Search results for: cost performance

Authors: I. Domingos, B. Esteves, A. Figueirinha, Luísa P. Cruz-Lopes, J. Ferreira, H. Pereira

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Chromium is one of the most common heavy metals which exist in very high concentrations in wastewater. The removal is very expensive due to the high cost of normal adsorbents. Lignocellulosic materials and mainly treated materials have proven to be a good solution for this problem. Adsorption tests were performed at different pH, different times and with varying concentrations. Results show that is at pH 3 that treated wood absorbs more chromium ranging from 70% (2h treatment) to almost 100% (12 h treatment) much more than untreated wood with less than 40%. Most of the adsorption is made in the first 2-3 hours for untreated and heat treated wood. Modified wood adsorbs more chromium throughout the time. For all the samples, adsorption fitted relatively well the Langmuir model with correlation coefficient ranging from 0.85 to 0.97. The results show that heat treated wood is a good adsorbent ant that this might be a good utilization for sawdust from treating companies.

Keywords: adsorption, chromium, heat treatment, wood modification

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Authors: Pei-Jyun Hsieh, Cheng-Hsuan Li, Bor-Chen Kuo

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For hyperspectral image classification, feature reduction is an important pre-processing for avoiding the Hughes phenomena due to the difficulty for collecting training samples. Hence, lots of researches developed feature selection methods such as F-score, HSIC (Hilbert-Schmidt Independence Criterion), and etc., to improve hyperspectral image classification. However, most of them only consider the class separability in the original space, i.e., a linear class separability. In this study, we proposed a nonlinear class separability measure based on kernel trick for selecting an appropriate feature subset. The proposed nonlinear class separability was formed by a generalized RBF kernel with different bandwidths with respect to different features. Moreover, it considered the within-class separability and the between-class separability. A genetic algorithm was applied to tune these bandwidths such that the smallest with-class separability and the largest between-class separability simultaneously. This indicates the corresponding feature space is more suitable for classification. In addition, the corresponding nonlinear classification boundary can separate classes very well. These optimal bandwidths also show the importance of bands for hyperspectral image classification. The reciprocals of these bandwidths can be viewed as weights of bands. The smaller bandwidth, the larger weight of the band, and the more importance for classification. Hence, the descending order of the reciprocals of the bands gives an order for selecting the appropriate feature subsets. In the experiments, three hyperspectral image data sets, the Indian Pine Site data set, the PAVIA data set, and the Salinas A data set, were used to demonstrate the selected feature subsets by the proposed nonlinear feature selection method are more appropriate for hyperspectral image classification. Only ten percent of samples were randomly selected to form the training dataset. All non-background samples were used to form the testing dataset. The support vector machine was applied to classify these testing samples based on selected feature subsets. According to the experiments on the Indian Pine Site data set with 220 bands, the highest accuracies by applying the proposed method, F-score, and HSIC are 0.8795, 0.8795, and 0.87404, respectively. However, the proposed method selects 158 features. F-score and HSIC select 168 features and 217 features, respectively. Moreover, the classification accuracies increase dramatically only using first few features. The classification accuracies with respect to feature subsets of 10 features, 20 features, 50 features, and 110 features are 0.69587, 0.7348, 0.79217, and 0.84164, respectively. Furthermore, only using half selected features (110 features) of the proposed method, the corresponding classification accuracy (0.84168) is approximate to the highest classification accuracy, 0.8795. For other two hyperspectral image data sets, the PAVIA data set and Salinas A data set, we can obtain the similar results. These results illustrate our proposed method can efficiently find feature subsets to improve hyperspectral image classification. One can apply the proposed method to determine the suitable feature subset first according to specific purposes. Then researchers can only use the corresponding sensors to obtain the hyperspectral image and classify the samples. This can not only improve the classification performance but also reduce the cost for obtaining hyperspectral images.

Keywords: hyperspectral image classification, nonlinear feature selection, kernel trick, support vector machine

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Authors: Soam Prakash, Namita Soni

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The synthesis of metallic nanoparticles is an active area of academic and more significantly, applied research in nanotechnology. Currently, nanoparticle research is an area of intense scientific interest. Silver (Ag) and Gold (Au) nanoparticles (NPs) have been the focus of fungi and plant based syntheses. Silver and gold nanoparticles are nanoparticles of silver and gold. These particles are of between 1 nm and 100 nm in size. Silver and gold have been use in the wide variety of potential applications in biomedical, optical, electronic field, treatment of burns, wounds, and several bacterial infections. There is a crucial need to produce new insecticides due to resistance and high-cost of organic insecticides which are more environmentally-friendly, safe, and target-specific. Synthesizing nanoparticles using plants and microorganisms can eliminate this problem by making the nanoparticles more biocompatible. Here we reviewed the mosquitocidal and antimicrobials activity of silver and gold nanoparticles using fungi, plants as well as bacteria.

Keywords: nano gold, nano silver, Malaria, Chikengunia, dengue control

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Authors: K. Domagala, D. Kata, T. Graule

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Diseases caused by contaminated drinking water are the worldwide problem, which leads to the death and severe illnesses for hundreds of millions million people each year. There is an urgent need for efficient water treatment techniques for virus pathogens removal. The aim of the research was to develop safe and economic solution, which help with the water treatment. In this study, the synthesis of copper-based multi-walled carbon nanotube composites is described. Proposed solution utilize combination of a low-cost material with a high active surface area and copper antiviral properties. Removal of viruses from water was possible by adsorption based on electrostatic interactions of negatively charged virus with a positively charged filter material.

