Search results for: hybrid meta-heuristic methods

Authors: Ana Paula Vilas Boas Viveiros Lopes, Marly Monteiro de Carvalho

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The new product development for decades has favored companies that can put their products to market quickly and efficiently, providing sustainable competitive advantage difficult to be achieved by their competitors. This paper presents the outcomes of a systematic review of the literature relating to new product development that was published between 1992 and 2012. A hybrid methodological approach that combines bibliometrics, content analysis and semantic analysis was applied. The review discusses the publication patterns, focusing on aspects related to scientific collaboration. The results show that the main academic journal that discusses this theme is “Journal of Product Innovation Management”. Although the first paper relating to this theme was published in 1992, the number of publications on the subject only began to increase substantially in 1999. Most of the studies reviewed in this paper applied qualitative research methods, indicating that most of the research on the theme is still in an exploratory phase.

Keywords: project type, project typology, new product development, sustainable competitive advantage

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Authors: Aslı Günay Bulutsuz, Mehmet Emin Yurci

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Severe plastic deformation techniques are top-down deformation methods which enable superior mechanical properties by decreasing grain size. Different kind severe plastic deformation methods have been widely being used at various process temperature and geometries. Besides manufacturing advantages of severe plastic deformation technique, most of the types are being used only at the laboratory level. They cannot be adapted to industrial usage due to their continuous manufacturability and manufacturing costs. In order to enhance these manufacturing difficulties and enable widespread usage, different kinds of methods have been developed. In this review, a comprehensive literature research was fulfilled in order to highlight continuous severe plastic deformation methods.

Keywords: continuous manufacturing, severe plastic deformation, ultrafine grains, grain size refinement

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Authors: Sonveer Singh, Sanjay Agrawal, D. V. Avasthi, Jayant Shekhar

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The aim of this paper is to improve the efficiency of photovoltaic thermal (PVT) system with the help of Genetic Algorithms with multi-objective function. There are some parameters that affect the efficiency of PVT system like depth and length of the channel, velocity of flowing fluid through the channel, thickness of the tedlar and glass, temperature of inlet fluid i.e. all above parameters are considered for optimization. An attempt has been made to the model and optimizes the parameters of glazed hybrid single channel PVT module when two objective functions have been considered separately. The two objective function for optimization of PVT module is overall electrical and thermal efficiency. All equations for PVT module have been derived. Using genetic algorithms (GAs), above two objective functions of the system has been optimized separately and analysis has been carried out for two cases. Two cases are: Case-I; Improvement in electrical and thermal efficiency when overall electrical efficiency is optimized, Case-II; Improvement in electrical and thermal efficiency when overall thermal efficiency is optimized. All the parameters that are used in genetic algorithms are the parameters that could be changed, and the non-changeable parameters, like solar radiation, ambient temperature cannot be used in the algorithm. It has been observed that electrical efficiency (14.08%) and thermal efficiency (19.48%) are obtained when overall thermal efficiency was an objective function for optimization. It is observed that GA is a very efficient technique to estimate the design parameters of hybrid single channel PVT module.

Keywords: genetic algorithm, energy, exergy, PVT module, optimization

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Authors: Komal Verma, V. S. Moholkar

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This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result is essentially a consequence of synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Microconvection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe₃O₄@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater The Fe₃O₄@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: Fe₃O₄@AC nanocomposite, RSM, COD;, LC-MS, Toxicity

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Authors: Hande Yavuz, Grégory Girard, Jinbo Bai

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Manufacturing of hybrid composites requires particular attention to overcome various critical weaknesses that are originated from poor interfacial compatibility. A large number of parameters have to be considered to optimize the interfacial bond strength either to avoid flaw sensitivity or delamination that occurs in composites. For this reason, surface characterization of reinforcement phase is needed in order to provide necessary data to drive an assessment of fiber-matrix interfacial compatibility prior to fabrication of composite structures. Compared to conventional plasma polymerization processes such as radiofrequency and microwave, dielectric barrier discharge assisted plasma polymerization is a promising process that can be utilized to modify the surface properties of carbon fibers in a continuous manner. Finding the most suitable conditions (e.g., plasma power, plasma duration, precursor proportion) for plasma polymerization of pyrrole in post-discharge region either in the presence or in the absence of p-toluene sulfonic acid monohydrate as well as the characterization of plasma polypyrrole coated fibers are the important aspects of this work. Throughout the current investigation, atomic force microscopy (AFM) and thermogravimetric analysis (TGA) are used to characterize plasma treated hybrid fibers (CNT-grafted Toray T700-12K carbon fibers, referred as T700/CNT). TGA results show the trend in the change of decomposition process of deposited polymer on fibers as a function of temperature up to 900 °C. Within the same period of time, all plasma pyrrole treated samples began to lose weight with relatively fast rate up to 400 °C which suggests the loss of polymeric structures. The weight loss between 300 and 600 °C is attributed to evolution of CO2 due to decomposition of functional groups (e.g. carboxyl compounds). With keeping in mind the surface chemical structure, the higher the amount of carbonyl, alcohols, and ether compounds, the lower the stability of deposited polymer. Thus, the highest weight loss is observed in 1400 W 45 s pyrrole+pTSA.H2O plasma treated sample probably because of the presence of less stable polymer than that of other plasma treated samples. Comparison of the AFM images for untreated and plasma treated samples shows that the surface topography may change on a microscopic scale. The AFM image of 1800 W 45 s treated T700/CNT fiber possesses the most significant increase in roughening compared to untreated T700/CNT fiber. Namely, the fiber surface became rougher with ~3.6 fold that of the T700/CNT fiber. The increase observed in surface roughness compared to untreated T700/CNT fiber may provide more contact points between fiber and matrix due to increased surface area. It is believed to be beneficial for their application as reinforcement in composites.

