Search results for: flexible optimization

Authors: M. Magrini, D. Moroni, G. Palazzese, G. Pieri, D. Azzarelli, A. Spada, L. Fanucci, O. Salvetti

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Railway crossings are complex entities whose optimal management cannot be addressed unless with the help of an intelligent transportation system integrating information both on train and vehicular flows. In this paper, we propose an integrated system named SIMPLE (Railway Safety and Infrastructure for Mobility applied at level crossings) that, while providing unparalleled safety in railway level crossings, collects data on rail and road traffic and provides value-added services to citizens and commuters. Such services include for example alerts, via variable message signs to drivers and suggestions for alternative routes, towards a more sustainable, eco-friendly and efficient urban mobility. To achieve these goals, SIMPLE is organized as a System of Systems (SoS), with a modular architecture whose components range from specially-designed radar sensors for obstacle detection to smart ETSI M2M-compliant camera networks for urban traffic monitoring. Computational unit for performing forecast according to adaptive models of train and vehicular traffic are also included. The proposed system has been tested and validated during an extensive trial held in the mid-sized Italian town of Montecatini, a paradigmatic case where the rail network is inextricably linked with the fabric of the city. Results of the tests are reported and discussed.

Keywords: Intelligent Transportation Systems (ITS), railway, railroad crossing, smart camera networks, radar obstacle detection, real-time traffic optimization, IoT, ETSI M2M, transport safety

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Authors: Zohreh Mohammadi, Jan Kaspar, Peter Lohmander, Robert Marusak, Harald Vacik, Ljusk Ola Eriksson

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Storms are important damaging agents in European forest ecosystems. In the latest decades, significant economic losses in European forestry occurred due to storms. This study investigates the problem of optimal harvest planning when forest stands risk to be felled by storms. One of the most applicable mathematical methods which are being used to optimize forest management is stochastic dynamic programming (SDP). This method belongs to the adaptive optimization class. Sequential decisions, such as harvest decisions, can be optimized based on sequential information about events that cannot be perfectly predicted, such as the future storms and the future states of wind protection from other forest stands. In this paper, stochastic dynamic programming is used to maximize the expected present value of the profits from an area consisting of several forest stands. The region of analysis is the Czech Republic. The harvest decisions, in a particular time period, should be simultaneously taken in all neighbor stands. The reason is that different stands protect each other from possible winds. The optimal harvest age of a particular stand is a function of wind speed and different wind protection effects. The optimal harvest age often decreases with wind speed, but it cannot be determined for one stand at a time. When we consider a particular stand, this stand also protects other stands. Furthermore, the particular stand is protected by neighbor stands. In some forest stands, it may even be rational to increase the harvest age under the influence of stronger winds, in order to protect more valuable stands in the neighborhood. It is important to integrate wind risk in forestry decision-making.

Keywords: Czech republic, forest stands, stochastic dynamic programming, wind risk

Procedia PDF Downloads 117

Authors: M. Kowalik, J. Masternak, K. Kazimierczuk, O. V. Khavryuchenko, B. Kupcewicz, B. Barszcz

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Recently, the growing interest of chemists in metal-organic coordination polymers (MOCPs) is primarily derived from their intriguing structures and potential applications in catalysis, gas storage, molecular sensing, ion exchanges, nonlinear optics, luminescence, etc. Currently, we are devoting considerable effort to finding the proper method of synthesizing new coordination polymers containing S- or N-heteroaromatic carboxylates as linkers and characterizing the obtained Pb(II) compounds according to their structural diversity, luminescence, and thermal properties. The choice of Pb(II) as the central ion of MOCPs was motivated by several reasons mentioned in the literature: i) a large ionic radius allowing for a wide range of coordination numbers, ii) the stereoactivity of the 6s2 lone electron pair leading to a hemidirected or holodirected geometry, iii) a flexible coordination environment, and iv) the possibility to form secondary bonds and unusual non-covalent interactions, such as classic hydrogen bonds and π···π stacking interactions, as well as nonconventional hydrogen bonds and rarely reported tetrel bonds, Pb(lone pair)···π interactions, C–H···Pb agostic-type interactions or hydrogen bonds, and chelate ring stacking interactions. Moreover, the construction of coordination polymers requires the selection of proper ligands acting as linkers, because we are looking for materials exhibiting different network topologies and fluorescence properties, which point to potential applications. The reaction of Pb(NO₃)₂ with 1H-pyrrole-2-carboxylic acid (2prCOOH) leads to the formation of a new four-nuclear Pb(II) polymer, [Pb4(2prCOO)₈(H₂O)]ₙ, which has been characterized by CHN, FT-IR, TG, PL and single-crystal X-ray diffraction methods. In view of the primary Pb–O bonds, Pb1 and Pb2 show hemidirected pentagonal pyramidal geometries, while Pb2 and Pb4 display hemidirected octahedral geometries. The topology of the strongest Pb–O bonds was determined as the (4·8²) fes topology. Taking the secondary Pb–O bonds into account, the coordination number of Pb centres increased, Pb1 exhibited a hemidirected monocapped pentagonal pyramidal geometry, Pb2 and Pb4 exhibited a holodirected tricapped trigonal prismatic geometry, and Pb3 exhibited a holodirected bicapped trigonal prismatic geometry. Moreover, the Pb(II) lone pair stereoactivity was confirmed by DFT calculations. The 2D structure was expanded into 3D by the existence of non-covalent O/C–H···π and Pb···π interactions, which was confirmed by the Hirshfeld surface analysis. The above mentioned interactions improve the rigidity of the structure and facilitate the charge and energy transfer between metal centres, making the polymer a promising luminescent compound.

