Search results for: plant growth models

Authors: Yasmeen Bassas, Sandra Kuebler, Allen Riddell

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Native language identification is one of the growing subfields in natural language processing (NLP). The task of native language identification (NLI) is mainly concerned with predicting the native language of an author’s writing in a second language. In this paper, we investigate the performance of two types of features; content-based features vs. content independent features, when they are evaluated on a different corpus (using social media data “Reddit”). In this NLI task, the predefined models are trained on one corpus (TOEFL), and then the trained models are evaluated on different data using an external corpus (Reddit). Three classifiers are used in this task; the baseline, linear SVM, and logistic regression. Results show that content-based features are more accurate and robust than content independent ones when tested within the corpus and across corpus.

Keywords: NLI, NLP, content-based features, content independent features, social media corpus, ML

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Authors: Pornsiri Kaewpradit, Chalisa Pourneaw

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Temperature control improvement of a membrane reactor with exothermic and reversible esterification reaction is studied in this work. It is well known that a batch membrane reactor requires different control strategies from a continuous one due to the fact that it is operated dynamically. Due to the effect of the operating temperature, the suitable control scheme has to be designed based reliable predictive model to achieve a desired objective. In the study, the optimization framework has been preliminary formulated in order to determine an optimal temperature trajectory for maximizing a desired product. In model predictive control scheme, a set of predictive models have been initially developed corresponding to the possible operating points of the system. The multiple predictive control moves have been further calculated on-line using the developed models corresponding to current operating point. It is obviously seen in the simulation results that the temperature control has been improved compared to the performance obtained by the conventional predictive controller. Further robustness tests have also been investigated in this study.

Keywords: model predictive control, batch reactor, temperature control, membrane reactor

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Jasper Kevin C. Dionisio, Denise Mae M. Unsay

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In a manufacturing firm, controlling the process ensures that optimum efficiency, productivity, and quality in an organization are achieved. An operation with no standardized procedure yields a poor productivity, inefficiency, and an out of control process. This study focuses on controlling the small intestine processing of a chicken dressing plant through the use of Statistical Process Control (SPC). Since the operation does not employ a standard procedure and does not have an established standard time, the process through the assessment of the observed time of the overall operation of small intestine processing, through the use of X-Bar R Control Chart, is found to be out of control. In the solution of this problem, the researchers conduct a motion and time study aiming to establish a standard procedure for the operation. The normal operator was picked through the use of Westinghouse Rating System. Instead of utilizing the traditional motion and time study, the researchers used the X-Bar R Control Chart in determining the process average of the process that is used for establishing the standard time. The observed time of the normal operator was noted and plotted to the X-Bar R Control Chart. Out of control points that are due to assignable cause were removed and the process average, or the average time the normal operator conducted the process, which was already in control and free form any outliers, was obtained. The process average was then used in determining the standard time of small intestine processing. As a recommendation, the researchers suggest the implementation of the standard time established which is with consonance to the standard procedure which was adopted from the normal operator. With that recommendation, the whole operation will induce a 45.54 % increase in their productivity.

Keywords: motion and time study, process controlling, statistical process control, X-Bar R Control chart

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Authors: Ayad Sleibi Mustafa, Ahmed Abdulkadhim Mohsin, Layth Noori Ali

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The deterioration of solid waste management in Baghdad city is considered as a great challenge in terms of human health and environment. Baghdad city is divided into thirteen districts which are distributed on both Tigris River banks. The west bank is Al-Karkh and the east bank is Al-Rusafa. Municipal Solid Waste Management is one of the most complicated problems facing the environment in Iraq. Population growth led to increase waste production and more load of the waste to the limited capacity infrastructure. The problems of municipal solid waste become more serious after the war in 2003. More waste is disposed in underground landfills in Baghdad with little or no concern for both human health and environment. The results showed that the total annually predicted solid waste is increasing for the period 2015-2030. Municipal solid waste in 2030 will be 6,427,773 tons in Baghdad city according to the population growth rate of 2.4%. This increase is estimated to be approximately 30%.

Keywords: municipal solid waste, solid waste composition and characteristics, Baghdad city, environment, human health

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Authors: Vu Thu Trang, Lam Xuan Thanh, Samira Sarter, Tomoko Shimamura, Hiroaki Takeuchi　　

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Antimicrobial activities of aminoreductone (AR), a product formed in the initial stage of Maillard reaction, were screened against pathogenic bacteria. A significant growth inhibition of AR against all 7 isolates (Staphylococcus aureus ATCC® 25923™, Salmonella Typhimurium ATCC® 14028™, Bacillus cereus ATCC® 13061™, Bacillus subtilis ATCC® 11774™, Escherichia coli ATCC® 25922™, Enterococcus faecalis ATCC® 29212™, Listeria innocua ATCC® 33090™) were observed by the standard disc diffusion methods. The inhibition zone for each isolate by AR (2.5 mg) ranged from 15±0 mm to 28.3±0.4 mm in diameter. The minimum inhibitory concentration (MIC) of AR ranging from 20 mM to 26 mM was proven in the seven isolates tested. AR also showed the similar effect of growth inhibition in comparison with antibiotics frequently used for the treatment of infections bacteria, such as amikacin, ciprofloxacin, meropennem, and levofloxacin. The results indicated that foods containing AR are valuable sources of bioactive compounds towards pathogenic bacteria.