Keywords: hybrid fibers, surface characterization, surface roughness, thermal stability

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Authors: Tareq Aljaber

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The number of mobile health apps is growing at a fast frequency as it's nearly doubled in a year between 2015 and 2016. Though, there is a lack of an effective evaluation framework to verify the usability and reliability of mobile phone health education applications which would help saving time and effort for the numerous user groups. This abstract describing a framework for evaluating mobile applications in specifically mobile health education applications, along with a guidance select tool to assist different users to select the most suitable mobile health education apps. The effective framework outcome is intended to meet the requirements and needs of the different stakeholder groups additionally to enhancing the development of mobile health education applications with software engineering approaches, by producing new and more effective techniques to evaluate such software. This abstract highlights the significance and consequences of mobile health education apps, before focusing the light on the required to create an effective evaluation framework for these apps. An explanation of the effective evaluation framework is going to be delivered in the abstract, beside with some specific evaluation metrics: an efficient hybrid of selected heuristic evaluation (HE) and usability evaluation (UE) metrics to enable the determination of the usefulness and usability of health education mobile apps. Moreover, an explanation of the qualitative and quantitative outcomes for the effective evaluation framework was accomplished using Epocrates mobile phone app in addition to some other mobile phone apps. This proposed framework-An Evaluation Framework for Mobile Health Education Apps-consists of a hybrid of 5 metrics designated from a larger set in usability evaluation and heuristic evaluation, illuminated grounded on 15 unstructured interviews from software developers (SD), health professionals (HP) and patients (P). These five metrics corresponding to explicit facets of usability recognised through a requirements analysis of typical stakeholders of mobile health apps. These five hybrid selected metrics were scattered across 24 specific questionnaire questions, which are available on request from first author. This questionnaire has been sent to 81 participants distributed in three sets of stakeholders from software developers (SD), health professionals (HP) and patients/general users (P/GU) on the purpose of ranking three sets of mobile health education applications. Finally, the outcomes from the questionnaire data helped us to approach our aims which are finding the profile for different stakeholders, finding the profile for different mobile health educations application packages, ranking different mobile health education application and guide us to build the select guidance too which is apart from the Evaluation Framework for Mobile Health Education Apps.

Keywords: evaluation framework, heuristic evaluation, usability evaluation, metrics

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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Transport infrastructures are high-cost, long-term investments that serve as vital foundations for the operation of a region or nation and are essential to a country’s or business’s economic development and prosperity, by improving well-being and generating jobs and income. The development of appropriate financing options is of key importance in the decision making process in order develop viable transport infrastructures. The development of transport infrastructure has increasingly been shifting toward alternative methods of project financing such as Public Private Partnership (PPPs) and hybrid forms. In this paper, a methodological decision-making framework based on the evaluation of the financial viability of transportation infrastructure for different financial schemes is presented. The framework leads to an assessment of the financial viability which can be achieved by performing various financing scenarios analyses. To illustrate the application of the proposed methodology, a case study of rail transport infrastructure financing scenario analysis in Greece is developed.

Keywords: rail transport infrastructure, financial viability, scenario analysis, rail project feasibility

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Authors: David Shengelia, Tamara Tsutsunava, Manana Togonidze, Giorgi Chichinadze, Giorgi Beridze

