Search results for: performance analysis

Authors: Mohammad Ali Ghareh, Habib Honari, Alireza Ahmadi

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The aim of this study was to investigate the relationship between strategic management and organizational culture in sport federations of Islamic Republic of Iran. Strategic management is a set of decisions and actions which define the long term performance of an organization. Organizational culture can be considered as an identity for every organization and somehow gives an identification to organization members. Organizational culture result in a certain commitments in organization members which is more valuable than individual profits and interests. The method of research was descriptive and correlational, conducted as a field study. The statistical population consisted of the employees of 10 sports federations and 170 persons were selected as sample. For data gathering, Barringer and Bluedorn’s strategic management questionnaire (1999) and Sakyn’s organizational culture questionnaire (2001) were used. The reliability of the questionnaires were 0.82 and 0.80 respectively, and the validity was approved by 8 experienced professors in sport management. To analyze data, KS (Kolmogorov–Smirnov) test and Pearson's coefficient were used. The results have shown that there is a significant meaningful relationship between strategic management and organizational culture (p < 0.05, r= 0.62). Beside this, there is a positive relationship between strategic management variables including scanning intensity, planning flexibility, locus of planning, planning horizon, strategic controls, and organizational culture (p < 0.05). Based on this research result it can be derived that strategic management planning and operation in terms of appropriate organizational culture is more applicable. By agreeing on their values and beliefs, adaptation to changes, caring about the individualities, coordination in tasks, modifying the individual and organizational goals, the federations will be able to achieve their strategic goals.

Keywords: strategic management, organizational culture, sports federations, Islamic Republic of Iran

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Authors: Muhammad A. Alsubaie, Mubarak K. H. Alhajri, Tarek S. Altowaim

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A repetitive controller designed to accommodate periodic disturbances via state feedback is discussed. Periodic disturbances can be represented by a time delay model in a positive feedback loop acting on system output. A direct use of the small gain theorem solves the periodic disturbances problem via 1) isolating the delay model, 2) finding the overall system representation around the delay model and 3) designing a feedback controller that assures overall system stability and tracking error convergence. This paper addresses uncertainty conditions for the repetitive controller designed in state feedback in either past error feedforward or current error feedback using singular values. The uncertainty investigation is based on the overall system found and the stability condition associated with it; depending on the scheme used, to set an upper/lower limit weighting parameter. This creates a region that should not be exceeded in selecting the weighting parameter which in turns assures performance improvement against system uncertainty. Repetitive control problem can be described in lifted form. This allows the usage of singular values principle in setting the range for the weighting parameter selection. The Simulation results obtained show a tracking error convergence against dynamic system perturbation if the weighting parameter chosen is within the range obtained. Simulation results also show the advantage of weighting parameter usage compared to the case where it is omitted.

Keywords: model mismatch, repetitive control, singular values, state feedback

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Authors: Monapat Sasingha, Suttisak Soralump

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This research presents the behavior of slope of the road along the canal stabilized by short piles. In this investigation, the centrifuge machine was used, modelling the condition of the water levels in the canal. The centrifuge tests were performed at 35 g. To observe the movement of the soil, visual analysis was performed to evaluate the failure behavior. Conclusively, the use of short piles to stabilize the canal slope proved to be an effective solution. However, the certain amount of settlement was found behind the short pile rows.

Keywords: centrifuge test, slope failure, embankment, stability of slope

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Authors: Shu-Han Hsu, Jiho Yoon, Chwen Sheu

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With the rapidly growing of blockchain technology and cryptocurrency, various industries which include tourism has added in cryptocurrency as the payment method of their transaction. More and more tourism companies accept payments in digital currency for flights, hotel reservations, transportation, and more. For travellers and tourists, using cryptocurrency as a payment method has become a way to circumvent costs and prevent risks. Understanding volatility dynamics and interdependencies between standard currency and cryptocurrency is important for appropriate financial risk management to assist policy-makers and investors in marking more informed decisions. The purpose of this paper has been to understand and explain the risk spillover effects between six major cryptocurrencies and the top ten most traded standard currencies. Using data for the daily closing price of cryptocurrencies and currency exchange rates from 7 August 2015 to 10 December 2019, with 1,133 observations. The diagonal BEKK model was used to analyze the co-volatility spillover effects between cryptocurrency returns and exchange rate returns, which are measures of how the shocks to returns in different assets affect each other’s subsequent volatility. The empirical results show there are co-volatility spillover effects between the cryptocurrency returns and GBP/USD, CNY/USD and MXN/USD exchange rate returns. Therefore, currencies (British Pound, Chinese Yuan and Mexican Peso) and cryptocurrencies (Bitcoin, Ethereum, Ripple, Tether, Litecoin and Stellar) are suitable for constructing a financial portfolio from an optimal risk management perspective and also for dynamic hedging purposes.

