Economic Geographical Analysis of The Finnish Paper Industry

The purpose of this academic economic geographical dissertation is to study and describe how competitiveness in the Finnish paper industry has developed during 2001–2008. During these years, the Finnish paper industry has faced economically challenging times. This dissertation attempts to fill the existing gap between theoretical and empirical discussions concerning economic geographical issues in the paper industry. The main research questions are: How have the supply chain costs and margins developed during 2001–2008? How do sales prices, transportation, and fixed and variable costs correlate with gross margins in a spatial context? The research object for this case study is a typical large Finnish paper mill that exports over 90 % of its production. The economic longitudinal research data were obtained from the case mill’s controlled economic system and, correlation (R2) analysis was used as the main research method. The time series data cover monthly economic and manufacturing observations from the mill from 2001 to 2008. The study reveals the development of prices, costs and transportation in the case mill, and it shows how economic variables correlate with the paper mills’ gross margins in various markets in Europe. The research methods of economic geography offer perspectives that pay attention to the spatial (market) heterogeneity. This type of research has been quite scarce in the research tradition of Finnish economic geography and supply chain management. This case study gives new insight into the research tradition of Finnish economic geography and supply chain management and its applications. As a concrete empirical result, this dissertation states that the competitive advantages of the Finnish paper industry were significantly weakened during 2001–2008 by low paper prices, costly manufacturing and expensive transportation. Statistical analysis expose that, in several important markets, transport costs lower gross margins as much as decreasing paper prices, which was a new finding. Paper companies should continuously pay attention to lowering manufacturing and transporting costs to achieve more profitable economic performance. The location of a mill being far from markets clearly has an economic impact on paper manufacturing, as paper demand is decreasing and oversupply is pressuring paper prices down. Therefore, market and economic forecasting in the paper industry is advantageous at the country and product levels while simultaneously taking into account the economic geographically specific dimensions.

Employer Branding in Power Industry

Companies invest in employer branding in order to get good applicants, retain employees and create the image of a great employer. Employer branding will become more prominent in the future because companies strive to gain competitive advantage. Power industry is an internationally remarkable field of business. Energy and the solutions of power technology are always needed and there is a major need for new experts in power industry. The competition of talented workforce will increase because of the decrease in working-age population. The fundamental purpose of this study is to examine what kind of motives and practices company has for employer branding in power industry. The objective is to find out the benefits of employer branding and how it is targeted towards potential and current employees. In addition, the aim is to examine whether companies see employer branding as a process and what kind of processes they have for employer branding. The theoretical contribution of this study is based on literature review, which provides a better understanding of employer branding. The empirical part is a qualitative case study of two large and international companies in the field of power industry. Employer branding in the case companies is examined using theme interviews. According to this study, employer branding is a significant part of companies’ business in power industry. The main motives for employer branding are better employer image, more efficient recruitment and improved job satisfaction. Employer branding is communicated and targeted according to target group. Recruitment and educational co-operation are the main objects of employer branding towards potential employees, whereas training and development are an essential part of employer branding towards current employees. This study also discovers that there is some kind of process aspect in the background of employer branding.

Convergence in Industry Evolution

The objective of the thesis is to enhance understanding of the evolution of convergence. Previous research has shown that the technological interfaces between distinct industries are one of the major sources of new radical cross-industry innovations. Despite the fact that convergence in industry evolution has attracted a substantial managerial interest, the conceptual confusion within the field of convergence exists. Firstly, this study clarifies the convergence phenomenon and its impact to industry evolution. Secondly, the study creates novel patent analysis methods to analyze technological convergence and provide tools for anticipating the early stages of convergence. Overall the study combines the industry evolution perspective and the convergence view of industrial evolution. The theoretical background for the study consists of the industry life cycle theories, technology evolution, and technological trajectories. The study links several important concepts in analyzing industry evolution, technological discontinuities, path-dependency, technological interfaces as a source of industry transformation, and the evolutionary stagesof convergence. Based on reviewing the literature a generic understanding of industry transformation and industrial dynamics was generated. In the convergence studies, the theoretical basis is in the discussion of different convergence types and their impacts on industry evolution, and in anticipating and monitoring the stages of convergence. The study is divided in two parts. The first part gives a general overview, and the second part comprises eight research publications. Our case study is based historically on two very distinct industries of the paper and electronics companies as a test environment to evaluate the importance of emerging business sectors and technological convergence as a source of industry transformation. Both qualitative and quantitative research methodology are utilized. The results of this study reveal that technological convergence and complementary innovations from different fields have significant effect to the emerging new business sector formation. The patent-based indicators in the analysis of technological convergence can be utilized on analyzing technology competition, capability and competence development, knowledge accumulation, knowledge spill-overs, and technology-based industry transformation. The patent-based indicators can provide insights to the future competitive environment. Results and conclusions from empirical part seem not be in conflict with real observations in the industry.

