In the environmental radioactivity laboratory, the nuclear waste contains a small amounts of the contaminated samples of a wide variety of characteristics are routinely analyzed by high gamma-ray efficiency detectors. A new numerical algorithm method (NAM) is developed in the present work, as an approximate analytical procedure for determining the efficiency of HPGe detectors, this algorithm uses low radioactive mixed-radionuclide gamma-ray cylindrical sources, placed parallel or perpendicular with respect to the detector symmetry axis. In addition, the self-attenuation factor and the coincidence summing effect are estimated by using the linear attenuation factor of the assayed source material and the geometrical configuration of the assay set-up at low source-detector distance. The discrepancies between the measured and the calculated efficiencies were less than 5% when the detectors are positioned close to the items being measured.

This paper presents diagonalization deconvolution filter estimation for a black-box model with a linear dynamics response and time-invariant evolutions. Instead of using the pseudo-inverse in deconvolution separation, a matrix blocks form was proposed applying the inverse scheme. This description allows a lower computational complexity than the pseudo-inverse requires, selecting the eigenvalues and eigenvectors conforming the adjoining region near the inverse. The organization of this paper considers: a) matrix diagonalization, b) deconvolution filter with diagonalization, c) functional error and its trace simulation, d) the computational complexity, e) simulation and f) annexes.

Using a non-Newtonian mathematical model for the blood flow in large vessels – elaborated and presented already by us in previous papers, we make some remarks on the wall shear stress (WSS) in the case of a human abdominal aortic aneurysm (AAA). We concentrate on the mechanical conditions which would lead to the rupture of the vascular vessel with aneurysm.\n The original feature is that the established condition is not backed on the real blood flow but only on the data got via the above mentioned model. This leads to a more suitable tool of risk rupture prediction which avoids almost completely the investigation in vivo.

The work describes an intelligent use of the supply chain configuration, having a dynamical structure that automatically actualizes the chain stages considering different service levels to the customer, each level will be selected automatically in accordance with its actual request. In computational sense, the model proposed works as intelligent processes selector,\nwhere the dynamical changes are developed in accordance to the configuration required based on the minimum cost. The basic decisions set are defined into a knowledge base\nusing decision rules as inferences, transforming these into actions over the elements required into the process supply. The intelligent computational system adjusts automatically all structure changes based on a specific configuration, described previously\ninto the knowledge base, adding intelligence, dynamism and robustness into the business process. Therefore, the learning model applied to business strategies as supply chain configuration system, provides a multiple option decision that considers different service levels offered. The operational model stages are described illustratively using the Matlab software.

The assessment of an engineering program consists of several components, each of which requires a number of judgments mainly based on imprecise and vague data. These impression and vagueness arise from direct and indirect human interpretations, evaluation and assessment. Assessment is one of the most important and difficult task in the learning and teaching processes. This study presents a new algorithmic approach for assessing the learning quality using program outcomes. Actual student outcomes were used to assess the engineering program outcomes and evaluate the student learning level by a mixed integer programming approach. It uses fuzzy set principles to represent the subjective concepts and Bloom’s taxonomy for assessment of learning levels. \nThe proposed model incorporates the course learning outcomes (CLOs) and program outcomes for assessment and allows the educators, families and educational institutions to have a better understanding on the learning performance criteria. It also aims at encouraging students to participate in the learning process and eventually provides a fair environment for assessment.

Abstract:The objectives of the present study are to determine the most important factors affecting industrial wood material production yield in natural oriental beech forests in Turkey using a multifaceted approach and to help entrepreneurs consider these factors to develop more sensitive and realistic production plans. In Günye Forest Management in Bart?n province of the West Black Sea Region of Turkey, 41 production units were chosen as the study area. The 1277 ha study area was included in the 2007 and 2010 production management plan. The general state of the stand, natural stand structure, and production methods and tools are the factors thought most strongly affect industrial wood material production yield; 26 variables representing these factors were evaluated in the study. Through multidimensional statistical analyses, including main components, factor and regression analysis, we found that the most important factors affecting production yield were fertility, aspect of land, skidding method, stand structure, skidding distance, growing stock, transportation and harmful abiotic factors. Production units were divided into three groups based on yield rates and the 26 variables, using discriminate analysis. From the results of the study, a sample model can be developed to help forest managers predict and plan annual industrial wood production more sensitively and realistically.

An accurate state estimation is crucial for maintaining system security, reliability and quality of a power system network. The accuracy of state estimation depends on the location of measurement devices. Considering the importance of measurement location, this paper presents an optimization method that identifies the optimal additional location to enhance the accuracy of state estimation. A novel approach of discrete Evolutionary Programming (EP) is proposed to solve the meter placement problem. The proposed method of discrete EP is applicable to solve the problem involving integers as control variables. Test result of IEEE 30 bus system indicates that the optimization method of discrete EP is superior to the heuristic method in terms of higher accuracy and larger networks.

Background: Recent studies on mammals have shown that the ovarian follicles might have a different origin. Stem cells of ovarian surface epithelium have the potential to differentiate into oocytes and granulosa cells. \nObjective: The present study was designed to study the capability of human ovarian surface epithelial stem cells to differentiate into follicles.\nMaterials and Methods: OSE cells were obtained from10 women. Stem cells of OSE were separated and cultured for 21 days. Morphology and morphometeryof cultured cells were studied at 1-, 5-, 9-, 15- and 21th day of culture. Furthermore, on day 21, GDF9 and BMP15 (mRNA) expressions were evaluated for screening of developmental stage of cultured OSE cells.\nResults: The results showed that the OSE stem cells were able to differentiate into oocyte-like cells and follicular-like structures after the 5th day of culture, although it was not observed in all the samples. On the final day (21th day), the cultured cells showed morphological characteristics similar to oocytes and granulosa cells. In addition, GDF9 and BMP15 genes were expressed in primary follicles. The number and surface area of proliferated cells increased in following days but the number of stem cells decreased.\nConclusion: OSE stem cells are bipotentand can differentiate into oocyte-like and granulosa-like cells. GDF9 and BMP15 are necessary for developing of primary follicles into secondary follicles. The hypothesis that OSE could supply necessary follicles in reproductive periods could be considered again.

Under-Voltage Load Shedding (UVLS) scheme is an important technique to maintain the voltage stability of power system. UVLS has been applied for transmission system in order to avoid the system blackouts. However, with the increasing number of Distributed Generation (DG) such as Photovoltaic (PV), the application of UVLS becomes important for islanded distribution systems. In this regards, a new UVLS scheme based on voltage stability index has been proposed in this paper. The voltage stability index is used as an indicator of the sequence of load to be shed. Based on the stability index, the loads that have the highest tendency of voltage collapse shall be the first load to be shed. The proposed scheme is tested on a practical distribution network energized by grid, a mini hydro generator and a PV solar system. The test results on various scenarios proven that the proposed method able to restore system stability.