Search results for: times series analysis

Authors: Mojtaba Ghodsi, Hamidreza Ziaifar, Morteza Mohammadzaheri, Payam Soltani

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This article presents an analytical model to estimate the harvested power from a Magnetostrictive cantilevered beam with tip excitation. Furthermore, the effects of internal and external damping on harvested power are investigated. The magnetostrictive material in this harvester is Galfenol. In comparison to other popular smart materials like Terfenol-D, Galfenol has higher strength and machinability. In this article, first, a mechanical model of the Euler-Bernoulli beam is employed to calculate the deflection of the harvester. Then, the magneto-mechanical equation of Galfenol is combined with Faraday's law to calculate the generated voltage of the Magnetostrictive cantilevered beam harvester. Finally, the beam model is incorporated in the aforementioned combination. The results show that a 30×8.5×1 mm Galfenol cantilever beam harvester with 80 turn pickup coil can generate up to 3.7 mV and 9 mW. Furthermore, sensitivity analysis made by Response Surface Method (RSM) shows that the harvested power is only sensitive to the internal damping coefficient.

Keywords: internal damping coefficient, external damping coefficient, euler-bernoulli, energy harvester, galfenol, magnetostrictive, response surface method

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Authors: Smita Pareek, Ratna Dahiya

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The power generated by solar photovoltaic (PV) module depends on surrounding irradiance, temperature, shading conditions, and shading pattern. This paper presents a simulation of photovoltaic module using Matlab/Simulink. PV Array is also simulated by series and parallel connections of modules and their characteristics curves are given. Further PV module topology/configuration are proposed for 5.5kW inverter available in the literature. Shading of a PV array either complete or partial can have a significant impact on its power output and energy yield; therefore, the simulated model characteristics curves (I-V and P-V) are drawn for uniform shading conditions (USC) and then output power, voltage and current are calculated for variation in insolation for shading conditions. Additionally the characteristics curves are also given for a predetermined shadowing condition.

Keywords: array, series, parallel, photovoltaic, partial shading

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Authors: Jadwiga Fila, Mateusz Jezowski, Pawel Poszytek

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The outbreak of the global COVID-19 pandemic started the times of crisis full of uncertainty, especially in the field of transnational cooperation projects based on the international mobility of their participants. This is notably the case of Erasmus+ Program for higher education, which is the flagship European initiative boosting cooperation between educational institutions, businesses, and other actors, enabling students and staff mobility, as well as strategic partnerships between different parties. The aim of this abstract is to study whether competences 4.0 are able to empower Erasmus+ project leaders in sustaining their international cooperation in times of global crisis, widespread online learning, and common project disruption or cancellation. The concept of competences 4.0 emerged from the notion of the industry 4.0, and it relates to skills that are fundamental for the current labor market. For the aim of the study presented in this abstract, four main 4.0 competences were distinguished: digital, managerial, social, and cognitive competence. The hypothesis for the study stipulated that the above-mentioned highly-developed competences may act as a protective shield against the pandemic challenges in terms of projects’ sustainability and continuation. The objective of the research was to assess to what extent individual competences are useful in managing projects in times of crisis. For this purpose, the study was conducted, involving, among others, 141 Polish higher education project leaders who were running their cooperation projects during the peak of the COVID-19 pandemic (Mar-Nov 2020). The research explored the self-perception of the above-mentioned competences among Erasmus+ project leaders and the contextual data regarding the sustainability of the projects. The quantitative character of data permitted validation of scales (Cronbach’s Alfa measure), and the use of factor analysis made it possible to create a distinctive variable for each competence and its dimensions. Finally, logistic regression was used to examine the association of competences and other factors on project status. The study shows that the project leaders’ competence profile attributed the highest score to digital competence (4.36 on the 1-5 scale). Slightly lower values were obtained for cognitive competence (3.96) and managerial competence (3.82). The lowest score was accorded to one specific dimension of social competence: adaptability and ability to manage stress (1.74), which proves that the pandemic was a real challenge which had to be faced by project coordinators. For higher education projects, 10% were suspended or prolonged because of the COVID-19 pandemic, whereas 90% were undisrupted (continued or already successfully finished). The quantitative analysis showed a positive relationship between the leaders’ levels of competences and the projects status. In the case of all competences, the scores were higher for project leaders who finished projects successfully than for leaders who suspended or prolonged their projects. The research demonstrated that, in the demanding times of the COVID-19 pandemic, competences 4.0, to a certain extent, do play a significant role in the successful management of Erasmus+ projects. The implementation and sustainability of international educational projects, despite mobility and sanitary obstacles, depended, among other factors, on the level of leaders’ competences.

