Search results for: hybrid inventory

Authors: Keisuke Takahata, Hiroshi Suetsugu

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Forest height is an important parameter for forest biomass estimation, and precise elevation data is essential for accurate forest height estimation. There are several globally or nationally available digital elevation models (DEMs) like SRTM and ASTER. However, its accuracy is reported to be low particularly in mountainous areas where there are closed canopy or steep slope. Recently, space-borne LiDAR, such as the Global Ecosystem Dynamics Investigation (GEDI), have started to provide sparse but accurate ground elevation and canopy height estimates. Several studies have reported the high degree of accuracy in their elevation products on their exact footprints, while it is not clear how this sparse information can be used for wider area. In this study, we developed a digital terrain model correction algorithm by spatially interpolating the difference between existing DEMs and GEDI elevation products by using Gaussian Process (GP) regression model. The result shows that our GP-based methodology can reduce the mean bias of the elevation data from 3.7m to 0.3m when we use airborne LiDAR-derived elevation information as ground truth. Our algorithm is also capable of quantifying the elevation data uncertainty, which is critical requirement for biomass inventory. Upcoming satellite-LiDAR missions, like MOLI (Multi-footprint Observation Lidar and Imager), are expected to contribute to the more accurate digital terrain model generation.

Keywords: digital terrain model, satellite LiDAR, gaussian processes, uncertainty quantification

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Authors: Peyman Honarmandi, Mazen Alhirsh

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Banner towing is a major form of advertisement. It consists of a banner showing a logo or a selection of words or letters being towed by an aircraft. Traditionally bush planes have been used to tow banners given their high thrust capabilities; however, with the development of remote-controlled (RC) aircraft, they could be a good replacement as RC planes mitigate the risk of human life and can be easier to operate. This paper studies the best banner design to be towed by an RC aircraft. This is done by conducting wind tunnel testing on an array of banners with different materials and designs. A pull gauge is used to record the drag force during testing, which is then used to calculate the coefficient of drag, Cd. The testing results show that the best banner design would be a hybrid design with a solid and mesh material. The design with the lowest Cd of 0.082 was a half ripstop nylon half polyester mesh design. On the other hand, the design with the highest Cd of 0.305 involved incorporating a tail chute to decrease fluttering.

Keywords: aerodynamics of banner, banner design, banner towing, drag coefficients of banner, RC aircraft banner

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Authors: Hesham Abd Elkhalek, Sherif M. Hafez, Yasser M. El Fahham

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Allocating limited budget to maintain bridge networks and selecting effective maintenance strategies for each bridge represent challenging tasks for maintenance managers and decision makers. In Egypt, bridges are continuously deteriorating. In many cases, maintenance works are performed due to user complaints. The objective of this paper is to develop a practical and reliable framework to manage the maintenance, repair, and rehabilitation (MR&R) activities of Bridges network considering performance and budget limits. The model solves an optimization problem that maximizes the average condition of the entire network given the limited available budget using Genetic Algorithm (GA). The framework contains bridge inventory, condition assessment, repair cost calculation, deterioration prediction, and maintenance optimization. The developed model takes into account multiple parameters including serviceability requirements, budget allocation, element importance on structural safety and serviceability, bridge impact on network, and traffic. A questionnaire is conducted to complete the research scope. The proposed model is implemented in software, which provides a friendly user interface. The framework provides a multi-year maintenance plan for the entire network for up to five years. A case study of ten bridges is presented to validate and test the proposed model with data collected from Transportation Authorities in Egypt. Different scenarios are presented. The results are reasonable, feasible and within acceptable domain.

Keywords: bridge management systems (BMS), cost optimization condition assessment, fund allocation, Markov chain

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Authors: Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir

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NSGA-II is one of the most well-known and most widely used evolutionary algorithms. In addition to its new versions, such as NSGA-III, there are several modified types of this algorithm in the literature. In this paper, a hybrid NSGA-II algorithm has been suggested for solving the multi-objective flexible job shop scheduling problem. For a better search, new neighborhood-based crossover and mutation operators are defined. To create new generations, the neighbors of the selected individuals by the tournament selection are constructed. Also, at the end of each iteration, before sorting, neighbors of a certain number of good solutions are derived, except for solutions protected by elitism. The neighbors are generated using a constraint-based neural network that uses various constructs. The non-dominated sorting and crowding distance operators are same as the classic NSGA-II. A comparison based on some multi-objective benchmarks from the literature shows the efficiency of the algorithm.

Keywords: flexible job shop scheduling problem, multi-objective optimization, NSGA-II algorithm, neighborhood structures

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Authors: Sultan Noman Qasem

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This paper presents an evolutionary algorithm for solving multi-objective optimization problems-based artificial neural network (ANN). The multi-objective evolutionary algorithm used in this study is genetic algorithm while ANN used is radial basis function network (RBFN). The proposed algorithm named memetic elitist Pareto non-dominated sorting genetic algorithm-based RBFNN (MEPGAN). The proposed algorithm is implemented on medical diseases problems. The experimental results indicate that the proposed algorithm is viable, and provides an effective means to design multi-objective RBFNs with good generalization capability and compact network structure. This study shows that MEPGAN generates RBFNs coming with an appropriate balance between accuracy and simplicity, comparing to the other algorithms found in literature.

