Search results for: conditional proportional reversed hazard rate model

Authors: Hamed Khezrzadeh

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Many investigations on the micromechanical structure of materials indicate that there exist fractal patterns at the micro scale in some of the main construction and industrial materials. A recently presented micro-fractal theory brings together the well-known periodic homogenization and the fractal geometry to construct an appropriate model for determination of the mechanical properties of particle reinforced composite materials. The proposed multi-step homogenization scheme considers the mechanical properties of different constituent phases in the composite together with the interaction between these phases throughout a step-by-step homogenization technique. In the proposed model the interaction of different phases is also investigated. By using this method the effect of fibers grading on the mechanical properties also could be studied. The theory outcomes are compared to the experimental data for different types of particle-reinforced composites which very good agreement with the experimental data is observed.

Keywords: fractal geometry, homogenization, micromehcanics, particulate composites

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Authors: Markus Mazzola, Gunther Schaaf

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A vehicle driving with an Adaptive Cruise Control System (ACC) is usually controlled decentrally, based on the information of radar systems and in some publications based on C2X-Communication (CACC) to guarantee stable platoons. In this paper, we present a Model Predictive Control (MPC) design of a centralized, server-based ACC-System, whereby the vehicular platoon is modeled and controlled as a whole. It is then proven that the proposed MPC design guarantees asymptotic stability and hence string stability of the platoon. The Networked MPC design is chosen to be able to integrate system constraints optimally as well as to reduce the effects of communication delay and packet loss. The performance of the proposed controller is then simulated and analyzed in an LTE communication scenario using the LTE/EPC Network Simulator LENA, which is based on the ns-3 network simulator.

Keywords: adaptive cruise control, centralized server, networked model predictive control, string stability

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Authors: Ayat-Allah Bouramdane

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Solar Photovoltaic (PV) and Concentrated Solar Power (CSP) do not burn fossil fuels and, therefore, could meet the world's needs for low-carbon power generation as they do not release greenhouse gases into the atmosphere as they generate electricity. The power output of the solar PV module and CSP collector is proportional to the temperature and the amount of solar radiation received by their surface. Hence, the determination of the most convenient locations of PV and CSP systems is crucial to maximizing their output power. This study aims to provide a hands-on and plausible approach to the multi-criteria evaluation of site suitability of PV and CSP plants using a combination of Geographic Referenced Information (GRI) and Analytic Hierarchy Process (AHP). Applying the GRI-based AHP approach is meant to specify the criteria and sub-criteria, to identify the unsuitable areas, the low-, moderate-, high- and very high suitable areas for each layer of GRI, to perform the pairwise comparison matrix at each level of the hierarchy structure based on experts' knowledge, and calculate the weights using AHP to create the final map of solar PV and CSP plants suitability in Morocco with a particular focus on the Dakhla city. The results recognize that solar irradiation is the main decision factor for the integration of these technologies on energy policy goals of Morocco but explicitly account for other factors that cannot only limit the potential of certain locations but can even exclude the Dakhla city classified as unsuitable area. We discuss the sensitivity of the PV and CSP site suitability to different aspects, such as the methodology, the climate conditions, and the technology used in each source, and provide the final recommendations to the Moroccan energy strategy by analyzing if actual Morocco's PV and CSP installations are located within areas deemed suitable and by discussing several cases to provide mutual benefits across the Food-Energy-Water nexus. The adapted methodology and conducted suitability map could be used by researchers or engineers to provide helpful information for decision-makers in terms of sites selection, design, and planning of future solar plants, especially in areas suffering from energy shortages, such as the Dakhla city, which is now one of Africa's most promising investment hubs and it is especially attractive to investors looking to root their operations in Africa and import to European markets.

Keywords: analytic hierarchy process, concentrated solar power, dakhla, geographic referenced information, Morocco, multi-criteria decision-making, photovoltaic, site suitability

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Authors: Afshin Keshvadi, Johari Endan, Haniff Harun, Desa Ahmad, Farah Saleena

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Experiments were conducted to develop a model for analyzing the ripening process of oil palm fresh fruits in relation to oil yield and oil quality of palm oil produced. This research was carried out on 8-year-old Tenera (Dura × Pisifera) palms planted in 2003 at the Malaysian Palm Oil Board Research Station. Fresh fruit bunches were harvested from designated palms during January till May of 2010. The bunches were divided into three regions (top, middle and bottom), and fruits from the outer and inner layers were randomly sampled for analysis at 8, 12, 16 and 20 weeks after anthesis to establish relationships between maturity and oil development in the mesocarp and kernel. Computations on data related to ripening time, oil content and oil quality were performed using several computer software programs (MSTAT-C, SAS and Microsoft Excel). Nine nonlinear mathematical models were utilized using MATLAB software to fit the data collected. The results showed mean mesocarp oil percent increased from 1.24 % at 8 weeks after anthesis to 29.6 % at 20 weeks after anthesis. Fruits from the top part of the bunch had the highest mesocarp oil content of 10.09 %. The lowest kernel oil percent of 0.03 % was recorded at 12 weeks after anthesis. Palmitic acid and oleic acid comprised of more than 73 % of total mesocarp fatty acids at 8 weeks after anthesis, and increased to more than 80 % at fruit maturity at 20 weeks. The Logistic model with the highest R2 and the lowest root mean square error was found to be the best fit model.

