Search results for: mathematical optimizations

Authors: Yuzhen Hu, Sirui Wang

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As a training base for intellectual talents, universities have a large number of students. Teaching is a primary activity in universities, and during the teaching process, a large number of people gather both inside and outside the teaching buildings, posing a strong risk of close contact. The class schedule is the fundamental basis for teaching activities in universities and plays a crucial role in the management of teaching order. Different class schedules can lead to varying degrees of indoor gatherings and trajectories of class attendees. In recent years, highly contagious diseases have frequently occurred worldwide, and how to reduce the risk of infection has always been a hot issue related to public safety. "Reducing gatherings" is one of the core measures in epidemic prevention and control, and it can be controlled through scientific scheduling in specific environments. Therefore, the scientific prevention and control goal can be achieved by considering the reduction of the risk of excessive gathering of people during the course schedule arrangement. Firstly, we address the issue of personnel gathering in various pathways on campus, with the goal of minimizing congestion and maximizing teaching effectiveness, establishing a nonlinear mathematical model. Next, we design an improved genetic algorithm, incorporating real-time evacuation operations based on tracking search and multidimensional positive gradient cross-mutation operations, considering the characteristics of outdoor crowd evacuation. Finally, we apply undergraduate course data from a university in Harbin to conduct a case study. It compares and analyzes the effects of algorithm improvement and optimization of gathering situations and explores the impact of path blocking on the degree of gathering of individuals on other pathways.

Keywords: the university timetabling problem, risk prevention, genetic algorithm, risk control

Procedia PDF Downloads 89

Authors: Carolina Payares-Asprino

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Dual-phase duplex stainless steel comprised of ferrite and austenite has shown high strength and corrosion resistance in many aggressive environments. Joining duplex alloys is challenging due to several embrittling precipitates and metallurgical changes during the welding process. The welding parameters strongly influence the quality of a weld joint. Therefore, it is necessary to quantify the weld bead’s integral properties as a function of welding parameters, especially when part of the weld bead is removed through a machining process due to aesthetic reasons or to couple the elements in the in-service structure. The present study uses the existing stress-strain model to predict the stress-strain curves for duplex stainless-steel welds under different welding conditions. Having mathematical expressions that predict the shape of the stress-strain curve is advantageous since it reduces the experimental work in obtaining the tensile test. In analysis and design, such stress-strain modeling simplifies the time of operations by being integrated into calculation tools, such as the finite element program codes. The elastic zone and the plastic zone of the curve can be defined by specific parameters, generating expressions that simulate the curve with great precision. There are empirical equations that describe the stress-strain curves. However, they only refer to the stress-strain curve for the stainless steel, but not when the material is under the welding process. It is a significant contribution to the applications of duplex stainless steel welds. For this study, a 3x3 matrix with a low, medium, and high level for each of the welding parameters were applied, giving a total of 27 weld bead plates. Two tensile specimens were manufactured from each welded plate, resulting in 54 tensile specimens for testing. When evaluating the four models used to predict the stress-strain curve in the welded specimens, only one model (Rasmussen) presented a good correlation in predicting the strain stress curve.

Keywords: duplex stainless steels, modeling, stress-stress curve, tensile test, welding

Procedia PDF Downloads 167

Authors: Afshin Shahbazi, Hadi Shadi Naghadeh, Ahmad Khodadadi Darban

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In the Magnetically Assisted Chemical Separation (MACS) process, tiny ferromagnetic particles coated with solvent extractant are used to selectively separate radionuclides and hazardous metals from aqueous waste streams. The contaminant-loaded particles are then recovered from the waste solutions using a magnetic field. In the present study, Cyanex272 or C272 (bis (2,4,4-trimethylpentyl) phosphinic acid) coated magnetic particles are being evaluated for the possible application in the extraction of Thorium (IV) from nuclear waste streams. The uptake behaviour of Th(IV) from nitric acid solutions was investigated by batch studies. Adsorption of Thorium (IV) from aqueous solution onto adsorbent was investigated in a batch system. Adsorption isotherm and adsorption kinetic studies of Thorium (IV) onto nanoparticles coated Cyanex272 were carried out in a batch system. The factors influencing Thorium (IV) adsorption were investigated and described in detail, as a function of the parameters such as initial pH value, contact time, adsorbent mass, and initial Thorium (IV) concentration. Magnetically Assisted Chemical Separation (MACS) process adsorbent showed best results for the fast adsorption of Th (IV) from aqueous solution at aqueous phase acidity value of 0.5 molar. In addition, more than 80% of Th (IV) was removed within the first 2 hours, and the time required to achieve the adsorption equilibrium was only 140 minutes. Langmuir and Frendlich adsorption models were used for the mathematical description of the adsorption equilibrium. Equilibrium data agreed very well with the Langmuir model, with a maximum adsorption capacity of 48 mg.g-1. Adsorption kinetics data were tested using pseudo-first-order, pseudo-second-order and intra-particle diffusion models. Kinetic studies showed that the adsorption followed a pseudo-second-order kinetic model, indicating that the chemical adsorption was the rate-limiting step.

Keywords: Thorium (IV) adsorption, MACS process, magnetic nanoparticles, Cyanex272

Procedia PDF Downloads 338

Authors: Mahmoud B. Rokaya

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The study of opinion mining and sentiment analysis includes analysis of opinions, sentiments, evaluations, attitudes, and emotions. The rapid growth of social media, social networks, reviews, forum discussions, microblogs, and Twitter, leads to a parallel growth in the field of sentiment analysis. The field of sentiment analysis tries to develop effective tools to make it possible to capture the trends of people. There are two approaches in the field, lexicon-based and corpus-based methods. A lexicon-based method uses a sentiment lexicon which includes sentiment words and phrases with assigned numeric scores. These scores reveal if sentiment phrases are positive or negative, their intensity, and/or their emotional orientations. Creation of manual lexicons is hard. This brings the need for adaptive automated methods for generating a lexicon. The proposed method generates dynamic lexicons based on the corpus and then classifies text using these lexicons. In the proposed method, different approaches are combined to generate lexicons from text. The proposed method classifies the tweets into 5 classes instead of +ve or –ve classes. The sentiment classification problem is written as an optimization problem, finding optimum sentiment lexicons are the goal of the optimization process. The solution was produced based on mathematical programming approaches to find the best lexicon to classify texts. A genetic algorithm was written to find the optimal lexicon. Then, extraction of a meta-level feature was done based on the optimal lexicon. The experiments were conducted on several datasets. Results, in terms of accuracy, recall and F measure, outperformed the state-of-the-art methods proposed in the literature in some of the datasets. A better understanding of the Arabic language and culture of Arab Twitter users and sentiment orientation of words in different contexts can be achieved based on the sentiment lexicons proposed by the algorithm.

