Search results for: graph based scheduling

Authors: Andrea Bellucci, Martina Tofi

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The aim of paper is to analyze business models of bancassurance in Italy for life business. The life insurance business is very developed in the Italian market and banks branches have 80% of the market share. Given its maturity, the life insurance market needs to consolidate its organizational form to allow for the development of non-life business, which nowadays collects few premiums but represents a great opportunity to enlarge the market share of bancassurance using its strength in the distribution channel while the market share of independent agents is decreasing. Starting with the main business model of bancassurance for life business, this paper will analyze the performances of life companies in the Italian market by balance sheet indicators and by main discriminant variables of business models. The study will observe trends from 2013 to 2015 for the Italian market by exploiting a database managed by Associazione Nazionale delle Imprese di Assicurazione (ANIA). The applied approach is based on a bottom-up analysis starting with variables and indicators to define business models’ classification. The statistical classification algorithm proposed by Ward is employed to design business models’ profiles. Results from the analysis will be a representation of the main business models built by their profile related to indicators. In that way, an unsupervised analysis is developed that has the limit of its judgmental dimension based on research opinion, but it is possible to obtain a design of effective business models.

Keywords: bancassurance, business model, non life bancassurance, insurance business value drivers

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Authors: Saeidreza Radpour, Md. Alam Mondal, Amit Kumar

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Market penetration of high energy efficiency technologies has key impacts on energy consumption and GHG mitigation. Also, it will be useful to manage the policies formulated by public or private organizations to achieve energy or environmental targets. Energy intensity in residential sector of Alberta was 148.8 GJ per household in 2012 which is 39% more than the average of Canada 106.6 GJ, it was the highest amount among the provinces on per household energy consumption. Energy intensity by appliances of Alberta was 15.3 GJ per household in 2012 which is 14% higher than average value of other provinces and territories in energy demand intensity by appliances in Canada. In this research, a framework has been developed to analyze the market penetration and market share of high energy efficiency technologies in residential sector. The overall methodology was based on development of data-intensive models’ estimation of the market penetration of the appliances in the residential sector over a time period. The developed models were a function of a number of macroeconomic and technical parameters. Developed mathematical equations were developed based on twenty-two years of historical data (1990-2011). The models were analyzed through a series of statistical tests. The market shares of high efficiency appliances were estimated based on the related variables such as capital and operating costs, discount rate, appliance’s life time, annual interest rate, incentives and maximum achievable efficiency in the period of 2015 to 2050. Results show that the market penetration of refrigerators is higher than that of other appliances. The stocks of refrigerators per household are anticipated to increase from 1.28 in 2012 to 1.314 and 1.328 in 2030 and 2050, respectively. Modelling results show that the market penetration rate of stand-alone freezers will decrease between 2012 and 2050. Freezer stock per household will decline from 0.634 in 2012 to 0.556 and 0.515 in 2030 and 2050, respectively. The stock of dishwashers per household is expected to increase from 0.761 in 2012 to 0.865 and 0.960 in 2030 and 2050, respectively. The increase in the market penetration rate of clothes washers and clothes dryers is nearly parallel. The stock of clothes washers and clothes dryers per household is expected to rise from 0.893 and 0.979 in 2012 to 0.960 and 1.0 in 2050, respectively. This proposed presentation will include detailed discussion on the modelling methodology and results.

Keywords: appliances efficiency improvement, energy star, market penetration, residential sector

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Authors: Armanul Hoque Shaon, Md Baizid Mahmud, Askander Nobi, Md. Raju Ahmed, Md. Jiabul Hoque

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In the Internet of Things (IoT), devices are linked to the internet through a wireless network, allowing them to collect and transmit data without the need for a human operator. Agriculture relies heavily on wireless sensors, which are a vital component of the Internet of Things (IoT). This kind of wireless sensor network monitors physical or environmental variables like temperatures, sound, vibration, pressure, or motion without relying on a central location or sink and collaboratively passes its data across the network to be analyzed. As the primary source of plant nutrients, the soil is critical to the agricultural industry's continued growth. We're excited about the prospect of developing an Internet of Things (IoT) solution. To arrange the network, the sink node collects groundwater levels and sends them to the Gateway, which centralizes the data and forwards it to the sensor nodes. The sink node gathers soil moisture data, transmits the mean to the Gateways, and then forwards it to the website for dissemination. The web server is in charge of storing and presenting the moisture in the soil data to the web application's users. Soil characteristics may be collected using a networked method that we developed to improve rice production. Paddy land is running out as the population of our nation grows. The success of this project will be dependent on the appropriate use of the existing land base.

Keywords: IoT based agriculture monitoring, intelligent irrigation, communicating network, rice production

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Authors: Li Chin Law, Epaminondas Mastorakos, Mohd Roslee Othman, Antonis Trakakis

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The paper introduces an alternative concept of carbon capture for shipping by using pre-combustion carbon capture technology (Pre-CCS), which was proven to be less energy intensive than post-combustion carbon capture from the engine exhaust. Energy assessment on amine-based post-combustion CCS on LNG-fuelled ships showed that the energy efficiency of CCS ships reduced from 48% to 36.6%. Then, an energy assessment was carried out to compare the power and heat requirements of the most used hydrogen production methods and carbon capture technologies. Steam methane reformer (SMR) was found to be 20% more energy efficient and achieved a higher methane conversion than auto thermal reaction and methane decomposition. Next, pressure swing adsorber (PSA) has shown a lower energy requirement than membrane separation, cryogenic separation, and amine absorption in pre-combustion carbon capture. Hence, an integrated system combining SMR and PSA (SMR-PSA) with waste heat integration (WHR) was proposed. This optimized SMR-based integrated system has achieved 65% of CO₂ reduction with less than 7-percentage point of energy penalty (41.7% of energy efficiency). Further integration of post-combustion CCS with the SMR-PSA integrated system improved carbon capture rate to 86.3% with 9-percentage points of energy penalty (39% energy efficiency). The proposed system was shown to be able to meet the carbon reduction targets set by International Maritime Organization (IMO) with certain energy penalties.

