Search results for: dynamic programming technique

Authors: Kang-Mo Jung

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Least squares support vector machine (LS-SVM) is a penalized regression which considers both fitting and generalization ability of a model. However, the squared loss function is very sensitive to even single outlier. We proposed a weighted absolute deviation loss function for the robustness of the estimates in least absolute deviation support vector machine. The proposed estimates can be obtained by a quadratic programming algorithm. Numerical experiments on simulated datasets show that the proposed algorithm is competitive in view of robustness to outliers.

Keywords: least absolute deviation, quadratic programming, robustness, support vector machine, weight

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Authors: Gkolfo I. Smani, Vasileios Megalooikonomou

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Social influence and influence diffusion have been studied in social networks. However, most existing tasks on this subject focus on static networks. In this paper, the problem of maximizing influence diffusion in dynamic social networks, i.e., the case of networks that change over time, is studied. The DM algorithm is an extension of the MATI algorithm and solves the influence maximization (IM) problem in dynamic networks and is proposed under the linear threshold (LT) and independent cascade (IC) models. Experimental results show that our proposed algorithm achieves a diffusion performance better by 1.5 times than several state-of-the-art algorithms and comparable results in diffusion scale with the Greedy algorithm. Also, the proposed algorithm is 2.4 times faster than previous methods.

Keywords: influence maximization, dynamic social networks, diffusion, social influence, graphs

Procedia PDF Downloads 238

Authors: Trupti Diwan

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Predicting student failure at school has changed into a difficult challenge due to both the large number of factors that can affect the reduced performance of students and the imbalanced nature of these kinds of data sets. This paper surveys the two elements needed to make prediction on Students’ Academic Performances which are parameters and methods. This paper also proposes a framework for predicting the performance of engineering students. Genetic programming can be used to predict student failure/success. Ranking algorithm is used to rank students according to their credit points. The framework can be used as a basis for the system implementation & prediction of students’ Academic Performance in Higher Learning Institute.

Keywords: classification, educational data mining, student failure, grammar-based genetic programming

Procedia PDF Downloads 422

Authors: Adhinarayanan Venkatasubramanian

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For design of high speed digital circuit wave pipeline is the best approach this can be operated at higher operating frequencies by adjusting clock periods and skews so as latch the o/p of combinational logic circuit at the stable period. In this paper, there are two methods are proposed in automation task one is BIST (Built in self test) and second method is Reconfigurable technique. For the above two approaches dedicated AND gate (multiplier) by applying wave pipeline technique. BIST approach is implemented by Xilinx Spartan-II device. In reconfigurable technique done by ASIC. From the results, wave pipeline circuits are faster than nonpipeline circuit and area, power dissipation are reduced by reconfigurable technique.

Keywords: SOC, wave-pipelining, FPGA, self-testing, reconfigurable, ASIC

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Authors: Tabassum Husain, Shen Peng Li, Zhaolin Chen

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This paper evaluates the usability of 3D Guided Image Filtering to enhance the quality of short-time binned dynamic PET images by using MRI images. Guided image filtering is an edge-preserving filter proposed to enhance 2D images. The 3D filter is applied on 1 and 5-minute binned images. The results are compared with 15-minute binned images and the Gaussian filtering. The guided image filter enhances the quality of dynamic PET images while also preserving important information of the voxels.

Keywords: dynamic PET images, guided image filter, image enhancement, information preservation filtering

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Authors: N. Dumitru, S. Dumitru, C. Copilusi, N. Ploscaru

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On this research, experimental analyses have been performed in order to determine the oil pump mechanism dynamics and stability from an oil unit mechanical structure. The experimental tests were focused on the vibrations which occur inside of the rod element during functionality of the oil pump unit. The oil pump mechanism dynamic parameters were measured and also determined through numerical computations. Entire research is based on the oil pump unit mechanical system virtual prototyping. For a complete analysis of the mechanism, the frequency dynamic response was identified, mainly for the mechanism driven element, based on two methods: processing and virtual simulations with MSC Adams aid and experimental analysis. In fact, through this research, a complete methodology is presented where numerical simulations of a mechanism with deformed elements are developed on a dynamic mode and these can be correlated with experimental tests.