Keywords: Competences 4.0, COVID-19 pandemic, Erasmus+ Program, international education, project sustainability

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Phumlani Msomi, Patrick Nonjola, Patrick Ndungu, James Ramontja

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A series of quaternized poly (2.6 dimethyl – 1.4 phenylene oxide)/ polysulfone (QPPO/PSF) blend anion exchange membrane (AEM) were successfully fabricated and characterized for methanol alkaline fuel cell application. Zinc Oxide (ZnO) nanoparticles were introduced in the polymer matrix to enhance the intrinsic properties of the AEM. To confirm successful fabrication, FT-IR spectroscopy and nuclear magnetic resonance (¹H NMR and HMBC ¹⁵N NMR) were used. The membrane properties were enhanced by the addition of ZnO nanoparticles. The addition of ZnO nanoparticles resulted to a higher ion exchange capacity (IEC) of 3.72 mmol.g⁻¹and a 30-fold ion conductivity (IC) increase of the nanocomposite due to no (zero (0)) methanol permeability at 30 °C and increased water uptake. The QPPO/PSF/2% ZnO composite retained over 80 % of its initial IC when evaluated for alkaline stability at room temperature. The maximum power output reached for the membrane electrode assembly (MEA) constructed with QPPO/PSF/2%ZnO is 69 mW.cm⁻², which is about three times more than the parent QPPO membrane. The above results indicate that QPPO/PSF-ZnO is a good candidate as an anion exchange membrane for fuel cell application.

Keywords: anion exchange membrane, fuel cell, zinc oxide, nanocomposite

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Authors: Dilani Wimalasiri, Robert Brkljaca, Sylvia Urban, Terrence Piva, Tien Huynh

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Momordica cochinchinensis (Cucurbitaceae) is used as food and traditional medicine in South East Asia and is commonly known as Red Gac. The fruit aril consists 70 times higher lycopene and 10 times higher β-carotene than all known fruits and vegetables. Despite its nutritional value there is little information available on its genetic variation and its influence on nutritional value. In this study; genetic and nutritional variation (lycopene and β-carotene) was investigated among 47 M. cochinchinensis samples collected from Australia, Thailand and Vietnam using molecular markers (RAPD and ISSR) and HPLC, respectively. UPGMA based cluster analysis of genetic data grouped Northern and Central Vietnam samples together but were separated from Australia, Thailand and Southern Vietnam samples. The concentration of lycopene was significantly higher among the samples collected from Central Vietnam (p<0.05) and the concentration of β-carotene was significantly higher among the samples collected from Northern Vietnam (p<0.05) indicating the existence of best varieties. This study provides vital information in genetic diversity and facilitates the selection and breeding for nutritious M. cochinchinensis varieties.

Keywords: momordica cochinchinensis, lycopene, beta carotene, genetic diversity

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Authors: Anne Gibbons

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Both inside and outside of academia, people have sought to understand the “sense of place” of various regions, many times over and for many different reasons. The concept of regional identity is highly complex and surrounded by considerable contention. There are multiple bodies of research on regional identity theory in many different disciplines and even across sub-disciplinary classifications. Each discipline takes a slightly different angle or perspective on regional identity, resulting in a fragmented body of work on this topic overall. There is a need to consolidate this body of increasingly fragmented theory through interdisciplinary integration. For the purpose of this study, the province of Saskatchewan will serve as an exemplar for exploring regional identity in a concrete context. Saskatchewan can be thought of as a ‘functional region,’ with clear boundaries and clear residency, from which regional identity can be studied. This thesis shares the outcomes of a qualitative study grounded in a series of group interviews with askatchewan residents, from which it is concluded that the use of interdisciplinary theory is an appropriate approach to the study of regional identity. Regional identity cannot be compartmentalized; it is a web of characteristics, attributes, and feelings that are inextricably linked. The thesis thus concludes by offering lessons learned about how we might better understand regional identity, as illuminated through both interdisciplinary theory and the lived experiences and imaginations of people living in the region of Saskatchewan.