Keywords: blockchain, co-volatility effects, cryptocurrencies, diagonal BEKK model, exchange rates, risk spillovers

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Authors: Felipe Aguirre

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In this paper some of the relevant features of the πλῆκτρον within GrecoLatin tradition will be analyzed. Starting from the formal aspects (shape, materials, technical properties) and the archaeological evidence, some of its symbolic implications that emerge in the light of literary and iconographic analysis will be discussed. I shall expose that, in addition to fulfilling a purely physical function within the process of sound production, the πλῆκτρον was the object of a rich imaginery that provided it with an allegorical, metaphorical-poetic and even metaphysical dimension.

Keywords: musicology, ethnomusicology, ancient greek music, plectrum, stringed instruments

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Authors: Ly Nguyen, Vidit Munshi

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During the Covid-19 recession, the United States government has implemented several instruments to mitigate the impacts and revitalize the economy. This paper explores the effects of the various government policy decisions on stock returns, housing prices, and investor psychology during the pandemic in the United States. A numerous previous literature studies on this subject, yet very few focus on the context similar to what we are currently experiencing. Our monthly data covering the period from January 2019 through July 2021 were collected from Datastream. Utilizing the VAR model, we document a dynamic relationship between the market and policy actions throughout the period. In particular, the movements of Unemployment, Stock returns, and Housing prices are strongly sensitive to changes in government policies. Our results also indicate that changes in production level, stock returns, and interest rates decisions influence how investors perceived future market risk and expectations. We do not find any significant nexus between monetary and fiscal policy. Our findings imply that information on government policy and stock market performance provide useful feedback to one another in order to make better decisions in the current and future pandemic. Understanding how the market responds to a shift in government practices has important implications for authorities in implementing policy to avoid assets bubbles and market overreactions. The paper also provides useful implications for investors in evaluating the effectiveness of different policies and diversifying portfolios to minimize systematic risk and maximize returns.

Keywords: Covid-19 recession, United States, government policies, investor psychology, housing prices, stock market returns

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Authors: Boukrouh Soumaya, Cabaraux Jean-François, Avril Claire, Noutfia Ali, Chentouf Mouad

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The introduction of marginal leguminous forage species in the diet of ruminants are of great importance. Bitter vetch is a good source of proteins, highly resistant against drought and poor soil conditions. Accordingly; two years field trials (2018/2019 and 2019-2020) were conducted to determine the digestibility of straw and grains of 17 promising bitter vetch ecotypes(Vicia ervilia) in the north of Morocco. In vitro dry and organic matter digestibility, gas production, and kinetics of fermentation of grains and straw were evaluated using gas production technique, pepsin-cellulase enzymatic digestibility of DM (CDDM)and OM (CDOM), as well as protease enzymatic CP degradation (CPD) and in vitro true digestibility, were performed using DAISYII Incubator. In vitro digestibility was performed using gas production method of (Menke et al., 1979) improved by Menke and Steingass (1988). Samples were incubated in glass syringes that contained rumen fluid and incubation solution that conserved in water bath in 39°C during 72 hours. Gas production was recorded after 2, 4, 8, 12, 24, 48, and 72 hours. Studied digestibility parameters were dry and organic matter digestibility, microbial biomass production, partitioning factor, and volatile fatty acids. Enzymatic dry matter digestibility was different (p < 0.05) among grains and straw for all ecotypes. It varied from 804.1 to 957.7 g/kg DM and 270.4 to 412.3 g/kg DM for grains and straw, respectively. Metabolizable energy varied between 11.7 to 14.3 MJ/kg DM and 2.6 to 5.0 MJ/kg DM for grains and straw, respectively. Potential gas production (A), the rate constants (c and d), and lag times of grains and straws from different bitter vetch ecotypes were different (p > 0.05). The results emphasized that in any evaluation of bitter vetch ecotypes, where straw of this legume seed is used as an animal feed, not only seed yield but also yield and quality of straw should be taken into consideration, particularly in areas where straw from this legume is considered as an important feedstuff for ruminants. Enzymatic digestibility was lower than in vitro digestibility by gaz production and by the DAISYII method because rumen fluid contains bacteria than increase digestibility. There was no difference between in vitro digestibility by gaz production and the DAISY II method. The DAISY II method can be used to increase labor efficiency in the in vitro DM digestibility analysis if gaz production is not necessary for analysis.

Keywords: bitter vetch, grains, straw, ecotype, in vitro digestibility, gaz production, enzymatic digestibility

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Authors: Lakshay Kharbanda, Aabhas Chauhan

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In this paper, an application of Normalized Compression Distance (NCD) to detect notable scene alterations occurring in videos is presented. Several research groups have been developing methods to perform image classification using NCD, a computable approximation to Normalized Information Distance (NID) by studying the degree of similarity in images. The timeframes where significant aberrations between the frames of a video have occurred have been identified by obtaining a threshold NCD value, using two compressors: LZMA and BZIP2 and defining scene alterations using Pixel Difference Percentage metrics.