Keywords: modal dynamic analysis, oil pump, vibrations, flexible elements, frequency response

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Authors: Galu Papy Yuma

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This paper presents a new dynamic simulation of a power system consisting of four machines equipped with the Generalized Unified Power Flow Controller (GUPFC) to improve power system stability. The dynamic simulation of the GUPFC consists of one shunt converter and two series converters based on voltage source converter, and DC link capacitor installed in the power system. MATLAB/Simulink is used to arrange the dynamic simulation of the GUPFC, where the power system is simulated in order to investigate the impact of the controller on power system oscillation damping and to show the simulation program reliability. The Improved Chaotic- Harmony Search (IC-HS) Algorithm is used to provide the parameter controller in order to lead-lag compensation design. The results obtained by simulation show that the power system with four machines is suitable for stability analysis. The use of GUPFC and IC-HS Algorithm provides the excellent capability in fast damping of power system oscillations and improve greatly the dynamic stability of the power system.

Keywords: GUPFC, IC-HS algorithm, Matlab/Simulink, damping oscillation

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Authors: Aouaouche Elmaouhab, Hassina Beggar

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Solving multi-objective discrete optimization applications has always been limited by the resources of one machine: By computing power or by memory, most often both. To speed up the calculations, the grid computing represents a primary solution for the treatment of these applications through the parallelization of these resolution methods. In this work, we are interested in the study of some methods for solving multiple objective integer linear programming problem based on Branch-and-Bound and the study of grid computing technology. This study allowed us to propose an implementation of the method of Abbas and Al on the grid by reducing the execution time. To enhance our contribution, the main results are presented.

Keywords: multi-objective optimization, integer linear programming, grid computing, parallel computing

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Authors: Albert K. Chong, Jasim Ahmed Ali Al-Baghdadi, Peter B. Milburn

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Precise capture of plantar 3D surface of the foot at the loading gait phases on rigid substrate was found to be valuable for the assessment of the physiology, health and problems of the feet. Photogrammetry, a precision 3D spatial data capture technique is suitable for this type of dynamic application. In this research, the technique is utilised to study of the effect on the plantar deformation for having a strip of kinesiology tape on the plantar surface while going through the loading phase of gait. For this pilot study, one healthy adult male subject was recruited under the USQ University human research ethics guidelines for this preliminary study. The 3D plantar deformation data of both with and without applying the tape were analysed. The results and analyses are presented together with the detail of the findings.

Keywords: gait, human plantar, plantar loading, photogrammetry, kinesiology tape

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Authors: Amar Khoukhi, Mohamed Shahab

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This paper presents the optimal control problem of mobile robot motion as a nonlinear programming problem (NLP) and solved using a direct method of numerical optimal control. The NLP is initialized with a B-Spline for which node locations are optimized using a genetic search. The system acceleration inputs and sampling periods are considered as optimization variables. Different scenarios with different objectives weights are implemented and investigated. Interesting results are found in terms of complying with the expected behavior of a mobile robot system and time-energy minimization.

Keywords: multi-objective control, non-holonomic systems, mobile robots, nonlinear programming, motion planning, B-spline, genetic algorithm

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Authors: Ali Mohammadi

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Every construction that is done, the most important part of attention for employers and contractors is its cost, and they always try to reduce costs so that they can compete in the market, so they estimate the cost of construction before starting their activities. The costs can be generally divided into four parts: the materials used, the equipment used, the manpower required, and the time required. In this article, we are trying to talk about the three items of equipment, manpower, and time, and examine how the use of apps can reduce the cost of construction, while due to various reasons, it has received less attention in the field of app design. Also, because we intend to use these apps in construction and they are used by engineers and experts, we define these apps as engineering apps because the idea of ​​their design must be by an engineer who works in that field. Also, considering that most engineers are familiar with programming during their studies, they can design the apps they need using simple programming software.