Keywords: coordination polymers, fluorescence properties, lead(II), lone electron pair stereoactivity, non-covalent interactions

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Authors: Liaqat Ali, Ehsan, Muhammad Shahzad, Nasir Orakzai

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Introduction: Internal optical urethrotomy is the main stay treatment modality in management of urethral stricture. Being minimal invasive with less morbidity, it is commonly performed and favored procedure by urologists across the globe. Although short-term success rate of optical urethrotomy is promising but long-term efficacy of IOU is questionable with high recurrence rate in different studies. Numerous techniques had been adopted to reduce the recurrence after IOU like prolong catheterization and self-clean intermittent catheterization with varying success. Mitomycin C has anti-fibroblast and anti-collagen properties and has been used in trabeculectomy, myringotomy and after keloid scar excision in contemporary surgical practice. Present study according to the best of our knowledge is a pioneer pilot study in Pakistan to determine the efficacy of Mitomycin C in preventing recurrence of urethral stricture after internal optical urethrotomy. Objective: To determine the efficacy of Mitomycin C in reducing the recurrence of anterior urethral stricture after internal optical urethrotomy. Methods: It is a randomized control trial conducted in department of urology, Institute of Kidney Diseases Hayatabad Medical Complex Peshawar from March 2011 till December 2013. After approval of hospital ethical committee, we included maximum of 2 cm anterior urethral stricture irrespective of etiology. Total of 140 patients were equally divided into two groups by lottery method. Group A (Case) comprising of 70 patients in whom Mitomycin C 0.1% was injected sub mucosal in stricture area at 1,11,6 and 12 O clock position using straight working channel paediatric cystoscope after conventional optical urethrotomy. Group B (Control) 70 patients in whom only optical urethrotomy was performed. SCIC was not offered in both the groups. All the patients were regularly followed on a monthly basis for 3 months then three monthly for remaining 9 months. Recurrence was diagnosed by using diagnostic tools of retrograde urethrogram and flexible urethroscopy in selected cased. Data was collected on structured Proforma and was analyzed on SPSS. Result: The mean age in Group A was 33 ±1.5 years and Group B was 35 years. External trauma was leading cause of urethral stricture in both groups 46 (65%) Group A and 50 (71.4%) Group B. In Group A. Iatrogenic urethral trauma was 2nd etiological factor in both groups. 18(25%) Group A while 15( 21.4%) in Group B. At the end of 1 year, At the end of one year, recurrence of urethral stricture was recorded in 11 (15.71%) patient in Mitomycin C Group A and it was recorded in 27 (38.5 %) patients in group B. Significant difference p=0.001 was found in favour of group A Mitomycin group. Conclusion: Recurrence of urethral stricture is high after optical urethrotomy. Mitomycin C is found highly effective in preventing recurrence of urethral stricture after IOU.

Keywords: urethral stricture, mitomycine, internal optical urethrotomy, medical and health sciences

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Authors: Suleiman Hassan Otuoze, Dexter Vernon Lloyd Hunt, Ian Jefferson

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Urbanization has continued to widen the gap between demand and resources available to provide resilient and sustainable transport services in many fast-growing developing countries' cities. Transport demand management is a decision-based optimization concept for both benchmarking and ensuring efficient use of transport resources. This study assesses the service quality of infrastructure and mobility services in the Nigerian cities of Kano and Lagos through five dimensions of quality (i.e., Tangibility, Reliability, Responsibility, Safety Assurance and Empathy). The methodology adopts a hybrid AHP-SERVQUAL model applied on questionnaire surveys to gauge the quality of satisfaction and the views of experts in the field. The AHP results prioritize tangibility, which defines the state of transportation infrastructure and services in terms of satisfaction qualities and intervention decision weights in the two cities. The results recorded ‘unsatisfactory’ indices of quality of performance and satisfaction rating values of 48% and 49% for Kano and Lagos, respectively. The satisfaction indices are identified as indicators of low performances of transportation demand management (TDM) measures and the necessity to re-order priorities and take proactive steps towards infrastructure. The findings pilot a framework for comparative assessment of recognizable standards in transport services, best ethics of management and a necessity of quality infrastructure to guarantee both resilient and sustainable urban mobility.

Keywords: transportation demand management, multi-criteria decision support, transport infrastructure, service quality, sustainable transport

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Authors: Ahmed Banda, Alaa Maghrabi, Aiman Fakieh

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Terahertz (THz) range lies in the area between 0.1 to 10 THz. The process of generating and detecting THz can be done through different techniques. One of the most familiar techniques is done through a photoconductive antenna (PCA). The process of generating THz radiation at PCA includes applying a laser pump in femtosecond and DC voltage difference. However, photocurrent is generated at PCA, which its value is affected by different parameters (e.g., dielectric properties, DC voltage difference and incident power of laser pump). THz radiation is used for biomedical applications. However, different biomedical fields need new technologies to meet patients’ needs (e.g. blood-related conditions). In this work, a novel method to check the red blood cells (RBCs) concentration of a blood sample using PCA is presented. RBCs constitute 44% of total blood volume. RBCs contain Hemoglobin that transfers oxygen from lungs to body organs. Then it returns to the lungs carrying carbon dioxide, which the body then gets rid of in the process of exhalation. The configuration has been simulated and optimized using COMSOL Multiphysics. The differentiation of RBCs concentration affects its dielectric properties (e.g., the relative permittivity of RBCs in the blood sample). However, the effects of four blood samples (with different concentrations of RBCs) on photocurrent value have been tested. Photocurrent peak value and RBCs concentration are inversely proportional to each other due to the change of dielectric properties of RBCs. It was noticed that photocurrent peak value has dropped from 162.99 nA to 108.66 nA when RBCs concentration has risen from 0% to 100% of a blood sample. The optimization of this method helps to launch new products for diagnosing blood-related conditions (e.g., anemia and leukemia). The resultant electric field from DC components can not be used to count the RBCs of the blood sample.