Keywords: interdisciplinary, regional identity, Saskatchewan, tourism studies

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Authors: Narjes Azimi

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It has been a while that narrative and storytelling turned to be the inevitable part of media. The narrative has so many aspects and among those entire aspects, the fantasy genre is consciously challenging one as fantasy readers are used to reading narratives like good versus evil plot. This paper will analyze the ASOIF TV series as a Meta narrative cultural production that deconstructs the elements of a traditional narrative. This study will shade on a grand narrative perspective from poststructuralism point of view. The theoretical framework is structuralism and post structuralism. Lyotard and Barthes are two main poststructuralists and focus of the study. Lyotard grand narrative elements will analyze in this research study. Fantasy genre generated a number of outstanding authors that explore innovative perspectives. Among all these leading authors George R.R Martin is one of the best. George R. R. Martin’s Fantasy a Song of Ice and Fire picturized the brutal world that seven kingdoms struggling for the power. Since 2011 this production has been followed and watched by millions of audiences all around the world. The methodology is the textual analysis of selected scenes. Martin’s distinctive fantasy style which makes it different from other fantasies, yet this shift does not negate how the previous fantasy writers represent the mentioned concepts of war, and etc., but Martin’ fantasy and left the mature audiences full of uncertainty.

Keywords: narrative theory, metanarrative, deconstruction, post-structuralism, Lyotard, Barthes

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Authors: Alam Ali, Ashok Kumar Pathak

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Path analysis is a statistical technique used to evaluate the strength of the direct and indirect effects of variables. One or more structural regression equations are used to estimate a series of parameters in order to find the better fit of data. Sometimes, exogenous variables do not show a significant strength of their direct and indirect effect when the assumption of classical regression (ordinary least squares (OLS)) are violated by the nature of the data. The main motive of this article is to investigate the efficacy of the copula-based regression approach over the classical regression approach and calculate the direct and indirect effects of variables when data violates the OLS assumption and variables are linked through an elliptical copula. We perform this study using a well-organized numerical scheme. Finally, a real data application is also presented to demonstrate the performance of the superiority of the copula approach.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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Authors: Harish Rajak, Preeti Patel

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HDAC inhibitors can reactivate gene expression and inhibit the growth and survival of cancer cells. The 3D-QSAR and Pharmacophore modeling studies were performed to identify important pharmacophoric features and correlate 3D-chemical structure with biological activity. The pharmacophore hypotheses were developed using e-pharmacophore script and phase module. Pharmacophore hypothesis represents the 3D arrangement of molecular features necessary for activity. A series of 55 compounds with well-assigned HDAC inhibitory activity was used for 3D-QSAR model development. Best 3D-QSAR model, which is a five PLS factor model with good statistics and predictive ability, acquired Q2 (0.7293), R2 (0.9811) and standard deviation (0.0952). Molecular docking were performed using Histone Deacetylase protein (PDB ID: 1t69) and prepared series of hydroxamic acid based HDAC inhibitors. Docking study of compound 43 show significant binding interactions Ser 276 and oxygen atom of dioxine cap region, Gly 151 and amino group and Asp 267 with carboxyl group of CONHOH, which are essential for anticancer activity. On docking, most of the compounds exhibited better glide score values between -8 to -10.5. We have established structure activity correlation using docking, energetic based pharmacophore modelling, pharmacophore and atom based 3D QSAR model. The results of these studies were further used for the design and testing of new HDAC analogs.

Keywords: Docking, e-pharmacophore, HDACIs, QSAR, Suberoylanilidehydroxamic acid.

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Authors: J. Scott Kenney

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Not all pain is created equal. In recent decades, the concept of Illegitimate pain has begun to shed light on the phenomena of emotional and physical pain that is misunderstood, neglected, or stigmatized, broadly conceptualized along dimensions of relative legitimation and physicality. Yet, beyond a pioneering study of the suffering of closeted LGBTQ + individuals, along with an analysis of the pains experienced by students at a religious boarding school, there has been insufficient attention to what lies behind such marginalized suffering beyond the original claim that it relates to broad interpretive standards and structured power relations, mediated through interaction in various groups/settings. This paper seeks to delve theoretically into this underdeveloped terrain. Building on earlier work, it takes direct aim at the definitional aspect that lies analytically prior to such matters, theoretically unpacking the role of ideology. Following a general introduction focused on theoretical relationships between social structure, power, and ideas, the paper reviews a range of sociological literature on relevant matters. After condensing the insights from these various literatures into a series of theoretical statements, the paper analytically engages with these to articulate a series of theoretical and methodological elaborations intended to practically assist researchers in empirically examining such matters in today's complex social environment.