Keywords: image compression, Kolmogorov complexity, normalized compression distance, root mean square error

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Authors: Tanu Khanuja, Harikrishnan N. Unni

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Head is the most vulnerable part of human body and may cause severe life threatening injuries. As the in vivo brain response cannot be recorded during injury, computational investigation of the head model could be really helpful to understand the injury mechanism. Majority of the physical damage to living tissues are caused by relative motion within the tissue due to tensile and shearing structural failures. The present Finite Element study focuses on investigating intracranial pressure and stress/strain distributions resulting from impact loads on various sites of human head. This is performed by the development of the 3D model of a human head with major segments like cerebrum, cerebellum, brain stem, CSF (cerebrospinal fluid), and skull from patient specific MRI (magnetic resonance imaging). The semi-automatic segmentation of head is performed using AMIRA software to extract finer grooves of the brain. To maintain the accuracy high number of mesh elements are required followed by high computational time. Therefore, the mesh optimization has also been performed using tetrahedral elements. In addition, model validation with experimental literature is performed as well. Hard tissues like skull is modeled as elastic whereas soft tissues like brain is modeled with viscoelastic prony series material model. This paper intends to obtain insights into the severity of brain injury by analyzing impacts on frontal, top, back, and temporal sites of the head. Yield stress (based on von Mises stress criterion for tissues) and intracranial pressure distribution due to impact on different sites (frontal, parietal, etc.) are compared and the extent of damage to cerebral tissues is discussed in detail. This paper finds that how the back impact is more injurious to overall head than the other. The present work would be helpful to understand the injury mechanism of traumatic brain injury more effectively.

Keywords: dynamic impact analysis, finite element analysis, intracranial pressure, MRI, traumatic brain injury, von Misses stress

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Authors: Haidy S. Ghali, Engy Serag, A. Samer Ezeldin

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Copper is an essential raw material used in the construction industry. During the year 2021 and the first half of 2022, the global market suffered from a significant fluctuation in copper raw material prices due to the aftermath of both the COVID-19 pandemic and the Russia-Ukraine war, which exposed its consumers to an unexpected financial risk. Thereto, this paper aims to develop two ANN-LSTM price prediction models, using Python, that can forecast the average monthly copper prices traded in the London Metal Exchange; the first model is a multivariate model that forecasts the copper price of the next 1-month and the second is a univariate model that predicts the copper prices of the upcoming three months. Historical data of average monthly London Metal Exchange copper prices are collected from January 2009 till July 2022, and potential external factors are identified and employed in the multivariate model. These factors lie under three main categories: energy prices and economic indicators of the three major exporting countries of copper, depending on the data availability. Before developing the LSTM models, the collected external parameters are analyzed with respect to the copper prices using correlation and multicollinearity tests in R software; then, the parameters are further screened to select the parameters that influence the copper prices. Then, the two LSTM models are developed, and the dataset is divided into training, validation, and testing sets. The results show that the performance of the 3-Month prediction model is better than the 1-Month prediction model, but still, both models can act as predicting tools for diverse economic situations.

Keywords: copper prices, prediction model, neural network, time series forecasting

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Authors: Z. Jamalzadeh, A. Niaei, H. Erfannia, S. G. Hosseini, A. S. Razmgir

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Due to developing the industries, the emission of pollutants such as NOx, SOx, and CO2 are rapidly increased. Generally, NOx is attributed to the mono nitrogen oxides of NO and NO2 that is one of the most important atmospheric contaminants. Hence, controlling the emission of nitrogen oxides is urgent environmentally. Selective Catalytic Reduction of NOx is one of the most common techniques for NOx removal in which Zeolites have wide application due to their high performance. In zeolitic processes, the catalytic reaction occurs mostly in the pores. Therefore, investigation the adsorption phenomena of the molecules in order to gain an insight and understand the catalytic cycle is of important. Hence, in current study, molecular simulations is applied for studying the adsorption phenomena in nanocatalysts applied for SCR of NOx process. The effect of cation addition to the support in the catalysts’ behavior through adsorption step was explored by Mont Carlo (MC). Simulation time of 1 Ns accompanying 1 fs time step, COMPASS27 Force Field and the cut off radios of 12.5 Ȧ was applied for performed runs. It was observed that the adsorption capacity increases in the presence of cations. The sorption isotherms demonstrated the behavior of type I isotherm categories and sorption capacity diminished with increase in temperature whereas an increase was observed at high pressures. Besides, NO sorption showed higher sorption capacity than NH3 in H–ZSM5. In this respect, the Energy distributions signified that the molecules could adsorb in just one sorption site at the catalyst and the sorption energy of NO was stronger than the NH3 in H-ZSM5. Furthermore, the isosteric heat of sorption data showed nearly same values for the molecules; however, it indicated stronger interactions of NO molecules with H-ZSM5 Zeolite compared to the isosteric heat of NH3 which was low in value.

