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.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Purchasing portfolio analysis and supplier classification

The purpose of the thesis is to classify suppliers and to enhance strategic purchasing in the case company. Supplier classification is conducted to fulfill the requirements of the company quality manual and international quality standards. To gain more benefit, a strategic purchasing tool, Kraljic’s purchasing portfolio and analytical hierarchy process are utilized for the base of supplier classification. Purchasing portfolio is used to give quick and easy visual insight on product group management form the viewpoint of purchasing. From the base on purchasing portfolio alternative purchasing and supplier strategies can be formed that enhance the strategic orientation of purchasing. Thus purchasing portfolio forces the company to orient on proactive and strategic purchasing. As a result a survey method for implementing purchasing portfolio in the company is developed that exploits analytical hierarchy process. Experts from the company appoint the categorization criteria and in addition, participate in the survey to categorize product groups on the portfolio. Alternative purchasing strategies are formed. Suppliers are classified depending on the importance and characteristics of the product groups supplied.

Evaluation of bursal lymphoid depletion: comparison between the conventional histology method and digital lymphocyte depletion evaluation system

Abstract: Fifty-five bursa of Fabricius (BF) were evaluated by optical microscopy for three different avian histopathologists (H1, H3 and H4) to determine the degree of lymphoid depletion. One histologist evaluated the same slides at two different times (H1 and H2) with four-months interval between the observations. The same BFs were evaluated using the system of Digital Lymphocyte Depletion Evaluation (ADDL), being performed by three differents operators of the system, not histopathologists. The results showed was a significant difference between the histopathologists and between the scores established by the same expert (H1 and H2). However, there were not significant differences between the scores with the ADDL system, obtained using ADDL. The results make clear the fragility of the subjective lymphocyte depletion score classification by the traditional histologic method, while the ADDL system proves to be more appropriated for the assessment of the lymphoid loss in the BF.

Covalidation of Integral Transforms and Method of Lines in Nonlinear Convection-Diffusion with Mathematica

The Mathematica system (version 4.0) is employed in the solution of nonlinear difusion and convection-difusion problems, formulated as transient one-dimensional partial diferential equations with potential dependent equation coefficients. The Generalized Integral Transform Technique (GITT) is first implemented for the hybrid numerical-analytical solution of such classes of problems, through the symbolic integral transformation and elimination of the space variable, followed by the utilization of the built-in Mathematica function NDSolve for handling the resulting transformed ODE system. This approach ofers an error-controlled final numerical solution, through the simultaneous control of local errors in this reliable ODE's solver and of the proposed eigenfunction expansion truncation order. For covalidation purposes, the same built-in function NDSolve is employed in the direct solution of these partial diferential equations, as made possible by the algorithms implemented in Mathematica (versions 3.0 and up), based on application of the method of lines. Various numerical experiments are performed and relative merits of each approach are critically pointed out.

Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection

The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.

Aircraft tracking and classification with vhf passive bistatic radar

Since the times preceding the Second World War the subject of aircraft tracking has been a core interest to both military and non-military aviation. During subsequent years both technology and configuration of the radars allowed the users to deploy it in numerous fields, such as over-the-horizon radar, ballistic missile early warning systems or forward scatter fences. The latter one was arranged in a bistatic configuration. The bistatic radar has continuously re-emerged over the last eighty years for its intriguing capabilities and challenging configuration and formulation. The bistatic radar arrangement is used as the basis of all the analyzes presented in this work. The aircraft tracking method of VHF Doppler-only information, developed in the first part of this study, is solely based on Doppler frequency readings in relation to time instances of their appearance. The corresponding inverse problem is solved by utilising a multistatic radar scenario with two receivers and one transmitter and using their frequency readings as a base for aircraft trajectory estimation. The quality of the resulting trajectory is then compared with ground-truth information based on ADS-B data. The second part of the study deals with the developement of a method for instantaneous Doppler curve extraction from within a VHF time-frequency representation of the transmitted signal, with a three receivers and one transmitter configuration, based on a priori knowledge of the probability density function of the first order derivative of the Doppler shift, and on a system of blocks for identifying, classifying and predicting the Doppler signal. The extraction capabilities of this set-up are tested with a recorded TV signal and simulated synthetic spectrograms. Further analyzes are devoted to more comprehensive testing of the capabilities of the extraction method. Besides testing the method, the classification of aircraft is performed on the extracted Bistatic Radar Cross Section profiles and the correlation between them for different types of aircraft. In order to properly estimate the profiles, the ADS-B aircraft location information is adjusted based on extracted Doppler frequency and then used for Bistatic Radar Cross Section estimation. The classification is based on seven types of aircraft grouped by their size into three classes.

Classification of brain tumor extracts by high resolution ¹H MRS using partial least squares discriminant analysis

High resolution proton nuclear magnetic resonance spectroscopy (¹H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T ¹H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out cross-validation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.