Keywords: deviance, ideology, illegitimate pain, social theory, victimization

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Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

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Authors: Flavia Cordeiro, Fabio Silva, Alvaro Eiras, Jose Luiz Acebal

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Aedes aegypti is present in the tropical and subtropical regions of the world and is a vector of several diseases such as dengue fever, yellow fever, chikungunya, zika etc. The growth in the number of arboviruses cases in the last decades became a matter of great concern worldwide. Meteorological factors like mean temperature and precipitation are known to influence the infestation by the species through effects on physiology and ecology, altering the fecundity, mortality, lifespan, dispersion behaviour and abundance of the vector. Models able to describe the dynamics of the vector population size should then take into account the meteorological variables. The relationship between meteorological factors and the population dynamics of Ae. aegypti adult females are studied to provide a good set of predictors to model the dynamics of the mosquito population size. The time-series data of capture of adult females of a public health surveillance program from the city of Lavras, MG, Brazil had its association with precipitation, humidity and temperature analysed through a set of statistical methods for time series analysis commonly adopted in Signal Processing, Information Theory and Neuroscience. Cross-correlation, multicollinearity test and whitened cross-correlation were applied to determine in which time lags would occur the influence of meteorological variables on the dynamics of the mosquito abundance. Among the findings, the studied case indicated strong collinearity between humidity and precipitation, and precipitation was selected to form a pair of descriptors together with temperature. In the techniques used, there were observed significant associations between infestation indicators and both temperature and precipitation in short, mid and long terms, evincing that those variables should be considered in entomological models and as public health indicators. A descriptive model used to test the results exhibits a strong correlation to data.

Keywords: Aedes aegypti, cross-correlation, multicollinearity, meteorological variables

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Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Cristina Prandi, Piermichele Kobauri

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The present study is based on molecular modeling of a series of twelve 5-(4-substituent-phenoxy)-3-methylfuran-2(5H)-one derivatives which have potential of strigolactones mimics toward Striga hermonthica. The first step of the analysis included the calculation of molecular descriptors which numerically describe the structures of the analyzed compounds. The descriptors ALOGP (lipophilicity), AClogS (water solubility) and BBB (blood-brain barrier penetration), served as the input variables in multiple linear regression (MLR) modeling of germination activity toward S. hermonthica. Two MLR models were obtained. The first MLR model contains ALOGP and AClogS descriptors, while the second one is based on these two descriptors plus BBB descriptor. Despite the braking Topliss-Costello rule in the second MLR model, it has much better statistical and cross-validation characteristics than the first one. The ALOGP and AClogS descriptors are often very suitable predictors of the biological activity of many compounds. They are very important descriptors of the biological behavior and availability of a compound in any biological system (i.e. the ability to pass through the cell membranes). BBB descriptor defines the ability of a molecule to pass through the blood-brain barrier. Besides the lipophilicity of a compound, this descriptor carries the information of the molecular bulkiness (its value strongly depends on molecular bulkiness). According to the obtained results of MLR modeling, these three descriptors are considered as very good predictors of germination activity of the analyzed compounds toward S. hermonthica seeds. This article is based upon work from COST Action (FA1206), supported by COST (European Cooperation in Science and Technology).

Keywords: chemometrics, germination activity, molecular modeling, QSAR analysis, strigolactones

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Authors: Andrew T. Hendrickson, Liven De Marez, Marijn Martens, Gytha Muller, Tudor Paisa, Koen Ponnet, Catherine Schweizer, Megan Van Meer, Mariek Vanden Abeele

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Quantifying and understanding the myriad ways people use their phones and how that impacts their relationships, cognitive abilities, mental health, and well-being is increasingly important in our phone-centric society. However, most studies on the patterns of phone use have focused on theory-driven tests of specific usage hypotheses using self-report questionnaires or analyses of smaller datasets. In this work we present a series of analyses from a large corpus of over 3000 users that combine data-driven and theory-driven analyses to identify reliable smartphone usage patterns and clusters of similar users. Furthermore, we compare the stability of user clusters across user- and system-initiated sessions, as well as during the hypothesized ritualized behavior times directly before and after sleeping. Our results indicate support for some hypothesized usage patterns but present a more complete and nuanced view of how people use smartphones.