Keywords: biomedical applications, photoconductive antenna, photocurrent, red blood cells, THz radiation

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Authors: R. Sharma, S. Kumar, C. Sharma

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A number of toxic chlorophenolic compounds are formed during pulp bleaching. The nature and concentration of these chlorophenolic compounds largely depends upon the amount and nature of bleaching chemicals used. These compounds are highly recalcitrant and difficult to remove but are partially removed by the biochemical treatment processes adopted by the paper industry. Identification and estimation of these chlorophenolic compounds has been carried out in the primary and secondary clarified effluents from the paper mill by GCMS. Twenty-six chorophenolic compounds have been identified and estimated in paper mill waste waters. Electrochemical treatment is an efficient method for oxidation of pollutants and has successfully been used to treat textile and oil waste water. Electrochemical treatment using less expensive anode material, stainless steel electrodes has been tried to study their removal. The electrochemical assembly comprised a DC power supply, a magnetic stirrer and stainless steel (316 L) electrode. The optimization of operating conditions has been carried out and treatment has been performed under optimized treatment conditions. Results indicate that 68.7% and 83.8% of cholorphenolic compounds are removed during 2 h of electrochemical treatment from primary and secondary clarified effluent respectively. Further, there is a reduction of 65.1, 60 and 92.6% of COD, AOX and color, respectively for primary clarified and 83.8%, 75.9% and 96.8% of COD, AOX and color, respectively for secondary clarified effluent. EC treatment has also been found to increase significantly the biodegradability index of wastewater because of conversion of non- biodegradable fraction into biodegradable fraction. Thus, electrochemical treatment is an efficient method for the degradation of cholorophenolic compounds, removal of color, AOX and other recalcitrant organic matter present in paper mill waste water.

Keywords: chlorophenolics, effluent, electrochemical treatment, wastewater

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Authors: Kanchan Negi

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Background: Modern and urban occupational culture have driven demands for people to work long hours and weekends and take work to home at times. Research on the health effects of these exhaustive temporal work patterns is scant or contradictory. This study examines the relationship between work patterns and wellbeing in a sample of women living in the metropolitan hub of Delhi. Method: This study is based on the data collected from 360 currently married women between age 29 and 49 years, working in the urban capital hub of India, i.e., Delhi. The women interviewed were professionals from the education, health, banking and information and technology (IT) sector. Bivariate analysis was done to study the characteristics of the sample. Logistic regression analysis was used to estimate the physical and psychological wellbeing across occupational characteristics. Results: Most of the working women were below age 35 years; around 30% of women worked in the education sector, 23% in health, 21% in banking and 26% in the IT sector. Over 55% of women were employed in the private sector and only 36% were permanent employees. Nearly 30% of women worked for more than the standard 8 hours a day. The findings from logistic regression showed that compared to women working in the education sector, those who worked in the banking and IT sector more likely to have physical and psychological health issues (OR 2.07-4.37, CI 1.17-4.37); women who bear dual burden of responsibilities had higher odds of physical and psychological health issues than women who did not (OR 1.19-1.85 CI 0.96-2.92). Women who worked for more than 8 hours a day (OR 1.15, CI 1.01-1.30) and those who worked for more than five days a week (OR 1.25, CI 1.05-1.35) were more likely to have physical health issues than women who worked for 6-8 hours a day and five days e week, respectively. Also, not having flexible work timings and compensatory holidays increased the odds of having physical and psychological health issues among working women (OR 1.17-1.29, CI 1.01-1.47). Women who worked in the private sector, those employed temporarily and who worked in the non-conducive environments were more likely to have psychological health issues as compared to women in the public sector, permanent employees and those who worked in a conducive environment, respectively (OR 1.33-1.67, CI 1.09-2.91). Women who did not have poor work-life balance had reduced the odds of psychological health issues than women with poor work-life balance (OR 0.46, CI 0.25-0.84). Conclusion: Poor wellbeing significantly linked to strenuous and rigid work patterns, suggesting that modern and urban work culture may contribute to the poor wellbeing of working women. Noticing the recent decline in female workforce participation in Delhi, schemes like Flexi-timings, compensatory holidays, work-from-home and daycare facilities for young ones must be welcomed; these policies already exist in some private sector firms, and the public sectors companies should also adopt such changes to ease the dual burden as homemaker and career maker. This could encourage women in the urban areas to readily take up the jobs with less juggle to manage home and work.

Keywords: occupational characteristics, urban India, well-being, working women

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Authors: Daud Mustafa Minhas, Raja Rehan Khalid, Georg Frey

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The next generation power systems are equipped with abundantly available free renewable energy resources (RES). During their low-cost operations, the price of electricity significantly reduces to a lower value, and sometimes it becomes negative. Therefore, it is recommended not to operate the traditional power plants (e.g. coal power plants) and to reduce the losses. In fact, it is not a cost-effective solution, because these power plants exhibit some shutdown and startup costs. Moreover, they require certain time for shutdown and also need enough pause before starting up again, increasing inefficiency in the whole power network. Hence, there is always a trade-off between avoiding negative electricity prices, and the startup costs of power plants. To exploit this trade-off and to increase the profit of a power plant, two main contributions are made: 1) introducing retrofit technology for state of art coal power plant; 2) proposing optimal control strategy for a power plant by exploiting different flexibility features. These flexibility features include: improving ramp rate of power plant, reducing startup time and lowering minimum load. While, the control strategy is solved as mixed integer linear programming (MILP), ensuring optimal solution for the profit maximization problem. Extensive comparisons are made considering pre and post-retrofit coal power plant having the same efficiencies under different electricity price scenarios. It concludes that if the power plant must remain in the market (providing services), more flexibility reflects direct economic advantage to the plant operator.

