Maximum Entropy Empirical Likelihood Methods Based on Laplace Transforms for Nonnegative Continuous Distribution with Actuarial Applications

Maximum entropy likelihood (MEEL) methods also known as exponential tilted empirical likelihood methods using constraints from model Laplace transforms (LT) are introduced in this paper. An estimate of overall loss of efficiency based on Fourier cosine series expansion of the density function is proposed to quantify the loss of efficiency when using MEEL methods. Penalty function methods are suggested for numerical implementation of the MEEL methods. The methods can easily be adapted to estimate continuous distribution with support on the real line encountered in finance by using constraints based on the model generating function instead of LT.

Likelihood and Quadratic Distance Methods for the Generalized Asymmetric Laplace Distribution for Financial Data

Maximum likelihood (ML) estimation for the generalized asymmetric Laplace (GAL) distribution also known as Variance gamma using simplex direct search algorithms is investigated. In this paper, we use numerical direct search techniques for maximizing the log-likelihood to obtain ML estimators instead of using the traditional EM algorithm. The density function of the GAL is only continuous but not differentiable with respect to the parameters and the appearance of the Bessel function in the density make it difficult to obtain the asymptotic covariance matrix for the entire GAL family. Using M-estimation theory, the properties of the ML estimators are investigated in this paper. The ML estimators are shown to be consistent for the GAL family and their asymptotic normality can only be guaranteed for the asymmetric Laplace (AL) family. The asymptotic covariance matrix is obtained for the AL family and it completes the results obtained previously in the literature. For the general GAL model, alternative methods of inferences based on quadratic distances (QD) are proposed. The QD methods appear to be overall more efficient than likelihood methods infinite samples using sample sizes n ≤5000 and the range of parameters often encountered for financial data. The proposed methods only require that the moment generating function of the parametric model exists and has a closed form expression and can be used for other models.

Preference of Dogs between Two Oral Formulations of Endectoparasiticides: NEXGARD SPECTRA^®(Afoxolaner and Milbemycin Oxime) and Simparica Trio^TM(Sarolaner, Moxidectin and Pyrantel)

Pet owner compliance is essential for the success of veterinary healthcare strategies. As some parasites are zoonotic, consistent parasite control is an integral part of the One-Health strategy. Highly palatable formulations help ensure compliance, as they offer a positive experience for the dog and the owner. This study was conducted to ascertain if dogs exhibited a preference between two commercially available oral formulations of broad-spectrum endectoparasiticides, NexGard Spectra (afoxolaner and milbemycin oxime) and Simparica Trio (sarolaner, moxidectin and pyrantel). For four consecutive days, 100 healthy dogs were offered both products and consumption was recorded. If one product was more consumed than the other, it was defined as the preferred product. No adverse event was recorded throughout the study. A total of 358 chewable tablets were consumed over four study days;78.5% of dogs voluntarily consumed NexGard Spectra (281 chews), while 21.5% of dogs voluntarily consumed Simparica Trio (77 chews, p < 0.01). Among 75 dogs which demonstrated a preference for a product, significantly more dogs preferred NexGard Spectra (94.7%) compared to Simparica Trio (5.3%) (p < 2.2 × 10-16), resulting in a preference ratio of 17.75 to 1 for NexGard Spectra.

A Semantic Metadata Enrichment Software Ecosystem (SMESE) Based on a Multi-Platform Metadata Model for Digital Libraries

Software industry has evolved to multi-product and multi-platform development based on a mix of proprietary and open source components. Such integration has occurred in software ecosystems through a software product line engineering (SPLE) process. However, metadata are underused in the SPLE and interoperability challenge. The proposed method is first, a semantic metadata enrichment software ecosystem (SMESE) to support multi-platform metadata driven applications, and second, based on mapping ontologies SMESE aggregates and enriches metadata to create a semantic master metadata catalogue (SMMC). The proposed SPLE process uses a component-based software development approach for integrating distributed content management enterprise applications, such as digital libraries. To perform interoperability between existing metadata models (such as Dublin Core, UNIMARC, MARC21, RDF/RDA and BIBFRAME), SMESE implements an ontology mapping model. SMESE consists of nine sub-systems: 1) Metadata initiatives & concordance rules;2) Harvesting of web metadata & data;3) Harvesting of authority metadata & data;4) Rule-based semantic metadata external enrichment;5) Rule-based semantic metadata internal enrichment;6) Semantic metadata external & internal enrichment synchronization;7) User interest-based gateway;8) Semantic master catalogue. To conclude, this paper proposes a decision support process, called SPLE decision support process (SPLE-DSP) which is then used by SMESE to support dynamic reconfiguration. SPLE-DSP consists of a dynamic and optimized metadata-based reconfiguration model. SPLE-DSP takes into account runtime metadata-based variability functionalities, context-awareness and self-adaptation. It also presents the design and implementation of a working prototype of SMESE applied to a semantic digital library.

On the Improvement of Wind Power Predictions Based on Terrain Characteristics and Measurements of the Annual Energy Production

The assessment of the production capacity of wind farms is a crucial step in wind farm design processes, where a poor assessment can cause significant economic losses. Data from Canadian wind farms benefiting from national production incentive programs show that wind farms are typically characterized by an overestimation of the production capacity. In this context, a study has been done to provide insight on the origin of the discrepancies between the energy production estimates and the measured energy generation, and to develop a method to reduce these discrepancies. To this end, the WAsP and MS-Micro models have been studied. Besides the wind speed measurements, topography indices have been developed to identify the influence of the various characteristics of the site on the error in the annual energy production (AEP). In addition, roughness classes have been created, including a reference roughness and a roughness complexity. The indices have also allowed establishing correlations and developing equations to evaluate the error based on the site characteristics and the positions of wind turbines on the measured annual energy production. An average reduction of up to 83% on the AEP errors was obtained when the methodology was applied to five wind farms in Canada.