Keywords: shipping, decarbonisation, alternative fuels, low carbon, hydrogen, carbon capture

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Authors: Büşra Durmaz, Füsun Curaoğlu

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While technology-oriented developments in the modern world change our perceptions of time and speed, they also force our food consumption patterns, such as getting pleasure from what we eat and eating slowly. The habit of eating quickly and hastily causes not only the feeling of not understanding the taste of the food eaten but also the inability to postpone the feeling of satiety and, therefore, many health problems. In this context, especially in the last ten years, in the field of industrial design, food manufacturers for healthy living and consumption have been collaborating with industrial designers on food design. The consumers of the new century, who are in an uncontrolled time intensity, receive support from small snacks as a source of happiness and pleasure in the little time intervals they can spare. At this point, especially chocolate has been a source of happiness for its consumers as a source of both happiness and pleasure for hundreds of years. However, when the portions have eaten cannot be controlled, a pleasure food such as chocolate can cause both health problems and many emotional problems, especially the feeling of guilt. Fast food, which is called food that is prepared and consumed quickly, has been increasing rapidly around the world in recent years. This study covers the process and results of a chocolate design based on the user experience of a university-industry cooperation project carried out within the scope of Eskişehir Technical University graduation projects. The aim of the project is a creative product design that will enable the user to experience chocolate consumption with a healthy eating approach. For this, while concepts such as pleasure, satiety, and taste are discussed; A survey with 151 people and semi-structured face-to-face interviews with 7 people during the experience design process within the scope of the user-oriented design approach, mainly literature review, within the scope of main topics such as mouth anatomy, tongue structure, taste, the functions of the eating action in the brain, hormones and chocolate, video A case study based on the research paradigm of Qualitative Research was structured within the scope of different research processes such as analysis and project diaries. As a result of the research, it has been reached that the melting in the mouth is the preferred experience of the users in order to spread the experience of eating chocolate for a long time based on pleasure while eating chocolate with healthy portions. In this context, researches about the production of sketches, mock-ups and prototypes of the product are included in the study. As a result, a product packaging design has been made that supports the active role of the senses such as sight, smell and hearing, where consumption begins, in order to consume chocolate by melting and to actively secrete the most important stimulus salivary glands in order to provide a healthy and long-term pleasure-based consumption.

Keywords: chocolate, eating habit, pleasure, saturation, sense of taste

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Authors: Zubair Ahmed, Andrea Barbieri

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The need to reduce energy consumption has prompted a considerable research effort for developing alternative energy-efficient lighting systems to replace conventional light sources (i.e., incandescent and fluorescent lamps). Organic light emitting device (OLED) technology offers the distinctive possibility to fabricate large area flat devices by vacuum or solution processing. Lanthanide β-diketonates complexes, due to unique photophysical properties of Ln(III) ions, have been explored as emitting layers in OLED displays and in solid-state lighting (SSL) in order to achieve high efficiency and color purity. For such applications, the excellent photoluminescence quantum yield (PLQY) and stability are the two key points that can be achieved simply by selecting the proper organic ligands around the Ln ion in a coordination sphere. Regarding the strategies to enhance the PLQY, the most common is the suppression of the radiationless deactivation pathways due to the presence of high-frequency oscillators (e.g., OH, –CH groups) around the Ln centre. Recently, a different approach to maximize the PLQY of Ln(β-DKs) has been proposed (named 'Escalate Coordination Anisotropy', ECA). It is based on the assumption that coordinating the Ln ion with different ligands will break the centrosymmetry of the molecule leading to less forbidden transitions (loosening the constraints of the Laporte rule). The OLEDs based on such complexes are available, but with low efficiency and stability. In order to get efficient devices, there is a need to develop some new Ln complexes with enhanced PLQYs and stabilities. For this purpose, the Ln complexes, both visible and (NIR) emitting, of variant coordination structures based on the various fluorinated/non-fluorinated β-diketones and O/N-donor neutral ligands were synthesized using a one step in situ method. In this method, the β-diketones, base, LnCl₃.nH₂O and neutral ligands were mixed in a 3:3:1:1 M ratio in ethanol that gave air and moisture stable complexes. Further, they were characterized by means of elemental analysis, NMR spectroscopy and single crystal X-ray diffraction. Thereafter, their photophysical properties were studied to select the best complexes for the fabrication of stable and efficient OLEDs. Finally, the OLEDs were fabricated and investigated using these complexes as emitting layers along with other organic layers like NPB,N,N′-Di(1-naphthyl)-N,N′-diphenyl-(1,1′-biphenyl)-4,4′-diamine (hole-transporting layer), BCP, 2,9-Dimethyl-4,7-diphenyl-1,10-phenanthroline (hole-blocker) and Alq3 (electron-transporting layer). The layers were sequentially deposited under high vacuum environment by thermal evaporation onto ITO glass substrates. Moreover, co-deposition techniques were used to improve charge transport in the devices and to avoid quenching phenomena. The devices show strong electroluminescence at 612, 998, 1064 and 1534 nm corresponding to ⁵D₀ →⁷F₂(Eu), ²F₅/₂ → ²F₇/₂ (Yb), ⁴F₃/₂→ ⁴I₉/₂ (Nd) and ⁴I1₃/₂→ ⁴I1₅/₂ (Er). All the devices fabricated show good efficiency as well as stability.

