On Dynamic Monitoring Methods for Networks-on-Chip

Rapid ongoing evolution of multiprocessors will lead to systems with hundreds of processing cores integrated in a single chip. An emerging challenge is the implementation of reliable and efficient interconnection between these cores as well as other components in the systems. Network-on-Chip is an interconnection approach which is intended to solve the performance bottleneck caused by traditional, poorly scalable communication structures such as buses. However, a large on-chip network involves issues related to congestion problems and system control, for instance. Additionally, faults can cause problems in multiprocessor systems. These faults can be transient faults, permanent manufacturing faults, or they can appear due to aging. To solve the emerging traffic management, controllability issues and to maintain system operation regardless of faults a monitoring system is needed. The monitoring system should be dynamically applicable to various purposes and it should fully cover the system under observation. In a large multiprocessor the distances between components can be relatively long. Therefore, the system should be designed so that the amount of energy-inefficient long-distance communication is minimized. This thesis presents a dynamically clustered distributed monitoring structure. The monitoring is distributed so that no centralized control is required for basic tasks such as traffic management and task mapping. To enable extensive analysis of different Network-on-Chip architectures, an in-house SystemC based simulation environment was implemented. It allows transaction level analysis without time consuming circuit level implementations during early design phases of novel architectures and features. The presented analysis shows that the dynamically clustered monitoring structure can be efficiently utilized for traffic management in faulty and congested Network-on-Chip-based multiprocessor systems. The monitoring structure can be also successfully applied for task mapping purposes. Furthermore, the analysis shows that the presented in-house simulation environment is flexible and practical tool for extensive Network-on-Chip architecture analysis.

Qualitative Characteristics and Quantitative Measures of Solution's Reliability in Discrete Optimization: Traditional Analytical Approaches, Innovative Computational Methods and Applicability

The purpose of this thesis is twofold. The first and major part is devoted to sensitivity analysis of various discrete optimization problems while the second part addresses methods applied for calculating measures of solution stability and solving multicriteria discrete optimization problems. Despite numerous approaches to stability analysis of discrete optimization problems two major directions can be single out: quantitative and qualitative. Qualitative sensitivity analysis is conducted for multicriteria discrete optimization problems with minisum, minimax and minimin partial criteria. The main results obtained here are necessary and sufficient conditions for different stability types of optimal solutions (or a set of optimal solutions) of the considered problems. Within the framework of quantitative direction various measures of solution stability are investigated. A formula for a quantitative characteristic called stability radius is obtained for the generalized equilibrium situation invariant to changes of game parameters in the case of the H¨older metric. Quality of the problem solution can also be described in terms of robustness analysis. In this work the concepts of accuracy and robustness tolerances are presented for a strategic game with a finite number of players where initial coefficients (costs) of linear payoff functions are subject to perturbations. Investigation of stability radius also aims to devise methods for its calculation. A new metaheuristic approach is derived for calculation of stability radius of an optimal solution to the shortest path problem. The main advantage of the developed method is that it can be potentially applicable for calculating stability radii of NP-hard problems. The last chapter of the thesis focuses on deriving innovative methods based on interactive optimization approach for solving multicriteria combinatorial optimization problems. The key idea of the proposed approach is to utilize a parameterized achievement scalarizing function for solution calculation and to direct interactive procedure by changing weighting coefficients of this function. In order to illustrate the introduced ideas a decision making process is simulated for three objective median location problem. The concepts, models, and ideas collected and analyzed in this thesis create a good and relevant grounds for developing more complicated and integrated models of postoptimal analysis and solving the most computationally challenging problems related to it.

Novel Methods for Error Modeling and Parameter Identification of a Redundant Serial-Parallel Hybrid Robot

To obtain the desirable accuracy of a robot, there are two techniques available. The first option would be to make the robot match the nominal mathematic model. In other words, the manufacturing and assembling tolerances of every part would be extremely tight so that all of the various parameters would match the “design” or “nominal” values as closely as possible. This method can satisfy most of the accuracy requirements， but the cost would increase dramatically as the accuracy requirement increases. Alternatively, a more cost-effective solution is to build a manipulator with relaxed manufacturing and assembling tolerances. By modifying the mathematical model in the controller, the actual errors of the robot can be compensated. This is the essence of robot calibration. Simply put, robot calibration is the process of defining an appropriate error model and then identifying the various parameter errors that make the error model match the robot as closely as possible. This work focuses on kinematic calibration of a 10 degree-of-freedom (DOF) redundant serial-parallel hybrid robot. The robot consists of a 4-DOF serial mechanism and a 6-DOF hexapod parallel manipulator. The redundant 4-DOF serial structure is used to enlarge workspace and the 6-DOF hexapod manipulator is used to provide high load capabilities and stiffness for the whole structure. The main objective of the study is to develop a suitable calibration method to improve the accuracy of the redundant serial-parallel hybrid robot. To this end, a Denavit–Hartenberg (DH) hybrid error model and a Product-of-Exponential (POE) error model are developed for error modeling of the proposed robot. Furthermore, two kinds of global optimization methods, i.e. the differential-evolution (DE) algorithm and the Markov Chain Monte Carlo (MCMC) algorithm, are employed to identify the parameter errors of the derived error model. A measurement method based on a 3-2-1 wire-based pose estimation system is proposed and implemented in a Solidworks environment to simulate the real experimental validations. Numerical simulations and Solidworks prototype-model validations are carried out on the hybrid robot to verify the effectiveness, accuracy and robustness of the calibration algorithms.