Keywords: oil palm, oil yield, ripening process, anthesis, fatty acids, modeling

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Authors: Heba M. Jahin, Ali F. Bakr, Zeyad T. Elsayad

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As smart spaces can be defined as any working environment which integrates embedded computers, information appliances and multi-modal sensors to remain focused on the interaction between the users, their activity, and their behavior in the space; hence, smart space must be aware of their contexts and automatically adapt to their changing context-awareness, by interacting with their physical environment through natural and multimodal interfaces. Also, by serving the information used proactively. This paper suggests a dynamic framework through the architectural design process of the space based on the principles of computational methods and context-awareness principles to help in creating a field of changes and modifications. It generates possibilities, concerns about the physical, structural and user contexts. This framework is concerned with five main processes: gathering and analyzing data to generate smart design scenarios, parameters, and attributes; which will be transformed by coding into four types of models. Furthmore, connecting those models together in the interaction model which will represent the context-awareness system. Then, transforming that model into a virtual and ambient environment which represents the physical and real environments, to act as a linkage phase between the users and their activities taking place in that smart space . Finally, the feedback phase from users of that environment to be sure that the design of that smart space fulfill their needs. Therefore, the generated design process will help in designing smarts spaces that can be adapted and controlled to answer the users’ defined goals, needs, and activity.

Keywords: computational methods, context-awareness, design process, smart spaces

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Authors: Gideon J. Bonthuys, Marco van Dijk, Jay N. Bhagwan

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Small scale hydropower used to play a very important role in the provision of energy to urban and rural areas of South Africa. The national electricity grid, however, expanded and offered cheap, coal generated electricity and a large number of hydropower systems were decommissioned. Unfortunately, large numbers of households and communities will not be connected to the national electricity grid for the foreseeable future due to high cost of transmission and distribution systems to remote communities due to the relatively low electricity demand within rural communities and the allocation of current expenditure on upgrading and constructing of new coal fired power stations. This necessitates the development of feasible alternative power generation technologies. A feasibility and implementation model was developed to assist in designing and financially evaluating small-scale hydropower (SSHP) plants. Several sites were identified using the model. The SSHP plants were designed for the selected sites and the designs for the different selected sites were priced using pricing models (civil, mechanical and electrical aspects). Following feasibility studies done on the designed and priced SSHP plants, a feasibility analysis was done and a design chart developed for future similar potential SSHP plant projects. The methodology followed in conducting the feasibility analysis for other potential sites consisted of developing cost and income/saving formulae, developing net present value (NPV) formulae, Capital Cost Comparison Ratio (CCCR) and levelised cost formulae for SSHP projects for the different types of plant installations. It included setting up a model for the development of a design chart for a SSHP, calculating the NPV, CCCR and levelised cost for the different scenarios within the model by varying different parameters within the developed formulae, setting up the design chart for the different scenarios within the model and analyzing and interpreting results. From the interpretation of the develop design charts for feasible SSHP in can be seen that turbine and distribution line cost are the major influences on the cost and feasibility of SSHP. High head, short transmission line and islanded mini-grid SSHP installations are the most feasible and that the levelised cost of SSHP is high for low power generation sites. The main conclusion from the study is that the levelised cost of SSHP projects indicate that the cost of SSHP for low energy generation is high compared to the levelised cost of grid connected electricity supply; however, the remoteness of SSHP for rural electrification and the cost of infrastructure to connect remote rural communities to the local or national electricity grid provides a low CCCR and renders SSHP for rural electrification feasible on this basis.

Keywords: cost, feasibility, rural electrification, small-scale hydropower

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Authors: Asawari Ajay Avhad

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The Soil and Water Assessment Tool (SWAT) is a hydrological model designed to predict the complex interactions within natural and human-altered watersheds. This research applies the SWAT model to the Ulhas River basin, a small watershed undergoing urbanization and characterized by bowl-like topography. Three simulation scenarios (LC17, LC22, and LC27) are investigated, each representing different land use and land cover (LULC) configurations, to assess the impact of urbanization on runoff. The LULC for the year 2027 is generated using the MOLUSCE Plugin of QGIS, incorporating various spatial factors such as DEM, Distance from Road, Distance from River, Slope, and distance from settlements. Future climate data is simulated within the SWAT model using historical data spanning 30 years. A susceptibility map for runoff across the basin is created, classifying runoff into five susceptibility levels ranging from very low to very high. Sub-basins corresponding to major urban settlements are identified as highly susceptible to runoff. With consideration of future climate projections, a slight increase in runoff is forecasted. The reliability of the methodology was validated through the identification of sub-basins known for experiencing severe flood events, which were determined to be highly susceptible to runoff. The susceptibility map successfully pinpointed these sub-basins with a track record of extreme flood occurrences, thus reinforcing the credibility of the assessment methodology. This study suggests that the methodology employed could serve as a valuable tool in flood management planning.