Keywords: social media, Twitter sentiment, sentiment analysis, lexicon, genetic algorithm, evolutionary computation

Procedia PDF Downloads 188

Authors: N. Santatriniaina, J. Deseure, T. Q. Nguyen, H. Fontaine, C. Beitia, L. Rakotomanana

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Nowadays, with the increasing of the wafer's size and the decreasing of critical size of integrated circuit manufacturing in modern high-tech, microelectronics industry needs a maximum attention to challenge the contamination control. The move to 300 mm is accompanied by the use of Front Opening Unified Pods for wafer and his storage. In these pods an airborne cross contamination may occur between wafers and the pods. A predictive approach using modeling and computational methods is very powerful method to understand and qualify the AMCs cross contamination processes. This work investigates the required numerical tools which are employed in order to study the AMCs cross-contamination transfer phenomena between wafers and FOUPs. Numerical optimization and finite element formulation in transient analysis were established. Analytical solution of one dimensional problem was developed and the calibration process of physical constants was performed. The least square distance between the model (analytical 1D solution) and the experimental data are minimized. The behavior of the AMCs intransient analysis was determined. The model framework preserves the classical forms of the diffusion and convection-diffusion equations and yields to consistent form of the Fick's law. The adsorption process and the surface roughness effect were also traduced as a boundary condition using the switch condition Dirichlet to Neumann and the interface condition. The methodology is applied, first using the optimization methods with analytical solution to define physical constants, and second using finite element method including adsorption kinetic and the switch of Dirichlet to Neumann condition.

Keywords: AMCs, FOUP, cross-contamination, adsorption, diffusion, numerical analysis, wafers, Dirichlet to Neumann, finite elements methods, Fick’s law, optimization

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Authors: Yaniv Knop, Alva Peled

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Over the past few years there has been a growing interest in the development of Portland Composite Cement, by partial replacement of the clinker with mineral additives. The motivations to reduce the clinker content are threefold: (1) Ecological - due to lower emission of CO2 to the atmosphere; (2) Economical - due to cost reduction; and (3) Scientific\Technology – improvement of performances. Among the mineral additives being used and investigated, limestone is one of the most attractive, as it is considered natural, available, and with low cost. The goal of the research is to develop green cement, by partial replacement of the clinker with limestone powder while improving the performances of the cement paste. This work studied blended cements with three limestone powder particle diameters: smaller than, larger than, and similarly sized to the clinker particle. Blended cement with limestone consisting of one particle size distribution and limestone consisting of a combination of several particle sizes were studied and compared in terms of hydration rate, hydration degree, and water demand to achieve normal consistency. The performances of these systems were also compared with that of the original cement (without added limestone). It was found that the ability to replace an active material with an inert additive, while achieving improved performances, can be obtained by increasing the packing density of the cement-based particles. This may be achieved by replacing the clinker with limestone powders having a combination of several different particle size distributions. Mathematical and physical models were developed to simulate the setting history from initial to final setting time and to predict the packing density of blended cement with limestone having different sizes and various contents. Besides the effect of limestone, as inert additive, on the packing density of the blended cement, the influence of the limestone particle size on three different chemical reactions were studied; hydration of the cement, carbonation of the calcium hydroxide and the reactivity of the limestone with the hydration reaction products. The main results and developments will be presented.

Keywords: packing density, hydration degree, limestone, blended cement

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Authors: Lydia Novozhilova, Vladimir Urazhdin

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An optimization problem for reinforced thin-walled vessels under uniform external pressure is considered. The conventional approaches to optimization generally start with pre-defined geometric parameters of the vessels, and then employ analytic or numeric calculations and/or experimental testing to verify functionality, such as stability under the projected conditions. The proposed approach consists of two steps. First, the feasibility domain will be identified in the multidimensional parameter space. Every point in the feasibility domain defines a design satisfying both geometric and functional constraints. Second, an objective function defined in this domain is formulated and optimized. The broader applicability of the suggested methodology is maximized by implementing the Support Vector Machines (SVM) classification algorithm of machine learning for identification of the feasible design region. Training data for SVM classifier is obtained using the Simulation package of SOLIDWORKS®. Based on the data, the SVM algorithm produces a curvilinear boundary separating admissible and not admissible sets of design parameters with maximal margins. Then optimization of the vessel parameters in the feasibility domain is performed using the standard algorithms for the constrained optimization. As an example, optimization of a ring-stiffened closed cylindrical thin-walled vessel with semi-spherical caps under high external pressure is implemented. As a functional constraint, von Mises stress criterion is used but any other stability constraint admitting mathematical formulation can be incorporated into the proposed approach. Suggested methodology has a good potential for reducing design time for finding optimal parameters of thin-walled vessels under uniform external pressure.