Keywords: pathogenic bacteria, aminoreductone, Maillard reaction, antimicrobial activity

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Authors: Prachi Singh

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This paper presents a low-cost, eco-friendly and reproducible microbe mediated biosynthesis of TiO₂ nanoparticles. TiO₂ nanoparticles synthesized using the bacterium, Bacillus subtilis, from titanium as a precursor, were confirmed by TEM analysis. The morphological characteristics state spherical shape, with the size of individual or aggregate nanoparticles, around 30-40 nm. Microbial resistance represents a challenge for the scientific community to develop new bioactive compounds. Here, the antibacterial effect of TiO₂ nanoparticles on Escherichia coli was investigated, which was confirmed by CFU (Colony-forming unit). Further, growth curve study of E. coli Hb101 in the presence and absence of TiO₂ nanoparticles was done. Optical density decrease was observed with the increase in the concentration of TiO₂. It could be attributed to the inactivation of cellular enzymes and DNA by binding to electron-donating groups such as carboxylates, amides, indoles, hydroxyls, thiols, etc. which cause little pores in bacterial cell walls, leading to increased permeability and cell death. This justifies that TiO₂ nanoparticles have efficient antibacterial effect and have potential to be used as an antibacterial agent for different purposes.

Keywords: antibacterial effect, CFU, Escherichia coli Hb101, growth curve, TEM, TiO2 nanoparticle, Toxicity, UV-Vis

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Authors: Abadi Berhane, Walelign Worku, Berhanu Abrha, Gebre Hadgu, Tigray

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Sesame is an important oilseed crop in Ethiopia; which is the second most exported agricultural commodity next to coffee. However, there is poor soil fertility management and a research-led farming system for the crop. The AquaCrop model was applied as a decision-support tool; which performs a semi-quantitative approach to simulate the yield of crops under different soil fertility levels. The objective of this experiment was to calibrate and validated the AquaCrop model for simulating the growth and yield of sesame under different nitrogen fertilizer levels and to test the performance of the model as a decision-support tool for improved sesame cultivation in the study area. The experiment was laid out as a randomized complete block design (RCBD) in a factorial arrangement in the 2016, 2017, and 2018 main cropping seasons. In this experiment, four nitrogen fertilizer rates; 0, 23, 46, and 69 Kg/ha nitrogen, and three improved varieties (Setit-1, Setit-2, and Humera-1). In the meantime, growth, yield, and yield components of sesame were collected from each treatment. Coefficient of determination (R2), Root mean square error (RMSE), Normalized root mean square error (N-RMSE), Model efficiency (E), and Degree of agreement (D) were used to test the performance of the model. The results indicated that the AquaCrop model successfully simulated soil water content with R2 varying from 0.92 to 0.98, RMSE 6.5 to 13.9 mm, E 0.78 to 0.94, and D 0.95 to 0.99; and the corresponding values for AB also varied from 0.92 to 0.98, 0.33 to 0.54 tons/ha, 0.74 to 0.93, and 0.9 to 0.98, respectively. The results on the canopy cover of sesame also showed that the model acceptably simulated canopy cover with R2 varying from 0.95 to 0.99, and a RMSE of 5.3 to 8.6%. The AquaCrop model was appropriately calibrated to simulate soil water content, canopy cover, aboveground biomass, and sesame yield; the results indicated that the model adequately simulated the growth and yield of sesame under the different nitrogen fertilizer levels. The AquaCrop model might be an important tool for improved soil fertility management and yield enhancement strategies of sesame. Hence, the model might be applied as a decision-support tool in soil fertility management in sesame production.

Keywords: aquacrop model, sesame, normalized water productivity, nitrogen fertilizer

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Authors: F. Lops, G. Disciglio, A. Carlucci, G. Gatta, L. Frabboni, A. Tarantino, E. Tarantino

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Phelipanche ramosa L. Pomel is a root holoparasitic weed plant of many cultivations, particularly of tomato (Lycopersicum esculentum L.) crop. In Italy, Phelipanche problem is increasing, both in density and in acreage. The biological control of this parasitic weed involves the use of living organisms as numerous fungi and bacteria that can infect the parasitic weed, while it may improve the crop growth. This paper deals with the biocontrol with microorganism, including Arbuscular mycorrhizal (AM) fungi and fungal pathogens as Fusarium oxisporum spp. Colonization of crop roots by AM fungi can provide protection of crops against parasitic weeds because of a reduction in their seed germination and attachment, while F. oxisporum, isolated from diseased broomrape tubercles, proved to be highly virulent on P. ramosa. The experimental trial was carried out in open field at Foggia province (Apulia Region, Southern Italy), during the spring-summer season 2016, in order to evaluate the effect of four biological treatments: AM fungi and Fusarium oxisporum applied in the soil alone or combined together, and Rizosum Max^® product, compared with the untreated control, to reduce the P. ramosa infestation in processing tomato crop. The principal results to be drawn from this study under field condition, in contrast of those reported previously under laboratory and greenhouse conditions, show that both AM fungi and F. oxisporum do not provide the reduction of the number of emerged shoots of P. ramosa. This can arise probably from the low efficacy seedling of the agent pathogens for the control of this parasite in the field. On the contrary, the Rizosum Max^® product, containing AM fungi and some rizophere bacteria combined with several minerals and organic substances, appears to be most effective for the reduction of P. ramosa infestation.

