Search results for: data structure

Authors: E. N. Vetrova, L.V. Lapochkina, N. V. Nikulina

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In the national economy, entrepreneurship plays the role of a buffer between economy and policy for it contributes to improving budget effectiveness and decreasing dependence of economy on the state. Entrepreneurship in industry makes it possible to increase the added value that is formed in production chains and to decrease dependence on import. Under the current circumstances, when sanctions are being imposed, this is especially relevant for Russia and for the realization of projects in the Russian Arctic. However, development of entrepreneurship in industry requires an enlightened state policy. The purpose of the research is elaboration of recommendations for improving economic effectiveness of the realization of the Arctic projects on the basis of conceptual proposals for the development of entrepreneurship in industry. The paper presents the studies of the extractive industry role in the Russian economy and proves its raw material character. The analysis of production chains in industry on the basis of the conception of the added value global chains demonstrated a low added value formed by Russian companies. The study of changes in the structure of economy based on systemic, statistical and comparative analyses revealed no positive changes in the structure of economy over the period under consideration. This is a manifestation of ineffectiveness of the Russian industrial policy in general and within the Arctic region in particular. The authors identified the problems information and implementation of the state industrial policy in the Arctic region and in the development of national entrepreneurship, analyzed the shortcomings of the current state policy in the sphere of the Russian industry. On the basis of the conducted studies, the authors formulated conceptual approaches to change the state policy in the Arctic. The basic idea of the authors is to substantiate the focus of the state regulation on the development of entrepreneurship in industry in the process of the Russian Arctic exploration. At the same time another problem is solved–that of the development of the manufacturing industry in the southern regions of the northwestern part of Russia. The criterion of effectiveness in this case is the economic effectiveness.

Keywords: entrepreneurship in industry, global chains of the added value, government regulation, industrial policies, production chains in the arctic region, economic effectiveness

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Authors: Waqas Ashraf, Yasir Nawab, Haritham Khan, Habib Awais, Shahbaz Ahmad

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Seersucker is a popular lightweight fabric widely used in men’s and women’s suiting, casual wear, children’s clothing, house robes, bed spreads and for spring and summer wear. The puckered effect generates air spaces between body and the fabric, keeping the wearer cool in hot conditions. The aim of this work was to develop knitted seersucker fabric on single cylinder weft knitting machine using plain jersey structure. Core spun cotton yarn and cotton spun yarn of same linear density were used. Core spun cotton yarn, contains cotton fiber in the sheath and elastase filament in the core. The both yarn were fed at regular interval to feeders on the machine. The loop length and yarn tension were kept constant at each feeder. The samples were then scoured and bleached. After wet processing, the fabric samples were washed and tumble dried. Parameters like loop length, stitch density and areal density were measured after conditioning these samples for 24 hours in Standard atmospheric condition. Produced sample has a regular puckering stripe along the width of the fabric with same height. The stitch density of both the flat and puckered area of relaxed fabric was found to be different .Air permeability and moisture management tests were performed. The results indicated that the knitted seersucker fabric has better wicking and moisture management properties as the flat area contact, whereas puckered area held away from the skin. Seersucker effect in knitted fabric was achieved by the difference of contraction of both sets of courses produced from different types of yarns. The seer sucker fabric produce by knitting technique is less expensive as compared to woven seer sucker fabric as there is no need of yarn preparation. The knitted seersucker fabric is more practicable for summer dresses, skirts, blouses, shirts, trousers and shorts.

Keywords: air permeability, knitted structure, moisture management, seersucker

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Authors: Luis A. Anchordoqui, Jorge F. Soriano, Diego F. Torres

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Auger data show evidence for a correlation between ultrahigh-energy cosmic rays (UHECRs) and nearby starburst galaxies. This intriguing correlation is consistent with data collected by the Telescope Array, which have revealed a much more pronounced directional 'hot spot' in arrival directions not far from the starburst galaxy M82. In this work, we assume starbursts are sources of UHECRs, and we investigate the prospects to use the observed distribution of UHECR arrival directions to constrain galactic magnetic field models. We show that if the Telescope Array hot spot indeed originates on M82, UHECR data would place a strong constraint on the turbulent component of the galactic magnetic field.

Keywords: galactic magnetic field, Pierre Auger observatory, telescope array, ultra-high energy cosmic rays

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Authors: Natarajan Tirupattur Srinivasan