Keywords: design parameters, feasibility domain, von Mises stress criterion, Support Vector Machine (SVM) classifier

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Authors: Nkwenti Mbelli Njah

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This research was motivated by a project requested by AXA on the topic of pensions payable under the workers compensation (WC) line of business. There are two types of pensions: the compulsorily recoverable and the not compulsorily recoverable. A pension is compulsorily recoverable for a victim when there is less than 30% of disability and the pension amount per year is less than six times the minimal national salary. The law defines that the mathematical provisions for compulsory recoverable pensions must be calculated by applying the following bases: mortality table TD88/90 and rate of interest 5.25% (maybe with rate of management). To manage pensions which are not compulsorily recoverable is a more complex task because technical bases are not defined by law and much more complex computations are required. In particular, companies have to predict the amount of payments discounted reflecting the mortality effect for all pensioners (this task is monitored monthly in AXA). The purpose of this research was thus to develop a stochastic model for the future mortality of the worker’s compensation pensioners of both the Portuguese market workers and AXA portfolio. Not only is past mortality modeled, also projections about future mortality are made for the general population of Portugal as well as for the two portfolios mentioned earlier. The global model was split in two parts: a stochastic model for population mortality which allows for forecasts, combined with a point estimate from a portfolio mortality model obtained through three different relational models (Cox Proportional, Brass Linear and Workgroup PLT). The one-year death probabilities for ages 0-110 for the period 2013-2113 are obtained for the general population and the portfolios. These probabilities are used to compute different life table functions as well as the not compulsorily recoverable reserves for each of the models required for the pensioners, their spouses and children under 21. The results obtained are compared with the not compulsory recoverable reserves computed using the static mortality table (TD 73/77) that is currently being used by AXA, to see the impact on this reserve if AXA adopted the dynamic tables.

Keywords: compulsorily recoverable, life table functions, relational models, worker’s compensation pensioners

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Authors: Peng Zhang, Lihui Zheng, Xiangchun Wang, Xiaopan Kou

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Quantitative research on the main control factors of lost circulation has few considerations and single data source. Using Unmanned Intervention Algorithm to find the main control factors of lost circulation adopts all measurable parameters. The degree of lost circulation is characterized by the loss rate as the objective function. Geological, engineering and fluid data are used as layers, and 27 factors such as wellhead coordinates and WOB are used as dimensions. Data classification is implemented to determine function independent variables. The mathematical equation of loss rate and 27 influencing factors is established by multiple regression method, and the undetermined coefficient method is used to solve the undetermined coefficient of the equation. Only three factors in t-test are greater than the test value 40, and the F-test value is 96.557%, indicating that the correlation of the model is good. The funnel viscosity, final shear force and drilling time were selected as the main control factors by elimination method, contribution rate method and functional method. The calculated values of the two wells used for verification differ from the actual values by -3.036m3/h and -2.374m3/h, with errors of 7.21% and 6.35%. The influence of engineering factors on the loss rate is greater than that of funnel viscosity and final shear force, and the influence of the three factors is less than that of geological factors. Quantitatively calculate the best combination of funnel viscosity, final shear force and drilling time. The minimum loss rate of lost circulation wells in Shunbei area is 10m3/h. It can be seen that man-made main control factors can only slow down the leakage, but cannot fundamentally eliminate it. This is more in line with the characteristics of karst caves and fractures in Shunbei fault solution oil and gas reservoir.

Keywords: drilling and completion, drilling fluid, lost circulation, loss rate, main controlling factors, unmanned intervention algorithm

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Authors: Ali Ayatic, Emad Mozaffari, Bahareh Tanhaei, Maryam Khajenoori, Saeedeh Movaghar Khoshkho, Ali Ayati

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The abuse of antibiotics, such as tetracycline (TC), is a great global threat to people and the use of topical antibiotics is a promising tact that can help to solve this problem. Antibiotic therapy is often appropriate and necessary for acute wound infections, while topical tetracycline can be highly efficient in improving the wound healing process in diabetics. Due to the advantages of drug-loaded hydrogels as wound dressing, such as ease of handling, high moisture resistance, excellent biocompatibility, and the ability to activate immune cells to speed wound healing, it was found as an ideal wound treatment. In this work, the tetracycline-loaded hydrogels combining agar (AG) and κ-carrageenan (k-CAR) as polymer materials were prepared, in which span60 surfactant was introduced inside as a drug carrier. The Field Emission Scanning Electron Microscopes (FESEM) and Fourier-transform infrared spectroscopy (FTIR) techniques were employed to provide detailed information on the morphology, composition, and structure of fabricated drug-loaded hydrogels and their mechanical properties, and hydrogel permeability to water vapor was investigated as well. Two types of gram-negative and gram-positive bacteria were used to explore the antibacterial properties of prepared tetracycline-contained hydrogels. Their swelling and drug release behavior was studied using the changing factors such as the ratio of polysaccharides (MAG/MCAR), the span60 surfactant concentration, potassium chloride (KCl) concentration and different release media (deionized water (DW), phosphate-buffered saline (PBS), and simulated wound fluid (SWF)) at different times. Finally, the kinetic behavior of hydrogel swelling was studied. Also, the experimental data of TC release to DW, PBS, and SWF using various mathematical models such as Higuchi, Korsmeyer-Peppas, zero-order, and first-order in the linear and nonlinear modes were evaluated.

Keywords: drug release, hydrogel, tetracycline, wound healing

Procedia PDF Downloads 80

Authors: Gianpaolo Ghiani, Emanuela Guerriero, Emanuele Manni, Alessandro Romano

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In this article, we deal with a variant of the classical course timetabling problem that has a practical application in many areas of education. In particular, in this paper we are interested in high schools remedial courses. The purpose of such courses is to provide under-prepared students with the skills necessary to succeed in their studies. In particular, a student might be under prepared in an entire course, or only in a part of it. The limited availability of funds, as well as the limited amount of time and teachers at disposal, often requires schools to choose which courses and/or which teaching units to activate. Thus, schools need to model the training offer and the related timetabling, with the goal of ensuring the highest possible teaching quality, by meeting the above-mentioned financial, time and resources constraints. Moreover, there are some prerequisites between the teaching units that must be satisfied. We first present a Mixed-Integer Programming (MIP) model to solve this problem to optimality. However, the presence of many peculiar constraints contributes inevitably in increasing the complexity of the mathematical model. Thus, solving it through a general purpose solver may be performed for small instances only, while solving real-life-sized instances of such model requires specific techniques or heuristic approaches. For this purpose, we also propose a heuristic approach, in which we make use of a fast constructive procedure to obtain a feasible solution. To assess our exact and heuristic approaches we perform extensive computational results on both real-life instances (obtained from a high school in Lecce, Italy) and randomly generated instances. Our tests show that the MIP model is never solved to optimality, with an average optimality gap of 57%. On the other hand, the heuristic algorithm is much faster (in about the 50% of the considered instances it converges in approximately half of the time limit) and in many cases allows achieving an improvement on the objective function value obtained by the MIP model. Such an improvement ranges between 18% and 66%.

