Search results for: correlation matrix

Authors: Aspasia Simpsi

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The aim of this study was to translate into Greek and then validate the psychometric properties of the Internet Gaming Disorder Scale–Short-Form (IGDS9-SF) (Pontes & Griffiths, 2015). This is the first short standardized psychometric tool to assess Internet Gaming Disorder (IGD) according to the DSM-V nine clinical criteria and among the most frequently examined. The translation of the test was done through the process of back-translation. To gain a better insight into the psychometric properties of this test, the questionnaire included demographic questions and the Greek version of the Internet Addiction Test (Young, 1998). The participants of the study were 241 adolescents aged between 12 to 18. They were nationally recruited in Greece through an online survey that was hosted on the platform of Qualtrics. Analysis revealed excellent reliability with Cronbach’s alpha coefficients α = .939 for IGDS9-SF and α = .940 for IAT. The use of Pearson product-moment correlation revealed a significant positive relationship between IGDS9-SF and IAT r (241) =.45, p < .001. Due to inconsistencies in terminology and tests in the field of IGD, what is recommended for future research is a consensus regarding IGD testing and research.

Keywords: internet gaming disorder, IGDS9-SF, psychometric properties, internet addiction

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Authors: Rui Magalhães, Sohel Rana, Raul Fangueiro, Clara Gonçalves, Pedro Nunes, Gustavo Dias

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Auxetic fibrous structures and composites with negative Poisson’s ratio (NPR) have huge potential for application in ballistic protection due to their high energy absorption and excellent impact resistance. In the present research, re-entrant lozenge auxetic fibrous structures were produced through weft knitting technology using high performance polyamide and para-aramid fibres. Fabric structural parameters (e.g. loop length) and machine parameters (e.g. take down load) were varied in order to investigate their influence on the auxetic behaviours of the produced structures. These auxetic structures were then impregnated with two types of polymeric resins (epoxy and polyester) to produce composite materials, which were subsequently characterized for the auxetic behaviour. It was observed that the knitted fabrics produced using the polyamide yarns exhibited NPR over a wide deformation range, which was strongly dependant on the loop length and take down load. The polymeric composites produced from the auxetic fabrics also showed good auxetic property, which was superior in case of the polyester matrix. The experimental results suggested that these composites made from the auxetic fibrous structures can be properly designed to find potential use in the body amours for personal protection applications.

Keywords: auxetic fabrics, high performance, composites, energy absorption, impact resistance

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Authors: Ahmad Shahfarhat, Ashraf Mohammadzade, Reza Saeedi, Hadi Hesari

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Background: Mothers of infants admitted at NICU are vulnerable to depression (affecting 10 to 20% of mothers during the first year after delivery) As you know, about half of women with prominent postpartum depression (PPD) symptoms are not diagnosed. The Edinburgh Postnatal Depression Scale (EPDS) is the most widely used screening instrument for PPD. In this study, we checked EPDS score of 12 or more on the second day (D2), discharge, day 28(D28), and day42 (D42) postpartum to determine the risk factors as well as the prevalence of PPD in a sample of mothers of NICU admitted neonates. Methods: A sample of 682 women used the EPDS on admission and at discharge. An assessment for PPD was performed on D28 and D42 by a telephone interview. Results: On admission, the average score on EPDS was 9.72 (SD = 4.4), and 27.4% of women (187) had an EPDS score ≥12. On Discharge, 4weeks and 6weeks postpartum the average score was ordinary 9.34 (SD = 3.8), 9.12 (SD = 3.7), 8.52(SD = 3.36), and (173)25.4 %,( 141)23.3 %,( 88)15.3% of women presented with PPD. a positive correlation was found between scores on EPDS on admission and D42 (P = 0.001). An analysis shows that mothers of twins (P = 0.001) and higher age mothers (P=0.001) are significantly associated with PPD. Conclusion: Women with EPDS score more than 12 and/or older will benefit from a closer follow-up during the rest of the post-partum period, and it is better to be under psychological support.

Keywords: NICU, depression, pregnancy, mothers

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Authors: M. Fems Kurotimi, Agada Franklin, Godsave Aladei, Opigo Helen

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Within the last 30 years, entrepreneurship education (EE) has continued to gain massive interest both in the field of research and among policy makers. This surge in interest can be attributed to the perceived importance EE plays in the equipping of potential entrepreneurs and as a 21^st century strategy to foster economic growth and development. This paper sets out to ascertain the correlation between EE and economic growth and development. A desk research approach was adopted where a multiplicity of literatures in the field were studied intensely. The findings reveal that indeed EE has a positive effect on entrepreneurship engagement thereby fostering economic growth and development. However, some research studies reported the contrary. That although EE may be able to equip potential entrepreneurs with requisite entrepreneurial skills and competencies, it will only be successful in producing entrepreneurs if they are internally driven to become entrepreneurs, because we cannot make people what they are not. The findings also reveal that countries that adopted EE early have more innovations inspired by entrepreneurs and are more developed than those that only recently adopted EE as a viable tool for entrepreneurship and economic development.

