Search results for: ecological planning method

Authors: Chariya Laohavich, Viboon Bunsrangsuk

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Objective: Bronchoscopy is a common outpatient procedure. The authors compared the patient anxiety level before and after received video-assisted procedural information. Method: One hundred and twenty patients who never received bronchoscopy and scheduled for elective bronchoscopy at outpatient Bronchosope unit at Ramathibodi Hospital, Mahidol University were randomized into control and intervention group. Video-assisted procedural information was given in intervention group. Pre and post procedural anxiety score were recorded and compared between two groups. Paired T-test was used for statistical analysis. Result: There was statistically significant decrease (p < 0.001) for anxiety score in patients who received video assisted procedural information compare with control group. Conclusion: Video-assisted procedural information should be given to patient who will have bronchoscopy to reduce anxiety.

Keywords: anxiety, bronchoscopy, video compact disc (VCD)

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Authors: Sirus Sharifi, Arunima Haldar, S. V. D. Nageswara Rao

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This research analyzes the effect of credit risk management practices of commercial banks in India and the relationship with their non-performing assets (NPAs). Required data on credit risk performance was collected through a survey questionnaire from top risk officers of 38 Indian banks. NPA data (period from 2012 to 2016) was collected from Prowess database compiled by the Centre for Monitoring Indian Economy (CMIE). The model was assessed utilizing cross sectional regression method. As expected, the results indicate a negative significant relationship between credit risk management in India banks and their NPA growth. The research has implications for banks given the high level of losses in India and other economies as well, and the implementation of Basel III standards by the central banks. This research would be an evidence on credit risk performance and its relationship with the level of non-performing assets (NPAs) in Indian banks.

Keywords: risk management, risk identification, banks, Non-Performing Assets (NPAs)

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Authors: Nkongho Ayuketang Arreyndip, Ebobenow Joseph

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In this paper, temperature extremes are forecast by employing the block maxima method of the generalized extreme value (GEV) distribution to analyse temperature data from the Cameroon Development Corporation (CDC). By considering two sets of data (raw data and simulated data) and two (stationary and non-stationary) models of the GEV distribution, return levels analysis is carried out and it was found that in the stationary model, the return values are constant over time with the raw data, while in the simulated data the return values show an increasing trend with an upper bound. In the non-stationary model, the return levels of both the raw data and simulated data show an increasing trend with an upper bound. This clearly shows that although temperatures in the tropics show a sign of increase in the future, there is a maximum temperature at which there is no exceedance. The results of this paper are very vital in agricultural and environmental research.

Keywords: forecasting, generalized extreme value (GEV), meteorology, return level

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Authors: Mohammad Ayobi

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Afghans have been immigrating to Iran for many years; The re-establishment of the Taliban in Afghanistan caused a flood of Afghan immigrants to Iran. One of the important issues related to the arrival of Afghan immigrants is the view that Afghan immigrants have toward Iranians. In this research, we seek to identify the schema of Afghan immigrants living in Iran about Iranians. A schema is a set of data or generalized knowledge that is formed in connection with a particular group or a particular person, or even a particular nationality to identify a person with pre-determined judgments about certain matters. The schemata between certain nationalities have a direct impact on the formation of interactions between them and can be effective in establishing or not establishing proper communication between the Afghan immigrant nationality and Iranians. For the scientific understanding of research, we use the theory of “schemata.” The method of this study is qualitative, and its data will be collected through semi-structured deep interviews, and data will be analyzed by thematic analysis. The expected findings in this study are that the schemata of Afghan immigrants are more negative than Iranians because Iranians are self-centered and fanatical about Afghans, and Afghans are only workers to them.

Keywords: schema study, Afghan immigrants, Iranians, in-depth interview

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Authors: Joseph Christopher R. Ragasa, Paolo Gabriel P. Casas, Nemesio S. Mangila, Maria Emma C. Villamin, Myra G. Bungag

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A procedure in measuring the thermal protrusion profiles of magnetic recording heads was developed using a Wyko HD-8100 optical interference-based instrument. The protrusions in the heads were made by the application of a constant power through the thermal flying height controller pads. It was found that the thermally-induced bubble is confined to form in the same head locations, primarily in the reader and writer regions, regardless of the direction of approach of temperature. An application of power to the thermal flying height control pads ranging from 0 to 50 milliWatts showed that the protrusions demonstrate a linear dependence with the supplied power. The efficiencies calculated using this method were compared to that obtained through Guzik and found to be 19.57% greater due to the static testing environment used in the testing.