Keywords: layout, as-bilt, monitoring, maps

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Authors: Vinayak Bassi, Rajpreet Singh

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Over the years, with the emergence of sophisticated computers and algorithms, finance has been quantified using computational prowess. Asset valuation has been one of the key components of quantitative finance. In fact, it has become one of the embryonic steps in determining risk related to a portfolio, the main goal of quantitative finance. This study comprises a drawing comparison between valuation output generated by two stochastic dynamic models, namely Black-Scholes and Dupire’s bi-dimensionality model. Both of these models are formulated for computing the valuation function for a portfolio of European options using Monte Carlo simulation methods. Although Monte Carlo algorithms have a slower convergence rate than calculus-based simulation techniques (like FDM), they work quite effectively over high-dimensional dynamic models. A fidelity gap is analyzed between the static (historical) and stochastic inputs for a sample portfolio of underlying assets. In order to enhance the performance efficiency of the model, the study emphasized the use of variable reduction methods and customizing random number generators to implement parallelization. An attempt has been made to further implement the Dupire’s model on a GPU to achieve higher computational performance. Furthermore, ideas have been discussed around the performance enhancement and bottleneck identification related to the implementation of options-pricing models on GPUs.

Keywords: monte carlo, stochastic models, computational finance, parallel programming, scientific computing

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Authors: Ahmed Guerine, Ali El Hafidi, Bruno Martin, Philippe Leclaire

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This paper investigates the nonlinear dynamic response of a mechanical torque limiter which is used to protect drive parts from overload (helical transmission gears). The system is driven by four excitations: two external excitations (aerodynamics torque and force) and two internal excitations (two mesh stiffness fluctuations). In this work, we develop a dynamic model with lumped components and 28 degrees of freedom. We use the Runge Kutta step-by-step time integration numerical algorithm to solve the equations of motion obtained by Lagrange formalism. The numerical results have allowed us to identify the sources of vibration in the wind turbine. Also, they are useful to help the designer to make the right design and correctly choose the times for maintenance.

Keywords: two-stage helical gear, lumped model, dynamic response, torque-limiter

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Authors: Osama Terra, Hatem Hussein

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Calibration of Optical Time Domain Reflectometer (OTDR) is crucial for the accurate determination of loss budget for long optical fiber links. In this paper, the calibration of the attenuation scale of an OTDR using two different techniques is discussed and implemented. The first technique is the external modulation method (EM). A setup is proposed to calibrate an OTDR over a dynamic range of around 15 dB based on the EM method. Afterwards, the OTDR is calibrated using two standard reference fibers (SRF). Both SRF are calibrated using cut-back technique; one of them is calibrated at our home institute (the National Institute of Standards – NIS) while the other at the National Physical Laboratory (NPL) of the United Kingdom to confirm our results. In addition, the parameters contributing the calibration uncertainty are thoroughly investigated. Although the EM method has several advantages over the SRF method, the uncertainties in the SRF method is found to surpass that of the EM method.

Keywords: optical time domain reflectometer, fiber attenuation measurement, OTDR calibration, external source method

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Authors: Gong Kangming, Zhao Caiqi

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High-rise special-shaped structure, such as main frame structure of the statues, is one of the structure forms in irregular structure widely used. Due to the complex shape of the statue structure, with a large aspect ratio, its wind load value and the overall mechanical properties are very different from the high-rise buildings with the general rules. The paper taking a certain 48 meters high main frame structure of the statue located in Shuangyashan City, Heilongjiang Province, static and dynamic properties are analyzed by the finite element software. Through static and dynamic analysis, it got a number of useful conclusions that have a certain reference value for the analysis and design of the future similar structure.

Keywords: a Buddhism goddess Guanyin body, wind load, dynamic analysis, bolster, node design

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Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a new hybrid Hopfield neural network is proposed for the dynamic, flexible job shop scheduling problem. A new heuristic based and easy to implement energy function is designed for the Hopfield neural network, which penalizes the constraints violation and decreases makespan. Moreover, for enhancing the performance, several heuristics are integrated to it that achieve active, and non-delay schedules also, prevent early convergence of the neural network. The suggested algorithm that is designed as a generalization of the previous studies for the flexible and dynamic scheduling problems can be used for solving real scheduling problems. Comparison of the presented hybrid method results with the previous studies results proves its efficiency.