Keywords: entrepreneurship, entrepreneurship education, economic development, economic growth, sustainable development

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Authors: Aldan A. Sapargaliyev, Yerbol A. Sapargaliyev

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Since the invention, the electric machine (EM) can be defined as oEM – one-vector electric machine, as it works due to one-vector inductive coupling with use of one-vector electromagnet. The disadvantages of oEM are large size and limited efficiency at low and medium power applications. This paper describes multi-vector electric machine (mEM) based on multi-vector inductive coupling, which is characterized by the increased surface area of ​​the inductive coupling per EM volume, with a reduced share of inefficient and energy-consuming part of the winding, in comparison with oEM’s. Particularly, it is considered, calculated and compared the performance of three different electrical motors and their power at the same volumes and rotor frequencies. It is also presented the result of calculation of correlation between power density and volume for oEM and mEM. The method of multi-vector inductive coupling enables mEM to possess 1.5-4.0 greater density of power per volume and significantly higher efficiency, in comparison with today’s oEM, especially in low and medium power applications. mEM has distinct advantages, when used in transport vehicles such as electric cars and aircrafts.

Keywords: electric machine, electric motor, electromagnet, efficiency of electric motor

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Authors: Sajid Shah, Yoshimitsu Uemura, Katsuki Kusakabe

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Sol-gel derived hydrophobic silica membranes with pore sizes less than 1 nm are quite attractive for gas separation in a wide range of temperatures. A nano-structured hydrophobic membrane was prepared by sol-gel technique on a porous α–Al₂O₃ tubular support with yttria stabilized zirconia (YSZ) as an intermediate layer. Bistriethoxysilylethane (BTESE) derived sol was modified by adding phenyltriethoxysilylethane (PhTES) as an organic template. Six times dip coated modified silica membrane having a thickness of about 782 nm was characterized by field emission scanning electron microscopy. Thermogravimetric analysis, together along contact angle and Fourier transform infrared spectroscopy, showed that hydrophobic properties were improved by increasing the PhTES content. The contact angle of water droplet increased from 37° for pure to 111.5° for the modified membrane. The permeance of single gas H₂ was higher than H₂:CO₂ ratio of 75:25 binary feed mixtures. However, the permeance of H₂ for 60:40 H₂:CO₂ was found lower than single and binary mixture 75:25 H₂:CO₂. The binary selectivity values for 75:25 H₂:CO₂ were 24.75, 44, and 57, respectively. Selectivity had an inverse relation with PhTES content. Hydrophobicity properties were improved by increasing PhTES content in the silica matrix. The system exhibits proper three layers adhesion or integration, and smoothness. Membrane system suitable in steam environment and high-temperature separation. It was concluded that the hydrophobic silica membrane is highly promising for the separation of H₂/CO₂ mixture from various H₂-containing process streams.

Keywords: gas separation, hydrophobic properties, silica membrane, sol–gel method

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Authors: Munnujahan Ara

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In this paper, we investigate the effect of friendly jamming power allocation strategies on the achievable average secrecy rate over a bank of parallel fading wiretap channels. We investigate the achievable average secrecy rate in parallel fading wiretap channels subject to Rayleigh and Rician fading. The achievable average secrecy rate, due to the presence of a line-of-sight component in the jammer channel is also evaluated. Moreover, we study the detrimental effect of correlation across the parallel sub-channels, and evaluate the corresponding decrease in the achievable average secrecy rate for the various fading configurations. We also investigate the tradeoff between the transmission power and the jamming power for a fixed total power budget. Our results, which are applicable to current orthogonal frequency division multiplexing (OFDM) communications systems, shed further light on the achievable average secrecy rates over a bank of parallel fading channels in the presence of friendly jammers.

Keywords: fading parallel channels, wire-tap channel, OFDM, secrecy capacity, power allocation

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Authors: M. Celeska, K. Najdenkoski, V. Dimchev, V. Stoilkov

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Accurate determination of wind turbine performance is necessary for economic operation of a wind farm. At present, the procedure to carry out the power performance verification of wind turbines is based on a standard of the International Electrotechnical Commission (IEC). In this paper, nonparametric statistical inference is applied to designing a simple, inexpensive method of verifying the power performance of a wind turbine. A statistical test is explained, examined, and the adequacy is tested over real data. The methods use the information that is collected by the SCADA system (Supervisory Control and Data Acquisition) from the sensors embedded in the wind turbines in order to carry out the power performance verification of a wind farm. The study has used data on the monthly output of wind farm in the Republic of Macedonia, and the time measuring interval was from January 1, 2016, to December 31, 2016. At the end, it is concluded whether the power performance of a wind turbine differed significantly from what would be expected. The results of the implementation of the proposed methods showed that the power performance of the specific wind farm under assessment was acceptable.