Keywords: thermal protrusion profile, magnetic recording heads, wyko interferometry, thermal flying height control

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Authors: Frederik Calsius, Mirela Popa, Alexia Briassouli

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In the field of machine learning, it is common practice to use benchmark datasets to prove the working of a method. The domain of action recognition in videos often uses datasets like Kinet-ics, Something-Something, UCF-101 and HMDB-51 to report results. Considering the properties of the datasets, there are no datasets that focus solely on very short clips (2 to 3 seconds), and on highly-similar fine-grained actions within one specific domain. This paper researches how current state-of-the-art action recognition methods perform on a dataset that consists of highly similar, fine-grained actions. To do so, a dataset of skateboarding tricks was created. The performed analysis highlights both benefits and limitations of state-of-the-art methods, while proposing future research directions in the activity recognition domain. The conducted research shows that the best results are obtained by fusing RGB data with OpenPose data for the Temporal Shift Module.

Keywords: activity recognition, fused deep representations, fine-grained dataset, temporal modeling

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Authors: Mingbao Chen, Mingli Zhao

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The coastal zone is the intersection of land and sea system, and also is the connecting zone of the two economic systems of land and sea. In the world, all countries attach great importance to the coastal zone management and the coastal zone economy. In China, the government has developed a number of related coastal management policies and institutional, such as marine functional zoning, main function zoning, integrated coastal zone management, to ensure the sustainable utilization of the coastal zone and promote the development of coastal economic. However, in practice, the effect is not satisfactory. This paper analyses the coastal areas of coastal zone management on coastal economic growth contribution based on coastal areas economic development data with the 2007-2015 in China, which uses the method of the evaluation index system of coastal zone management institutional efficiency. The results show that the coastal zone management institutional objectives are not clear, and the institutional has high repeatability. At the same time, over management of coastal zone leads to low economic efficiency because the government management boundary is blurred.

Keywords: institutional overlap, over management, coastal zone management, coastal zone economy

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Authors: M. Firoz Kalam, Wilfried Schuetz, Jan Hendrik Bredehoeft

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Thiophene sulfur compounds' removal from diesel oil by batch adsorption process using commercial powdered activated carbon was designed and optimized in two-level factorial design method. This design analysis was used to find out the effects of operating parameters directing the adsorption process, such as amount of adsorbent, temperature and stirring time. The desulfurization efficiency was considered the response or output variable. Results showed that the stirring time had the largest effects on sulfur removal efficiency as compared with other operating parameters and their interactions under the experimental ranges studied. A regression model was generated to observe the closeness between predicted and experimental values. The three-dimensional plots and contour plots of main factors were generated according to the regression results to observe the optimal points.

Keywords: activated carbon, adsorptive desulfurization, factorial design, process optimization

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Authors: Sunitha Sampathi, Pankaj Kumar Tiriya, Sonia Gera, Sravanthi Reddy Pailla, V. Likhitha, A. J. Maruthi

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Surgical site infections (SSIs) are the most common nosocomial infections localized at the incision site. With an estimated 27 million surgical procedures each year in USA, approximately 2-5% rate of SSIs are predicted to occur annually. SSIs are treated with antibiotic medication. Current trend suggest that the direct drug delivery from the suture to the scared tissue can improve patient comfort and wound recovery. For that reason coating the surface of the medical device such as suture and catguts with broad spectrum antibiotics can prevent the formation of bactierial colonies with out comprimising the mechanical properties of the sutures.Hence, the present study was aimed to develop and evaluate a surgical suture coated with an antibiotic Ciprofloxacin hydrochloride loaded on gold nanoparticles. Gold nanoparticles were synthesized by chemical reduction method and conjugated with ciprofloxacin using Polyvinylpyrolidone as stabilizer and gold as carrier. Ciprofloxacin conjugated gold nanoparticles were coated over an absorbable surgical suture made of Polyglactan using sodium alginate as an immobilising agent by slurry dipping technique. The average particle size and Polydispersity Index of drug conjugated gold NPs were found to be 129±2.35 nm and 0.243±0.36 respectively. Gold nanoparticles are characterized by UV-Vis absorption spectroscopy, Fourier Transform Infrared Spectroscopy (FT-IR), Scanning electron microscopy and Transmission electron microscopy. FT-IR revealed that there is no chemical interaction between drug and polymer. Antimicrobial activity for coated sutures was evaluated by disc diffusion method on culture plates of both gram negative (E-coli) and gram positive bacteria (Staphylococcus aureus) and results found to be satisfactory. In vivo studies for coated sutures was performed on Swiss albino mice and histological evaluation of intestinal wound healing parameters such as wound edges in mucosa, muscularis, presence of necrosis, exudates, granulation tissue, granulocytes, macrophages, restoration, and repair of mucosal epithelium and muscularis propria on day 7 after surgery were studied. The control animal group, sutured with plain suture (uncoated suture) showed signs of restoration and repair, but presence of necrosis, heamorraghic infiltration and granulation tissue was still noticed. Whereas the animal group treated with ciprofloxacin and ciprofloxacin gold nanoparticle coated sutures has shown promising decrease in terms of haemorraghic infiltration, granulation tissue, necrosis and better repaired muscularis layers on comparision with plain coated sutures indicating faster rate of repair and less chance of sepsis. Hence coating of sutures with broad spectrum antibiotics can be an alternate technique to reduce SSIs.

