NATURAL REGENERATION STRATUM AS AN INDICATOR OF RESTORATION IN AREA OF ENVIRONMENTAL COMPENSATION FOR MINING LIMESTONE, MUNICIPALITY OF BARROSO, MG, BRAZIL

ABSTRACT This study was conducted in a forest under restoration process, which belongs to the company Holcim Brasil S/A, in the municipality of Barroso, state of Minas Gerais (21º00'to 22º00'S and 43º00' to 44º00'W), where 40 plots (2 x 2 m) were set, spaced at 10 m, forming eight strata parallel to the watercourse present in the area. Floristic composition and natural regeneration stratum were characterized, and the formed strata allowed evaluating whether the riparian vegetation and watercourse influence on the local regeneration. It was found 162 individuals of 13 families, 18 genera and 22 species, and 10,125 individuals/ha were estimated. Successional classes from pioneer and early secondary and zoochory dispersion syndrome prevailed among species and individuals. The watercourse and riparian vegetation did not exercise significant influence (p> 0.05) on the number of species and regenerating individuals among the different strata of the forest. The diversity index of Shannon-Wiener (H') and equability of Pielou (J') were 2.691 and 0.870, respectively. The species Psidium guajava and Myrtaceae families presented the highest VI (value of importance). Natural regeneration analysis showed the low floristic diversity in the area, suggesting that corrective management actions should be adopted.

Measuring Cost of Poor Quality in Industrial Electronics

Quality is not only free but it can be a profit maker. Every dollar that is not spent on doing things wrong becomes a dollar right on the bottom line. The main objective of this thesis is to give an answer on how cost of poor quality can be measured theoretically correctly. Different calculation methods for cost of poor quality are presented and discussed in order to give comprehensive picture about measurement process. The second objective is to utilize the knowledge from the literature review and to apply it when creating a method for measuring cost of poor quality in supplier performance rating. Literature review indicates that P-A-F model together with ABC methodology provides a mean for quality cost calculations. These models give an answer what should be measured and how this measurement should be carried out. However, when product or service quality costs are incurred when quality character derivates from target value, then QLF seems to be most appropriate methodology for quality cost calculation. These methodologies were applied when creating a quality cost calculation method for supplier performance ratings.

A decision support system for cost determination in grain storage facility operations

Many research works have being carried out on analyzing grain storage facility costs; however a few of them had taken into account the analysis of factors associated to all pre-processing and storage steps. The objective of this work was to develop a decision support system for determining the grain storage facility costs and utilization fees in grain storage facilities. The data of a CONAB storage facility located in Ponta Grossa - PR, Brazil, was used as input of the system developed to analyze its specific characteristics, such as amount of product received and stored throughout the year, hourly capacity of drying, cleaning, and receiving, and dispatch. By applying the decision support system, it was observed that the reception and expedition costs were exponentially reduced as the turnover rate of the storage increased. The cleaning and drying costs increased linearly with grain initial moisture. The storage cost increased exponentially as the occupancy rate of the storage facility decreased.

Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants

This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.

Efficiency of distinct data mining algorithms for classifying stress level in piglets from their vocalization

Among the challenges of pig farming in today's competitive market, there is factor of the product traceability that ensures, among many points, animal welfare. Vocalization is a valuable tool to identify situations of stress in pigs, and it can be used in welfare records for traceability. The objective of this work was to identify stress in piglets using vocalization, calling this stress on three levels: no stress, moderate stress, and acute stress. An experiment was conducted on a commercial farm in the municipality of Holambra, São Paulo State , where vocalizations of twenty piglets were recorded during the castration procedure, and separated into two groups: without anesthesia and local anesthesia with lidocaine base. For the recording of acoustic signals, a unidirectional microphone was connected to a digital recorder, in which signals were digitized at a frequency of 44,100 Hz. For evaluation of sound signals, Praat® software was used, and different data mining algorithms were applied using Weka® software. The selection of attributes improved model accuracy, and the best attribute selection was used by applying Wrapper method, while the best classification algorithms were the k-NN and Naive Bayes. According to the results, it was possible to classify the level of stress in pigs through their vocalization.

Using data mining to identify factors that influence the degree of leg injuries in broilers

Locomotor problems prevent the bird to move freely, jeopardizing the welfare and productivity, besides generating injuries on the legs of chickens. The objective of this study was to evaluate the influence of age, use of vitamin D, the asymmetry of limbs and gait score, the degree of leg injuries in broilers, using data mining. The analysis was performed on a data set obtained from a field experiment in which it was used two groups of birds with 30 birds each, a control group and one treated with vitamin D. It was evaluated the gait score, the asymmetry between the right and left toes, and the degree of leg injuries. The Weka ® software was used in data mining. In particular, C4.5 algorithm (also known as J48 in Weka environment) was used for the generation of a decision tree. The results showed that age is the factor that most influences the degree of leg injuries and that the data from assessments of gait score were not reliable to estimate leg weakness in broilers.