Keywords: canonical correlation analysis, power curve, power performance, wind energy

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Authors: Sayed A. Elsayed, Emad Z. Ibrahim, Osama M. Mesalhy, Mohamed A. Abdelatief

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An experimental and numerical study has been conducted to clarify fluid flow characteristics and pressure drop distributions of a cross-flow heat exchanger employing staggered wing-shaped tubes at different angels of attack. The water-side Rew and the air-side Rea were at 5 x 102 and at from 1.8 x 103 to 9.7 x 103, respectively. Three cases of the tubes arrangements with various angles of attack, row angles of attack and 90° cone angles were employed at the considered Rea range. Correlation of pressure drop coefficient Pdc in terms of Rea, design parameters for the studied cases were presented. The flow pattern around the staggered wing-shaped tubes bundle were predicted by using commercial CFD FLUENT 6.3.26 software package. Results indicated that the values of Pdc were increased by increasing the angle of attack from 0° to 45°, while the opposite was true for angles of attack from 135° to 180°. Comparisons between the experimental and numerical results of the present study and those, previously, obtained for similar available studies showed good agreements.

Keywords: wing-shaped tubes, cross-flow cooling, staggered arrangement, CFD

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Authors: Ezgi Cetinkaya

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In the psychological literature, there are a few studies that focus on actors' self-perceptions and their social adjustment skills. Therefore the aim of the study was to shed light on the self-concept clarity, sociotrophy, and self-monitoring levels of professional actors. For this purpose, actors and non-actors are compared to their peers. The study was conducted with the participation of 106 actors and 131 non-actors. A descriptive method of research was employed and data was collected through the concept Clarity scale by Campbell et al. (1996), the Pleasing Others and Concern For Disapproval subscales of Sociotrophy and Autonomy scale by Beck et al. (1983), and the Self-Monitoring Scale by Snyder ( 1983). ANOVA and correlation analysis was done by using SPSS. Results showed that there is no significant difference between actors and non-actors at any age in terms of Self Concept Clarity. 25-25 years non-actors were found to have the highest self-concept clarity while the young actors had the lowest. The study didn’t reveal significant differences between the groups in terms of Sociotropy scores. The actor’s sociothropic tendencies weren’t enhanced by the experience. The study demonstrated that 25-35-year-old actors are higher self-monitors than 25-35-year-old non-actors.

Keywords: self-concept, self-monitoring, autonomy, sociotropy, theatre, acting, creativity, identity

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Authors: Hari Krishan Sharma, Sanjay Kumar Sharma, Sushil Kumar Swar

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Inadequate transverse reinforcement is considered as the main reason for the beam column joint shear failure observed during recent earthquakes. DSP matrix consists of cement and high content of micro-silica with low water to cement ratio while the aggregates are graded quartz sand. The use of reinforcing fibres leads not only to the increase of tensile/bending strength and specific fracture energy, but also to reduction of brittleness and, consequently, to production of non-explosive ruptures. Besides, fibre-reinforced materials are more homogeneous and less sensitive to small defects and flaws. Recent works on the freeze-thaw durability (also in the presence of de-icing salts) of fibre-reinforced DSP confirm the excellent behaviour in the expected long term service life.DSP materials, including fibre-reinforced DSP and CRC (Compact Reinforced Composites) are obtained by using high quantities of super plasticizers and high volumes of micro-silica. Steel fibres with high tensile yield strength of smaller diameter and short length in different fibre volume percentage and aspect ratio tilized to improve the performance by reducing the brittleness of matrix material. In the case of High Performance Densified Small Particle Concrete (HPDSPC), concrete is dense at the micro-structure level, tensile strain would be much higher than that of the conventional SFRC, SIFCON & SIMCON. Beam-column sub-assemblages used as moment resisting constructed using HPDSPC in the joint region with varying quantities of steel fibres, fibre aspect ratio and fibre orientation in the critical section. These HPDSPC in the joint region sub-assemblages tested under cyclic/earthquake loading. Besides loading measurements, frame displacements, diagonal joint strain and rebar strain adjacent to the joint will also be measured to investigate stress-strain behaviour, load deformation characteristics, joint shear strength, failure mechanism, ductility associated parameters, stiffness and energy dissipated parameters of the beam column sub-assemblages also evaluated. Finally a design procedure for the optimum design of HPDSPC corresponding to moment, shear forces and axial forces for the reinforced concrete beam-column joint sub-assemblage proposed. The fact that the implementation of material brittleness measure in the design of RC structures can improve structural reliability by providing uniform safety margins over a wide range of structural sizes and material compositions well recognized in the structural design and research. This lead to the development of high performance concrete for the optimized combination of various structural ratios in concrete for the optimized combination of various structural properties. The structural applications of HPDSPC, because of extremely high strength, will reduce dead load significantly as compared to normal weight concrete thereby offering substantial cost saving and by providing improved seismic response, longer spans, and thinner sections, less reinforcing steel and lower foundation cost. These cost effective parameters will make this material more versatile for use in various structural applications like beam-column joints in industries, airports, parking areas, docks, harbours, and also containers for hazardous material, safety boxes and mould & tools for polymer composites and metals.

