Longitudinal distribution of bean seeds in horizontal plate meter operating with one or two seed outlets

This study aimed to evaluate the effect of horizontal plate meter with oblong holes operating with one or two seed outlets at different speeds over the accuracy of longitudinal distribution of common bean seeds (Phaseolus vulgaris L.). The experiment was performed in laboratory using the meter with one and two seed outlet points in relation to ten tangential disk plate speeds (0.03 to 0.30 m s-1). It was used a complete randomized design with four replications, summing up 80 experimental treatments. Tangential speed quantitative factor was estimated through a 2nd order polynomial regression. There was no significant difference in the behavior of the seed meter operating with one or two outlets in the metering of bean seeds in all tested speeds, with percentage of single seeds spacing over 60% in tangential speeds below of 0.24 m s-1.

Economic analysis of cashew early dwarf Crop BRS - 189 depending on water levels and doses of potassium fertilization

Water and fertilizer among the production factors are the elements that most restrict the production of cashew. The precise amount of these factors is essential to the success of the crop yield. This research aimed to determine the best factor-product ratio and analyze technical and economic indicators, of productivity of the cashew clone BRS 189 (Anacardium occidentale) to production factors water and potassium. The experiment was conducted from May 2009 to December 2009 in an experimental area of 56.0 m x 112.0 m in the irrigated Curu - Pentecoste, located in the municipality of Pentecoste, Ceará, Brazil. Production factors water (W) and potassium (K) were the independent variables and productivity (Y), the dependent variable. Ten statistical models that have proven satisfactory for obtaining production function were tested. The marginal rate of substitution was obtained through the ratio of the potassium marginal physical product and the water marginal physical product. The most suited model to the conditions of the experiment was the quadratic polynomial without intercept and interaction. Considering that the price of the water was 0.10 R$ mm -1, the price of the potassium 2.19 R$ kg -1 and the price of the cashew 0.60 R$ kg-1, the amounts of water and K2O to obtain the maximum net income were 6,349.1 L plant-1 of water and 128.7 g plant -1year, -1 respectively. Substituting the values obtained in the production function, the maximum net income was achieved with a yield of 7,496.8 kg ha-1 of cashew.

Mapping of use and occupation of the soil and irrigation water quality in the city of Salto do Lontra-Paraná, Brazil

The objective of this study consisted on mapping the use and soil occupation and evaluation of the quality of irrigation water used in Salto do Lontra, in the state of Paraná, Brazil. Images of the satellite SPOT-5 were used to perform the supervised classification of the Maximum Likelihood algorithm - MAXVER, and the water quality parameters analyzed were pH, EC, HCO3-, Cl-, PO4(3-), NO3-, turbidity, temperature and thermotolerant coliforms in two distinct rainfall periods. The water quality data were subjected to statistical analysis by the techniques of PCA and FA, to identify the most relevant variables in assessing the quality of irrigation water. The characterization of soil use and occupation by the classifier MAXVER allowed the identification of the following classes: crops, bare soil/stubble, forests and urban area. The PCA technique applied to irrigation water quality data explained 53.27% of the variation in water quality among the sampled points. Nitrate, thermotolerant coliforms, temperature, electrical conductivity and bicarbonate were the parameters that best explained the spatial variation of water quality.

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%.

Preventive diagnosis of dairy cow lameness

This research aimed to develop a Fuzzy inference based on expert system to help preventing lameness in dairy cattle. Hoof length, nutritional parameters and floor material properties (roughness) were used to build the Fuzzy inference system. The expert system architecture was defined using Unified Modelling Language (UML). Data were collected in a commercial dairy herd using two different subgroups (H1 and H2), in order to validate the Fuzzy inference functions. The numbers of True Positive (TP), False Positive (FP), True Negative (TN), and False Negative (FN) responses were used to build the classifier system up, after an established gold standard comparison. A Lesion Incidence Possibility (LIP) developed function indicates the chances of a cow becoming lame. The obtained lameness percentage in H1 and H2 was 8.40% and 1.77%, respectively. The system estimated a Lesion Incidence Possibility (LIP) of 5.00% and 2.00% in H1 and H2, respectively. The system simulation presented 3.40% difference from real cattle lameness data for H1, while for H2, it was 0.23%; indicating the system efficiency in decision-making.

Bankruptcy prediction using fuzzy methods

In this thesis, a classi cation problem in predicting credit worthiness of a customer is tackled. This is done by proposing a reliable classi cation procedure on a given data set. The aim of this thesis is to design a model that gives the best classi cation accuracy to e ectively predict bankruptcy. FRPCA techniques proposed by Yang and Wang have been preferred since they are tolerant to certain type of noise in the data. These include FRPCA1, FRPCA2 and FRPCA3 from which the best method is chosen. Two di erent approaches are used at the classi cation stage: Similarity classi er and FKNN classi er. Algorithms are tested with Australian credit card screening data set. Results obtained indicate a mean classi cation accuracy of 83.22% using FRPCA1 with similarity classi- er. The FKNN approach yields a mean classi cation accuracy of 85.93% when used with FRPCA2, making it a better method for the suitable choices of the number of nearest neighbors and fuzziness parameters. Details on the calibration of the fuzziness parameter and other parameters associated with the similarity classi er are discussed.