Keywords: data mining, experience sampling, smartphone usage, health and well being

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Authors: Vramori Mitra, Bornali Sarma, Arun K. Sarma

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Recurrence is a ubiquitous feature of any real dynamical system. The states in phase space trajectory of a system have an inherent tendency to return to the same state or its close state after certain time laps. Recurrence quantification analysis technique, based on this fundamental feature of a dynamical system, detects evaluation of state under variation of control parameter of the system. The paper presents the investigation of nonlinear dynamical behavior of plasma floating potential fluctuations obtained by using a Langmuir probe in different magnetic field under the variation of discharge voltages. The main measures of recurrence quantification analysis are considered as determinism, linemax and entropy. The increment of the DET and linemax variables asserts that the predictability and periodicity of the system is increasing. The variable linemax indicates that the chaoticity is being diminished with the slump of magnetic field while increase of magnetic field enhancing the chaotic behavior. Fractal property of the plasma time series estimated by DFA technique (Detrended fluctuation analysis) reflects that long-range correlation of plasma fluctuations is decreasing while fractal dimension is increasing with the enhancement of magnetic field which corroborates the RQA analysis.

Keywords: detrended fluctuation analysis, chaos, phase space, recurrence

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Authors: Selin Guney, Andres Riquelme

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Among the main purposes of optimal and efficient forecasts of agricultural commodity prices is to guide the firms to advance the economic decision making process such as planning business operations and marketing decisions. Governments are also the beneficiaries and suppliers of agricultural price forecasts. They use this information to establish a proper agricultural policy, and hence, the forecasts affect social welfare and systematic errors in forecasts could lead to a misallocation of scarce resources. Various empirical approaches have been applied to forecast commodity prices that have used different methodologies. Most commonly-used approaches to forecast commodity sectors depend on classical time series models that assume values of the response variables are precise which is quite often not true in reality. Recently, this literature has mostly evolved to a consideration of fuzzy time series models that provide more flexibility in terms of the classical time series models assumptions such as stationarity, and large sample size requirement. Besides, fuzzy modeling approach allows decision making with estimated values under incomplete information or uncertainty. A number of fuzzy time series models have been developed and implemented over the last decades; however, most of them are not appropriate for forecasting repeated and nonconsecutive transitions in the data. The modeling scheme used in this paper eliminates this problem by introducing Markov modeling approach that takes into account both the repeated and nonconsecutive transitions. Also, the determination of length of interval is crucial in terms of the accuracy of forecasts. The problem of determining the length of interval arbitrarily is overcome and a methodology to determine the proper length of interval based on the distribution or mean of the first differences of series to improve forecast accuracy is proposed. The specific purpose of this paper is to propose and investigate the potential of a new forecasting model that integrates methodologies for determining the proper length of interval based on the distribution or mean of the first differences of series and Fuzzy Time Series- Markov Chain model. Moreover, the accuracy of the forecasting performance of proposed integrated model is compared to different univariate time series models and the superiority of proposed method over competing methods in respect of modelling and forecasting on the basis of forecast evaluation criteria is demonstrated. The application is to daily corn and soybean prices observed at three commercially important North Carolina markets; Candor, Cofield and Roaring River for corn and Fayetteville, Cofield and Greenville City for soybeans respectively. One main conclusion from this paper is that using fuzzy logic improves the forecast performance and accuracy; the effectiveness and potential benefits of the proposed model is confirmed with small selection criteria value such MAPE. The paper concludes with a discussion of the implications of integrating fuzzy logic and nonarbitrary determination of length of interval for the reliability and accuracy of price forecasts. The empirical results represent a significant contribution to our understanding of the applicability of fuzzy modeling in commodity price forecasts.