Keywords: Arbuscular mycorrhized fungi, biocontrol methods, Phelipanche ramosa, tomato crop

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Authors: Harish Rajak, Preeti Patel

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The application of histone deacetylase inhibitors is a well-known strategy in prevention of cancer which shows acceptable preclinical antitumor activity due to its ability of growth inhibition and apoptosis induction of cancer cell. Molecular docking were performed using Histone Deacetylase protein (PDB ID:1t69) and prepared series of hydroxamic acid based HDACIs. On the basis of docking study, it was predicted that compound 1 has significant binding interaction with HDAC protein and three hydrogen bond interactions takes place, which are essential for antitumor activity. On docking, most of the compounds exhibited better glide score values between -8 to -10 which is close to the glide score value of suberoylanilide hydroxamic acid. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. The 3D-QSAR models provided a good correlation between predicted and actual anticancer activity. Best QSAR model showed Q2 (0.7974), R2 (0.9200) and standard deviation (0.2308). QSAR visualization maps suggest that hydrogen bond acceptor groups at carbonyl group of cap region and hydrophobic groups at ortho, meta, para position of R9 were favorable for HDAC inhibitory activity. We established structure activity correlation using docking, pharmacophore modeling and atom based 3D QSAR model for hydroxamic acid based HDACIs.

Keywords: HDACIs, QSAR, e-pharmacophore, docking, suberoylanilide hydroxamic acid

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Authors: Nazira Kakulia

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The analysis of transformation of institutional changes outlines two important characteristics. These are: the speed of the changes and their sequence. Successful transformation must be carried out in three different stages; On the first stage, macroeconomic stabilization must be achieved with the help of fiscal and monetary tools. Two-tier banking system should be established and the active functions of central bank should be replaced by the passive ones (reserve requirements and refinancing rate), together with the involvement growth of private sector. Fiscal policy by itself here means the creation of tax system which must replace previously existing direct state revenues; the share of subsidies in the state expenses must be reduced also. The second stage begins after reaching the macroeconomic stabilization at a time of change of formal institutes which must stimulate the private business. Corporate legislation creates a competitive environment at the market and the privatization of state companies takes place. Bankruptcy and contract law is created. he third stage is the most extended one, which means the formation of all state structures that is necessary for the further proper functioning of a market economy. These three stages about the cycle period of political and social transformation and the hierarchy of changes can also be grouped by the different methodology: on the first and the most short-term stage the transfer of power takes place. On the second stage institutions corresponding to new goal are created. The last phase of transformation is extended in time and it includes the infrastructural, socio-cultural and socio-structural changes. The main goal of this research is to explore and identify the features of such kind of models.

Keywords: competitive environment, fiscal policy, macroeconomic stabilization, tax system

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Authors: Balgaisha Mukanova, Natalya Glazyrina, Sergey Glazyrin

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The formulated problem of optimization of the technological process of water treatment for thermal power plants is considered in this article. The problem is of multiparametric nature. To optimize the process, namely, reduce the amount of waste water, a new technology was developed to reuse such water. A mathematical model of the technology of wastewater reuse was developed. Optimization parameters were determined. The model consists of a material balance equation, an equation describing the kinetics of ion exchange for the non-equilibrium case and an equation for the ion exchange isotherm. The material balance equation includes a nonlinear term that depends on the kinetics of ion exchange. A direct problem of calculating the impurity concentration at the outlet of the water treatment plant was numerically solved. The direct problem was approximated by an implicit point-to-point computation difference scheme. The inverse problem was formulated as relates to determination of the parameters of the mathematical model of the water treatment plant operating in non-equilibrium conditions. The formulated inverse problem was solved. Following the results of calculation the time of start of the filter regeneration process was determined, as well as the period of regeneration process and the amount of regeneration and wash water. Multi-parameter optimization of water treatment process for thermal power plants allowed decreasing the amount of wastewater by 15%.

Keywords: direct problem, multiparametric optimization, optimization parameters, water treatment

Procedia PDF Downloads 385

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

Procedia PDF Downloads 541

Authors: C. Pislaru, A. Shebani

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This paper uses the radial basis function neural network (RBFNN) for system identification of nonlinear systems. Five nonlinear systems are used to examine the activity of RBFNN in system modeling of nonlinear systems; the five nonlinear systems are dual tank system, single tank system, DC motor system, and two academic models. The feed forward method is considered in this work for modelling the non-linear dynamic models, where the K-Means clustering algorithm used in this paper to select the centers of radial basis function network, because it is reliable, offers fast convergence and can handle large data sets. The least mean square method is used to adjust the weights to the output layer, and Euclidean distance method used to measure the width of the Gaussian function.