Keywords: radial basis function network, hybrid learning, multi-objective optimization, genetic algorithm

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Authors: Fatemeh Saadat Ghareh Bagh, Srimanta Ray, Jerald Lalman

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Lignin, the largest inventory of organic carbon with a high caloric energy value is a major component in woody and non-woody biomass. In pulping mills, a large amount of the lignin is burned for energy. At the same time, the phenolic structure of lignin enables it to be converted to value-added compounds.This study has focused on extracting lignin from black liquor using deep eutectic solvents (DESs). Therefore, three choline chloride (ChCl)-DESs paired with lactic acid (LA) (1:11), oxalic acid.2H₂O (OX) (1:4), and malic acid (MA) (1:3) were synthesized at 90oC and atmospheric pressure. The kinetics of lignin recovery from black liquor using DES was investigated at three moderate temperatures (338, 353, and 368 K) at time intervals from 30 to 210 min. The extracted lignin (acid soluble lignin plus Klason lignin) was characterized by Fourier transform infrared spectroscopy (FTIR). The FTIR studies included comparing the extracted lignin with a model Kraft lignin. The extracted lignin was characterized spectrophotometrically to determine the acid soluble lignin (ASL) [TAPPI UM 250] fraction and Klason lignin was determined gravimetrically using TAPPI T 222 om02. The lignin extraction reaction using DESs was modeled by first-order reaction kinetics and the activation energy of the process was determined. The ChCl:LA-DES recovered lignin was 79.7±2.1% at 368K and a DES:BL ratio of 4:1 (v/v). The quantity of lignin extracted for the control solvent, [emim][OAc], was 77.5+2.2%. The activation energy measured for the LA-DES system was 22.7 KJ mol⁻¹, while the activation energy for the OX-DES and MA-DES systems were 7.16 KJ·mol⁻¹ and 8.66 KJ·mol⁻¹ when the total lignin recovery was 75.4 ±0.9% and 62.4 ±1.4, % respectively.

Keywords: black liquor, deep eutectic solvents, kinetics, lignin

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Authors: Jens Hagman, Jenny Janhager Stier, Ellen Olausson, Anne Y. Faxer, Ana Magazinius

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Sweden has the second highest electric vehicle (plug-in hybrid and battery electric vehicle) sales per capita in Europe but in relation to sales of internal combustion engine electric vehicles sales are still minuscular (< 4%). Much research effort has been placed on various technical and user focused barriers and enablers for adoption of electric vehicles. Less effort has been placed on investigating the retail (dealership-customer) sales process of vehicles in general and electric vehicles in particular. Arguably, no one ought to be better informed about needs and desires of potential electric vehicle buyers than car salesmen, originating from their daily encounters with customers at the dealership. The aim of this paper is to explore the conditions of selling electric vehicle from a car salesmen’s perspective. This includes identifying barriers and enablers for electric vehicle sales originating from internal (dealership and brand) and external (customer, government) sources. In this interview study five car brands (manufacturers) that sell both electric and internal combustion engine vehicles have been investigated. A total of 15 semi-structured interviews have been conducted (three per brand, in rural and urban settings and at different dealerships). Initial analysis reveals several barriers and enablers, experienced by car salesmen, which influence electric vehicle sales. Examples of as reported by car salesmen identified barriers are: -Electric vehicles earn car salesmen less commission on average compared to internal combustion engine vehicles. -It takes more time to sell and deliver an electric vehicle than an internal combustion engine vehicle. -Current leasing contracts entails relatively low second-hand value estimations for electric vehicles and thus a high leasing fee, which negatively affects the attractiveness of electric vehicles for private consumers in particular. -High purchasing price discourages many consumers from considering electric vehicles. -The education and knowledge level of electric vehicles differs between car salesmen, which could affect their self-confidence in meeting well prepared and question prone electric vehicle buyers. Examples of identified enablers are: -Company car tax regulation promotes sales of electric vehicles; in particular, plug-in hybrid electric vehicles are sold extensively to companies (up to 95 % of sales). -Low operating cost of electric vehicles such as fuel and service is an advantage when understood by consumers. -The drive performance of electric vehicles (quick, silent and fun to drive) is attractive to consumers. -Environmental aspects are considered important for certain consumer groups. -Fast technological improvements, such as increased range are opening up a wider market for electric vehicles. -For one of the brands; attractive private lease campaigns have proved effective to promote sales. This paper gives insights of an important but often overlooked aspect for the diffusion of electric vehicles (and durable products in general); the interaction between car salesmen and customers at the critical acquiring moment. Extracted through interviews with multiple car salesmen. The results illuminate untapped potential for sellers (salesmen, dealerships and brands) to mitigating sales barriers and strengthening sales enablers and thus becoming a more important actor in the electric vehicle diffusion process.

