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.

Soil chiseling and fertilizer location in sugarcane ratoon cultivation

While the pre-harvest sugarcane burning is a disused practice, green harvest requires changes concerning ratoon cultivation due to the presence of a thick layer of straw. The experiment, conducted in a mechanical green harvesting area cultivated with sugarcane, consisted of two stages: in the first stage, the mechanical straw cutting performance of flat disks with different geometry edges was evaluated, considering two types of disks and 10 replications in a completely randomized design; in the second stage, the effect of soil chiseling on both sides of planting lines, using shanks with straw cutting flat disks, was assessed, as well as fertilizer deposition form. The experimental design in the second stage was completely randomized, with seven treatments and five replications. Treatments consisted of a combination of two straw cutting disks (smooth or toothed edge), chiseling presence or absence, and fertilizer deposition forms (broadcast, on the planting line, and incorporated into chiseling furrows). The toothed disk differed from the smooth one, presenting lower values of horizontal and vertical forces, and torque. The agroindustrial variables pol (%), brix (%), fiber (%), and ATR (kg Mg-1) were not influenced by the fertilizer deposition form and soil chiseling. However, the localized fertilizer deposition increased crop yield when compared with broadcast fertilization.

Strategic outsourcing of R&D: The location-specific advantages of India to the pharmaceutical industry

Companies are increasingly under pressure to be more efficient both in terms of costs and overall performance and thus, they seek new ways to develop their products and innovate. For pharmaceutical industry it can take several decades to launch a new drug to the markets. Since pharmaceutical industry is one of the most research-intensive industries, is outsourcing one way to enhance the R&D processes of such companies. It is said that outsourcing to offshore locations is vastly more challenging and complicated than any other exporting activity or inter-company relationship that has evoked a lot of discussion. By outsourcing strategically, companies must also thoroughly focus on transaction costs and core competences. Today, the suppliers are looked for beyond national boundaries and furthermore, the location of the outsourcing activity must also be thoroughly considered. Consequently, the purpose of this study is to analyze what is known of strategic outsourcing of pharmaceutical R&D to India. In order to meet the purpose of the study, this study tries to answer three sub-questions set to it: first, what is strategic outsourcing, second, why pharmaceutical companies utilize strategic outsourcing of R&D and last, why pharmaceutical companies select India as the location for outsourcing their R&D. The study is a qualitative study. The purpose of the study was approached by a literature review with systematic elements and sub-questions were analyzed through different relevant theories, such as theory of transaction costs, core competences and location advantages. Applicable academic journal articles were comprehensively included in the study. The data was collected from electronic journal article databases using key words and almost only peer-reviewed, as new as possible articles were included. Also both the reference list of the included articles and article recommendations from professionals generated more articles for inclusion. The data was analyzed through thematization that resulted in themes that illuminate the purpose of the study and sub-questions. As an outcome of the analysis, each of the theory chapters in the study represents one sub-question. The literature used in this study revealed that strategic outsourcing of R&D is increasingly used in pharmaceutical industry and the major motives to practice it has to do with lowering costs, accessing skilled labor, resources and knowledge and enhancing their quality while speeding up the introduction of new drugs. Mainly for the above-mentioned motives India is frequently chosen as the target location for pharma outsourcers. Still, the literature is somewhat incomplete in this complex phenomenon and more research is needed.

The effects of location, feedstock availability, and supply-chain logistics on the greenhouse gas emissions of forest-biomass energy utilization in Finland

Forest biomass represents a geographically distributed feedstock, and geographical location affects the greenhouse gas (GHG) performance of a given forest-bioenergy system in several ways. For example, biomass availability, forest operations, transportation possibilities and the distances involved, biomass end-use possibilities, fossil reference systems, and forest carbon balances all depend to some extent on location. The overall objective of this thesis was to assess the GHG emissions derived from supply and energy-utilization chains of forest biomass in Finland, with a specific focus on the effect of location in relation to forest biomass’s availability and the transportation possibilities. Biomass availability and transportation-network assessments were conducted through utilization of geographical information system methods, and the GHG emissions were assessed by means of lifecycle assessment. The thesis is based on four papers in which forest biomass supply on industrial scale was assessed. The feedstocks assessed in this thesis include harvesting residues, smalldiameter energy wood and stumps. The principal implication of the findings in this thesis is that in Finland, the location and availability of biomass in the proximity of a given energyutilization or energy-conversion plant is not a decisive factor in supply-chain GHG emissions or the possible GHG savings to be achieved with forest-biomass energy use. Therefore, for the greatest GHG reductions with limited forest-biomass resources, energy utilization of forest biomass in Finland should be directed to the locations where most GHG savings are achieved through replacement of fossil fuels. Furthermore, one should prioritize the types of forest biomass with the lowest direct supply-chain GHG emissions (e.g., from transport and comminution) and the lowest indirect ones (in particular, soil carbon-stock losses), regardless of location. In this respect, the best combination is to use harvesting residues in combined heat and power production, replacing peat or coal.