POPULATION STRUCTURE AND PRODUCTION OF COPAIBA OLEORESIN BETWEEN VALLEYS AND HILLSIDES OF THE MINING AREA OFTROMBETAS RIVER - PARÁ1

ABSTRACT We aimed in this work to study natural populations of copaiba (Copaifera multijuga Hayne) on the Monte Branco mountain at Porto Trombetas-PA, in order to support sustainable management and the exploitation of oleoresin from copaiba. We studied the population structure of copaiba on hillsides and valleys of the south face of Monte Branco, within Saracá Taquera National Forest, where bauxite ore was extracted in the biennium 2013-2014 by Mineração Rio do Norte (MRN). We produced a 100% forest inventory of the specie and of oleoresin extraction in order to quantify the potential production of the remaining area. The density of copaiba individuals with DBH > 30 cm was 0.33 individuals per hectare in the hillside and 0.25 individuals per hectare in the valley. Both environments presented a density of 0.28 individuals per hectare. The average copaiba oleoresin yield was 0.661±0.334 liters in the hillside and 0.765±0.280 liters in the valley. The average value of both environments together (hillside and valley) was 0.714±0.218 liters. From all individuals with DBH over 30 cm, 38 (58%) produced some amount of oleoresin, averaging 1.113±0.562 liters in the hillside, 1.329±0.448 liters in the valley and 1.190±0.355 liters in both environments together. The results show the need for planning the use of the surroundings of the study area in order to reach the required volume of copaiba to make feasible the sustainable management of oleoresin extraction in the region.

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.

The success factors of the Danish energy service industry

The objective of the research was to understand the success factors of the Danish energy service industry. The research phenomenon was studied greatly but the aim was to examine it from the service logic point of view. The research was threefold and it examined the phenomena from the company, industrial and national levels. The purpose of the multi-level study was to understand all the success factors and to examine how they are combined together. First, the research problem was approached through the literature review. After that, the empirical part of the study was conducted as a case study and the data was collected by theme interviews. The collected data was analyzed through theoretical point of view and compared with earlier studies. This study shows that the most important success factor was the country, because it has affected to the other aspects of the success. Because the actors of the industry are linked together tightly, communication and common understanding of business is essential to the industry success. The new energy technologies do not produce directly added value for the customers. This has sifted energy business towards service business, and the customers have been included in the value creation process.

Técnicas de mineração de dados para análise da precipitação pluvial decenal no Rio Grande do Sul

O objetivo deste trabalho foi analisar o comportamento espaçotemporal da precipitação pluvial no Estado do Rio Grande do Sul, entre os decênios de 1987-1996 e 1997-2006, por meio de técnicas de mineração de dados. As séries históricas foram adquiridas no sistema de informações hidrológicas Hidroweb. A metodologia utilizada teve como base o modelo CRISP-DM (Cross Industry Standard Process for Data Mining). Foram definidas áreas pluviometricamente homogêneas para os decênios de 1987-1996 e 1997-2006. Em seguida, pela sobreposição dos agrupamentos obtidos para os dois períodos, encontraram-se seis zonas comuns aos dois decênios (A a F). As alterações ocorridas foram avaliadas nas seguintes escalas temporais: anual, sazonal e mensalmente. Os resultados indicaram incrementos significativos (20 a 240 mm) na precipitação anual em todas as zonas, exceto na zona A. Na análise sazonal, as variações foram aleatórias, sendo que, na primavera, todas as zonas apresentaram incremento significativo (44 a 142 mm). Na análise mensal, destaca-se a redução ocorrida no mês de janeiro em todas as zonas, exceto na E. Nos demais meses, as variações foram aleatórias. Os resultados mostram que, entre os decênios, houve uma alteração no volume da precipitação pluvial em todas as escalas temporais analisadas.

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.

Anaerobic co-digestion of crude glycerin and starch industry effluent

The Brazil's Biodiesel Production and Use Program introduces biodiesel in the Brazilian energy matrix, bringing along the perspective of a growth of the glycerin offer, co-product generated in the proportion of 10 kg for each 100 L of biodiesel. The aim of this study was to evaluate the addition of crude glycerin in the anaerobic digestion of cassava starch industry effluent (cassava wastewater), in a horizontal semi-continuous flow reactor of one phase in laboratory scale. It was used a reactor with a 8.77 L of useful volume, a medium support for corrugated conduit of polyvinyl chloride (PVC), temperature of 261 ºC, fed with cassava wastewater and glycerin, with hydraulic detention times of 4 and 5 days and increasing volumetric organic load of 3.05; 9.32; 14.83 and 13.59 g COD L-1 d-1, obtained with the addition of glycerin at 0; 2; 3 and 2% (v/v), respectively. The average removal efficiencies of TS and TVS were decreasing from the addition of glycerin to the cassava wastewater, averaging 81.19 to 55.58% for TS and 90.21 to 61.45% for TVS. The addition of glycerin at 2% increased the biogas production compared to the control treatment, reaching 1.979 L L-1 d-1. The biogas production as a function of the consumed COD was higher for the control treatment than for the treatments with addition of glycerin, which indicates lower conversion of organic matter into biogas.

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.

Anaerobic reactors with biofilter and different diameter-length ratios in cassava starch industry wastewater treatment

The use of anaerobic reactors with media support in the treatment of wastewater from the cassava starch industry has emerged as a viable option because it allows the application of high organic loads and a significant reduction of the HDT needed for the treatment. This research aimed at studying the process of biodigestion in two anaerobic reactors with bamboo support, in the treatment of effluent of cassava starch, by evaluating their performance. The two reactors used present the following diameter: length ratio, 1:6 and 1:3. The organic loads applied to the systems were 0.519, 1.156, 1.471, 3.049, 4.347, 4.708 and 5.601g.L-1.d-1. Regarding the efficiency of removal of COD, TS and TVS, no statistically significant differences were obtained between the reactors. The two systems evaluated showed a stable behavior with respect to the VA/TA (volatile acidity/total alkalinity) for all submitted loads. The reactors tended to the maintenance of biogas production as a function of consumed COD for the last three organic loads applied, indicating an ability to withstand higher organic loads.

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.