Keywords: ciprofloxacin hydrochloride, gold nanoparticles, surgical site infections, sutures

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Authors: Adrian Sauer, Lorenz Einberger, Florian Hilpert

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The advancements and technical innovations in the field of electric unmanned aviation over the past years opened the third dimension in areas like surveillance, logistics, and mobility for a wide range of private and commercial users. Researchers and companies are faced with the task of integrating their technology into airborne platforms. Especially start-ups and researchers require unmanned aerial vehicles (UAV), which can be quickly developed for specific use cases without spending significant time and money. This paper shows a design approach for the rapid development of a lightweight automatic separate-lift-thrust (SLT) electric vertical take-off and landing (eVTOL) UAV prototype, which is able to fulfill basic transportation as well as surveillance missions. The design approach does not require expensive or time-consuming design loop software. Thereby developers can easily understand, adapt, and adjust the presented method for their own project. The approach is mainly focused on crucial design aspects such as aerofoil, tuning, and powertrain.

Keywords: aerofoil, drones, rapid prototyping, powertrain

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Authors: Sina Abadzadesahraei, Stephen Déry, John Rex

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Climate research has repeatedly identified strong associations between anthropogenic emissions of ‘greenhouses gases’ and observed increases of global mean surface air temperature over the past century. Studies have also demonstrated that the degree of warming varies regionally. Canada is not exempt from this situation, and evidence is mounting that climate change is beginning to cause diverse impacts in both environmental and socio-economic spheres of interest. For example, northeastern British Columbia (BC), whose climate is controlled by a combination of maritime, continental and arctic influences, is warming at a greater rate than the remainder of the province. There are indications that these changing conditions are already leading to shifting patterns in the region’s hydrological cycle, and thus its available water resources. Coincident with these changes, northeastern BC is undergoing rapid development for oil and gas extraction: This depends largely on subsurface hydraulic fracturing (‘fracking’), which uses enormous amounts of freshwater. While this industrial activity has made substantial contributions to regional and provincial economies, it is important to ensure that sufficient and sustainable water supplies are available for all those dependent on the resource, including ecological systems. In this turn demands a comprehensive understanding of how water in all its forms interacts with landscapes, the atmosphere, and of the potential impacts of changing climatic conditions on these processes. The aim of this study is therefore to characterize and quantify all components of the water budget in the small watershed of Coles Lake (141.8 km², 100 km north of Fort Nelson, BC), through a combination of field observations and numerical modelling. Baseline information will aid the assessment of the sustainability of current and future plans for freshwater extraction by the oil and gas industry, and will help to maintain the precarious balance between economic and environmental well-being. This project is a perfect example of interdisciplinary research, in that it not only examines the hydrology of the region but also investigates how natural gas operations and growth can affect water resources. Therefore, a fruitful collaboration between academia, government and industry has been established to fulfill the objectives of this research in a meaningful manner. This project aims to provide numerous benefits to BC communities. Further, the outcome and detailed information of this research can be a huge asset to researchers examining the effect of climate change on water resources worldwide.

Keywords: northeastern British Columbia, water resources, climate change, oil and gas extraction

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Authors: Rushi Naaz, Diksha Suchdeva

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Background: Temperament is a very important aspect of functioning that needs to be understood in children of patients suffering from schizophrenia. The children of parents with mental disorder have substantially increased risk of psychiatric illness in them and may exhibit a range of problems from minor variations in temperament and adjustment to manifest psychiatric disorder. Method: A case control study was conducted to study the temperament characteristics and psychopathology in children of patients suffering from schizophrenia as compared to those of healthy controls. Both the groups were evaluated on Temperament Measurement Schedule and Childhood Psychopathology Measurement Schedule. Results: The results showed that children of patients suffering from schizophrenia were withdrawing, less adaptable, less sociable and had lower activity level than children of healthy parents. However, on the measure of psychopathology, no significant difference was found. Conclusion: Since temperament can be identified at an early age, children at risk for the disorder later on could be identified early enough for possible primary intervention.

