Corporate Social Responsibility and Creating Shared Value: Case of Latvia

Creating shared value (CSV) is a newly introduced concept whose essence and expressions, relationship to Corporate social responsibility (CSR) and implications for the business and society is now at the core of management and social responsibility debates of the scientific world. The aim of the paper is to gain clearer understanding of the CSR and CSV concepts, their implementation and role in sustainable development of organizations in Latvia. In this paper the authors discuss and compare the two conceptsand, based on the results of Sustainability Index (SI) initiative and analysis of publically available company information, evaluate their implementation in Latvia and draw conclusions on the development trends and potential of these approaches in Latvian market.

From Individual Memory to Organizational Memory (Intelligence of Organizations)

Intensive changes of environment and strong market competition have raised management of information and knowledge to the strategic level of companies. In a knowledge based economy only those organizations are capable of living which have up-to-date, special knowledge and they are able to exploit and develop it. Companies have to know what knowledge they have by taking a survey of organizational knowledge and they have to fix actual and additional knowledge in organizational memory. The question is how to identify, acquire, fix and use knowledge effectively. The paper will show that over and above the tools of information technology supporting acquisition, storage and use of information and organizational learning as well as knowledge coming into being as a result of it, fixing and storage of knowledge in the memory of a company play an important role in the intelligence of organizations and competitiveness of a company.

Mathematical Modeling of SISO based Timoshenko Structures – A Case Study

This paper features the mathematical modeling of a single input single output based Timoshenko smart beam. Further, this mathematical model is used to design a multirate output feedback based discrete sliding mode controller using Bartoszewicz law to suppress the flexural vibrations. The first 2 dominant vibratory modes is retained. Here, an application of the discrete sliding mode control in smart systems is presented. The algorithm uses a fast output sampling based sliding mode control strategy that would avoid the use of switching in the control input and hence avoids chattering. This method does not need the measurement of the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement.

Surface Flattening based on Linear-Elastic Finite Element Method

This paper presents a linear-elastic finite element method based flattening algorithm for three dimensional triangular surfaces. First, an intrinsic characteristic preserving method is used to obtain the initial developing graph, which preserves the angles and length ratios between two adjacent edges. Then, an iterative equation is established based on linear-elastic finite element method and the flattening result with an equilibrium state of internal force is obtained by solving this iterative equation. The results show that complex surfaces can be dealt with this proposed method, which is an efficient tool for the applications in computer aided design, such as mould design.

Preparation of ATO Conductive Particles with Narrow Size Distribution

Antimosy-doped tin oxide (ATO) particles were prepared via chemical coprecipitation and reverse emulsion. The size and size distribution of ATO particles were obviously decreased via reverse microemulsion method. At the relatively high yield the ATO particles were nearly spherical in shape, meanwhile the crystalline structure and excellent conductivity were reserved, which could satisfy the requirement as composite fillers, such as dielectric filler of polyimide film.

An Experimental Study on Effects of Applying the Pulsating Flow to a Gas-Solid Fluidized Bed

There have been widespread applications of fluidized beds in industries which are related to the combination of gas-solid particles during the last decade. For instance, in order to crack the catalyses in petrochemical industries or as a drier in food industries. High capacity of fluidized bed in heat and mass transfer has made this device very popular. In order to achieve a higher efficiency of fluidized beds, a particular attention has been paid to beds with pulsating air flow. In this paper, a fluidized bed device with pulsating flow has been designed and constructed. Size of particles have been used during the test are in the range of 40 to 100μm. The purpose of this experimental test is to investigate the air flow regime, observe the particles- movement and measure the pressure loss along the bed. The effects of pulsation can be evaluated by comparing the results for both continuous and pulsating flow. Results of both situations are compared for various gas speeds. Moreover the above experiment is numerically simulated by using Fluent software and its numerical results are compared with the experimental results.

Optimal Design of UPFC Based Damping Controller Using Iteration PSO

This paper presents a novel approach for tuning unified power flow controller (UPFC) based damping controller in order to enhance the damping of power system low frequency oscillations. The design problem of damping controller is formulated as an optimization problem according to the eigenvalue-based objective function which is solved using iteration particle swarm optimization (IPSO). The effectiveness of the proposed controller is demonstrated through eigenvalue analysis and nonlinear time-domain simulation studies under a wide range of loading conditions. The simulation study shows that the designed controller by IPSO performs better than CPSO in finding the solution. Moreover, the system performance analysis under different operating conditions show that the δE based controller is superior to the mB based controller.