Keywords: multi walled carbon nanotubes, water purification, virus removal, water treatment

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Authors: Nagalingam Arun Prasanth, Ahmed Syed Adnan, S. H. Yeo

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Surface topography plays a significant role in the functional performance of engineered parts. It is important to have a control on the surface geometry and understanding on the surface details to get the desired performance. Hence, in the current research contribution, a non-contact micro-texturing technique has been explored and developed. The technique involves ultrasonic excitation of a tool as a prime source of surface texturing for aluminum alloy workpieces. The specimen surface is polished first and is then immersed in a liquid bath containing 10% weight concentration of Ti6Al4V grade 5 spherical powders. A submerged slurry jet is used to recirculate the spherical powders under the ultrasonic horn which is excited at an ultrasonic frequency and amplitude of 40 kHz and 70 µm respectively. The distance between the horn and workpiece surface was remained fixed at 200 µm using a precision control stage. Texturing effects were investigated for different process timings of 1, 3 and 5 s. Thereafter, the specimens were cleaned in an ultrasonic bath for 5 mins to remove loose debris on the surface. The developed surfaces are characterized by optical and contact surface profiler. The optical microscopic images show a texture of circular spots on the workpiece surface indented by titanium spherical balls. Waviness patterns obtained from contact surface profiler supports the texturing effect produced from the proposed technique. Furthermore, water droplet tests were performed to show the efficacy of the proposed technique to develop hydrophilic surfaces and to quantify the texturing effect produced.

Keywords: surface texturing, surface modification, topography, ultrasonic

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Authors: Belkacem Benadda, Adil Benabdellah, Boutheyna Souna

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The Internet of Things (IoT) is an unprecedented creation. Electronics objects are now able to interact, share, respond and adapt to their environment on a much larger basis. Actual spread of these modern means of connectivity and solutions with high data volume exchange are affecting our ways of life. Accommodation is becoming an intelligent living space, not only suited to the people circumstances and desires, but also to systems constraints to make daily life simpler, cheaper, increase possibilities and achieve a higher level of services and luxury. In this paper we are as Internet access, teleworking, consumption monitoring, information search, etc.). This paper addresses the design and integration of a smart home, it also purposes an IoT solution that allows smart power consumption based on measurements from power-grid and deep learning analysis.

Keywords: array sensors, IoT, power grid, FPGA, embedded

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Authors: Nicola Rubino

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This paper presents an analysis of a group of commodity exporting countries' nominal exchange rate movements in relationship to the US dollar. Using a series of Unrestricted Self-exciting Threshold Autoregressive models (SETAR), we model and evaluate sixteen national CPI price differentials relative to the US dollar CPI. Out-of-sample forecast accuracy is evaluated through calculation of mean absolute error measures on the basis of two-hundred and fifty-three months rolling window forecasts and extended to three additional models, namely a logistic smooth transition regression (LSTAR), an additive non linear autoregressive model (AAR) and a simple linear Neural Network model (NNET). Our preliminary results confirm presence of some form of TAR non linearity in the majority of the countries analyzed, with a relatively higher goodness of fit, with respect to the linear AR(1) benchmark, in five countries out of sixteen considered. Although no model appears to statistically prevail over the other, our final out-of-sample forecast exercise shows that SETAR models tend to have quite poor relative forecasting performance, especially when compared to alternative non-linear specifications. Finally, by analyzing the implied half-lives of the > coefficients, our results confirms the presence, in the spirit of arbitrage band adjustment, of band convergence with an inner unit root behaviour in five of the sixteen countries analyzed.

Keywords: transition regression model, real exchange rate, nonlinearities, price differentials, PPP, commodity points

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Authors: Ozlem Uguz, Ali Demirci, Hanzade Haykiri-Acma, Serdar Yaman

