Search results for: linearly constrained minimum variance
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3525

Search results for: linearly constrained minimum variance

3525 Efficient Antenna Array Beamforming with Robustness against Random Steering Mismatch

Authors: Ju-Hong Lee, Ching-Wei Liao, Kun-Che Lee

Abstract:

This paper deals with the problem of using antenna sensors for adaptive beamforming in the presence of random steering mismatch. We present an efficient adaptive array beamformer with robustness to deal with the considered problem. The robustness of the proposed beamformer comes from the efficient designation of the steering vector. Using the received array data vector, we construct an appropriate correlation matrix associated with the received array data vector and a correlation matrix associated with signal sources. Then, the eigenvector associated with the largest eigenvalue of the constructed signal correlation matrix is designated as an appropriate estimate of the steering vector. Finally, the adaptive weight vector required for adaptive beamforming is obtained by using the estimated steering vector and the constructed correlation matrix of the array data vector. Simulation results confirm the effectiveness of the proposed method.

Keywords: adaptive beamforming, antenna array, linearly constrained minimum variance, robustness, steering vector

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3524 Wind Turbine Control Performance Evaluation Based on Minimum-Variance Principles

Authors: Zheming Cao

Abstract:

Control loops are the most important components in the wind turbine system. Product quality, operation safety, and the economic performance are directly or indirectly connected to the performance of control systems. This paper proposed a performance evaluation method based on minimum-variance for wind turbine control system. This method can be applied on PID controller for pitch control system in the wind turbine. The good performance result demonstrated in the paper was achieved by retuning and optimizing the controller settings based on the evaluation result. The concepts presented in this paper are illustrated with the actual data of the industrial wind farm.

Keywords: control performance, evaluation, minimum-variance, wind turbine

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3523 A Comparative Analysis of Global Minimum Variance and Naïve Portfolios: Performance across Stock Market Indices and Selected Economic Regimes Using Various Risk-Return Metrics

Authors: Lynmar M. Didal, Ramises G. Manzano Jr., Jacque Bon-Isaac C. Aboy

Abstract:

This study analyzes the performance of global minimum variance and naive portfolios across different economic periods, using monthly stock returns from the Philippine Stock Exchange Index (PSEI), S&P 500, and Dow Jones Industrial Average (DOW). The performance is evaluated through the Sharpe ratio, Sortino ratio, Jensen’s Alpha, Treynor ratio, and Information ratio. Additionally, the study investigates the impact of short selling on portfolio performance. Six-time periods are defined for analysis, encompassing events such as the global financial crisis and the COVID-19 pandemic. Findings indicate that the Naive portfolio generally outperforms the GMV portfolio in the S&P 500, signifying higher returns with increased volatility. Conversely, in the PSEI and DOW, the GMV portfolio shows more efficient risk-adjusted returns. Short selling significantly impacts the GMV portfolio during mid-GFC and mid-COVID periods. The study offers insights for investors, suggesting the Naive portfolio for higher risk tolerance and the GMV portfolio as a conservative alternative.

Keywords: portfolio performance, global minimum variance, naïve portfolio, risk-adjusted metrics, short-selling

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3522 Testing the Simplification Hypothesis in Constrained Language Use: An Entropy-Based Approach

Authors: Jiaxin Chen

Abstract:

Translations have been labeled as more simplified than non-translations, featuring less diversified and more frequent lexical items and simpler syntactic structures. Such simplified linguistic features have been identified in other bilingualism-influenced language varieties, including non-native and learner language use. Therefore, it has been proposed that translation could be studied within a broader framework of constrained language, and simplification is one of the universal features shared by constrained language varieties due to similar cognitive-physiological and social-interactive constraints. Yet contradicting findings have also been presented. To address this issue, this study intends to adopt Shannon’s entropy-based measures to quantify complexity in language use. Entropy measures the level of uncertainty or unpredictability in message content, and it has been adapted in linguistic studies to quantify linguistic variance, including morphological diversity and lexical richness. In this study, the complexity of lexical and syntactic choices will be captured by word-form entropy and pos-form entropy, and a comparison will be made between constrained and non-constrained language use to test the simplification hypothesis. The entropy-based method is employed because it captures both the frequency of linguistic choices and their evenness of distribution, which are unavailable when using traditional indices. Another advantage of the entropy-based measure is that it is reasonably stable across languages and thus allows for a reliable comparison among studies on different language pairs. In terms of the data for the present study, one established (CLOB) and two self-compiled corpora will be used to represent native written English and two constrained varieties (L2 written English and translated English), respectively. Each corpus consists of around 200,000 tokens. Genre (press) and text length (around 2,000 words per text) are comparable across corpora. More specifically, word-form entropy and pos-form entropy will be calculated as indicators of lexical and syntactical complexity, and ANOVA tests will be conducted to explore if there is any corpora effect. It is hypothesized that both L2 written English and translated English have lower entropy compared to non-constrained written English. The similarities and divergences between the two constrained varieties may provide indications of the constraints shared by and peculiar to each variety.

Keywords: constrained language use, entropy-based measures, lexical simplification, syntactical simplification

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3521 Combined Localization, Beamforming, and Interference Threshold Estimation in Underlay Cognitive System

Authors: Omar Nasr, Yasser Naguib, Mohamed Hafez

Abstract:

This paper aims at providing an innovative solution for blind interference threshold estimation in an underlay cognitive network to be used in adaptive beamforming by secondary user Transmitter and Receiver. For the task of threshold estimation, blind detection of modulation and SNR are used. For the sake of beamforming several localization algorithms are compared to settle on best one for cognitive environment. Beamforming algorithms as LCMV (Linear Constraint Minimum Variance) and MVDR (Minimum Variance Distortion less) are also proposed and compared. The idea of just nulling the primary user after knowledge of its location is discussed against the idea of working under interference threshold.

Keywords: cognitive radio, underlay, beamforming, MUSIC, MVDR, LCMV, threshold estimation

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3520 Virtual Dimension Analysis of Hyperspectral Imaging to Characterize a Mining Sample

Authors: L. Chevez, A. Apaza, J. Rodriguez, R. Puga, H. Loro, Juan Z. Davalos

Abstract:

Virtual Dimension (VD) procedure is used to analyze Hyperspectral Image (HIS) treatment-data in order to estimate the abundance of mineral components of a mining sample. Hyperspectral images coming from reflectance spectra (NIR region) are pre-treated using Standard Normal Variance (SNV) and Minimum Noise Fraction (MNF) methodologies. The endmember components are identified by the Simplex Growing Algorithm (SVG) and after adjusted to the reflectance spectra of reference-databases using Simulated Annealing (SA) methodology. The obtained abundance of minerals of the sample studied is very near to the ones obtained using XRD with a total relative error of 2%.

Keywords: hyperspectral imaging, minimum noise fraction, MNF, simplex growing algorithm, SGA, standard normal variance, SNV, virtual dimension, XRD

Procedia PDF Downloads 107
3519 Efficiency of Robust Heuristic Gradient Based Enumerative and Tunneling Algorithms for Constrained Integer Programming Problems

Authors: Vijaya K. Srivastava, Davide Spinello

Abstract:

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

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

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3518 The Characteristics of the Fragments from Cylindrical Casing with One of End Caps Fully Constrained

Authors: Yueguang Gao, Qi Huang, Shunshan Feng

Abstract:

In order to study the process and characteristic of the fragments in the warhead with one end cap under full constraint condition, we established a cylindrical casing with two end caps which one of which was fully constrained using the simulation analysis. The result showed that the fragmentation of cylindrical casing with one end full constrained has its own characteristic. The Mach stem was generated when the detonation wave propagated to the fully constrained end cap under the condition of one end detonation, working on unreactive explosives and causing the nearby fragment subjected to nearly 2.5 times the normal pressure to obtain a higher speed. The cylindrical casing first ruptured at the contact surface with the fully constrained end, and then at the end cover of the initiating end, and then the rupture extends to the whole cylindrical casing. The detonation products started to leak out from the rupture. Driving fragments to fly and forming two dense flying areas. The analysis of this paper can provide a reference for the optimal design of this kind of warhead.