Keywords: discrete optimization, power plant flexibility, profit maximization, unit commitment model

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Authors: Margarita S. Tikhonova, Alireza Baniasad, Anton G. Kalmykov, Georgy A. Kalmykov, Ralf Littke

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There is a high complexity in the pore structure of organic-rich rocks caused by the combination of inter-particle porosity from inorganic mineral matter and ultrafine intra-particle porosity from both organic matter and clay minerals. Fluids are retained in that pore space, but there are major uncertainties in how and where the fluids are stored and to what extent they are accessible or trapped in 'closed' pores. A large degree of tortuosity may lead to fractionation of organic matter so that the lighter and flexible compounds would diffuse to the reservoir whereas more complicated compounds may be locked in place. Additionally, parts of hydrocarbons could be bound to solid organic matter –kerogen– and mineral matrix during expulsion and migration. Larger compounds can occupy thin channels so that clogging or oil and gas entrapment will occur. Sequential extraction of applying different solvents is a powerful tool to provide more information about the characteristics of trapped organic matter distribution. The Upper Jurassic – Lower Cretaceous Bazhenov shale is one of the most petroliferous source rock extended in West Siberia, Russia. Concerning the variable mineral composition, pore space distribution and thermal maturation, there are high uncertainties in distribution and composition of organic matter in this formation. In order to address this issue geological and geochemical properties of 30 samples including mineral composition (XRD and XRF), structure and texture (thin-section microscopy), organic matter contents, type and thermal maturity (Rock-Eval) as well as molecular composition (GC-FID and GC-MS) of different extracted materials during sequential extraction were considered. Sequential extraction was performed by a Soxhlet apparatus using different solvents, i.e., n-hexane, chloroform and ethanol-benzene (1:1 v:v) first on core plugs and later on pulverized materials. The results indicate that the studied samples are mainly composed of type II kerogen with TOC contents varied from 5 to 25%. The thermal maturity ranged from immature to late oil window. Whereas clay contents decreased with increasing maturity, the amount of silica increased in the studied samples. According to molecular geochemistry, stored hydrocarbons in open and closed pore space reveal different geochemical fingerprints. The results improve our understanding of hydrocarbon expulsion and migration in the organic-rich Bazhenov shale and therefore better estimation of hydrocarbon potential for this formation.

Keywords: Bazhenov formation, bitumen, molecular geochemistry, sequential extraction

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Authors: J. B. Frisch, D. Evandiloff, P. Martin, N. Ouizille, F. Pires

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Smart Beta strategies intend to be an asset management revolution with reference to classical cap-weighted indices. Indeed, these strategies allow a better control on portfolios risk factors and an optimized asset allocation by taking into account specific risks or wishes to generate alpha by outperforming indices called 'Beta'. Among many strategies independently used, this paper focuses on four of them: Minimum Variance Portfolio, Equal Risk Contribution Portfolio, Maximum Diversification Portfolio, and Equal-Weighted Portfolio. Their efficiency has been proven under constraints like momentum or market phenomenon, suggesting a reconsideration of cap-weighting.
 To further increase strategy return efficiency, it is proposed here to compare their strengths and weaknesses inside time intervals corresponding to specific identifiable market phases, in order to define adapted strategies depending on pre-specified situations. 
Results are presented as performance curves from different combinations compared to a benchmark. If a combination outperforms the applicable benchmark in well-defined actual market conditions, it will be preferred. It is mainly shown that such investment 'rules', based on both historical data and evolution of Smart Beta strategies, and implemented according to available specific market data, are providing very interesting optimal results with higher return performance and lower risk.
 Such combinations have not been fully exploited yet and justify present approach aimed at identifying relevant elements characterizing them.

Keywords: smart beta, minimum variance portfolio, equal risk contribution portfolio, maximum diversification portfolio, equal weighted portfolio, combinations

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Authors: Yanping Liao, Congcong He, Ruigang Zhao

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The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: constraint parameters, derivative matrix, magnetocardiography, regular term, total variation

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Authors: Youssef Mazloum, Haytham Sayah, Maroun Nemer

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The penetration of renewable energy sources into the electric grid is significantly increasing. However, the intermittence of these sources breaks the balance between supply and demand for electricity. Hence, the importance of the energy storage technologies, they permit restoring the balance and reducing the drawbacks of intermittence of the renewable energies. This paper discusses the modeling and the cost-effectiveness of an isobaric adiabatic compressed air energy storage (IA-CAES) system. The proposed system is a combination among a compressed air energy storage (CAES) system with pumped hydro storage system and thermal energy storage system. The aim of this combination is to overcome the disadvantages of the conventional CAES system such as the losses due to the storage pressure variation, the loss of the compression heat and the use of fossil fuel sources. A steady state model is developed to perform an energy and exergy analyses of the IA-CAES system and calculate the distribution of the exergy losses in the latter system. A sensitivity analysis is also carried out to estimate the effects of some key parameters on the system’s efficiency, such as the pinch of the heat exchangers, the isentropic efficiency of the rotating machinery and the pressure losses. The conducted sensitivity analysis is a local analysis since the sensibility of each parameter changes with the variation of the other parameters. Therefore, an exergoeconomic study is achieved as well as a cost optimization in order to reduce the electricity cost produced during the production phase. The optimizer used is OmOptim which is a genetic algorithms based optimizer.

Keywords: cost-effectiveness, Exergoeconomic analysis, isobaric adiabatic compressed air energy storage (IA-CAES) system, thermodynamic modeling

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Authors: Zoran Herceg, Višnja Stulić, Anet Režek Jambrak, Tomislava Vukušić

