Energy input–output analysis and application of artificial neural networks for predicting greenhouse basil production

In this study, various Artificial Neural Networks (ANNs) were developed to estimate the production yield of greenhouse basil in Iran. For this purpose, the data collected by random method from 26 greenhouses in the region during four periods of plant cultivation in 2009–2010. The total input energy and energy ratio for basil production were 14,308,998 MJ ha^?1 and 0.02, respectively. The developed ANN was a multilayer perceptron (MLP) with seven neurons in the input layer, one, two and three hidden layer(s) of various numbers of neurons and one neuron (basil yield) in the output layer. The input energies were human labor, diesel fuel, chemical fertilizers, farm yard manure, chemicals, electricity and transportation. Results showed, the ANN model having 7-20-20-1 topology can predict the yield value with higher accuracy. So, this two hidden layer topology was selected as the best model for estimating basil production of regional greenhouses with similar conditions. For the optimal model, the values of the models outputs correlated well with actual outputs, with coefficient of determination (R²) of 0.976. For this configuration, RMSE and MAE values were 0.046 and 0.035, respectively. Sensitivity analysis revealed that chemical fertilizers are the most significant parameter in the basil production.     

Avoiding Conversion and Rearrangement Overhead in SIMD Architectures

Single-Instruction Multiple-Data (SIMD) instructions provide an inexpensive way to exploit the Data-Level Parallelism in multimedia applications. However, the performance improvement obtained by employing SIMD instructions is often limited because frequently many overhead instructions are required to bring data in a form amenable to SIMD processing. In this paper, we employ two techniques to overcome this limitation. The first technique, extended subwords, uses four extra bits for every byte in a media register. This allows many SIMD operations to be performed without overflow and avoids packing/unpacking conversion overhead. The second technique, Matrix Register File (MRF), allows flexible row-wise as well as column-wise access to the register file. It is useful for many two-dimensional multimedia algorithms such as the (I) Discrete Cosine Transform, 2 × 2 Haar Transform, and pixel padding. In addition, we propose a few new media instructions. Experimental results obtained by extending the SimpleScalar toolset show that these techniques improve performance by up to a factor of 4.5 compared to a conventional SIMD instruction set extension.     

Seismic geomorphology and stratigraphic trap analyses of the Lower Cretaceous siliciclastic reservoir in the Kopeh Dagh-Amu Darya Basin

Lower Cretaceous Shurijeh–Shatlyk Formations host some of the main reservoirs in the Kopeh Dagh-Amu Darya Basin.Exploration in this area so far has focused on the development of structural traps, but recognition of stratigraphic traps in this area is of increasing importance. Integration of 3D seismic data with borehole data from thirteen wells and five outcrop sections was used to identify potential reservoir intervals and survey the hydrocarbon trap types in the East Kopeh Dagh Foldbelt(NE Iran). Analyses of horizontal slices indicated that the lower Shurijeh was deposited in a braided fluvial system.Generally, three types of channel were identified in the lower Shurijeh Formation: type 1, which is low-sinuosity channels interpreted to be filled with non-reservoir fine-grained facies; type 2, which is a moderately sinuous sand-filled channel with good prospectively; and type 3, which is narrow, high sinuosity channel filled with fine-grained sediments. Results indicate that upper Shurijeh–Shatlyk Formations were deposited in fluvial to delta and shallow marine environments. The identified delta forms the second reservoir zone in the Khangiran Field. Study of the stratigraphic aspects of the Shurijeh succession indicates that both lower and upper Shurijeh reservoirs are stratigraphic reservoir traps that improved during folding.     