Keywords: Monte Carlo simulation, adsorption, NOx, ZSM5

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Authors: Nanine Fouche

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The Cape Flats is a low-lying sand-covered expanse of approximately 460 square kilometres, situated to the southeast of the central business district of Cape Town in the Western Cape of South Africa. The aeolian sands masking this area are often loose and compressible in the upper 1m to 1.5m of the surface, and there is a general exceedance of the maximum allowable settlement in these sands. The settlement of shallow foundations on Cape Flats sands is commonly predicted using the results of in-situ tests such as the SPT or DPSH due to the difficulty of retrieving undisturbed samples for laboratory testing. Varying degrees of accuracy and reliability are associated with these methods. More recently, shear wave velocity (Vs) profiles obtained from seismic testing, such as continuous surface wave tests (CSW), are being used for settlement prediction. Such predictions have the advantage of considering non-linear stress-strain behaviour of soil and the degradation of stiffness with increasing strain. CSW tests are rarely executed in the Cape Flats, whereas SPT’s are commonly performed. For this reason, and to facilitate better settlement predictions in Cape Flats sand, equations representing shear wave velocity (Vs) as a function of SPT blow count (N60) and vertical effective stress (v’) were generated by statistical regression of site investigation data. To reveal the most appropriate method of overburden correction, analyses were performed with a separate overburden term (Pa/σ’v) as well as using stress corrected shear wave velocity and SPT blow counts (correcting Vs. and N60 to Vs1and (N1)60respectively). Shear wave velocity profiles and SPT blow count data from three sites masked by Cape Flats sands were utilised to generate 80 Vs-SPT N data pairs for analysis. Investigated terrains included sites in the suburbs of Athlone, Muizenburg, and Atlantis, all underlain by windblown deposits comprising fine and medium sand with varying fines contents. Elastic settlement analysis was also undertaken for the Cape Flats sands, using a non-linear stepwise method based on small-strain stiffness estimates, which was obtained from the best Vs-N60 model and compared to settlement estimates using the general elastic solution with stiffness profiles determined using Stroud’s (1989) and Webb’s (1969) SPT N60-E transformation models. Stroud’s method considers strain level indirectly whereasWebb’smethod does not take account of the variation in elastic modulus with strain. The expression of Vs. in terms of N60 and Pa/σv’ derived from the Atlantis data set revealed the best fit with R2 = 0.83 and a standard error of 83.5m/s. Less accurate Vs-SPT N relations associated with the combined data set is presumably the result of inversion routines used in the analysis of the CSW results showcasing significant variation in relative density and stiffness with depth. The regression analyses revealed that the inclusion of a separate overburden term in the regression of Vs and N60, produces improved fits, as opposed to the stress corrected equations in which the R2 of the regression is notably lower. It is the correction of Vs and N60 to Vs1 and (N1)60 with empirical constants ‘n’ and ‘m’ prior to regression, that introduces bias with respect to overburden pressure. When comparing settlement prediction methods, both Stroud’s method (considering strain level indirectly) and the small strain stiffness method predict higher stiffnesses for medium dense and dense profiles than Webb’s method, which takes no account of strain level in the determination of soil stiffness. Webb’s method appears to be suitable for loose sands only. The Versak software appears to underestimate differences in settlement between square and strip footings of similar width. In conclusion, settlement analysis using small-strain stiffness data from the proposed Vs-N60 model for Cape Flats sands provides a way to take account of the non-linear stress-strain behaviour of the sands when calculating settlement.

Keywords: sands, settlement prediction, continuous surface wave test, small-strain stiffness, shear wave velocity, penetration resistance

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Authors: Oliver Commichau, Richard Krimm, Bernd-Arno Behrens

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A growing demand on the production rate of modern presses leads to higher stroke rates. Commonly used material feeding devices for presses like grippers and roll-feeding systems can only achieve high stroke rates along with high gripper forces, to avoid stick-slip. These forces are limited by the sensibility of the surfaces of the workpieces. Stick-slip leads to scratches on the surface and false positioning of the workpiece. In this paper, a new contactless feeding device is presented, which develops higher feeding force without damaging the surface of the workpiece through gripping forces. It is based on the principle of the linear induction motor. A primary part creates a magnetic field and induces eddy currents in the electrically conductive material. A Lorentz-Force applies to the workpiece in feeding direction as a mutual reaction between the eddy-currents and the magnetic induction. In this study, the FEA model of this approach is shown. The calculation of this model was used to identify the influence of various design parameters on the performance of the feeder and thus showing the promising capabilities and limits of this technology. In order to validate the study, a prototype of the feeding device has been built. An experimental setup was used to measure pulling forces and placement accuracy of the experimental feeder in order to give an outlook of a potential industrial application of this approach.

Keywords: conductive material, contactless feeding, linear induction, Lorentz-Force

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Authors: El Mahdi Barrah, Said Safi, Abdessamad Malaoui

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In this paper, we present an algorithm for reconstruction from incomplete 2D scans for tifinagh characters. This algorithm is based on using correlation between the lost block and its neighbors. This system proposed contains three main parts: pre-processing, features extraction and recognition. In the first step, we construct a database of tifinagh characters. In the second step, we will apply “shape analysis algorithm”. In classification part, we will use Neural Network. The simulation results demonstrate that the proposed method give good results.