Manual and semi-automatic quantification of in vivo ¹H-MRS data for the classification of human primary brain tumors

In vivo proton magnetic resonance spectroscopy (¹H-MRS) is a technique capable of assessing biochemical content and pathways in normal and pathological tissue. In the brain, ¹H-MRS complements the information given by magnetic resonance images. The main goal of the present study was to assess the accuracy of ¹H-MRS for the classification of brain tumors in a pilot study comparing results obtained by manual and semi-automatic quantification of metabolites. In vivo single-voxel ¹H-MRS was performed in 24 control subjects and 26 patients with brain neoplasms that included meningiomas, high-grade neuroglial tumors and pilocytic astrocytomas. Seven metabolite groups (lactate, lipids, N-acetyl-aspartate, glutamate and glutamine group, total creatine, total choline, myo-inositol) were evaluated in all spectra by two methods: a manual one consisting of integration of manually defined peak areas, and the advanced method for accurate, robust and efficient spectral fitting (AMARES), a semi-automatic quantification method implemented in the jMRUI software. Statistical methods included discriminant analysis and the leave-one-out cross-validation method. Both manual and semi-automatic analyses detected differences in metabolite content between tumor groups and controls (P < 0.005). The classification accuracy obtained with the manual method was 75% for high-grade neuroglial tumors, 55% for meningiomas and 56% for pilocytic astrocytomas, while for the semi-automatic method it was 78, 70, and 98%, respectively. Both methods classified all control subjects correctly. The study demonstrated that ¹H-MRS accurately differentiated normal from tumoral brain tissue and confirmed the superiority of the semi-automatic quantification method.

Novel retrograde puncture method to establish preperitoneal space for laparoscopic direct inguinal hernia repair with internal ring suturing

The aim of this study was to explore the clinical efficacy of a novel retrograde puncture approach to establish a preperitoneal space for laparoscopic direct inguinal hernia repair with inguinal ring suturing. Forty-two patients who underwent laparoscopic inguinal hernia repair with retrograde puncture for preperitoneal space establishment as well as inguinal ring suturing between August 2013 and March 2014 at our hospital were enrolled. Preperitoneal space was successfully established in all patients, with a mean establishment time of 6 min. Laparoscopic repairs were successful in all patients, with a mean surgical time of 26±15.1 min. Mean postoperative hospitalization duration was 3.0±0.7 days. Two patients suffered from postoperative local hematomas, which were relieved after puncturing and drainage. Four patients had short-term local pain. There were no cases of chronic pain. Patients were followed up for 6 months to 1 year, and no recurrence was observed. Our results demonstrate that preperitoneal space established by the retrograde puncture technique can be successfully used in adult laparoscopic hernioplasty to avoid intraoperative mesh fixation, and thus reduce medical costs.

Effect of drying method on the adsorption isotherms and isosteric heat of passion fruit pulp powder

The sorption behavior of dry products is generally affected by the drying method. The sorption isotherms are useful to determine and compare thermodynamic properties of passion fruit pulp powder processed by different drying methods. The objective of this study is to analyze the effects of different drying methods on the sorption properties of passion fruit pulp powder. Passion fruit pulp powder was dehydrated using different dryers: vacuum, spray dryer, vibro-fluidized, and freeze dryer. The moisture equilibrium data of Passion Fruit Pulp (PFP) powders with 55% of maltodextrin (MD) were determined at 20, 30, 40 and 50 ºC. The behavior of the curves was type III, according to Brunauer's classification, and the GAB model was fitted to the experimental equilibrium data. The equilibrium moisture contents of the samples were little affected by temperature variation. The spray dryer provides a dry product with higher adsorption capacity than that of the other methods. The vibro-fluidized bed drying showed higher adsorption capacity than that of vacuum and freeze drying. The vacuum and freeze drying presented the same adsorption capacity. The isosteric heats of sorption were found to decrease with increasing moisture content. Considering the effect of drying methods, the highest isosteric heat of sorption was observed for powders produced by spray drying, whereas powders obtained by vacuum and freeze drying showed the lowest isosteric heats of sorption.

TAKING ADVANTAGE OF THE LOCAL ADVANTAGE? - Investment value of the analyst local advantage in the Finnish stock market in 2006–2014

An investor can either conduct independent analysis or rely on the analyses of others. Stock analysts provide markets with expectations regarding particular securities. However, analysts have different capabilities and resources, of which investors are seldom cognizant. The local advantage refers to the advantage stemming from cultural or geographical proximity to securities analyzed. The research has confirmed that local agents are generally more accurate or produce excess returns. This thesis tests the investment value of the local advantage regarding Finnish stocks via target price data. The empirical section investigates the local advantage from several aspects. It is discovered that local analysts were more focused on certain sectors generally located close to consumer markets. Market reactions to target price revisions were generally insignificant with the exception to local positive target prices. Both local and foreign target prices were overly optimistic and exhibited signs of herding. Neither group could be identified as a leader or follower of new information. Additionally, foreign price change expectations were more in line with the quantitative models and ideas such as beta or return mean reversion. The locals were more accurate than foreign analysts in 5 out of 9 sectors and vice versa in one. These sectors were somewhat in line with coverage decisions and buttressed the idea of local advantage stemming from proximity to markets, not to headquarters. The accuracy advantage was dependent on sample years and on the measure used. Local analysts ranked magnitudes of price changes more accurately in optimistic and foreign analysts in pessimistic target prices. Directional accuracy of both groups was under 50% and target prices held no linear predictive power. Investment value of target prices were tested by forming mean-variance efficient portfolios. Parallel to differing accuracies in the levels of expectations foreign portfolio performed better when short sales were allowed and local better when disallowed. Both local and non-local portfolios performed worse than a passive index fund, albeit not statistically significantly. This was in line with previously reported low overall accuracy and different accuracy profiles. Refraining from estimating individual stock returns altogether produced statistically significantly higher Sharpe ratios compared to local or foreign portfolios. The proposed method of testing the investment value of target prices of different groups suffered from some inconsistencies. Nevertheless, these results are of interest to investors seeking the advice of security analysts.