Keywords: dynamic flexible job shop scheduling, neural network, heuristics, constrained optimization

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Authors: Abidemi C. Adegboye, Nosakhare Ikponmwosa, Rogers A. Akinsokeji

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For many resource-rich developing countries, fiscal policy has become a key tool used for short-run fiscal management since it is considered as playing a critical role in injecting part of resource rents into the economies. However, given its instability, reliance on revenue from commodity exports renders fiscal management, budgetary planning and the efficient use of public resources difficult. In this study, the linkage between commodity prices and fiscal operations among a sample of commodity-exporting countries in sub-Saharan Africa (SSA) is investigated. The main question is whether commodity price fluctuations affects the effectiveness of fiscal policy as a macroeconomic stabilization tool in these countries. Fiscal management effectiveness is considered as the ability of fiscal policy to react countercyclically to output gaps in the economy. Fiscal policy is measured as the ratio of fiscal deficit to GDP and the ratio of government spending to GDP, output gap is measured as a Hodrick-Prescott filter of output growth for each country, while commodity prices are associated with each country based on its main export commodity. Given the dynamic nature of fiscal policy effects on the economy overtime, a dynamic framework is devised for the empirical analysis. The panel cointegration and error correction methodology is used to explain the relationships. In particular, the study employs the panel ECM technique to trace short-term effects of commodity prices on fiscal management and also uses the fully modified OLS (FMOLS) technique to determine the long run relationships. These procedures provide sufficient estimation of the dynamic effects of commodity prices on fiscal policy. Data used cover the period 1992 to 2016 for 11 SSA countries. The study finds that the elasticity of the fiscal policy measures with respect to the output gap is significant and positive, suggesting that fiscal policy is actually procyclical among the countries in the sample. This implies that fiscal management for these countries follows the trend of economic performance. Moreover, it is found that fiscal policy has not performed well in delivering macroeconomic stabilization for these countries. The difficulty in applying fiscal stabilization measures is attributable to the unstable revenue inflows due to the highly volatile nature of commodity prices in the international market. For commodity-exporting countries in SSA to improve fiscal management, therefore, fiscal planning should be largely decoupled from commodity revenues, domestic revenue bases must be improved, and longer period perspectives in fiscal policy management are the critical suggestions in this study.

Keywords: commodity prices, ECM, fiscal policy, fiscal procyclicality, fully modified OLS, sub-saharan africa

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Authors: Panprapa Yongtrakul, Punyaphat Sirithanabadeekul, Pakjira Siriphan

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Background: The thread lift technique has become popular because it is less invasive, requires a shorter operation, less downtime, and results in fewer postoperative complications. The advantage of the technique is that the thread can be inserted under the skin without the need for long incisions. Currently, there are a lot of thread lift techniques with respect to the specific types of thread used on specific areas, such as the mid-face, lower face, or neck area. Objective: To review the thread lift technique for specific areas according to type of thread, patient selection, and how to match the most appropriate to the patient. Materials and Methods: A literature review technique was conducted by searching PubMed and MEDLINE, then compiled and summarized. Result: We have divided our protocols into two sections: Protocols for short suture, and protocols for long suture techniques. We also created 3D pictures for each technique to enhance understanding and application in a clinical setting. Conclusion: There are advantages and disadvantages to short suture and long suture techniques. The best outcome for each patient depends on appropriate patient selection and determining the most suitable technique for the defect and area of patient concern.

Keywords: thread lift, thread lift method, thread lift technique, thread lift procedure, threading

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Authors: Noppadon Sintuboon, Benjamas Sawatdipong, Anchalee Kongsuk

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This study was conducted to investigate the engineering parameters: compressional wave: Vp, shear wave: Vs, and density: ρ related to the dynamically geotechnical properties of soils compaction in the core of earth-filled dam located in northern part of Thailand by using multichannel analysis of surface wave (MASW) techniques. The Vp, Vs, and ρ from MASW were 1,624 - 1,649 m/s, 301-323 m/s, and 1,829 kg/m3, respectively. Those parameters were calculated to Poison’s ratio: ν (0.48), shear modulus: G (1.66 x 108 - 1.92 x 108 kg/m2), Vp/Vs ratio (5.10 – 5.39) and Standard Penetration Test (SPT) showing the dynamic characteristics of soil deformation and stress resulting from dynamic loads. The results of this study will be useful in primary evaluating the current condition and foundation of the dam and can be compared to the data from the laboratory in the future.

