The Determinants of Voluntary Disclosure in Croatia

Study investigates the level and extent of voluntary disclosure practice in Croatia. The research was conducted on the sample of 130 medium and large companies. Findings indicate that two thirds of the companies analyzed disclose below-average number of additional information. The explanatory analyses has shown that firm size, listing status and industrial sector significantly and positively affect the level and extent of voluntary disclosure in the annual report of Croatian companies. On the other hand, profitability and ownership structure were found statistically insignificant. Unlike previous studies, this paper deals with level of voluntary disclosure of medium and large companies, as well as companies whose shares are not listed on the organized capital market, which can be found as our contribution. Also, the research makes contribution by providing the insights into voluntary disclosure practices in Croatia, as a case of macro-oriented accounting system economy, i.e. bank oriented economy with an emerging capital market.

Pesticides Use in Rural Settings in Romania

The environment pollution with pesticides and heavy metals is a recognized problem nowadays, with extension to the global scale the tendency of amplification. Even with all the progress in the environmental field, both in the emphasize of the effect of the pollutants upon health, the linked studies environment-health are insufficient, not only in Romania but all over the world also. We aim to describe the particular situation in Romania regarding the uncontrolled use of pesticides, to identify and evaluate the risk zones for health and the environment in Romania, with the final goal of designing adequate programs for reduction and control of the risk sources. An exploratory study was conducted to determine the magnitude of the pesticide use problem in a population living in Saliste, a rural setting in Transylvania, Romania. The significant stakeholders in Saliste region were interviewed and a sample from the population living in Saliste area was selected to fill in a designed questionnaire. All the selected participants declared that they used pesticides in their activities for more than one purpose. They declared they annually applied pesticides for a period of time between 11 and 30 years, from 5 to 9 days per year on average, mainly on crops situated at some distance from the houses but high risk behavior was identified as the volunteers declared the use of pesticides in the backyard gardens, near their homes, where children were playing. The pesticide applicators did not have the necessary knowledge about safety and exposure. The health data must be correlated with exposure biomarkers in attempt to identify the possible health effects of the pesticides exposure. Future plans include educational campaigns to raise the awareness of the population on the danger of uncontrolled use of pesticides.

Adaptive Sampling Algorithm for ANN-based Performance Modeling of Nano-scale CMOS Inverter

This paper presents an adaptive technique for generation of data required for construction of artificial neural network-based performance model of nano-scale CMOS inverter circuit. The training data are generated from the samples through SPICE simulation. The proposed algorithm has been compared to standard progressive sampling algorithms like arithmetic sampling and geometric sampling. The advantages of the present approach over the others have been demonstrated. The ANN predicted results have been compared with actual SPICE results. A very good accuracy has been obtained.

Effect of Crystallographic Orientation on the Pitting Corrosion Resistance of Laser Surface Melted AISI 304L Austenitic Stainless Steel

The localized corrosion behavior of laser surface melted 304L austenitic stainless steel was studied by potentiodynamic polarization test. The extent of improvement in corrosion resistance was governed by the preferred orientation and the percentage of delta ferrite present on the surface of the laser melted sample. It was established by orientation imaging microscopy that the highest pitting potential value was obtained when grains were oriented in the most close- packed [101] direction compared to the random distribution of the base metal and other laser surface melted samples oriented in [001] direction. The sample with lower percentage of ferrite had good pitting resistance.

Face Detection using Gabor Wavelets and Neural Networks

This paper proposes new hybrid approaches for face recognition. Gabor wavelets representation of face images is an effective approach for both facial action recognition and face identification. Perform dimensionality reduction and linear discriminate analysis on the down sampled Gabor wavelet faces can increase the discriminate ability. Nearest feature space is extended to various similarity measures. In our experiments, proposed Gabor wavelet faces combined with extended neural net feature space classifier shows very good performance, which can achieve 93 % maximum correct recognition rate on ORL data set without any preprocessing step.