Keywords: Tifinagh character recognition, neural networks, local cost computation, ANN

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Authors: Thimma Reddy Pothireddy, Ramesh Srikonda

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India is prone to natural disasters such as Floods, droughts, cyclones, earthquakes and landslides frequently due to its geographical considerations. It has become a persistent phenomenon as observed in last ten decades. The recent survey indicates that about 60% of the landmass is prone to earthquakes of various intensities with reference to Richard scale, over 40 million hectares is prone to floods; about 8% of the total area is prone to cyclones and 68% of the area is vulnerable to drought. Climate change is likely to be perceived through the experience of extreme weather events. There is growing societal concern about climate change, given the potential impacts of associated natural hazards such as cyclones, flooding, earthquakes, landslides etc. The recent natural calamities such as Cyclone Hudhud had crossed the land at Northern cost of AP, Vishakapatanam on 12 Oct’2014 with a wind speed ranging between 175 – 200 kmph and the records show that the tidal waves were reached to the height of 14mts and above; and it alarms us to have critical focus on planning issues so as to find appropriate solutions. The existing condition is effective is in terms of institutional set up along with responsive management mechanism of disaster mitigation but considerations at settlement planning level to allow mitigation operations are not adequate. This paper deals to understand the response to climate change will possibly happen through adaptation to climate hazards and essential to work out an appropriate mechanism and disaster receptive settlement planning for responding to natural (and climate-related) calamities particularly to cyclones and floods. The statistics indicate that 40 million hectares flood prone (5% of area), and 1853 kmts of cyclone prone coastal length in India so it is essential and crucial to have appropriate physical planning considerations to improve preparedness and to operate mitigation measures effectively to minimize the loss and damage. Vijayawada capital region which is susceptible to cyclonic and floods has been studied with respect to trajectory analysis to work out risk vulnerability and to integrated disaster mitigation physical planning considerations.

Keywords: meta analysis, vulnerability index, physical planning, trajectories

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Authors: Khalid Javed

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This study examines a feature of the budget process called the tax expenditure budget. The tax expenditure concept relies heavily on a normative notion that shielding certain. Taxpayer income from taxation deprives government of its rightful revenues. This view is inconsistent with the proposition that income belongs to the taxpayers and that tax liability is determined through the democratic process, not through arbitrary, bureaucratic Assumptions. Furthermore, the methodology of the tax expenditure budget is problematic as its expansive tax base treats the multiple taxation of saving as the norm. By using an expansive view of income as the underlying assumption of the tax expenditure concept, this viewpoint institutionalizes a particular bias into the decision-making process.

Keywords: revenue, expenditure, tax budget, propostion

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Authors: Yves Mann Elate Lea Mbassi, Marie Solange Evehe Bebandoue, Wilfred Fon Mbacham

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Improving the catalytic performance of enzymes has been a long-standing theme of analytical biochemistry research. Induction of peroxidase activity by metals is a common reaction in higher plants. We thought that this increase in peroxidase activity may be due, on the one hand, to the stimulation of the gene expression of these enzymes but also to a modification of their chemical reactivity following the binding of some metal ions on their active site. We tested the effect of some metal salts (MgCl₂, MnCl₂, ZnCl₂, CaCl₂ and CuSO₄) on the activity and thermostability of peroxidase A6, a thermostable peroxidase that we discovered and purified in a previous study. The chromogenic substrate used was 3,3′,5,5′-tetramethylbenzidine. Of all the metals tested for their effect on A6, only magnesium and copper had a significant effect on the activity of the enzyme at room temperature. The Mann-Whitney test shows a slight inhibitory effect of activity by the magnesium salt (P = 0.043), while the activity of the enzyme is 5 times higher in the presence of the copper salt (P = 0.002). Moreover, the thermostability of peroxidase A6 is increased when calcium and copper salts are present. The activity in the presence of CaCl₂ is 8 times higher than the residual activity of the enzyme alone after incubation at 80°C for 10 min and 35 times higher in the presence of CuSO4 under the same conditions. In addition, manganese and zinc salts slightly reduce the thermostability of the enzyme. The activity and structural stability of peroxidase A6 can clearly be activated by Cu₂+, which therefore enhance the oxidation of 3,3′,5,5′-tetramethylbenzidine, which was used in this study as a chromogenic substrate. Ca₂+ likely has a more stabilizing function for the catalytic site.

Keywords: peroxidase activity, copper ions, calcium ions, thermostability

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Authors: A. Almaneea, N. Kapur, J. L. Summers, H. M. Thompson

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Meeting the growth in demand for digital services such as social media, telecommunications, and business and cloud services requires large scale data centres, which has led to an increase in their end use energy demand. Generally, over 30% of data centre power is consumed by the necessary cooling overhead. Thus energy can be reduced by improving the cooling efficiency. Air and liquid can both be used as cooling media for the data centre. Traditional data centre cooling systems use air, however liquid is recognised as a promising method that can handle the more densely packed data centres. Liquid cooling can be classified into three methods; rack heat exchanger, on-chip heat exchanger and full immersion of the microelectronics. This study quantifies the improvements of heat transfer specifically for the case of immersed microelectronics by varying the CPU and heat sink location. Immersion of the server is achieved by filling the gap between the microelectronics and a water jacket with a dielectric liquid which convects the heat from the CPU to the water jacket on the opposite side. Heat transfer is governed by two physical mechanisms, which is natural convection for the fixed enclosure filled with dielectric liquid and forced convection for the water that is pumped through the water jacket. The model in this study is validated with published numerical and experimental work and shows good agreement with previous work. The results show that the heat transfer performance and Nusselt number (Nu) is improved by 89% by placing the CPU and heat sink on the bottom of the microelectronics enclosure.