Keywords: commodity, forecast, fuzzy, Markov

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Authors: R. Pääkkönen, L. Korpinen, F. Gobba

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The objective of our study is to investigate UV exposure in Finland through sample measurements as a typical case study in summer and winter. We measured UV-BC weighted radiation and calculated a daily dose, which is about 100–150 times the Finnish exposure limit value in summer and 1–6 times in winter. The measured ultraviolet indices varied from 0 to 7 (scale 0–18), which is less than the values obtained in countries that are located farther south from Tampere latitude of 61 degrees. In wintertime, the UV exposure was modest compared to summertime, 50–150 mW/m² and about 1–5 mW/m² in summer and winter, respectively. However, technical means to manage UV exposure in Scandinavia are also needed in summer- and springtime.

Keywords: ultraviolet radiation, measurement, winter, summer

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Authors: Strahinja Kovačević, Sanja Podunavac-Kuzmanović, Lidija Jevrić, Milica Karadžić

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The present study is based on the quantitative structure-activity relationship (QSAR) analysis of eighteen compounds with anti-prion activity. The structures and anti-prion activities (expressed in response units, RU%) of the analyzed compounds are taken from CHEMBL database. In the first step of analysis 85 molecular descriptors were calculated and based on them the hierarchical cluster analysis (HCA) and principal component analysis (PCA) were carried out in order to detect potential significant similarities or dissimilarities among the studied compounds. The calculated molecular descriptors were physicochemical, lipophilicity and ADMET (absorption, distribution, metabolism, excretion and toxicity) descriptors. The first stage of the QSAR analysis was simple linear regression modeling. It resulted in one acceptable model that correlates Henry's law constant with RU% units. The obtained 2D-QSAR model was validated by cross-validation as an internal validation method. The validation procedure confirmed the model’s quality and therefore it can be used for prediction of anti-prion activity. The next stage of the analysis of anti-prion activity will include 3D-QSAR and molecular docking approaches in order to select the most promising compounds in treatment of prion diseases. These results are the part of the project No. 114-451-268/2016-02 financially supported by the Provincial Secretariat for Science and Technological Development of AP Vojvodina.

Keywords: anti-prion activity, chemometrics, molecular modeling, QSAR

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Authors: Toufik Bensana, Slimane Mekhilef, Kamel Tadjine

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Vibration analysis has been frequently applied in the condition monitoring and fault diagnosis of rolling element bearings. Unfortunately, the vibration signals collected from a faulty bearing are generally non stationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA) and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, condition monitoring, local mean decomposition, rolling element bearing, vibration analysis

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Authors: Toufik Bensana, Medkour Mihoub, Slimane Mekhilef

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The use of vibration analysis has been established as the most common and reliable method of analysis in the field of condition monitoring and diagnostics of rotating machinery. Rolling bearings cover a broad range of rotary machines and plays a crucial role in the modern manufacturing industry. Unfortunately, the vibration signals collected from a faulty bearing are generally nonstationary, nonlinear and with strong noise interference, so it is essential to obtain the fault features correctly. In this paper, a novel numerical analysis method based on local mean decomposition (LMD) is proposed. LMD decompose the signal into a series of product functions (PFs), each of which is the product of an envelope signal and a purely frequency modulated FM signal. The envelope of a PF is the instantaneous amplitude (IA), and the derivative of the unwrapped phase of a purely flat frequency demodulated (FM) signal is the IF. After that, the fault characteristic frequency of the roller bearing can be extracted by performing spectrum analysis to the instantaneous amplitude of PF component containing dominant fault information. The results show the effectiveness of the proposed technique in fault detection and diagnosis of rolling element bearing.

Keywords: fault diagnosis, rolling element bearing, local mean decomposition, condition monitoring

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Authors: Seung-Seok Bak, Chang-Mu Jung

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An enough amount supply of industrial complexes is an important national policy in South Korea, which is highly dependent on foreign trade. A development process of the industrial complex can distinguish between the planning stage and the construction stage. The planning stage consists of the process of consulting with many stakeholders on the contents of the development of industrial complex, feasibility study, compliance with the Regional policies, and so on. The industrial complex planning stage, including licensing procedure, usually takes about three years in South Korea. The government determined that the appropriate supply of industrial complexes have been delayed, due to the long licensing period and drafted a law to shorten the license period in 2008. The law was expected to shorten the period of licensing, which was about three years, to six months. This paper attempts to show that the shortening of the licensing period does not positively affect the appropriate supply of industrial complexes. To do this, we used Interrupted Time Series Designs. As a result, it was found that the supply of industrial complexes was influenced more by other factors such as actual industrial complex demand of private sector and macro-level economic variables. In addition, the specific provisions of the law conflict with local policy and cause some problems such as damage to nature and agricultural land, traffic congestion.