Development of a rapid method for the determination of antibiotic residues in honey using UPLC-ESI-MS/MS

Abstract An accurate, reliable and fast multianalyte/multiclass ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) method was developed and validated for the simultaneous analysis of 23 pharmaceuticals, belonging to different classes amphenicols, sulfonamides, tetracyclines, in honey samples. The method developed consists of ultrasonic extraction followed by UPLC–ESI–MS/MS with electrospray ionization in both positive mode and negative mode. The influence of the extraction solvents and mobile phase composition on the sensitivity of the method, and the optimum conditions for sample weight and extraction temperature in terms of analyte recovery were extensively studied. The identification of antibiotics is fulfilled by simultaneous use of chromatographic separation using an Acquity BEH C18 (100 mm x 2.1 mm, 1.7 µm) analytical column with a gradient elution of mobile phases and tandem mass spectrometry with an electrospray ionization. Finally, the method developed was applied to the determination of target analytes in honey samples obtained from the local markets and several beekeepers in Muğla, Turkey. Ultrasonic-extraction of pharmaceuticals from honey samples is a well-established technique by UPLC–ESI–MS/MS, the uniqueness of this study lies in the simultaneous determination of a remarkable number of compounds belonging to 23 drug at the sub-nanogram per kilogram level.

Blue and Uv-Emitting Upconversion Nanoparticles: Synthesis and (Bio) Analytical Applications.

Rare-earth based upconverting nanoparticles (UCNPs) have attracted much attention due to their unique luminescent properties. The ability to convert multiple photons of lower energy to ones with higher energy through an upconversion (UC) process offers a wide range of applications for UCNPs. The emission intensities and wavelengths of UCNPs are important performance characteristics, which determine the appropriate applications. However, insufficient intensities still limit the use of UCNPs; especially the efficient emission of blue and ultraviolet (UV) light via upconversion remains challenging, as these events require three or more near-infrared (NIR) photons. The aim of the study was to enhance the blue and UV upconversion emission intensities of Tm3+ doped NaYF4 nanoparticles and to demonstrate their utility in in vitro diagnostics. As the distance between the sensitizer and the activator significantly affect the energy transfer efficiency, different strategies were explored to change the local symmetry around the doped lanthanides. One important strategy is the intentional co-doping of active (participate in energy transfer) or passive (do not participate in energy transfer) impurities into the host matrix. The roles of doped passive impurities (K+ and Sc3+) in enhancing the blue and UV upconversions, as well as in influencing the intense UV upconversion emission through excess sensitization (active impurity) were studied. Additionally, the effects of both active and passive impurity doping on the morphological and optical performance of UCNPs were investigated. The applicability of UV emitting UCNPs as an internal light source for glucose sensing in a dry chemistry test strip was demonstrated. The measurements were in agreement with the traditional method based on reflectance measurements using an external UV light source. The use of UCNPs in the glucose test strip offers an alternative detection method with advantages such as control signals for minimizing errors and high penetration of the NIR excitation through the blood sample, which gives more freedom for designing the optical setup. In bioimaging, the excitation of the UCNPs in the transparent IR region of the tissue permits measurements, which are free of background fluorescence and have a high signal-to-background ratio. In addition, the narrow emission bandwidth of the UCNPs enables multiplexed detections. An array-in-well immunoassay was developed using two different UC emission colours. The differentiation between different viral infections and the classification of antibody responses were achieved based on both the position and colour of the signal. The study demonstrates the potential of spectral and spatial multiplexing in the imaging based array-in-well assays.

Comparing the alternative utilization method for coconut in Nzema, Ghana

There are many opportunities to utilise coconut in Nzema to support farmers. Coconut oil that is mainly used for food preparation in Nzema can be utilized as fuel to support overcoming of the energy crisis in the Ghana. Coconut oil in Nzema is not used in both transportation and electricity generation. A few of the waste husk and shell are mainly used as fuel in homes for heating but greater amount is left to rot or burn the coconut plantation. In addition, some portion of the granulated coconut kernel is sometime used as feed for piggery feed and the rest of the granulated kernel are left as waste on the oil processing site. In this thesis, the author identified alternative utilization of cocoanut, for instance the use of coconut husk and shell for charcoal production, and the use of coconut trunks as construction materials. It is envisaged that exploring these alternatives will not only reduce carbon emission in the country but will also contribute significantly to the sustainability of the local agro-industry.