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Orthoclase gabbro intrusive exposes in the Eastern part of the Dzirula crystalline massif of the Central Transcaucasian microcontinent. It is intruded in the Baikal quartz-diorite gneisses as a stock-like body. The intrusive is characterized by heterogeneity of rock composition: variability of mineral content and irregular distribution of rock-forming minerals. The rocks are represented by pyroxenites, gabbro-pyroxenites and gabbros of different composition – K-feldspar, pyroxene-hornblende and biotite bearing varieties. Scientific views on the genesis and age of the orthoclase gabbro intrusive are considerably different. Based on the long-term pertogeochemical and geochronological investigations of the intrusive with such an extraordinary composition the authors came to the following conclusions. According to geological and geophysical data, it is stated that in the Saurian orogeny horizontal tectonic layering of the Earth’s crust of the Central Transcaucasian microcontinent took place. That is precisely this fact that explains the formation of the orthoclase gabbro intrusive. During the tectonic doubling of the Earth’s crust of the mentioned microcontinent thick tectonic nappes of mafic and sialic layers overlap the sialic basement (‘inversion’ layer). The initial magma of the intrusive was of high-temperature basite-ultrabasite composition, crystallization products of which are pyroxenites and gabbro-pyroxenites. Petrochemical data of the magma attest to its formation in the Upper mantle and partially in the ‘crustal astenolayer’. Then, a newly formed overheated dry magma with phenocrysts of clinopyrocxene and basic plagioclase intruded into the ‘inversion’ layer. From the new medium it was enriched by the volatile components causing the selective melting and as a result the formation of leucocratic quartz-feldspar material. At the same time in the basic magma intensive transformation of pyroxene to hornblende was going on. The basic magma partially mixed with the newly formed acid magma. These different magmas intruded first into the allochthonous basite layer without its significant transformation and then into the upper sialic layer and crystallized here at a depth of 7-10 km. By petrochemical data the newly formed leucocratic granite magma belongs to the S type granites, but the above mentioned mixed magma – to H (hybrid) type. During the final stage of magmatic processes the gabbroic rocks impregnated with high-temperature feldspar-bearing material forming anorthoclase or orthoclase. Thus, so called ‘orthoclase gabbro’ includes the rocks of various genetic groups: 1. protolith of gabbroic intrusive; 2. hybrid rock – K-feldspar gabbro and 3. leucocratic quartz-feldspar bearing rock. Petrochemical and geochemical data obtained from the hybrid gabbro and from the inrusive protolith differ from each other. For the identification of petrogenetic model of the orthoclase gabbro intrusive formation LA-ICP-MS- U-Pb zircon dating has been conducted in all three genetic types of gabbro. The zircon age of the protolith – mean 221.4±1.9 Ma and of hybrid K-feldspar gabbro – mean 221.9±2.2 Ma, records crystallization time of the intrusive, but the zircon age of quartz-feldspar bearing rocks – mean 323±2.9 Ma, as well as the inherited age (323±9, 329±8.3, 332±10 and 335±11 Ma) of hybrid K-feldspar gabbro corresponds to the formation age of Late Variscan granitoids widespread in the Dzirula crystalline massif.

Keywords: The Caucasus, isotope dating, orthoclase-bearing gabbro, petrogenetic model

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Authors: Ketan Mahawer, Abeer Mutto, S. K. Gupta

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The mining wastewater contains inorganic metal salts, which makes it saline and additionally contributes to contaminating the surface and underground freshwater reserves that exist nearby mineral processing industries. Therefore, treatment of wastewater and water recovery is obligatory by any available technology before disposing it into the environment. Currently, reverse osmosis (RO) is the commercially acceptable conventional membrane process for saline wastewater treatment, but consumes an enormous amount of energy and makes the process expensive. To solve this industrial problem with minimum energy consumption, we tested the feasibility of forward osmosis-nanofiltration (FO-NF) hybrid process for the mining wastewater treatment. The FO-NF process experimental results for 0.029M concentration of saline wastewater treated by 0.42 M sodium-sulfate based draw solution shows that specific energy consumption of the FO-NF process compared with standalone NF was slightly above (between 0.5-1 kWh/m3) from conventional process. However, average freshwater recovery was 30% more from standalone NF with same feed and operating conditions. Hence, FO-NF process in place of RO/NF offers a huge possibility for treating mining industry wastewater and concentrates the metals as the by-products without consuming an excessive/large amount of energy and in addition, mitigates the fouling in long periods of treatment, which also decreases the maintenance and replacement cost of the separation process.

Keywords: forward osmosis, nanofiltration, mining, draw solution, divalent solute

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Authors: Daniel Tochwin

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Continuous improvement is an essential part of effective process performance management. In order to achieve continuous quality improvement, each organization must use the appropriate selection of tools and techniques. The basic condition for success is a proper understanding of the business need faced by the company and the selection of appropriate methods to improve a given production process. The main aim of this article is to analyze the methods of conduct which are popular in practice when implementing process improvements and then to determine whether the tested methods include repetitive systematics of the approach, i.e., a similar sequence of the same or similar actions. Based on an extensive literature review, 4 methods of continuous improvement of production processes were selected: A3 report, Gemba Kaizen, PDCA cycle, and Deming cycle. The research shows that all frequently used improvement methods are generally based on the PDCA cycle, and the differences are due to "(re)interpretation" and the need to adapt the continuous improvement approach to the specific business process. The research shows that all the frequently used improvement methods are generally based on the PDCA cycle, and the differences are due to "(re) interpretation" and the need to adapt the continuous improvement approach to the specific business process.

Keywords: continuous improvement, lean methods, process improvement, PDCA

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Authors: Swati Tomar, Sunil Kumar Gupta