Comparison of two commercial kits and two extraction methods for fecal glucocorticoid analysis in ocelots (Leopardus pardalis) submitted to ACTH challenge

The ocelot (Leopardus pardalis) is included in list of wild felid species protected by CITES and is part of conservation strategies that necessarily involve the use of assisted reproduction techniques, which requires practical and minimally invasive techniques of high reproducibility that permit the study of animal reproductive physiology. The objective of this study was to compare and validate two commercial assays: ImmuChem Double Antibody Corticosterone 125I RIA from ICN Biomedicals, Costa Mesa, CA, USA; and Coat-a-Count Cortisol 125I RIA from DPC, Los Angeles, CA, USA, for assessment of fecal glucocorticoid metabolites in ocelots submitted to ACTH (adrenocorticotropic hormone) challenge. Fecal samples were collected from five ocelots kept at the Brazilian Center of Neotropical Felines, Associação Mata Ciliar, São Paulo, Brazil, and one of the animals was chosen as a negative control. The experiment was conducted over a period of 9 days. On day 0, a total dose of 100 IU ACTH was administered intramuscularly. Immediately after collection the samples were stored at 20C in labeled plastic bags. The hormone metabolites were subsequently extracted and assayed using the two commercial kits. Previously it was performed a trial with the DPC kit to check the best extraction method for hormones metabolites. Data were analyzed with the SAS program for Windows V8 and reported as means ± SEM. The Schwarzenberger extraction method was slightly better when compared with the Wasser extraction method (103,334.56 ± 19,010.37ng/g of wet feces and 59,223.61 ± 12,725.36ng/g of wet feces respectively; P=0,0657). The ICN kit detected an increase in glucocorticoid metabolite concentrations in a more reliable manner. Metabolite concentrations (ng/g wet feces) on day 0 and day 1 were 66,956.28 ± 36,786.93 and 92,991.19 ± 28,555.63 for the DPC kit, and 205,483.32 ± 83,811.32 and 814,578.75 ± 292,150.47 for the ICN kit, respectively. The limit of detection for the ICN kit was 7.7 ng/mL for 100% B/Bo (25ng/mL for 88%B/Bo) and for the DPC kit it was 0.2ug/dL for 90.95% B/Bo (1ug/dL for 81.27% B/Bo). In conclusion it was confirmed that the Schwarzenberger extraction method and the ICN kit are superior for extracting and measuring fecal glucocorticoid metabolites in ocelot fecal samples.

Evaluation of Bubble Formation and Break Up in Suppression Pools by Using Pattern Recognition Methods

During a possible loss of coolant accident in BWRs, a large amount of steam will be released from the reactor pressure vessel to the suppression pool. Steam will be condensed into the suppression pool causing dynamic and structural loads to the pool. The formation and break up of bubbles can be measured by visual observation using a suitable pattern recognition algorithm. The aim of this study was to improve the preliminary pattern recognition algorithm, developed by Vesa Tanskanen in his doctoral dissertation, by using MATLAB. Video material from the PPOOLEX test facility, recorded during thermal stratification and mixing experiments, was used as a reference in the development of the algorithm. The developed algorithm consists of two parts: the pattern recognition of the bubbles and the analysis of recognized bubble images. The bubble recognition works well, but some errors will appear due to the complex structure of the pool. The results of the image analysis were reasonable. The volume and the surface area of the bubbles were not evaluated. Chugging frequencies calculated by using FFT fitted well into the results of oscillation frequencies measured in the experiments. The pattern recognition algorithm works in the conditions it is designed for. If the measurement configuration will be changed, some modifications have to be done. Numerous improvements are proposed for the future 3D equipment.