Keywords: future land use impact, flood management, run off prediction, ArcSWAT

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Authors: Takahiro Saida, Takahiro Kogiso, Takahiro Maruyama

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The ordered structural carbon (OSC) material is expected to apply to the electrode of secondary batteries, the catalyst supports, and the biomaterials because it shows the low substance-diffusion resistance by its uniform pore size. In general, the OSC material is synthesized using the template material. Changing size and shape of this template provides the pore size of OSC material according to the purpose. Depositing the oxide nanosheets on the polymer sphere template by the layer by layer (LbL) method was reported as one of the preparation methods of OSC material. The LbL method can provide the controlling thickness of structural wall without the surface modification. When the preparation of the uniform carbon sphere prepared by the LbL method which composed of the graphene oxide wall and the polymethyl-methacrylate (PMMA) core, the reduction treatment will be the important object. Since the graphene oxide has poor electron conductivity due to forming a lot of functional groups on the surface, it could be hard to apply to the electrode of secondary batteries and the catalyst support of fuel cells. In this study, the graphene oxide wall of carbon sphere was reduced by the thermal treatment under the vacuum conditions, and its crystalline structure and electronic state were characterized. Scanning electron microscope images of the carbon sphere after the heat treatment at 300ºC showed maintaining sphere shape, but its shape was collapsed with increasing the heating temperature. In this time, the dissolution rate of PMMA core and the reduction rate of graphene oxide were proportionate to heating temperature. In contrast, extending the heating time was conducive to the conservation of the sphere shape. From results of X-ray photoelectron spectroscopy analysis, its electronic state of the surface was indicated mainly sp² carbon. From the above results, we succeeded in the synthesis of the sphere structure composed by the reduction graphene oxide.

Keywords: carbon sphere, graphene oxide, reduction, layer by layer

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Authors: Uwe C. Fischer

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Mental health and well-being for employees working in the human service system are getting more and more important given the increasing rate of absenteeism at work. Besides individual capacities, social and community factors seem to be important in the working setting. Starting from a demand resource framework including the classical demand control aspects, social support systems, specific demands and resources of the client work, and work-family conflict were considered in the present study. We state hypothetically, that these factors have a meaningful association with the mental quality of life of employees working in the field of social, educational and health sectors. 1140 employees, working in human service organizations (education, youth care, nursing etc.) were asked for strains and resources at work (selected scales from Salutogenetic Subjective Work Assessment SALSA and own new scales for client work), work-family conflict, and mental quality of life from the German Short Form Health Survey. Considering the complex influences of the variables, we conducted a multiple hierarchical regression analysis. One third of the whole variance of the mental quality of life can be declared by the different variables of the model. When the variables concerning social influences were included in the hierarchical regression, the influence of work related control resource decreased. Excessive workload, work-family conflict, social support by supervisors, co-workers and other persons outside work, as well as strains and resources associated with client work had significant regression coefficients. Conclusions: Social support systems are crucial in the social, educational and health related service sector, regarding the influence on mental well-being. Especially the work-family conflict focuses on the importance of the work-life balance. Also the specific strains and resources of the client work, measured with new constructed scales, showed great impact on mental health. Therefore occupational health promotion should focus more on the social factors within and outside the working place.

Keywords: client interaction, human service system, mental health, social support, work-family conflict

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Authors: I. Toumi, Y. Abed, A. Bouafia

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This paper presents a methodology for identifying the cohesive soil parameters that takes into account different constitutive equations. The procedure, applied to identify the parameters of generalized Prager model associated to the Drucker & Prager failure criterion from a pressuremeter expansion curve, is based on an inverse analysis approach, which consists of minimizing the function representing the difference between the experimental curve and the simulated curve using a simplex algorithm. The model response on pressuremeter path and its identification from experimental data lead to the determination of the friction angle, the cohesion and the Young modulus. Some parameters effects on the simulated curves and stresses path around pressuremeter probe are presented. Comparisons between the parameters determined with the proposed method and those obtained by other means are also presented.

Keywords: cohesive soils, cavity expansion, pressuremeter test, finite element method, optimization procedure, simplex algorithm

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Authors: Bohli Afef

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The fifth-generation (5G) wireless systems is featured by extreme densities of cell stations to overcome the higher future demand. Hence, interference management is a crucial challenge in 5G ultra-dense cellular networks. In contrast to the classical inter-cell interference coordination approach, which is no longer fit for the high density of cell-tiers, this paper proposes a novel virtual coordination based on the dynamic common cognitive monitor channel protocol to deal with the inter-cell interference issue. A tractable and flexible model for the coverage probability of a typical user is developed through the use of the stochastic geometry model. The analyses of the performance of the suggested protocol are illustrated both analytically and numerically in terms of coverage probability.