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Electrical discharge plasma is a new non-thermal processing technique which is used for the inactivation of contaminating and hazardous microbes in liquids. Plasma is a source of different antimicrobial species including UV photons, charged particles, and reactive species such as superoxide, hydroxyl radicals, nitric oxide and ozone. Escherichia coli was studied as foodborne pathogen. The aim of this work was to examine inactivation effects of electrical discharge plasma treatment on the Escherichia coli MG 1655 in pure culture. Two types of plasma configuration and polarity were used. First configuration was with titanium wire as high voltage needle and another with medical stainless steel needle used to form bubbles in treated volume and titanium wire as high voltage needle. Model solution samples were inoculated with Escerichia coli MG 1655 and treated by electrical discharge plasma at treatment time of 5 and 10 min, and frequency of 60, 90 and 120 Hz. With the first configuration after 5 minutes of treatment at frequency of 120 Hz the inactivation rate was 1.3 log₁₀ reduction and after 10 minutes of treatment the inactivation rate was 3.0 log₁₀ reduction. At the frequency of 90 Hz after 10 minutes inactivation rate was 1.3 log₁₀ reduction. With the second configuration after 5 minutes of treatment at frequency of 120 Hz the inactivation rate was 1.2 log₁₀ reduction and after 10 minutes of treatment the inactivation rate was also 3.0 log₁₀ reduction. In this work it was also examined the formation of biofilm, nucleotide and protein leakage at 260/280 nm, before and after treatment and recuperation of treated samples. Further optimization of method is needed to understand mechanism of inactivation.

Keywords: electrical discharge plasma, escherichia coli MG 1655, inactivation, point-to-plate electrode configuration

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Authors: Kulvinder Bajwa, Narsi R. Bishnoi

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Finding a sustainable alternative for today’s petrochemical industry is a major challenge facing by researchers, scientists, chemical engineers, and society at the global level. Microorganisms are considered to be sustainable feedstock for 3rd generation biofuel production. In this study, we have investigated the potential of a native bacterial strain isolated from a petrol contaminated site for the production of biodiesel. The bacterium was identified to be Rhodococcus opacus by biochemical test and 16S rRNA. Compositional analysis of bacterial biomass has been carried out by Fourier transform infrared spectroscopy (FTIR) in order to confirm lipid profile. Lipid and biomass were optimized by combination with Box Behnken design (BBD) of response surface methodology. The factors selected for the optimization of growth condition were glucose, yeast extract, and ammonium nitrate concentration. The experimental model developed through RSM in terms of effective operational factors (BBD) was found to be suitable to describe the lipid and biomass production, which indicated higher lipid and biomass with a minimum concentration of ammonium nitrate, yeast extract, and quite higher dose of glucose supplementation. Optimum results of the experiments were found to be 2.88 gL⁻¹ biomass and lipid content 38.75% at glucose 20 gL⁻¹, ammonium nitrate 0.5 gL⁻¹ and yeast extract 1.25 gL⁻¹. Furthermore, GCMS study revealed that Rhodococcus opacus has favorable fatty acid profile for biodiesel production.

Keywords: biofuel, Oleaginious bacteria, Rhodococcus opacus, FTIR, BBD, free fatty acids

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Authors: R. Khenata, T. Djied, R. Ahmed, H. Baltache, S. Bin-Omran, A. Bouhemadou

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We predict structural, phase transition as well as opto-electronic properties of the filled-tetrahedral (Nowotny-Juza) NaZnAs compound in this study. Calculations are carried out by employing the full potential (FP) linearized augmented plane wave (LAPW) plus local orbitals (lo) scheme developed within the structure of density functional theory (DFT). Exchange-correlation energy/potential (EXC/VXC) functional is treated using Perdew-Burke and Ernzerhof (PBE) parameterization for generalized gradient approximation (GGA). In addition to Trans-Blaha (TB) modified Becke-Johnson (mBJ) potential is incorporated to get better precision for optoelectronic properties. Geometry optimization is carried out to obtain the reliable results of the total energy as well as other structural parameters for each phase of NaZnAs compound. Order of the structural transitions as a function of pressure is found as: Cu2Sb type → β → α phase in our study. Our calculated electronic energy band structures for all structural phases at the level of PBE-GGA as well as mBJ potential point out; NaZnAs compound is a direct (Γ–Γ) band gap semiconductor material. However, as compared to PBE-GGA, mBJ potential approximation reproduces higher values of fundamental band gap. Regarding the optical properties, calculations of real and imaginary parts of the dielectric function, refractive index, reflectivity coefficient, absorption coefficient and energy loss-function spectra are performed over a photon energy ranging from 0.0 to 30.0 eV by polarizing incident radiation in parallel to both [100] and [001] crystalline directions.

Keywords: NaZnAs, FP-LAPW+lo, structural properties, phase transition, electronic band-structure, optical properties

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Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

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Authors: Bokkasam Sasidhar, Ibrahim Aljasser

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The problem of finding optimal schedules for each equipment in a production process is considered, which consists of a single stage of manufacturing and which can handle different types of products, where changeover for handling one type of product to the other type incurs certain costs. The machine capacity is determined by the upper limit for the quantity that can be processed for each of the products in a set up. The changeover costs increase with the number of set ups and hence to minimize the costs associated with the product changeover, the planning should be such that similar types of products should be processed successively so that the total number of changeovers and in turn the associated set up costs are minimized. The problem of cost minimization is equivalent to the problem of minimizing the number of set ups or equivalently maximizing the capacity utilization in between every set up or maximizing the total capacity utilization. Further, the production is usually planned against customers’ orders, and generally different customers’ orders are assigned one of the two priorities – “normal” or “priority” order. The problem of production planning in such a situation can be formulated into a Multiple Arc Network (MAN) model and can be solved sequentially using the algorithm for maximizing flow along a MAN and the algorithm for maximizing flow along a MAN with priority arcs. The model aims to provide optimal production schedule with an objective of maximizing capacity utilization, so that the customer-wise delivery schedules are fulfilled, keeping in view the customer priorities. Algorithms have been presented for solving the MAN formulation of the production planning with customer priorities. The application of the model is demonstrated through numerical examples.