Scalable algorithms for height field illumination

Global illumination algorithms are at the center of realistic image synthesis and account for non-trivial light transport and occlusion within scenes, such as indirect illumination, ambient occlusion, and environment lighting. Their computationally most difficult part is determining light source visibility at each visible scene point. Height fields, on the other hand, constitute an important special case of geometry and are mainly used to describe certain types of objects such as terrains and to map detailed geometry onto object surfaces. The geometry of an entire scene can also be approximated by treating the distance values of its camera projection as a screen-space height field. In order to shadow height fields from environment lights a horizon map is usually used to occlude incident light. We reduce the per-receiver time complexity of generating the horizon map on N N height fields from O(N) of the previous work to O(1) by using an algorithm that incrementally traverses the height field and reuses the information already gathered along the path of traversal. We also propose an accurate method to integrate the incident light within the limits given by the horizon map. Indirect illumination in height fields requires information about which other points are visible to each height field point. We present an algorithm to determine this intervisibility in a time complexity that matches the space complexity of the produced visibility information, which is in contrast to previous methods which scale in the height field size. As a result the amount of computation is reduced by two orders of magnitude in common use cases. Screen-space ambient obscurance methods approximate ambient obscurance from the depth bu er geometry and have been widely adopted by contemporary real-time applications. They work by sampling the screen-space geometry around each receiver point but have been previously limited to near- field effects because sampling a large radius quickly exceeds the render time budget. We present an algorithm that reduces the quadratic per-pixel complexity of previous methods to a linear complexity by line sweeping over the depth bu er and maintaining an internal representation of the processed geometry from which occluders can be efficiently queried. Another algorithm is presented to determine ambient obscurance from the entire depth bu er at each screen pixel. The algorithm scans the depth bu er in a quick pre-pass and locates important features in it, which are then used to evaluate the ambient obscurance integral accurately. We also propose an evaluation of the integral such that results within a few percent of the ray traced screen-space reference are obtained at real-time render times.

Efficient Optimization Algorithms for Nonlinear Data Analysis

Identification of low-dimensional structures and main sources of variation from multivariate data are fundamental tasks in data analysis. Many methods aimed at these tasks involve solution of an optimization problem. Thus, the objective of this thesis is to develop computationally efficient and theoretically justified methods for solving such problems. Most of the thesis is based on a statistical model, where ridges of the density estimated from the data are considered as relevant features. Finding ridges, that are generalized maxima, necessitates development of advanced optimization methods. An efficient and convergent trust region Newton method for projecting a point onto a ridge of the underlying density is developed for this purpose. The method is utilized in a differential equation-based approach for tracing ridges and computing projection coordinates along them. The density estimation is done nonparametrically by using Gaussian kernels. This allows application of ridge-based methods with only mild assumptions on the underlying structure of the data. The statistical model and the ridge finding methods are adapted to two different applications. The first one is extraction of curvilinear structures from noisy data mixed with background clutter. The second one is a novel nonlinear generalization of principal component analysis (PCA) and its extension to time series data. The methods have a wide range of potential applications, where most of the earlier approaches are inadequate. Examples include identification of faults from seismic data and identification of filaments from cosmological data. Applicability of the nonlinear PCA to climate analysis and reconstruction of periodic patterns from noisy time series data are also demonstrated. Other contributions of the thesis include development of an efficient semidefinite optimization method for embedding graphs into the Euclidean space. The method produces structure-preserving embeddings that maximize interpoint distances. It is primarily developed for dimensionality reduction, but has also potential applications in graph theory and various areas of physics, chemistry and engineering. Asymptotic behaviour of ridges and maxima of Gaussian kernel densities is also investigated when the kernel bandwidth approaches infinity. The results are applied to the nonlinear PCA and to finding significant maxima of such densities, which is a typical problem in visual object tracking.