Keywords: heuristic, MIP model, remedial course, school, timetabling

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Authors: Mouna Baassi, Mohamed Moussaoui, Sanchaita Rajkhowa, Hatim Soufi, Said Belaaouad

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The objective of this paper is to address the challenging task of targeting Human Immunodeficiency Virus type 1 Reverse Transcriptase (HIV-1 RT) in the treatment of AIDS. Reverse Transcriptase inhibitors (RTIs) have limitations due to the development of Reverse Transcriptase mutations that lead to treatment resistance. In this study, a combination of statistical analysis and bioinformatics tools was adopted to develop a mathematical model that relates the structure of compounds to their inhibitory activities against HIV-1 Reverse Transcriptase. Our approach was based on a series of compounds recognized for their HIV-1 RT enzymatic inhibitory activities. These compounds were designed via software, with their descriptors computed using multiple tools. The most statistically promising model was chosen, and its domain of application was ascertained. Furthermore, compounds exhibiting comparable biological activity to existing drugs were identified as potential inhibitors of HIV-1 RT. The compounds underwent evaluation based on their chemical absorption, distribution, metabolism, excretion, toxicity properties, and adherence to Lipinski's rule. Molecular docking techniques were employed to examine the interaction between the Reverse Transcriptase (Wild Type and Mutant Type) and the ligands, including a known drug available in the market. Molecular dynamics simulations were also conducted to assess the stability of the RT-ligand complexes. Our results reveal some of the new compounds as promising candidates for effectively inhibiting HIV-1 Reverse Transcriptase, matching the potency of the established drug. This necessitates further experimental validation. This study, beyond its immediate results, provides a methodological foundation for future endeavors aiming to discover and design new inhibitors targeting HIV-1 Reverse Transcriptase.

Keywords: QSAR, ADMET properties, molecular docking, molecular dynamics simulation, reverse transcriptase inhibitors, HIV type 1

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Authors: M. S. Aparna, Pushparaj Shetty D.

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Nowadays social networking sites have become so popular that the producers or the sellers look for these sites as one of the best options to target the right audience to market their products. There are several tools available to monitor or analyze the social networks. Our task is to identify the right community web pages and find out the behavior analysis of the members by using these tools and formulate an appropriate strategy to market the products or services to achieve the set goals. The advertising becomes more effective when the information of the product/ services come from a known source. The strategy explores great buying influence in the audience on referral marketing. Our methodology proceeds with critical budget analysis and promotes viral influence propagation. In this context, we encompass the vital bits of budget evaluation such as the number of optimal seed nodes or primary influential users activated onset, an estimate coverage spread of nodes and maximum influence propagating distance from an initial seed to an end node. Our proposal for Buyer Prediction mathematical model arises from the urge to perform complex analysis when the probability density estimates of reliable factors are not known or difficult to calculate. Order Statistics and Buyer Prediction mapping function guarantee the selection of optimal influential users at each level. We exercise an efficient tactics of practicing community pages and user behavior to determine the product enthusiasts on social networks. Our approach is promising and should be an elementary choice when there is little or no prior knowledge on the distribution of potential buyers on social networks. In this strategy, product news propagates to influential users on or surrounding networks. By applying the same technique, a user can search friends who are capable to advise better or give referrals, if a product interests him.

Keywords: viral marketing, social network analysis, community web pages, buyer prediction, influence propagation, budget constraints

Procedia PDF Downloads 262

Authors: Waqas Ahmed Khan Afridi, Subhas Chandra Mukhopadhyay, Bandita Mainali

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The research paper presents a unique approach to evapotranspiration (ET) prediction using a Support Vector Machine (SVM) learning algorithm. The study leverages real-time sensor node data to develop an accurate and adaptable prediction model, addressing the inherent challenges of traditional ET estimation methods. The integration of the SVM algorithm with real-time sensor node data offers great potential to improve spatial and temporal resolution in ET predictions. In the model development, key input features are measured and computed using mathematical equations such as Penman-Monteith (FAO56) and soil water balance (SWB), which include soil-environmental parameters such as; solar radiation (Rs), air temperature (T), atmospheric pressure (P), relative humidity (RH), wind speed (u2), rain (R), deep percolation (DP), soil temperature (ST), and change in soil moisture (∆SM). The one-year field data are split into combinations of three proportions i.e. train, test, and validation sets. While kernel functions with tuning hyperparameters have been used to train and improve the accuracy of the prediction model with multiple iterations. This paper also outlines the existing methods and the machine learning techniques to determine Evapotranspiration, data collection and preprocessing, model construction, and evaluation metrics, highlighting the significance of SVM in advancing the field of ET prediction. The results demonstrate the robustness and high predictability of the developed model on the basis of performance evaluation metrics (R2, RMSE, MAE). The effectiveness of the proposed model in capturing complex relationships within soil and environmental parameters provide insights into its potential applications for water resource management and hydrological ecosystem.