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Quantum mechanics( QM) and (special) relativity (SR) have indeed revolutionized the very thinking of physicists, and the spectacular successes achieved over a century due to these two theories are mind-boggling. However, there is still a strong disquiet among some physicists. While the mathematical structure of these two theories has been established beyond any doubt, their physical interpretations are still being contested by many. Even after a hundred years of their existence, we cannot answer a very simple question, “What is an electron”? Physicists are struggling even now to come to grips with the different interpretations of quantum mechanics with all their ramifications. However, it is indeed strange that the (special) relativity theory of Einstein enjoys many orders of magnitude of “acceptance”, though both theories have their own stocks of weirdness in the results, like time dilation, mass increase with velocity, the collapse of the wave function, quantum jump, tunnelling, etc. Here, in this paper, it would be shown that by postulating an intrinsic internal motion to these enigmatic electrons, one can build a fairly consistent picture of reality, revealing a very simple picture of nature. This is also evidenced by Schrodinger’s ‘Zitterbewegung’ motion, about which so much has been written. This leads to a helical trajectory of electrons when they move in a laboratory frame. It will be shown that the helix is a three-dimensional wave having all the characteristics of our familiar 2D wave. Again, the helix, being a geodesic on an imaginary cylinder, supports ‘quantization’, and its representation is just the complex exponentials matching with the wave function of quantum mechanics. By postulating the instantaneous velocity of the electrons to be always ‘c’, the velocity of light, the entire relativity comes alive, and we can interpret the ‘time dilation’, ‘mass increase with velocity’, etc., in a very simple way. Thus, this model unifies both QM and SR without the need for a counterintuitive postulate of Einstein about the constancy of the velocity of light for all inertial observers. After all, if the motion of an inertial frame cannot affect the velocity of light, the converse that this constant also cannot affect the events in the frame must be true. But entire relativity is about how ‘c’ affects time, length, mass, etc., in different frames.

Keywords: quantum reconstruction, special theory of relativity, quantum mechanics, zitterbewegung, complex wave function, helix, geodesic, Schrodinger’s wave equations

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Authors: Jaishree Ranganathan, Poonam Rajurkar, Angelina A. Tzacheva, Zbigniew W. Ras

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In today’s world, business often depends on the customer feedback and reviews. Sentiment analysis helps identify and extract information about the sentiment or emotion of the of the topic or document. Attribute selection is a challenging problem, especially with large datasets in actionable pattern mining algorithms. Action Rule Mining is one of the methods to discover actionable patterns from data. Action Rules are rules that help describe specific actions to be made in the form of conditions that help achieve the desired outcome. The rules help to change from any undesirable or negative state to a more desirable or positive state. In this paper, we present a Lexicon based weighted scheme approach to identify emotions from customer feedback data in the area of manufacturing business. Also, we use Rough sets and explore the attribute selection method for large scale datasets. Then we apply Actionable pattern mining to extract possible emotion change recommendations. This kind of recommendations help business analyst to improve their customer service which leads to customer satisfaction and increase sales revenue.

Keywords: actionable pattern discovery, attribute selection, business data, data mining, emotion

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Authors: Shriya Shukla, Lachin Fernando

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Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

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Authors: Sharmistha Mukherjee

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Health care is the basic requirement for all. The prime question is who gets what, where and how? The unequal distribution of basic facilities do have a adverse effect on the users. The paper tries to examine health care in terms of available facilities, the health care need and how people perceive to it in a small town of Jalpaiguri in the midst of tea gardens in North Bengal. The morbidity pattern is also minutely observed with a section describing the organizational structure of health care keeping in mind the utilization.

Keywords: availability, distribution, health care, utilization

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Authors: Desplanches Maxime

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Accurate estimation of the remaining useful life of lithium-ion batteries for electronic devices is crucial. Data-driven methodologies encounter challenges related to data volume and acquisition protocols, particularly in capturing a comprehensive range of aging indicators. To address these limitations, we propose a hybrid approach that integrates an electrochemical model with state-of-the-art data analysis techniques, yielding a comprehensive database. Our methodology involves infusing an aging phenomenon into a Newman model, leading to the creation of an extensive database capturing various aging states based on non-destructive parameters. This database serves as a robust foundation for subsequent analysis. Leveraging advanced data analysis techniques, notably principal component analysis and t-Distributed Stochastic Neighbor Embedding, we extract pivotal information from the data. This information is harnessed to construct a regression function using either random forest or support vector machine algorithms. The resulting predictor demonstrates a 5% error margin in estimating remaining battery life, providing actionable insights for optimizing usage. Furthermore, the database was built from the Newman model calibrated for aging and performance using data from a European project called Teesmat. The model was then initialized numerous times with different aging values, for instance, with varying thicknesses of SEI (Solid Electrolyte Interphase). This comprehensive approach ensures a thorough exploration of battery aging dynamics, enhancing the accuracy and reliability of our predictive model. Of particular importance is our reliance on the database generated through the integration of the electrochemical model. This database serves as a crucial asset in advancing our understanding of aging states. Beyond its capability for precise remaining life predictions, this database-driven approach offers valuable insights for optimizing battery usage and adapting the predictor to various scenarios. This underscores the practical significance of our method in facilitating better decision-making regarding lithium-ion battery management.