Keywords: system identification, nonlinear systems, neural networks, radial basis function, K-means clustering algorithm

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Authors: V. K. Rajaletchumy, S. L. Chia, M. I. Setyawati, M. S. Muthu, S. S. Feng, D. T. Leong

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Triple negative breast cancers (TNBC) can be classified as one of the most aggressive with a high rate of local recurrences and systematic metastases. TNBCs are insensitive to existing hormonal therapy or targeted therapies such as the use of monoclonal antibodies, due to the lack of oestrogen receptor (ER) and progesterone receptor (PR) and the absence of overexpression of human epidermal growth factor receptor 2 (HER2) compared with other types of breast cancers. The absence of targeted therapies for selective delivery of therapeutic agents into tumours, led to the search for druggable targets in TNBC. In this study, we developed a targeted micellar system of cetuximab-conjugated micelles of D-α-tocopheryl polyethylene glycol succinate (vitamin E TPGS) for targeted delivery of docetaxel as a model anticancer drug for the treatment of TNBCs. We examined the efficacy of our micellar system in xenograft models of triple negative breast cancers and explored the effect of the micelles on post-treatment tumours in order to elucidate the mechanism underlying the nanomedicine treatment in oncology. The targeting micelles were found preferentially accumulated in tumours immediately after the administration of the micelles compare to normal tissue. The fluorescence signal gradually increased up to 12 h at the tumour site and sustained for up to 24 h, reflecting the increases in targeted micelles (TPFC) micelles in MDA-MB-231/Luc cells. In comparison, for the non-targeting micelles (TPF), the fluorescence signal was evenly distributed all over the body of the mice. Only a slight increase in fluorescence at the chest area was observed after 24 h post-injection, reflecting the moderate uptake of micelles by the tumour. The successful delivery of docetaxel into tumour by the targeted micelles (TPDC) exhibited a greater degree of tumour growth inhibition than Taxotere® after 15 days of treatment. The ex vivo study has demonstrated that tumours treated with targeting micelles exhibit enhanced cell cycle arrest and attenuated proliferation compared with the control and with those treated non-targeting micelles. Furthermore, the ex vivo investigation revealed that both the targeting and non-targeting micellar formulations shows significant inhibition of cell migration with migration indices reduced by 0.098- and 0.28-fold, respectively, relative to the control. Overall, both the in vivo and ex vivo data increased the confidence that our micellar formulations effectively targeted and inhibited EGF-overexpressing MDA-MB-231 tumours.

Keywords: biodegradable polymers, cancer nanotechnology, drug targeting, molecular biomaterials, nanomedicine

Procedia PDF Downloads 278

Authors: Ren Moses, Emmanuel Kidando, Eren Ozguven, Yassir Abdelrazig

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This study applied traffic speed and occupancy to develop clustering models that identify different traffic conditions. Particularly, these models are based on the Dirichlet Process Mixture of Generalized Linear regression (DML) and change-point regression (CR). The model frameworks were implemented using 2015 historical traffic data aggregated at a 15-minute interval from an Interstate 295 freeway in Jacksonville, Florida. Using the deviance information criterion (DIC) to identify the appropriate number of mixture components, three traffic states were identified as free-flow, transitional, and congested condition. Results of the DML revealed that traffic occupancy is statistically significant in influencing the reduction of traffic speed in each of the identified states. Influence on the free-flow and the congested state was estimated to be higher than the transitional flow condition in both evening and morning peak periods. Estimation of the critical speed threshold using CR revealed that 47 mph and 48 mph are speed thresholds for congested and transitional traffic condition during the morning peak hours and evening peak hours, respectively. Free-flow speed thresholds for morning and evening peak hours were estimated at 64 mph and 66 mph, respectively. The proposed approaches will facilitate accurate detection and prediction of traffic congestion for developing effective countermeasures.

Keywords: traffic congestion, multistate speed distribution, traffic occupancy, Dirichlet process mixtures of generalized linear model, Bayesian change-point detection

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Authors: Ehsan Etesami, Mostafa Noroozi

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Thalassiosira weissflogii with proper size and nutrition value specially PUFA n-3 has been widely used in bivalve shellfish larviculture and shrimp industries. This diatom was isolated from Caspian Sea and identified with morphology and molecular characters. T. weissflogii was cultivated in normal and nitrogen deficiency F2 medium during 18 to 30 days, in addition, the growth indices, total lipid, and EPA-DHA content were elucidated. The growth indices of the cells decreased during the stress experiments while the total lipid levels increased during prolonged culturing (30 days). The maximum level of C20:5 was calculated as 8.8 (%TFA) in normal condition during 30 days; however, the combination of N- deficiency condition with prolonged culturing led to the increase of the level of C22:6 from 3.5 to 12.63 (%TFA). The concept of N-deficiency along with prolonged culturing of Thalassiosira weissflogii can improve PUFA n-3 content in order to use in shellfish and shrimp industries.

Keywords: DHA, Thalassiosira weissflogii, nitrogen deficiency, EPA, fatty acids, aquafeed