Keywords: electroluminescence, lanthanides, paramagnetic NMR, photoluminescence

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Authors: Getaneh Berie Tarekegn, Li-Chia Tai

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With the rapid advancement of artificial intelligence, low-power built-in sensors on Internet of Things devices, and communication technologies, location-aware services have become increasingly popular and have permeated every aspect of people’s lives. Global navigation satellite systems (GNSSs) are the default method of providing continuous positioning services for ground and aerial vehicles, as well as consumer devices (smartphones, watches, notepads, etc.). However, the environment affects satellite positioning systems, particularly indoors, in dense urban and suburban cities enclosed by skyscrapers, or when deep shadows obscure satellite signals. This is because (1) indoor environments are more complicated due to the presence of many objects surrounding them; (2) reflection within the building is highly dependent on the surrounding environment, including the positions of objects and human activity; and (3) satellite signals cannot be reached in an indoor environment, and GNSS doesn't have enough power to penetrate building walls. GPS is also highly power-hungry, which poses a severe challenge for battery-powered IoT devices. Due to these challenges, IoT applications are limited. Consequently, precise, seamless, and ubiquitous Positioning, Navigation and Timing (PNT) systems are crucial for many artificial intelligence Internet of Things (AI-IoT) applications in the era of smart cities. Their applications include traffic monitoring, emergency alarming, environmental monitoring, location-based advertising, intelligent transportation, and smart health care. This paper proposes a generative AI-based positioning scheme for large-scale wireless settings using fingerprinting techniques. In this article, we presented a novel semi-supervised deep convolutional generative adversarial network (S-DCGAN)-based radio map construction method for real-time device localization. We also employed a reliable signal fingerprint feature extraction method with t-distributed stochastic neighbor embedding (t-SNE), which extracts dominant features while eliminating noise from hybrid WLAN and long-term evolution (LTE) fingerprints. The proposed scheme reduced the workload of site surveying required to build the fingerprint database by up to 78.5% and significantly improved positioning accuracy. The results show that the average positioning error of GAILoc is less than 0.39 m, and more than 90% of the errors are less than 0.82 m. According to numerical results, SRCLoc improves positioning performance and reduces radio map construction costs significantly compared to traditional methods.

Keywords: location-aware services, feature extraction technique, generative adversarial network, long short-term memory, support vector machine

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Authors: Papon Thamvasupong, Kwanchanok Viravaidya-Pasuwat

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Osteoarthritis affects a lot of people worldwide. Local injection of glucosamine is one of the alternative treatment methods to replenish the natural lubrication of cartilage. However, multiple injections can potentially lead to possible bacterial infection. Therefore, a drug delivery system is desired to reduce the frequencies of injections. A hydrogel is one of the delivery systems that can control the release of drugs. Thermo-reversible hydrogels can be beneficial to the drug delivery system especially in the local injection route because this formulation can change from liquid to gel after getting into human body. Once the gel is in the body, it will slowly release the drug in a controlled manner. In this study, various formulations of Pluronic-based hydrogels were synthesized for the controlled release of glucosamine. One of the challenges of the Pluronic controlled release system is its fast dissolution rate. To overcome this problem, alginate and calcium sulfate (CaSO₄) were added to the polymer solution. The characteristics of the hydrogels were investigated including the gelation temperature, gelation time, hydrogel dissolution and glucosamine release mechanism. Finally, a mathematical model of glucosamine release from Pluronic-alginate-hyaluronic acid hydrogel was developed. Our results have shown that crosslinking Pluronic gel with alginate did not significantly extend the dissolution rate of the gel. Moreover, the gel dissolution profiles and the glucosamine release mechanisms were best described using the zeroth-order kinetic model, indicating that the release of glucosamine was primarily governed by the gel dissolution.

Keywords: controlled release, drug delivery system, glucosamine, pluronic, thermoreversible hydrogel

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Authors: Y. S. Darmanto, P. H. Riyadi, S. Susanti

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Recently, approximately 9.1 million people of 237.56 million of Indonesian population suffer diabetes. Such condition was caused by high rice consumption of most Indonesian people. It has been known that rice contains low amylose, high calorie, and possesses hyperglycemic properties. Through this study, we tried to solve that problem by creating a super food in order to provide an alternative healthy and balanced diet. We formulated Taro and Seaweed flour based analog rice that fortified by various fishes bone collagens. Corms of Taro contain easily digestible starch and seaweed is rich in fiber, vitamin, and mineral. That mixture was fortified with collagen-containing unique amino acids such as glysine, lysine, alanine, arginine, proline, and hydroxyprolin. Subsequently, super analog rice was characterized about its nutritional composition such are proximate analyses, water, dietary fiber and amylose content. Furthermore, its morphological structure was analyzed by using scanning electron microscopy while the level of consumer preferences was performed by hedonic test. Results demonstrated that fortification by using various fishes bone collagen into analog rice were significantly different in nutritional composition, morphological structure as well as its preferences. Thus, this study was expected as new avenue in functional food discovery especially in the treatment and prevention of diabetic diseases.

Keywords: analogue rice, taro, seaweed, collagen

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Authors: Akinbo Razak Yinka, Adesanya Kehinde Kazeem, Oladokun Oluwagbenga Peter

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Time series data are sequences of observations collected over a period of time. Such data can be used to predict health outcomes, such as disease progression, mortality, hospitalization, etc. The Statistical approach is based on mathematical models that capture the patterns and trends of the data, such as autocorrelation, seasonality, and noise, while Neural methods are based on artificial neural networks, which are computational models that mimic the structure and function of biological neurons. This paper compared both parametric and non-parametric time series models of patients treated for malaria in Maternal and Child Health Centres in Lagos State, Nigeria. The forecast methods considered linear regression, Integrated Moving Average, ARIMA and SARIMA Modeling for the parametric approach, while Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) Network were used for the non-parametric model. The performance of each method is evaluated using the Mean Absolute Error (MAE), R-squared (R2) and Root Mean Square Error (RMSE) as criteria to determine the accuracy of each model. The study revealed that the best performance in terms of error was found in MLP, followed by the LSTM and ARIMA models. In addition, the Bootstrap Aggregating technique was used to make robust forecasts when there are uncertainties in the data.