Optimization of PV/Diesel Production through Data Monitoring

The study PV/diesel system is a stand-alone microgrid powered by the PV/diesel combination without production storage. The study focused on optimising PV/diesel production by monitoring data. It also referred to a comparison of sensitive factors in PV/diesel production. This study implemented structural and non-structural factors of the said system. A literature search was conducted to determine the factors involved. So, factors such as system autonomy, energy quality, system stability and data monitoring were considered for the study. Thus, after a detailed presentation of the data monitoring, a comparison based on the method, Analysis of Failure Modes, their Effects and Criticalities (FMEA) was carried out. At the end of the comparison, a hierarchy of parameters in the exploitation of the energy production of autonomous microgrids was made. From its results, it emerges a good consideration of the factor “data monitoring” in the management of the system studied. The results obtained confirm the importance of data monitoring for a better optimization of energy production. A monitoring program or procedure has been developed according to the originality that the present study has identified. The study also made it possible to evaluate the performance of data monitoring for the energy production of photovoltaic systems in general and hybrid PV/diesel systems in particular.

Estimation Models for Software Functional Test Effort

The International Software Benchmarking and Standards Group (ISBSG) data-base was used to build estimation models for estimating software functional test effort. The analysis of the data revealed three test productivity patterns representing economies or diseconomies of scale and these patterns served as a basis for investigating the characteristics of the corresponding projects. Three groups of projects related to the three different productivity patterns, characterized by domain, team size, elapsed time and rigor of verification and validation carried out during development, were found to be statistically significant. Within each project group, the variations in test effort can be explained, in addition to functional size, by 1) the processes executed during development, and 2) the processes adopted for testing. Portfolios of estimation models were built using combinations of the three independent variables. Performance of the estimation models built using the function point method innovated by the Common Software Measurement International Consortium (COSMIC) known as COSMIC Function Points, and the one advocated by the International Function Point Users Group (IFPUG) known as IFPUG Function Points, were compared to evaluate the impact of these respective sizing methods on test effort estimation.

Maintenance Task Scheduling, Reaching a Twofold Objective

In this paper, the problem of maintenance task scheduling is tackled with a twofold objective: meeting the performance criteria of a company and taking into account some operators’ requirements. The production manager makes sure that makespan is optimised while developing operators’ flexibility. The use of skill matrixes enables him to make pairs and to develop training in order to make trainees more autonomous. Operators’ requirements are in particular related to periods of unavailability and their wishes relating to their tasks. Given the complexity of the problem, an exact solution isn’t conceivable and our research focuses on a metaheuritic method giving us a solution that is considered satisfactory. A multi-criteria analysis of the results is performed in order to reach a compromise among conflicting goals.

Comparative Study of the Effects of Thermal and Photochemical Accelerated Oxidations on Quality of “Green Type” and “Black Type” French Olive Oils

Oxidative stability of two commercial olive oils of different specificity (green type and black type) has been studied during thermal and photochemical accelerated processes through the evolution of quality indices. It might help to assure a good utilisation of olive oil. In most of works described in literature, they are measured individually. In this study, a Principal Component Analysis (PCA) has been performed to emphasize their variation and describe in concise way the quality and the safety of extra-virgin olive oil after two oxidative stresses. No difference had been detected between both type oils when they are heated. Peroxides, aldehydes and conjugated dienes and trienes were formed but rapidly degraded into final oxidation compounds, mainly acid compounds. During the photochemical process, similar changes occurred slower and the green type oil had shown better stability because of its higher phenolic content. The fatty acids had been more impacted (higher disappearance of monounsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA)) when the oils were heated than when irradiated. Saturated fatty acids (SFA), MUFA and PUFA were the most relevant indicators to characterize non-oxidized oils and PV characterized the early stage of oil oxidation.

Determination of the Deep Optical Properties of Healthy and Diseased Skin Using Diffuse Reflectance Spectroscopy

In this study, we focused on diffuse reflectance spectroscopy, a rapid and noninvasive spectroscopy technique that has considerable potential for medical diagnosis. In order to better understand and analyze the signals induced by this method, we performed a series of in vivo measurements on healthy and diseased skin. Measurement sites on a human hand and feet were chosen. Some preliminary results obtained on these sites show the feasibility of this technique in clinics.

Interaction of the Mining Environment on the Properties of Hydraulic Mortars in Silty Sands in Togo

The objective of this study is to determine the influence of the surrounding soils on the granular properties of the silty sands of Togo and on the resistance of the mortars. Sand compositions are made by substituting silty sands with clay soil, vegetal soil, lateritic soil or fine elements (<0.08 mm) which are the surrounding land polluting the sands in Togo. After identification tests, the mixtures were used to prepare test specimens of mortar which are subjected to bending and compression. It appears that additions of clay and plastic soils (ES = 0, VBM > 0.53 and IP > 19) from 10% to 35% cause drops in resistance of mortars from 7% to 96%;this loss is 8% to 70% for the rates of addition of less clayey soil (ES = 33, VBM = 0.40 and IP = 0) at rates of 10% to 100%. As for fine powdery soils (ES = 56.53 and VBM = 0.25), they have virtually no influence on resistance (loss of less than 3% for rates of 100%). Construction stakeholders thus have a decision-making tool for the choice of silty sand extraction zones according to the surrounding land and the quality of the desired concrete.