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Anammox is a promising and cost effective alternative to conventional treatment systems that facilitates direct oxidation of ammonium nitrogen under anaerobic conditions with nitrite as an electron acceptor without addition of any external carbon sources. The present study investigates the process kinetics of laboratory scale anammox hybrid reactor (AHR) which combines the dual advantages of attached and suspended growth. The performance & behaviour of AHR was studied under varying hydraulic retention time (HRTs) and nitrogen loading rate (NLRs). The experimental unit consisted of 4 numbers of 5L capacity anammox hybrid reactor inoculated with mixed seed culture containing anoxic and activated sludge. Pseudo steady state (PSS) ammonium and nitrite removal efficiencies of 90.6% and 95.6%, respectively, were achieved during acclimation phase. After establishment of PSS, the performance of AHR was monitored at seven different HRTs of 3.0, 2.5, 2.0, 1.5, 1.0, 0.5 and 0.25 d with increasing NLR from 0.4 to 4.8 kg N/m3d. The results showed that with increase in NLR and decrease in HRT (3.0 to 0.25 d), AHR registered appreciable decline in nitrogen removal efficiency from 92.9% to 67.4 %, respectively. The HRT of 2.0 d was considered optimal to achieve substantial nitrogen removal of 89%, because on further decrease in HRT below 1.5 days, remarkable decline in the values of nitrogen removal efficiency were observed. Analysis of data indicated that attached growth system contributes an additional 15.4 % ammonium removal and reduced the sludge washout rate (additional 29% reduction). This enhanced performance may be attributed to 25% increase in sludge retention time due to the attached growth media. Three kinetic models, namely, first order, Monod and Modified Stover-Kincannon model were applied to assess the substrate removal kinetics of nitrogen removal in AHR. Validation of the models were carried out by comparing experimental set of data with the predicted values obtained from the respective models. For substrate removal kinetics, model validation revealed that Modified Stover-Kincannon is most precise (R2=0.943) and can be suitably applied to predict the kinetics of nitrogen removal in AHR. Lawrence and McCarty model described the kinetics of bacterial growth. The predicted value of yield coefficient and decay constant were in line with the experimentally observed values.

Keywords: anammox, kinetics, modelling, nitrogen removal, sludge wash out rate, AHR

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Authors: Wilhelmus Hary Susilo

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The marketplace would have at least some resources that are unique (e.g., well communication, knowledgeable employees, consumer value, effective transaction, efficient production processes and institutional branding). The institutions should have an advantage in resources and then could lead to positions of competitive advantage. These major challenges focus on increasing unique consumer value on reliable purchases that influence of loyalty and pursuit of a sustainable competitive advantage from the Institutions in Jakarta. Furthermore, a research was conducted with a quantitative method and a confirmatory strategic research design. The research resulted in entire confirmatory factors analysis (1st CFA and 2nd CFA) among variables pertains to; χ2//Df (9.30, 4.38, 6.95, 2.76, 2.97, 2.91, 2.32 and 6.90), GFI (0.72, 0.82, 0.82, 0.81, 0.78, 0.84, 0.89 and 0.70) and CFI (0.90, 0.95, 0.93, 0.92, 0.95, 0.91, 0.96 and 0.89), which indicates a good model. Furthermore, the hybrid model is well fit with, χ2//Df=1.84, P value = 0.00, RMSEA = 0.076, GFI = 0.76, NNFI= 0.95, PNFI= 0.82, IFI= 0.96, RFI= 0.91, AGFI= 0.71 and CFI= 0.96. The result was significant hypothesis, i.e. variables of communitization marketing 3.0 and price perception influenced to unique value of consumer with tvalue =4.46 and 5.89. Furthermore, the consumers value influenced the purchasing with t value = 5.94. Additionally, the loyalty, the ‘communitization’, and the character building marketing 3.0 are affecting the pursuit of a sustainable competitive advantage from institutions with t value = 7.57, -2.12, and 2.04. Finally, the test between the most superior variable dimensions is significantly correlated between INOV and WDES, RESPON and ATT covariance matrix value= 0.72 and 0.71. Thus, ‘communitization’ and character building marketing 3.0 with dimensions of responsibility and technologies would increase a competitive advantage with the dimensions of the innovation and the job design from the institutions.

Keywords: consumer loyalty, marketing 3.0, unique consumer value, purchase, sustainable competitive advantage

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Authors: Bingchun Liu, Pei-Chann Chang, Natasha Huang, Dun Li

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Machine Learning and Data Mining are the two important tools for extracting useful information and knowledge from large datasets. In machine learning, classification is a wildly used technique to predict qualitative variables and is generally preferred over regression from an operational point of view. Due to the enormous increase in air pollution in various countries especially China, Air Quality Classification has become one of the most important topics in air quality research and modelling. This study aims at introducing a hybrid classification model based on information theory and Support Vector Machine (SVM) using the air quality data of four cities in China namely Beijing, Guangzhou, Shanghai and Tianjin from Jan 1, 2014 to April 30, 2016. China's Ministry of Environmental Protection has classified the daily air quality into 6 levels namely Serious Pollution, Severe Pollution, Moderate Pollution, Light Pollution, Good and Excellent based on their respective Air Quality Index (AQI) values. Using the information theory, information gain (IG) is calculated and feature selection is done for both categorical features and continuous numeric features. Then SVM Machine Learning algorithm is implemented on the selected features with cross-validation. The final evaluation reveals that the IG and SVM hybrid model performs better than SVM (alone), Artificial Neural Network (ANN) and K-Nearest Neighbours (KNN) models in terms of accuracy as well as complexity.

Keywords: machine learning, air quality classification, air quality index, information gain, support vector machine, cross-validation

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Authors: V. Vicente E. Mujica, Gustavo Gonzalez

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The global coverage of broadband multimedia and internet-based services in terrestrial-satellite networks demand particular interests for satellite providers in order to enhance services with low latencies and high signal quality to diverse users. In particular, the delay of on-board processing is an inherent source of latency in a satellite communication that sometimes is discarded for the end-to-end delay of the satellite link. The frame work for this paper includes modelling of an on-orbit satellite payload using an agent model that can reproduce the properties of processing delays. In essence, a comparison of different spatial interpolation methods is carried out to evaluate physical data obtained by an GEO satellite in order to define a discretization function for determining that delay. Furthermore, the performance of the proposed agent and the development of a delay discretization function are together validated by simulating an hybrid satellite and terrestrial network. Simulation results show high accuracy according to the characteristics of initial data points of processing delay for Ku bands.