Keywords: ARIMA, bootstrap aggregation, MLP, LSTM, SARIMA, time-series analysis

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Authors: Anuradha Chug, Sunali Gandhi

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Regression Testing is a very expensive and time-consuming process carried out to ensure the validity of modified software. Due to the availability of insufficient resources to re-execute all the test cases in time constrained environment, efforts are going on to generate test data automatically without human efforts. Many search based techniques have been proposed to generate efficient, effective as well as optimized test data, so that the overall cost of the software testing can be minimized. The generated test data should be able to uncover all potential lapses that exist in the software or product. Inspired from the natural behavior of bat for searching her food sources, current study employed a meta-heuristic, search-based bat algorithm for optimizing the test data on the basis certain parameters without compromising their effectiveness. Mathematical functions are also applied that can effectively filter out the redundant test data. As many as 50 Java programs are used to check the effectiveness of proposed test data generation and it has been found that 86% saving in testing efforts can be achieved using bat algorithm while covering 100% of the software code for testing. Bat algorithm was found to be more efficient in terms of simplicity and flexibility when the results were compared with another nature inspired algorithms such as Firefly Algorithm (FA), Hill Climbing Algorithm (HC) and Ant Colony Optimization (ACO). The output of this study would be useful to testers as they can achieve 100% path coverage for testing with minimum number of test cases.

Keywords: regression testing, test case selection, test case prioritization, genetic algorithm, bat algorithm

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Authors: K. Melouk, M. Dellakrachaï

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Analytical formula for the optical gain based on a simple parabolic-band by introducing theoretical expressions for the quantized energy is presented. The model used in this treatment take into account the effects of intraband relaxation. It is shown, as a result, that the gain for the TE mode is larger than that for TM mode and the presence of acceptor impurity increase the peak gain.

Keywords: InGaAsP, laser, quantum well, semiconductor

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Authors: Ana Elvira Ojanguren Lopez, Javier Martin Arista

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The aims of this paper are to present the automatisation procedure adopted in the implementation of a parallel corpus of Old English, as well as, to assess the progress of automatisation with respect to tagging, annotation, and lemmatisation. The corpus consists of an aligned parallel text with word-for-word comparison Old English-English that provides the Old English segment with inflectional form tagging (gloss, lemma, category, and inflection) and lemma annotation (spelling, meaning, inflectional class, paradigm, word-formation and secondary sources). This parallel corpus is intended to fill a gap in the field of Old English, in which no parallel and/or lemmatised corpora are available, while the average amount of corpus annotation is low. With this background, this presentation has two main parts. The first part, which focuses on tagging and annotation, selects the layouts and fields of lexical databases that are relevant for these tasks. Most information used for the annotation of the corpus can be retrieved from the lexical and morphological database Nerthus and the database of secondary sources Freya. These are the sources of linguistic and metalinguistic information that will be used for the annotation of the lemmas of the corpus, including morphological and semantic aspects as well as the references to the secondary sources that deal with the lemmas in question. Although substantially adapted and re-interpreted, the lemmatised part of these databases draws on the standard dictionaries of Old English, including The Student's Dictionary of Anglo-Saxon, An Anglo-Saxon Dictionary, and A Concise Anglo-Saxon Dictionary. The second part of this paper deals with lemmatisation. It presents the lemmatiser Norna, which has been implemented on Filemaker software. It is based on a concordance and an index to the Dictionary of Old English Corpus, which comprises around three thousand texts and three million words. In its present state, the lemmatiser Norna can assign lemma to around 80% of textual forms on an automatic basis, by searching the index and the concordance for prefixes, stems and inflectional endings. The conclusions of this presentation insist on the limits of the automatisation of dictionary-based annotation in a parallel corpus. While the tagging and annotation are largely automatic even at the present stage, the automatisation of alignment is pending for future research. Lemmatisation and morphological tagging are expected to be fully automatic in the near future, once the database of secondary sources Freya and the lemmatiser Norna have been completed.

Keywords: corpus linguistics, historical linguistics, old English, parallel corpus

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Authors: Mehdi Mirzaei Alavijeh, Farzad Jalilian

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Background: Marijuana is the most widely used illicit drug worldwide, especially among adolescents and young adults, which can cause numerous complications. The aim of this study was to determine the pattern, motivation use, and factors related to marijuana use among Iranian youths based on the integrative model of behavioral prediction Methods: A cross-sectional study was conducted among 174 youths marijuana user in Kermanshah County and Isfahan County, during summer 2014 which was selected with the convenience sampling for participation in this study. A self-reporting questionnaire was applied for collecting data. Data were analyzed by SPSS version 21 using bivariate correlations and linear regression statistical tests. Results: The mean marijuana use of respondents was 4.60 times at during week [95% CI: 4.06, 5.15]. Linear regression statistical showed, the structures of integrative model of behavioral prediction accounted for 36% of the variation in the outcome measure of the marijuana use at during week (R2 = 36% & P < 0.001); and among them attitude, marijuana refuse, and subjective norms were a stronger predictors. Conclusion: Comprehensive health education and prevention programs need to emphasize on cognitive factors that predict youth’s health-related behaviors. Based on our findings it seems, designing educational and behavioral intervention for reducing positive belief about marijuana, marijuana self-efficacy refuse promotion and reduce subjective norms encourage marijuana use has an effective potential to protect youths marijuana use.