Keywords: high performance densified small particle concrete (HPDSPC), steel fibre reinforced concrete (SFRC), slurry infiltrated concrete (SIFCON), Slurry infiltrated mat concrete (SIMCON)

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Authors: Mohammed T. Hayajneh

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Machining of Metal Matrix Composites (MMCs) is very significant process and has been a main problem that draws many researchers to investigate the characteristics of MMCs during different machining process. The poor machining properties of hard particles reinforced MMCs make drilling process a rather interesting task. Unlike drilling of conventional materials, many problems can be seriously encountered during drilling of MMCs, such as tool wear and cutting forces. Cutting tool wear is a very significant concern in industries. Cutting tool wear not only influences the quality of the drilled hole, but also affects the cutting tool life. Prediction the cutting tool life during drilling is essential for optimizing the cutting conditions. However, the relationship between tool life and cutting conditions, tool geometrical factors and workpiece material properties has not yet been established by any machining theory. In this research work, fuzzy subtractive clustering system has been used to model the cutting tool life in drilling of Al₂O₃ particle reinforced aluminum alloy composite to investigate of the effect of cutting conditions on cutting tool life. This investigation can help in controlling and optimizing of cutting conditions when the process parameters are adjusted. The built model for prediction the tool life is identified by using drill diameter, cutting speed, and cutting feed rate as input data. The validity of the model was confirmed by the examinations under various cutting conditions. Experimental results have shown the efficiency of the model to predict cutting tool life.

Keywords: composite, fuzzy, tool life, wear

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Authors: Thammamonr Khunrattanaporn

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The purpose of the research was to examine the relationship between the marketing mix factors and valuable of Muay Thai Training and Thai massage in foreign tourists’ perception. The research used the 8 P’s of marketing framework presented in the theory of compound marketing services strategy. Data was collect using survey for 400 questionnaires using the Quota sampling from foreign tourists travelling in Thailand. The data was analyzed to determine valuation statistics, the frequency, percent average, means and standard deviation and pearson's correlation coefficients. The result shows the foreign tourists’ perception with the marketing mix strategy in term of Muay Thai training and massage regarding curriculum areas: product, pricing, channel distribution, Promotion, Personnel services, Physical evidence and external partnerships the overall, it significant at a high level. The awareness level of service and value for travelers had two aspects of service quality and value for money it significant at the highest level.

Keywords: foreign tourists’ perception, marketing mix strategy, Muay Thai training, the massage

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Authors: G. Beulah Gnana Ananthi, A. Jaffer Sathick, M. Abirami

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Fibre reinforced concrete (FRC) has been widely used in industrial pavements and non-structural elements such as pipes, culverts, tunnels, and precast elements. The strengthening effect of fibres in the concrete matrix is achieved primarily due to the bridging effect of fibres at the crack interfaces. The workability of the concrete was reduced on addition of high percentages of steel fibres. The optimum percentage of addition of steel fibres varies with its aspect ratio. For this study, 1% addition of steel has resulted to be the optimum percentage for both Hooked and Crimped Steel Fibres and was added to the beam specimens. The fibres restrain efficiently the cracks and take up residual stresses beyond the cracking. In this sense, diagonal cracks are effectively stitched up by fibres crossing it. The failure of beams within the shear failure range changed from shear to flexure in the presence of sufficient steel fibre quantity. The shear strength is increased with the addition of steel fibres and had exceeded the enhancement obtained with the transverse reinforcement. However, such increase is not directly in proportion with the quantity of fibres used. Considering all the clarification made in the present experimental investigation, it is concluded that 1% of crimped steel fibres with an aspect ratio of 50 is the best type of steel fibres for replacement of transverse stirrups in high strength concrete beams when compared to the steel fibres with hooked ends.