Neural Network Controller for Mobile Robot Motion Control

In this paper the neural network-based controller is designed for motion control of a mobile robot. This paper treats the problems of trajectory following and posture stabilization of the mobile robot with nonholonomic constraints. For this purpose the recurrent neural network with one hidden layer is used. It learns relationship between linear velocities and error positions of the mobile robot. This neural network is trained on-line using the backpropagation optimization algorithm with an adaptive learning rate. The optimization algorithm is performed at each sample time to compute the optimal control inputs. The performance of the proposed system is investigated using a kinematic model of the mobile robot.

Effect of Pre-drying Treatments on Quality Characteristics of Dehydrated Tomato Slices

Tomato powder has good potential as substitute of tomato paste and other tomato products. In order to protect physicochemical properties and nutritional quality of tomato during dehydration process, investigation was carried out using different drying methods and pretreatments. Solar drier and continuous conveyor (tunnel) drier were used for dehydration where as calcium chloride (CaCl2), potassium metabisulphite (KMS), calcium chloride and potassium metabisulphite (CaCl2 +KMS), and sodium chloride (NaCl) selected for treatment.. lycopene content, dehydration ratio, rehydration ratio and non-enzymatic browning in addition to moisture, sugar and titrable acidity were studied. Results show that pre-treatment with CaCl2 and NaCl increased water removal and moisture mobility in tomato slices during drying of tomatoes. Where CaCl2 used along with KMS the NEB was recorded the least compared to other treatments and the best results were obtained while using the two chemicals in combination form. Storage studies in LDPE polymeric and metalized polyesters films showed less changes in the products packed in metallized polyester pouches and even after 6 months lycopene content did not decrease more than 20% as compared to the control sample and provide extension of shelf life in acceptable condition for 6 months. In most of the quality characteristics tunnel drier samples presented better values in comparison to solar drier.

Effects of Data Correlation in a Sparse-View Compressive Sensing Based Image Reconstruction

Computed tomography and laminography are heavily investigated in a compressive sensing based image reconstruction framework to reduce the dose to the patients as well as to the radiosensitive devices such as multilayer microelectronic circuit boards. Nowadays researchers are actively working on optimizing the compressive sensing based iterative image reconstruction algorithm to obtain better quality images. However, the effects of the sampled data’s properties on reconstructed the image’s quality, particularly in an insufficient sampled data conditions have not been explored in computed laminography. In this paper, we investigated the effects of two data properties i.e. sampling density and data incoherence on the reconstructed image obtained by conventional computed laminography and a recently proposed method called spherical sinusoidal scanning scheme. We have found that in a compressive sensing based image reconstruction framework, the image quality mainly depends upon the data incoherence when the data is uniformly sampled.

The Effect of Education Level on Psychological Empowerment and Burnout-The Mediating Role of Workplace Learning Behaviors

The study investigates the relationship between education level, workplace learning behaviors, psychological empowerment and burnout in a sample of 191 teachers. We hypothesized that education level will positively affect psychological state of increased empowerment and decreased burnout, and we purposed that these effects will be mediated by workplace learning behaviors. We used multiple regression analyses to test the model that included also the 6 following control variables: The teachers' age, gender, and teaching tenure; the schools' religious level, the pupils' needs: regular/ special needs, and the class level: elementary/ high school. The results support the purposed mediating model.

Osmotic Dehydration of Beetroot in Salt Solution: Optimization of Parameters through Statistical Experimental Design

Response surface methodology was used for quantitative investigation of water and solids transfer during osmotic dehydration of beetroot in aqueous solution of salt. Effects of temperature (25 – 45oC), processing time (30–150 min), salt concentration (5–25%, w/w) and solution to sample ratio (5:1 – 25:1) on osmotic dehydration of beetroot were estimated. Quadratic regression equations describing the effects of these factors on the water loss and solids gain were developed. It was found that effects of temperature and salt concentrations were more significant on the water loss than the effects of processing time and solution to sample ratio. As for solids gain processing time and salt concentration were the most significant factors. The osmotic dehydration process was optimized for water loss, solute gain, and weight reduction. The optimum conditions were found to be: temperature – 35oC, processing time – 90 min, salt concentration – 14.31% and solution to sample ratio 8.5:1. At these optimum values, water loss, solid gain and weight reduction were found to be 30.86 (g/100 g initial sample), 9.43 (g/100 g initial sample) and 21.43 (g/100 g initial sample) respectively.