Keywords: earth-filled dam, MASW, dynamic elastic constant, shear wave

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Authors: Marita Heyns

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Job insecurity is a distressing phenomenon which has far reaching consequences for both employees and their organizations. Previously, much attention has been given to the link between job insecurity and individual level performance outcomes, while less is known about how subjectively perceived job insecurity might transfer beyond the individual level to affect performance of the organization on an aggregated level. Research focusing on how employees’ fear of job loss might affect the organization’s ability to respond proactively to volatility and drastic change through applying its capabilities of sensing, seizing, and reconfiguring, appears to be practically non-existent. Equally little is known about the potential underlying mechanisms through which job insecurity might affect the dynamic capabilities of an organization. This study examines how job insecurity might affect dynamic organizational capability through trust as an underling process. More specifically, it considered the simultaneous roles of trust at an impersonal (organizational) level as well as trust at an interpersonal level (in leaders and co-workers) as potential underlying mechanisms through which job insecurity might affect the organization’s dynamic capability to respond to opportunities and imminent, drastic change. A quantitative research approach and a stratified random sampling technique enabled the collection of data among 314 managers at four different plant sites of a large South African steel manufacturing organization undergoing dramatic changes. To assess the study hypotheses, the following statistical procedures were employed: Structural equation modelling was performed in Mplus to evaluate the measurement and structural models. The Chi-square values test for absolute fit as well as alternative fit indexes such as the Comparative Fit Index and the Tucker-Lewis Index, the Root Mean Square Error of Approximation and the Standardized Root Mean Square Residual were used as indicators of model fit. Composite reliabilities were calculated to evaluate the reliability of the factors. Finally, interaction effects were tested by using PROCESS and the construction of two-sided 95% confidence intervals. The findings indicate that job insecurity had a lower-than-expected detrimental effect on evaluations of the organization’s dynamic capability through the conducive buffering effects of trust in the organization and in its leaders respectively. In contrast, trust in colleagues did not seem to have any noticeable facilitative effect. The study proposes that both job insecurity and dynamic capability can be managed more effectively by also paying attention to factors that could promote trust in the organization and its leaders; some practical recommendations are given in this regard.

Keywords: dynamic organizational capability, impersonal trust, interpersonal trust, job insecurity

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Authors: K. -H. Yang

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Supplier selection problem is one of the important issues of supply chain problems. Two categories of methodologies include qualitative and quantitative approaches which can be applied to supplier selection problems. However, due to the complexities of the problem and lacking of reliable and quantitative data, qualitative approaches are more than quantitative approaches. This study considers operational cost and supplier’s reliability factor and solves the problem by using a quantitative approach. A mixed integer programming model is the primary analytic tool. Analyses of different scenarios with variable cost and reliability structures show that the effectiveness of this approach to the supplier selection problem.

Keywords: mixed integer programming, quantitative approach, supplier’s reliability, supplier selection

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Authors: L. Al-Mulla, B. M. Thomas, N. R. Bhat, M. K. Suleiman, P. George

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Mangroves are halophytic shrubs habituated in the intertidal zones in the tropics and subtropics, forming a complex and highly dynamic coastal ecosystem. Historical evidence indicating the existence followed by the extinction of mangrove in Kuwait; hence, continuous projects have been established to reintroduce this plant to the marine ecosystem. One of the major challenges in establishing large-scale mangrove plantations in Kuwait is the very high rate of seedling mortality, which should ideally be less than 20%. This study was conducted at three selected locations in the Kuwait bay during 2016-2017, to evaluate the effect of four planting techniques on mangrove seedling establishment. Coir-pillow planting technique, comp-mat planting technique, and anchored container planting technique were compared with the conventional planting method. The study revealed that the planting techniques significantly affected the establishment of mangrove seedlings in the initial stages of growth. Location-specific difference in seedling establishment was also observed during the course of the study. However, irrespective of the planting techniques employed, high seedling mortality was observed in all the planting locations towards the end of the study; which may be attributed to the physicochemical characteristics of the mudflats selected.