Keywords: evapotranspiration, FAO56, KNIME, machine learning, RStudio, SVM, sensors

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Authors: Kharisma Utomo Mulyodinoto, Suwarno, Ahmed Abu-Siada

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Transformer insulating oil is a key component that can be utilized to detect incipient faults within operating transformers without taking them out of service. Dissolved gas-in-oil analysis has been widely accepted as a powerful technique to detect such incipient faults. While the measurement of dissolved gases within transformer oil samples has been standardized over the past two decades, analysis of the results is not always straightforward as it depends on personnel expertise more than mathematical formulas. In analyzing such data, the generation rate of each dissolved gas is of more concern than the absolute value of the gas. As such, history of dissolved gases within a particular transformer should be archived for future comparison. Lack of such history may lead to misinterpretation of the obtained results. IEEE C57.104-2008 standards have classified the health condition of the transformer based on the absolute value of individual dissolved gases along with the total dissolved combustible gas (TDCG) within transformer oil into 4 conditions. While the technique is easy to implement, it is considered as a very conservative technique and is not widely accepted as a reliable interpretation tool. Moreover, measured gases for the same oil sample can be within various conditions limits and hence, misinterpretation of the data is expected. To overcome this limitation, this paper introduces a fuzzy logic approach to predict the health condition of the transformer oil based on IEEE C57.104-2008 standards along with Roger ratio and IEC ratio-based methods. DGA results of 31 chosen oil samples from 469 transformer oil samples of normal transformers and pre-known fault-type transformers that were collected from Indonesia Electrical Utility Company, PT. PLN (Persero), from different voltage rating: 500/150 kV, 150/20 kV, and 70/20 kV; different capacity: 500 MVA, 60 MVA, 50 MVA, 30 MVA, 20 MVA, 15 MVA, and 10 MVA; and different lifespan, are used to test and establish the fuzzy logic model. Results show that the proposed approach is of good accuracy and can be considered as a platform toward the standardization of the dissolved gas interpretation process.

Keywords: dissolved gas analysis, fuzzy logic, health index, IEEE C57.104-2008, IEC ratio method, Roger ratio method

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Authors: Ahmad AlAbdullah, Ali AlQallaf, Mahdi Hussain, Mohammed AlAttar, Salman Ashknani, Magdy Helal

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We study the effectiveness of the parking service provided at Kuwaiti commercial malls and explore potential problems and feasible improvements. Commercial malls are important to Kuwaitis as the entertainment and shopping centers due to the lack of other alternatives. The difficulty and relatively long times wasted in finding a parking spot at the mall are real annoyances. We applied queuing analysis to one of the major malls that offer paid-parking (1040 parking spots) in addition to free parking. Patrons of the mall usually complained of the traffic jams and delays at entering the paid parking (average delay to park exceeds 15 min for about 62% of the patrons, while average time spent in the mall is about 2.6 hours). However, the analysis showed acceptable service levels at the check-in gates of the parking garage. Detailed review of the vehicle movement at the gateways indicated that arriving and departing cars both had to share parts of the gateway to the garage, which caused the traffic jams and delays. A simple comparison we made indicated that the largest commercial mall in Kuwait does not suffer such parking issues, while other smaller, yet important malls do, including the one we studied. It was suggested that well-designed inlets and outlets of that gigantic mall permitted smooth parking despite being totally free and mall is the first choice for most people for entertainment and shopping. A simulation model is being developed for further analysis and verification. Simulation can overcome the mathematical difficulty in using non-Poisson queuing models. The simulation model is used to explore potential changes to the parking garage entrance layout. And with the inclusion of the drivers’ behavior inside the parking, effectiveness indicators can be derived to address the economic feasibility of extending the parking capacity and increasing service levels. Outcomes of the study are planned to be generalized as appropriate to other commercial malls in Kuwait

Keywords: commercial malls, parking service, queuing analysis, simulation modeling

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Authors: Ling Liyun

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In the field of contemporary architecture, complex forms of architectural works continue to emerge in the world, along with some new terminology emerged: digital architecture, parametric design, algorithm generation, building information modeling, CNC construction and so on. Architects gradually mastered the new skills of mathematical logic in the form of exploration, virtual simulation, and the entire design and coordination in the construction process. Digital construction technology has a greater degree in controlling construction, and ensure its accuracy, creating a series of new construction techniques. As a result, the use of digital technology is an improvement and expansion of the practice of digital architecture design revolution. We worked by reading and analyzing information about the digital architecture development process, a large number of cases, as well as architectural design and construction as a whole process. Thus current developments were introduced and discussed in our paper, such as architectural discourse, design theory, digital design models and techniques, material selecting, as well as artificial intelligence space design. Our paper also pays attention to the representative three cases of digital design and construction experiment at great length in detail to expound high-informatization, high-reliability intelligence, and high-technique in constructing a humane space to cope with the rapid development of urbanization. We concluded that the opportunities and challenges of the shift existed in architectural paradigms, such as the cooperation methods, theories, models, technologies and techniques which were currently employed in digital design research and digital praxis. We also find out that the innovative use of space can gradually change the way people learn, talk, and control information. The past two decades, digital technology radically breaks the technology constraints of industrial technical products, digests the publicity on a particular architectural style (era doctrine). People should not adapt to the machine, but in turn, it’s better to make the machine work for users.

Keywords: artificial intelligence, collaboration, digital architecture, digital design theory, material selection, space construction

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Authors: Zhuo Feng, Ying Gao

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Public-private partnership (PPP), as an innovative way to provide infrastructures by the private sector, is being widely used throughout the world. Compared with the traditional mode, PPP emerges largely for merits of relieving public budget constraint and improving infrastructure supply efficiency by involving private funds. However, PPP projects are characterized by large scale, high investment, long payback period, and long concession period. These characteristics make PPP projects full of risks. One of the most important risks faced by the private sector is demand risk because many factors affect the real demand. If the real demand is far lower than the forecasting demand, the private sector will be got into big trouble because operating revenue is the main means for the private sector to recoup the investment and obtain profit. Therefore, it is important to study how the government compensates the private sector when the demand risk occurs in order to achieve Pareto-improvement. This research focuses on price compensation mechanism, an ex-post compensation mechanism, and analyzes, by mathematical modeling, the impact of price compensation mechanism on payoff of the private sector and consumer surplus for PPP toll road projects. This research first investigates whether or not price compensation mechanisms can obtain Pareto-improvement and, if so, then explores boundary conditions for this mechanism. The research results show that price compensation mechanism can realize Pareto-improvement under certain conditions. Especially, to make the price compensation mechanism accomplish Pareto-improvement, renegotiation costs of the government and the private sector should be lower than a certain threshold which is determined by marginal operating cost and distortionary cost of the tax. In addition, the compensation percentage should match with the price cut of the private investor when demand drops. This research aims to provide theoretical support for the government when determining compensation scope under the price compensation mechanism. Moreover, some policy implications can also be drawn from the analysis for better risk-sharing and sustainability of PPP projects.