Green synthesis of ZnO and ZnO/CuO nanocomposites in <Emphasis Type="Italic">Mentha longifolia</Emphasis> leaf extract: characterization and their application as anti-bacterial agents

In this work, we fabricated ZnO and ZnO/CuO nanocomposites using Mentha longifolia leaf extract as a natural, non-toxic, and efficient stabilizer. Anti-bacterial activities of the prepared samples against two pathogenic bacteria, Escherichia coli (Gram-negative), and Staphylococcus aureus (Gram-positive) were investigated. The properties of the as-prepared samples were characterized by XRD, EDX, SEM, TEM, TGA, FT-IR, UV–Vis DRS, and BET instruments. The XRD analysis indicated that the size of crystallites was decreased for the ZnO powder prepared in the presence of the leaf extract. The SEM images showed that the samples consist of spherical shaped well-distributed particles. In addition, the presence of biomolecules from the leaf extract was revealed by EDX, TGA, FT-IR, and UV–Vis DRS analyses, which are important in biosynthesis process. The highest anti-bacterial activity belonged to the ZnO/CuO (10%) nanocomposite and the other compounds, including ZnO/CuO (5%), ZnO (ext), and ZnO (W) were in the next ranks, respectively. It was observed that the viability percentages against E. coli (10.16?±?2.2) is higher than that of S. aureus (17.1?±?0.87) in the presence of the ZnO/CuO (10%) nanocomposite. Ultimately, the mechanism for the action of the ZnO/CuO (10%) nanocomposite was explored through the SEM images, which involved the disruption of the bacterial membranes.     

10 Years of research on debugging concurrent and multicore software: a systematic mapping study

Debugging—the process of identifying, localizing and fixing bugs—is a key activity in software development. Due to issues such as non-determinism and difficulties of reproducing failures, debugging concurrent software is significantly more challenging than debugging sequential software. A number of methods, models and tools for debugging concurrent and multicore software have been proposed, but the body of work partially lacks a common terminology and a more recent view of the problems to solve. This suggests the need for a classification, and an up-to-date comprehensive overview of the area. This paper presents the results of a systematic mapping study in the field of debugging of concurrent and multicore software in the last decade (2005–2014). The study is guided by two objectives: (1) to summarize the recent publication trends and (2) to clarify current research gaps in the field. Through a multi-stage selection process, we identified 145 relevant papers. Based on these, we summarize the publication trend in the field by showing distribution of publications with respect to year, publication venues, representation of academia and industry, and active research institutes. We also identify research gaps in the field based on attributes such as types of concurrency bugs, types of debugging processes, types of research and research contributions. The main observations from the study are that during the years 2005–2014: (1) there is no focal conference or venue to publish papers in this area; hence, a large variety of conferences and journal venues (90) are used to publish relevant papers in this area; (2) in terms of publication contribution, academia was more active in this area than industry; (3) most publications in the field address the data race bug; (4) bug identification is the most common stage of debugging addressed by articles in the period; (5) there are six types of research approaches found, with solution proposals being the most common one; and (6) the published papers essentially focus on four different types of contributions, with “methods” being the most common type. We can further conclude that there are still quite a number of aspects that are not sufficiently covered in the field, most notably including (1) exploring correction and fixing bugs in terms of debugging process; (2) order violation, suspension and starvation in terms of concurrency bugs; (3) validation and evaluation research in the matter of research type; (4) metric in terms of research contribution. It is clear that the concurrent, parallel and multicore software community needs broader studies in debugging. This systematic mapping study can help direct such efforts.     

A Real-Time Power Controller for Grid-Connected Inverters in LV Smart Microgrids

This paper presents a real-time power flow controller for VSIs （voltage source inverters） interfaced to low voltage microgrids. The proposed controller is modular, flexible, intelligent, inexpensive, portable, adaptive and designed to positively contribute in low voltage microgrids in which the lines R/X ratio is greater than the transmission lines. Therefore, the proposed control strategy is developed for operation in distribution lines. The controller strategy is different from the conventional grid-connected inverters which are designed based on transmission line characteristics. This controller, using a Texas Instrument general purpose DSP （digital signal processor）, is programmed and tuned using MATLAB/SIMULINK in order to enhance self-healing, reliability and stability of the grid. This general purpose controller makes proper decisions using its local measurements as the primary source of data. The controller has the capability of communicating with the adjacent controllers and sharing the information if/when needed. The power flow output of the inverter is tested for both islanded and grid-connected modes of operation. The inverter positively contributes to active and reactive power supply while operating in grid-connected mode. The proposed control method has been implemented on a Texas Instrument DSC （digital signal controller） chip and tested on a hardware test bench at the Alternative Energy Laboratory at WVU1T （West Virginia University Institute of Technology）. The system＇s experimental results veri~ the validity and efficiency of the proposed controller.     