Keywords: scheduling, maximal flow problem, multiple arc network model, optimization

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Authors: Xiaocong Liu, Huazhen Wang, Ting He, Xiaozheng Li, Weihan Zhang, Jian Chen

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The utilization of electronic medical record (EMR) data to establish the disease diagnosis model has become an important research content of biomedical informatics. Deep learning can automatically extract features from the massive data, which brings about breakthroughs in the study of EMR data. The challenge is that deep learning lacks semantic knowledge, which leads to impracticability in medical science. This research proposes a method of incorporating lexical-semantic knowledge from abundant entities into a convolutional neural network (CNN) framework for pediatric disease diagnosis. Firstly, medical terms are vectorized into Lexical Semantic Vectors (LSV), which are concatenated with the embedded word vectors of word2vec to enrich the feature representation. Secondly, the semantic distribution of medical terms serves as Semantic Decision Guide (SDG) for the optimization of deep learning models. The study evaluate the performance of LSV-SDG-CNN model on four kinds of Chinese EMR datasets. Additionally, CNN, LSV-CNN, and SDG-CNN are designed as baseline models for comparison. The experimental results show that LSV-SDG-CNN model outperforms baseline models on four kinds of Chinese EMR datasets. The best configuration of the model yielded an F1 score of 86.20%. The results clearly demonstrate that CNN has been effectively guided and optimized by lexical-semantic knowledge, and LSV-SDG-CNN model improves the disease classification accuracy with a clear margin.

Keywords: convolutional neural network, electronic medical record, feature representation, lexical semantics, semantic decision

Procedia PDF Downloads 111

Authors: Walid Tawfik

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The interaction of high intensity ultrashort laser pulses with plasma generates many significant applications, including soft x-ray lasers, time-resolved laser induced plasma spectroscopy LIPS, and laser-driven accelerators. The development in producing of femtosecond down to ten femtosecond optical pulses has facilitates scientists with a vital tool in a variety of ultrashort phenomena, such as high field physics, femtochemistry and high harmonic generation HHG. In this research, we generate a two-octave-wide ultrashort supercontinuum pulses with an optical spectrum extending from 3.5 eV (ultraviolet) to 1.3 eV (near-infrared) using a capillary fiber filled with neon gas. These pulses are formed according to nonlinear self-phase modulation in the neon gas as a nonlinear medium. The investigations of the created pulses were made using spectral phase interferometry for direct electric-field reconstruction (SPIDER). A complete description of the output pulses was considered. The observed characterization of the produced pulses includes the beam profile, the pulse width, and the spectral bandwidth. After reaching optimization conditions, the intensity of the reconstructed pulse autocorrelation function was applied for the shorts pulse duration to achieve transform limited ultrashort pulses with durations below 6-fs energies up to 600μJ. Moreover, the effect of neon pressure variation on the pulse width was examined. The nonlinear self-phase modulation realized to be increased with the pressure of the neon gas. The observed results may lead to an advanced method to control and monitor ultrashort transit interaction in femtochemistry.

Keywords: supercontinuum, ultrafast, SPIDER, ultra-broadband

Procedia PDF Downloads 201

Authors: Pia Wetzl

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The learning process of students can be optimized by combining online teaching with face-to-face sessions. So-called blended learning offers extensive flexibility as well as contact opportunities with fellow students and teachers. Furthermore, learning can be individualized and self-regulated. The aim of this article is to investigate which factors are necessary for blended learning to be successful. Semi-structured interviews were conducted with students (N = 60) and lecturers (N = 21) from different disciplines at two German universities. The questions focused on the perception of online, face-to-face and blended learning courses. In addition, questions focused on possible optimization potential and obstacles to practical implementation. The results show that on-site presence is very important for blended learning to be successful. If students do not get to know each other on-site, there is a risk of loneliness during the self-learning phases. This has a negative impact on motivation. From the perspective of the lecturers, the willingness of the students to participate in the sessions on-site is low. Especially when there is no obligation to attend, group work is difficult to implement because the number of students attending is too low. Lecturers would like to see more opportunities from the university and its administration to enforce attendance. In their view, this is the only way to ensure the success of blended learning. In addition, they see the conception of blended learning courses as requiring a great deal of time, which they are not always willing to invest. More incentives are necessary to keep the lecturers motivated to develop engaging teaching material. The study identifies factors that can help teachers conceptualize blended learning. It also provides specific implementation advice and identifies potential impacts. This catalogue has great value for the future-oriented development of courses at universities. Future studies could test its practical use.

Keywords: blended learning, higher education, teachers, student learning, qualitative research

Procedia PDF Downloads 46

Authors: Wageeh A. Nafei

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This paper explores the role of Paradoxical Leadership (PL) in enhancing Organizational Success (OS) at private hospitals in Egypt. Based on the collected data from employees in private hospitals (doctors, nursing staff, and administrative staff). The researcher has adopted a sampling method to collect data for the study. The appropriate statistical methods, such as Alpha Correlation Coefficient (ACC), Confirmatory Factor Analysis (CFA), and Multiple Regression Analysis (MRA), are used to analyze the data and test the hypotheses. The research has reached a number of results, the most important of which are (1) there is a statistical relationship between the independent variable represented by PL and the dependent variable represented by Organizational Success (OS). The paradoxical leader encourages employees to express their opinions and builds a work environment characterized by flexibility and independence. Also, the paradoxical leader works to support specialized work teams, which leads to the creation of new ideas, on the one hand, and contributes to the achievement of outstanding performance on the other hand. (2) the mentality of the paradoxical leader is flexible and capable of absorbing all suggestions from all employees. Also, the paradoxical leader is interested in enhancing cooperation among them and provides an opportunity to transfer experience and increase knowledge-sharing. Also, the sharing of knowledge creates the necessary diversity that helps the organization to obtain rich external information and enables the organization to deal with a rapidly changing environment. (3) The PL approach helps in facing the paradoxical demands of employees. A paradoxical leader plays an important role in reducing the feeling of instability in the work environment and lack of job security, reducing negative feelings for employees, restoring balance in the work environment, improving the well-being of employees, and increasing the degree of job satisfaction of employees in the organization. The study referred to a number of recommendations, the most important of which are (1) the leaders of the organizations must listen to the views of employees and their needs and move away from the official method of control. The leader should give sufficient freedom to employees to participate in decision-making and maintain enough space among them. The treatment between the leaders and employees must be based on friendliness, (2) the need for organizational leaders to pay attention to sharing knowledge among employees through training courses. The leader should make sure that every information provided by the employee is valuable and useful, which can be used to solve a problem that may face his/her colleagues at work, (3) the need for organizational leaders to pay attention to sharing knowledge among employees through brainstorming sessions. The leader should ensure that employees obtain knowledge from their colleagues and share ideas and information among them. This is in addition to motivating employees to complete their work in a new creative way, which leads to employees’ not feeling bored of repeating the same routine procedures in the organization.