Comparison of two methods for glucocorticoid evaluation in maned wolves

Analysis of faecal glucocorticoid metabolites provides a powerful noninvasive tool for monitoring adrenocortical activity in wild animals. However, differences regarding the metabolism and excretion of these substances make a validation for each species and sex investigated obligatory. Although maned wolves (Chrysocyon brachyurus) are the biggest canids in South America, their behaviour and physiology are poorly known and they are at risk in the wild. Two methods for measuring glucocorticoid metabolites in maned wolves were validated: a radio- and an enzyme immunoassay. An ACTH challenge was used to demonstrate that changes in adrenal function are reflected in faecal glucocorticoid metabolites. Our results suggest that both methods enable a reliable assessment of stress hormones in maned wolves avoiding short-term rises in glucocorticoid concentrations due to handling and restraint. These methods can be used as a valuable tool in studies of stress and conservation in this wild species.

Magnetic Resocance Imaging Methods in the Follow-up of Multiple Sclerosis and in Farby Disease

Multiple sclerosis (MS) is a chronic immune-mediated inflammatory disorder of the central nervous system. MS is the most common disabling central nervous system (CNS) disease of young adults in the Western world. In Finland, the prevalence of MS ranges between 1/1000 and 2/1000 in different areas. Fabry disease (FD) is a rare hereditary metabolic disease due to mutation in a single gene coding α-galactosidase A (alpha-gal A) enzyme. It leads to multi-organ pathology, including cerebrovascular disease. Currently there are 44 patients with diagnosed FD in Finland. Magnetic resonance imaging (MRI) is commonly used in the diagnostics and follow-up of these diseases. The disease activity can be demonstrated by occurrence of new or Gadolinium (Gd)-enhancing lesions in routine studies. Diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI) are advanced MR sequences which can reveal pathologies in brain regions which appear normal on conventional MR images in several CNS diseases. The main focus in this study was to reveal whether whole brain apparent diffusion coefficient (ADC) analysis can be used to demonstrate MS disease activity. MS patients were investigated before and after delivery and before and after initiation of diseasemodifying treatment (DMT). In FD, DTI was used to reveal possible microstructural alterations at early timepoints when excessive signs of cerebrovascular disease are not yet visible in conventional MR sequences. Our clinical and MRI findings at 1.5T indicated that post-partum activation of the disease is an early and common phenomenon amongst mothers with MS. MRI seems to be a more sensitive method for assessing MS disease activity than the recording of relapses. However, whole brain ADC histogram analysis is of limited value in the follow-up of inflammatory conditions in a pregnancy-related setting because the pregnancy-related physiological effects on ADC overwhelm the alterations in ADC associated with MS pathology in brain tissue areas which appear normal on conventional MRI sequences. DTI reveals signs of microstructural damage in brain white matter of FD patients before excessive white matter lesion load can be observed on conventional MR scans. DTI could offer a valuable tool for monitoring the possible effects of enzyme replacement therapy in FD.

Comparison of two methods of tear sampling for protein quantification by Bradford method

The aim of this study was to compare two methods of tear sampling for protein quantification. Tear samples were collected from 29 healthy dogs (58 eyes) using Schirmer tear test (STT) strip and microcapillary tubes. The samples were frozen at -80ºC and analyzed by the Bradford method. Results were analyzed by Student's t test. The average protein concentration and standard deviation from tears collected with microcapillary tube were 4.45mg/mL ±0.35 and 4,52mg/mL ±0.29 for right and left eyes respectively. The average protein concentration and standard deviation from tears collected with Schirmer Tear Test (STT) strip were and 54.5mg/mL ±0.63 and 54.15mg/mL ±0.65 to right and left eyes respectively. Statistically significant differences (p<0.001) were found between the methods. In the conditions in which this study was conducted, the average protein concentration obtained with the Bradford test from tear samples obtained by Schirmer Tear Test (STT) strip showed values higher than those obtained with microcapillary tube. It is important that concentration of tear protein pattern values should be analyzed according the method used to collect tear samples.

Identification of new flagellin-encoding fliC genes in Escherichia coli isolated from domestic animals using RFLP-PCR and sequencing methods

Identification of Escherichia coli requires knowledge regarding the prevalent serotypes and virulence factors profiles allows the classification in pathogenic/non-pathogenic. However, some of these bacteria do not express flagellar antigen invitro. In this case the PCR-restriction fragment length polymorphism (RFLP-PCR) and sequencing of the fliC may be suitable for the identification of antigens by replacing the traditional serology. We studied 17 samples of E. coli isolated from animals and presenting antigen H nontypeable (HNT). The H antigens were characterized by PCR-RFLP and sequencing of fliC gene. Three new flagellin genes were identified, for which specific antisera were obtained. The PCR-RFLP was shown to be faster than the serotyping H antigen in E. coli, provided information on some characteristics of these antigens and indicated the presence of new genes fliC.