Keywords: Li-ion battery, aging, diagnostics, data analysis, prediction, machine learning, electrochemical model, regression

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Authors: Olaiya Folorunsho, Comfort Y. Daramola, Joel N. Ugwu, Lawrence B. Adewole, Olufisayo S. Ekundayo

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In today world, there is a tremendous rise in the usage of internet due to the fact that almost all the communication and information sharing is done over the web. Conversely, there is a continuous growth of unauthorized access to confidential data. This has posed a challenge to information security expertise whose major goal is to curtail the menace. One of the approaches to secure the safety delivery of data/information to the rightful destination without any modification is steganography. Steganography is the art of hiding information inside an embedded information. This research paper aimed at designing a secured algorithm with the use of image steganographic technique that makes use of Least Significant Bit (LSB) algorithm for embedding the data into the bit map image (bmp) in order to enhance security and reliability. In the LSB approach, the basic idea is to replace the LSB of the pixels of the cover image with the Bits of the messages to be hidden without destroying the property of the cover image significantly. The system was implemented using C# programming language of Microsoft.NET framework. The performance evaluation of the proposed system was experimented by conducting a benchmarking test for analyzing the parameters like Mean Squared Error (MSE) and Peak Signal to Noise Ratio (PSNR). The result showed that image steganography performed considerably in securing data hiding and information transmission over the networks.

Keywords: steganography, image steganography, least significant bits, bit map image

Procedia PDF Downloads 247

Authors: Ali Razmi, Saeed Golian

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Climate change is known to have the potential to impact adversely hydrologic patterns for variables such as rainfall, maximum and minimum temperature and sea level rise. Long-term average of these climate variables could possibly change over time due to climate change impacts. In this study, trend analysis was performed on rainfall, maximum and minimum temperature and water level data of a coastal area in Manhattan, New York City, Central Park and Battery Park stations to investigate if there is a significant change in the data mean. Partial Man-Kendall test was used for trend analysis. Frequency analysis was then performed on data using common probability distribution functions such as Generalized Extreme Value (GEV), normal, log-normal and log-Pearson. Goodness of fit tests such as Kolmogorov-Smirnov are used to determine the most appropriate distributions. In flood frequency analysis, rainfall and water level data are often separately investigated. However, in determining flood zones, simultaneous consideration of rainfall and water level in frequency analysis could have considerable effect on floodplain delineation (flood extent and depth). The present study aims to perform flood frequency analysis considering joint probability distribution for rainfall and storm surge. First, correlation between the considered variables was investigated. Joint probability distribution of extreme water level and temperature was also investigated to examine how global warming could affect sea level flooding impacts. Copula functions were fitted to data and joint probability of water level with rainfall and temperature for different recurrence intervals of 2, 5, 25, 50, 100, 200, 500, 600 and 1000 was determined and compared with the severity of individual events. Results for trend analysis showed increase in long-term average of data that could be attributed to climate change impacts. GEV distribution was found as the most appropriate function to be fitted to the extreme climate variables. The results for joint probability distribution analysis confirmed the necessity for incorporation of both rainfall and water level data in flood frequency analysis.

Keywords: climate change, climate variables, copula, joint probability

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Authors: O. T. Oluriz, O. D. Akinyemi, J. A.Olowofela, O. A. Idowu, S. A. Ganiyu

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This study was carried out using aeromagnetic data which record variation in the magnitude of the earth magnetic field in order to detect local changes in the properties of the underlying geology. The aeromagnetic data (Sheet No. 261) was acquired from the archives of Nigeria Geological Survey Agency of Nigeria, obtained in 2009. The study present estimation of source parameters within an area of about 3,025 square kilometers on geographic latitude to and longitude to within Ibadan and it’s environs in Oyo State, southwestern Nigeria. The area under study belongs to part of basement complex in southwestern Nigeria. Estimation of source parameters of aeromagnetic data was achieve through the application of source imaging parameters (SPI) techniques that provide delineation, depth, dip contact, susceptibility contrast and mineral potentials of magnetic signatures within the region. The depth to the magnetic sources in the area ranges from 0.675 km to 4.48 km. The estimated depth limit to shallow sources is 0.695 km and depth to deep sources is 4.48 km. The apparent susceptibility values of the entire study area obtained ranges from 0.01 to 0.005 [SI]. This study has shown that the magnetic susceptibility within study area is controlled mainly by super paramagnetic minerals.

Keywords: aeromagnetic, basement complex, meta-sediment, precambrian

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Authors: Kalpana Sharma, Jyoti Mann

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The study was designed towards institutional analysis for a clear understanding of the process involved in functioning and layout of determinants influencing physical education teacher’s education program in India. This further can be recommended for selection of parameters for creating sector benchmarking for physical education teachers training institutions across India. 165 stakeholders involving students, teachers, parents, administrators were surveyed from the identified seven institutions and universities from different states of India. They were surveyed on the basis of seven broad parameters which were associated with the post graduate physical education program in India. A physical education program assessment tool of 52 items was designed to administer it among the stakeholders selected for the survey. An item analysis of the contents was concluded through the review process from selected experts working in higher education with experience in teacher training program in physical education. The data was collected from the stakeholders of the selected institutions through Physical Education Program Assessment Tool (PEPAT). The hypothesis that PE teacher education program is independent of physical education institutions was significant. The study directed a need towards robust admission process emphasizing on identification, selection of potential candidates and quality control of intake with the scientific process developed according to the Indian education policies and academic structure. The results revealed that the universities do not have similar functional and delivery process related to the physical education teacher training program. The study reflects towards the need for physical education universities and institutions to identify the best practices to be followed regarding the functioning of delivery of physical education programs at various institutions through strategic management studies on the identified parameters before establishing strict standards and norms for achieving excellence in physical education in India.