Keywords: terrestrial-satellite networks, latency, on-orbit satellite payload, simulation

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Authors: Olusola Bamisile, Ferdinard Dika, Mustafa Dagbasi, Serkan Abbasoglu

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The aim of this study was to model an air conditioning system that brings about effective cooling and reduce fossil fuel consumption with solar energy as an alternative source of energy. The objective of the study is to design a system with high COP, low usage of electricity and to integrate solar energy into AC systems. A hybrid solar assisted air conditioning system is designed to produce 30kW cooling capacity and R744 (CO₂) is used as a refrigerant. The effect of discharge pressure on the performance of the system is studied. The subcool temperature, evaporating temperature (5°C) and suction gas return temperature (12°C) are kept constant for the four different discharge pressures considered. The cooling gas temperature is set at 25°C, and the discharge pressure includes 80, 85, 90 and 95 bars. Copeland Scroll software is used for the simulation. A pressure-enthalpy graph is also used to deduce each enthalpy point while numerical methods were used in making other calculations. From the result of the study, it is observed that a higher COP is achieved with the use of solar assisted systems. As much as 46% of electricity requirements will be save using solar input at compressor stage.

Keywords: air conditioning, solar energy, performance, energy saving

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Authors: Biswaranjan D. Mohapatra, Ipsha Hota, Swarna P. Mantry, Nibedita Behera, Kumar S. K. Varadwaj

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Designing highly active and low-cost oxygen evolution (2H₂O → 4H⁺ + 4e⁻ + O₂) electrocatalyst is one of the most active areas of advanced energy research. Some precious metal-based electrocatalysts, such as IrO₂ and RuO₂, have shown excellent performance for oxygen evolution reaction (OER); however, they suffer from high-cost and low abundance which limits their applications. Recently, layered double hydroxides (LDHs), composed of layers of divalent and trivalent transition metal cations coordinated to hydroxide anions, have gathered attention as an alternative OER catalyst. However, LDHs are insulators and coupled with carbon materials for the electrocatalytic applications. Graphene covalently doped with nitrogen has been demonstrated to be an excellent electrocatalyst for energy conversion technologies such as; oxygen reduction reaction (ORR), oxygen evolution reaction (OER) & hydrogen evolution reaction (HER). However, they operate at high overpotentials, significantly above the thermodynamic standard potentials. Recently, we reported remarkably enhanced catalytic activity of benzoate or 1-pyrenebutyrate functionalized N-doped graphene towards the ORR in alkaline medium. The molecular and heteroatom co-doping on graphene is expected to tune the electronic structure of graphene. Therefore, an innovative catalyst architecture, in which LDHs are anchored on aromatic acid functionalized ‘N’ doped graphene may presumably boost the OER activity to a new benchmark. Herein, we report fabrication of Co₂Fe-LDH on aromatic acid (AA) functionalized ‘N’ doped reduced graphene oxide (NG) and studied their OER activities in alkaline medium. In the first step, a novel polyol method is applied for synthesis of AA functionalized NG, which is well dispersed in aqueous medium. In the second step, Co₂Fe LDH were grown on AA functionalized NG by co-precipitation method. The hybrid samples are abbreviated as Co₂Fe LDH/AA-NG, where AA is either Benzoic acid or 1, 3-Benzene dicarboxylic acid (BDA) or 1, 3, 5 Benzene tricarboxylic acid (BTA). The crystal structure and morphology of the samples were characterized by X-ray diffraction (XRD), scanning electron microscope (SEM) and transmission electron microscope (TEM). These studies confirmed the growth of layered single phase LDH. The electrocatalytic OER activity of these hybrid materials was investigated by rotating disc electrode (RDE) technique on a glassy carbon electrode. The linear sweep voltammetry (LSV) on these catalyst samples were taken at 1600rpm. We observed significant OER performance enhancement in terms of onset potential and current density on Co₂Fe LDH/BTA-NG hybrid, indicating the synergic effect. This exploration of molecular functionalization effect in doped graphene and LDH system may provide an excellent platform for innovative design of OER catalysts.

Keywords: π-π functionalization, layered double hydroxide, oxygen evolution reaction, reduced graphene oxide

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Authors: Dagmara Malina, Katarzyna Bialik-Wąs, Klaudia Pluta