Keywords: infrastructure, price compensation mechanism, public-private partnership, renegotiation

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Authors: E. E. Tereshatov, M. Yu. Boltoeva, V. Mazan, M. F. Volia, C. M. Folden III

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Room temperature ionic liquids (RTILs) are a class of liquid organic salts with melting points below 20 °C that are considered to be environmentally friendly ‘designers’ solvents. Pure hydrophobic ILs are known to extract metallic species from aqueous solutions. The closest analogues of ionic liquids are deep eutectic solvents (DESs), which are a eutectic mixture of at least two compounds with a melting point lower than that of each individual component. DESs are acknowledged to be attractive for organic synthesis and metal processing. Thus, these non-volatile and less toxic compounds are of interest for critical metal extraction. The US Department of Energy and the European Commission consider indium as a key metal. Its chemical homologue, thallium, is also an important material for some applications and environmental safety. The aim of this work is to systematically investigate In and Tl extraction from aqueous solutions into pure fluorinated ILs and hydrophobic DESs. The dependence of the Tl extraction efficiency on the structure and composition of the ionic liquid ions, metal oxidation state, and initial metal and aqueous acid concentrations have been studied. The extraction efficiency of the TlXz3–z anionic species (where X = Cl– and/or Br–) is greater for ionic liquids with more hydrophobic cations. Unexpectedly high distribution ratios (> 103) of Tl(III) were determined even by applying a pure ionic liquid as receiving phase. An improved mathematical model based on ion exchange and ion pair formation mechanisms has been developed to describe the co-extraction of two different anionic species, and the relative contributions of each mechanism have been determined. The first evidence of indium extraction into new quaternary ammonium- and menthol-based hydrophobic DESs from hydrochloric and oxalic acid solutions with distribution ratios up to 103 will be provided. Data obtained allow us to interpret the mechanism of thallium and indium extraction into ILs and DESs media. The understanding of Tl and In chemical behavior in these new media is imperative for the further improvement of separation and purification of these elements.

Keywords: deep eutectic solvents, indium, ionic liquids, thallium

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Authors: Agoston Restas

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Introduction: This paper describes many initiatives and shows also practical examples which happened recently using Unmanned Aerial Systems (UAS) to support disaster management. Since the operation of manned aircraft at disasters is usually not only expensive but often impossible to use as well, in many cases managers fail to use the aerial activity. UAS can be an alternative moreover cost-effective solution for supporting disaster management. Methods: This article uses thematic division of UAS applications; it is based on two key elements, one of them is the time flow of managing disasters, other is its tactical requirements. Logically UAS can be used like pre-disaster activity, activity immediately after the occurrence of a disaster and the activity after the primary disaster elimination. Paper faces different disasters, like dangerous material releases, floods, earthquakes, forest fires and human-induced disasters. Research used function analysis, practical experiments, mathematical formulas, economic analysis and also expert estimation. Author gathered international examples and used own experiences in this field as well. Results and discussion: An earthquake is a rapid escalating disaster, where, many times, there is no other way for a rapid damage assessment than aerial reconnaissance. For special rescue teams, the UAS application can help much in a rapid location selection, where enough place remained to survive for victims. Floods are typical for a slow onset disaster. In contrast, managing floods is a very complex and difficult task. It requires continuous monitoring of dykes, flooded and threatened areas. UAS can help managers largely keeping an area under observation. Forest fires are disasters, where the tactical application of UAS is already well developed. It can be used for fire detection, intervention monitoring and also for post-fire monitoring. In case of nuclear accident or hazardous material leakage, UAS is also a very effective or can be the only one tool for supporting disaster management. Paper shows some efforts using UAS to avoid human-induced disasters in low-income countries as part of health cooperation.

Keywords: disaster management, floods, forest fires, Unmanned Aerial Systems

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Authors: H. Hammoudi, S. Bendenia, I. Batonneau-Gener, A. Khelifa

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Applying growing zeolites is due to their intrinsic physicochemical properties: a porous structure, regular, generating a large free volume, a high specific surface area, acidic properties of interest to the origin of their activity, selectivity energy and dimensional, leading to a screening phenomenon, hence the name of molecular sieves is generally attributed to them. Most of the special properties of zeolites have been valued as direct applications such as ion exchange, adsorption, separation and catalysis. Due to their crystalline structure stable, their large pore volume and their high content of cation X zeolites are widely used in the process of adsorption and separation. The acidic properties of zeolites X and interesting selectivity conferred on them their porous structure is also have potential catalysts. The study presented in this manuscript is devoted to the chemical modification of an X zeolite by cation exchange. Ion exchange of zeolite NaX by Zn 2 + cations and / or Cu 2 + is gradually conducted by following the evolution of some of its characteristics: crystallinity by XRD, micropore volume by nitrogen adsorption. Once characterized, the different samples will be used for the adsorption of propane and propylene. Particular attention is paid thereafter, on the modeling of adsorption isotherms. In this vein, various equations of adsorption isotherms and localized mobile, some taking into account the adsorbate-adsorbate interactions, are used to describe the experimental isotherms. We also used the Toth equation, a mathematical model with three parameters whose adjustment requires nonlinear regression. The last part is dedicated to the study of acid properties of Cu (x) X, Zn (x) X and CuZn (x) X, with the adsorption-desorption of pyridine followed by IR. The effect of substitution at different rates of Na + by Cu2 + cations and / or Zn 2 +, on the crystallinity and on the textural properties was treated. Some results on the morphology of the crystallites and the thermal effects during a temperature rise, obtained by scanning electron microscopy and DTA-TGA thermal analyzer, respectively, are also reported. The acidity of our different samples was also studied. Thus, the nature and strength of each type of acidity are estimated. The evaluation of these various features will provide a comparison between Cu (x) X, Zn (x) X and CuZn (x) X. One study on adsorption of C3H8 and C3H6 in NaX, Cu (x) X , Zn (x) x and CuZn (x) x has been undertaken.