Keywords: Avicennia marina (Forsk.) Vierh, coastal pollution, heavy metal accumulation, marine ecosystem, sedimentation, tidal inundation

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Authors: Alexandru-Ion Marinescu

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There exist a plethora of methods in the scientific literature which tackle the well-established task of credit score evaluation. In its most abstract form, a credit scoring algorithm takes as input several credit applicant properties, such as age, marital status, employment status, loan duration, etc. and must output a binary response variable (i.e. “GOOD” or “BAD”) stating whether the client is susceptible to payment return delays. Data imbalance is a common occurrence among financial institution databases, with the majority being classified as “GOOD” clients (clients that respect the loan return calendar) alongside a small percentage of “BAD” clients. But it is the “BAD” clients we are interested in since accurately predicting their behavior is crucial in preventing unwanted loss for loan providers. We add to this whole context the constraint that the algorithm must yield an actual, tractable mathematical formula, which is friendlier towards financial analysts. To this end, we have turned to genetic algorithms and genetic programming, aiming to evolve actual mathematical expressions using specially tailored mutation and crossover operators. As far as data representation is concerned, we employ a very flexible mechanism – LINQ expression trees, readily available in the C# programming language, enabling us to construct executable pieces of code at runtime. As the title implies, they model trees, with intermediate nodes being operators (addition, subtraction, multiplication, division) or mathematical functions (sin, cos, abs, round, etc.) and leaf nodes storing either constants or variables. There is a one-to-one correspondence between the client properties and the formula variables. The mutation and crossover operators work on a flattened version of the tree, obtained via a pre-order traversal. A consequence of our chosen technique is that we can identify and discard client properties which do not take part in the final score evaluation, effectively acting as a dimensionality reduction scheme. We compare ourselves with state of the art approaches, such as support vector machines, Bayesian networks, and extreme learning machines, to name a few. The data sets we benchmark against amount to a total of 8, of which we mention the well-known Australian credit and German credit data sets, and the performance indicators are the following: percentage correctly classified, area under curve, partial Gini index, H-measure, Brier score and Kolmogorov-Smirnov statistic, respectively. Finally, we obtain encouraging results, which, although placing us in the lower half of the hierarchy, drive us to further refine the algorithm.

Keywords: expression trees, financial credit scoring, genetic algorithm, genetic programming, symbolic evolution

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Authors: Genady Grabarnik, Serge Yaskolko

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Generative Artificial Intelligence (AI) has significantly expanded its applicability with the incorporation of Large Language Models (LLMs) and become a technology with promise to automate some areas that were very difficult to automate before. The paper describes the introduction of generative Artificial Intelligence into Introductory Computer and Data Science courses and analysis of effect of such introduction. The generative Artificial Intelligence is incorporated in the educational process two-fold: For the instructors, we create templates of prompts for generation of tasks, and grading of the students work, including feedback on the submitted assignments. For the students, we introduce them to basic prompt engineering, which in turn will be used for generation of test cases based on description of the problems, generating code snippets for the single block complexity programming, and partitioning into such blocks of an average size complexity programming. The above-mentioned classes are run using Large Language Models, and feedback from instructors and students and courses’ outcomes are collected. The analysis shows statistically significant positive effect and preference of both stakeholders.

Keywords: introductory computer and data science education, generative AI, large language models, application of LLMS to computer and data science education

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Authors: Min Dai, Hong Liu, Shuaijie Qian

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We study a portfolio selection problem of an investor who faces constraints on rebalancing frequency, which is common in pension fund investment. We formulate it as a multiple optimal stopping problem and utilize the dynamic programming principle. By numerically solving the corresponding Hamilton-Jacobi-Bellman (HJB) equation, we find a series of free boundaries characterizing optimal strategy, and the constraints significantly impact the optimal strategy. Even in the absence of transaction costs, there is a no-trading region, depending on the number of the remaining trading chances. We also find that the equivalent wealth loss caused by the constraints is large. In conclusion, our model clarifies the impact of the constraints on transaction frequency on the optimal strategy.