Keywords: children, childhood psychopathology, parental psychopathology, psychiatric disorders, schizophrenia, temperament

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Authors: Burçe Boyraz

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This study examines appearances of brand placement as an alternative communication strategy in television series by focusing on Yalan Dünya which is one of the most popular television series in Turkey. Consequently, this study has a descriptive research design and quantitative content analysis method is used in order to analyze frequency and time data of brand placement appearances in first 3 seasons of Yalan Dünya with 16 episodes. Analysis of brand placement practices in Yalan Dünya is dealt in three categories: episode-based analysis, season-based analysis and comparative analysis. At the end, brand placement practices in Yalan Dünya are evaluated in terms of type, form, duration and legal arrangements. As a result of this study, it is seen that brand placement plays a determinant role in Yalan Dünya content. Also, current legal arrangements make brand placement closer to other traditional communication strategies instead of differing brand placement from them distinctly.

Keywords: advertising, alternative communication strategy, brand placement, Yalan Dünya

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Authors: Zdeněk Veselý, Milan Honner, Jiří Mach

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The aim of the performed work is to establish the 2D and 3D model of direct unsteady task of sample heat treatment by moving source employing computer model on the basis of finite element method. The complex boundary condition on heat loaded sample surface is the essential feature of the task. Computer model describes heat treatment of the sample during heat source movement over the sample surface. It is started from the 2D task of sample cross section as a basic model. Possibilities of extension from 2D to 3D task are discussed. The effect of the addition of third model dimension on the temperature distribution in the sample is showed. Comparison of various model parameters on the sample temperatures is observed. Influence of heat source motion on the depth of material heat treatment is shown for several velocities of the movement. Presented computer model is prepared for the utilization in laser treatment of machine parts.

Keywords: computer simulation, unsteady model, heat treatment, complex boundary condition, moving heat source

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Authors: Lamia L. G. Al-Mahamad, Benjamin R. Horrocks, Andrew Houlton

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Hydrogels based on metal coordination polymers of nucleosides and a range of metal ions (Au, Ag, Cu) have been prepared and characterized by atomic force microscopy (AFM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, ultraviolet-visible absorption spectroscopy, and powder X-ray diffraction. AFM images of the xerogels revealed the formation of extremely long polymer molecules (> 10 micrometers, the maximum scan range). This result is also consistent with TEM images which show a fibrous morphology. Oxidative doping of the Au-nucleoside fibres produces an electrically conductive nanowire. No sharp Bragg peaks were found at the at the X-ray diffraction pattern for metal ions hydrogels indicating that the samples were amorphous, but instead the data showed broad peaks in the range 20 < Q < 40 and correspond to distances d=2μ/Q. The data was analysed using a simplified Rietveld method by fitting a regression model to obtain the distance between atoms.

Keywords: hydrogel, metal ions, nanowire, nucleoside

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Authors: Zhi Huang

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This study follows on from previous survey and focus group research exploring the effective teaching process in a translation classroom in Australian universities through case study method. The data analysis draws on social constructivist theory in translation teaching and focuses on teaching process aiming to discover how effective translation teachers conduct teaching in the classroom. The results suggest that effective teaching requires the teacher to have ability in four aspects: classroom management, classroom pedagogy, classroom communication, and teacher roles. Effective translation teachers are able to control the whole learning process, facilitate students in independent learning, guide students to be more critical about translation, giving both positive and negative feedback for students to reflect on their own, and being supportive, patient and encouraging to students for better classroom communication and learning outcomes. This study can be applied to other teachers in translation so that they can reflect on their own teaching in their education contexts and strive for being a more qualified translation teacher and achieving teaching effectiveness.

Keywords: case study, classroom observation, classroom teaching, effective translation teaching, teacher effectiveness

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Authors: Yang Cui, Yong Qiang Chen

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An appropriate project delivery system (PDS) is crucial to the success of a construction project. Case-based reasoning (CBR) is a useful support for PDS selection. However, the traditional CBR approach represents cases as attribute-value vectors without taking relations among attributes into consideration, and could not calculate the similarity when the structures of cases are not strictly same. Therefore, this paper solves this problem by adopting the relational case-based reasoning (RCBR) approach for PDS selection, considering both the structural similarity and feature similarity. To develop the feature terms of the construction projects, the criteria and factors governing PDS selection process are first identified. Then, feature terms for the construction projects are developed. Finally, the mechanism of similarity calculation and a case study indicate how RCBR works for PDS selection. The adoption of RCBR in PDS selection expands the scope of application of traditional CBR method and improves the accuracy of the PDS selection system.