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Lignitic coal holds its position as Turkey’s most important indigenous energy source to generate energy in thermal power plants. Hence, efficient and environmental-friendly use of lignite in electricity generation is of great importance. Thus, clean coal technologies have been planned to mitigate emissions and provide more efficient burning in power plants. In this context, oxygen enriched combustion (oxy-combustion) is regarded as one of the clean coal technologies, which based on burning with oxygen concentrations higher than that in air. As it is known that the most of the Turkish coals are low rank with high mineral matter content, unburnt carbon trapped in ash is, unfortunately, high, and it leads significant losses in the overall efficiencies of the thermal plants. Besides, the necessity of burning huge amounts of these low calorific value lignites to get the desired amount of energy also results in the formation of large amounts of ash that is rich in unburnt carbon. Oxygen enriched combustion technology enables to increase the burning efficiency through the complete burning of almost all of the carbon content of the fuel. This also contributes to the protection of air quality and emission levels drop reasonably. The aim of this study is to investigate the unburnt carbon content and the burning reactivities of several different lignite samples under oxygen enriched conditions. For this reason, the combined effects of temperature and oxygen/nitrogen ratios in the burning atmosphere were investigated and interpreted. To do this, Turkish lignite samples from Adıyaman-Gölbaşı and Kütahya-Tunçbilek regions were characterized first by proximate and ultimate analyses and the burning profiles were derived using DTA (Differential Thermal Analysis) curves. Then, these lignites were subjected to slow burning process in a horizontal tube furnace at different temperatures (200ºC, 400ºC, 600ºC for Adıyaman-Gölbaşı lignite and 200ºC, 450ºC, 800ºC for Kütahya-Tunçbilek lignite) under atmospheres having O₂+N₂ proportions of 21%O₂+79%N₂, 30%O₂+70%N₂, 40%O₂+60%N₂, and 50%O₂+50%N₂. These burning temperatures were specified based on the burning profiles derived from the DTA curves. The residues obtained from these burning tests were also analyzed by proximate and ultimate analyses to detect the unburnt carbon content along with the unused energy potential. Reactivity of these lignites was calculated using several methodologies. Burning yield under air condition (21%O₂+79%N₂) was used a benchmark value to compare the effectiveness of oxygen enriched conditions. It was concluded that oxygen enriched combustion method enhanced the combustion efficiency and lowered the unburnt carbon content of ash. Combustion of low-rank coals under oxygen enriched conditions was found to be a promising way to improve the efficiency of the lignite-firing energy systems. However, cost-benefit analysis should be considered for a better justification of this method since the use of more oxygen brings an unignorable additional cost.

Keywords: coal, energy, oxygen enriched combustion, reactivity

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Authors: Muhammad Farid, Jen Der Day

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The purpose of this study is to explore the construct of service innovation model for Small and medium-sized enterprises (SMEs) in automotive service industries. A case study of repair shop of the motorcycle at Makassar city illustrates measure innovation implementation, the degree of innovation, and identifies the type of innovation by the service innovation model for SMEs. In this paper, we interview 10 managers of SMEs and analyze their answers. We find that innovation implementation has been slowly; only producing new service innovation 0.62 unit average per year. Incremental innovation is the present option for SMEs, because they choose safer roads to improve service continuously. If want to create radical innovation, they still consider the aspect of cost, system, and readiness of human resources.

Keywords: service innovation, incremental innovation, SMEs, automotive service industries

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Authors: Zhaoyang Liu, Detao Qin, Darren Delai Sun

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The onshore production of oil and gas (for example, shale gas) generates large quantities of wastewater, referred to be ‘produced water’, which contains high contents of oils and salts. The direct discharge of produced water, if not appropriately treated, can be toxic to the environment and human health. Membrane filtration has been deemed as an environmental-friendly and cost-effective technology for treating oily wastewater. However, conventional polymeric membranes have their drawbacks of either low salt rejection rate or high membrane fouling tendency when treating oily wastewater. Recent years, forward osmosis (FO) membrane filtration has emerged as a promising technology with its unique advantages of low operation pressure and less membrane fouling tendency. However, until now there is still no report about FO membranes specially designed and fabricated for treating the oily and salty produced water. In this study, a novel nanocomposite FO membrane was developed specially for treating oil- and salt-polluted produced water. By leveraging the recent advance of nanomaterials and nanotechnology, this nanocomposite FO membrane was designed to be made of double layers: an underwater oleophobic selective layer on top of a nanomaterial infused polymeric support layer. Wherein, graphene oxide (GO) nanosheets were selected to add into the polymeric support layer because adding GO nanosheets can optimize the pore structures of the support layer, thus potentially leading to high water flux for FO membranes. In addition, polyvinyl alcohol (PVA) hydrogel was selected as the selective layer because hydrated and chemically-crosslinked PVA hydrogel is capable of simultaneously rejecting oil and salt. After nanocomposite FO membranes were fabricated, the membrane structures were systematically characterized with the instruments of TEM, FESEM, XRD, ATR-FTIR, surface zeta-potential and Contact angles (CA). The membrane performances for treating produced waters were tested with the instruments of TOC, COD and Ion chromatography. The working mechanism of this new membrane was also analyzed. Very promising experimental results have been obtained. The incorporation of GO nanosheets can reduce internal concentration polarization (ICP) effect in the polymeric support layer. The structural parameter (S value) of the new FO membrane is reduced by 23% from 265 ± 31 μm to 205 ± 23 μm. The membrane tortuosity (τ value) is decreased by 20% from 2.55 ± 0.19 to 2.02 ± 0.13 μm, which contributes to the decrease of S value. Moreover, the highly-hydrophilic and chemically-cross-linked hydrogel selective layer present high antifouling property under saline oil/water emulsions. Compared with commercial FO membrane, this new FO membrane possesses three times higher water flux, higher removal efficiencies for oil (>99.9%) and salts (>99.7% for multivalent ions), and significantly lower membrane fouling tendency (<10%). To our knowledge, this is the first report of a nanocomposite FO membrane with the combined merits of high salt rejection, high oil repellency and high water flux for treating onshore oil/gas produced waters. Due to its outstanding performance and ease of fabrication, this novel nanocomposite FO membrane possesses great application potential in wastewater treatment industry.