Keywords: portfolio selection, rebalancing frequency, optimal strategy, free boundary, optimal stopping

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Authors: Fairouz Fakhfakh, Hatem Hadj Kacem, Ahmed Hadj Kacem

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Cloud computing offers a new model of service provisioning for workflow applications, thanks to its elasticity and its paying model. However, it presents various challenges that need to be addressed in order to be efficiently utilized. The resources provisioning problem for workflow applications has been widely studied. Nevertheless, the existing works did not consider the change in workflow instances while they are being executed. This functionality has become a major requirement to deal with unusual situations and evolution. This paper presents a first step towards the resources provisioning for a dynamic workflow. In fact, we propose a provisioning algorithm which minimizes the overall workflow execution cost, while meeting a deadline constraint. Then, we extend it to support the dynamic adding of tasks. Experimental results show that our proposed heuristic demonstrates a significant reduction in resources cost by using a consolidation process.

Keywords: cloud computing, resources provisioning, dynamic workflow, workflow applications

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Authors: Amirhossein Khazali, Mohsen Kalantar

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Energy storage units can play an important role to provide an economic and secure operation of future energy systems. In this paper, a stochastic energy and reserve market clearing scheme is presented considering storage energy units. The approach is proposed to deal with stochastic and non-dispatchable renewable sources with a high level of penetration in the energy system. A two stage stochastic programming scheme is formulated where in the first stage the energy market is cleared according to the forecasted amount of wind generation and demands and in the second stage the real time market is solved according to the assumed scenarios.

Keywords: energy and reserve market, energy storage device, stochastic programming, wind generation

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Authors: Bharath R., Tharun Sai N., Bhuvan G.

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This project focuses on developing a Parallel Computing method aimed at optimizing matrix multiplication through GPU acceleration. Addressing algorithmic challenges, GPU programming intricacies, and integration issues, the project aims to enhance efficiency and scalability. The methodology involves algorithm design, GPU programming, and optimization techniques. Future plans include advanced optimizations, extended functionality, and integration with high-level frameworks. User engagement is emphasized through user-friendly interfaces, open- source collaboration, and continuous refinement based on feedback. The project's impact extends to significantly improving matrix multiplication performance in scientific computing and machine learning applications.

Keywords: matrix multiplication, parallel processing, cuda, performance boost, neural networks

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Authors: Alireza Nikbakht Shahbazi, Emadeddin Shirali

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Since optimization issues of water resources are complicated due to the variety of decision making criteria and objective functions, it is sometimes impossible to resolve them through regular optimization methods or, it is time or money consuming. Therefore, the use of modern tools and methods is inevitable in resolving such problems. An accurate and essential utilization policy has to be determined in order to use natural resources such as water reservoirs optimally. Water reservoir programming studies aim to determine the final cultivated land area based on predefined agricultural models and water requirements. Dam utilization rule curve is also provided in such studies. The basic information applied in water reservoir programming studies generally include meteorological, hydrological, agricultural and water reservoir related data, and the geometric characteristics of the reservoir. The system of Dez dam water resources was simulated applying the basic information in order to determine the capability of its reservoir to provide the objectives of the performed plan. As a meta-exploratory method, genetic algorithm was applied in order to provide utilization rule curves (intersecting the reservoir volume). MATLAB software was used in order to resolve the foresaid model. Rule curves were firstly obtained through genetic algorithm. Then the significance of using rule curves and the decrease in decision making variables in the system was determined through system simulation and comparing the results with optimization results (Standard Operating Procedure). One of the most essential issues in optimization of a complicated water resource system is the increasing number of variables. Therefore a lot of time is required to find an optimum answer and in some cases, no desirable result is obtained. In this research, intersecting the reservoir volume has been applied as a modern model in order to reduce the number of variables. Water reservoir programming studies has been performed based on basic information, general hypotheses and standards and applying monthly simulation technique for a statistical period of 30 years. Results indicated that application of rule curve prevents the extreme shortages and decrease the monthly shortages.

Keywords: optimization, rule curve, genetic algorithm method, Dez dam reservoir

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Authors: José Neves, M. Rosário Martins, Fátima Candeias, Diana Ferreira, Sílvia Arantes, Júlio Cruz-Morais, Guida Gomes, Joaquim Macedo, António Abelha, Henrique Vicente

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Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

Keywords: artificial neuronal networks, essential oils, knowledge representation and reasoning, logic programming, Schinus molle L., Schinus terebinthifolius Raddi

Procedia PDF Downloads 542