Keywords: fibre reinforced concrete, steel fibre, shear strength, crack pattern

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Authors: Paulina Solórzano Salgado, Luis Rodrigo Valencia Pérez, Alberto de Jesús Pastrana Palma

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In this research, it is presented a digital maturity framework, which contributes to the development of small and medium-sized enterprises (SMEs) in the commercial sector. This proposal is based on three important concepts: Marketing activities in the enterprise, information and communication technologies ICT, as well as Innovation. Prior to the development of this framework, was formulated a quantitative assessment tool through a literature review, and was validated with a method used by experts, and which determines the relationship of digital marketing and innovation activities in companies. The instrument was applied to 64 Mexican companies from the Made in Mexico database, which allowed both descriptive results and correlation results. These contributed to the development of the methodology, and confirming that the management of digital marketing has a positive relation with innovation activities of companies. Also, that analytics in digital marketing is a source for its development. In this paper, the management stages and activities are presented to be developed by companies in order to generate knowledge, which will allow them to reach its digital maturity.

Keywords: digital marketing, digital maturity, innovation, SMEs

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Authors: Benhui Fan, Fahmi Bedoui, Jinbo Bai

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Incorporated carbon nanotube-BaTiO₃ hybrids (H-CNT-BT) with core-shell structure, a better dispersion of CNTs can be achieved in a semi-crystalline polymeric matrix, polyvinylidene fluoride (PVDF). Carried by BT particles, CNTs are easy to mutually connect which helps to obtain an extremely low percolation threshold (fc). After thermal treatments, the dielectric constants (ε’) of samples further increase which depends on the conditions of thermal treatments such as annealing temperatures, annealing durations and cooling ways. Thus, in order to study more comprehensively about the influence of thermal treatments on composite’s dielectric behaviors, in situ synchrotron X-ray is used to detect re-crystalline behavior of PVDF. Results of wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS) show that after the thermal treatment, the content of β polymorph (the polymorph with the highest ε’ among all the polymorphs of PVDF’s crystalline structure) has increased nearly double times at the interfacial region of CNT-PVDF, and the thickness of amorphous layers (La) in PVDF’s long periods (Lp) has shrunk around 10 Å. The evolution of CNT’s network possibly occurs in the procedure of La shrinkage, where the strong interfacial polarization may be aroused and increases ε’ at low frequency. Moreover, an increase in the thickness of crystalline lamella may also arouse more orientational polarization and improve ε’ at high frequency.

Keywords: dielectric properties, thermal treatments, carbon nanotubes, crystalline structure

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Authors: Bao Thach Nguyen, Abbas Mohajerani

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The California bearing ratio (CBR) has been acknowledged as an important parameter to characterize the bearing capacity of earth structures, such as earth dams, road embankments, airport runways, bridge abutments, and pavements. Technically, the CBR test can be carried out in the laboratory or in the field. The CBR test is time-consuming and is infrequently performed due to the equipment needed and the fact that the field moisture content keeps changing over time. Over the years, many correlations have been developed for the prediction of CBR by various researchers, including the dynamic cone penetrometer, undrained shear strength, and Clegg impact hammer. This paper reports and discusses some of the results from a study on the prediction of CBR. In the current study, the CBR test was performed in the laboratory on some fine-grained subgrade soils collected from various locations in Victoria. Based on the test results, a satisfactory empirical correlation was found between the CBR and the physical properties of the experimental soils.

Keywords: California bearing ratio, fine-grained soils, soil physical properties, pavement, soil test

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Authors: Sheng Huang, Xin Zhao, Xiaofeng Gao, Tao Zhou, Shijin Dai, Youcai Zhao

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Adsorption of heavy metal pollutants (Zn, Cd, Pb, Cr, Cu) and organic pesticide (phorate, dithiophosphate diethyl, triethyl phosphorothioate), along with their multi-contamination on the surface of industrial construction & demolition waste (C&D waste) was investigated. Brick powder was selected as the appropriate waste while its maximum equilibrium adsorption amount of heavy metal under single controlled contamination matrix reached 5.41, 0.81, 0.45, 1.13 and 0.97 mg/g, respectively. Effects of pH and spiking dose of ICDW was also investigated. Equilibrium adsorption amount of organic pesticide varied from 0.02 to 0.97 mg/g, which was negatively correlated to the size distribution and hydrophilism. Existence of organic pesticide on surface of ICDW caused various effects on the heavy metal adsorption, mainly due to combination of metal ions and the floccule formation along with wrapping behaviors by pesticide pollutants. Adsorption of Zn was sharply decreased from 7.1 to 0.15 mg/g compared with clean ICDW and phorate contaminated ICDW, while that of Pb, Cr and Cd experienced an increase- then decrease procedure. On the other hand, runoff of pesticide contaminants was investigated under 25 mm/h simulated rainfall. Results showed that the cumulative runoff amount fitted well with curve obtained from a power function, of which r2=0.95 and 0.91 for 1DAA (1 day between contamination and runoff) and 7DAA, respectively. This study helps provide evaluation of industrial construction and demolition waste contamination into aquatic systems.