Keywords: customer barriers, electric vehicle promotion, sales of electric vehicles, interviews with car salesmen

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Authors: Fabiola Trejo Perez, Rolando Diaz Loving

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Sexual pleasure consists of the positively valued feelings induced by sexual stimuli, but it is also weighed down by pop-psychological baggage, and subjected to cross-cultural and cross-historical variation. Social and individual interpretations of what can or can’t be considered as pleasurable are intertwined with culture’s predominant values, norms and beliefs. For each culture, sexual norms work as a guide to be followed in order to model socially accepted behaviors. Therefore, cultural messages regarding sexuality are usually directed to restrict men and women from enjoyment, sexual satisfaction and specifically orgasm. Given that sexual pleasure hasn’t been recognized as an accepted topic of open discussion, particularly for women, people have to eventually complement their knowledge using their own experience filling in the blanks from what little has been said. Thus, this research aims to identify which are the particular social messages associated with the easing or inhibition of sexual pleasure. Three hundred Mexican men and women ages 25 to 35 years old answered a self-report survey composed by the Inventory of facilitators and inhibitors of sexual pleasure and the Sexual premises questionnaire via pencil-paper and online. Results show a high endorsement to double standard messages associated with higher levels of sexual pleasure inhibitors like feeling pressured to have sexual activity, guilt and inability to reach orgasm, in contrast with people who endorse more permissive norms and beliefs, feeling connected to their sexual partners and confident with themselves. These results illustrate that the shaping of sexuality, from experience to society, is comprised of an important relationship between culture and sexual pleasure.

Keywords: culture, sexual double standard, sexual norms and beliefs, sexual pleasure

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Authors: Franco Ceasar Agbalog, Shintaro Yukawa

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Mindfulness is increasingly being used as a method for resolving conflict. However, less is known about how its positive outcome develops. To better understand the underlying effects of mindfulness on conflict resolution strategies, this study examines the potential mediating factors between them. The researchers hypothesized that Emotional Intelligence (EI) mediates the effects of mindfulness on conflict resolution strategies due to its similar components to the benefits of mindfulness, such as awareness and control of one’s emotions, awareness and understanding of other’s emotions, and cultivation of compassion and empathy. Using a random sampling, 157 participants completed three questionnaires: Five Facet Mindfulness Questionnaire (FFMQ), Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF), and Rahim Organizational Conflict Inventory-II (ROCI-II). Utilizing the SPSS Process, results showed a significant relationship between mindfulness and EI. However, among the five approaches to conflict resolution, only the integrating style was significantly related to EI. Following the principle of Mediation Analysis, mindfulness has an indirect effect on integrating style. Moreover, mindfulness and conflict resolution strategies were not significantly related. This is a rather surprising result because research literature has always indicated a positive relationship between the two variables. These findings imply that although integrating style is generally considered the best approach in handling conflict, each style may be appropriate depending on the situation. Mindfulness allows practitioners to have a holistic view of the conflict situation and choose the approach they think best for that specific situation. This could explain why statistically, there is no direct effect of mindfulness on conflict resolution strategies. This work provides basis for the necessity to investigate the factors of conflict instead of the conflict resolution strategies; factors that can be manipulated and may be directly influenced by mindfulness.

Keywords: conflict resolution strategies, emotional intelligence, mindfulness and conflict, ROCI-II integrating style

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Authors: Mila Radovanovic, Jovana Jestrovic, Ivana Mihic

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Deciding whether to have a child is a complex psychological process, and the child's birth is an everlasting change in the life of the family. Researchers from all over the world have been recognized the importance of the motivation for parenthood in latter family life, but there is no very clear picture of factors which make the difference in this motivation. One of these factors can be the method of conception and results of the earlier studies are different- some showed the differences, but the others did not. The aim of this study was to determine the type and intensity of motivation for parenting among women in Serbia and to examine whether there are differences in motivation depend on the method of conception. The total sample consisted of 94 women- 57 pregnant women who conceive naturally and the same number of women in the process of in vitro fertilization, who still haven’t known the final result of the process- are they pregnant or no. The Child Study Inventory, which estimates four types of motivation for parenthood- altruistic, instrumental, narcissistic and fatalistic-was used for this purpose. Multivariate analysis of variance was used to answer the main question of the study. The results indicate that there is no statistically significant difference between the two groups of women, while the most common is the altruistic motivation that emphasizes the psychological value of the child, and sees the motivation for parenting as a desire to give love to the child. The results are encouraging because altruistic motivation is intrinsic one and the protective factor for latter family relations and care about child and sensitivity of parents. Altruistic motivation is showed like a good predictor in developing stable emotional relationship between mother and her baby but also is correlated with the higher satisfaction with marriage.