Keywords: relational cased-based reasoning, case-based reasoning, project delivery system, PDS selection

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Authors: Mahdi Sadeghian, Mahmoud Hassanlourad, Alireza Ardakani, Reza Dinarvand

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In this research, the behavior of monopiles, under lateral loads, was investigated with vertical and oblique piles by Finite Element Method. In engineering practice when soil-pile interaction comes to the picture some simplifications are applied to reduce the design time. As a simplified replacement of soil and pile interaction analysis, pile could be replaced by a column. The height of the column would be equal to the free length of the pile plus a portion of the embedded length of it. One of the important factors studied in this study was that columns with an equivalent length (free length plus a part of buried depth) could be used instead of soil and pile modeling. The results of the analysis show that the more internal friction angle of the soil increases, the more the bearing capacity of the soil is achieved. This additional length is 6 to 11 times of the pile diameter in dense soil although in loose sandy soil this range might increase.

Keywords: Depth of fixity, Lateral bearing capacity, Oblique pile, Pile group, Soil-structure interaction

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Authors: I. M. L. Nadeesha Jayaweera, Adao Alex Trindade

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In choosing a candidate model in likelihood-based modeling via an information criterion, the practitioner is often faced with the difficult task of deciding just how far up the ranked list to look. Motivated by this pragmatic necessity, we construct an uncertainty band for a generalized (model selection) information criterion (GIC), defined as a criterion for which the limit in probability is identical to that of the normalized log-likelihood. This includes common special cases such as AIC & BIC. The method starts from the asymptotic normality of the GIC for the joint distribution of the candidate models in an independent and identically distributed (IID) data framework and proceeds by deriving the (asymptotically) exact distribution of the minimum. The calculation of an upper quantile for its distribution then involves the computation of multivariate Gaussian integrals, which is amenable to efficient implementation via the R package "mvtnorm". The performance of the methodology is tested on simulated data by checking the coverage probability of nominal upper quantiles and compared to the bootstrap. Both methods give coverages close to nominal for large samples, but the bootstrap is two orders of magnitude slower. The methodology is subsequently extended to two other commonly used model structures: regression and time series. In the regression case, we derive the corresponding asymptotically exact distribution of the minimum GIC invoking Lindeberg-Feller type conditions for triangular arrays and are thus able to similarly calculate upper quantiles for its distribution via multivariate Gaussian integration. The bootstrap once again provides a default competing procedure, and we find that similar comparison performance metrics hold as for the IID case. The time series case is complicated by far more intricate asymptotic regime for the joint distribution of the model GIC statistics. Under a Gaussian likelihood, the default in most packages, one needs to derive the limiting distribution of a normalized quadratic form for a realization from a stationary series. Under conditions on the process satisfied by ARMA models, a multivariate normal limit is once again achieved. The bootstrap can, however, be employed for its computation, whence we are once again in the multivariate Gaussian integration paradigm for upper quantile evaluation. Comparisons of this bootstrap-aided semi-exact method with the full-blown bootstrap once again reveal a similar performance but faster computation speeds. One of the most difficult problems in contemporary statistical methodological research is to be able to account for the extra variability introduced by model selection uncertainty, the so-called post-model selection inference (PMSI). We explore ways in which the GIC uncertainty band can be inverted to make inferences on the parameters. This is being attempted in the IID case by pivoting the CDF of the asymptotically exact distribution of the minimum GIC. For inference one parameter at a time and a small number of candidate models, this works well, whence the attained PMSI confidence intervals are wider than the MLE-based Wald, as expected.

Keywords: model selection inference, generalized information criteria, post model selection, Asymptotic Theory

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Authors: A. T. Kuda, J. J. Dayya, A. Jimoh

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This paper investigates the fault detection and Isolation technique of measurement data sets from a three tank system using analytical model-based temporal redundancy which is based on residual generation using parity equations/space approach. It further briefly outlines other approaches of model-based residual generation. The basic idea of parity space residual generation in temporal redundancy is dynamic relationship between sensor outputs and actuator inputs (input-output model). These residuals where then used to detect whether or not the system is faulty and indicate the location of the fault when it is faulty. The method obtains good results by detecting and isolating faults from the considered data sets measurements generated from the system.