Keywords: fragment, cylindrical casing, detonation waves, numerical simulation

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3517 Estimation of Stress-Strength Parameter for Burr Type XII Distribution Based on Progressive Type-II Censoring

Authors: A. M. Abd-Elfattah, M. H. Abu-Moussa

Abstract:

In this paper, the estimation of stress-strength parameter R = P(Y < X) is considered when X; Y the strength and stress respectively are two independent random variables of Burr Type XII distribution. The samples taken for X and Y are progressively censoring of type II. The maximum likelihood estimator (MLE) of R is obtained when the common parameter is unknown. But when the common parameter is known the MLE, uniformly minimum variance unbiased estimator (UMVUE) and the Bayes estimator of R = P(Y < X) are obtained. The exact con dence interval of R based on MLE is obtained. The performance of the proposed estimators is compared using the computer simulation.

Keywords: Burr Type XII distribution, progressive type-II censoring, stress-strength model, unbiased estimator, maximum-likelihood estimator, uniformly minimum variance unbiased estimator, confidence intervals, Bayes estimator

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3516 Stability of Canola Varieties for Oil Percent in Four Regions of Iran

Authors: Seyed Mohammad Nasir Mousavi, Amir Mashayekh, Pasha Hejazi, Sanaz Kanani Zadeh Khalkhali

Abstract:

To determine the stability of the oil percent canola varieties, an experiment was done in a randomized complete block design with four replications in four research stations of the country Shahrood, Esfahan, Kermanshah, Varamin. Analysis of variance showed that there is cultivars considerable variability in the percentage of oil. The results showed that the coefficient of variation of oil Hyola 401 and Hyola308 stability and flexibility are high. Cultivars Cooper and Likord are minimum variance Shukla that stable for the percentage of oil Based on the chart AMMI 1, cultivars Zarfam and Hyola 401 are of oil percentage than other varieties had higher stability. On the chart AMMI2, cultivars Karun and Hyola 308 are identified as stable, also location Isfahan is stable

Keywords: canola, stability, AMMI, variance Shukla

Procedia PDF Downloads 339
3515 Efficient Frontier: Comparing Different Volatility Estimators

Authors: Tea Poklepović, Zdravka Aljinović, Mario Matković

Abstract:

Modern Portfolio Theory (MPT) according to Markowitz states that investors form mean-variance efficient portfolios which maximizes their utility. Markowitz proposed the standard deviation as a simple measure for portfolio risk and the lower semi-variance as the only risk measure of interest to rational investors. This paper uses a third volatility estimator based on intraday data and compares three efficient frontiers on the Croatian Stock Market. The results show that range-based volatility estimator outperforms both mean-variance and lower semi-variance model.

Keywords: variance, lower semi-variance, range-based volatility, MPT

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3514 Assessing the Adoption of Health Information Systems in a Resource-Constrained Country: A Case of Uganda

Authors: Lubowa Samuel

Abstract:

Health information systems, often known as HIS, are critical components of the healthcare system to improve health policies and promote global health development. In a broader sense, HIS as a system integrates data collecting, processing, reporting, and making use of various types of data to improve healthcare efficacy and efficiency through better management at all levels of healthcare delivery. The aim of this study is to assess the adoption of health information systems (HIS) in a resource-constrained country drawing from the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model. The results indicate that the user's perception of the technology and the poor information technology infrastructures contribute a lot to the low adoption of HIS in resource-constrained countries.

Keywords: health information systems, resource-constrained countries, health information systems

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3513 BIASS in the Estimation of Covariance Matrices and Optimality Criteria

Authors: Juan M. Rodriguez-Diaz

Abstract:

The precision of parameter estimators in the Gaussian linear model is traditionally accounted by the variance-covariance matrix of the asymptotic distribution. However, this measure can underestimate the true variance, specially for small samples. Traditionally, optimal design theory pays attention to this variance through its relationship with the model's information matrix. For this reason it seems convenient, at least in some cases, adapt the optimality criteria in order to get the best designs for the actual variance structure, otherwise the loss in efficiency of the designs obtained with the traditional approach may be very important.