Keywords: assessment, benchmarking, curriculum, physical education, teacher education

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Authors: Hamidreza Namazi

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Fractal analysis is assessing fractal characteristics of data. It consists of several methods to assign fractal characteristics to a dataset which may be a theoretical dataset or a pattern or signal extracted from phenomena including natural geometric objects, sound, market fluctuations, heart rates, digital images, molecular motion, networks, etc. Fractal analysis is now widely used in all areas of science. An important limitation of fractal analysis is that arriving at an empirically determined fractal dimension does not necessarily prove that a pattern is fractal; rather, other essential characteristics have to be considered. For this purpose a Visual C++ based software called FRATSAN (FRActal Time Series ANalyser) was developed which extract information from signals through three measures. These measures are Fractal Dimensions, Jeffrey’s Measure and Hurst Exponent. After computing these measures, the software plots the graphs for each measure. Besides computing three measures the software can classify whether the signal is fractal or no. In fact, the software uses a dynamic method of analysis for all the measures. A sliding window is selected with a value equal to 10% of the total number of data entries. This sliding window is moved one data entry at a time to obtain all the measures. This makes the computation very sensitive to slight changes in data, thereby giving the user an acute analysis of the data. In order to test the performance of this software a set of EEG signals was given as input and the results were computed and plotted. This software is useful not only for fundamental fractal analysis of signals but can be used for other purposes. For instance by analyzing the Hurst exponent plot of a given EEG signal in patients with epilepsy the onset of seizure can be predicted by noticing the sudden changes in the plot.

Keywords: EEG signals, fractal analysis, fractal dimension, hurst exponent, Jeffrey’s measure

Procedia PDF Downloads 452

Authors: Jinghua Zhang

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Shaft-tunnel junction is a typical case of the structural nonuniformity in underground structures. The shaft and the tunnel possess greatly different structural features. Even under uniform excitations, they tend to behave discrepantly. Studies on shaft-tunnel junctions are mainly performed numerically. Shaking table tests are also conducted. Although many numerical and experimental data are obtained, an analytical solution still has great merits of gaining more insights into the shaft-tunnel problem. This paper will try to remedy the situation. Since the seismic responses of shaft-tunnel junctions are very related to directions of the excitations, they are studied in two scenarios: the longitudinal-excitation scenario and the transverse-excitation scenario. The former scenario will be addressed in this paper. Given that responses of the tunnel are highly dependent on the shaft, the analytical solutions would be developed firstly for the vertical shaft. Then, the seismic responses of the tunnel would be discussed. Since vertical shafts bear a resemblance to rigid caissons, the solution proposed in this paper is derived by introducing terms of shaft-tunnel and soil-tunnel interactions into equations originally developed for rigid caissons. The validity of the solution is examined by a validation model computed by finite element method. The mutual influence between the shaft and the tunnel is introduced. The soil-structure interactions are discussed parametrically based on the proposed equations. The shaft-tunnel relative displacement and the soil-tunnel relative stiffness are found to be the most important parameters affecting the magnitudes and distributions of the internal forces of the tunnel. A hinge-joint at the shaft-tunnel junction could significantly reduce the degree of stress concentration compared with a rigid joint.

Keywords: analytical solution, longitudinal excitation, numerical validation , shaft-tunnel junction

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Authors: Yunus Onur Yildiz, Mesut Kirca

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In this study, mechanical properties of a nanoporous metal coated with a different metallic material are studied through a new atomistic modelling technique and molecular dynamics (MD) simulations. This new atomistic modelling technique is based on the Voronoi tessellation method for the purpose of geometric representation of the ligaments. With the proposed technique, atomistic models of nanoporous metals which have randomly oriented ligaments with non-uniform mass distribution along the ligament axis can be generated by enabling researchers to control both ligament length and diameter. Furthermore, by the utilization of this technique, atomistic models of coated nanoporous materials can be numerically obtained for further mechanical or thermal characterization. In general, this study consists of two stages. At the first stage, we use algorithms developed for generating atomic coordinates of the coated nanoporous material. In this regard, coordinates of randomly distributed points are determined in a controlled way to be employed in the establishment of the Voronoi tessellation, which results in randomly oriented and intersected line segments. Then, line segment representation of the Voronoi tessellation is transformed to atomic structure by a special process. This special process includes generation of non-uniform volumetric core region in which atoms can be generated based on a specific crystal structure. As an extension, this technique can be used for coating of nanoporous structures by creating another volumetric region encapsulating the core region in which atoms for the coating material are generated. The ultimate goal of the study at this stage is to generate atomic coordinates that can be employed in the MD simulations of randomly organized coated nanoporous structures. At the second stage of the study, mechanical behavior of the coated nanoporous models is investigated by examining deformation mechanisms through MD simulations. In this way, the effect of coating on the mechanical behavior of the selected material couple is investigated.