Keywords: marijuana, youth, integrative model of behavioral prediction, Iran

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Authors: Junie B. Billones, Maria Constancia O. Carrillo, Voltaire G. Organo, Stephani Joy Y. Macalino, Inno A. Emnacen, Jamie Bernadette A. Sy

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One of the major interferences in the Philippines’ tuberculosis control program is the widespread prevalence of Mtb strains that are resistant to known drugs, such as the MDR-TB (Multi Drug Resistant Tuberculosis) and XDR-TB (Extensively Drug Resistant Tuberculosis). Therefore, there is a pressing need to search for novel Mtb drug targets in order to be able to combat these drug resistant strains. The enzyme 7,8-diaminopelargonic acid aminotransferase enzyme, or more commonly known as BioA, is one such ideal target, as it is known that humans do not possess this enzyme. BioA primarily plays a key role in Mtb’s lipid biosynthesis pathway; more specifically in the synthesis of the enzyme cofactor biotin. In this study, structure-based pharmacophore screening, docking, and ADMET evaluation of compounds obtained from the DrugBank chemical database were performed against the MtbBioA enzyme. Results of the screening, docking, ADMET, and TOPKAT calculations revealed that out of the 6,516 compounds in the library, only 7 compounds indicated more favorable binding energies as compared to the enzyme’s known inhibitor, amiclenomycin (ACM), as well as good solubility and toxicity properties. Moreover, out of these 7 compounds, Molecule 6 exhibited the best solubility and toxicity properties. In the future, these lead compounds may then be subjected to bioactivity assays in vitro or in vivo for further evaluation of its therapeutic efficacy.

Keywords: 7, 8-diaminopelargonic acid aminotransferase, BioA, pharmacophore, molecular docking, ADMET, TOPKAT

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Authors: Zhehao Zhang

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Walking has become an indispensable and sustainable way of travel for college students in their daily lives; campus street is an important carrier for students to walk and take part in a variety of activities, improving the walkability of campus streets plays an important role in optimizing the quality of campus space environment, promoting the campus walking system and inducing multiple walking behaviors. The purpose of this paper is to explore the effect of campus layout, facility distribution, and location site selection on the walkability of campus streets, and assess the street design qualities from the elements of imageability, enclosure, complexity, transparency, and human scale, and further examines the relationship between street-level urban design perceptual qualities and walkability and its effect on walking behavior in the campus. Taking Tianjin University as the research object, this paper uses the optimized walk score method based on walking frequency, variety, and distance to evaluate the walkability of streets from a macro perspective and measures the urban design qualities in terms of the calculation of street physical environment characteristics, as well as uses behavior annotation and street image data to establish temporal and spatial behavior database to analyze walking activity from the microscopic view. In addition, based on the conclusions, the improvement and design strategy will be presented from the aspects of the built walking environment, street vitality, and walking behavior.

Keywords: walkability, streetscapes, pedestrian activity, walk score

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Authors: Muhammad L. A. Dwiyoga

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The condition of a spatial land in the industrial park needs special attention to be studied more deeply. Geoplanology modeling can help arrange area according to his ability. This research method is to perform the analysis of remote sensing, Geographic Information System, and more comprehensive analysis to determine geological characteristics and the ability to land on the area of research and its relation to the geological disaster. Cilegon is part of Banten province located in western Java, and the direction of the north is the Strait of Borneo. While the southern part is bordering the Indian Ocean. Morphology study area is located in the highlands to low. In the highlands of identified potential landslide prone, whereas in low-lying areas of potential flooding. Moreover, in the study area has the potential prone to earthquakes, this is due to the proximity of enough research to Mount Krakatau and Subdcution Zone. From the results of this study show that the study area has a susceptibility to landslides located around the District Waringinkurung. While the region as a potential flood areas in the District of Cilegon and surrounding areas. Based on the seismic data, this area includes zones with a range of magnitude 1.5 to 5.5 magnitude at a depth of 1 to 60 Km. As for the ability of its territory, based on the analyzes and studies carried out the need for renewal of the map Spatial Plan that has been made, considering the development of a fairly rapid Cilegon area.

Keywords: geoplanology, spatial plan, geological hazard, cilegon, Indonesia

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Authors: Vanessa Kummer, Maik Meusel

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Real estate demand estimates are typically derived from transaction data. However, in regions with excess demand, transactions are driven by supply and therefore do not indicate what people are actually looking for. To estimate the demand for housing in Switzerland, search subscriptions from all important Swiss real estate platforms are used. These data do, however, suffer from missing information—for example, many users do not specify how many rooms they would like or what price they would be willing to pay. In economic analyses, it is often the case that only complete data is used. Usually, however, the proportion of complete data is rather small which leads to most information being neglected. Also, the data might have a strong distortion if it is complete. In addition, the reason that data is missing might itself also contain information, which is however ignored with that approach. An interesting issue is, therefore, if for economic analyses such as the one at hand, there is an added value by using the whole data set with the imputed missing values compared to using the usually small percentage of complete data (baseline). Also, it is interesting to see how different algorithms affect that result. The imputation of the missing data is done using unsupervised learning. Out of the numerous unsupervised learning approaches, the most common ones, such as clustering, principal component analysis, or neural networks techniques are applied. By training the model iteratively on the imputed data and, thereby, including the information of all data into the model, the distortion of the first training set—the complete data—vanishes. In a next step, the performances of the algorithms are measured. This is done by randomly creating missing values in subsets of the data, estimating those values with the relevant algorithms and several parameter combinations, and comparing the estimates to the actual data. After having found the optimal parameter set for each algorithm, the missing values are being imputed. Using the resulting data sets, the next step is to estimate the willingness to pay for real estate. This is done by fitting price distributions for real estate properties with certain characteristics, such as the region or the number of rooms. Based on these distributions, survival functions are computed to obtain the functional relationship between characteristics and selling probabilities. Comparing the survival functions shows that estimates which are based on imputed data sets do not differ significantly from each other; however, the demand estimate that is derived from the baseline data does. This indicates that the baseline data set does not include all available information and is therefore not representative for the entire sample. Also, demand estimates derived from the whole data set are much more accurate than the baseline estimation. Thus, in order to obtain optimal results, it is important to make use of all available data, even though it involves additional procedures such as data imputation.