Keywords: nanocomposite, membrane, polymer, graphene oxide

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Authors: P. S. Jain, K. D. Bobade, S. J. Surana

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A simple, selective, precise and Stability-indicating High-performance thin-layer chromatographic method for analysis of Naftopidil both in a bulk and in pharmaceutical formulation has been developed and validated. The method employed, HPTLC aluminium plates precoated with silica gel as the stationary phase. The solvent system consisted of hexane: ethyl acetate: glacial acetic acid (4:4:2 v/v). The system was found to give compact spot for Naftopidil (Rf value of 0.43±0.02). Densitometric analysis of Naftopidil was carried out in the absorbance mode at 253 nm. The linear regression analysis data for the calibration plots showed good linear relationship with r2=0.999±0.0001 with respect to peak area in the concentration range 200-1200 ng per spot. The method was validated for precision, recovery and robustness. The limits of detection and quantification were 20.35 and 61.68 ng per spot, respectively. Naftopidil was subjected to acid and alkali hydrolysis, oxidation and thermal degradation. The drug undergoes degradation under acidic, basic, oxidation and thermal conditions. This indicates that the drug is susceptible to acid, base, oxidation and thermal conditions. The degraded product was well resolved from the pure drug with significantly different Rf value. Statistical analysis proves that the method is repeatable, selective and accurate for the estimation of investigated drug. The proposed developed HPTLC method can be applied for identification and quantitative determination of Naftopidil in bulk drug and pharmaceutical formulation.

Keywords: naftopidil, HPTLC, validation, stability, degradation

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Authors: Vighnesh Daas, David B. Tann, Mahmood Datoo

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The incorporation of recycled plastic fibres in concrete as reinforcement is a potential sustainable alternative for replacement of ordinary steel bars. It provides a scope for waste reduction and re-use of plastics in the construction industry on a large scale. Structural use of fibre reinforced concrete is limited to short span members and low reliability classes. In this study, recycled carpet fibres made of 95% polypropylene with length of 45mm were used for experimental investigations. The performance of recycled polypropylene fibres under structural loading has been compared with commercially available virgin fibres at low volume fractions of less than 1%. A series of 100 mm cubes and 125x200x2000 mm beams were used to conduct strength tests in bending and compression to measure the influence of type and volume of fibres on the structural behaviour of fibre reinforced concrete beams. The workability of the concrete mix decreased as a function of fibre content and resulted in a modification of the mix design. The beams failed in a pseudo-ductile manner with an enhanced bending capacity. The specimens showed significant improvement in the post-cracking behaviour and load carrying ability as compared to conventional reinforced concrete members. This was associated to the binding properties of the fibres in the concrete matrix. With the inclusion of fibres at low volumes of 0-0.5%, there was reduction in crack sizes and deflection. This study indicates that the inclusion of recycled polypropylene fibres at low volumes augments the structural behaviour of concrete as compared to conventional reinforced concrete as well as virgin fibre reinforced concrete.

Keywords: fibre reinforced concrete, polypropylene, recycled, strength

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Authors: Beier Zhu, Rui Zhang, Qi Song

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Text contained within fixed-layout documents can be of great semantic value and so requires a high localization accuracy, such as ID cards, invoices, cheques, and passports. Recently, algorithms based on deep convolutional networks achieve high performance on text detection tasks. However, for text localization in fixed-layout documents, such algorithms detect word bounding boxes individually, which ignores the layout information. This paper presents a novel architecture built on convolutional neural networks (CNNs). A global text localization network and a regional bounding-box regression network are introduced to tackle the problem in a coarse-to-fine manner. The text localization network simultaneously locates word bounding points, which takes the layout information into account. The bounding-box regression network inputs the features pooled from arbitrarily sized RoIs and refine the localizations. These two networks share their convolutional features and are trained jointly. A typical type of fixed-layout documents: ID cards, is selected to evaluate the effectiveness of the proposed system. These networks are trained on data cropped from nature scene images, and synthetic data produced by a synthetic text generation engine. Experiments show that our approach locates high accuracy word bounding boxes and achieves state-of-the-art performance.

Keywords: bounding box regression, convolutional networks, fixed-layout documents, text localization

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Authors: Fabrizio Logiurato

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Light Polarization has many technological applications, and its discovery was crucial to reveal the transverse nature of the electromagnetic waves. However, despite its fundamental and practical importance, in high school, this property of light is often neglected. This is a pity not only for its conceptual relevance, but also because polarization gives the possibility to perform many brilliant experiments with low cost materials. Moreover, the treatment of this matter lends very well to an interdisciplinary approach between art, biology and technology, which usually makes things more interesting to students. For these reasons, we have developed, and in this work, we introduce a laboratory on light polarization for high school and undergraduate students. They can see beautiful pictures when birefringent materials are set between two crossed polarizing filters. Pupils are very fascinated and drawn into by what they observe. The colourful images remind them of those ones of abstract painting or alien landscapes. With this multidisciplinary teaching method, students are more engaged and participative, and also, the learning process of the respective physics concepts is more effective.