Keywords: adsorption mechanism, industrial construction waste, metals, pesticide, runoff

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Hala O. El-Mesallamy, Salwa M. Suwailem, Mae M. Seleem

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Visfatin and apelin are two new adipokines that recently gained a special interest in diabetes research. This study was conducted to study the interplay between these two adipokines and their correlation with other inflammatory and biochemical parameters in type 2 diabetic (T2D) postmenopausal women with CAD. Visfatin and apelin were measured by enzyme-linked immunoassay (ELISA). Visfatin was found to be significantly higher in the following groups: T2D patients without CAD, non-obese and obese T2D patients with CAD when compared to control group. Apelin was found to be significantly lower in non-obese and obese T2D patients with CAD when compared to control group. Visfatin and apelin were found to be significantly associated with each other and with other biochemical parameters. The current study provides evidence for the interplay between visfatin and apelin through the inflammatory milieu characteristic of T2D and their possible role in the pathogenesis of CAD complication of T2D.

Keywords: apelin, coronary artery disease, inflammation, type 2 diabetes, visfatin

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Authors: Abiodun Amusan, Olugbenga Akinola, Kazeem Akano, María Hernández-Castañeda, Jenna Dick, Akintunde Sowunmi, Geoffrey Hart, Grace Gbotosho

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Introduction: Artemisinin-based Combination Therapy (ACTs) is the cornerstone malaria treatment option in most malaria-endemic countries. Unfortunately, the malaria control effort is constantly being threatened by resistance of Plasmodium falciparum to ACTs. The recent evidence of artemisinin resistance in East Africa and its possibility of spreading to other African regions portends an imminent health catastrophe. This study aimed at evaluating the occurrence, prevalence, and influence of artemisinin-resistance markers on treatment outcomes in Ibadan before and after post-adoption of artemisinin combination therapy (ACTs) in Nigeria in 2005. Method: The study involved day zero dry blood spot (DBS) obtained from malaria patients during retrospective (2000-2005) and prospective (2021) studies. A cohort in the prospective study received oral dihydroartemisinin-piperaquine and underwent a 42-day follow-up to observe treatment outcomes. Genomic DNA was extracted from the DBS samples using a QIAamp blood extraction kit. Fragments of P. falciparum kelch13 (Pfkelch13), P. falciparum coronin (Pfcoronin), P. falciparum multidrug resistance 2 (PfMDR2), and P. falciparum chloroquine resistance transporter (PfCRT) genes were amplified and sequenced on a sanger sequencing platform to identify artemisinin resistance-associated mutations. Mutations were identified by aligning sequenced data with reference sequences obtained from the National Center for Biotechnology Information. Data were analyzed using descriptive statistics and student t-tests. Results: Mean parasite clearance time (PCT) and fever clearance time (FCT) were 2.1 ± 0.6 days (95% CI: 1.97-2.24) and 1.3 ± 0.7 days (95% CI: 1.1-1.6) respectively. Four mutations, K189T [34/53(64.2%)], R255K [2/53(3.8%)], K189N [1/53(1.9%)] and N217H [1/53(1.9%)] were identified within the N-terminal (Coiled-coil containing) domain of Pfkelch13. No artemisinin resistance-associated mutation usually found within the β-propeller domain of the Pfkelch13 gene was found in these analyzed samples. However, K189T and R255K mutations showed a significant correlation with longer parasite clearance time in the patients (P<0.002). The observed Pfkelch13 gene changes did not influence the baseline mean parasitemia (P = 0.44). P76S [17/100 (17%)] and V62M [1/100 (1%)] changes were identified in the Pfcoronin gene fragment without any influence on the parasitological parameters. No change was observed in the PfMDR2 gene, while no artemisinin resistance-associated mutation was found in the PfCRT gene. Furthermore, a sample each in the retrospective study contained the Pfkelch13 K189T and Pfcoronin P76S mutations. Conclusion: The study revealed absence of genetic-based evidence of artemisinin resistance in the study population at the time of study. The high frequency of K189T Pfkelch13 mutation and its correlation with increased parasite clearance time in this study may depict geographical variation of resistance mediators and imminent artemisinin resistance, respectively. The study also revealed an inherent potential of parasites to harbour drug-resistant genotypes before the introduction of ACTs in Nigeria.