Keywords: demand estimate, missing-data imputation, real estate, unsupervised learning

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Authors: J. Bahrawi, M. Elhag

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Estimation of evapotranspiration is always a major component in water resources management. Traditional techniques of calculating daily evapotranspiration based on field measurements are valid only for local scales. Earth observation satellite sensors are thus used to overcome difficulties in obtaining daily evapotranspiration measurements on regional scale. The Surface Energy Balance System (SEBS) model was adopted to estimate daily evapotranspiration and relative evaporation along with other land surface energy fluxes. The model requires agro-climatic data that improve the model outputs. Advance Along Track Scanning Radiometer (AATSR) and Medium Spectral Resolution Imaging Spectrometer (MERIS) imageries were used to estimate the daily evapotranspiration and relative evaporation over the entire Nile Delta region in Egypt supported by meteorological data collected from six different weather stations located within the study area. Daily evapotranspiration maps derived from SEBS model show a strong agreement with actual ground-truth data taken from 92 points uniformly distributed all over the study area. Moreover, daily evapotranspiration and relative evaporation are strongly correlated. The reliable estimation of daily evapotranspiration supports the decision makers to review the current land use practices in terms of water management, while enabling them to propose proper land use changes.

Keywords: daily evapotranspiration, relative evaporation, SEBS, AATSR, MERIS, Nile Delta

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Authors: Sonam Behl, Raju, Ginu Rajan, Paul Farrar, B. Gangadhara Prusty

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Reinforcing dental composites with micro-sized fibres can significantly improve the physio-mechanical properties of dental composites. The short fibres can be oriented randomly within dental composites, thus providing quasi-isotropic reinforcing efficiency unlike unidirectional/bidirectional fibre reinforced composites enhancing anisotropic properties. Thus, short fibres reinforced dental composites are getting popular among practitioners. However, despite their popularity, resin-based dental composites are prone to failure on account of shrinkage during photo polymerisation. The shrinkage in the structure may lead to marginal gap formation, causing secondary caries, thus ultimately inducing failure of the restoration. The traditional methods to evaluate polymerisation shrinkage using strain gauges, density-based measurements, dilatometer, or bonded-disk focuses on average value of volumetric shrinkage. Moreover, the results obtained from traditional methods are sensitive to the specimen geometry. The present research aims to evaluate the real-time shrinkage strain at selected locations in the material with the help of optical fibre Bragg grating (FBG) sensors. Due to the miniature size (diameter 250 µm) of FBG sensors, they can be easily embedded into small samples of dental composites. Furthermore, an FBG array into the system can map the real-time shrinkage strain at different regions of the composite. The evaluation of real-time monitoring of shrinkage values may help to optimise the physio-mechanical properties of composites. Previously, FBG sensors have been able to rightfully measure polymerisation strains of anisotropic (unidirectional or bidirectional) reinforced dental composites. However, very limited study exists to establish the validity of FBG based sensors to evaluate volumetric shrinkage for randomly oriented fibres reinforced composites. The present study aims to fill this research gap and is focussed on establishing the usage of FBG based sensors for evaluating the shrinkage of dental composites reinforced with randomly oriented fibres. Three groups of specimens were prepared by mixing the resin (80% UDMA/20% TEGDMA) with 55% of silane treated BaAlSiO₂ particulate fillers or by adding 5% of micro-sized fibres of diameter 5 µm, and length 250/350 µm along with 50% of silane treated BaAlSiO₂ particulate fillers into the resin. For measurement of polymerisation shrinkage strain, an array of three fibre Bragg grating sensors was embedded at a depth of 1 mm into a circular Teflon mould of diameter 15 mm and depth 2 mm. The results obtained are compared with the traditional method for evaluation of the volumetric shrinkage using density-based measurements. Degree of conversion was measured using FTIR spectroscopy (Spotlight 400 FT-IR from PerkinElmer). It is expected that the average polymerisation shrinkage strain values for dental composites reinforced with micro-sized fibres can directly correlate with the measured degree of conversion values, implying that more C=C double bond conversion to C-C single bond values also leads to higher shrinkage strain within the composite. Moreover, it could be established the photonics approach could help assess the shrinkage at any point of interest in the material, suggesting that fibre-Bragg grating sensors are a suitable means for measuring real-time polymerisation shrinkage strain for randomly fibre reinforced dental composites as well.

Keywords: dental composite, glass fibre, polymerisation shrinkage strain, fibre-Bragg grating sensors

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Authors: Farzaneh Badinlou, Reza Kormi-Nouri, Monika Knopf, Kamal Kharrazi

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When we teach, we have two critical elements at our disposal to help students: learning styles as well as testing styles. There are many different ways in which educators can effectively teach their students; verbal learning and experience-based learning. Lecture as a form of verbal learning style is a traditional arrangement in which teachers are more active and share information verbally with students. In experienced-based learning as the process of through, students learn actively through hands-on learning materials and observing teachers or others. Meanwhile, standard testing or assessment is the way to determine progress toward proficiency. Teachers and instructors mainly use essay (requires written responses), multiple choice questions (includes the correct answer and several incorrect answers as distractors), or open-ended questions (respondents answers it with own words). The current study focused on exploring an effective teaching style and testing methods as the function of age over school ages. In the present study, totally 410 participants were selected randomly from four grades (2ⁿᵈ, 4ᵗʰ, 6ᵗʰ, and 8ᵗʰ). Each subject was tested individually in one session lasting around 50 minutes. In learning tasks, the participants were presented three different instructions for learning materials (learning by doing, learning by observing, and learning by listening). Then, they were tested via different standard assessments as free recall, cued recall, and recognition tasks. The results revealed that generally students remember more of what they do and what they observe than what they hear. The age effect was more pronounced in learning by doing than in learning by observing, and learning by listening, becoming progressively stronger in the free-recall, cued-recall, and recognition tasks. The findings of this study indicated that learning by doing and free recall task is more age sensitive, suggesting that both of them are more strategic and more affected by developmental differences. Pedagogically, these results denoted that learning by modeling and engagement in program activities have the special role for learning. Moreover, the findings indicated that the multiple-choice questions can produce the best performance for school-aged children but is less age-sensitive. By contrast, the essay as essay can produce the lowest performance but is more age-sensitive. It will be very helpful for educators to know that what types of learning styles and test methods are most effective for students in each school grade.