Feature selection using Fuzzy Entropy measures with Yu's Similarity measure

In this study, feature selection in classification based problems is highlighted. The role of feature selection methods is to select important features by discarding redundant and irrelevant features in the data set, we investigated this case by using fuzzy entropy measures. We developed fuzzy entropy based feature selection method using Yu's similarity and test this using similarity classifier. As the similarity classifier we used Yu's similarity, we tested our similarity on the real world data set which is dermatological data set. By performing feature selection based on fuzzy entropy measures before classification on our data set the empirical results were very promising, the highest classification accuracy of 98.83% was achieved when testing our similarity measure to the data set. The achieved results were then compared with some other results previously obtained using different similarity classifiers, the obtained results show better accuracy than the one achieved before. The used methods helped to reduce the dimensionality of the used data set, to speed up the computation time of a learning algorithm and therefore have simplified the classification task

Evaluation of follicular lymphoid depletion in the Bursa of Fabricius: an alternative methodology using digital image analysis and artificial neural networks

Fifty Bursa of Fabricius (BF) were examined by conventional optical microscopy and digital images were acquired and processed using Matlab® 6.5 software. The Artificial Neuronal Network (ANN) was generated using Neuroshell® Classifier software and the optical and digital data were compared. The ANN was able to make a comparable classification of digital and optical scores. The use of ANN was able to classify correctly the majority of the follicles, reaching sensibility and specificity of 89% and 96%, respectively. When the follicles were scored and grouped in a binary fashion the sensibility increased to 90% and obtained the maximum value for the specificity of 92%. These results demonstrate that the use of digital image analysis and ANN is a useful tool for the pathological classification of the BF lymphoid depletion. In addition it provides objective results that allow measuring the dimension of the error in the diagnosis and classification therefore making comparison between databases feasible.

Effects of starter diet supplementation with arginine on broiler production performance and on small intestine morphometry

The effects of starter diet (days 1 to 21) supplemented with arginine (Arg) on the production performance and duodenum and jejunum mucosa morphometry of broilers were studied. Male Cobb broiler chickens (990) were randomly assigned to one of five treatments in a complete random design. Measurements of 33 chicks per treatment were made in six repetitions. The treatments consisted of a basal diet with 1.390% digestible Arg (no supplementation) and four dietary levels (1.490%, 1.590%, 1.690%, and 1.790%), providing a relationship with lysine of 1.103; 1.183; 1.262; 1.341 and 1.421%, respectively. From the age of 22 days on, all birds received conventional grower diet. The data were submitted to regression analysis by polynomial decomposition of the degrees of freedom in relation to the levels of Arg. The Arg supplementation increased (P<0.05) the live weight and the feed conversion ratio without increasing the feed intake of the birds. However, no effect was observed (P>0.05) in the growth phase (days 22 to 42) in the absence of the Arg supplementation. The supplementation of Arg over of NRC recommendation during the starter phase may be necessary for the expression of the maximal weight gain potential in birds. No effect (P<0.05) of Arg dietary supplementation was observed either on small intestine weight and length at any age. However, the duodenum villus:crypt ratio increased and the crypt depth decreased in the first week in response to increasing dietary Arg. It is concluded that broiler Arg dietary supplementation in the starter diet improved production performance and small intestine morphometry, especially in the first week.

Learning Grasp Affordances from Vision

Monimutkaisissa ja muuttuvissa ympäristöissä työskentelevät robotit tarvitsevat kykyä manipuloida ja tarttua esineisiin. Tämä työ tutkii robottitarttumisen ja robottitartuntapis-teiden koneoppimisen aiempaa tutkimusta ja nykytilaa. Nykyaikaiset menetelmät käydään läpi, ja Le:n koneoppimiseen pohjautuva luokitin toteutetaan, koska se tarjoaa parhaan onnistumisprosentin tutkituista menetelmistä ja on muokattavissa sopivaksi käytettävissä olevalle robotille. Toteutettu menetelmä käyttää intensititeettikuvaan ja syvyyskuvaan po-hjautuvia ominaisuuksi luokitellakseen potentiaaliset tartuntapisteet. Tämän toteutuksen tulokset esitellään.

Control of Structures with Cubic and Quadratic Non-Linearities with Time Delay Consideration

This paper studies the effect of time delay on the active non-linear control of dynamically loaded flexible structures. The behavior of non-linear systems under state feedback control, considering a fixed time delay for the control force, is investigated. A control method based on non-linear optimal control, using a tensorial formulation and state feedback control is used. The state equations and the control forces are expressed in polynomial form and a performance index, quadratic in both state vector and control forces, is used. General polynomial representations of the non-linear control law are obtained and implemented for control algorithms up to the fifth order. This methodology is applied to systems with quadratic and cubic non-linearities. Strongly non-linear systems are tested and the effectiveness of the control system including a delay for the application of control forces is discussed. Numerical results indicate that the adopted control algorithm can be efficient for non-linear systems, chiefly in the presence of strong non-linearities but increasing time delay reduces the efficiency of the control system. Numerical results emphasize the importance of considering time delay in the project of active structural control systems.