Keywords: ultra dense heterogeneous networks, dynamic common channel protocol, cognitive radio, stochastic geometry, coverage probability

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Authors: Said Ettaieb, Kamel Hamrouni, Su Ruan

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This paper presents a new method based both on Active Shape Model and a priori knowledge about the spatio-temporal shape variation for tracking deformable structures in medical imaging. The main idea is to exploit the a priori knowledge of shape that exists in ASM and introduce new knowledge about the shape variation over time. The aim is to define a new more stable method, allowing the reliable detection of structures whose shape changes considerably in time. This method can also be used for the three-dimensional segmentation by replacing the temporal component by the third spatial axis (z). The proposed method is applied for the functional and morphological study of the heart pump. The functional aspect was studied through temporal sequences of scintigraphic images and morphology was studied through MRI volumes. The obtained results are encouraging and show the performance of the proposed method.

Keywords: active shape model, a priori knowledge, spatiotemporal shape variation, deformable structures, medical images

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Authors: Sam Khozama, Ali M. Mayya

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Breast cancer is one of the most common types in women. Early prediction of breast cancer helps physicians detect cancer in its early stages. Big cancer data needs a very powerful tool to analyze and extract predictions. Machine learning and deep learning are two of the most efficient tools for predicting cancer based on textual data. In this study, we developed a fusion model of two machine learning and deep learning models. To obtain the final prediction, Long-Short Term Memory (LSTM) and ensemble learning with hyper parameters optimization are used, and score-level fusion is used. Experiments are done on the Breast Cancer Surveillance Consortium (BCSC) dataset after balancing and grouping the class categories. Five different training scenarios are used, and the tests show that the designed fusion model improved the performance by 3.3% compared to the individual models.

Keywords: machine learning, deep learning, cancer prediction, breast cancer, LSTM, fusion

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Authors: Amadou Darboe, Kuo Hsien-Wen

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Background/Objective: The Effort-Reward Imbalance (ERI) model by Siegrist et al (1986) have been widely used to examine the relationship between psychosocial factors at work and health. It claimed that failed reciprocity in terms of high efforts and low rewards elicits strong negative emotions in combination with sustained autonomic activation and is hazardous to health. The aim of this study is to identify the association between Self-rated Health and Effort-reward Imbalance (ERI) among Nurses and Environmental Health officers in the Gambia. Method: a cross-sectional study was conducted using a multi-stage random sampling of 296 healthcare professionals (206 nurses and 90 environmental health officers) working in public health facilities. The 22 items Effort-reward imbalance questionnaire (ERI-L version 22.11.2012) will be used to collect data on the psychosocial factors defined by the model. In addition, self-rated health will be assessed by using structured questionnaires containing Likert scale items. Results: We found that self-rated health among environmental health officers has a significant negative correlation with extrinsic effort and a positive significant correlations with occupational reward and job satisfaction. However, among the nurses only job satisfaction was significantly correlated with self-rated health and was positive. Overall, Extrinsic effort has a significant negative correlation with reward and job satisfaction but a positive correlation with over-commitment. Conclusion: Because low reward and high over-commitment among the nursing group, It is necessary to modify working conditions through improving psychosocial factors, such as reasonable allocation of resources to increase pay or rewards from government.

Keywords: effort-reward imbalance model, healthcare professionals, self-rated health

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Authors: Walid Louhichi, Mouhebeddine Berrima, Narjes Ben Rajed

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Elasticity is the essential property of cloud computing. As the name suggests, it constitutes the ability of a cloud system to adjust resource provisioning in relation to fluctuating workload. There are two types of elasticity operations, vertical and horizontal. In this work, we are interested in horizontal scaling, which is ensured by two mechanisms; scaling in and scaling out. Following the sizing of the system, we can adopt scaling in in the event of over-supply and scaling out in the event of under-supply. In this paper, we propose a formal model, based on colored and temporized Petri nets, for the modeling of the duplication and the removal of a virtual machine from a server. This model is based on formal Petri Nets modeling language. The proposed models are edited, verified, and simulated with two examples implemented in CPNtools, which is a modeling tool for colored and timed Petri nets.

Keywords: cloud computing, elasticity, elasticity controller, petri nets, scaling in, scaling out

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Authors: Yun-Chin Chung, Nileema Divate, Gen-Hung Chen, Pei-Ru Huang, Rupesh Divate