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The growing significance of transdermal systems, in which skin is a route for systemic drug delivery, has generated a considerable amount of data which has resulted in a deeper understanding of the mechanisms of transport across the skin in the context of the controlled and prolonged release of active substances. One of such solutions may be the use of carrier systems based on intelligent polymers with different physicochemical properties. In these systems, active substances, e.g. drugs, can be conjugated (attached), immobilized, or encapsulated in a polymer matrix that is sensitive to specific environmental conditions (e.g. pH or temperature changes). Intelligent polymers can be divided according to their sensitivity to specific environmental stimuli such as temperature, pH, light, electric, magnetic, sound, or electromagnetic fields. Materials & methods—The first stage of the presented research concerned the synthesis of pH-sensitive polymeric carriers by a radical polymerization reaction. Then, the selected active substance (hydrocortisone) was introduced into polymeric carriers. In a further stage, bio-hybrid sodium alginate/poly(vinyl alcohol) – SA/PVA-based hydrogel matrices modified with various carrier-drug systems were prepared with the chemical cross-linking method. The conducted research included the assessment of physicochemical properties of obtained materials i.e. degree of hydrogel swelling and degradation studies as a function of pH in distilled water and phosphate-buffered saline (PBS) at 37°C in time. The gel fraction represents the insoluble gel fraction as a result of inter-molecule cross-linking formation was also measured. Additionally, the chemical structure of obtained hydrogels was confirmed using FT-IR spectroscopic technique. The dynamic light scattering (DLS) technique was used for the analysis of the average particle size of polymer-carriers and carrier-drug systems. The nanocarriers morphology was observed using SEM microscopy. Results & Discussion—The analysis of the encapsulated polymeric carriers showed that it was possible to obtain the time-stable empty pH-sensitive carrier with an average size 479 nm and the encapsulated system containing hydrocortisone with an average 543 nm, which was introduced into hydrogel structure. Bio-hybrid hydrogel matrices are stable materials, and the presence of an additional component: pH-sensitive carrier – hydrocortisone system, does not reduce the degree of cross-linking of the matrix nor its swelling ability. Moreover, the results of swelling tests indicate that systems containing higher concentrations of the drug have a slightly higher sorption capacity in each of the media used. All analyzed materials show stable and statically changing swelling values in simulated body fluids - there is no sudden fluid uptake and no rapid release from the material. The analysis of FT-IR spectra confirms the chemical structure of the obtained bio-hybrid hydrogel matrices. In the case of modifications with a pH-sensitive carrier, a much more intense band can be observed in the 3200-3500 cm⁻¹ range, which most likely originates from the strong hydrogen interactions that occur between individual components.

Keywords: hydrogels, polymer nanocarriers, sodium alginate/poly(vinyl alcohol) matrices, wound dressings.

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Authors: Peikun Zhang, Chunhua Cui

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Photoelectrochemical (PEC) water splitting provides a promising pathway to convert solar energy into renewable fuels. However, the main and seemingly insurmountable obstacle is that the sluggish kinetics of oxygen evolution reaction (OER) severely jeopardizes the overall efficiency, thus exploring highly active, stable, and appreciable catalysts is urgently requested. Herein a competitive coordination strategy was demonstrated to form a reversible hybrid homo-heterogeneous catalyst for efficient OER in alkaline media. The dynamic process involves an in-situ anchoring of soluble nickel–bipyridine pre-catalyst to a conductive substrate under OER and a re-dissolution course under open circuit potential, induced by the competitive coordination between nickel–bipyridine and nickel-hydroxyls. This catalyst allows to elaborately self-modulate a charge-transfer layer thickness upon the catalytic on-off operation, which affords substantially increased active sites, yet remains light transparency, and sustains the stability of over 200 hours of continuous operation. The integration of this catalyst with exemplified state-of-the-art Ni-sputtered Si photoanode can facilitate a ~250 mV cathodic shift at a current density of 20 mA cm-2. This finding helps the understanding of catalyst from a “dynamic” perspective, which represents a viable alternative to address remaining hurdles toward solar-driven water oxidation.

Keywords: molecular catalyst, oxygen evolution reaction, solar energy, transition metal complex, water splitting

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Authors: Hyunchul Ahn, William X. S. Wong

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Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

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Authors: Annette Louise Dupont

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Background and Introduction: Broadly defined, hybridity is a condition of racial and cultural ‘cross-pollination’ which arises as a result of contact between colonized and colonizer. It remains a highly contested concept in postcolonial studies as it is implicitly underpinned by colonial notions of ‘racial purity.’ While some postcolonial scholars argue that individuals exercise significant agency in the construction of their hybrid subjectivities, others underscore associated experiences of exclusion, marginalization, and alienation. Kuwait and the Philippines are among the most disparate of contemporary postcolonial states. While oil resources transformed the former British Mandate of Kuwait into one of the world’s richest countries, enduring poverty in the former US colony of the Philippines drives a global diaspora which produces multiple Filipino hybridities. Although more Filipinos work in the Arabian Gulf than in any other region of the world, scholarly and literary accounts of their experiences of hybridization in this region are relatively scarce when compared to those set in North America, Australia, Asia, and Europe. Study Aims and Significance: This paper aims to address this existing lacuna by investigating hybridity and other postcolonial themes in a novel by a Kuwaiti author which vividly portrays the lives of immigrants and citizens in Kuwait and which gives a rare voice and insight into the struggles of an Arab-Filipino and European-Filipina. Specifically, this paper explores the relationships between colonial discourses of ‘black’ and ‘white’ and postcolonial discourses pertaining to ‘brown’ Filipinos and ‘brown’ Arabs, in order to assess their impacts on the protagonists’ hybrid subjectivities. Methodology: Foucault’s notions of discourse not only provide a conceptual basis for analyzing the colonial ideology of Orientalism, but his theories related to the social exclusion of the ‘mad’ also elucidate the mechanisms by which power can operate to marginalize, alienate and subjectify the Other, therefore a Foucauldian lens is applied to the analysis of postcolonial themes and hybrid subjectivities portrayed in the novel. Findings: The study finds that Kuwaiti and Filipino discursive practices mirror those of former white colonialists and colonized black laborers and that these discursive practices combine with a former British colonial system of foreign labor sponsorship to create a form of governmentality in Kuwait which is based on exclusion and control. The novel’s rich social description and the reflections of the key protagonist and narrator suggest that such fiction has a significant role to play in highlighting the historical and cultural specificities of experiences of postcolonial hybridity in under-researched geographic, economic, social, and political settings. Whereas hybridity can appear abstract in scholarly accounts, the significance of literary accounts in which the lived experiences of hybrid protagonists are anchored to specific historical periods, places and discourses, is that contextual particularities are neither obscured nor dehistoricized. Conclusions: The application of Foucauldian theorizations of discourse, disciplinary, and biopower to the analysis of this Kuwaiti literary text serves to extend an understanding of the effects of contextually-specific discourses on hybrid Filipino subjectivities, as well as a knowledge of prevailing social dynamics in a little-researched postcolonial Arabian Gulf state.