Substitution-Newton-Raphson method applied to the modeling of a vapour compression refrigeration system using different representations of the thermodynamic properties of R-134a

This paper gives a detailed presentation of the Substitution-Newton-Raphson method, suitable for large sparse non-linear systems. It combines the Successive Substitution method and the Newton-Raphson method in such way as to take the best advantages of both, keeping the convergence features of the Newton-Raphson with the low requirements of memory and time of the Successive Substitution schemes. The large system is solved employing few effective variables, using the greatest possible part of the model equations in substitution fashion to fix the remaining variables, but maintaining the convergence characteristics of the Newton-Raphson. The methodology is exemplified through a simple algebraic system, and applied to a simple thermodynamic, mechanical and heat transfer modeling of a single-stage vapor compression refrigeration system. Three distinct approaches for reproducing the thermodynamic properties of the refrigerant R-134a are compared: the linear interpolation from tabulated data, the use of polynomial fitted curves and the use of functions derived from the Helmholtz free energy.

Welding current effect on diffusible hydrogen content in flux cored arc weld metal

The application of flux cored arc welding (FCAW) has increased in manufacturing and fabrication. Even though FCAW is well known for its good capability in producing quality welds, few reports have been published on the cause of the relatively high diffusible hydrogen content in the weld metal and its relation with the ingredients used in the wire production and with the welding parameters (mainly welding current). This paper describes experiments where data obtained from weld metal diffusible hydrogen analysis, metal droplet collection, and high-speed recording of metal droplet transfer were used to evaluate the effect of welding current on diffusible hydrogen content in the weld metal. The results from gas chromatography analysis showed that weld metal hydrogen content indeed increased with welding current. A polynomial regressional analysis concluded that hydrogen increase with current was better described by a linear function with proportional constant of approximately 0.7 or 70%. Different from the GMA welding transfer behavior, statistical analysis showed only a small increase in metal droplet size with increasing current. The metal transfer mode remained in the globular range for currents between 100 and 150 A. The most surprising findings were with the high-speed cinematography recording. Observing the high speed movies, it was possible to see that at low current, "unmelted" flux sporadically touched the weld pool but at higher current, the flux remained touching the weld pool during the whole time of droplet formation and transfer. It is believed that since the flux has ingredients that contain hydrogen, hydrogen passes through the arc undisturbed, going to the weld bead intact and increasing the hydrogen content in the weld metal. Another important observation is regarding to droplet size. Droplet size increased with increasing current because forces from decomposed gases from the flux could sustain the droplets, retarding their transfer and allowing them to grow.

Steganografia ja kuvien digitaalinen vesileimaus

Steganografian tarkoituksena on salaisen viestin piilottaminen muun informaation sekaan. Tutkielmassa perehdytään kirjallisuuden pohjalta steganografiaan ja kuvien digitaaliseen vesileimaamiseen. Tutkielmaan kuuluu myös kokeellinen osuus. Siinä esitellään vesileimattujen kuvien tunnistamiseen kehitetty testausjärjestelmä ja testiajojen tulokset. Testiajoissa kuvasarjoja on vesileimattu valituilla vesileimausmenetelmillä parametreja vaihdellen. Tunnistettaville kuville tehdään piirreirrotus. Erotellut piirteet annetaan parametreina luokittimelle, joka tekee lopullisen tunnistamispäätöksen. Tutkimuksessa saatiin toteutettua toimiva ohjelmisto vesileiman lisäämiseen ja vesileimattujen kuvien tunnistamiseen kuvajoukosta. Tulosten perusteella, sopivalla piirreirrottimella ja tukivektorikoneluokittimella päästään yli 95 prosentin tunnistamistarkkuuteen.

Adaptive control of Hydraulic Drive

Adaptive control systems are one of the most significant research directions of modern control theory. It is well known that every mechanical appliance’s behavior noticeably depends on environmental changes, functioning-mode parameter changes and changes in technical characteristics of internal functional devices. An adaptive controller involved in control process allows reducing an influence of such changes. In spite of this such type of control methods is applied seldom due to specifics of a controller designing. The work presented in this paper shows the design process of the adaptive controller built by Lyapunov’s function method for the Hydraulic Drive. The calculation needed and the modeling were conducting with MATLAB® software including Simulink® and Symbolic Math Toolbox™ etc. In the work there was applied the Jacobi matrix linearization of the object’s mathematical model and derivation of the suitable reference models based on Newton’s characteristic polynomial. The intelligent adaptive to nonlinearities algorithm for solving Lyapunov’s equation was developed. Developed algorithm works properly but considered plant is not met requirement of functioning with. The results showed confirmation that adaptive systems application significantly increases possibilities in use devices and might be used for correction a system’s behavior dynamics.