Keywords: artemisinin resistance, plasmodium falciparum, Pfkelch13 mutations, Pfcoronin

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Authors: Patrick Cummings, Laura Cassani, Deirdre Kelliher

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In this paper we present findings from a research effort to apply a hybrid collaborative-context approach for a system focused on Marine Corps civil affairs data collection, aggregation, and analysis called the Marine Civil Information Management System (MARCIMS). The goal of this effort is to provide operators with information to make sense of the interconnectedness of entities and relationships in their area of operation and discover existing data to support civil military operations. Our approach to build a recommendation engine was designed to overcome several technical challenges, including 1) ensuring models were robust to the relatively small amount of data collected by the Marine Corps civil affairs community; 2) finding methods to recommend novel data for which there are no interactions captured; and 3) overcoming confirmation bias by ensuring content was recommended that was relevant for the mission despite being obscure or less well known. We solve this by implementing a combination of collective matrix factorization (CMF) and graph-based random walks to provide recommendations to civil military operations users. We also present a method to resolve the challenge of computation complexity inherent from highly connected nodes through a precomputed process.

Keywords: Recommendation engine, collaborative filtering, context based recommendation, graph analysis, coverage, civil affairs operations, Marine Corps

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Sanja Seljan, Ivan Dunđer

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The paper presents combined automatic speech recognition (ASR) for English and machine translation (MT) for English and Croatian in the domain of business correspondence. The first part presents results of training the ASR commercial system on two English data sets, enriched by error analysis. The second part presents results of machine translation performed by online tool Google Translate for English and Croatian and Croatian-English language pairs. Human evaluation in terms of usability is conducted and internal consistency calculated by Cronbach's alpha coefficient, enriched by error analysis. Automatic evaluation is performed by WER (Word Error Rate) and PER (Position-independent word Error Rate) metrics, followed by investigation of Pearson’s correlation with human evaluation.

Keywords: automatic machine translation, integrated language technologies, quality evaluation, speech recognition

Procedia PDF Downloads 467

Authors: Noureddine Ramdani

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In recent years, extensive attention has been given to the study of conductive nanocomposites due to their unique properties, which are dependent on their size and shape. The potential applications of these materials include electromagnetic interference shielding, energy storage, photovoltaics, and others. These outstanding properties have led to increased interest and research in this field. In this work, a conductive poly benzoxazine nanocomposite, PBZ/Gr-Cu, was synthesized through a compression molding technique to achieve a high-performance material suitable for electromagnetic interference (EMI) shielding applications. The microstructure of the nanocomposites was analyzed using scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR). The thermal stability, electrical conductivity, and EMI shielding properties of the nanocomposites were evaluated using thermogravimetric analysis, a four-point probe, and a VNA analyzer, respectively. The TGA results revealed that the thermal stability and electrical conductivity of the nanocomposites were significantly enhanced by the incorporation of Gr/Cu nanoparticles. The nanocomposites exhibited a low percolation threshold of about 3.5 wt.% and an increase in carrier concentration and mobility of the carriers with increasing hybrid nanofiller content, causing the composites to behave as n-type semiconductors. These nanocomposites also displayed a high dielectric constant and a high dissipation factor in the frequency range of 8-12 GHz, resulting in higher EMI shielding effectiveness (SE) of 25-44 dB. These characteristics make them promising candidates for lightweight EMI shielding materials in aerospace and radar evasion applications.

Keywords: polybenzoxazine matrix, conductive nanocomposites, electrical conductivity, EMI shielding

Procedia PDF Downloads 64

Authors: Amir Ikram, Qin Su, Muhammad Fiaz, Muhammad Waqas Shabbir

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Women entrepreneurship witnessed a healthy rise in the last decade or so, and the scenario in Pakistan is not different. However female leaders are facing various, cultural, career oriented, and professional challenges. The study investigates the impact of social and industry-specific challenges on female entrepreneurship; social challenges was evaluated in terms of culture, and industry-specific challenges was measured in terms of team management and career growth. Purposive sampling was employed to collect data from 75 multicultural organizations operating in the culturally diverse and historic city of Lahore, Pakistan. Cronbach’s alpha was conducted to endorse the reliability of survey questionnaire, while correlation and regression analysis were used to test hypotheses. Industry-specific challenges were found to be more significant as compared to cultural factors. The paper also highlights the importance of female entrepreneurship for emerging economies, and suggests that bringing women to mainstream professions can lead to economic success.