Keywords: atomistic modelling, molecular dynamic, nanoporous metals, voronoi tessellation

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Authors: Howaida I. Abd-Alla, Omnia Kutkat, Yassmin Moatasim, Magda T. Ibrahim, Marwa A. Mostafa, Mohamed GabAllah, Mounir M. El-Safty

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Artemisia judaica (known shih-balady), Azadirachta indica and Sophora tomentosa (known yellow necklace pod) are members of available medicinal plants well-known for their traditional medical use in Egypt which suggests that they probably harbor broad-spectrum antiviral, immunostimulatory and anti-inflammatory functions. Their ethyl acetate-dichloromethane (1:1, v/v) extracts were evaluated for the potential anti-Middle East respiratory syndrome-related coronavirus (anti-MERS-CoV) activity. Their cytotoxic activity was tested in Vero-E6 cells using 3-(4,-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) method with minor modification. The plot of percentage cytotoxicity for each extract concentration has calculated the concentration which exhibited 50% cytotoxic concentration (TC50). A plaque reduction assay was employed using safe dose of extract to evaluate its effect on virus propagation. The highest inhibition percentage was recorded for the yellow necklace pod, followed by Shih-balady. The possible mode of action of virus inhibition was studied at three different levels viral replication, viral adsorption and virucidal activity. The necklace pod leaves have induced virucidal effects and direct effects on the replication of virus. Phytochemical investigation of the promising necklace pod led to the isolation and structure determination of nine compounds. The structure of each compound was determined by a variety of spectroscopic methods. Compounds 4-O-methyl sorbitol 1, 8-methoxy daidzin 6 and 6-methoxy apigenin-7-O-β-D-glucopyranoside 8 were isolated for the first time from the Sophora genus and the other six compounds were the first time that they were isolated from this species according to available works of literature. Generally, the highest anti-CoV 2 activity of S. tomentosa was associated with the crude ethanolic extract, indicating the possibility of synergy among the antiviral phytochemical constituents (1-9).

Keywords: coronavirus, MERS-CoV, mode of action, necklace pod, shih-balady

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Authors: T. R. Bandara, H. Jaelani, G. J. Griffin

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The conversion of lignocellulosic waste materials, such as sugar cane bagasse, to biofuels such as ethanol has attracted significant interest as a potential element for transforming transport fuel supplies to totally renewable sources. However, the refractory nature of the cellulosic structure of lignocellulosic materials has impeded progress on developing an economic process, whereby the cellulose component may be effectively broken down to glucose monosaccharides and then purified to allow downstream fermentation. Ionic liquid (IL) treatment of lignocellulosic biomass has been shown to disrupt the crystalline structure of cellulose thus potentially enabling the cellulose to be more readily hydrolysed to monosaccharides. Furthermore, conventional hydrolysis of lignocellulosic materials yields byproducts that are inhibitors for efficient fermentation of the monosaccharides. However, selective extraction of monosaccharides from an aqueous/IL phase into an organic phase utilizing a combination of boronic acids and quaternary amines has shown promise as a purification process. Hydrolysis of sugar cane bagasse immersed in an aqueous solution with IL (1-ethyl-3-methylimidazolium acetate) was conducted at different pH and temperature below 100 ºC. It was found that the use of a high concentration of hydrochloric acid to acidify the solution inhibited the hydrolysis of bagasse. At high pH (i.e. basic conditions), using sodium hydroxide, catalyst yields were reduced for total reducing sugars (TRS) due to the rapid degradation of the sugars formed. For purification trials, a supported liquid membrane (SLM) apparatus was constructed, whereby a synthetic solution containing xylose and glucose in an aqueous IL phase was transported across a membrane impregnated with phenyl boronic acid/Aliquat 336 to an aqueous phase. The transport rate of xylose was generally higher than that of glucose indicating that a SLM scheme may not only be useful for purifying sugars from undesirable toxic compounds, but also for fractionating sugars to improve fermentation efficiency.

Keywords: biomass, bagasse, hydrolysis, monosaccharide, supported liquid membrane, purification

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Authors: Ruangdech Sirikit

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The purposes of this study were analyzed differential item functioning and differential test functioning of SWUSAT aptitude test classification by sex variable. The data used in this research is the secondary data from Srinakharinwirot University Scholastic Aptitude Test 2011 (SWUSAT 2011) SWUSAT test consists of four subjects. There are verbal ability test, number ability test, reasoning ability test and spatial ability test. The data analysis was carried out in 2 steps. The first step was analyzing descriptive statistics. In the second step were analyzed differential item functioning (DIF) and differential test functioning (DTF) by using the DIFAS program. The research results were as follows: The results of data analysis for all 10 tests in year 2011. Sex was the characteristic that found DIF all 10 tests. The percentage of item number that found DIF was between 10% - 46.67%. There are 4 tests that most of items favors female group. There are 3 tests that most of items favors male group and there are 3 tests that the number of items favors female group equal favors male group. For Differential test functioning (DTF), there are 8 tests that have small DIF effect variance.