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Many environmental factors, such as glucose concentration, ethanol, temperature, osmotic pressure and pH, decrease the production rate of ethanol using yeast as a starter. Fermentation starters with high tolerance to various stresses are always demanded for brewing industry. Trehalose, a storage carbohydrate in cell wall of yeast, plays an important role in tolerance of environmental stress by preserving integrity of plasma membrane and stabilizing proteins. Furan aldehydes are toxic to yeast and the growth rate of yeast is significantly reduced if furan aldehydes were present in the fermentation medium. In yeast, aldehyde reductase is involved in the detoxification of reactive aldehydes and consequently the growth of yeast is improved. The aims of this study were to construct a genetic recombinant Saccharomyces cerevisiae or Pichia pastoris with furfural and HMF degrading and high ethanol tolerance capacities. Yeast strains were engineered by genetic recombination for overexpression of trehalose-6-phosphate synthase gene (tps1) and aldehyde reductase gene (ari1). TPS1 gene was cloned from S. cerevisiae by reverse transcription-polymerase chain reaction (RT-PCR) and then ligated with pGAPZαC vector. The constructed vector, pGAPZC-tps1, was transformed to recombinant yeasts strain with overexpression of ari1. The transformants with pGAPZC-tps1-ari1 were generated called STA (S. cerevisiae) and PTA (P. pastoris) with overexpression of tps1, ari1. PCR with tps1-specific primers and western blot with his-tag confirmed the gene insertion and protein expression of tps1 in the transformants, respectively. The neutral trehalase gene (nth1) of STA was successfully deleted and the novel strain STAΔN will be used for further study, including the measurement of trehalose concentration and ethanol, furfural tolerance assay.

Keywords: genetic recombinant, yeast, ethanol tolerance, trehalase, aldehyde reductase

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Authors: N. Tahouni, M. Gholami, M. H. Panjeshahi

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Gas flaring is one of the most GHG emitting sources in the oil and gas industries. It is also a major way for wasting such an energy that could be better utilized and even generates revenue. Minimize flaring is an effective approach for reducing GHG emissions and also conserving energy in flaring systems. Integrating waste and flared gases into the fuel gas networks (FGN) of refineries is an efficient tool. A fuel gas network collects fuel gases from various source streams and mixes them in an optimal manner, and supplies them to different fuel sinks such as furnaces, boilers, turbines, etc. In this article we use fuel gas network model proposed by Hasan et al. as a base model and modify some of its features and add constraints on emission pollution by gas flaring to reduce GHG emissions as possible. Results for a refinery case study showed that integration of flare gas stream with waste and natural gas streams to construct an optimal FGN can significantly reduce total annualized cost and flaring emissions.

Keywords: flaring, fuel gas network, GHG emissions, stream

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Authors: Jonas Pedro Fabris, Alberth Almeida Amorim Souza, Maria Emilia Camargo, Suzana Leitão Russo

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With the law Nº. 9279, of May 14, 1996, the Brazilian government regulates rights and obligations relating to industrial property considering the economic development of the country as granting patents, trademark registration, registration of industrial designs and other forms of protection copyright. In this study, we show the application of the methodology of Box and Jenkins in the series of deposits of industrial design at the National Institute of Industrial Property for the period from May 1996 to April 2013. First, a graphical analysis of the data was done by observing the behavior of the data and the autocorrelation function. The best model found, based on the analysis of charts and statistical tests suggested by Box and Jenkins methodology, it was possible to determine the model number for the deposit of industrial design, SARIMA (2,1,0)(2,0,0), with an equal to 9.88% MAPE.

Keywords: ARIMA models, autocorrelation, Box and Jenkins Models, industrial design, MAPE, time series

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Authors: Dibakar Chakrabarty, Mebada Suiting

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Rapid urbanization coupled with changes in land use pattern results in increasing peak discharge and shortening of catchment time of concentration. The consequence is floods, which often inundate roads and inhabited areas of cities and towns. Management of storm water resulting from rainfall has, therefore, become an important issue for the municipal bodies. Proper management of storm water obviously includes adequate design of storm water drainage networks. The design of storm water network is a costly exercise. Least cost design of storm water networks assumes significance, particularly when the fund available is limited. Optimal design of a storm water system is a difficult task as it involves the design of various components, like, open or closed conduits, storage units, pumps etc. In this paper, a methodology for least cost design of storm water drainage systems is proposed. The methodology proposed in this study consists of coupling a storm water simulator with an optimization method. The simulator used in this study is EPA’s storm water management model (SWMM), which is linked with Genetic Algorithm (GA) optimization method. The model proposed here is a mixed integer nonlinear optimization formulation, which takes care of minimizing the sectional areas of the open conduits of storm water networks, while satisfactorily conveying the runoff resulting from rainfall to the network outlet. Performance evaluations of the developed model show that the proposed method can be used for cost effective design of open conduit based storm water networks.

Keywords: genetic algorithm (GA), optimal design, simulation-optimization, storm water network, SWMM

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Authors: Agustinus Rudatyo Himamunanto, Anastasia Rita Widiarti

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Transliteration using Javanese manuscripts is one of methods to preserve and legate the wealth of literature in the past for the present generation in Indonesia. The transliteration manual process commonly requires philologists and takes a relatively long time. The automatic transliteration process is expected to shorten the time so as to help the works of philologists. The preprocessing and segmentation stage firstly done is used to manage the document images, thus obtaining image script units that will compile input document images free from noise and have the similarity in properties in the thickness, size, and slope. The next stage of characteristic extraction is used to find unique characteristics that will distinguish each Javanese script image. One of characteristics that is used in this research is the number of black pixels in each image units. Each image of Java scripts contained in the data training will undergo the same process similar to the input characters. The system testing was performed with the data of the book Hamong Tani. The book Hamong Tani was selected due to its content, age and number of pages. Those were considered sufficient as a model experimental input. Based on the results of random page automatic transliteration process testing, it was determined that the maximum percentage correctness obtained was 81.53%. The percentage of success was obtained in 32x32 pixel input image size with the 5x5 image window. With regard to the results, it can be concluded that the automatic transliteration model offered is relatively good.