Evaluation of Location Intelligence exploitation in capital-intensive business

As technology has developed it has increased the number of data produced and collected from business environment. Over 80% of that data includes some sort of reference to geographical location. Individuals have used that information by utilizing Google Maps or different GPS devices, however such information has remained unexploited in business. This thesis will study the use and utilization of geographically referenced data in capital-intensive business by first providing theoretical insight into how data and data-driven management enables and enhances the business and how especially geographically referenced data adds value to the company and then examining empirical case evidence how geographical information can truly be exploited in capital-intensive business and what are the value adding elements of geographical information to the business. The study contains semi-structured interviews that are used to scan attitudes and beliefs of an organization towards the geographic information and to discover fields of applications for the use of geographic information system within the case company. Additionally geographical data is tested in order to illustrate how the data could be used in practice. Finally the outcome of the thesis provides understanding from which elements the added value of geographical information in business is consisted of and how such data can be utilized in the case company and in capital-intensive business.

Virtual Runtime Application Partitions for Resource Management in Massively Parallel Architectures

This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.

Genesis and Evolution of Brittle Structures In Southwestern Finland and Western South Africa. Insights into Fault Reactivation, Fluid Flow and Structural Maturity in Precambrian Cratons

The bedrock of old crystalline cratons is characteristically saturated with brittle structures formed during successive superimposed episodes of deformation and under varying stress regimes. As a result, the crust effectively deforms through the reactivation of pre-existing structures rather than by through the activation, or generation, of new ones, and is said to be in a state of 'structural maturity'. By combining data from Olkiluoto Island, southwestern Finland, which has been investigated as the potential site of a deep geological repository for high-level nuclear waste, with observations from southern Sweden, it can be concluded that the southern part of the Svecofennian shield had already attained structural maturity during the Mesoproterozoic era. This indicates that the phase of activation of the crust, i.e. the time interval during which new fractures were generated, was brief in comparison to the subsequent reactivation phase. Structural maturity of the bedrock was also attained relatively rapidly in Namaqualand, western South Africa, after the formation of first brittle structures during Neoproterozoic time. Subsequent brittle deformation in Namaqualand was controlled by the reactivation of pre-existing strike-slip faults.In such settings, seismic events are likely to occur through reactivation of pre-existing zones that are favourably oriented with respect to prevailing stresses. In Namaqualand, this is shown for present day seismicity by slip tendency analysis, and at Olkiluoto, for a Neoproterozoic earthquake reactivating a Mesoproterozoic fault. By combining detailed field observations with the results of paleostress inversions and relative and absolute time constraints, seven distinctm superimposed paleostress regimes have been recognized in the Olkiluoto region. From oldest to youngest these are: (1) NW-SE to NNW-SSE transpression, which prevailed soon after 1.75 Ga, when the crust had sufficiently cooled down to allow brittle deformation to occur. During this phase conjugate NNW-SSE and NE-SW striking strike-slip faults were active simultaneous with reactivation of SE-dipping low-angle shear zones and foliation planes. This was followed by (2) N-S to NE-SW transpression, which caused partial reactivation of structures formed in the first event; (3) NW-SE extension during the Gothian orogeny and at the time of rapakivi magmatism and intrusion of diabase dikes; (4) NE-SW transtension that occurred between 1.60 and 1.30 Ga and which also formed the NW-SE-trending Satakunta graben located some 20 km north of Olkiluoto. Greisen-type veins also formed during this phase. (5) NE-SW compression that postdates both the formation of the 1.56 Ga rapakivi granites and 1.27 Ga olivine diabases of the region; (6) E-W transpression during the early stages of the Mesoproterozoic Sveconorwegian orogeny and which also predated (7) almost coaxial E-W extension attributed to the collapse of the Sveconorwegian orogeny. The kinematic analysis of fracture systems in crystalline bedrock also provides a robust framework for evaluating fluid-rock interaction in the brittle regime; this is essential in assessment of bedrock integrity for numerous geo-engineering applications, including groundwater management, transient or permanent CO2 storage and site investigations for permanent waste disposal. Investigations at Olkiluoto revealed that fluid flow along fractures is coupled with low normal tractions due to in-situ stresses and thus deviates from the generally accepted critically stressed fracture concept, where fluid flow is concentrated on fractures on the verge of failure. The difference is linked to the shallow conditions of Olkiluoto - due to the low differential stresses inherent at shallow depths, fracture activation and fluid flow is controlled by dilation due to low normal tractions. At deeper settings, however, fluid flow is controlled by fracture criticality caused by large differential stress, which drives shear deformation instead of dilation.