Keywords: Filipino, Foucault, hybridity, Kuwait

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Authors: Namita Mittal, Himakshi Shekhawat, Ankit Vidyarthi

Abstract:

In medical research study, doctors and radiologists face lot of complexities in analysing the brain tumors in Magnetic Resonance (MR) images. Brain tumor detection is difficult due to amorphous tumor shape and overlapping of similar tissues in nearby region. So, radiologists require one such clinically viable solution which helps in automatic segmentation of tumor inside brain MR image. Initially, segmentation methods were used to detect tumor, by dividing the image into segments but causes loss of information. In this paper, a hybrid method is proposed which detect Region of Interest (ROI) on the basis of difference in intensity values and texture values of tumor region using nearby tissues with Gradient Vector Flow (GVF) technique in the identification of ROI. Proposed approach uses both intensity and texture values for identification of abnormal section of the brain MR images. Experimental results show that proposed method outperforms GVF method without any loss of information.

Keywords: brain tumor, GVF, intensity, MR images, segmentation, texture

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Authors: Mousa Meratizaman, Sina Monadizadeh, Majid Amidpour

Abstract:

One of the most favorable thermal desalination methods used widely today is Multi Effect Desalination. High energy consumption in this method causes coupling it with high temperature power cycle like gas turbine. This combination leads to higher energy efficiency. One of the high temperature power systems which have cogeneration opportunities is Solid Oxide Fuel Cell / Gas Turbine. Integration of Multi Effect Desalination with Solid Oxide Fuel Cell /Gas Turbine power cycle in a range of 300-1000 kW is considered in this article. The exhausted heat of Solid Oxide Fuel Cell /Gas Turbine power cycle is used in Heat Recovery Steam Generator to produce needed motive steam for Desalination unit. Thermodynamic simulation and parametric studies of proposed system are carried out to investigate the system performance.

Keywords: solid oxide fuel cell, thermodynamic simulation, multi effect desalination, gas turbine hybrid cycle

Procedia PDF Downloads 376

Authors: M. Akhlaque Ahmed, Sidra A. Shaikh, Maliha A. Siddiqui, Adeel Tahir

Abstract:

Global and diffuse solar radiation on horizontal surface of southern sindh namely Karachi, Hyderabad, Nawabshah were carried out using sunshine hour data of the area to asses the feasibility of solar Energy utilization at Sindh province for power generation. From the observation, result is derived which shows a drastic variation in the diffuse and direct component of solar radiation for summer and winter for Southern Sindh that is both contributes 50% for Karachi and Hyderabad. In Nawabshah area, the contribution of diffuse solar radiation is low in monsoon months, July and August. The Kᴛ value of Nawabshah indicates a clear sky almost throughout the year. The percentage of diffuse radiation does not exceed more than 20%. In Nawabshah, the appearance of cloud is rare even in monsoon months. The estimated values indicate that Nawabshah has high solar potential whereas Karachi and Hyderabad has low solar potential. During the monsoon months, the southern part of Sind can utilize the hybrid system with wind power. Near Karachi and Hyderabad, the wind speed ranges between 6.2 to 6.9 m/sec. There exist a wind corridor near Karachi, Hyderabad, Gharo, Keti Bander and Shah Bander. The short fall of solar can be compensated by wind because in monsoon months July and August the wind speed are higher in the southern region of Sindh.

Keywords: hybrid power system, power generation, solar and wind energy potential, southern Sindh

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Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

Abstract:

The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Faizan Khan, Xiaodong Yang

Abstract:

Internet Service Providers are driving endless demands for higher bandwidth and data throughput as new services and applications require higher bandwidth. Users want immediate and accurate data delivery. This article focuses on converting old conventional networks into passive optical networks based on time division and wavelength division multiplexing. The main focus of this research is to use a hybrid of time-division multiplexing and wavelength-division multiplexing to improve network efficiency and performance. In this paper, we design an 80 Gbps Passive Optical Network (PON), which meets the need of the Next Generation PON Stage 2 (NGPON2) proposed in this paper. The hybrid of the Time and Wavelength division multiplexing (TWDM) is said to be the best solution for the implementation of NGPON2, according to Full-Service Access Network (FSAN). To co-exist with or replace the current PON technologies, many wavelengths of the TWDM can be implemented simultaneously. By utilizing 8 pairs of wavelengths that are multiplexed and then transmitted over optical fiber for 40 Kms and on the receiving side, they are distributed among 256 users, which shows that the solution is reliable for implementation with an acceptable data rate. From the results, it can be concluded that the overall performance, Quality Factor, and bandwidth of the network are increased, and the Bit Error rate is minimized by the integration of this approach.