Keywords: fault detection, fault isolation, disturbing influences, system failure, parity equation/relation, structured parity equations

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Authors: Ainul Haque, Ameeye Kumar Nayak

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Flow enhancement and species transport in a slit hydrophobic microchannel is studied for non-Newtonian fluids with the externally imposed electric field and pressure gradient. The incompressible Poisson-Nernst-Plank equations and the Navier-Stokes equations are approximated by lubrication theory to quantify the flow structure due to hydrophobic and hydrophilic surfaces. The analytical quantification of velocity and pressure of electroosmotic flow (EOF) is made with the numerical results due to the staggered grid based finite volume method for flow governing equations. The resistance force due to fluid friction and shear force along the surface are decreased by the hydrophobicity, enables the faster movement of fluid particles. The resulting flow enhancement factor Ef is increased with the low viscous fluid and provides maximum species transport. Also, the analytical comparison of EOF with pressure driven EOF justifies the flow enhancement due to hydrophobicity and shear impact on flow variation.

Keywords: electroosmotic flow, hydrophobic surface, power-law fluid, shear effect

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Authors: Thinh Ngo, Paul Rad, Brian Kelley

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Noise estimation is essential in today wireless systems for power control, adaptive modulation, interference suppression and quality of service. Deep learning (DL) has already been applied in the physical layer for modulation and signal classifications. Unacceptably low accuracy of less than 50% is found to undermine traditional application of DL classification for SNR prediction. In this paper, we use divide-and-conquer algorithm and classifier fusion method to simplify SNR classification and therefore enhances DL learning and prediction. Specifically, multiple CNNs are used for classification rather than a single CNN. Each CNN performs a binary classification of a single SNR with two labels: less than, greater than or equal. Together, multiple CNNs are combined to effectively classify over a range of SNR values from −20 ≤ SNR ≤ 32 dB.We use pre-trained CNNs to predict SNR over a wide range of joint channel parameters including multiple Doppler shifts (0, 60, 120 Hz), power-delay profiles, and signal-modulation types (QPSK,16QAM,64-QAM). The approach achieves individual SNR prediction accuracy of 92%, composite accuracy of 70% and prediction convergence one order of magnitude faster than that of traditional estimation.

Keywords: classification, CNN, deep learning, prediction, SNR

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Authors: Béchir Wanassi, Béchir Azzouz, Taher Halimi, Mohamed Ben Hassen

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Mechanical recycling of post-industrial cotton yarn wastes, as well as the effects of passage number on the properties of reclaimed fibers, have been investigated. A new Modified Fiber Quality Index (MFQI) and Spinning Consistency Index (MSCI) for the characterization of the quality are presented. This index gives the real potential of spinnability according to its physical properties. The best quality of reclaimed fibers (after 7th passage) was used to produce rotor yarns. 100% recycling cotton yarns were produced in open-end spinning system with different rotor speed (i.e. 65000, 70000, and 80000 rpm), opening roller speed (i.e. 7700, 8200, and 8700 rpm) and twist factor (i.e. 137, 165, and 183). The effects of spinning parameters were investigated to evaluate a 100% recycling cotton yarns quality (TQI, hairiness, thin places, and thick places) using DOE method.

Keywords: cotton wastes, DOE, mechanical recycling, rotor spinning

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Authors: Samah Laalej, Abdelfattah Bouatem

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In the field of wind turbine blades, it is complicated to evaluate the aerodynamic performances through experimental measurements as it requires a lot of computing time and resources. Therefore, in this paper, a hybrid BEM-CFD numerical technique is developed to predict power and aerodynamic forces acting on the blades. Computational fluid dynamics (CFD) simulation was conducted to calculate the drag and lift forces through Ansys software using the K-w model. Then an enhanced BEM code was created to predict the power outputs generated by the wind turbine using the aerodynamic properties extracted from the CFD approach. The numerical approach was compared and validated with experimental data. The power curves calculated from this hybrid method were in good agreement with experimental measurements for all velocity ranges.

Keywords: blade element momentum, aerodynamic forces, wind turbine blades, computational fluid dynamics approach

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Authors: Ajit Rai, Hamza Deroui, Blandine Vacher, Khwansiri Ninpan, Arthur Aumont, Francesco Vitillo, Robert Plana