Keywords: CPU location, data centre cooling, heat sink in enclosures, immersed microelectronics, turbulent natural convection in enclosures

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Authors: Rui Lança, Elisa Silva, Fátima Farinha, Miguel José Oliveira, Manuel Duarte Pinheiro, Cátia Miguel

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Tourism has a great potential to bring up progress across the Sustainable Development Goals (SDGs). If well managed and monitored, the tourism sector can create quality jobs, reduce poorness and offer incentives for environmental preservation, helping on the transition towards more inclusive and resilient economies. However, without proper safeguards and investments, expansion of the tourism market will increase pressure on biodiversity and the ecosystems on which the livelihoods of local communities depend. Competitivity is a key dimension in tourism, sustainable tourism challenge new dimensions to competitivity, namely environmental, social, institutional and economic achieve a medium and long-term competitivity. It is undoubtedly clear on the tourism sector, the importance of the region sustainability in the current touristic destinations offer. The basis of a tourism region prosperity will depend on /of it. The OBSERVE project intends to be an instrument for monitoring and evaluating the sustainability levels of the Algarve region. Its main objective is to provide environmental, economic, social-cultural and institutional indicators to support the decision-making process for a sustainable growth of the region. The project´s main goal is a digital portal with the most relevant indicators to allow evaluating and communicating the performance of the region in a sustainable growth perspective. This paper presents the OBSERVE project and highlights the potential contribution to a broad perspective of competitivity and its contribution for different stakeholders and the touristic value chain. Limitations and opportunities are also discussed.

Keywords: sustainable tourism, competitivity, OBSERVE project, Algarve region

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Authors: Gu Pang, Bartosz Gebka

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We forecast the demand of total container throughput at the Indonesia’s largest seaport, Tanjung Priok Port. We propose four univariate forecasting models, including SARIMA, the additive Seasonal Holt-Winters, the multiplicative Seasonal Holt-Winters and the Vector Error Correction Model. Our aim is to provide insights into whether forecasting the total container throughput obtained by historical aggregated port throughput time series is superior to the forecasts of the total throughput obtained by summing up the best individual terminal forecasts. We test the monthly port/individual terminal container throughput time series between 2003 and 2013. The performance of forecasting models is evaluated based on Mean Absolute Error and Root Mean Squared Error. Our results show that the multiplicative Seasonal Holt-Winters model produces the most accurate forecasts of total container throughput, whereas SARIMA generates the worst in-sample model fit. The Vector Error Correction Model provides the best model fits and forecasts for individual terminals. Our results report that the total container throughput forecasts based on modelling the total throughput time series are consistently better than those obtained by combining those forecasts generated by terminal-specific models. The forecasts of total throughput until the end of 2018 provide an essential insight into the strategic decision-making on the expansion of port's capacity and construction of new container terminals at Tanjung Priok Port.

Keywords: SARIMA, Seasonal Holt-Winters, Vector Error Correction Model, container throughput

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Authors: Sergio Haram Sarmiento, Arcady Ponosov

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Based on appropriate multivariate statistical methodology, we suggest a generic framework for efficient parameter estimation for ordinary differential equations and the corresponding nonlinear models. In this framework classical linear regression strategies is refined into a nonlinear regression by a locally linear modelling technique (known as metamodelling). The approach identifies those latent variables of the given model that accumulate most information about it among all approximations of the same dimension. The method is applied to several benchmark problems, in particular, to the so-called ”power-law systems”, being non-linear differential equations typically used in Biochemical System Theory.

Keywords: principal component analysis, generalized law of mass action, parameter estimation, metamodels

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Authors: Loha Hashimy, Isabella Castillo