Keywords: development of parental role, in vitro fertilization, motivation for parenthood, pregnancy

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Authors: Benyelles Zakaria, Yousfi Djaafar, Karoui Moussa Sofiane

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Agriculture is fundamental and remains an important objective in the Algerian economy, based on traditional techniques and structures, it generally has a purpose of consumption. Collection of agricultural statistics in Algeria is done using traditional methods, which consists of investigating the use of land through survey and field survey. These statistics suffer from problems such as poor data quality, the long delay between collection of their last final availability and high cost compared to their limited use. The objective of this work is to develop a processing chain for a reliable inventory of agricultural land by trying to develop and implement a new method of extracting information. Indeed, this methodology allowed us to combine data from remote sensing and field data to collect statistics on areas of different land. The contribution of remote sensing in the improvement of agricultural statistics, in terms of area, has been studied in the wilaya of Sidi Bel Abbes. It is in this context that we applied a method for extracting information from satellite images. This method is called the non-negative matrix factorization, which does not consider the pixel as a single entity, but will look for components the pixel itself. The results obtained by the application of the MNF were compared with field data and the results obtained by the method of maximum likelihood. We have seen a rapprochement between the most important results of the FMN and those of field data. We believe that this method of extracting information from satellite data leads to interesting results of different types of land uses.

Keywords: blind source separation, hyper-spectral image, non-negative matrix factorization, remote sensing

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Authors: Abdulaziz Alageel, Martino Luis, Shuya Zhong

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The main focus of this research study is on the challenges faced in decision-making in a supply chain network regarding the facility location while considering carbon emissions. The study aims (i) to locate facilities (i.e., distribution centeres) in a continuous space considering limitations of capacity and the costs associated with opening and (ii) to reduce the cost of carbon emissions by selecting the mode of transportation. The problem is formulated as mixed-integer linear programming. This study hybridised a greedy randomised adaptive search (GRASP) and variable neighborhood search (VNS) to deal with the problem. Well-known datasets from the literature (Brimberg et al. 2001) are used and adapted in order to assess the performance of the proposed method. The proposed hybrid method produces encouraging results based on computational analysis. The study also highlights some research avenues for future recommendations.

Keywords: supply chain, facility location, weber problem, sustainability

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Authors: Ammar Alali, Mahmoud Abughaban, William Contreras Otalvora

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Optimizing the drilling process for cost and efficiency requires the optimization of the rate of penetration (ROP). ROP is the measurement of the speed at which the wellbore is created, in units of feet per hour. It is the primary indicator of measuring drilling efficiency. Maximization of the ROP can indicate fast and cost-efficient drilling operations; however, high ROPs may induce unintended events, which may lead to nonproductive time (NPT) and higher net costs. The proposed ROP optimization solution is a hybrid, data-driven system that aims to improve the drilling process, maximize the ROP, and minimize NPT. The system consists of two phases: (1) utilizing existing geological and drilling data to train the model prior, and (2) real-time adjustments of the controllable dynamic drilling parameters [weight on bit (WOB), rotary speed (RPM), and pump flow rate (GPM)] that direct influence on the ROP. During the first phase of the system, geological and historical drilling data are aggregated. After, the top-rated wells, as a function of high instance ROP, are distinguished. Those wells are filtered based on NPT incidents, and a cross-plot is generated for the controllable dynamic drilling parameters per ROP value. Subsequently, the parameter values (WOB, GPM, RPM) are calculated as a conditioned mean based on physical distance, following Inverse Distance Weighting (IDW) interpolation methodology. The first phase is concluded by producing a model of drilling best practices from the offset wells, prioritizing the optimum ROP value. This phase is performed before the commencing of drilling. Starting with the model produced in phase one, the second phase runs an automated drill-off test, delivering live adjustments in real-time. Those adjustments are made by directing the driller to deviate two of the controllable parameters (WOB and RPM) by a small percentage (0-5%), following the Constrained Random Search (CRS) methodology. These minor incremental variations will reveal new drilling conditions, not explored before through offset wells. The data is then consolidated into a heat-map, as a function of ROP. A more optimum ROP performance is identified through the heat-map and amended in the model. The validation process involved the selection of a planned well in an onshore oil field with hundreds of offset wells. The first phase model was built by utilizing the data points from the top-performing historical wells (20 wells). The model allows drillers to enhance decision-making by leveraging existing data and blending it with live data in real-time. An empirical relationship between controllable dynamic parameters and ROP was derived using Artificial Neural Networks (ANN). The adjustments resulted in improved ROP efficiency by over 20%, translating to at least 10% saving in drilling costs. The novelty of the proposed system lays is its ability to integrate historical data, calibrate based geological formations, and run real-time global optimization through CRS. Those factors position the system to work for any newly drilled well in a developing field event.

Keywords: drilling optimization, geological formations, machine learning, rate of penetration

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Authors: Renée Fregosi

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The contribution presently proposed will report on the beginnings of a Franco-Chilean study to be launched in 2015 by a multidisciplinary team of Renée Fregosi Political Science University Paris 3 / CECIEC, Norma Muñoz Public Policies University of Santiago of Chile, Jean-Daniel Lelievre, Medicine Paris 11 University, Marcelo WOLFF Medicine University of Chile, Cecilia Blatrix Political Science University Paris-Tech, Ernesto OTTONE, Political Science University of Chile, Paul DENY Medicine Paris 13 University, Rafael Bugueno Medicine Hospital Urgencia Pública of Santiago, Eduardo CARRASCO Political Science Paris 3 University. The problem of hidden populations challenges some criteria and concepts to re-examine: in particular the concept of target population, sampling methods to "snowball" and the cost-effectiveness criterion that shows the connection of political and scientific fields. Furthermore, if the pattern of homosexual transmission still makes up the highest percentage of the modes of infection with HIV, there is a continuous increase in the number of people infected through heterosexual sex, including women and persons aged 50 years and older. This group can be described as " unknown risk people." Access to these populations is a major challenge and raises methodological, ethical and political issues of prevention, particularly on the issue of screening. This paper proposes an inventory of these types of problems and their articulation, to define a new phase in the prevention against HIV refocused on women.