Procedia PDF Downloads 139

Authors: Shuailing Cui, Nakajiam Naoto

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The tourism industry has experienced significant growth worldwide since the end of World War II. Tourists are drawn to suburban areas during weekends and holidays to explore historical and cultural heritage sites. Since the 1970s, there has been a resurgence in population growth in metropolitan areas, which has fueled the demand for suburban tourism and facilitated its development. The construction of infrastructure, such as railway lines and arterial roads, has also supported the growth of tourism. Tourists engaging in various activities can have a significant impact on the destinations they visit. Tourism has not only affected the local economy but has also begun to alter the social structures, culture, and lifestyle of the destinations visited. In addition, the growing number of tourists has affected the local commercial structure and daily life of suburban residents. Therefore, there is a need to figure out how tourism activities influence the residential environment of the tourist destination and how this influence changes over time. This study aims to analyze the transformation of the relationship between tourism activities and the residential environment in the Naka-Uji area of Uji City, Kyoto Prefecture. Specifically, it investigates how the growth of the tourism industry has influenced the local residential environment and how this influence has changed over time. The findings of the study indicate that the growth of tourism in the Naka-Uji area has had both positive and negative effects on the local residential environment. On the one hand, the tourism industry has created job opportunities and improved local economic conditions. On the other hand, it has also caused environmental degradation, particularly in terms of increased traffic and the construction of parking lots. The study also found that the development of the tourism industry has influenced the social structures, culture, and lifestyle of residents. For instance, the increase in the number of tourists has led to changes in the commercial structure and daily life of suburban residents. The study highlights the importance of collaboration and shared benefits among stakeholders in tourism development, particularly in terms of preserving the cultural and natural heritage of tourist destinations while promoting sustainable development. Overall, this study contributes to the growing body of research on the impact of tourism on suburban areas. It provides insights into the complex relationships between tourism, the natural environment, the local economy, and residential life and emphasizes the need for sustainable tourism development in suburban areas. The findings of this study have important implications for policymakers, urban planners, and other stakeholders involved in promoting regional revitalization and sustainable tourism development.

Keywords: tourism, residential environment, suburban area, metropolis

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Authors: Shuailing CUI, Nakajima Naoto

Abstract:

The tourism industry has experienced significant growth worldwide since the end of World War II. Tourists are drawn to suburban areas during weekends and holidays to explore historical and cultural heritage sites. Since the 1970s, there has been a resurgence in population growth in metropolitan areas, which has fueled the demand for suburban tourism and facilitated its development. The construction of infrastructure, such as railway lines and arterial roads, has also supported the growth of tourism. Tourists engaging in various activities can have a significant impact on the destinations they visit. Tourism has not only affected the local economy but has also begun to alter the social structures, culture, and lifestyle of the destinations visited. In addition, the growing number of tourists has affected the local commercial structure and daily life of suburban residents. Therefore, there is a need to figure out how tourism activities influence the residential environment of the tourist destination and how this influence changes over time. This study aims to analyze the transformation of the relationship between tourism activities and the residential environment in the Naka-Uji area of Uji City, Kyoto Prefecture. Specifically, it investigates how the growth of the tourism industry has influenced the local residential environment and how this influence has changed over time. The findings of the study indicate that the growth of tourism in the Naka-Uji area has had both positive and negative effects on the local residential environment. On the one hand, the tourism industry has created job opportunities and improved local economic conditions. On the other hand, it has also caused environmental degradation, particularly in terms of increased traffic and the construction of parking lots. The study also found that the development of the tourism industry has influenced the social structures, culture, and lifestyle of residents. For instance, the increase in the number of tourists has led to changes in the commercial structure and daily life of suburban residents. The study highlights the importance of collaboration and shared benefits among stakeholders in tourism development, particularly in terms of preserving the cultural and natural heritage of tourist destinations while promoting sustainable development. Overall, this study contributes to the growing body of research on the impact of tourism on suburban areas. It provides insights into the complex relationships between tourism, the natural environment, the local economy, and residential life, and emphasizes the need for sustainable tourism development in suburban areas. The findings of this study have important implications for policymakers, urban planners, and other stakeholders involved in promoting regional revitalization and sustainable tourism development.

Keywords: tourism, residential environment, suburban area, metropolis

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Authors: Muhammad Imran, Iqra Basit, Mobushir Riaz Khan, Sajid Rasheed Ahmad

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The present study investigates the space-time impact of climate change on the rice crop calendar in tropical Gujranwala, Pakistan. The climate change impact was quantified through the climatic variables, whereas the existing calendar of the rice crop was compared with the phonological stages of the crop, depicted through the time series of the Normalized Difference Vegetation Index (NDVI) derived from Landsat data for the decade 2005-2015. Local maxima were applied on the time series of NDVI to compute the rice phonological stages. Panel models with fixed and cross-section fixed effects were used to establish the relation between the climatic parameters and the time-series of NDVI across villages and across rice growing periods. Results show that the climatic parameters have significant impact on the rice crop calendar. Moreover, the fixed effect model is a significant improvement over cross-sectional fixed effect models (R-squared equal to 0.673 vs. 0.0338). We conclude that high inter-annual variability of climatic variables cause high variability of NDVI, and thus, a shift in the rice crop calendar. Moreover, inter-annual (temporal) variability of the rice crop calendar is high compared to the inter-village (spatial) variability. We suggest the local rice farmers to adapt this change in the rice crop calendar.

Keywords: Landsat NDVI, panel models, temperature, rainfall

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Authors: Ahmadali Tahmasebimoradi, Chetra Mang, Xavier Lorang