Keywords: development of industrial complexes, industrial complexes, interrupted time series designs, simplification of licensing procedures for industrial complexes, time series regression

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Authors: Marcel Ciesla, Victoria Oberascher, Sven Eder, Stefan Kirchweger, Wolfgang E. Baaske, Gerald Ostermayer

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The omnipresent trend towards sustainable mobility is a major challenge, especially for commuters in rural areas. The use of micro public transport systems is expected to significantly reduce pollutant emissions, as several commuters travel the first mile together with a single pick-up bus instead of their own car. In this paper, different aspects of such a micro public transport system are analyzed. The main findings of the investigations should be how the travel times of commuters change and how many CO₂ emissions can be saved if some of the commuters use public transport instead of their own vehicle.

Keywords: micro public transport, green transportation, sustainable mobility, low-emission commuting

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Authors: Renata Konadu

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In Ghana, electricity has become the main form of energy which all sectors of the economy rely on for their businesses. Therefore, as the economy grows, the demand and consumption of electricity also grow alongside due to the heavy dependence on it. However, since the supply of electricity has not increased to match the demand, there has been frequent power outages and load shedding affecting business performances. To solve this problem and advance policies to secure electricity in Ghana, it is imperative that those factors that cause consumption to increase be analysed by considering the three classes of consumers; residential, industrial and non-residential. The main argument, however, is that, export of electricity to other neighbouring countries should be included in the electricity consumption model and considered as one of the significant factors which can decrease or increase consumption. The author made use of multivariate time series data from 1980-2010 and econometric models such as Ordinary Least Squares (OLS) and Vector Error Correction Model. Findings show that GDP growth, urban population growth, electricity exports and industry value added to GDP were cointegrated. The results also showed that there is unidirectional causality from electricity export and GDP growth and Industry value added to GDP to electricity consumption in the long run. However, in the short run, there was found to be a directional causality among all the variables and electricity consumption. The results have useful implication for energy policy makers especially with regards to electricity consumption, demand, and supply.

Keywords: electricity consumption, energy policy, GDP growth, vector error correction model

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Authors: Pager Mansaram Pandit

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The present paper aims to changing trends of population in Nashik district. The spatial variation of changing trends of population from 1901 to 2011. Nasik, lying between 19° 33’ and 20° 53’ north latitude and 73° 16’ and 75° 16’, with an area of 15530 Sq. K.M.North South length is 120 km. East West length is 200 km. Nashik has a population of 6,109,052 of which 3,164,261 are males and 2,944,791 and females. Average literacy rate of Nashik district in 2011 was 82.91 compared to 80.96 in 2001. In 1901 the density was 52 and in 2011 the density was 393 per sq. km. The progressive growth rate from 1901 to 2012 was 11.25 to 642.22 percent, respectively. The population trend is calculated with the help of time series. In 1901 population was 45.44% more and less in 1941 i.e. -13.86. From 1921 to 1981 the population was below the population trend but after 1991 population it gradually increased. The average rainfall it receives is 1034 mm. In the present times, because of advances in good climate, industrialization, development of road, University level educational facilities, religious importance, cargo services, good quality of grapes, pomegranates and onions, more and more people are being attracted towards Nashik districts. Another cause for the increase in the population is the main attraction of Ramkund, Muktidham Temple, Kalaram Temple, Coin Museum, and Trimbakeshwar.

Keywords: density, growth, population, population trend

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Authors: Zineb Benouahmane, Zhang Lifeng

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Experimental oxidation tests at high temperature (1300°C-1500°C) on α-SiC samples have been performed with different holding times and atmosphere (air, argon). Oxidized samples were then analyzed using X-ray photoelectron spectroscopy coupled to SEM and DAKTEK surface profiler verification. The oxidation rate and the mas gain were found to increase with temperature and holding times, corresponding to a passive oxidation regime which lead to the formation of SiO2 layer. The sessile drop method is employed in order to measure the wetting angles between Si/SiC system at high temperature (1430°C-1550°C). Contact angle can be varied between 44 °C to 85°C, by controlling the oxygen content in α-SiC. Increasing the temperature occurred the infiltration of liquid silicon and deoxidation of the coating.