Low cost driver device for microclimate maintenance in the pre-milking of dairy cattle

Due to the importance of the environment on animal production and thus environmental control, the study aims to build a system for monitoring and control the meteorological variables, temperature and relative humidity, low cost, which can be associated with an evaporative cooling system (ECS). The system development included all the stages of assembly, test and laboratory calibration, and later the validation of the equipment carried in the field. The validation step showed results which allowed concluding that the system can be safely used in the monitoring of these variables. The controller was efficient in management of the microclimate in the waiting corral and allowed the maintenance of the air temperature within the comfort range for dairy cattle in pre-milking with averaged 25.09 ºC during the afternoon. The equipment showed the lower cost (R$ 325.76) when compared to other middle market (R$ 450.00).

Data mining techniques for identification of spectrally homogeneous areas using NDVI temporal profiles of soybean crop

The aim of this study was to group temporal profiles of 10-day composites NDVI product by similarity, which was obtained by the SPOT Vegetation sensor, for municipalities with high soybean production in the state of Paraná, Brazil, in the 2005/2006 cropping season. Data mining is a valuable tool that allows extracting knowledge from a database, identifying valid, new, potentially useful and understandable patterns. Therefore, it was used the methods for clusters generation by means of the algorithms K-Means, MAXVER and DBSCAN, implemented in the WEKA software package. Clusters were created based on the average temporal profiles of NDVI of the 277 municipalities with high soybean production in the state and the best results were found with the K-Means algorithm, grouping the municipalities into six clusters, considering the period from the beginning of October until the end of March, which is equivalent to the crop vegetative cycle. Half of the generated clusters presented spectro-temporal pattern, a characteristic of soybeans and were mostly under the soybean belt in the state of Paraná, which shows good results that were obtained with the proposed methodology as for identification of homogeneous areas. These results will be useful for the creation of regional soybean "masks" to estimate the planted area for this crop.

Vocalization data mining for estimating swine stress conditions

This study aimed to identify differences in swine vocalization pattern according to animal gender and different stress conditions. A total of 150 barrow males and 150 females (Dalland® genetic strain), aged 100 days, were used in the experiment. Pigs were exposed to different stressful situations: thirst (no access to water), hunger (no access to food), and thermal stress (THI exceeding 74). For the control treatment, animals were kept under a comfort situation (animals with full access to food and water, with environmental THI lower than 70). Acoustic signals were recorded every 30 minutes, totaling six samples for each stress situation. Afterwards, the audios were analyzed by Praat® 5.1.19 software, generating a sound spectrum. For determination of stress conditions, data were processed by WEKA® 3.5 software, using the decision tree algorithm C4.5, known as J48 in the software environment, considering cross-validation with samples of 10% (10-fold cross-validation). According to the Decision Tree, the acoustic most important attribute for the classification of stress conditions was sound Intensity (root node). It was not possible to identify, using the tested attributes, the animal gender by vocal register. A decision tree was generated for recognition of situations of swine hunger, thirst, and heat stress from records of sound intensity, Pitch frequency, and Formant 1.

Generic Life Cycle Cost Model and Cost-effective Solutions

Life cycle costing (LCC) practices are spreading from military and construction sectors to wider area of industries. Suppliers as well as customers are demanding comprehensive cost knowledge that includes all relevant cost elements through the life cycle of products. The problem of total cost visibility is being acknowledged and the performance of suppliers is evaluated not just by low acquisition costs of their products, but by total value provided through the life time of their offerings. The main purpose of this thesis is to provide better understanding of product cost structure to the case company. Moreover, comprehensive theoretical body serves as a guideline or methodology for further LCC process. Research includes the constructive analysis of LCC related concepts and features as well as overview of life cycle support services in manufacturing industry. The case study aims to review the existing LCC practices within the case company and provide suggestions for improvements. It includes identification of most relevant life cycle cost elements, development of cost breakdown structure and generic cost model for data collection. Moreover, certain cost-effective suggestions are provided as well. This research should support decision making processes, assessment of economic viability of products, financial planning, sales and other processes within the case company.