Residual Stresses in Thermally Sprayed Gas Turbine Components

In this paper, the residual stress of thermal spray coatings in gas turbine component by curvature method has been studied. The samples and shaft were coated by hard WC-12Co cermets using high velocity oxy fuel (HVOF) after preparation in same conditions. The curvature of coated samples was measured by using of coordinate measurement machine (CMM). The metallurgical and Tribological studies has been made on the coated shaft using optical microscopy and scanning electron microscopy (SEM)

Phenolic Compounds in Red Fruits Produced in Organic Farming at Maturation Stage

The agricultural organic farming is different from conventional farming in a way that is aimed at providing a balanced and constructive action in agricultural systems. With the increase in intensive agriculture, undesirable changes were being observed in ecosystems with irreparable damage being caused to the natural equilibrium. This is the reason for the increasing interest in organic farming as an environment friendly agricultural production method. In the present work three red fruits produced in organic farming were analyzed, namely raspberry, gooseberry and blueberry. The samples were harvested in a local farm when at plain maturation. The results obtained allowed to conclude that the blueberry contained higher amounts of phenolic compounds, total tannins and total anthocyanins than raspberry and gooseberry. Furthermore, the HPLC analysis allowed to identify monomeric anthocyanins and phenolic acids in the three fruits studied.

Maya Semantic Technique: A Mathematical Technique Used to Determine Partial Semantics for Declarative Sentences

This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely Cµ programming. In this domain all the keywords and programming concepts are known and understood.

Hydrolysis Characteristics of Polycrystalline Lithium Hydride Powders and Sintered Bulk

Ambient hydrolysis products in moist air and hydrolysis kinetics in argon with humidity of RH1.5% for polycrystalline LiH powders and sintered bulks were investigated by X-ray diffraction, Raman spectroscopy and gravimetry. The results showed that the hydrolysis products made up a layered structure of LiOH•H2O/LiOH/Li2O from surface of the sample to inside. In low humid argon atmosphere, the primary hydrolysis product was Li2O rather than LiOH. The hydrolysis kinetic curves of LiH bulks present a paralinear shape, which could be explained by the “Layer Diffusion Control" model. While a three-stage hydrolysis kinetic profile was observed for LiH powders under the same experimental conditions. The first two sections were similar to that of the bulk samples, and the third section also presents a linear reaction kinetics but with a smaller reaction rate compared to the second section because of a larger exothermic effect for the hydrolysis reaction of LiH powder.

The effect of Gamma Irradiation on the Nutritional Properties of Functional Products of the Green Banana

Banana is one of the most consumed fruits in the tropics and subtropics. Brazil accounts for about 9% of the world banana production. However, the production losses are as high as 30 to 40% and even much higher in some developing countries. The green banana flour is a complex carbohydrate source, including a high total starch (73.4%), resistant starch (17.5%) with functional properties. Gamma irradiation is considered to be an alternative method for food preservation. It has been performed due to the need of extending the shelf - life of foods, whilst maintaining their safety and avoiding one of the main concerns: the nutrient loss. In this work data about on the effects of ionizing radiation on the physicochemical analysis (carbohydrate, proteins, lipids, alimentary fiber, moistures and ashes) of Brazilian functional products (biscuits and bread) of the green banana pulp are presented. The caloric value was calculated. No significant difference was observed between the samples of irradiated and non – irradiated green banana biscuits with the following determinations: carbohydrates, proteins, alimentary fiber and ashes. Only a small significant difference was found in lipids (macronutrients). The results of physical chemical analysis of the irradiated and non- irradiated green banana bread non- irradiated showed no significant difference with the following determinations: carbohydrates, lipids (macronutrients), moisture, ashes and caloric value. A small difference was found in proteins (macronutrients). Irradiation of functional products (biscuits and bread) with doses of 1 and 3kGy maintained their original macronutrients content, showing good radioresistance.