Keywords: light polarization, optical activity, multidisciplinary education, science and art

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Authors: Sunil Kayesth, Kamal Kumar Gupta

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Influence of hexane extract of Catharanthus roseus leaves on reproductive fitness of Dysdercus koenigii was investigated by evaluating mating behaviour, oviposition behaviour and fertility of the treated insects. The volatiles of the plants were extracted in hexane by ‘cold extraction method’. The insects were treated with the extracts by ‘dry film residual method’. Our studies indicated that the treated male showed altered courtship behaviour, less number of mounting attempts, took more time to mate, less percent successful mating, and more disrupted mating. Similarly, the treated female exhibited either mating refusal or neutral behaviour towards courting males. The maximum disruption in the mating was observed in a cross T♂ X T♀, where males and females were treated with Catharanthus extract. The Dysdercus treated with Catharanthus extracts also showed marked reduction in their reproductive success. The treated females laid lesser number of egg batches and eggs in their life span. Catharanthus extract was effective in alteration of the oviposition behaviour. The eggs laid by the mated females were fertile indicating insemination of the mated females. However, the percent hatchability of the eggs laid by the treated females was less than control. The GC-MS analysis of the extract revealed the presence of juvenile hormone mimics, and the intermediates of juvenile hormone biosynthesis. Therefore, some of these compounds individually or synergistically alter reproductive behaviour of Dysdercus.

Keywords: Catharanthus roseus, Dysdercus koenigii, GC-MS analysis, reproductive performance

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Authors: Ramesh Nagarajappa, Upasana Mohapatra

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Considered a modern phobia, Nomophobia (NO MObile PHOne PhoBIA) is a term that describes the irrational fear or anxiety of being unable to access one’s own mobile phone. Objectives: To develop and validate the nomophobia questionnaire, administering it to a sample of adolescents representing undergraduate dental students. To assess the prevalence of Nomophobia, determine the usage pattern of mobile phones, and evaluate the impact due to lack of access to mobile phones among undergraduate dental students. Methodology: A cross-sectional study was conducted on 302 undergraduate students at Bhubaneswar through a self-administered questionnaire via Google Forms consisting of 19 items evaluating the pattern and anxiety related to usage of mobile phones. Responses were recorded on a 5-point Likert scale. Kruskal Wallis, Mann-Whitney U, and Chi-square tests were used for statistical analysis. Results: Test-Retest reliability showed kappa of k=0.86 and Internal consistency Chronbach’s-Alpha to be α=0.82. Prevalence of nomophobia (score ≥ 58) was 32.1%, and students at risk of being nomophobic (score 39-57) was 61.9%. It was highest in males (32.6%) and amongst the interns (41.9%) and lowest (25.5%) amongst the second-year students. Participants felt nervous/insecure if their phones were away from them because of the fear that somebody might have accessed their data (3.07±1.93) and or tried to contact them (3.09±1.13), which were not statistically significant (p>0.05). Conclusions: Effect of mobile phone on dental students and the fear of not having their phones with them is increasing elaborately, that needs to be controlled, which if not achieved, would negatively hamper their academic performance and their being in the society.

Keywords: addiction, dental students, mobile phone, nomophobia

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Authors: Afsal Mohammed Kadavilpparampu, Haider A. J. Al Lawati, Fakhr Eldin O. Suliman, Salma M. Z. Al Kindy

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In this work, we evaluated the appropriateness of various oxidants that can be used potentially with Ru(bipy)32+ CL system while performing CL detection in a microfluidic device using eight common active pharmaceutical ingredients- ciprofloxacin, hydrochlorothiazide, norfloxacin, buspirone, fexofenadine, cetirizine, codeine, and dextromethorphan. This is because, microfludics have very small channel volume and the residence time is also very short. Hence, a highly efficient oxidant is required for on-chip CL detection to obtain analytically acceptable CL emission. Three common oxidants were evaluated, lead dioxide, cerium ammonium sulphate and ammonium peroxydisulphate. Results obtained showed that ammonium peroxydisulphate is the most appropriate oxidant which can be used in microfluidic setup and all the tested analyte give strong CL emission while using this oxidant. We also found that Ru(bipy)33+ generated off-line by oxidizing [Ru(bipy)3]Cl2.6H2O in acetonitrile under acidic condition with lead dioxide was stable for more than 72 hrs. A highly sensitive microbore HPLC- CL method using ammonium peroxydisulphate as an oxidant in a microfluidic on-chip CL detection has been developed for the analyses of fixed-dose combinations of pseudoephedrine (PSE), fexofenadine (FEX) and cetirizine (CIT) in biological fluids and pharmaceutical formulations with minimum sample pre-treatment.

Keywords: oxidants, microbore High Performance Liquid Chromatography, chemiluminescence, microfluidics

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Authors: Hatice Özbek, Caner Çil, Ahmet Rodoplu

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Automotive lighting is the leading function in the configuration of vehicle architecture. Especially headlights and taillights from external lighting functions are among the structures that determine the stylistic character of the vehicle. At the same time, the fact that lighting functions are related to many other functions brings along difficulties in design. Customers expect maximum quality from the vehicle. In these circumstances, it is necessary to make designs that aim to keep the performance of bulbs with limited working lives at the highest level. With this study, the factors that influence the working lives of filament lamps were examined and bulb explosions that can occur sooner than anticipated in the future were prevented while the vehicle was still in the design phase by determining the relations with electrical, dynamical and static variables. Especially the filaments of the bulbs used in the front lighting of the vehicle are deformed in a shorter time due to the high voltage requirement. In addition to this, rear lighting lamps vibrate as a result of the tailgate opening and closing and cause the filaments to be exposed to high stress. With this study, the findings that cause bulb explosions were evaluated. Among the most important findings: 1. The structure of the cables to the lighting functions of the vehicle and the effect of the voltage values are drawn; 2. The effect of the vibration to bulb throughout the life of the vehicle; 3 The effect of the loads carried to bulb while the vehicle doors are opened and closed. At the end of the study, the maximum performance was established in the bulb lifetimes with the optimum changes made in the vehicle architecture based on the findings obtained.