Development of Cost Estimation with Feedback Information in EPCM Business

Target company of this study is a large machinery company, which is, inter alia, engaged in energy and pulp engineering, procurement and construction management (EPCM) supply business. The main objective of this study was to develop cost estimation of the target company by providing more accurate, reliable and up-to-date information through enterprise resource planning (ERP) system. Another objective was to find cost-effective methods to collect total cost of ownership information to support more informed supplier selection decision making. This study is primarily action-oriented, but also constructive, and it can be divided in two sections: theoretical literature review and empirical study on the abovementioned part of the target company’s business. Development of information collection is, in addition to literature review, based on nearly 30 qualitative interviews of employees at various organizational units, functions and levels at the target company. At the core of development was to make initial data more accurate, reliable and available, a necessary prerequisite for informed use of the information. Certain development suggestions and paths were presented in order to regain confidence in ERP system as information source by reorganizing work breakdown structure and by complementing mere cost information with quantitative, technical and scope information. Several methods to use the information ever more effectively were also discussed. While implementation of the development suggestions outreached the scope of this study, it was forwarded in test environment and interest groups.

Assessing the Environmental Value of Water Treatment Solutions in the Mining Industry

Environmental accountability has become a major source of competitive advantage for industrial companies, because customers consider it as relevant buying criterion. However, in order to leverage their environmental responsibility, industrial suppliers have to be able to demonstrate the environmental value of their products and services, which is also the aim of Kemira, a global water chemistry company considered in this study. The aim of this thesis is to develop a tool which Kemira can use to assess the environmental value of their solutions for the customer companies in mining industry. This study answers to questions on what kinds of methods to assess environmental impacts exist, and what kind of tool could be used to assess the environmental value of Kemira’s water treatment solutions. The environmental impacts of mining activities vary greatly between different mines. Generally the major impacts include the water related issues and wastes. Energy consumption is also a significant environmental aspect. Water related issues include water consumption and impacts in water quality. There are several methods to assess environmental impacts, for example life cycle assessment, eco-efficiency tools, footprint calculations and process simulation. In addition the corresponding financial value may be estimated utilizing monetary assessment methods. Some of the industrial companies considered in the analysis of industry best practices use environmental and sustainability assessments. Based on the theoretical research and conducted interviews, an Excel based tool utilizing reference data on previous customer cases and customer specific test results was considered to be most suitable to assess the environmental value of Kemira’s solutions. The tool can be used to demonstrate the functionality of Kemira’s solutions in customers’ processes, their impacts in other process parameters and their environmental and financial aspects. In the future, the tool may be applied to fit also Kemira’s other segments, not only mining industry.

The cost of excessive postoperative use of antimicrobials: the context of a public hospital

OBJECTIVE: To evaluate the improper use of antimicrobials during the postoperative period and its economic impact.METHODS: We conducted a prospective cohort study by collecting data from medical records of 237 patients operated on between 01/11/08 and 31/12/08.RESULTS: from the 237 patients with the information collected, 217 (91.56%) received antimicrobials. During the postoperative period, 125 (57.7%) patients received more than two antimicrobials. On average, 1.7 ± 0.6 antimicrobials were prescribed to patients, the most commonly prescribed antibiotic being cephalothin, in 41.5% (154) of cases. The direct cost of antimicrobial therapy accounted for 63.78% of all drug therapy, this large percentage being attributed in part to the extended antimicrobial prophylaxis. In the case of clean operations, where there was a mean duration of 5.2 days of antibiotics, antimicrobials represented 44.3% of the total therapy cost.CONCLUSION: The data illustrate the impact of overuse of antimicrobials, with questionable indications, creating situations that compromise patient safety and increasing costs in the assessed hospital.

Teaching project: a low-cost swine model for chest tube insertion training

Objective: to describe and evaluate the acceptance of a low-cost chest tube insertion porcine model in a medical education project in the southwest of Paraná, Brazil. Methods: we developed a low-cost and low technology porcine model for teaching chest tube insertion and used it in a teaching project. Medical trainees - students and residents - received theoretical instructions about the procedure and performed thoracic drainage in this porcine model. After performing the procedure, the participants filled a feedback questionnaire about the proposed experimental model. This study presents the model and analyzes the questionnaire responses. Results: seventy-nine medical trainees used and evaluated the model. The anatomical correlation between the porcine model and human anatomy was considered high and averaged 8.1±1.0 among trainees. All study participants approved the low-cost porcine model for chest tube insertion. Conclusion: the presented low-cost porcine model for chest tube insertion training was feasible and had good acceptability among trainees. This model has potential use as a teaching tool in medical education.