Keywords: adsorption, acidity, ion exchange, zeolite

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Authors: Iuri Salukvadze

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Development of Georgian Economy largely depends on its effective use of its transit country potential. The value of Georgia as the part of Europe-Asia corridor has increased; this increases the interest of western and eastern countries to Georgia as to the country that laid on the transit axes that implies transit infrastructure creation and development in Georgia. It is important to use compacted concrete with the additive in modern road construction industry. Even in the 21-century, concrete remains as the main vital constructive building material, therefore innovative, economic and environmentally protected technologies are needed. Georgian construction market requires the use of concrete of new generation, adaptation of nanotechnologies to the local realities that will give the ability to create multifunctional, nano-technological high effective materials. It is highly important to research their physical and mechanical states. The study of compacted concrete with the additives is necessary to use in the road construction in the future and to increase hardness of roads in Georgia. The aim of the research is to study the physical-mechanical properties of the compacted concrete with the additives based on the local materials. Any experimental study needs large number of experiments from one side in order to achieve high accuracy and optimal number of the experiments with minimal charges and in the shortest period of time from the other side. To solve this problem in practice, it is possible to use experiments planning static and mathematical methods. For the materials properties research we will use distribution hypothesis, measurements results by normal law according to which divergence of the obtained results is caused by the error of method and inhomogeneity of the object. As the result of the study, we will get resistible compacted concrete with additives for the motor roads that will improve roads infrastructure and give us saving rate while construction of the roads and their exploitation.

Keywords: construction, seismic protection systems, soil, motor roads, concrete

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Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

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Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, Unmanned Aerial Vehicle (UAV), uniform, random, kriging

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Authors: Wassie Molla, Klaas Frankena, Mart De Jong

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Lumpy skin disease (LSD) is a severe viral disease of cattle, which often occurs in epidemic form. It is caused by lumpy skin disease virus of the genus capripoxvirus of family poxviridae. Mathematical models play important role in the study of infectious diseases epidemiology. They help to explain the dynamics and understand the transmission of an infectious disease within a population. Understanding the transmission dynamics of lumpy skin disease between animals is important for the implementation of effective prevention and control measures against the disease. This study was carried out in central and north-western part of Ethiopia with the objectives to understand LSD outbreak dynamics, quantify the transmission between animals and herds, and estimate the disease reproduction ratio in dominantly crop-livestock mixed and commercial herd types. Field observation and follow-up study were undertaken, and the transmission parameters were estimated based on a SIR epidemic model in which individuals are susceptible (S), infected and infectious (I), and recovered and immune or dead (R) using the final size and generalized linear model methods. The result showed that a higher morbidity was recorded in infected crop-livestock (24.1%) mixed production system herds than infected commercial production (17.5%) system herds whereas mortality was higher in intensive (4.0%) than crop-livestock (1.5%) system and the differences were statistically significant. The transmission rate among animals and between herds were 0.75 and 0.68 per week, respectively in dominantly crop-livestock production system. The transmission study undertaken in dominantly crop-livestock production system highlighted the presence of statistically significant seasonal difference in LSD transmission among animals. The reproduction numbers of LSD in dominantly crop-livestock production system were 1.06 among animals and 1.28 between herds whereas it varies from 1.03 to 1.31 among animals in commercial production system. Though the R estimated for LSD in different production systems at different localities is greater than 1, its magnitude is low implying that the disease can be easily controlled by implementing the appropriate control measures.

Keywords: commercial, crop-livestock, Ethiopia, LSD, reproduction number, transmission

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Authors: Rima A. Ajlouni

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The discovery of quasi-periodic structures in material science is revealing an exciting new class of symmetries, which has never been explored before. Due to their unique structural and visual properties, these symmetries are drawing interest from many scientific and design disciplines. Especially, in art and architecture, these symmetries can provide a rich source of geometry for exploring new patterns, forms, systems, and structures. However, the structural systems of these complicated symmetries are still posing a perplexing challenge. While much of their local order has been explored, the global governing system is still unresolved. Understanding their unique global long-range order is essential to their generation and application. The recent discovery of dodecagonal quasi-periodic patterns in historical Islamic architecture is generating a renewed interest into understanding the mathematical principles of traditional Islamic geometry. Astonishingly, many centuries before its description in the modern science, ancient artists, by using the most primitive tools (a compass and a straight edge), were able to construct patterns with quasi-periodic formations. These ancient patterns can be found all over the ancient Islamic world, many of which exhibit formations with 5, 8, 10 and 12 quasi-periodic symmetries. Based on the examination of these historical patterns and derived from the generating principles of Islamic geometry, a global multi-level structural model is presented that is able to describe the global long-range order of dodecagonal quasi-periodic formations in Islamic Architecture. Furthermore, this method is used to construct new quasi-periodic tiling systems as well as generating their deflation and inflation rules. This method can be used as a general guiding principle for constructing infinite patches of dodecagon-based quasi-periodic formations, without the need for local strategies (tiling, matching, grid, substitution, etc.) or complicated mathematics; providing an easy tool for scientists, mathematicians, teachers, designers and artists, to generate and study a wide range of dodecagonal quasi-periodic formations.

Keywords: dodecagonal, Islamic architecture, long-range order, quasi-periodi

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Authors: Chen Xiatong

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The study aims to explore the interrelationship between corporate governance factors and firm performance in Mainland China using a mixed-method approach. To clarify the current effectiveness of corporate governance, uncover the complex interrelationships between governance factors and firm performance, and enhance understanding of corporate governance strategies in Mainland China. The research involves quantitative methods like statistical analysis of governance factors and firm performance data, as well as qualitative approaches including policy research, case studies, and interviews with staff members. The study aims to reveal the current effectiveness of corporate governance in Mainland China, identify complex interrelationships between governance factors and firm performance, and provide suggestions for companies to enhance their governance practices. The research contributes to enriching the literature on corporate governance by providing insights into the effectiveness of governance practices in Mainland China and offering suggestions for improvement. Quantitative data will be gathered through surveys and sampling methods, focusing on governance factors and firm performance indicators. Qualitative data will be collected through policy research, case studies, and interviews with staff members. Quantitative data will be analyzed using statistical, mathematical, and computational techniques. Qualitative data will be analyzed through thematic analysis and interpretation of policy documents, case study findings, and interview responses. The study addresses the effectiveness of corporate governance in Mainland China, the interrelationship between governance factors and firm performance, and staff members' perceptions of corporate governance strategies. The research aims to enhance understanding of corporate governance effectiveness, enrich the literature on governance practices, and contribute to the field of business management and human resources management in Mainland China.