Keywords: vehicle architecture, automotive lighting functions, filament lamps, bulb lifetime

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Authors: Livia Calcagni

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Most of the largest cities in the world are located in areas that are vulnerable to coastal erosion and flooding, both linked to climate change and rising sea levels (RSL). Nevertheless, more and more people are moving to these vulnerable areas as cities keep growing. Architects, engineers and policy makers are called to rethink the way we live and to provide timely and adequate responses not only by investigating measures to improve the urban fabric, but also by developing strategies capable of planning change, exploring unusual and resilient frontiers of living, such as floating architecture. Since the beginning of the 21st century we have seen a dynamic growth of water-based architecture. At the same time, the shortage of land available for urban development also led to reclaim the seabed or to build floating structures. In light of these considerations, time is ripe to consider floating architecture not only as a full-fledged building typology but especially as a full-fledged adaptation solution for RSL. Currently, there is no global international legal framework for urban development on water and there is no structured performance based building design (PBBD) approach for floating architecture in most countries, let alone national regulatory systems. Thus, the research intends to identify the technological, morphological, functional, economic, managerial requirements that must be considered in a the development of the PBBD framework conceived as a meta-design tool. As it is expected that floating urban development is mostly likely to take place as extension of coastal areas, the needs and design criteria are definitely more similar to those of the urban environment than of the offshore industry. Therefor, the identification and categorization of parameters takes the urban-architectural guidelines and regulations as the starting point, taking the missing aspects, such as hydrodynamics, from the offshore and shipping regulatory frameworks. This study is carried out through an evidence-based assessment of performance guidelines and regulatory systems that are effective in different countries around the world addressing on-land and on-water architecture as well as offshore and shipping industries. It involves evidence-based research and logical argumentation methods. Overall, this paper highlights how inhabiting water is not only a viable response to the problem of RSL, thus a resilient frontier for urban development, but also a response to energy insecurity, clean water and food shortages, environmental concerns and urbanization, in line with Blue Economy principles and the Agenda 2030. Moreover, the discipline of architecture is presented as a fertile field for investigating solutions to cope with climate change and its effects on life safety and quality. Future research involves the development of a decision support system as an information tool to guide the user through the decision-making process, emphasizing the logical interaction between the different potential choices, based on the PBBD.

Keywords: adaptation measures, floating architecture, performance based building design, resilient architecture, rising sea levels

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Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

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Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

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Authors: Yangzhi Li

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Network transfer of information and performance customization is now a viable method of digital industrial production in the era of Industry 4.0. Robot platforms and network platforms have grown more important in digital design and construction. The pressing need for novel building techniques is driven by the growing labor scarcity problem and increased awareness of construction safety. Robotic approaches in construction research are regarded as an extension of operational and production tools. Several technological theories related to robot autonomous recognition, which include high-performance computing, physical system modeling, extensive sensor coordination, and dataset deep learning, have not been explored using intelligent construction. Relevant transdisciplinary theory and practice research still has specific gaps. Optimizing high-performance computing and autonomous recognition visual guidance technologies improves the robot's grasp of the scene and capacity for autonomous operation. Intelligent vision guidance technology for industrial robots has a serious issue with camera calibration, and the use of intelligent visual guiding and identification technologies for industrial robots in industrial production has strict accuracy requirements. It can be considered that visual recognition systems have challenges with precision issues. In such a situation, it will directly impact the effectiveness and standard of industrial production, necessitating a strengthening of the visual guiding study on positioning precision in recognition technology. To best facilitate the handling of complicated components, an approach for the visual recognition of parts utilizing machine learning algorithms is proposed. This study will identify the position of target components by detecting the information at the boundary and corner of a dense point cloud and determining the aspect ratio in accordance with the guidelines for the modularization of building components. To collect and use components, operational processing systems assign them to the same coordinate system based on their locations and postures. The RGB image's inclination detection and the depth image's verification will be used to determine the component's present posture. Finally, a virtual environment model for the robot's obstacle-avoidance route will be constructed using the point cloud information.

Keywords: robotic construction, robotic assembly, visual guidance, machine learning

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Authors: Ahmad Nawid Mirzad, Akira Goto, Takuto Endo, Hitoshi Ano, Hiromu Katamoto, Takenori Yamauchi

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The objective of this study was to evaluate the effects of live yeast supplementation on oxidative stress biomarker and antioxidant vitamin levels as well as lactation performance in Holstein Friesian cows during the summer season in Fukuoka prefecture. Sixteen lactating cows weighing 707.50 ± 13.09 kg (Mean ± SE) were used and randomly assigned to either supplemented (n = 8) or control (n = 8) group. The cows in supplemented group were administered with live yeast product at 10 g/d per cow from middle of July to middle of September for eight weeks. In treatment group, serum levels of derivatives of reactive oxygen metabolites (d-ROMs) were lower at week six. In addition, serum levels of glucose and retinol were higher at week eight and those of α-tocopherol were higher at week 2 in treatment group. During study period daily average milk yield decreased in both groups. Daily average milk yield 63 days after the onset of supplementation in treatment and control groups were 23.5 and 22.2 kg, respectively. The reduction rate of milk yield in treatment group tended to be lower (17.6 vs. 20.0%). These results suggest that live yeast supplementation may reduce oxidative stress and improve energy metabolism in lactating dairy cows during the summer season.