Keywords: paradoxical leadership, organizational success, human resourece, management

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Authors: Luis Guiliana, Andrea Osorio

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The lack of comprehension of the reservoir geomechanics conditions may cause operational problems that cost to the industry billions of dollars per year. The drilling operations at the Ceuta Field, Area 2 South, Maracaibo Lake, have been very expensive due to problems associated with drilling. The principal objective of this investigation is to develop a 3D geomechanical model in this area, in order to optimize the future drillings in the field. For this purpose, a 1D geomechanical model was built at first instance, following the workflow of the MEM (Mechanical Earth Model), this consists of the following steps: 1) Data auditing, 2) Analysis of drilling events and structural model, 3) Mechanical stratigraphy, 4) Overburden stress, 5) Pore pressure, 6) Rock mechanical properties, 7) Horizontal stresses, 8) Direction of the horizontal stresses, 9) Wellbore stability. The 3D MEM was developed through the geostatistic model of the Eocene C-SUP VLG-3676 reservoir and the 1D MEM. With this data the geomechanical grid was embedded. The analysis of the results threw, that the problems occurred in the wells that were examined were mainly due to wellbore stability issues. It was determined that the stress field change as the stratigraphic column deepens, it is normal to strike-slip at the Middle Miocene and Lower Miocene, and strike-slipe to reverse at the Eocene. In agreement to this, at the level of the Eocene, the most advantageous direction to drill is parallel to the maximum horizontal stress (157º). The 3D MEM allowed having a tridimensional visualization of the rock mechanical properties, stresses and operational windows (mud weight and pressures) variations. This will facilitate the optimization of the future drillings in the area, including those zones without any geomechanics information.

Keywords: geomechanics, MEM, drilling, stress

Procedia PDF Downloads 251

Authors: Andrew Fox, Qingping Yang, Yuanhong Zhao, Tao Zhang

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Furniture is a very significant subdivision of architecture and its inherent interior design activities. The furniture industry has developed from an artisan-driven craft industry, whose forerunners saw themselves manifested in their crafts and treasured a sense of pride in the creativity of their designs, these days largely reduced to an anonymous collective mass-produced output. Although a very conservative industry, there is great potential for the implementation of collaborative digital technologies allowing a reconfigured artisan experience to be reawakened in a new and exciting form. The furniture manufacturing industry, in general, has been slow to adopt new methodologies for a design using artificial and rule-based generative design. This tardiness has meant the loss of potential to enhance its capabilities in producing sustainable, flexible, and mass customizable ‘right first-time’ designs. This paper aims to demonstrate the concept methodology for the creation of alternative and inspiring aesthetic structures for robot-based additive manufacturing (RBAM). These technologies can enable the economic creation of previously unachievable structures, which traditionally would not have been commercially economic to manufacture. The integration of these technologies with the computing power of generative design provides the tools for practitioners to create concepts which are well beyond the insight of even the most accomplished traditional design teams. This paper aims to address the problem by introducing generative design methodologies employing the Autodesk Fusion 360 platform. Examination of the alternative methods for its use has the potential to significantly reduce the estimated 80% contribution to environmental impact at the initial design phase. Though predominantly a design methodology, generative design combined with RBAM has the potential to leverage many lean manufacturing and quality assurance benefits, enhancing the efficiency and agility of modern furniture manufacturing. Through a case study examination of a furniture artifact, the results will be compared to a traditionally designed and manufactured product employing the Ecochain Mobius product life cycle analysis (LCA) platform. This will highlight the benefits of both generative design and robot-based additive manufacturing from an environmental impact and manufacturing efficiency standpoint. These step changes in design methodology and environmental assessment have the potential to revolutionise the design to manufacturing workflow, giving momentum to the concept of conceiving a pre-industrial model of manufacturing, with the global demand for a circular economy and bespoke sustainable design at its heart.

Keywords: robot, manufacturing, generative design, sustainability, circular econonmy, product life cycle assessment, furniture

Procedia PDF Downloads 112

Authors: Devendra Sillu, Shekhar Agnihotri

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The 'nano-biocatalyst' utilizes an ordered assembling of enzyme on to nanomaterial carriers to catalyze desirable biochemical kinetics and substrate selectivity. The current study describes an inter-disciplinary approach for converting agriculture waste, sugarcane bagasse into D-glucose exploiting halloysite nanotubes (HNTs) decorated cellulase enzyme as nano-biocatalytic system. Cellulase was successfully immobilized on HNTs employing polydopamine as an eco-friendly crosslinker while iron oxide nanoparticles were attached to facilitate magnetic recovery of material. The characterization studies (UV-Vis, TEM, SEM, and XRD) displayed the characteristic features of both cellulase and magnetic HNTs in the resulting nanocomposite. Various factors (i.e., working pH, temp., crosslinker conc., enzyme conc.) which may influence the activity of biocatalytic system were investigated. The experimental design was performed using Response Surface Methodology (RSM) for process optimization. Analyses data demonstrated that the nanobiocatalysts retained 80.30% activity even at elevated temperature (55°C) and excellent storage stabilities after 10 days. The repeated usage of system revealed a remarkable consistent relative activity over several cycles. The immobilized cellulase was employed to decompose agro-waste and the maximum decomposition rate of 67.2 % was achieved. Conclusively, magnetic HNTs can serve as a potential support for enzyme immobilization with long term usage, good efficacy, reusability and easy recovery from solution.