Green synthesis of stable silver nanoparticles by the main reduction component of green tea (Camellia sinensis L.)

Recently the use of medicinal plants potential in the production of nanoparticles has received serious attention. Here, the main component of Camellia sinensis L. (green tea) extract was detected by spectroscopy and the optimal conditions were determined for their performance in green synthesis of silver nanoparticles at room temperature. Epigallocatechin gallate was identified as the dominant component in the extract as determined by spectroscopy, and it was established that its oxidation was a function of the solution pH. Transmission electron microscopy, dynamic light scattering, and visible absorption spectroscopy (UV‐Vis) confirmed the reduction in silver ions to silver nanoparticles (Ag NPs). Controlling over Ag NPs shape and narrow size distribution was achieved with 10 ml green tea leaf extract solution and in different reaction pH. Spherical colloidal Ag NPs with well‐defined hydrodynamic diameters (with average hydrodynamic size of 27.9–50.2 nm) were produced. Silver nitrate concentrations used in this study were lower than that of reported in similar works, and synthesis efficiency was also higher. Nanoparticles were perfectly spherical and their uniformity, compared to similar studies, was much higher. These NPs showed higher degree of stability and were aqueously stable for >10 months in dark glasses at 4°C.Inspec keywords: hydrodynamics, nanoparticles, particle size, pH, visible spectra, ultraviolet spectra, reduction (chemical), transmission electron microscopy, silver, microorganisms, nanofabrication, colloids, biomedical materials, nanomedicine, drug delivery systemsOther keywords: transmission electron microscopy, dynamic light scattering, visible absorption spectroscopy, silver ions, narrow size distribution, silver nitrate concentrations, green synthesis, medicinal plants, solution pH, green tea leaf, hydrodynamic size, silver nanoparticles, Camellia sinensis L, drug delivery, reduction component, epigallocatechin gallate, UV‐visible spectra, hydrodynamic diameters, spherical colloidal Ag NPs, temperature 4.0 degC, Ag     

A new application of an improved DRBEM model for water wave propagation over a frictional uneven bottom

This paper presents a numerical scheme to approximate water wave diffraction, refraction and frictional dissipation over an axi-symmetric pit. Based on an improved extended mild-slope equation (EMSE) including bottom friction effect, as the elliptic governing differential equation, dual reciprocity boundary element method (DRBEM) is employed to model water wave propagation over an axi-symmetric pit. To the authors' knowledge, this is the first application of DRBEM for water wave scattering over a pit. In order to promote accuracy of the model, not only effects of the bottom curvature and the slope-squared terms which are neglected in the mild-slope equation (MSE), are considered, but also effect of the bottom friction is measured by the improved EMSE. Numerical results are compared with existing analytical or numerical solutions or with experimental data by several examples. Through these numerical experiments reliability and efficiency of present DRBEM model for determining the total wave field over an uneven bottom is approved.     

Parallel implementation of Gray Level Co-occurrence Matrices and Haralick texture features on cell architecture

Texture features extraction algorithms are key functions in various image processing applications such as medical images, remote sensing, and content-based image retrieval. The most common way to extract texture features is the use of Gray Level Co-occurrence Matrices (GLCMs). The GLCM contains the second-order statistical information of spatial relationship of the pixels of an image. Haralick texture features are extracted using these GLCMs. However, the GLCMs and Haralick texture features extraction algorithms are computationally intensive. In this paper, we apply different parallel techniques such as task- and data-level parallelism to exploit available parallelism of those applications on the Cell multi-core processor. Experimental results have shown that our parallel implementations using 16 Synergistic Processor Elements significantly reduce the computational times of the GLCMs and texture features extraction algorithms by a factor of 10× over non-parallel optimized implementations for different image sizes from 128×128 to 1024×1024.