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Thanks to the additive manufacturing process, lattice structures are replacing the traditional structures in aeronautical and automobile industries. In order to evaluate the mechanical response of the lattice structures, one has to resort to numerical techniques. Ansys is a globally well-known and trusted commercial software that allows us to model the lattice structures and analyze their mechanical responses using either solid or beam elements. In this software, a script may be used to systematically generate the lattice structures for any size. On the one hand, solid elements allow us to correctly model the contact between the substrates (the supports of the lattice structure) and the lattice structure, the local plasticity, and the junctions of the microbeams. However, their computational cost increases rapidly with the size of the lattice structure. On the other hand, although beam elements reduce the computational cost drastically, it doesn’t correctly model the contact between the lattice structures and the substrates nor the junctions of the microbeams. Also, the notion of local plasticity is not valid anymore. Moreover, the deformed shape of the lattice structure doesn’t correspond to the deformed shape of the lattice structure using 3D solid elements. In this work, motivated by the pros and cons of the 3D and beam models, a numerically hybrid model is presented for the lattice structures to reduce the computational cost of the simulations while avoiding the aforementioned drawbacks of the beam elements. This approach consists of the utilization of solid elements for the junctions and beam elements for the microbeams connecting the corresponding junctions to each other. When the global response of the structure is linear, the results from the hybrid models are in good agreement with the ones from the 3D models for body-centered cubic with z-struts (BCCZ) and body-centered cubic without z-struts (BCC) lattice structures. However, the hybrid models have difficulty to converge when the effect of large deformation and local plasticity are considerable in the BCCZ structures. Furthermore, the effect of the junction’s size of the hybrid models on the results is investigated. For BCCZ lattice structures, the results are not affected by the junction’s size. This is also valid for BCC lattice structures as long as the ratio of the junction’s size to the diameter of the microbeams is greater than 2. The hybrid model can take into account the geometric defects. As a demonstration, the point clouds of two lattice structures are parametrized in a platform called LATANA (LATtice ANAlysis) developed by IRT-SystemX. In this process, for each microbeam of the lattice structures, an ellipse is fitted to capture the effect of shape variation and roughness. Each ellipse is represented by three parameters; semi-major axis, semi-minor axis, and angle of rotation. Having the parameters of the ellipses, the lattice structures are constructed in Spaceclaim (ANSYS) using the geometrical hybrid approach. The results show a negligible discrepancy between the hybrid and 3D models, while the computational cost of the hybrid model is lower than the computational cost of the 3D model.

Keywords: additive manufacturing, Ansys, geometric defects, hybrid finite element model, lattice structure

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Authors: Swati Bhomia, C. M. Kishtawal, Neeru Jaiswal

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Traditionally, monsoon forecasts have encountered many difficulties that stem from numerous issues such as lack of adequate upper air observations, mesoscale nature of convection, proper resolution, radiative interactions, planetary boundary layer physics, mesoscale air-sea fluxes, representation of orography, etc. Uncertainties in any of these areas lead to large systematic errors. Global circulation models (GCMs), which are developed independently at different institutes, each of which carries somewhat different representation of the above processes, can be combined to reduce the collective local biases in space, time, and for different variables from different models. This is the basic concept behind the multi-model superensemble and comprises of a training and a forecast phase. The training phase learns from the recent past performances of models and is used to determine statistical weights from a least square minimization via a simple multiple regression. These weights are then used in the forecast phase. The superensemble forecasts carry the highest skill compared to simple ensemble mean, bias corrected ensemble mean and the best model out of the participating member models. This approach is a powerful post-processing method for the estimation of weather forecast parameters reducing the direct model output errors. Although it can be applied successfully to the continuous parameters like temperature, humidity, wind speed, mean sea level pressure etc., in this paper, this approach is applied to rainfall, a parameter quite difficult to handle with standard post-processing methods, due to its high temporal and spatial variability. The present study aims at the development of advanced superensemble schemes comprising of 1-5 day daily precipitation forecasts from five state-of-the-art global circulation models (GCMs), i.e., European Centre for Medium Range Weather Forecasts (Europe), National Center for Environmental Prediction (USA), China Meteorological Administration (China), Canadian Meteorological Centre (Canada) and U.K. Meteorological Office (U.K.) obtained from THORPEX Interactive Grand Global Ensemble (TIGGE), which is one of the most complete data set available. The novel approaches include the dynamical model selection approach in which the selection of the superior models from the participating member models at each grid and for each forecast step in the training period is carried out. Multi-model superensemble based on the training using similar conditions is also discussed in the present study, which is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional multi-model ensemble (MME) approaches. Further, a variety of methods that incorporate a 'neighborhood' around each grid point which is available in literature to allow for spatial error or uncertainty, have also been experimented with the above mentioned approaches. The comparison of these schemes with respect to the observations verifies that the newly developed approaches provide more unified and skillful prediction of the summer monsoon (viz. June to September) rainfall compared to the conventional multi-model approach and the member models.

Keywords: multi-model superensemble, dynamical model selection, similarity criteria, neighborhood technique, rainfall prediction

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Authors: Ramachandra C. G., Amarnath. M., Prashanth Pai M., Nagesh S. N.

Abstract:

The machine's performance level drops down over a period of time due to the wear and tear of its components. The early detection of an emergent fault becomes very vital in order to obtain uninterrupted production in a plant. Maintenance is an activity that helps to keep the machine's performance at an anticipated level, thereby ensuring the availability of the machine to perform its intended function. At present, a number of modern maintenance techniques are available, such as preventive maintenance, predictive maintenance, condition-based maintenance, total productive maintenance, etc. Condition-based maintenance or condition monitoring is one such modern maintenance technique in which the machine's condition or health is checked by the measurement of certain parameters such as sound level, temperature, velocity, displacement, vibration, etc. It can recognize most of the factors restraining the usefulness and efficacy of the total manufacturing unit. This research work is conducted on a Batch Mill in a tire production unit located in the Southern Karnataka region. The health of the mill is assessed using amplitude of vibration as a parameter of measurement. Most commonly, the vibration level is assessed using various points on the machine bearing. The normal or standard level is fixed using reference materials such as manuals or catalogs supplied by the manufacturers and also by referring vibration standards. The Rio-Vibro meter is placed in different locations on the batch-off mill to record the vibration data. The data collected are analyzed to identify the malfunctioning components in the batch off the mill, and corrective measures are suggested.