Keywords: bit error rate, fiber to the home, passive optical network, time and wavelength division multiplexing

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Authors: Jyothi P. Phatak, L. Venkatesha, C. S. Raviprasad

Abstract:

The performance improvement of Hybrid Energy Storage System (HESS) in Electric Vehicle (EV) has been in discussion over the last decade. The important issues in terms of performance parameters addressed are, range of vehicle and battery (BA) peak current. Published literature has either addressed battery peak current reduction or range improvement in EV. Both the issues have not been specifically discussed and analyzed. This paper deals with both range improvement in EV and battery peak current reduction by applying a new Karnaugh Map (K-Map) constructed rule based energy management strategy to proposed HESS. The strategy allows Ultracapacitor (UC) to assist battery when the vehicle accelerates there by reducing the burden on battery. Simulation is carried out for various operating modes of EV considering both urban and highway driving conditions. Simulation is done for different values of UC by keeping battery rating constant for each driving cycle and results are presented. Feasible value of UC is selected based on simulation results. The results of proposed HESS show an improvement in performance parameters compared to Battery only Energy Storage System (BESS). Battery life is improved to considerable extent and there is an overall development in the performance of electric vehicle.

Keywords: electric vehicle, PID controller, energy management strategy, range, battery current, ultracapacitor

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Authors: Nashrawan Naser Taha, Andrew M. Cox

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In a multi-cultural learning context, where ties are weak and dynamic, combining qualitative with quantitative research methods may be more effective. Such a combination may also allow us to answer different types of question, such as about people’s perception of the network. In this study the use of observation, interviews and photos were explored as ways of enhancing data from social network questionnaires. Integrating all of these methods was found to enhance the quality of data collected and its accuracy, also providing a richer story of the network dynamics and the factors that shaped these changes over time.

Keywords: mixed methods, social network analysis, multi-cultural learning, social network dynamics

Procedia PDF Downloads 508

Authors: Galina Mihaleva, C. Koh

Abstract:

Fashion, like many other design fields, undergoes numerous evolutions throughout the ages. This paper aims to recognize and evaluate the significance of advance technology in fashion design and examine how it changes the role of modern fashion designers by modifying the creation process. It also touches on how modern culture is involved in such developments and how it affects fashion design in terms of conceptualizing and fabrication. The methodology used is through surveying the various examples of technological applications to fashion design and drawing parallels between what was achievable then and what is achievable now. By comparing case studies, existing fashion design examples and crafting method experimentations; we then spot patterns in which to predict the direction of future developments in the field. A breakdown on the elements of technology in fashion design helps us understand the driving force behind such a trend. The results from explorations in the paper have shown that there is an observed pattern of a distinct increase in interest and progress in the field of fashion technology, which leads to the birth of hybrid crafting methods. In conclusion, it is shown that as fashion technology continues to evolve, their role in clothing crafting becomes more prominent and grows far beyond the humble sewing machine.

Keywords: fashion design, functional aesthetics, smart textiles, 3D printing

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Authors: Serkan Aras, Emrah Gulay

Abstract:

Combining various forecasting models is an important tool for researchers to attain more accurate forecasts. A great number of papers have shown that selecting single models as dissimilar models, or methods based on different information as possible leads to better forecasting performances. However, there is not a certain rule regarding the number of single models to be used in any combining methods. This study focuses on determining the optimal or near optimal number for single models with the help of statistical tests. An extensive experiment is carried out by utilizing some well-known time series data sets from diverse fields. Furthermore, many rival forecasting methods and some of the commonly used combining methods are employed. The obtained results indicate that some statistically significant performance differences can be found regarding the number of the single models in the combining methods under investigation.

Keywords: combined forecast, forecasting, M-competition, time series

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Authors: Manideepa Saha, Jahnavi Chakrabarty

Abstract:

Generalized Jacobi (GJ) and Generalized Gauss-Seidel (GGS) methods are most effective than conventional Jacobi and Gauss-Seidel methods for solving linear system of equations. It is known that GJ and GGS methods converge for strictly diagonally dominant (SDD) and for M-matrices. In this paper, we study the convergence of GJ and GGS converge for symmetric positive definite (SPD) matrices, L-matrices and H-matrices. We introduce a generalization of successive overrelaxation (SOR) method for solving linear systems and discuss its convergence for the classes of SDD matrices, SPD matrices, M-matrices, L-matrices and for H-matrices. Advantages of generalized SOR method are established through numerical experiments over GJ, GGS, and SOR methods.

Keywords: convergence, Gauss-Seidel, iterative method, Jacobi, SOR

Procedia PDF Downloads 186