Morphometric Analysis of Tor tambroides by Stepwise Discriminant and Neural Network Analysis

The population structure of the Tor tambroides was investigated with morphometric data (i.e. morphormetric measurement and truss measurement). A morphometric analysis was conducted to compare specimens from three waterfalls: Sunanta, Nan Chong Fa and Wang Muang waterfalls at Khao Nan National Park, Nakhon Si Thammarat, Southern Thailand. The results of stepwise discriminant analysis on seven morphometric variables and 21 truss variables per individual were the same as from a neural network. Fish from three waterfalls were separated into three groups based on their morphometric measurements. The morphometric data shows that the nerual network model performed better than the stepwise discriminant analysis.

A Laser Point Interaction System Integrating Mouse Functions

The computer has become an essential tool in modern life, and the combined use of a computer with a projector is very common in teaching and presentations. However, as typical computer operating devices involve a mouse or keyboard, when making presentations, users often need to stay near the computer to execute functions such as changing pages, writing, and drawing, thus, making the operation time-consuming, and reducing interactions with the audience. This paper proposes a laser pointer interaction system able to simulate mouse functions in order that users need not remain near the computer, but can directly use laser pointer operations from at a distance. It can effectively reduce the users- time spent by the computer, allowing for greater interactions with the audience.

Blind Image Deconvolution by Neural Recursive Function Approximation

This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.

Particle Simulation of Rarefied Gas Flows witha Superimposed Wall Surface Temperature Gradient in Microgeometries

Rarefied gas flows are often occurred in micro electro mechanical systems and classical CFD could not precisely anticipate the flow and thermal behavior due to the high Knudsen number. Therefore, the heat transfer and the fluid dynamics characteristics of rarefied gas flows in both a two-dimensional simple microchannel and geometry similar to single Knudsen compressor have been investigated with a goal of increasing performance of a actual Knudsen compressor by using a particle simulation method. Thermal transpiration and thermal creep, which are rarefied gas dynamic phenomena, that cause movement of the flow from less to higher temperature is generated by using two different longitude temperature gradients (Linear, Step) along the walls of the flow microchannel. In this study the influence of amount of temperature gradient and governing pressure in various Knudsen numbers and length-to-height ratios have been examined.

A Method for Identifying Physical Parameters with Linear Fractional Transformation

This paper proposes a new parameter identification method based on Linear Fractional Transformation (LFT). It is assumed that the target linear system includes unknown parameters. The parameter deviations are separated from a nominal system via LFT, and identified by organizing I/O signals around the separated deviations of the real system. The purpose of this paper is to apply LFT to simultaneously identify the parameter deviations in systems with fewer outputs than unknown parameters. As a fundamental example, this method is implemented to one degree of freedom vibratory system. Via LFT, all physical parameters were simultaneously identified in this system. Then, numerical simulations were conducted for this system to verify the results. This study shows that all the physical parameters of a system with fewer outputs than unknown parameters can be effectively identified simultaneously using LFT.

Transient Thermal Stresses of Functionally Graded Thick Hollow Cylinder under the Green-Lindsay Model

The transient thermoelastic response of thick hollow cylinder made of functionally graded material under thermal loading is studied. The generalized coupled thermoelasticity based on the Green-Lindsay model is used. The thermal and mechanical properties of the functionally graded material are assumed to be varied in the radial direction according to a power law variation as a function of the volume fractions of the constituents. The thermal and elastic governing equations are solved by using Galerkin finite element method. All the finite element calculations were done by using commercial finite element program FlexPDE. The transient temperature, radial displacement, and thermal stresses distribution through the radial direction of the cylinder are plotted.

A CFD Study of Heat Transfer Enhancement in Pipe Flow with Al2O3 Nanofluid

Fluids are used for heat transfer in many engineering equipments. Water, ethylene glycol and propylene glycol are some of the common heat transfer fluids. Over the years, in an attempt to reduce the size of the equipment and/or efficiency of the process, various techniques have been employed to improve the heat transfer rate of these fluids. Surface modification, use of inserts and increased fluid velocity are some examples of heat transfer enhancement techniques. Addition of milli or micro sized particles to the heat transfer fluid is another way of improving heat transfer rate. Though this looks simple, this method has practical problems such as high pressure loss, clogging and erosion of the material of construction. These problems can be overcome by using nanofluids, which is a dispersion of nanosized particles in a base fluid. Nanoparticles increase the thermal conductivity of the base fluid manifold which in turn increases the heat transfer rate. In this work, the heat transfer enhancement using aluminium oxide nanofluid has been studied by computational fluid dynamic modeling of the nanofluid flow adopting the single phase approach.