Keywords: Javanese script, character recognition, statistical, automatic transliteration

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Authors: Quang Dong Dang

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This paper examines the possible effects of stock market developments by channels on income and wealth inequality. We use the Bayesian Multilevel Model with the explanatory variables of the market’s channels, such as accessibility, efficiency, and market health in six selected countries: the US, UK, Japan, Vietnam, Thailand, and Malaysia. We found that generally, the improvements in the stock market alleviate income inequality. However, stock market expansions in higher-income countries are likely to trigger income inequality. We also found that while enhancing the quality of channels of the stock market has counter-effects on wealth equality distributions, open accessibilities help reduce wealth inequality distributions within the scope of the study. In addition, the inverted U-shaped hypothesis seems not to be valid in six selected countries between the period from 2006 to 2020.

Keywords: Bayesian multilevel model, income inequality, inverted u-shaped hypothesis, stock market development, wealth inequality

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Authors: Luojie Tang, Libin Ouyang, Yihang Gao

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The natural landscape and urban-rural structure, with their attractiveness in the Dali area around Erhai Lake, exhibit striking similarities with Howard's Garden City. With the emergence of the unique phenomenon of the first large-scale gathering of digital nomads in China in Dali, an analysis of Dali's natural, economic, and cultural representations and structures reveals that the Garden City model can no longer fully explain the current overall human living environment in Dali. By interpreting the bottom-up local construction process in Dali based on landscape identity, the transformation of production and lifestyle under new technologies such as ICT(Information and Communication Technology), and the values and lifestyle reshaping embodied in the "reverse urbanization" phenomenon of the middle class in Dali, it is believed that Dali has moved towards a "contemporary garden city influenced by new technology." The article summarizes the characteristics and connotations of this Garden City and provides corresponding strategies for its continued healthy development.

Keywords: dali, ICT, rural-urban relationship, garden city model

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Authors: Kira Toxopeus, Kamran Siddiqui

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Channel flows are common in a wide range of engineering applications. In some types of channel flows, particularly the ones involving chemical or biological processes, the control of the flow temperature is crucial to maintain the optimal conditions for the chemical reaction or to control the growth of biological species. This often becomes an issue when the flow experiences temperature fluctuations due to external conditions. While active heating and cooling could regulate the channel temperature, it may not be feasible logistically or economically and is also regarded as a non-sustainable option. Thermal energy storage utilizing phase change material (PCM) could provide the required thermal regulation sustainably by storing the excess heat from the channel and releasing it back as required, thus regulating the channel temperature within a range in the proximity of the PCM melting temperature. However, in designing such systems, the configuration of the PCM storage within the channel is critical as it could influence the channel flow dynamics, which would, in turn, affect the heat exchange between the channel fluid and the PCM. The present research is focused on the investigation of the flow dynamical behavior in the channel during heat transfer from the channel flow to the PCM thermal energy storage. Offset vertical columns in a narrow channel were used that contained the PCM. Two different column shapes, square and circular, were considered. Water was used as the channel fluid that entered the channel at a temperature higher than that of the PCM melting temperature. Hence, as the water was passing through the channel, the heat was being transferred from the water to the PCM, causing the PCM to store the heat through a phase transition from solid to liquid. Particle image velocimetry (PIV) was used to measure the two-dimensional velocity field of the channel flow as it flows between the PCM columns. Thermocouples were also attached to the PCM columns to measure the PCM temperature at three different heights. Three different water flow rates (0.5, 0.75 and 1.2 liters/min) were considered. At each flow rate, experiments were conducted at three different inlet water temperatures (28ᵒC, 33ᵒC and 38ᵒC). The results show that the flow rate and the inlet temperature influenced the flow behavior inside the channel.

Keywords: channel flow, phase change material, thermal energy storage, thermal regulation

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Authors: Dimakatso B. Gumede, Nicolette N. Houreld