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In today's rapidly evolving technological landscape, the importance of precise navigation and mapping systems cannot be understated. As various sectors undergo transformative changes, the market potential for Advanced Mapping and Management Systems (AMMS) emerges as a critical focus area. The Galileo/GNSS-Based Autonomous Mobile Mapping System (GAMMS) project, specifically targeted toward high-definition mapping (HDM), endeavours to provide insights into this market within the broader context of the geomatics and navigation fields. With the growing integration of Autonomous Vehicles (AVs) into our transportation systems, the relevance and demand for sophisticated mapping solutions like HDM have become increasingly pertinent. The research employed a meticulous, lean, stepwise, and interconnected methodology to ensure a comprehensive assessment. Beginning with the identification of pivotal project results, the study progressed into a systematic market screening. This was complemented by an exhaustive desk research phase that delved into existing literature, data, and trends. To ensure the holistic validity of the findings, extensive consultations were conducted. Academia and industry experts provided invaluable insights through interviews, questionnaires, and surveys. This multi-faceted approach facilitated a layered analysis, juxtaposing secondary data with primary inputs, ensuring that the conclusions were both accurate and actionable. Our investigation unearthed a plethora of drivers steering the HD maps landscape. These ranged from technological leaps, nuanced market demands, and influential economic factors to overarching socio-political shifts. The meteoric rise of Autonomous Vehicles (AVs) and the shift towards app-based transportation solutions, such as Uber, stood out as significant market pull factors. A nuanced PESTEL analysis further enriched our understanding, shedding light on political, economic, social, technological, environmental, and legal facets influencing the HD maps market trajectory. Simultaneously, potential roadblocks were identified. Notable among these were barriers related to high initial costs, concerns around data quality, and the challenges posed by a fragmented and evolving regulatory landscape. The GAMMS project serves as a beacon, illuminating the vast opportunities that lie ahead for the HD mapping sector. It underscores the indispensable role of HDM in enhancing navigation, ensuring safety, and providing pinpoint, accurate location services. As our world becomes more interconnected and reliant on technology, HD maps emerge as a linchpin, bridging gaps and enabling seamless experiences. The research findings accentuate the imperative for stakeholders across industries to recognize and harness the potential of HD mapping, especially as we stand on the cusp of a transportation revolution heralded by Autonomous Vehicles and advanced geomatic solutions.

Keywords: high-definition mapping (HDM), autonomous vehicles, PESTEL analysis, market drivers

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Authors: Aly Audu Fada

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The mono-economic structure of Nigerian economy has made it depend on oil for so many years. Apart from the negative effect of its exploitation, relying solely on oil as the major source of revenue for peddling the ship of development is myopic. The crumbling oil price in the world market is one proof of the dangers of this over-dependence. This paper highlights the consequences of the oil-driven economy and explores the various opportunities that are accessible in tourism through a contextual analysis. It is recommended that those at the helm of affairs should initiate collaboration between the public and private sectors to explore and harness the rich tourism resources naturally dispersed across the country to achieve the objectives of economic transformation agenda of the Federal Government.

Keywords: diversifying, economic, tourism, oil

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Authors: Manjari Srivastsva, Ruta Vyas

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The research in the area of self leadership advocates employee/team empowerment. It is well understood that empowered employees would contribute more and better to their organizational outcomes. This research is a part of an ongoing larger research in the area of empowering leadership behavior. The present research aims to understand some of the antecedents to empowering behavior of leaders such that the organizations can focus on the right elements and invest in the appropriate areas during their leadership development activities. The research is exploratory field study. Sampling is purposive, employing triadic design i.e. a manager and two of his/her subordinates are selected for data collection. The total no. of respondents is 240, with 80 managers and 160 of their direct reports. Initially focus group interview was done and based on the inputs from focus group, quantitative data was collected personally by the researchers using questionnaire. The sample is drawn from seven professionally run organization including those of Indian origin as well as multi-national companies. This study proposes to explore the constituents of empowering behavior both from leaders’ and their subordinates’ perspective and also see the relationship between some of the personal variables of leaders as an antecedent to empowering behavior. Similarly, the study aims to explore the subordinates’ perspectives as an antecedent to empowering behavior. The relationship between antecedent variables and empowering behavior is tested for moderation employing organization culture. Exploratory and confirmatory factor analysis was done to establish the validity of the questionnaires. Further hierarchical regression analysis results revealed that organization based self-esteem and global self-esteem impact leaders’ empowering behavior and this relationship is further moderated by organization culture. Team members’ perspective showed higher importance for task characteristics and members' readiness from the point of view of empowerment. The relation between task characteristics and members’ readiness was not moderated by culture. The finding from this research may be utilized by professionals to guide organizations desiring rapid and sustainable growth, to develop leaders who empower their teams such that they act as leaders themselves and become stimulants for the growth of organizations.

Keywords: empowering behavior, team leaders, subordinates, self-esteem, organization culture, task characteristics, team members readiness

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Authors: Andrey Angorsky

Abstract:

In the article an issue about the possible number of fundamental physical interactions is studied. The theory of similarity on the dimensionless quantity as the damping ratio serves as the instrument of analysis. The structure with the features of Higgs field comes out from non-commutative expression for this ratio. The experimentally checked up supposition about the nature of dark energy is spoken out.