Keywords: HIV testing, hidden populations, difficult to reach PLWHA, women, unknown risk people

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

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Authors: Jin Hun Choi, So Hyun Ahn, Seong Keun Wang, Ik-Seung Chee, Jung Lan Kim, Sun Woo Lee

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Objectives: The purpose of the study is to investigate the effects of day hospital care in hospitalized schizophrenic patients in terms of treatment adherence and treatment outcomes. Methods: Among schizophrenic patients hospitalized between 2011 and 2012, 23 day hospital care patient and 40 control subjects were included in the study. All candidates underwent Beck Cognitive Insight Scale, Drug Attitude Inventory, World Health Organization Quality of Life Assessment and Psychological Well-Being Scale when their symptoms were stabilized during hospitalization, and after being discharged, 23 patients received day hospital care for two months and then changed to out-patient care while 40 patients received out-patient care immediately after discharge. At the point of two months of out-patient care, the treatment adherence of the two groups was evaluated; tracking observation was performed until February, 2013, and survival rates were compared between the two groups. Results: Treatment adherence was higher in the day hospital care group than in the control group. Kaplan-Meier survival analysis showed a higher survival rate for the day hospital care group compared to the control group. Levels of cognitive insight and quality of life were higher after day hospital care than before day hospital care in the day hospital care group. Conclusions: Through the study, it was confirmed that when hospitalized schizophrenic patients received continuous day hospital care after being discharged, they received further out-patient care more faithfully. The study is considered to aid in the understanding regarding schizophrenic patients’ treatment adherence issues and improvement of treatment outcomes.

Keywords: schizophrenia, day hospital care, adherence, outcomes

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Authors: (Ted) Edward Holmberg, Mahdi Abdelguerfi, Elias Ioup

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This research details a coverage measure for evaluating the effectiveness of observer node placements in a spatial bipartite network. This coverage measure can be used to optimize the configuration of stationary or mobile spatially oriented observer nodes, or a hybrid of the two, over time in order to fully utilize their capabilities. To demonstrate the practical application of this approach, we construct a SpatioTemporal Bipartite Network (STBN) using real-time crime center (RTCC) camera nodes and NOPD calls for service (CFS) event nodes from New Orleans, La (NOLA). We use the coverage measure to identify optimal placements for moving mobile RTCC camera vans to improve coverage of vulnerable areas based on temporal patterns.

Keywords: coverage measure, mobile node dynamics, Monte Carlo simulation, observer nodes, observable nodes, spatiotemporal bipartite knowledge graph, temporal spatial analysis

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Authors: S. Cichosz, A. Masek

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A new cellulose hybrid modification approach, which is undoubtedly a scientific novelty, is introduced. The study reports the properties of cellulose (Arbocel UFC100 – Ultra Fine Cellulose) and characterizes cellulose filled polymer composites based on an ethylene-norbornene copolymer (TOPAS Elastomer E-140). Moreover, the approach of physicochemical two-stage cellulose treatment is introduced: solvent exchange (to ethanol or hexane) and further chemical modification with maleic anhydride (MA). Furthermore, the impact of the drying process on cellulose properties was investigated. Suitable measurements were carried out to characterize cellulose fibers: spectroscopic investigation (Fourier Transform Infrared Spektrofotometer-FTIR, Near InfraRed spectroscopy-NIR), thermal analysis (Differential scanning calorimetry, Thermal gravimetric analysis ) and Karl Fischer titration. It should be emphasized that for all UFC100 treatments carried out, a decrease in moisture content was evidenced. FT-IR reveals a drop in absorption band intensity at 3334 cm-1, the peak is associated with both –OH moieties and water. Similar results were obtained with Karl Fischer titration. Based on the results obtained, it may be claimed that the employment of ethanol contributes greatly to the lowering of cellulose water absorption ability (decrease of moisture content to approximately 1.65%). Additionally, regarding polymer composite properties, crucial data has been obtained from the mechanical and thermal analysis. The highest material performance was noted in the case of the composite sample that contained cellulose modified with MA after a solvent exchange with ethanol. This specimen exhibited sufficient tensile strength, which is almost the same as that of the neat polymer matrix – in the region of 40 MPa. Moreover, both the Payne effect and filler efficiency factor, calculated based on dynamic mechanical analysis (DMA), reveal the possibility of the filler having a reinforcing nature. What is also interesting is that, according to the Payne effect results, fibers dried before the further chemical modification are assumed to allow more regular filler structure development in the polymer matrix (Payne effect maximum at 1.60 MPa), compared with those not dried (Payne effect in the range 0.84-1.26 MPa). Furthermore, taking into consideration the data gathered from DSC and TGA, higher thermal stability is obtained in case of the materials filled with fibers that were dried before the carried out treatments (degradation activation energy in the region of 195 kJ/mol) in comparison with the polymer composite samples filled with unmodified cellulose (degradation activation energy of approximately 180 kJ/mol). To author’s best knowledge this work results in the introduction of a novel, new filler hybrid treatment approach. Moreover, valuable data regarding the properties of composites filled with cellulose fibers of various moisture contents have been provided. It should be emphasized that plant fiber-based polymer bio-materials described in this research might contribute significantly to polymer waste minimization because they are more readily degraded.