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Diabetic foot ulcers (DFUs) are a complication of diabetes mellitus (DM), a metabolic disease caused by insulin resistance or insufficiency, resulting in hyperglycaemia and low-grade chronic inflammation. Current therapies for treating DFUs include wound debridement, glycaemic control, and wound dressing. However, these therapies are moderately effective as there is a recurrence of these ulcers and an increased risk of lower limb amputations. Photobiomodulation (PBM), which is the application of non-invasive low-level light for wound healing at the spectrum of 660-1000 nm, has shown great promise in accelerating the healing of chronic wounds. However, its underlying mechanisms are not clearly defined. Studies have indicated that PBM induces wound healing via the activation of signaling pathways that are involved in tissue repair, such as the transforming growth factor-β (TGF-β). However, other signaling pathways, such as the WNT/β-catenin pathway, which is also critical for wound repair, have not been investigated. This study aimed to elucidate if PBM at 660 nm and a fluence of 5 J/cm² activates the WNT/β-catenin signaling pathway for wound healing in a diabetic cellular model. Human dermal fibroblasts (WS1) were continuously cultured high-glucose (26.5 mM D-glucose) environment to create a diabetic cellular model. A central scratch was created in the diabetic model to ‘wound’ the cells. The diabetic wounded (DW) cells were thereafter irradiated at 660 nm and a fluence of 5 J/cm². Cell migration, gene expression and protein assays were conducted at 24- and 48-h post-PBM. The results showed that PBM at 660 nm and a fluence of 5 J/cm² significantly increased cell migration in diabetic wounded cells at 24-h post-PBM. The expression of CTNNB1, ACTA2, COL1A1 and COL3A1 genes was also increased in DW cells post-PBM. Furthermore, there was increased cytoplasmic accumulation and nuclear localization of β-catenin at 24 h post-PBM. The findings in this study demonstrate that PBM activates the WNT/β-catenin signaling pathway by inducing the accumulation of β-catenin in diabetic wounded cells, leading to increased cell migration and expression of wound repair markers. These results thus indicate that PBM has the potential to improve wound healing in diabetic ulcers via activation of the WNT/β-catenin signaling pathway.

Keywords: wound healing, diabetic ulcers, photobiomodulation, WNT/β-catenin, signalling pathway

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Authors: Kraiem Khadija, Hamadi Kallali, Naceur Jedidi

Abstract:

Constructed wetland systems are eco-technology recognized as environmentally friendly and emerging innovative solutions remediation as these systems are cost-effective and sustainable wastewater treatment systems. The performance of these biological system is affected by various factors such as plant, substrate, wastewater type, hydraulic loading rate, hydraulic retention time, water depth, and operation mood. The objective of this study was to to assess the alters of plant species on pollutants reduction and enrichment of anammox and nitrifing denitrifing bacteria in a modified vertical flow (VFCW) constructed wetland. This tests were carried out using three modified vertical constructed wetlands with a surface of 0.23 m² and depth 80 cm. It was a saturated vertical constructed wetland at the bottom. The saturation zone is maintained by the siphon structure at the outlet. The VFCW (₁) system was unplanted, VFCW (₂) planted with Typha angustofolia, and VFCW(₃) planted with Phragmites australis. The experimental units were fed with domestic wastewater and were operated by batch mode during 8 months at an average hydraulic loading rate around 20 cm day− 1. The operation cycle was two days feeding and five days rest. Results indicated that plants presence improved the removal efficiency; the removal rates of organic matter (85.1–90.9%; COD and 81.8–88.9%; BOD5), nitrogen (54.2–73%; NTK and 66–77%; NH4 -N) were higher by 10.7–30.1% compared to the unplanted vertical constructed wetland. On the other hand, the plant species had no significant effect on removal efficiency of COD, The removal of COD was similar in VFCW (₂) and VFCW (₃) (p > 0.05), attaining average removal efficiencies of 88.7% and 85.2%, respectively. Whereas it had a significant effect on NTK removal (p > 0.05), with an average removal rate of 72% versus 51% for VFCW (₂) and VFCW (₃), respectively. Among the three sets of vertical flow constructed wetlands, the VFCW(₂) removed the highest percent of total streptococcus, fecal streptococcus total coliforms, fecal coliforms, E. coli as 59, 62, 52, 63, and 58%, respectively. The presence and the plant species alters the community composition and abundance of the bacteria. The abundance of bacteria in the planted wetland was much higher than that in the unplanted one. VFCW(₃) had the highest relative abundance of nitrifying bacteria such as Nitrosospira (18%), Nitrosospira (12%), and Nitrobacter (8%). Whereas the vertical constructed wetland planted with typha had larger number of denitrifying species, with relative abundances of Aeromonas (13%), Paracoccus (11%), Thauera (7%), and Thiobacillus (6%). However, the abundance of nitrifying bacteria was very lower in this system than VFCW(₂). Interestingly, the presence of Thypha angustofolia species favored the enrichment of anammox bacteria compared to unplanted system and system planted with phragmites australis. The results showed that the middle layer had the most accumulation of anammox bacteria, which the anaerobic condition is better and the root system is moderate. Vegetation has several characteristics that make it an essential component of wetlands, but its exact effects are complex and debated.