Keywords: experience-based learning, learning style, school-aged children, testing methods, verbal learning

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Authors: Nazli Uren, Ayse Okur

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Tactile comfort of a textile product is an essential property and a major concern when it comes to customer perceptions and preferences. The subjective nature of comfort and the difficulties regarding the simulation of human hand sensory feelings make it hard to establish a well-accepted link between tactile comfort and objective evaluations. On the other hand, shear behavior of a fabric is a mechanical parameter which can be measured by various objective test methods. The principal aim of this study is to determine the tactile comfort of commercially available denim fabrics by subjective measurements, create a tactile score database for denim fabrics and investigate the relations between tactile comfort and shear behavior. In-plane shear behaviors of 17 different commercially available denim fabrics with a variety of raw material and weave structure were measured by a custom design shear frame and conventional bias extension method in two corresponding diagonal directions. Tactile comfort of denim fabrics was determined via subjective customer evaluations as well. Aforesaid relations were statistically investigated and introduced as regression equations. The analyses regarding the relations between tactile comfort and shear behavior showed that there are considerably high correlation coefficients. The suggested regression equations were likewise found out to be statistically significant. Accordingly, it was concluded that the tactile comfort of denim fabrics can be estimated with a high precision, based on the results of in-plane shear behavior measurements.

Keywords: denim fabrics, in-plane shear behavior, linear regression estimation, tactile comfort

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Authors: Thuy Phan, Stephanie Luallin

Abstract:

Inclusive education policies have demonstrated benefits for students with and without disabilities in the US. There are several laws that relate to inclusive education, such as 'No Child Left Behind', 'The Individuals with Disabilities Education Act'. However, the application of these inclusive education laws and policies vary per state and school district. Classroom teachers in an inclusive classroom often experience confusion as to how to apply these policies in order to create appropriate inclusive learning environments that meet the abilities and needs of their diverse student population. The study aims to investigate teachers’ perspective of their capacities to create an appropriate learning environment for their diverse student population including students with disabilities. Qualitative method is implemented in this study, using open-end interview questions to investigate teachers’ perspective of their capacities to create an appropriate inclusive learning environment for all students based on current inclusive education laws and district policies in the state of Colorado, USA. These findings may indicate a lack of confidence in teachers’ capacity to create appropriate inclusive learning environments based on laws and district policies; including challenges that classroom teachers may experience in creating inclusive learning environments. The purpose of this study is to examine the adequate preparation of classroom teachers in creating inclusive classrooms with the intent of determining implications for developing policies in inclusive education.

Keywords: educator’s capacity, inclusive education, inclusive learning environment, policy

Procedia PDF Downloads 169

Authors: Neda Azimi, Masoud Rahimi, Faezeh Mohammadi

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Computational fluid dynamics (CFD) simulation was performed to investigate the effect of ferrofluid stimulation on hydrodynamic and mass transfer characteristics of two immiscible liquid phases in a Y-micromixer. The main purpose of this work was to develop a numerical model that is able to simulate hydrodynamic of the ferrofluid flow under magnetic field and determine its effect on mass transfer characteristics. A uniform external magnetic field was applied perpendicular to the flow direction. The volume of fluid (VOF) approach was used for simulating the multiphase flow of ferrofluid and two-immiscible liquid flows. The geometric reconstruction scheme (Geo-Reconstruct) based on piecewise linear interpolation (PLIC) was used for reconstruction of the interface in the VOF approach. The mass transfer rate was defined via an equation as a function of mass concentration gradient of the transported species and added into the phase interaction panel using the user-defined function (UDF). The magnetic field was solved numerically by Fluent MHD module based on solving the magnetic induction equation method. CFD results were validated by experimental data and good agreements have been achieved, which maximum relative error for extraction efficiency was about 7.52 %. It was showed that ferrofluid actuation by a magnetic field can be considered as an efficient mixing agent for liquid-liquid two-phase mass transfer in microdevices.

Keywords: CFD modeling, hydrodynamic, micromixer, ferrofluid, mixing

Procedia PDF Downloads 195

Authors: Badr M. Thamer

Abstract:

The use of hydrogels as adsorbents for pollutants removal from wastewater is limited due to their high swelling properties and the difficulty in recovering them after the adsorption process. To overcome these problems, a new hydrogel nanocomposite based on chitosan-g-polyacrylic acid/oxidized electrospun carbon nanofibers (CT-g-PAA/O-ECNFs) was prepared by in-situ grafting polymerization process. The prepared hydrogel nanocomposite was used as a novel effective and highly reusable adsorbent for the removal of methylene blue (MB) from polluted water with low cost. The morphology and the structure of CT-g-PAA/O-ECNFs were investigated by numerous techniques. The effect of incorporating O-ECNFs on the swelling capability of the prepared hydrogel was explored in distillated water and MB solution at normal pH. The effect of parameters including the ratio of O-ECNFs, contact time, pH, initial concentration, and temperature on the adsorption process were explored. The adsorption isotherm and kinetic were studied by numerous non-linear models. The obtained results confirmed that the incorporation of O-ECNFs into the hydrogel network improved its ability towards MB dye removal with decreasing their swelling capacity. The adsorption process depends on the pH value of the dye solution. Additionally, the adsorption and kinetic results were fitted using the Freundlich isotherm model and pseudo second order model (PSO), respectively. Moreover, the new adsorbents can be recycled for at least five cycles keeping its adsorption capacity and can be easily recovered without loss in its initial weight.