Keywords: correlated observations, information matrix, optimality criteria, variance-covariance matrix

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3512 Second Order Optimality Conditions in Nonsmooth Analysis on Riemannian Manifolds

Authors: Seyedehsomayeh Hosseini

Abstract:

Much attention has been paid over centuries to understanding and solving the problem of minimization of functions. Compared to linear programming and nonlinear unconstrained optimization problems, nonlinear constrained optimization problems are much more difficult. Since the procedure of finding an optimizer is a search based on the local information of the constraints and the objective function, it is very important to develop techniques using geometric properties of the constraints and the objective function. In fact, differential geometry provides a powerful tool to characterize and analyze these geometric properties. Thus, there is clearly a link between the techniques of optimization on manifolds and standard constrained optimization approaches. Furthermore, there are manifolds that are not defined as constrained sets in R^n an important example is the Grassmann manifolds. Hence, to solve optimization problems on these spaces, intrinsic methods are used. In a nondifferentiable problem, the gradient information of the objective function generally cannot be used to determine the direction in which the function is decreasing. Therefore, techniques of nonsmooth analysis are needed to deal with such a problem. As a manifold, in general, does not have a linear structure, the usual techniques, which are often used in nonsmooth analysis on linear spaces, cannot be applied and new techniques need to be developed. This paper presents necessary and sufficient conditions for a strict local minimum of extended real-valued, nonsmooth functions defined on Riemannian manifolds.

Keywords: Riemannian manifolds, nonsmooth optimization, lower semicontinuous functions, subdifferential

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3511 Cuckoo Search (CS) Optimization Algorithm for Solving Constrained Optimization

Authors: Sait Ali Uymaz, Gülay Tezel

Abstract:

This paper presents the comparison results on the performance of the Cuckoo Search (CS) algorithm for constrained optimization problems. For constraint handling, CS algorithm uses penalty method. CS algorithm is tested on thirteen well-known test problems and the results obtained are compared to Particle Swarm Optimization (PSO) algorithm. Mean, best, median and worst values were employed for the analyses of performance.

Keywords: cuckoo search, particle swarm optimization, constrained optimization problems, penalty method

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3510 Conservativeness of Probabilistic Constrained Optimal Control Method for Unknown Probability Distribution

Authors: Tomoaki Hashimoto

Abstract:

In recent decades, probabilistic constrained optimal control problems have attracted much attention in many research field. Although probabilistic constraints are generally intractable in an optimization problem, several tractable methods haven been proposed to handle probabilistic constraints. In most methods, probabilistic constraints are reduced to deterministic constraints that are tractable in an optimization problem. However, there is a gap between the transformed deterministic constraints in case of known and unknown probability distribution. This paper examines the conservativeness of probabilistic constrained optimization method with the unknown probability distribution. The objective of this paper is to provide a quantitative assessment of the conservatism for tractable constraints in probabilistic constrained optimization with the unknown probability distribution.

Keywords: optimal control, stochastic systems, discrete time systems, probabilistic constraints

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3509 Optical and Mechanical Characterization of Severe Plastically Deformed Copper Alloy Processed by Constrained Groove Pressing

Authors: Jaya Prasad Vanam, Vinay Anurag P, Vidya Sravya N S, Kishore Babu Nagamothu

Abstract:

Constrained Groove Pressing (CGP) is one of the severe plastic deformation technique (SPD) by which we can process Ultra Fine Grained (UFG)/plane metallic materials. This paper discusses the effects of CGP on Cu-Zn alloy specimen at room temperature. A comprehensive study is made on the structural and mechanical properties of Brass specimen before and after Constrained grooves Pressing. Entire process is simulated in AFDEX CAE Software. It is found that most of the properties are superior with respect to brass samples such as yield strength, ultimate tensile strength, hardness, strain rate, etc., and they are found to be better for the CGP processed specimen. The results are discussed with respective graphs.