Keywords: wastawater, constructed wetland, anammox, removal

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Authors: Ana C. Sousa, Beatriz C. Santos, Fátima N. Serralha

Abstract:

The Tagus estuary is heavily affected by industrial and urban activities, making bioremediation studies crucial for environmental preservation. Fuel contamination in the area can arise from various anthropogenic sources, such as oil spills from shipping, fuel storage and transfer operations, and industrial discharges. These pollutants can cause severe harm to the ecosystem and the organisms, including humans, that inhabit it. Nonetheless, there are always natural organisms with the ability to resist these pollutants and transform them into non-toxic or harmless substances, which defines the process of bioremediation. Exploring the microbial communities existing in soil and their capacity to break down hydrocarbons has the potential to enhance the development of more efficient bioremediation approaches. The aim of this investigation was to explore the existence of hydrocarbonoclastic microorganisms in six locations within the Tagus estuary, three on the north bank: Trancão River, Praia Fluvial do Cais das Colinas and Praia de Algés, and three on the south bank: Praia Fluvial de Alcochete, Praia Fluvial de Alburrica, and Praia da Trafaria. In all studied locations, native microorganisms of the genus Pseudomonas were identified. The bioremediation rate of common hydrocarbons like gasoline, hexane, and toluene was assessed using the redox indicator 2,6-dichlorophenolindophenol (DCPIP). Effective hydrocarbon-degrading bacterial strains were identified in all analyzed areas, despite adverse environmental conditions. The highest bioremediation rates were achieved for gasoline (68%) in Alburrica, hexane (65%) in Algés, and toluene (79%) in Algés. Generally, the bacteria demonstrated efficient degradation of hydrocarbons added to the culture medium, with higher rates of aerobic biodegradation of hydrocarbons observed. These findings underscore the necessity for further in situ studies to better comprehend the relationship between native microbial communities and the potential for pollutant degradation in soil.

Keywords: biodegradability rate, hydrocarbonoclastic microorganisms, soil bioremediation, tagus estuary

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Authors: Manan’Iarivo Rasolonjanahary, Chris Bingham, Nigel Schofield, Masoud Bazargan

Abstract:

This paper presents the research and application of model predictive scheduled charging of electric vehicles (EV) subject to limited available power resource. To focus on algorithm and operational characteristics, the EV interface to the source is modelled as a battery state equation during the charging operation. The researched methods allow for the priority scheduling of EV charging in a multi-vehicle regime and when subject to limited source power availability. Priority attribution for each connected EV is described. The validity of the developed methodology is shown through the simulation of different scenarios of charging operation of multiple connected EVs including non-scheduled and scheduled operation with various numbers of vehicles. Performance of the developed algorithms is also reported with the recommendation of the choice of suitable parameters.

Keywords: model predictive control, non-scheduled, power limited sources, scheduled and stop-start battery charging

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Authors: O. Ahmed Apampa, Yinusa, A. Jimoh

Abstract:

The aim of this study was to develop an appropriate model for predicting the compaction behavior of lateritic soils and corn cob ash (CCA) stabilized lateritic soils. This was done by first adopting an equation earlier developed for fine-grained soils and subsequent adaptation by others and extending it to modified lateritic soil through the introduction of alpha and beta parameters which are polynomial functions of the CCA binder input. The polynomial equations were determined with MATLAB R2011 curve fitting tool, while the alpha and beta parameters were determined by standard linear programming techniques using the Solver function of Microsoft Excel 2010. The model so developed was a good fit with a correlation coefficient R2 value of 0.86. The paper concludes that it is possible to determine the optimum moisture content and the maximum dry density of CCA stabilized soils from the compaction test of the unmodified soil, and recommends that this procedure is extended to other binder stabilized lateritic soils to facilitate quick decision making in roadworks.

Keywords: compaction, corn cob ash, lateritic soil, stabilization

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Authors: Martin Böhmer, Agatha Dabrowski, Boris Otto

Abstract:

The trend of digitization significantly changes the role of data for enterprises. Data turn from an enabler to an intangible organizational asset that requires management and qualifies as a tradeable good. The idea of a networked economy has gained momentum in the data domain as collaborative approaches for data management emerge. Traditional organizational knowledge consequently needs to be extended by comprehensive knowledge about data. The knowledge about data is vital for organizations to ensure that data quality requirements are met and data can be effectively utilized and sovereignly governed. As this specific knowledge has been paid little attention to so far by academics, the aim of the research presented in this paper is to conceptualize it by proposing a “data knowledge model”. Relevant model entities have been identified based on a design science research (DSR) approach that iteratively integrates insights of various industry case studies and literature research.

Keywords: data management, digitization, industry 4.0, knowledge engineering, metamodel

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Authors: Edlira Donefski, Tina Donefski, Lorenc Ekonomi

Abstract:

Edgeworth Approximation, Bootstrap, and Monte Carlo Simulations have considerable impacts on achieving certain results related to different problems taken into study. In our paper, we have treated a financial case related to the effect that has the components of a cash-flow of one of the most successful businesses in the world, as the financial activity, operational activity, and investment activity to the cash and cash equivalents at the end of the three-months period. To have a better view of this case, we have created a vector autoregression model, and after that, we have generated the impulse responses in the terms of asymptotic analysis (Edgeworth Approximation), Monte Carlo Simulations, and residual bootstrap based on the standard errors of every series created. The generated results consisted of the common tendencies for the three methods applied that consequently verified the advantage of the three methods in the optimization of the model that contains many variants.

Keywords: autoregression, bootstrap, edgeworth expansion, Monte Carlo method

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