Keywords: carbon nanofibers, hydrogels, nanocomposites, water treatment

Procedia PDF Downloads 145

Authors: V. Charaia

Abstract:

From the strategic point of view, not all Foreign Direct Investments (FDIs) are always positively benefiting the host economy, i.e. not all Multinational Enterprises (MNEs) are promoting local/host economies. FDI could have different impact on different sectors of the economy, based not only on annual investment amount, but MNE motivations and peculiarities of the host economy in particular. FDI analysis based only on its amount can lead to incorrect decisions, it is much more important to understand the essence of investment. Consequently, our research is oriented on MNE’s motivations, answering which sectors are most popular among international investors and why, what motivated them to invest into one or another business. Georgian economy for the last period of time is attracting more and more efficiency seeking investments, which could be translated as - concentrating production in a limited number of locations to supply various markets, while benefiting local economy with: new technologies, employment, exports diversification, increased income for the local economy and so on. Foreign investors and MNEs in particular are no longer and not so much interested in the resource seeking investments, which was the case for Georgia in the last decade of XX century. Despite the fact of huge progress for the Georgian economy, still there is a room for foreign investors to make a local market oriented investments. The local market is still rich in imported products, which should be replaced by local ones. And the last but not the least important issue is that approximately 30% of all FDIs in Georgia according to this research are “efficiency seeking” investments, which is an enormous progress and a hope for future Georgian success.

Keywords: investments, MNE, FDI motivations, Georgian economy

Procedia PDF Downloads 331

Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other. As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO

Procedia PDF Downloads 442

Authors: Wessam H. Abd-Elsalam, Mona M. Saber, Samar M. Abouelatta

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Non-steroidal anti-inflammatory drugs (NSAIDs) are considered a double edged sword in inflammatory bowel diseases (IBDs). Some studies reported their advantageous effect in decreasing inflammation, and other studies reported that their use is associated with colitis aggravation. This study aimed to use specifically formulated trehalose-based nano-carriers that targets the colon in an attempt to alleviate inflammation caused by NSAIDs. L-α-phosphatidylcholine (PL), trehalose, and transcutol were used to prepare the trehalosomes (THs), which were also loaded with Tenoxicam(TXM) as a model NSAID. To optimize the formulation variables, a full 23 factorial design, using Design-Expert® software, was performed. The optimized formulation composed of trehalose: PL at a weight ratio of 1:1, 377.72 mg transcutol, and sonicated for 4 min, possessed a spherical shape with a size of 268.61 nm and EE% of 97.83% and released 70.22% of its drug content over 24 h. The superior protective action of TXM loaded THs compared to TXM suspension and drug-free THs was shown by the inhibition of the inflammatory biomarkers, namely; IL-1ß, IL-6, and TNF-alpha levels, as well as oxidative stress markers, measured as GSH and MDA. Improved histopathology of the colonic tissue in male New Zealand rabbits also confirmed the superiority of the TXM loaded THs compared to the unformulated drug or the drug free nano-carriers. Our findings highlight the prosperous role of THs in colon targeting and its anti-inflammatory characteristics in guarding against possible NSAIDs-driven exacerbation of colitis.

Keywords: inflammatory bowel disease, trehalose, trehalosomes, colon targeting

Procedia PDF Downloads 136

Authors: Hooman Dabirmanesh, Attila M. Zsaki

Abstract:

The toppling failure mode in a rock mass is considerably different from the most common sliding failure type along an existing or an induced slip plane. Block toppling is observed in a rock mass which consists of both a widely-spaced basal cross-joint set and a closely-spaced discontinuity set dipping into the slope. For this case, failure occurs when the structure cannot bear the tensile portion of bending stress, and the columns or blocks overturn by their own weight. This paper presents a particle-based discrete element model of rock blocks subjected to a toppling failure where geometric conditions and interaction among blocks are investigated. A series of parametric studies have been conducted on particles’ size, arrangement and bond contact among of particles which are made the blocks. Firstly, a numerical investigation on a one-block system was verified. Afterward, a slope consisting of multi-blocks was developed to study toppling failure and interaction forces between blocks. The results show that the formation of blocks, especially between the block and basal plane surface, can change the process of failure. The results also demonstrate that the initial configuration of particles used to form the blocks has a significant role in achieving accurate simulation results. The size of particles and bond contacts have a considerable influence to change the progress of toppling failure.

Keywords: block toppling failure, contact interaction, discrete element, particle size, random generation

Procedia PDF Downloads 200

Authors: Betim Bahtiri, B. Arash, R. Rolfes

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Epoxy-based materials are frequently exposed to high-humidity environments in many engineering applications. As a result, their material properties would be degraded by water absorption. A full characterization of the material properties under hygrothermal conditions requires time- and cost-consuming experimental tests. To gain insights into the physics of diffusion mechanisms, atomistic simulations have been shown to be effective tools. Concerning the diffusion of water in polymers, spatial trajectories of water molecules are obtained from molecular dynamics (MD) simulations allowing the interpretation of diffusion pathways at the nanoscale in a polymer network. Conventional MD simulations of water diffusion in amorphous polymers lead to discrepancies at low temperatures due to the short timescales of the simulations. In the proposed model, this issue is solved by using a combined scheme of autonomous basin climbing (ABC) with kinetic Monte Carlo and reactive MD simulations to investigate the diffusivity of water molecules in epoxy resins across a wide range of temperatures. It is shown that the proposed simulation framework estimates kinetic properties of water diffusion in epoxy resins that are consistent with experimental observations and provide a predictive tool for investigating the diffusion of small molecules in other amorphous polymers.

Keywords: epoxy resins, water diffusion, autonomous basin climbing, kinetic Monte Carlo, reactive molecular dynamics

Procedia PDF Downloads 64