Keywords: constrained groove pressing, AFDEX, ultra fine grained materials, severe plastic deformation technique

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3508 Multi-Objective Multi-Mode Resource-Constrained Project Scheduling Problem by Preemptive Fuzzy Goal Programming

Authors: Busaba Phurksaphanrat

Abstract:

This research proposes a pre-emptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of make-span. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, pre-emptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions.

Keywords: multi-mode resource constrained project scheduling problem, fuzzy set, goal programming, pre-emptive fuzzy goal programming

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3507 The Rupture Potential of Nerve Tissue Constrained Intracranial Saccular Aneurysm

Authors: M. Alam, P. Seshaiyer

Abstract:

The rupture predictability of intracranial aneurysm is one of the most important parameters for physicians in surgical treatment. As most of the intracranial aneurysms are asymptomatic, still the rupture potential of both symptomatic and asymptomatic lesions is relatively unknown. Moreover, an intracranial aneurysm constrained by a nerve tissue might be a common scenario for a physician to deal with during the treatment process. Here, we perform a computational modeling of nerve tissue constrained intracranial saccular aneurysm to show a protective role of constrained tissue on the aneurysm. A comparative parametric study of the model also performs taking long constraint, medium constraint, short constraint, point contact, narrow neck aneurysm, wide neck aneurysm as parameters for the analysis. Results show that contact constraint aneurysm generates less stress near the fundus compared to no constraint aneurysm, hence works as a protective wall for the aneurysm not to be ruptured.

Keywords: rupture potential, intracranial saccular aneurysm, anisotropic hyper-elastic material, finite element analysis

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3506 A Generalized Family of Estimators for Estimation of Unknown Population Variance in Simple Random Sampling

Authors: Saba Riaz, Syed A. Hussain

Abstract:

This paper is addressing the estimation method of the unknown population variance of the variable of interest. A new generalized class of estimators of the finite population variance has been suggested using the auxiliary information. To improve the precision of the proposed class, known population variance of the auxiliary variable has been used. Mathematical expressions for the biases and the asymptotic variances of the suggested class are derived under large sample approximation. Theoretical and numerical comparisons are made to investigate the performances of the proposed class of estimators. The empirical study reveals that the suggested class of estimators performs better than the usual estimator, classical ratio estimator, classical product estimator and classical linear regression estimator. It has also been found that the suggested class of estimators is also more efficient than some recently published estimators.

Keywords: study variable, auxiliary variable, finite population variance, bias, asymptotic variance, percent relative efficiency

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3505 Distributed Energy Storage as a Potential Solution to Electrical Network Variance

Authors: V. Rao, A. Bedford

Abstract:

As the efficient performance of national grid becomes increasingly important to maintain the electrical network stability, the balance between the generation and the demand must be effectively maintained. To do this, any losses that occur in the power network must be reduced by compensating for it. In this paper, one of the main cause for the losses in the network is identified as the variance, which hinders the grid’s power carrying capacity. The reason for the variance in the grid is investigated and identified as the rise in the integration of renewable energy sources (RES) such as wind and solar power. The intermittent nature of these RES along with fluctuating demands gives rise to variance in the electrical network. The losses that occur during this process is estimated by analyzing the network’s power profiles. Whilst researchers have identified different ways to tackle this problem, little consideration is given to energy storage. This paper seeks to redress this by considering the role of energy storage systems as potential solutions to reduce variance in the network. The implementation of suitable energy storage systems based on different applications is presented in this paper as part of variance reduction method and thus contribute towards maintaining a stable and efficient grid operation.

Keywords: energy storage, electrical losses, national grid, renewable energy, variance

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3504 Portfolio Risk Management Using Quantum Annealing

Authors: Thomas Doutre, Emmanuel De Meric De Bellefon

Abstract:

This paper describes the application of local-search metaheuristic quantum annealing to portfolio opti- mization. Heuristic technics are particularly handy when Markowitz’ classical Mean-Variance problem is enriched with additional realistic constraints. Once tailored to the problem, computational experiments on real collected data have shown the superiority of quantum annealing over simulated annealing for this constrained optimization problem, taking advantages of quantum effects such as tunnelling.