Keywords: damping ratio, dark energy, dimensionless quantity, fundamental physical interactions, Higgs field, non-commutative expression

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Authors: Achim Kampker, Heiner H. Heimes, Mathias Ordung, Christoph Lienemann, Ansgar Hollah, Nemanja Sarovic

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Electric cars with their fast innovation cycles and their disruptive character offer a high degree of freedom regarding innovative design for remanufacturing. Remanufacturing increases not only the resource but also the economic efficiency by a prolonged product life time. The reduced power train wear of electric cars combined with high manufacturing costs for batteries allow new business models and even second life applications. Modular and intermountable designed battery packs enable the replacement of defective or outdated battery cells, allow additional cost savings and a prolongation of life time. This paper discusses opportunities for future remanufacturing value chains of electric cars and their battery components and how to address their potentials with elaborate designs. Based on a brief overview of implemented remanufacturing structures in different industries, opportunities of transferability are evaluated. In addition to an analysis of current and upcoming challenges, promising perspectives for a sustainable electric car circular economy enabled by design for remanufacturing are deduced. Two mathematical models describe the feasibility of pursuing a circular economy of lithium ion batteries and evaluate remanufacturing in terms of sustainability and economic efficiency. Taking into consideration not only labor and material cost but also capital costs for equipment and factory facilities to support the remanufacturing process, cost benefit analysis prognosticate that a remanufacturing battery can be produced more cost-efficiently. The ecological benefits were calculated on a broad database from different research projects which focus on the recycling, the second use and the assembly of lithium ion batteries. The results of this calculations show a significant improvement by remanufacturing in all relevant factors especially in the consumption of resources and greenhouse warming potential. Exemplarily suitable design guidelines for future remanufacturing lithium ion batteries, which consider modularity, interfaces and disassembly, are used to illustrate the findings. For one guideline, potential cost improvements were calculated and upcoming challenges are pointed out.

Keywords: circular economy, electric mobility, lithium ion batteries, remanufacturing

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Authors: Alireza Alesaadi

Abstract:

Reliability analysis is a powerful method for determining the weak points of the electrical networks. In designing of electrical network, it is tried to design the most reliable network with minimal system shutting down, but it is usually associated with increasing the cost. In this paper, using adaptive genetic algorithm, a method was presented that provides the most reliable system with a certain economical cost. Finally, the proposed method is applied to a sample network and results will be analyzed.

Keywords: reliability, adaptive genetic algorithm, electrical network, communication engineering

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Authors: Saad M. Darwish, Adel A. El-Zoghabi, Moustafa F. Ashry

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The popularity of the Internet and the availability of powerful computers and high-speed networks as low-cost commodity components are changing the way we use computers today. These technical opportunities have led to the possibility of using geographically distributed and multi-owner resources to solve large-scale problems in science, engineering, and commerce. Recent research on these topics has led to the emergence of a new paradigm known as Grid computing. To achieve the promising potentials of tremendous distributed resources, effective and efficient load balancing algorithms are fundamentally important. Unfortunately, load balancing algorithms in traditional parallel and distributed systems, which usually run on homogeneous and dedicated resources, cannot work well in the new circumstances. In this paper, the concept of a fast fractal transform in heterogeneous grid computing based on R-tree and the domain-range entropy is proposed to improve fault tolerance and load balancing algorithm by improve connectivity, communication delay, network bandwidth, resource availability, and resource unpredictability. A novel two-dimension figure of merit is suggested to describe the network effects on load balance and fault tolerance estimation. Fault tolerance is enhanced by adaptively decrease replication time and message cost while load balance is enhanced by adaptively decrease mean job response time. Experimental results show that the proposed method yields superior performance over other methods.

Keywords: Grid computing, load balancing, fault tolerance, R-tree, heterogeneous systems

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Authors: Vijaya K. Srivastava, Davide Spinello

Abstract:

This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3ⁿ enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3ⁿ integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.

Keywords: constrained integer problems, enumerative search algorithm, Heuristic algorithm, Tunneling algorithm

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Authors: J. Pazourek, K. Šmejkal, P. Kollár, J. Rajchard, J. Šinko, Z. Balounová, E. Vlková, H. Salmonová

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Pectinatella magnifica (Leidy, 1851) is an invasive freshwater animal that lives in colonies. A colony of Pectinatella magnifica (a gelatinous blob) can be up to several feet in diameter large and under favorable conditions it exhibits an extreme growth rate. Recently European countries around rivers of Elbe, Oder, Danube, Rhine and Vltava have confirmed invasion of Pectinatella magnifica, including freshwater reservoirs in South Bohemia (Czech Republic). Our project (Czech Science Foundation, GAČR P503/12/0337) is focused onto biology and chemistry of Pectinatella magnifica. We monitor the organism occurrence in selected South Bohemia ponds and sandpits during the last years, collecting information about physical properties of surrounding water, and sampling the colonies for various analyses (classification, maps of secondary metabolites, toxicity tests). Because the gelatinous matrix is during the colony lifetime also a host for algae, bacteria and cyanobacteria (co-habitants), in this contribution, we also applied a high performance liquid chromatography (HPLC) method for determination of potentially present cyanobacterial toxins (microcystin-LR, microcystin-RR, nodularin). Results from the last 3-year monitoring show that these toxins are under limit of detection (LOD), so that they do not represent a danger yet. The final goal of our study is to assess toxicity risks related to fresh water resources invaded by Pectinatella magnifica, and to understand the process of invasion, which can enable to control it.

Keywords: cyanobacteria, fresh water resources, Pectinatella magnifica invasion, toxicity monitoring

Procedia PDF Downloads 219