Keywords: corporate governance, business management, human resources management, board of directors

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Authors: Urbánek Jiří J., Krahulec Josef, Urbánek Jiří F., Johanidesová Jitka

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These Computational assistance for the research and modelling of critical infrastructure subjects continuity deal with this paper. It enables us the using of prevailing operation system MS Office (SmartArt...) for mathematical models, using DYVELOP (Dynamic Vector Logistics of Processes) method. It serves for crisis situations investigation and modelling within the organizations of critical infrastructure. In the first part of the paper, it will be introduced entities, operators and actors of DYVELOP method. It uses just three operators of Boolean algebra and four types of the entities: the Environments, the Process Systems, the Cases and the Controlling. The Process Systems (PrS) have five “brothers”: Management PrS, Transformation PrS, Logistic PrS, Event PrS and Operation PrS. The Cases have three “sisters”: Process Cell Case, Use Case and Activity Case. They all need for the controlling of their functions special Ctrl actors, except ENV – it can do without Ctrl. Model´s maps are named the Blazons and they are able mathematically - graphically express the relationships among entities, actors and processes. In the second part of this paper, the rich blazons of DYVELOP method will be used for the discovering and modelling of the cycling cases and their phases. The blazons need live PowerPoint presentation for better comprehension of this paper mission. The crisis management of energetic crisis infrastructure organization is obliged to use the cycles for successful coping of crisis situations. Several times cycling of these cases is a necessary condition for the encompassment of the both the emergency event and the mitigation of organization´s damages. Uninterrupted and continuous cycling process bring for crisis management fruitfulness and it is a good indicator and controlling actor of organizational continuity and its sustainable development advanced possibilities. The research reliable rules are derived for the safety and reliable continuity of energetic critical infrastructure organization in the crisis situation.

Keywords: blazons, computational assistance, DYVELOP method, critical infrastructure

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Authors: Natarajan Tirupattur Srinivasan

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

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

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Authors: Ranadhir Roy

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Inverse problems arise in medical (molecular) imaging. These problems are characterized by large in three dimensions, and by the diffusion equation which models the physical phenomena within the media. The inverse problems are posed as a nonlinear optimization where the unknown parameters are found by minimizing the difference between the predicted data and the measured data. To obtain a unique and stable solution to an ill-posed inverse problem, a priori information must be used. Mathematical conditions to obtain stable solutions are established in Tikhonov’s regularization method, where the a priori information is introduced via a stabilizing functional, which may be designed to incorporate some relevant information of an inverse problem. Effective determination of the Tikhonov regularization parameter requires knowledge of the true solution, or in the case of optical imaging, the true image. Yet, in, clinically-based imaging, true image is not known. To alleviate these difficulties we have applied the penalty/modified barrier function (PMBF) method instead of Tikhonov regularization technique to make the inverse problems well-posed. Unlike the Tikhonov regularization method, the constrained optimization technique, which is based on simple bounds of the optical parameter properties of the tissue, can easily be implemented in the PMBF method. Imposing the constraints on the optical properties of the tissue explicitly restricts solution sets and can restore uniqueness. Like the Tikhonov regularization method, the PMBF method limits the size of the condition number of the Hessian matrix of the given objective function. The accuracy and the rapid convergence of the PMBF method require a good initial guess of the Lagrange multipliers. To obtain the initial guess of the multipliers, we use a least square unconstrained minimization problem. Three-dimensional images of fluorescence absorption coefficients and lifetimes were reconstructed from contact and noncontact experimentally measured data.

Keywords: constrained minimization, ill-conditioned inverse problems, Tikhonov regularization method, penalty modified barrier function method

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Authors: Ravi Ande, Mousumi Hazari

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One of the common geophysical techniques for mapping subsurface geo-electrical structures, extensive hydro-geological research, and engineering and environmental geophysics applications is the use of time domain electromagnetic (TDEM)/transient electromagnetic (TEM) soundings. A large transmitter loop for energising the ground and a small receiver loop or magnetometer for recording the transient voltage or magnetic field in the air or on the surface of the earth, with the receiver at the center of the loop or at any random point inside or outside the source loop, make up a large loop TEM system. In general, one can acquire data using one of the configurations with a large loop source, namely, with the receiver at the center point of the loop (central loop method), at an arbitrary in-loop point (in-loop method), coincident with the transmitter loop (coincidence-loop method), and at an arbitrary offset loop point (offset-loop method), respectively. Because of the mathematical simplicity associated with the expressions of EM fields, as compared to the in-loop and offset-loop systems, the central loop system (for ground surveys) and coincident loop system (for ground as well as airborne surveys) have been developed and used extensively for the exploration of mineral and geothermal resources, for mapping contaminated groundwater caused by hazardous waste and thickness of permafrost layer. Because a proper analytical expression for the TEM response over the layered earth model for the large loop TEM system does not exist, the forward problem used in this inversion scheme is first formulated in the frequency domain and then it is transformed in the time domain using Fourier cosine or sine transforms. Using the EMLCLLER algorithm, the forward computation is initially carried out in the frequency domain. As a result, the EMLCLLER modified the forward calculation scheme in NLSTCI to compute frequency domain answers before converting them to the time domain using Fourier Cosine and/or Sine transforms.

Keywords: time domain electromagnetic (TDEM), TEM system, geoelectrical sounding structure, Fourier cosine

Procedia PDF Downloads 92