Keywords: halloysite nanotubes, enzyme immobilization, cellulase, response surface methodology, magnetic recovery

Procedia PDF Downloads 106

Authors: Filip Buruiana, Alexander Hall, Reimar Hofmann, Thomas Hofmann, Silviu Ganceanu, Alexandru Tudorica

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In-memory column-stores make interactive analysis feasible for many big data scenarios. PowerDrill is a system used internally at Google for exploration in logs data. Even though it is a highly parallelized column-store and uses in memory caching, interactive response times cannot be achieved for all datasets (note that it is common to analyze data with 50 billion records in PowerDrill). In this paper, we investigate two orthogonal approaches to optimize performance at the expense of an acceptable loss of accuracy. Both approaches can be implemented as outer wrappers around existing database engines and so they should be easily applicable to other systems. For the first optimization we show that memory is the limiting factor in executing queries at speed and therefore explore possibilities to improve memory efficiency. We adapt some of the theory behind data sketches to reduce the size of particularly expensive fields in our largest tables by a factor of 4.5 when compared to a standard compression algorithm. This saves 37% of the overall memory in PowerDrill and introduces a 0.4% relative error in the 90th percentile for results of queries with the expensive fields. We additionally evaluate the effects of using sampling on accuracy and propose a simple heuristic for annotating individual result-values as accurate (or not). Based on measurements of user behavior in our real production system, we show that these estimates are essential for interpreting intermediate results before final results are available. For a large set of queries this effectively brings down the 95th latency percentile from 30 to 4 seconds.

Keywords: big data, in-memory column-store, high-performance SQL queries, approximate SQL queries

Procedia PDF Downloads 234

Authors: Anil Bhandari, Imran Khan Pathan, Peeyush K. Sharma, Rakesh K. Patel, Suresh Purohit

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The purpose of this study was to prepare time and pH dependent release tablets of Ayurvedic Churna formulation and evaluate their advantages as colon targeted drug delivery system. The Vidangadi Churna was selected for this study which contains Embelin and Gallic acid. Embelin is used in Helminthiasis as therapeutic agent. Embelin is insoluble in water and unstable in gastric environment so it was formulated in time and pH dependent tablets coated with combination of two polymers Eudragit L100 and ethyl cellulose. The 150mg of core tablet of dried extract and lactose were prepared by wet granulation method. The compression coating was used in the polymer concentration of 150mg for both the layer as upper and lower coating tablet was investigated. The results showed that no release was found in 0.1 N HCl and pH 6.8 phosphate buffers for initial 5 hours and about 98.97% of the drug was released in pH 7.4 phosphate buffer in total 17 hours. The in vitro release profiles of drug from the formulation could be best expressed first order kinetics as highest linearity (r2= 0.9943). The results of the present study have demonstrated that the time and pH dependent tablets system is a promising vehicle for preventing rapid hydrolysis in gastric environment and improving oral bioavailability of Embelin and Gallic acid for treatment of Helminthiasis.

Keywords: embelin, gallic acid, Vidangadi Churna, colon targeted drug delivery

Procedia PDF Downloads 335

Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and time-consuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil, geotechnical engineering

Procedia PDF Downloads 316

Authors: Manjitsingh Rajput

Abstract:

Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

Procedia PDF Downloads 58

Authors: R. Kenova, K. Anguelov, R. Nikolova

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The human factor plays a major role in boosting the competitive capacity of logistic enterprises. This is of particular importance when it comes to logistic companies. On the one hand they should be strictly compliant with legislation; on the other hand, they should be competitive in terms of pricing and of delivery timelines. Moreover, their policies should allow them to be as flexible as possible. All these circumstances are reason for very serious challenges for the qualification, motivation and experience of the human resources, working in logistic companies or in logistic departments of trade and industrial enterprises. The geographic place of Bulgaria puts it in position of a country with some specific competitive advantages in the goods transport from Europe to Asia and back. Along with it, there is a number of logistic companies, that operate in this sphere in Bulgaria. In the current paper, the authors aim to establish the condition of the administrative capacity and human resources in the logistic companies and logistic departments of trade and industrial companies in Bulgaria in order to propose some guidelines for improving of their effectiveness. Due to independent empirical research, conducted in Bulgarian logistic, trade and industrial enterprises, the authors investigate both the impact degree and the interdependence of various factors that characterize the administrative capacity. The study is conducted with a prepared questionnaire, in format of direct interview with the respondents. The volume of the poll is 50 respondents, representatives of: general managers of industrial or trade enterprises; logistic managers of industrial or trade enterprises; general managers of forwarding companies – either with own or with hired transport; experts from Bulgarian association of logistics; logistic lobbyist and scientists of the relevant area. The data are gathered for 3 months, then arranged by a specialized software program and analyzed by preset criteria. Based on the results of this methodological toolbox, it can be claimed that there is a correlation between the individual criteria. Also, a commitment between the administrative capacity and other factors that determine the competitiveness of the studied companies is established. In this paper, the authors present results of the empirical research that concerns the number and the workload in the logistic departments of the enterprises. Also, what is commented is the experience, related to logistic processes management and human resources competence. Moreover, the overload level of the logistic specialists is analyzed as one of the main threats for making mistakes and losing clients. The paper stands behind the thesis that there is indispensability of forming an effective and efficient administrative capacity, based on the number, qualification, experience and motivation of the staff in the logistic companies. The paper ends with recommendations about the qualification and experience of the specialists in logistic departments; providing effective and efficient administrative capacity in the logistic departments; interdependence of the human factor and the other factors that influence the enterprise competitiveness.

Keywords: administrative capacity, human resources, logistic competitiveness, staff qualification

Procedia PDF Downloads 123