Keywords: differential item functioning, differential test functioning, SWUSAT, aptitude test

Procedia PDF Downloads 593

Authors: Abigail Qian Zhou

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In today's China, the well-educated middle class, with stable jobs and above-average income, are the driving force behind its Internet society. Through the analysis of data from the 2015 Chinese General Social Survey and 50 interviewees, this study investigates the current situation of this group’s specific internet usage. The findings of this study demonstrate that daily life among the members of this socioeconomic group is closely tied to the Internet. For Chinese middle class, the Internet is used to socialize and entertain self and others. It is also used to search for and share information as well as to build their identities. The empirical results of this study will provide a reference, supported by factual data, for enterprises seeking to target the Chinese middle class through online marketing efforts.

Keywords: middle class, Internet use, network behaviour, online marketing, China

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Authors: Muhammad Umar Mushtaq, Muhammad Bilal Khan Niazi, Nouman Ahmad, Dooa Arif

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Apart from organic dyes, heavy metals such as Pb, Ni, Cr, and Cu are present in textile effluent and pose a threat to humans and the environment. Many studies on removing heavy metallic ions from textile wastewater have been conducted in recent decades using metal-organic frameworks (MOFs). In this study new polyether sulfone ultrafiltration membrane, modified with Cu/Co and Cu/Zn-based bimetal-organic frameworks (MOFs), was produced. Phase inversion was used to produce the membrane, and atomic force microscopy (AFM), scanning electron microscopy (SEM) were used to characterize it. The bimetallic MOFs-based membrane structure is complex and can be comprehended using characterization techniques. The bimetallic MOF-based filtration membranes are designed to selectively adsorb specific contaminants while allowing the passage of water molecules, improving the ultrafiltration efficiency. MOFs' adsorption capacity and selectivity are enhanced by functionalizing them with particular chemical groups or incorporating them into composite membranes with other materials, such as polymers. The morphology and performance of the bimetallic MOF-based membrane were investigated regarding pure water flux and metal ion rejection. The advantages of developed bimetallic MOFs based membranes for wastewater treatment include enhanced adsorption capacity because of the presence of two metals in their structure, which provides additional binding sites for contaminants, leading to a higher adsorption capacity and more efficient removal of pollutants from wastewater. Based on the experimental findings, bimetallic MOF-based membranes are more capable of rejecting metal ions from industrial wastewater than conventional membranes that have already been developed. Furthermore, the difficulties associated with operational parameters, including pressure gradients and velocity profiles, are simulated using Ansys Fluent software. The simulation results obtained for the operating parameters are in complete agreement with the experimental results.

Keywords: bimetallic MOFs, heavy metal ions, industrial wastewater treatment, ultrafiltration.

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Authors: Ferry Kurniawan

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In this paper, we nowcast quarterly output growth in Indonesia by exploiting higher frequency data (monthly indicators) using a mixed-frequency factor model and exploiting both quarterly and monthly data. Nowcasting quarterly GDP in Indonesia is particularly relevant for the central bank of Indonesia which set the policy rate in the monthly Board of Governors Meeting; whereby one of the important step is the assessment of the current state of the economy. Thus, having an accurate and up-to-date quarterly GDP nowcast every time new monthly information becomes available would clearly be of interest for central bank of Indonesia, for example, as the initial assessment of the current state of the economy -including nowcast- will be used as input for longer term forecast. We consider a small scale mixed-frequency factor model to produce nowcasts. In particular, we specify variables as year-on-year growth rates thus the relation between quarterly and monthly data is expressed in year-on-year growth rates. To assess the performance of the model, we compare the nowcasts with two other approaches: autoregressive model –which is often difficult when forecasting output growth- and Mixed Data Sampling (MIDAS) regression. In particular, both mixed frequency factor model and MIDAS nowcasts are produced by exploiting the same set of monthly indicators. Hence, we compare the nowcasts performance of the two approaches directly. To preview the results, we find that by exploiting monthly indicators using mixed-frequency factor model and MIDAS regression we improve the nowcast accuracy over a benchmark simple autoregressive model that uses only quarterly frequency data. However, it is not clear whether the MIDAS or mixed-frequency factor model is better. Neither set of nowcasts encompasses the other; suggesting that both nowcasts are valuable in nowcasting GDP but neither is sufficient. By combining the two individual nowcasts, we find that the nowcast combination not only increases the accuracy - relative to individual nowcasts- but also lowers the risk of the worst performance of the individual nowcasts.