Keywords: optimization, portfolio risk management, quantum annealing, metaheuristic

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3503 Irreducible Sign Patterns of Minimum Rank of 3 and Symmetric Sign Patterns That Allow Diagonalizability

Authors: Sriparna Bandopadhyay

Abstract:

It is known that irreducible sign patterns in general may not allow diagonalizability and in particular irreducible sign patterns with minimum rank greater than or equal to 4. It is also known that every irreducible sign pattern matrix with minimum rank of 2 allow diagonalizability with rank of 2 and the maximum rank of the sign pattern. In general sign patterns with minimum rank of 3 may not allow diagonalizability if the condition of irreducibility is dropped, but the problem of whether every irreducible sign pattern with minimum rank of 3 allows diagonalizability remains open. In this paper it is shown that irreducible sign patterns with minimum rank of 3 under certain conditions on the underlying graph allow diagonalizability. An alternate proof of the results that every sign pattern matrix with minimum rank of 2 and no zero lines allow diagonalizability with rank of 2 and also that every full sign pattern allows diagonalizability with all permissible ranks of the sign pattern is given. Some open problems regarding composite cycles in an irreducible symmetric sign pattern that support of a rank principal certificate are also answered.

Keywords: irreducible sign patterns, minimum rank, symmetric sign patterns, rank -principal certificate, allowing diagonalizability

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3502 Analysis of Temporal Factors Influencing Minimum Dwell Time Distributions

Authors: T. Pedersen, A. Lindfeldt

Abstract:

The minimum dwell time is an important part of railway timetable planning. Due to its stochastic behaviour, the minimum dwell time should be considered to create resilient timetables. While there has been significant focus on how to determine and estimate dwell times, to our knowledge, little research has been carried out regarding temporal and running direction variations of these. In this paper, we examine how the minimum dwell time varies depending on temporal factors such as the time of day, day of the week and time of the year. We also examine how it is affected by running direction and station type. The minimum dwell time is estimated by means of track occupation data. A method is proposed to ensure that only minimum dwell times and not planned dwell times are acquired from the track occupation data. The results show that on an aggregated level, the average minimum dwell times in both running directions at a station are similar. However, when temporal factors are considered, there are significant variations. The minimum dwell time varies throughout the day with peak hours having the longest dwell times. It is also found that the minimum dwell times are influenced by weekday, and in particular, weekends are found to have lower minimum dwell times than most other days. The findings show that there is a potential to significantly improve timetable planning by taking minimum dwell time variations into account.

Keywords: minimum dwell time, operations quality, timetable planning, track occupation data

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3501 Impact of Increasing Distributed Solar PV Systems on Distribution Networks in South Africa

Authors: Aradhna Pandarum

Abstract:

South Africa is experiencing an exponential growth of distributed solar PV installations. This is due to various factors with the predominant one being increasing electricity tariffs along with decreasing installation costs, resulting in attractive business cases to some end-users. Despite there being a variety of economic and environmental advantages associated with the installation of PV, their potential impact on distribution grids has yet to be thoroughly investigated. This is especially true since the locations of these units cannot be controlled by Network Service Providers (NSPs) and their output power is stochastic and non-dispatchable. This report details two case studies that were completed to determine the possible voltage and technical losses impact of increasing PV penetration in the Northern Cape of South Africa. Some major impacts considered for the simulations were ramping of PV generation due to intermittency caused by moving clouds, the size and overall hosting capacity and the location of the systems. The main finding is that the technical impact is different on a constrained feeder vs a non-constrained feeder. The acceptable PV penetration level is much lower for a constrained feeder than a non-constrained feeder, depending on where the systems are located.