Keywords: cow, live yeast, milk, oxidative stress, summer season

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Authors: Natalia Rudeli, Elisabeth Viles, Adrian Santilli

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Delays in the construction industry are a global phenomenon. Many construction projects experience extensive delays exceeding the initially estimated completion time. The main purpose of this study is to identify construction projects typical behaviors in order to develop a prognosis and management tool. Being able to know a construction projects schedule tendency will enable evidence-based decision-making to allow resolutions to be made before delays occur. This study presents an innovative approach that uses Cluster Analysis Method to support predictions during Earned Value Analyses. A clustering analysis was used to predict future scheduling, Earned Value Management (EVM), and Earned Schedule (ES) principal Indexes behaviors in construction projects. The analysis was made using a database with 90 different construction projects. It was validated with additional data extracted from literature and with another 15 contrasting projects. For all projects, planned and executed schedules were collected and the EVM and ES principal indexes were calculated. A complete linkage classification method was used. In this way, the cluster analysis made considers that the distance (or similarity) between two clusters must be measured by its most disparate elements, i.e. that the distance is given by the maximum span among its components. Finally, through the use of EVM and ES Indexes and Tukey and Fisher Pairwise Comparisons, the statistical dissimilarity was verified and four clusters were obtained. It can be said that construction projects show an average delay of 35% of its planned completion time. Furthermore, four typical behaviors were found and for each of the obtained clusters, the interim milestones and the necessary rhythms of construction were identified. In general, detected typical behaviors are: (1) Projects that perform a 5% of work advance in the first two tenths and maintain a constant rhythm until completion (greater than 10% for each remaining tenth), being able to finish on the initially estimated time. (2) Projects that start with an adequate construction rate but suffer minor delays culminating with a total delay of almost 27% of the planned time. (3) Projects which start with a performance below the planned rate and end up with an average delay of 64%, and (4) projects that begin with a poor performance, suffer great delays and end up with an average delay of a 120% of the planned completion time. The obtained clusters compose a tool to identify the behavior of new construction projects by comparing their current work performance to the validated database, thus allowing the correction of initial estimations towards more accurate completion schedules.

Keywords: cluster analysis, construction management, earned value, schedule

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Authors: Suriyani Ariffin, Nor Aziah Alias, Khairil Iskandar Othman, Haslinda Yusoff

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An Integrated Cumulative Grade Point Average (iCGPA) is a mechanism and strategy to ensure the curriculum of an academic programme is constructively aligned to the expected learning outcomes and student performance based on the attainment of those learning outcomes that is reported objectively in a spider web. Much effort and time has been spent to develop a viable mechanism and trains academics to utilize the platform for reporting. The question is: How well do learners conceive the idea of their achievement via iCGPA and whether quality learner attributes have been nurtured through the iCGPA mechanism? This paper presents the architecture of an integrated CGPA mechanism purported to address a holistic evaluation from the evaluation of courses learning outcomes to aligned programme learning outcomes attainment. The paper then discusses the students’ understanding of the mechanism and evaluation of their achievement from the generated spider web. A set of questionnaires were distributed to a group of students with iCGPA reporting and frequency analysis was used to compare the perspectives of students on their performance. In addition, the questionnaire also explored how they conceive the idea of an integrated, holistic reporting and how it generates their motivation to improve. The iCGPA group was found to be receptive to what they have achieved throughout their study period. They agreed that the achievement level generated from their spider web allows them to develop intervention and enhance the programme learning outcomes before they graduate.

Keywords: learning outcomes attainment, iCGPA, programme learning outcomes, spider web, iCGPA reporting skills

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Authors: Yeliz Karaca, Rana Karabudak

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Multifractal Denoising techniques are used in the identification of significant attributes by removing the noise of the dataset. Magnetic resonance (MR) image technique is the most sensitive method so as to identify chronic disorders of the nervous system such as Multiple Sclerosis. MRI and Expanded Disability Status Scale (EDSS) data belonging to 120 individuals who have one of the subgroups of MS (Relapsing Remitting MS (RRMS), Secondary Progressive MS (SPMS), Primary Progressive MS (PPMS)) as well as 19 healthy individuals in the control group have been used in this study. The study is comprised of the following stages: (i) L2 Norm Multifractal Denoising technique, one of the multifractal technique, has been used with the application on the MS data (MRI and EDSS). In this way, the new dataset has been obtained. (ii) The new MS dataset obtained from the MS dataset and L2 Multifractal Denoising technique has been applied to the K-Means and Fuzzy C Means clustering algorithms which are among the unsupervised methods. Thus, the clustering performances have been compared. (iii) In the identification of significant attributes in the MS dataset through the Multifractal denoising (L2 Norm) technique using K-Means and FCM algorithms on the MS subgroups and control group of healthy individuals, excellent performance outcome has been yielded. According to the clustering results based on the MS subgroups obtained in the study, successful clustering results have been obtained in the K-Means and FCM algorithms by applying the L2 norm of multifractal denoising technique for the MS dataset. Clustering performance has been more successful with the MS Dataset (L2_Norm MS Data Set) K-Means and FCM in which significant attributes are obtained by applying L2 Norm Denoising technique.