Keywords: nowcasting, mixed-frequency data, factor model, nowcasts combination

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Authors: M. F. Haroun, T. A. Gulliver

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In this paper, an encryption algorithm is proposed for real-time image encryption. The scheme employs a dual chaotic generator based on a three dimensional (3D) discrete Lorenz attractor. Encryption is achieved using non-autonomous modulation where the data is injected into the dynamics of the master chaotic generator. The second generator is used to permute the dynamics of the master generator using the same approach. Since the data stream can be regarded as a random source, the resulting permutations of the generator dynamics greatly increase the security of the transmitted signal. In addition, a technique is proposed to mitigate the error propagation due to the finite precision arithmetic of digital hardware. In particular, truncation and rounding errors are eliminated by employing an integer representation of the data which can easily be implemented. The simple hardware architecture of the algorithm makes it suitable for secure real-time applications.

Keywords: chaotic systems, image encryption, non-autonomous modulation, FPGA

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Authors: Shoohira Aftab, Hammad Afzal

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Information integration is a well known procedure to provide consolidated view on sets of heterogeneous information sources. It not only provides better statistical analysis of information but also facilitates users to query without any knowledge on the underlying heterogeneous information sources The problem of providing a consolidated view of information can be handled using Semantic data (information stored in such a way that is understandable by machines and integrate-able without manual human intervention). However, integrating information using semantic web technology without any access management enforced, will results in increase of privacy and confidentiality concerns. In this research we have designed and developed a framework that would allow information from heterogeneous formats to be consolidated, thus resolving the issue of interoperability. We have also devised an access control system for defining explicit privacy constraints. We designed and applied our framework on both semantic and non-semantic data from heterogeneous resources. Our approach is validated using scenario based testing.

Keywords: information integration, semantic data, interoperability, security, access control system

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Authors: Nassima Hamzaoui, Mostefa Ghamnia

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Nanoscale thin films of pure and Mn-doped Nickel oxide (NiO) were prepared by dissolving nickel chloride hexahydrate (NiCl2, 6H2O) and manganese chloride tetrahydrate (MnCl2,4H2O) under experimental conditions. The resulting solution was stirred at room temperature for 30 OC minutes in order to obtain homogeneity. The solution was sprayed onto heated glass substrates. The films obtained were characterized by X-ray diffraction to verify crystallinity. Atomic force microscopy (AFM) reveals surface topographical structure. UV-visible spectroscopy shows good transparency of the NiO layers.

Keywords: films, NiO, AFM, X-ray diffraction

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Authors: Ainas Belkacem, Fourar Ali

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The present study focuses on the mathematical modeling and calculation of physical parameters of water pollution by oil and sand in regime fully dispersed in water. In this study, the sand particles and oil are suspended in the case of fully developed turbulence. The study consists to understand, model and predict the viscosity, the structure and dynamics of these types of mixtures. The work carried out is Numerical and validated by experience.

Keywords: multi phase flow, pollution, suspensions, turbulence

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Authors: B. K. Gill, Himani Sharma, V. K. Rattan

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Experimental data of refractive index, excess molar volume and viscosity of binary mixture of morpholine with cumene over the whole composition range at 298.15 K, 303.15 K, 308.15 K and normal atmospheric pressure have been measured. The experimental data were used to compute the density, deviation in molar refraction, deviation in viscosity and excess Gibbs free energy of activation as a function of composition. The experimental viscosity data have been correlated with empirical equations like Grunberg- Nissan, Herric correlation and three body McAllister’s equation. The excess thermodynamic properties were fitted to Redlich-Kister polynomial equation. The variation of these properties with composition and temperature of the binary mixtures are discussed in terms of intermolecular interactions.

Keywords: cumene, excess Gibbs free energy, excess molar volume, morpholine

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Authors: T. M. Samuel, O. O. Aremu, I. O. Ismaila, L. I. Onu, B. O. Adetifa, S. E. Adegbite, O. O. Olokoshe

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The imperative of anthropometry in designing to fit cannot be overemphasized. Of essence is the variability of measurements among population for which data is collected. In this paper anthropometric data were collected for the design of gari-frying facility such that work system would be designed to fit the gari-frying population in the Southwestern states of Nigeria comprising Lagos, Ogun, Oyo, Osun, Ondo, and Ekiti. Twenty-seven body dimensions were measured among 120 gari-frying processors. Statistical analysis was performed using SPSS package to determine the mean, standard deviation, minimum value, maximum value and percentiles (2nd, 5th, 25th, 50th, 75th, 95th, and 98th) of the different anthropometric parameters. One sample t-test was conducted to determine the variation within the population. The 50th percentiles of some of the anthropometric parameters were compared with those from other populations in literature. The correlation between the worker’s age and the body anthropometry was also investigated.The mean weight, height, shoulder height (sitting), eye height (standing) and eye height (sitting) are 63.37 kg, 1.57 m, 0.55 m, 1.45 m, and 0.67 m respectively.Result also shows a high correlation with other populations and a statistically significant difference in variability of data within the population in all the body dimensions measured. With a mean age of 42.36 years, results shows that age will be a wrong indicator for estimating the anthropometry for the population.