Keywords: medium voltage networks, power system losses, power system voltage, solar photovoltaic

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3500 Effects of Tillage and Crop Residues Management in Improving Rainfall-Use Efficiency in Dryland Crops under Sandy Soils

Authors: Cosmas Parwada, Ronald Mandumbu, Handseni Tibugari, Trust Chinyama

Abstract:

A 3-yr field experiment to evaluate effects of tillage and residue management on soil water storage (SWS), grain yield, harvest index (HI) and water use efficiency (WUE) of sorghum was done in sandy soils. Treatments were conventional (CT) and minimum (MT) tillage without residue retention and conventional (CT × RT) and minimum (MT × RT) tillage with residue retention. Change in SWS was higher under CT and MT than in CT × RT and MT × RT, especially in the 0-10 cm soil layer. Grain yield and HI were significantly (P < 0.05) lower in CT and MT than CT × RT and MT × RT. Grain yield and HI were significantly (P < 0.05) positively correlated to WUE but WUE significantly (P < 0.05) negatively correlated to sand (%) particle content. The SWS was lower in winter but higher in summer and was significantly correlated to soil organic carbon (SOC), sand (%), grain yield (t/ha), HI and WUE. The WUE linearly increasing from first to last cropping seasons in tillage with returned residues; higher in CT × RT and MT × RT that promoted SOC buildup than where crop residues were removed. Soil tillage decreased effects of residues on SWS, WUE, grain yield and HI. Minimum tillage coupled to residue retention sustainably enhanced WUE but further research to investigate the interaction effects of the tillage on WUE and soil fertility management is required. Understanding and considering the WUE in crops can be a primary condition for cropping system designs. The findings pave way for further research and crop management programmes, allowing to valorize the water in crop production.

Keywords: evapotranspiration, infiltration rate, organic mulch, sand, water use efficiency

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3499 Optimization of Smart Beta Allocation by Momentum Exposure

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

Abstract:

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

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

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3498 Study of Ether Species Effects on Physicochemical Properties of Palm Oil Ether Monoesters as Novel Biodiesels

Authors: Hejun Guo, Shenghua Liu

Abstract:

Five palm oil ether monoesters utilized as novel biodiesels were synthesized and structurally identified in the paper. Investigation was made on the effect of ether species on physicochemical properties of the palm oil ether monoesters. The results showed that density, kinematic viscosity, smoke point, and solidifying point increase linearly with their CH2 group number in certain relationships. Cetane number is enhanced whereas heat value decreases linearly with CH2 group number. In addition, the influencing regularities of volumetric content of the palm oil ether monoesters on the fuel properties were also studied when the ether monoesters are used as diesel fuel additives.

Keywords: biodiesel, palm oil ether monoester, ether species, physicochemical property

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3497 A Kruskal Based Heuxistic for the Application of Spanning Tree

Authors: Anjan Naidu

Abstract:

In this paper we first discuss the minimum spanning tree, then we use the Kruskal algorithm to obtain minimum spanning tree. Based on Kruskal algorithm we propose Kruskal algorithm to apply an application to find minimum cost applying the concept of spanning tree.

Keywords: Minimum Spanning tree, algorithm, Heuxistic, application, classification of Sub 97K90

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3496 Sales-Based Dynamic Investment and Leverage Decisions: A Longitudinal Study

Authors: Rihab Belguith, Fathi Abid

Abstract:

The paper develops a system-based approach to investigate the dynamic adjustment of debt structure and investment policies of the Dow-Jones index. This approach enables the assessment of relations among sales, debt, and investment opportunities by considering the simultaneous effect of the market environmental change and future growth opportunities. We integrate the firm-specific sales variance to capture the industries' conditions in the model. Empirical results were obtained through a panel data set of firms with different sectors. The analysis support that environmental change does not affect equally the different industry since operating leverage differs among industries and so the sensitivity to sales variance. Including adjusted-specific variance, we find that there is no monotonic relation between leverage, sales, and investment. The firm may choose a low debt level in response to high sales variance but high leverage to attenuate the negative relation between sales variance and the current level of investment. We further find that while the overall effect of debt maturity on leverage is unaffected by the level of growth opportunities, the shorter the maturity of debt is, the smaller the direct effect of sales variance on investment.

Keywords: dynamic panel, investment, leverage decision, sales uncertainty

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