Keywords: clinical decision support, clustering algorithms, multiple sclerosis, multifractal techniques

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Authors: Sana Dridi, Jalel Aouissi, Rafla Attia, Taoufik Hermassi, Thouraya Sahli

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Soil erosion is an increasing issue in Mediterranean countries. In Tunisia, the capacity of dam reservoirs continues to decrease as a consequence of soil erosion. This study aims to predict sediment yield to enrich soil management practices using Soil and Water Assessment Tools model (SWAT) in the Siliana watershed (1041.6 km²), located in the northwest of Tunisia. A database was constructed using remote sensing and Geographical Information System. Climatic and flow data were collected from water resources directorates in Tunisia. The SWAT model was built to simulate hydrological processes and sediment transport. A sensitivity analysis, calibration, and validation were performed using SWAT-CUP software. The model calibration of stream flow simulations shows a good performance with NSE and R² values of 0.77 and 0.79, respectively. The model validation shows a very good performance with values of NSE and R² for 0.8 and 0.88, respectively. After calibration and validation of stream flow simulation, the model was used to simulate the soil erosion and sediment load transport. The spatial distributions of soil loss rate for determining the critical sediment source areas show that 63 % of the study area has a low soil loss rate less than 7 t ha⁻¹y⁻¹. The annual average soil loss rate simulated with the SWAT model in the Siliana watershed is 4.62 t ha⁻¹y⁻¹.

Keywords: water erosion, SWAT model, streamflow, SWATCUP, sediment yield

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Authors: Cebrail Çiflikli, Emre Öner Tartan

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Parallel to the fast worldwide increase of elderly population and spreading unhealthy life habits, there is a significant rise in the number of patients and health problems. The supervision of people who have health problems and oversight in detection of people who have potential risks, bring a considerable cost to health system and increase workload of physician. To provide an efficient solution to this problem, in the recent years mobile applications have shown their potential for wide usage in health monitoring. In this paper we present an Android mobile application that records and evaluates ECG signal using Pan-Tompkins algorithm for QRS detection. The application model includes an alarm mechanism that is proposed to be used for sending message including abnormality information and location information to health supervisor.

Keywords: Android mobile application, ECG monitoring, QRS detection, Pan-Tompkins Algorithm

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Authors: Bilal Ahmed

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Rehabilitation of congenital and acquired maxillofacial defects is always a challenging clinical scenario. These defects pose major physiological and psychological threat not only to the patient but to the entire family. There has been an enormous scientific development in maxillofacial rehabilitation with the advent of CAD CAM, 3-D scanning, Osseo-integrated implants and improved restorative materials. There are also specialized centers with latest diagnostic and treatment facilities in the developed countries. However, in certain clinical case scenarios, conventional prosthodontic principles are still the gold standards. Similarly in a less developed world, financial and technical constraints are factors affecting treatment planning and final outcomes. However, we can do a lot of benefits to the affected human beings, even with use of simple and cost-effective conventional prosthodontic techniques and materials. These treatment strategies may sometimes be considered as intermediate or temporary options, but with regular follow-up maintenance these can be used on a definitive basis.

Keywords: maxillofacial defects, obturators, prosthodontics, medical and health sciences

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Authors: Dirk Briskorn, Michael Dienstknecht

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Cranes are a key element in construction projects as they are the primary lifting equipment and among the most expensive construction equipment. Thus, selecting cranes and locating them on-site is an important factor for a project's profitability. We focus on a site with supply and demand areas that have to be connected by tower cranes. There are several types of tower cranes differing in certain specifications such as costs or operating radius. The objective is to select cranes and determine their locations such that each demand area is connected to its supply area at minimum cost. We detail the problem setting and show how to obtain a discrete set of candidate locations for each crane type without losing optimality. This discretization allows us to reduce our problem to the classic set cover problem. Despite its NP-hardness, we achieve good results employing a standard solver and a greedy heuristic, respectively.

Keywords: positioning, selection, standard solver, tower cranes

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Authors: Mohammed Jourdani, Hamid Mounir, Abdellatif El Marjani

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Proton exchange membrane fuel cells (PEMFCs) have been developed as a promising power source for transportation and stationary applications, and power devices for computers and mobile telephones. This paper discusses and summarizes the latest developments of materials and remaining challenges of PEMFC. The different contributions to the material of all components and the efficiencies are analyzed. Many technical advances are introduced to increase the PEMFC fuel cell efficiency and life time for transportation, stationary and portable utilization. By the last years the total cost of this system is decreasing. However, the remaining challenges that need to be overcome mean that it will be several years before full commercialization can take place.

Keywords: PEMFC fuel cell, materials, recent development, efficiency, life time, commercialization possibility

Procedia PDF Downloads 307