Keywords: anthropometry, cassava processing, design to fit, gari-frying, workstation design

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Authors: Hoai Nam Huynh, Edouard Rivière-Lorphèvre, Olivier Verlinden

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Manufacturing technologies are becoming continuously more diversified over the years. The increasing use of robots for various applications such as assembling, painting, welding has also affected the field of machining. Machining robots can deal with larger workspaces than conventional machine-tools at a lower cost and thus represent a very promising alternative for machining applications. Furthermore, their inherent structure ensures them a great flexibility of motion to reach any location on the workpiece with the desired orientation. Nevertheless, machining robots suffer from a lack of stiffness at their joints restricting their use to applications involving low cutting forces especially finishing operations. Vibratory instabilities may also happen while machining and deteriorate the precision leading to scrap parts. Some researchers are therefore concerned with the identification of optimal parameters in robotic machining. This paper continues the development of a virtual robotic machining simulator in order to find optimized cutting parameters in terms of depth of cut or feed per tooth for example. The simulation environment combines an in-house milling routine (DyStaMill) achieving the computation of cutting forces and material removal with an in-house multibody library (EasyDyn) which is used to build a dynamic model of a 3-DOF planar robot with flexible links. The position of the robot end-effector submitted to milling forces is controlled through an inverse kinematics scheme while controlling the position of its joints separately. Each joint is actuated through a servomotor for which the transfer function has been computed in order to tune the corresponding controller. The output results feature the evolution of the cutting forces when the robot structure is deformable or not and the tracking errors of the end-effector. Illustrations of the resulting machined surfaces are also presented. The consideration of the links flexibility has highlighted an increase of the cutting forces magnitude. This proof of concept will aim to enrich the database of results in robotic machining for potential improvements in production.

Keywords: control, milling, multibody, robotic, simulation

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Authors: Arunas Burinskas, Aurelija Burinskiene

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On average, ten percent of drugs - commercial products are not available in pharmacies due to shortage. The shortage event disbalance sales and requires a recovery period, which is too long. Therefore, one of the critical issues that pharmacies do not record potential sales transactions during shortage and recovery periods. The authors suggest estimating outliers during shortage and recovery periods. To shorten the recovery period, the authors suggest using average sales per sales day prediction, which helps to protect the data from being downwards or upwards. Authors use the outlier’s visualization method across different drugs and apply the Grubbs test for significance evaluation. The researched sample is 100 drugs in a one-month time frame. The authors detected that high demand variability products had outliers. Among analyzed drugs, which are commercial products i) High demand variability drugs have a one-week shortage period, and the probability of facing a shortage is equal to 69.23%. ii) Mid demand variability drugs have three days shortage period, and the likelihood to fall into deficit is equal to 34.62%. To avoid shortage events and minimize the recovery period, real data must be set up. Even though there are some outlier detection methods for drug data cleaning, they have not been used for the minimization of recovery period once a shortage has occurred. The authors use Grubbs’ test real-life data cleaning method for outliers’ adjustment. In the paper, the outliers’ adjustment method is applied with a confidence level of 99%. In practice, the Grubbs’ test was used to detect outliers for cancer drugs and reported positive results. The application of the Grubbs’ test is used to detect outliers which exceed boundaries of normal distribution. The result is a probability that indicates the core data of actual sales. The application of the outliers’ test method helps to represent the difference of the mean of the sample and the most extreme data considering the standard deviation. The test detects one outlier at a time with different probabilities from a data set with an assumed normal distribution. Based on approximation data, the authors constructed a framework for scaling potential sales and estimating outliers with Grubbs’ test method. The suggested framework is applicable during the shortage event and recovery periods. The proposed framework has practical value and could be used for the minimization of the recovery period required after the shortage of event occurrence.

Keywords: drugs, Grubbs' test, outlier, shortage event

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Authors: Hina Javed

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This study investigated the different strategies used by Pakistani students learning English as a second language at secondary level school. The basic premise of the study is that ESL students face tremendous difficulty while they are reading a text in English. It also purports to dig into the different causes of their slow reading. They might range from word reading accuracy, mental translation, lexical density, cultural gaps, complex syntactic constructions, and back skipping. Sixty Grade 7 students from two secondary mainstream schools in Lahore were selected for the study, thirty being boys and thirty girls. They were administered reading-related and reading speed pre and post-tests. The purpose of the tests was to gauge their performance on different reading tasks so as to be able to see how they used strategies, if any, and also to ascertain the causes hampering their performance on those tests. In the pretests, they were given simple texts with considerable lexical density and moderately complex sentential layout. In the post-tests, the reading tasks contained comic strips, texts with visuals, texts with controlled vocabulary, and an evenly distributed varied range of simple, compound, and complex sentences. Both the tests were timed. The results gleaned through the data gathered corroborated the researchers’ basic hunch that they performed significantly better than pretests. The findings suggest that the morphological structure of words and lexical density are the main sources of reading comprehension difficulties in poor ESL readers. It is also confirmed that if the texts are accompanied by pictorial visuals, it greatly facilitates students’ reading speed and comprehension. There is no substantial evidence that ESL readers adopt any specific strategy while reading in English.

Keywords: slow ESL reading speed, mental translation, complex syntactic constructions, back skipping

Procedia PDF Downloads 55