Endothelial-Cell-Mediated Displacement of Extracellular Matrix during Angiogenesis

Mechanical interaction between endothelial cells (ECs) and the extracellular matrix (or collagen gel) is known to influence the sprouting response of endothelial cells during angiogenesis. This influence is believed to impact on the capability of endothelial cells to sense soluble chemical cues. Quantitative analysis of endothelial-cell-mediated displacement of the collagen gel provides a means to explore this mechanical interaction. Existing analysis in this context is generally limited to 2D settings. In this paper, we investigate the mechanical interaction between endothelial cells and the extracellular matrix in terms of the endothelial-cellmediated displacement of the collagen gel in both 2D and 3D. Digital image correlation and Digital volume correlation are applied on confocal reflectance image stacks to analyze cell-mediated displacement of the gel. The skeleton of the sprout is extracted from phase contrast images and superimposed on the displacement field to further investigate the link between the development of the sprout and the displacement of the gel.

Synthesis, Characterization and PL Properties of Cds Nanoparticles Confined within a Functionalized SBA-15 Mesoprous

A simple and dexterous in situ method was introduced to load CdS nanocrystals into organofunctionalized mesoporous, which used an ion-exchange method. The products were extensively characterized by combined spectroscopic methods. X- ray diffraction (XRD) and high-resolution transmission electron microscopy (HRTEM) demonstrated both the maintenance of pore symmetry (space group p6mm) of SBA-15 and the presence of CdS nanocrystals with uniform sizes of about 6 - 8 nm inside the functionalized SBA-15 channels. These mesoporous silica-supported CdS composites showed room temperature photoluminescence properties with a blue shift, indicating the quantum size effect of nanocrystalline CdS.

Cr, Fe and Se Contents of the Turkish Black and Green Teas and the Effect of Lemon Addition

Tea is consumed by a big part of the world-s population. It has an enormous importance for the Turkish culture. Nearly it is brewed every morning and evening at the all houses. Also it is consumed with lemon wedge. Habitual drinking of tea infusions may significantly contribute to daily dietary requirements of elements. Different instrumental techniques are used for determination of these elements. But atomic and mass spectroscopic methods are preferred most. In these study chromium, iron and selenium contents after the hot water brewing of black and green tea were determined by Optical Emission Spectroscopy (ICP-OES). Furthermore, effect of lemon addition on chromium, iron and selenium concentration tea infusions is investigated. Results of the investigation showed that concentration of chromium, iron and selenium increased in black tea with lemon addition. On the other hand only selenium is increased with lemon addition in green tea. And iron concentration is not detected in green tea but its concentration is determined as 1.420 ppm after lemon addition.

Clustering based Voltage Control Areas for Localized Reactive Power Management in Deregulated Power System

In this paper, a new K-means clustering based approach for identification of voltage control areas is developed. Voltage control areas are important for efficient reactive power management in power systems operating under deregulated environment. Although, voltage control areas are formed using conventional hierarchical clustering based method, but the present paper investigate the capability of K-means clustering for the purpose of forming voltage control areas. The proposed method is tested and compared for IEEE 14 bus and IEEE 30 bus systems. The results show that this K-means based method is competing with conventional hierarchical approach

5-Aminolevulinic Acid-Loaded Gel, Sponge Collagen to Enhance the Delivery Ability to Skin

Topical photodynamic therapy (PDT) with 5-aminolevulinic acid (ALA) is an alternative therapy for treating superficial cancer, especially for skin or oral cancer. ALA, a precursor of the photosensitizer protoporphyrin IX (PpIX), is present as zwitterions and hydrophilic property which make the low permeability through the cell membrane. Collagen is a traditional carrier; its molecular composed various amino acids which bear positive charge and negative charge. In order to utilize the ion-pairs with ALA and collagen, the study employed various pH values adjusting the net charge. The aim of this study was to compare a series collagen form, including solution, gel and sponge to investigate the topical delivery behavior of ALA. The in vivo confocal laser scanning microscopy (CLSM) study demonstrated that PpIX generation ability was different pattern after apply for 6 h. Gel type could generate high PpIX, and archived more deep of skin depth.

Counterpropagation Neural Network for Solving Power Flow Problem

Power flow (PF) study, which is performed to determine the power system static states (voltage magnitudes and voltage angles) at each bus to find the steady state operating condition of a system, is very important and is the most frequently carried out study by power utilities for power system planning, operation and control. In this paper, a counterpropagation neural network (CPNN) is proposed to solve power flow problem under different loading/contingency conditions for computing bus voltage magnitudes and angles of the power system. The counterpropagation network uses a different mapping strategy namely counterpropagation and provides a practical approach for implementing a pattern mapping task, since learning is fast in this network. The composition of the input variables for the proposed neural network has been selected to emulate the solution process of a conventional power flow program. The effectiveness of the proposed CPNN based approach for solving power flow is demonstrated by computation of bus voltage magnitudes and voltage angles for different loading conditions and single line-outage contingencies in IEEE 14-bus system.