Keywords: cellulose fibers, solvent exchange, moisture content, ethylene-norbornene copolymer

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Authors: Kumar Sankaran, Santanu Chattopadhyay, Golok Behari Nando, Sujith Nair, Sreejesh Arayambath, Unnikrishnan Govindan

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Rubber nanocomposites based on Bromobutyl rubber (BIIR), Polyepichlorohydrin rubber (CO), Carbon black (CB) and organically modified montmorillonite clay (NC) were prepared via melt compounding technique. The developed quaternary nanocomposites were characterized analytically and their properties were compared against the standard BIIR compound. BIIR-CO nanocomposites showed improved physico-mechanical properties as compared to that of the standard BIIR compound. Hybrid microstructure (NC-CB) development, clay exfoliation and better filler dispersion in the quaternary nanocomposite significantly contributed to the overall enhancement of properties. Introduction of CO in the system increased the specific gravity and hardness of the compound as compared to that of the standard compound. XRD analysis, AFM imaging and HR-TEM measurements confirmed exfoliation and a good level of dispersion of the NC in the composites. Permeability of developed BIIR-CO nanocomposites decreases significantly as compared to that of the standard BIIR compound.

Keywords: rubber nanocomposites, morphology, permeability, BIIR

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Authors: S. P. Koko, K. Kusakana, H. J. Vermaak

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Standalone micro-hydrokinetic river (MHR) system is one of the promising technologies to be used for remote rural electrification. It simply requires the flow of water instead of elevation or head, leading to expensive civil works. This paper demonstrates an economic benefit offered by a standalone MHR system when compared to the commonly used standalone systems such as solar, wind and diesel generator (DG) at the selected study site in Kwazulu Natal. Wind speed and solar radiation data of the selected rural site have been taken from national aeronautics and space administration (NASA) surface meteorology database. The hybrid optimization model for electric renewable (HOMER) software was used to determine the most feasible solution when using MHR, solar, wind or DG system to supply 5 rural houses. MHR system proved to be the best cost-effective option to consider at the study site due to its low cost of energy (COE) and low net present cost (NPC).

Keywords: economic analysis, micro-hydrokinetic, rural-electrification, cost of energy (COE), net present cost (NPC)

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Authors: Hafsa Raheel

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Background: Adolescents who suffer from depression early in life, have an increase in suicidal tendency, anxiety, conduct disorders, substance abuse, and continue to be depressed, later on in life. This study was conducted to identify the prevalence and correlates of depression among adolescent girls in Riyadh city in order to carry out early intervention. Methods: A cross‑sectional, school‑based survey was conducted among 1028 adolescent girls aged 15–19 years in secondary schools of Riyadh city. Riyadh was divided into clusters and within each cluster, both public and private schools were enrolled. From the selected schools students from grade 10–12 were surveyed. Survey was conducted using a structured questionnaire including the beck depression inventory‑II, and questions exploring the correlates of depression. Results: About 30% of participants were found to be depressed. Depression was more prevalent among female adolescents whose household income was inferior to 12,000 Saudi Riyal/month (odds ratio [OR] 2.17, confidence interval [CI] 0.97–6.84), did not have a good relationship with peers and family members (OR 4.63, CI 2.56–8.41), lived with single parent or alone (OR 1.77, CI 0.97–3.23), had been emotionally abused (OR 3.45, CI 2.56–8.41), and those who had been subjected to physical violence at least once (OR 3.34, CI 1.89–5.91). Conclusions: Strategies need to be developed to identify early signs and symptoms of depression among Saudi female adolescents. Training can be given to groups of students to help their peers, and also to the teachers to identify, and help students identify early signs of depression and provide them with better‑coping strategies to combat progression of depression and anxiety among such adolescents.