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Large-scale critical industrial scheduling problems are based on Resource-Constrained Project Scheduling Problems (RCPSP), that necessitate integration with other optimization problems (e.g., vehicle routing, supply chain, or unique industrial ones), thus requiring practical solutions (i.e., modular, computationally efficient with feasible solutions). To the best of our knowledge, the current industrial state of the art is not addressing this holistic problem. We propose an original modular solution that answers the issues exhibited by the delivery of complex projects. With three interlinked entities (project, task, resources) having their constraints, it uses a greedy heuristic with a dynamic cost function for each task with a situational assessment at each time step. It handles large-scale data and can be easily integrated with other optimization problems, already existing industrial tools and unique constraints as required by the use case. The solution has been tested and validated by domain experts on three use cases: outage management in Nuclear Power Plants (NPPs), planning of future NPP maintenance operation, and application in the defense industry on supply chain and factory relocation. In the first use case, the solution, in addition to the resources’ availability and tasks’ logical relationships, also integrates several project-specific constraints for outage management, like, handling of resource incompatibility, updating of tasks priorities, pausing tasks in a specific circumstance, and adjusting dynamic unit of resources. With more than 20,000 tasks and multiple constraints, the solution provides a feasible schedule within 10-15 minutes on a standard computer device. This time-effective simulation corresponds with the nature of the problem and requirements of several scenarios (30-40 simulations) before finalizing the schedules. The second use case is a factory relocation project where production lines must be moved to a new site while ensuring the continuity of their production. This generates the challenge of merging job shop scheduling and the RCPSP with location constraints. Our solution allows the automation of the production tasks while considering the rate expectation. The simulation algorithm manages the use and movement of resources and products to respect a given relocation scenario. The last use case establishes a future maintenance operation in an NPP. The project contains complex and hard constraints, like on Finish-Start precedence relationship (i.e., successor tasks have to start immediately after predecessors while respecting all constraints), shareable coactivity for managing workspaces, and requirements of a specific state of "cyclic" resources (they can have multiple states possible with only one at a time) to perform tasks (can require unique combinations of several cyclic resources). Our solution satisfies the requirement of minimization of the state changes of cyclic resources coupled with the makespan minimization. It offers a solution of 80 cyclic resources with 50 incompatibilities between levels in less than a minute. Conclusively, we propose a fast and feasible modular approach to various industrial scheduling problems that were validated by domain experts and compatible with existing industrial tools. This approach can be further enhanced by the use of machine learning techniques on historically repeated tasks to gain further insights for delay risk mitigation measures.

Keywords: deterministic scheduling, optimization coupling, modular scheduling, RCPSP

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Authors: Musthaya Patchanee

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The study of Sanitary landfill in Bang Nok-khwaek municipality consists of two procedures. First, to survey and create the spatial database by using physical factor, environmental factor, economical factor and social factor to follow the method of Geographic information system: GIS, second, to analyze the proper spatial for allocating the sanitary landfill in Bang Nok-khwaek municipality by using Overlay techniques to calculate the weighting linear total in Arc GIS program. The study found that there are 2.49 sq.km. proper spatial for the sanitary landfill in Bang Nok-khwaek municipals city which is 66.76% of the whole area. The highest proper spatial is 0.02 sq.km. which is 0.54%, The high proper spatial is 0.3 sq.km. which is 8.04%, the moderate spatial is 1.62 sq.km. which is 43.43% and the low proper spatial is 0.55 sq.km. which is 14.75%. These results will be used as the guideline to select the sanitary landfill area in accordance with sanitation standard for Subdistrict Administrative Organization and Subbdistrict Municipality in Samut Songkhram provice.

Keywords: Geographic Information System (GIS), sanitary landfill, Bang Nok-Khwaek municipality, Subdistrict Administrative Organization

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Authors: Wen Liu

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With the rapid progress of modern cities, the railway construction must be developing quickly in China. As a typical high-density country, shopping center on the subway should be one important factor during the process of urban development. The paper discusses the influence of the layout of shopping center on the subway, and put it in the time and space’s axis of Shanghai urban development. We use the digital technology to establish the database of relevant information. And then get the change role about shopping center on subway in Shanghaiby the Kernel density estimate. The result shows the development of shopping center on subway has a relationship with local economic strength, population size, policy support, and city construction. And the suburbanization trend of shopping center would be increasingly significant. By this case research, we could see the Kernel density estimate is an efficient analysis method on the spatial layout. It could reveal the characters of layout form of shopping center on subway in essence. And it can also be applied to the other research of space form.

Keywords: Shanghai, shopping center on the subway, layout form, Kernel density estimate

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Authors: Yusuf U. Datti

Abstract:

It is becoming increasingly clear that the consumption of resources now enjoyed in the developed nations will be impossible to be sustained worldwide. While developing countries still have the advantage of low consumption and a smaller ecological footprint per person, they cannot simply develop in the same way as other western cities have developed in the past. The severe reality of population and consumption inequalities makes it contentious whether studies done in developed countries can be translated and applied to developing countries. Additional to this disparities, there are few or no metabolism of energy studies in Nigeria. Rather more contentious majority of energy metabolism studies have been done only in developed countries. While researches in Nigeria concentrate on other aspects/principles of sustainability such as water supply, sewage disposal, energy supply, energy efficiency, waste disposal, etc., which will not accurately capture the environmental impact of energy flow in Nigeria, this research will set itself apart by examining the flow of energy in Nigeria and the impact that the flow will have on the environment. The aim of the study is to examine and quantify the metabolic flows of energy in Nigeria and its corresponding environmental impact. The study will quantify the level and pattern of energy inflow and the outflow of greenhouse emissions in Nigeria. This study will describe measures to address the impact of existing energy sources and suggest alternative renewable energy sources in Nigeria that will lower the emission of greenhouse gas emissions. This study will investigate the metabolism of energy in Nigeria through a three-part methodology. The first step involved selecting and defining the study area and some variables that would affect the output of the energy (time of the year, stability of the country, income level, literacy rate and population). The second step involves analyzing, categorizing and quantifying the amount of energy generated by the various energy sources in the country. The third step involves analyzing what effect the variables would have on the environment. To ensure a representative sample of the study area, Africa’s most populous country, with economy that is the second biggest and that is among the top largest oil producing countries in the world is selected. This is due to the understanding that countries with large economy and dense populations are ideal places to examine sustainability strategies; hence, the choice of Nigeria for the study. National data will be utilized unless where such data cannot be found, then local data will be employed which will be aggregated to reflect the national situation. The outcome of the study will help policy-makers better target energy conservation and efficiency programs and enables early identification and mitigation of any negative effects in the environment.

Keywords: built environment, energy metabolism, environmental impact, greenhouse gas emissions and sustainability

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Authors: Felix Schumann, Giorgia Carratta, Tobias Dauth, Liv Jaeckel

Abstract:

In the last few decades, the rapid growth of the use and disposal of plastic items has led to their overaccumulation in the environment. As a result, plastic pollution has become a subject of global concern. Today plastics are used as raw materials in almost every industry. While the recognition of the ecological, social, and economic impact of plastics in academic research is on the rise, the potential role of the ‘plastic industry’ in dealing with such issues is still largely underestimated. Therefore, the literature on sustainable plastic management is still nascent and fragmented. Working towards sustainability requires a fundamental shift in the way companies employ plastics in their day-to-day business. For that reason, the applicability of the business model concept has recently gained momentum in environmental research. Business model innovation is increasingly recognized as an important driver to re-conceptualize the purpose of the firm and to readily integrate sustainability in their business. It can serve as a starting point to investigate whether and how sustainability can be realized under industry- and firm-specific circumstances. Yet, there is no comprehensive view in the plastic industry on how firms start refining their business models to embed sustainability in their operations. Our study addresses this gap, looking primarily at the industrial sectors responsible for the production of the largest amount of plastic waste today: plastic packaging, consumer goods, construction, textile, and transport. Relying on the archetypes of sustainable business models and applying them to the aforementioned sectors, we try to identify companies’ current strategies to make their business models more sustainable. Based on the thematic clustering, we can develop an integrative framework for the plastic industry. The findings are underpinned and illustrated by a variety of relevant plastic management solutions that the authors have identified through a systematic literature review and analysis of existing, empirically grounded research in this field. Using the archetypes, we can promote options for business model innovations for the most important sectors in which plastics are used. Moreover, by linking the proposed business model archetypes to the plastic industry, our research approach guides firms in exploring sustainable business opportunities. Likewise, researchers and policymakers can utilize our classification to identify best practices. The authors believe that the study advances the current knowledge on sustainable plastic management through its broad empirical industry analyses. Hence, the application of business model archetypes in the plastic industry will be useful for shaping companies’ transformation to create and deliver more sustainability and provides avenues for future research endeavors.

Keywords: business models, environmental economics, plastic management, plastic pollution, sustainability

Procedia PDF Downloads 80

Authors: Hsu-Yung Cheng, Kuo-Chang Hsu, Chi-Chang Chan, Mei-Hui Tseng, Chih-Chang Yu, Ya-Sheng Liu

Abstract:

Photovoltaics modules are usually not installed horizontally to avoid water or dust accumulation. However, the measured irradiance data on tilted surfaces are rarely available since installing pyranometers with various tilt angles induces high costs. Therefore, estimating solar irradiance on tilted surfaces is an important research topic. In this work, artificial neural networks (ANN) are utilized to construct the transfer model to estimate solar irradiance on tilted surfaces. Instead of predicting tilted irradiance directly, the proposed method estimates the differences between the horizontal irradiance and the irradiance on a tilted surface. The outputs of the ANNs in the proposed design are differential values. The experimental results have shown that the proposed ANNs with differential outputs can substantially improve the estimation accuracy compared to ANNs that estimate the titled irradiance directly.

Keywords: photovoltaics, artificial neural networks, tilted irradiance, solar energy

Procedia PDF Downloads 376