya, dynamical model, Endemic region, Routh-Hurwitz criteria.

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Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

Abstract:

In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary design optimisation, rule based architecture, aircraft design, decision support system.

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Authors: M. Ondova, A. Estokova

Abstract:

Rapid industrialization results in increased use of natural resources bring along serious ecological and environmental imbalance due to the dumping of industrial wastes. Principles of sustainable construction have to be accepted with regard to the consumption of natural resources and the production of harmful emissions. Cement is a great importance raw material in the building industry and today is its large amount used in the construction of concrete pavements. Concerning raw materials cost and producing CO₂ emission the replacing of cement in concrete mixtures with more sustainable materials is necessary. To reduce this environmental impact people all over the world are looking for a solution. Over a period of last ten years, the image of fly ash has completely been changed from a polluting waste to resource material and it can solve the major problems of cement use. Fly ash concretes are proposed as a potential approach for achieving substantial reductions in cement. It is known that it improves the workability of concrete, extends the life cycle of concrete roads, and reduces energy use and greenhouse gas as well as amount of coal combustion products that must be disposed in landfills.

Life cycle assessment also proved that a concrete pavement with fly ash cement replacement is considerably more environmentally friendly compared to standard concrete roads. In addition, fly ash is cheap raw material, and the costs saving are guaranteed. The strength properties, resistance to a frost or de-icing salts, which are important characteristics in the construction of concrete pavements, have reached the required standards as well. In terms of human health it can´t be stated that a concrete cover with fly ash could be dangerous compared with a cover without fly ash. Final Multi-criteria analysis also pointed that a concrete with fly ash is a clearly proper solution.

Keywords: Life cycle assessment, fly ash, waste, concrete pavements

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

Abstract:

In many data mining applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. In this paper we consider partially monotone prediction problems, where the target variable depends monotonically on some of the input variables but not on all. We propose a novel method to construct prediction models, where monotone dependences with respect to some of the input variables are preserved by virtue of construction. Our method belongs to the class of mixture models. The basic idea is to convolute monotone neural networks with weight (kernel) functions to make predictions. By using simulation and real case studies, we demonstrate the application of our method. To obtain sound assessment for the performance of our approach, we use standard neural networks with weight decay and partially monotone linear models as benchmark methods for comparison. The results show that our approach outperforms partially monotone linear models in terms of accuracy. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: mixture models, monotone neural networks, partially monotone models, partially monotone problems.

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Authors: Mehmet Altınöz

Abstract:

Organizational communication is an administrative function crucial especially for executives in the implementation of organizational and administrative functions. Executives spend a significant part of their time on communicative activities. Doing his or her daily routine, arranging meeting schedules, speaking on the telephone, reading or replying to business correspondence, or fulfilling the control functions within the organization, an executive typically engages in communication processes. Efficient communication is the principal device for the adequate implementation of administrative and organizational activities. For this purpose, management needs to specify the kind of communication system to be set up and the kind of communication devices to be used. Communication is vital for any organization. In conventional offices, communication takes place within the hierarchical pyramid called the organizational structure, and is known as formal or informal communication. Formal communication is the type that works in specified structures within the organizational rules and towards the organizational goals. Informal communication, on the other hand, is the unofficial type taking place among staff as face-to-face or telephone interaction. Communication in virtual as well as conventional offices is essential for obtaining the right information in administrative activities and decision-making. Virtual communication technologies increase the efficiency of communication especially in virtual teams. Group communication is strengthened through an inter-group central channel. Further, ease of information transmission makes it possible to reach the information at the source, allowing efficient and correct decisions. Virtual offices can present as a whole the elements of information which conventional offices produce in different environments. At present, virtual work has become a reality with its pros and cons, and will probably spread very rapidly in coming years, in line with the growth in information technologies.

Keywords: Organization, conventional office, virtual office, communication, communication model, communication functions, communication methods, vertical communication, linear communication, diagonal communication

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

Abstract:

The application of stability theory has led to detailed studies of different types of vessels; however, the shortage of information relating to multihull vessels demanded further investigation. This study shows that the position of the hulls has a very influential effect on both the transverse and longitudinal stability of the tricore. HSC stability code is applied for the optimisation of the hull configurations. Such optimization criteria would undoubtedly aid the performance of the vessel for both commercial or leisure purposes

Keywords: Stability, Multihull, Tricore

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