Evaluation of Eating Habits among Portuguese University Students: A Preliminary Study

Portuguese diet has been gradually diverging from the basic principles of healthy eating, leading to an unbalanced dietary pattern which, associated with increasing sedentary lifestyle, has a negative impact on public health. The main objective of this work was to characterize the dietary habits of university students in Viseu, Portugal. The study consisted of a sample of 80 university students, aged between 18 and 28 years. Anthropometric data (weight (kg) and height (m)) were collected and Body Mass Index (BMI) was calculated. The dietary habits were assessed through a three-day food record and the software Medpoint was used to convert food into energy and nutrients. The results showed that students present a normal body mass index. Female university students made a higher number of daily meals than male students, and these last skipped breakfast more frequently. The values of average daily intake of energy, macronutrients and calcium were higher in males. The food pattern was characterized by a predominant consumption of meat, cereal, fats and sugar. Dietary intake of dairy products, fruits, vegetables and legumes does not meet the recommendations, revealing inadequate food habits such as hypoglycemic, hyperprotein and hyperlipidemic diet. Our findings suggest that preventive interventions should be focus in promoting healthy eating habits and physical activity in adulthood.

Determination of the Specific Activity of Soil and Fertilizers in Sergipe - Brazil

Measurements of radioactivity in the environment is of great importance to monitor and control the levels of radiation to which man is exposed directly or indirectly. It is necessary to show that regardless of working or being close to nuclear power plants, people are daily in contact with some amount of radiation from the actual environment and food that are ingested, contradicting the view of most of them. The aim of this study was to analyze the rate of natural and artificial radiation from radionuclides present in cement, soil and fertilizers used in Sergipe State – Brazil. The radionuclide activitiesmeasured all samples arebelow the Brazilian limit of the exclusion and exemption criteria from the requirement of radiation protection.It was detected Be-7 in organic fertilizers that means a short interval between the brewing processes for use in agriculture. It was also detected an unexpected Cs-137 in some samples; however its activities does not represent risk for the population. Th-231 was also found in samples of soil and cement in the state of Sergipe that is an unprecedented result.

Efficient Boosting-Based Active Learning for Specific Object Detection Problems

In this work, we present a novel active learning approach for learning a visual object detection system. Our system is composed of an active learning mechanism as wrapper around a sub-algorithm which implement an online boosting-based learning object detector. In the core is a combination of a bootstrap procedure and a semi automatic learning process based on the online boosting procedure. The idea is to exploit the availability of classifier during learning to automatically label training samples and increasingly improves the classifier. This addresses the issue of reducing labeling effort meanwhile obtain better performance. In addition, we propose a verification process for further improvement of the classifier. The idea is to allow re-update on seen data during learning for stabilizing the detector. The main contribution of this empirical study is a demonstration that active learning based on an online boosting approach trained in this manner can achieve results comparable or even outperform a framework trained in conventional manner using much more labeling effort. Empirical experiments on challenging data set for specific object deteciton problems show the effectiveness of our approach.

Frozen Fish: Control of Glazing Operation

Glazing is a process used to reduce undesirable drying or dehydration of fish during frozen or cold storage. To evaluate the effect of the time/ temperature binomial of the cryogenic frozen tunnel in the amount of glazing watera Central Composite Rotatable Design was used, with application of the Response Surface Methodology. The results reveal that the time/ temperature obtained for pink cusk-eel in experimental conditions for glazing water are similar to the industrial process, but for red fish and merluza the industrial process needs some adjustments. Control charts were established and implementedto control the amount of glazing water on sardine and merluza. They show that the freezing process was statistically controlled but there were some tendencies that must be analyzed, since the trend of sample mean values approached either of the limits, mainly in merluza. Thus, appropriate actions must be taken, in order to improve the process.

A Real-Time Specific Weed Recognition System Using Statistical Methods

The identification and classification of weeds are of major technical and economical importance in the agricultural industry. To automate these activities, like in shape, color and texture, weed control system is feasible. The goal of this paper is to build a real-time, machine vision weed control system that can detect weed locations. In order to accomplish this objective, a real-time robotic system is developed to identify and locate outdoor plants using machine vision technology and pattern recognition. The algorithm is developed to classify images into broad and narrow class for real-time selective herbicide application. The developed algorithm has been tested on weeds at various locations, which have shown that the algorithm to be very effectiveness in weed identification. Further the results show a very reliable performance on weeds under varying field conditions. The analysis of the results shows over 90 percent classification accuracy over 140 sample images (broad and narrow) with 70 samples from each category of weeds.