Keywords: oxidation, wettability, silicon, SiC

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Authors: Erick Pruchnicki, Nikhil Padhye

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Plates are important engineering structures which have attracted extensive research since the 19th century. The subject of this work is statical analysis of a linearly elastic homogenous plate under small deformations. A 'thin plate' is a three-dimensional structure comprising of a small transverse dimension with respect to a flat mid-surface. The general aim of any plate theory is to deduce a two-dimensional model, in terms of mid-surface quantities, to approximately and accurately describe the plate's deformation in terms of mid-surface quantities. In recent decades, a common starting point for this purpose is to utilize series expansion of a displacement field across the thickness dimension in terms of the thickness parameter (h). These attempts are mathematically consistent in deriving leading-order plate theories based on certain a priori scaling between the thickness and the applied loads; for example, asymptotic methods which are aimed at generating leading-order two-dimensional variational problems by postulating formal asymptotic expansion of the displacement fields. Such methods rigorously generate a hierarchy of two-dimensional models depending on the order of magnitude of the applied load with respect to the plate-thickness. However, in practice, applied loads are external and thus not directly linked or dependent on the geometry/thickness of the plate; thus, rendering any such model (based on a priori scaling) of limited practical utility. In other words, the main limitation of these approaches is that they do not furnish a single plate model for all orders of applied loads. Following analogy of recent efforts of deploying Fourier-series expansion to study convergence of reduced models, we propose two-dimensional model(s) resulting from truncation of the potential energy and rigorously prove the convergence of these two-dimensional plate models to the parent three-dimensional linear elasticity with increasing truncation order of the potential energy.

Keywords: plate theory, Fourier-series expansion, convergence result, Legendre polynomials

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Authors: Burcu Guvenek, Volkan Alptekin

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Turkey is a country in the process of development and its economy has undergone structural reforms in order to realize a sustainable development and energy has vital role as a basic input for this aim. Turkey has been in the process of economic growth and development and, because of this, has an increasing energy need. This paper investigates relationship between economic growth and electricity consumption using annual data for Turkey between 1970-2008 by using bounds test. As economic growth and energy consumption variables used in empirical analysis was different order of integration I(0) and I(1), we employed bounds test approach. We have not found co-integration relationship between the variables.

Keywords: bounds test, economic growth, energy consumption, Turkey

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Authors: Julia B. Kischkat, Charlie D. Waters

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This research aims to understand the factors that may affect the survival and productivity of Pacific salmonids through two components. The first component is lab-based and aims to improve high-performance liquid chromatography to better quantify vitamin deficiencies such as thiamine. The lab work is conducted at the National Oceanic and Atmospheric Administration (NOAA) Ted Stevens Marine Research Institute in Juneau, Alaska. Deficiencies in thiamine have been shown to reduce the survival of salmonids at early life stages. The second component involves the analysis of a 22-year data set of migration timing of juvenile Coho Salmon, Dolly Varden, Steelhead, and returning adult Steelhead at Little Port Walter, Alaska. The statistical analysis quantifies their migration fluctuations and whether they correlate to various environmental conditions such as temperature, salinity, and precipitation.

Keywords: climate change, smolt timing, phenology, migration timing, salmon, time series analysis, ecology, chemistry, fisheries science

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Authors: Nazima Ellahi, Danish Ramzan

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There is a growing trend among development economists regarding the importance of financial sector for economic development and growth activities. The development thus introduced, helps to promote welfare effects and poverty alleviation. This study is an attempt to find the nature of link between Islamic banking financing and development of output growth for Pakistan. Time series data set has been utilized for a time period ranging from 1990 to 2010. Following the Phillip Perron (PP) and Augmented Dicky Fuller (ADF) test of unit root this study applied Ordinary Least Squares (OLS) method of estimation and found encouraging results in favor of promoting the Islamic banking practices in Pakistan.

Keywords: Islamic finance, poverty alleviation, economic growth, finance, commerce

Procedia PDF Downloads 345