Keywords: adolescents, depression, Saudi Arabia, mental health

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Authors: Hamza A. A. Al-Sewadi, Adnan H. M. Al-Helali, Samaa A. K. Khamis

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Ownership proofs of multimedia such as text, image, audio or video files can be achieved by the burial of watermark is them. It is achieved by introducing modifications into these files that are imperceptible to the human senses but easily recoverable by a computer program. These modifications would be in the time domain or frequency domain or both. This paper presents a procedure for watermarking by mixing amplitude modulation with frequency transformation histogram; namely a specific value is used to modulate the intensity component Y of the YIQ components of the carrier image. This scheme is referred to as histogram embedding technique (HET). Results comparison with those of other techniques such as discrete wavelet transform (DWT), discrete cosine transform (DCT) and singular value decomposition (SVD) have shown an enhance efficiency in terms of ease and performance. It has manifested a good degree of robustness against various environment effects such as resizing, rotation and different kinds of noise. This method would prove very useful technique for copyright protection and ownership judgment.

Keywords: authentication, copyright protection, information hiding, ownership, watermarking

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Authors: Mahdi Amne Elahi, Marcus Koch, Peter Plapper

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Due to the demand of miniaturizing in automotive industry, the application of laser welding is quite promising. The current study focused on laser micro-welding of CuSn6 bronze and nickel wire for a miniature electromechanical hybrid component. Due to the advantages of laser welding, the welding can be tailored specifically for the requirements of the part. Scanning electron and optical microscopy were implemented to study the microstructure and tensile-shear test was selected to represent the mechanical properties. Different welding sides, beam oscillations, and speeds have been investigated to optimize the tensile-shear load and microstructure. The results show that the mechanical properties and microstructure of the joint is highly under the influence of the mentioned parameters. Due to the lack of intermetallic compounds, the soundness of the joint is achievable by manipulating the geometry of the weld seam and minimize weld defects.

Keywords: bronze, laser micro-welding, microstructure, nickel, tensile shear test

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Authors: Luis Rodrigo Valencia Pérez, Juan Manuel Peña Aguilar, Adelina Morita Alexander, Alberto Lamadrid Alvarez, Héctor Fernando Valencia Pérez

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Financial education is among the areas of opportunity in the Spanish-speaking from an early age to high school, through mobile devices such as cell phones and tablets using ludic and fun applications like interactive games, children can learn money management and investment through time, thereby fostering the habit of saving and/or sound management of cash and family business resources, having interaction with an uncontrolled environment such as the involvement of other players in the external decisions of the environment in which the game is play. The application proposed in Phase 1 (design and development) was designed in multi-user environments, under methodologies of hybrid programming for any platform on the market and designed under CMMI standards that allow for quality production over time, following up on these improvements counting with continuous user feedback and usage statistics.

Keywords: mobile educational games, ludic games, children, multiuser, design and software development

Procedia PDF Downloads 382

Authors: A. Peniak, J. Makarovič, P. Rafajdus, P. Dúbravka

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The purpose of this work is to optimize a Switched Reluctance Motor (SRM) for an automotive application, specifically for a fully electric car. A new optimization approach is proposed. This unique approach transforms automotive customer requirements into an optimization problem, based on sound knowledge of a SRM theory. The approach combines an analytical and a finite element analysis of the motor to quantify static nonlinear and dynamic performance parameters, as phase currents and motor torque maps, an output power and power losses in order to find the optimal motor as close to the reality as possible, within reasonable time. The new approach yields the optimal motor which is competitive with other types of already proposed motors for automotive applications. This distinctive approach can also be used to optimize other types of electrical motors, when parts specifically related to the SRM are adjusted accordingly.

Keywords: automotive, drive system, electric car, finite element method, hybrid car, optimization, switched reluctance motor

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Authors: Usman D. Hamza, Noor S. Nasri, Mohammed Jibril, Husna M. Zain

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Activated carbons (M4P0, M4P2, and M5P2) used in this research were produced from palm shell and polyetherether ketone (PEEK) via carbonization, impregnation, and microwave activation. The adsorption/desorption process was carried out using static volumetric adsorption. Regeneration is important in the overall economy of the process and waste minimization. This work focuses on the thermal regeneration of the CO2 exhausted microwave activated carbons. The regeneration strategy adopted was thermal with nitrogen purge desorption with N2 feed flow rate of 20 ml/min for 1 h at atmospheric pressure followed by drying at 1500C. Seven successive adsorption/regeneration processes were carried out on the material. It was found that after seven adsorption regeneration cycles; the regeneration efficiency (RE) for CO2 activated carbon from palm shell only (M4P0) was more than 90% while that of hybrid palm shell-PEEK (M4P2, M5P2) was above 95%. The cyclic adsorption and regeneration shows the stability of the adsorbent materials.