Keywords: cultural challenges, emerging economy, female entrepreneurship, leadership

Procedia PDF Downloads 310

Authors: Naila Naseer

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Emotional Intelligence (EI) concept is not new yet unique and interesting. EI is a person’s ability to be aware of his/her own emotions and to manage, handle and communicate emotions with others effectively. The present study was conducted to assess the relationship between emotional intelligence and age of graduate level students at Allama Iqbal Open University (AIOU). Population consisted of Allama Iqbal Open University students (B.Ed 3rd Semester, Autumn 2007) from Rawalpindi and Islamabad regions. Total number of sample consisted of 469 participants was randomly drawn out by using table of random numbers. Bar-On EQ-i was administered on the participants through personal contact. The instrument was also validated through pilot study on a random sample of 50 participants (B.Ed students Spring 2006), who had completed their B.Ed degree successfully. Data was analyzed and tabulated in percentages, frequencies, mean, standard deviation, correlation, and scatter gram in SPSS (version 16.0 for windows). The results revealed that students with higher age group had scored low on the scale (Bar-On EQ-i). Moreover, the students in low age groups exhibited higher levels of EI as compared with old age students.

Keywords: emotional intelligence, age level, learning, emotion-related feelings

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Authors: Mitra Ghiasi, Roghayeh Ghorbani Bousari

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Nowadays, the aim of the organizations is to gain sustainable competitive. So, developing their intellectual capital, encouraging innovation, increasing suitable performance can be done by knowledge management. Knowledge turns into science if knowledge is used to improve decision making, decision quality and make effective decisions. The current research intends to investigate the relationship between cybernetics and knowledge management from the perspective of users who are members of electronic discussion groups (ALA, ALIA). The research methodology is survey method, and it is a type of correlation research. Cybernetics and knowledge management questionnaires used for collecting data. The questionnaire that was designed in electronic format, distributed among two electronic discussion groups during 30 days and completed by 100 members of each electronic discussion groups. The finding of this research showed that although cybernetics has an impact on knowledge management, there is no significant difference between the ALA and ALIA user's view regard to effect of cybernetics on knowledge management. The results also indicated that this conceptual model is consistent with the data collected from the sample.

Keywords: ALA discussion group, ALIA discussion group, cybernetics, knowledge management

Procedia PDF Downloads 222

Authors: Robson da C. Santos, Carlos Henrique de A. S. P. Coutinho, Lucas Moreira Dias, Gerson Gomes Cunha

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The article refers to the development of an augmented reality 3D display, through the control of servo motors and projection of image with aid of video projector on the model. Augmented Reality is a branch that explores multiple approaches to increase real-world view by viewing additional information along with the real scene. The article presents the broad use of electrical, electronic, mechanical and industrial automation for geospatial visualizations, applications in mathematical models with the visualization of functions and 3D surface graphics and volumetric rendering that are currently seen in 2D layers. Application as a 3D display for representation and visualization of Digital Terrain Model (DTM) and Digital Surface Models (DSM), where it can be applied in the identification of canyons in the marine area of the Campos Basin, Rio de Janeiro, Brazil. The same can execute visualization of regions subject to landslides, as in Serra do Mar - Agra dos Reis and Serranas cities both in the State of Rio de Janeiro. From the foregoing, loss of human life and leakage of oil from pipelines buried in these regions may be anticipated in advance. The physical design consists of a table consisting of a 9 x 16 matrix of servo motors, totalizing 144 servos, a mesh is used on the servo motors for visualization of the models projected by a retro projector. Each model for by an image pre-processing, is sent to a server to be converted and viewed from a software developed in C # Programming Language.

Keywords: visualization, 3D models, servo motors, C# programming language

Procedia PDF Downloads 323

Authors: Dilip Depan, Austin Simoneaux, William Chirdon, Ahmed Khattab

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In this study, we present a novel approach to synthesize polymer nanocomposites with nanohybrid shish-kebab architecture (NHSK). For this low-density and high density polyethylene (PE) was crystallized on various carbon nano-fillers using a novel and convenient method to prepare high-yield NHSK. Polymer crystals grew epitaxially on carbon nano-fillers using a solution crystallization method. The mixture of polymer and carbon fillers in xylene was flocculated and precipitated in ethanol to improve the product yield. Carbon nanofillers of varying diameter were also used as a nucleating template for polymer crystallization. The morphology of the prepared nanocomposites was characterized scanning electron microscopy (SEM), while differential scanning calorimetry (DSC) was used to quantify the amount of crystalline polymer. Interestingly, whatever the diameter of the carbon nanofiller is, the lamellae of PE is always perpendicular to the long axis of nanofiller. Surface area analysis was performed using BET. Our results indicated that carbon nanofillers of varying diameter can be used to effectively nucleate the crystallization of polymer. The effect of molecular weight and concentration of the polymer was discussed on the basis of chain mobility and crystallization capability of the polymer matrix. Our work shows a facile, rapid, yet high-yield production method to form polymer nanocomposites to reveal application potential of NHSK architecture.

Keywords: carbon nanotubes, polyethylene, nanohybrid shish-kebab, crystallization, morphology

Procedia PDF Downloads 313