Keywords: availability, displacement, vibration, rio-vibro, condition monitoring

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Authors: Habtamu Tkubet Ebuy

Abstract:

Purpose Conventional dynamic energy simulation tools go beyond the static dimension of simplified methods by providing better and more accurate prediction of building performance. However, their ability to forecast actual performance is undermined by a low representation of human interactions. The purpose of this study is to examine the potential benefits of incorporating information on occupant diversity into occupant behavior models used to simulate building performance. The co-simulation of the stochastic behavior of the occupants substantially increases the accuracy of the simulation. Design/methodology/approach In this article, probabilistic models of the "opening and closing" behavior of the window of inhabitants have been developed in a separate multi-agent platform, SimOcc, and implemented in the building simulation, TRNSYS, in such a way that the behavior of the window with the interconnectivity can be reflected in the simulation analysis of the building. Findings The results of the study prove that the application of complex behaviors is important to research in predicting actual building performance. The results aid in the identification of the gap between reality and existing simulation methods. We hope this study and its results will serve as a guide for researchers interested in investigating occupant behavior in the future. Research limitations/implications Further case studies involving multi-user behavior for complex commercial buildings need to more understand the impact of the occupant behavior on building performance. Originality/value This study is considered as a good opportunity to achieve the national strategy by showing a suitable tool to help stakeholders in the design phase of new or retrofitted buildings to improve the performance of office buildings.

Keywords: occupant behavior, co-simulation, energy consumption, thermal comfort

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Authors: Alon Cohen, Jeffrey Kantor, Shalom Levy

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Technology adoption models are extensively used in the literature to explore drivers and inhibitors affecting the adoption of Computer Assisted Audit Techniques and Tools (CAATTs). Further studies from recent years suggested additional factors that may affect technology adoption by CPA firms. However, the adoption of CAATTs by financial auditors differs from the adoption of technologies in other industries. This is a result of the unique characteristics of the auditing process, which are expressed in the audit risk elements and the risk-based auditing approach, as encoded in the auditing standards. Since these audit risk factors are not part of the existing models that are used to explain technology adoption, these models do not fully correspond to the specific needs and requirements of the auditing domain. The overarching objective of this qualitative research is to fill the gap in the literature, which exists as a result of using generic technology adoption models. Followed by a pretest and based on semi-structured in-depth interviews with 16 Israeli CPA firms of different sizes, this study aims to reveal determinants related to audit risk factors that influence the adoption of CAATTs in audits and proposes a new modeling approach for the successful adoption of CAATTs. The findings emphasize several important aspects: (1) while large CPA firms developed their own inner guidelines to assess the audit risk components, other CPA firms do not follow a formal and validated methodology to evaluate these risks; (2) large firms incorporate a variety of CAATTs, including self-developed advanced tools. On the other hand, small and mid-sized CPA firms incorporate standard CAATTs and still need to catch up to better understand what CAATTs can offer and how they can contribute to the quality of the audit; (3) the top management of mid-sized and small CPA firms should be more proactive and updated about CAATTs capabilities and contributions to audits; and (4) All CPA firms consider professionalism as a major challenge that must be constantly managed to ensure an optimal CAATTs operation. The study extends the existing knowledge of CAATTs adoption by looking at it from a risk-based auditing approach. It suggests a new model for CAATTs adoption by incorporating influencing audit risk factors that auditors should examine when considering CAATTs adoption. Since the model can be used in various audited scenarios and supports strategic, risk-based decisions, it maximizes the great potential of CAATTs on the quality of the audits. The results and insights can be useful to CPA firms, internal auditors, CAATTs developers and regulators. Moreover, it may motivate audit standard-setters to issue updated guidelines regarding CAATTs adoption in audits.

Keywords: audit risk, CAATTs, financial auditing, information technology, technology adoption models

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Authors: Zahreddine Hafsi, Manoranjan Mishra , Sami Elaoud

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Ensuring the maximum recovery rate of oil from reservoir rocks is a challenging task that requires preliminary numerical analysis of different techniques used to enhance the recovery process. After conventional oil recovery processes and in order to retrieve oil left behind after the primary recovery phase, water flooding in one of several techniques used for enhanced oil recovery (EOR). In this research work, EOR via water flooding is numerically modeled, and hydrodynamic instabilities resulted from immiscible oil-water flow in reservoir rocks are investigated. An oil reservoir is a porous medium consisted of many fractures of tiny dimensions. For modeling purposes, the oil reservoir is considered as a collection of capillary tubes which provides useful insights into how fluids behave in the reservoir pore spaces. Equations governing oil-water flow in oil reservoir rocks are developed and numerically solved following a finite element scheme. Numerical results are obtained using Comsol Multiphysics software. The two phase Darcy module of COMSOL Multiphysics allows modelling the imbibition process by the injection of water (as wetting phase) into an oil reservoir. Van Genuchten, Brooks Corey and Levrett models were considered as retention models and obtained flow configurations are compared, and the governing parameters are discussed. For the considered retention models it was found that onset of instabilities viz. fingering phenomenon is highly dependent on the capillary pressure as well as the boundary conditions, i.e., the inlet pressure and the injection velocity.