Keywords: activated carbon, palm shell-PEEK, regeneration, thermal

Procedia PDF Downloads 488

Authors: Ferzat Anka

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Many types of problems can be solved using traditional analytical methods. However, these methods take a long time and cause inefficient use of resources. In particular, different approaches may be required in solving complex and global engineering problems that we frequently encounter in real life. The bigger and more complex a problem, the harder it is to solve. Such problems are called Nondeterministic Polynomial time (NP-hard) in the literature. The main reasons for recommending different metaheuristic algorithms for various problems are the use of simple concepts, the use of simple mathematical equations and structures, the use of non-derivative mechanisms, the avoidance of local optima, and their fast convergence. They are also flexible, as they can be applied to different problems without very specific modifications. Thanks to these features, it can be easily embedded even in many hardware devices. Accordingly, this approach can also be used in trend application areas such as IoT, big data, and parallel structures. Indeed, the metaheuristic approaches are algorithms that return near-optimal results for solving large-scale optimization problems. This study is focused on the new metaheuristic method that has been merged with the chaotic approach. It is based on the chaos theorem and helps relevant algorithms to improve the diversity of the population and fast convergence. This approach is based on Chimp Optimization Algorithm (ChOA), that is a recently introduced metaheuristic algorithm inspired by nature. This algorithm identified four types of chimpanzee groups: attacker, barrier, chaser, and driver, and proposed a suitable mathematical model for them based on the various intelligence and sexual motivations of chimpanzees. However, this algorithm is not more successful in the convergence rate and escaping of the local optimum trap in solving high-dimensional problems. Although it and some of its variants use some strategies to overcome these problems, it is observed that it is not sufficient. Therefore, in this study, a newly expanded variant is described. In the algorithm called Ex-ChOA, hybrid models are proposed for position updates of search agents, and a dynamic switching mechanism is provided for transition phases. This flexible structure solves the slow convergence problem of ChOA and improves its accuracy in multidimensional problems. Therefore, it tries to achieve success in solving global, complex, and constrained problems. The main contribution of this study is 1) It improves the accuracy and solves the slow convergence problem of the ChOA. 2) It proposes new hybrid movement strategy models for position updates of search agents. 3) It provides success in solving global, complex, and constrained problems. 4) It provides a dynamic switching mechanism between phases. The performance of the Ex-ChOA algorithm is analyzed on a total of 8 benchmark functions, as well as a total of 2 classical and constrained engineering problems. The proposed algorithm is compared with the ChoA, and several well-known variants (Weighted-ChoA, Enhanced-ChoA) are used. In addition, an Improved algorithm from the Grey Wolf Optimizer (I-GWO) method is chosen for comparison since the working model is similar. The obtained results depict that the proposed algorithm performs better or equivalently to the compared algorithms.

Keywords: optimization, metaheuristic, chimp optimization algorithm, engineering constrained problems

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Authors: Shahlan Surat, Saemah Rahman, Saadiah Kummin

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When teachers reflect and evaluate whether their teaching methods actually have an impact on students’ learning, they will adjust their practices accordingly. This inevitably improves their students’ learning and performance. The approach in meta-teaching can invigorate and create a passion for teaching. It thus helps to increase the commitment and love for the teaching profession. This study was conducted to determine the level of metacognitive thinking of teachers in the process of teaching and learning in the classroom. Metacognitive thinking teachers include the use of metacognitive knowledge which consists of different types of knowledge: declarative, procedural and conditional. The ability of the teachers to plan, monitor and evaluate the teaching process can also be determined. This study was conducted on 377 graduate teachers in Klang Valley, Malaysia. The stratified sampling method was selected for the purpose of this study. The metacognitive teaching inventory consisting of 24 items is called InKePMG (Teacher Indicators of Effectiveness Meta-Teaching). The results showed the level of mean is high for two components of metacognitive knowledge; declarative knowledge (mean = 4.16) and conditional (mean = 4.11) whereas, the mean of procedural knowledge is 4.00 (moderately high). Similarly, the level of knowledge in monitoring (mean = 4.11), evaluating (mean = 4.00) which indicate high score and planning (mean = 4.00) are moderately high score among teachers. In conclusion, this study shows that the planning and procedural knowledge is an important element in improving the quality of teachers teaching in the classroom. Thus, the researcher recommended that further studies should focus on training programs for teachers on metacognitive skills and also on developing creative thinking among teachers.

Keywords: metacognitive thinking skills, procedural knowledge, conditional knowledge, meta-teaching and regulation of cognitive

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Authors: Gopashis Biswas G. Son

Abstract:

This paper will attempt to explore the notions that the two Caribbean poets- Derek Walcott and Edward Kamau Brathwaite endorse on Caribbean history in their poems. Though both of these poets hold almost the same notion regarding history but their approach is totally different from one another. Coming from a 'hybrid' race, Walcott is aware of the history and acknowledges it and writes in 'mulatto of style'; whereas Brathwaite is enraged by it and attempts to sublimate it to erect a history of the new world. It is Walcott’s view to rise above the delusion and hatred and engulf the world of literature with creativity. On the other hand, Brathwaite holds the grudge which helps him not to forget and forgive the past experience but to transform that very experience into something positive which may help the Caribbean to transform their frustration into something creative and to help the Caribbean to overcome the present struggle against the legacy of colonization. Following discourse analysis, this paper seeks to identify if it is possible to rewrite and re-‘right’ the Caribbean history which has been lost in the route and analyze Walcott and Brathwaite’s attitude towards that very history which has been implemented through their poetry.

Keywords: Caribbean history, colonialism, mulatto of style, Walcott vis-à-vis Brathwaite

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Authors: Ashwani Kumar

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Use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function.

Keywords: NIR light, tissue, blurring, Monte Carlo simulation

Procedia PDF Downloads 494