Keywords: capillary pressure, EOR process, immiscible flow, numerical modelling

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Authors: Won Kyung Ham, Kang Hoon Cho, Sang C. Park

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Presented in this paper is a framework of a software ‘WEMax’. The WEMax is invented for analysis and simulation for manned assembly lines to sustain and improve performance of manufacturing systems. In a manufacturing system, performance, such as productivity, is a key of competitiveness for output products. However, the manned assembly lines are difficult to forecast performance, because human labors are not expectable factors by computer simulation models or mathematical models. Existing approaches to performance forecasting of the manned assembly lines are limited to matters of the human itself, such as ergonomic and workload design, and non-human-factor-relevant simulation. Consequently, an approach for the forecasting and improvement of manned assembly line performance is needed to research. As a solution of the current problem, this study proposes a framework that is for generation and simulation of virtual manned assembly lines, and the framework has been implemented as a software.

Keywords: performance forecasting, simulation, virtual manned assembly line, WEMax

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Authors: Yuchen Sharon Sung, Yingjui Tseng

Abstract:

High-rise residential buildings have become the most mainstream housing pattern in the world’s metropolises under the current trend of urbanization. The facades of high-rise buildings are essential elements of the urban landscape. The skins of these facades are important media between the interior and exterior of high- rise buildings. It not only connects between users and environments, but also plays an important functional and aesthetic role. This research involves a study of skins of high-rise residential buildings using the methodology of shape grammar to find out the rules which determine the combinations of the facade patterns and analyze the patterns’ parameters using software Grasshopper. We chose a number of facades of high-rise residential buildings as source to discover the underlying rules and concepts of the generation of facade skins. This research also provides the rules that influence the composition of facade skins. The items of the facade skins, such as windows, balconies, walls, sun visors and metal grilles are treated as elements in the system of facade skins. The compositions of these elements will be categorized and described by logical rules; and the types of high-rise building facade skins will be modelled by Grasshopper. Then a variety of analyzed patterns can also be applied on other facade skins through this parametric mechanism. Using these patterns established in the models, researchers can analyze each single item to do more detail tests and architects can apply each of these items to construct their facades for other buildings through various combinations and permutations. The goal of these models is to develop a mechanism to generate prototypes in order to facilitate generation of various facade skins.

Keywords: facade skin, grasshopper, high-rise residential building, shape grammar

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Authors: V. D. Thi, M. Li, M. Khelifa, M. El Ganaoui, Y. Rogaume

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This paper presents a two-dimensional model to study the heat and moisture transfer through porous building materials. Dynamic and static coupled models of heat and moisture transfer in porous material under low temperature are presented and the coupled models together with variable initial and boundary conditions have been considered in an analytical way and using the finite element method. The resulting coupled model is converted to two nonlinear partial differential equations, which is then numerically solved by an implicit iterative scheme. The numerical results of temperature and moisture potential changes are compared with the experimental measurements available in the literature. Predicted results demonstrate validation of the theoretical model and effectiveness of the developed numerical algorithms. It is expected to provide useful information for the porous building material design based on heat and moisture transfer model.

Keywords: finite element method, heat transfer, moisture transfer, porous materials, wood

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Authors: Benbiao Song, Yan Gao, Zhuo Liu

Abstract:

Geostatistical modeling is the key technic for reservoir characterization, the quality of geological models will influence the prediction of reservoir performance greatly, but few studies have been done to quantify the factors impacting geostatistical reservoir modeling accuracy. In this study, 16 fluvial prototype models have been established to represent different geological complexity, 6 cases range from 16 to 361 wells were defined to reproduce all those 16 prototype models by different methodologies including SIS, object-based and MPFS algorithms accompany with different constraint parameters. Modeling accuracy ratio was defined to quantify the influence of each factor, and ten realizations were averaged to represent each accuracy ratio under the same modeling condition and parameters association. Totally 5760 simulations were done to quantify the relative contribution of each factor to the simulation accuracy, and the results can be used as strategy guide for facies modeling in the similar condition. It is founded that data density, geological trend and geological complexity have great impact on modeling accuracy. Modeling accuracy may up to 90% when channel sand width reaches up to 1.5 times of well space under whatever condition by SIS and MPFS methods. When well density is low, the contribution of geological trend may increase the modeling accuracy from 40% to 70%, while the use of proper variogram may have very limited contribution for SIS method. It can be implied that when well data are dense enough to cover simple geobodies, few efforts were needed to construct an acceptable model, when geobodies are complex with insufficient data group, it is better to construct a set of robust geological trend than rely on a reliable variogram function. For object-based method, the modeling accuracy does not increase obviously as SIS method by the increase of data density, but kept rational appearance when data density is low. MPFS methods have the similar trend with SIS method, but the use of proper geological trend accompany with rational variogram may have better modeling accuracy than MPFS method. It implies that the geological modeling strategy for a real reservoir case needs to be optimized by evaluation of dataset, geological complexity, geological constraint information and the modeling objective.

Keywords: fluvial facies, geostatistics, geological trend, modeling strategy, modeling accuracy, variogram

Procedia PDF Downloads 257