Comparison of methods for determination of nutrient digestibility of a dry kibble diet for ocelots

In this experiment, methods of total fecal collection (TFC) and internal markers (acid-insoluble ash - AIA, crude fiber - CF, and acid-detergent fiber - ADF) were compared for determination of the coefficients of apparent digestibility (CAD) for dry matter (DM), crude protein (CP), ether extract (EE), nitrogen-free extracts (NFE), and gross energy (GE) of commercial feline dry kibble for ocelots (Leopardus pardalis). Six adult animals, weighing 12.45±1.37 kg, gradually received experimental kibble in their usual diet until the beginning of the experiment and were submitted to an adaptation period ten days prior to the collection period. CAD obtained by TFC, AIA, CF, and ADF were, respectively, 73.7, 76.83, 62.01, and 46.03% for dry matter; 81.9, 84.8, 75.8, and 63.8% for crude protein; 85, 86.7, 78.5, and 69.1% for ether extract; 78.52, 79.55, 69.11, and 53.04% for nitrogen-free extracts; and 80.5, 82.2, 71.4, and 58.4% for gross energy. The AIA method showed to be efficient in determining coefficients of apparent digestibility and may contribute to investigations on the digestibility of diets for wild felines. In comparison to the items of ocelot's usual diet, the kibble used in this paper provided an adequate nutritional supply with reduced daily costs per animal.

Analytical methods for analyzing organic peroxides

Työn tarkoituksena oli kehittää analyyttinen erotusmenetelmä eräässä valmistusprosessissa käytettävän hapettavan aineen ja liuottimen välillä syntyvien reaktiotuotteiden tutkimiseen ja analysoimiseen. Lisäksi tarkoituksena oli tutkia prosessiolosuhteiden turvallisuutta. Kirjallisuusosassa käsitellään erilaisia orgaanisia peroksideja, niiden käyttötarkoituksia ja niiden käyttöön liittyviä huomioitavia asioita. Lisäksi tarkastellaan yleisimpiä analyysimenetelmiä, joita on käytetty erilaisten peroksidien analysoinnissa. Näitä analyysimenetelmiä on useimmiten käytetty nestemäisten näytteiden tutkimuksissa. Harvemmin on analysoitu kaasu- ja kiintoainenäytteitä. Kokeellisessa osassa kehitettiin kirjallisuuden perusteella peroksidiyhdisteille identifiointimenetelmä ja tutkittiin prosessin näytteet. Analyysimenetelmiksi valittiin iodometrinen titraus ja HPLC-UV-MS-menetelmä. Lisäksi käytettiin peroksidimittaukseen soveltuvia testiliuskoja. Tutkimus osoitti, että iodometrisen titrauksen ja testiliuskojen perusteella näytteissä oli vähäisiä määriä peroksideja viikon jälkeen peroksidilisäyksestä. HPLC-UV-MS-analyysien perusteella näytteiden analysointia häiritsi selluloosa, jota löytyi jokaisesta näytteestä.

Multidata inverse problems and Bayesian solution methods in astronomy

Statistical analyses of measurements that can be described by statistical models are of essence in astronomy and in scientific inquiry in general. The sensitivity of such analyses, modelling approaches, and the consequent predictions, is sometimes highly dependent on the exact techniques applied, and improvements therein can result in significantly better understanding of the observed system of interest. Particularly, optimising the sensitivity of statistical techniques in detecting the faint signatures of low-mass planets orbiting the nearby stars is, together with improvements in instrumentation, essential in estimating the properties of the population of such planets, and in the race to detect Earth-analogs, i.e. planets that could support liquid water and, perhaps, life on their surfaces. We review the developments in Bayesian statistical techniques applicable to detections planets orbiting nearby stars and astronomical data analysis problems in general. We also discuss these techniques and demonstrate their usefulness by using various examples and detailed descriptions of the respective mathematics involved. We demonstrate the practical aspects of Bayesian statistical techniques by describing several algorithms and numerical techniques, as well as theoretical constructions, in the estimation of model parameters and in hypothesis testing. We also apply these algorithms to Doppler measurements of nearby stars to show how they can be used in practice to obtain as much information from the noisy data as possible. Bayesian statistical techniques are powerful tools in analysing and interpreting noisy data and should be preferred in practice whenever computational limitations are not too restrictive.

Uterine lymphangiography: comparison of two methods for locating the medial iliac lymph node

Different methods for lymphatic mapping in dogs, such as infusing tissues with vital dyes or radioactive substances, have been studied, aiming at the early detection of lymph node metastasis. Thus, one could anticipate therapeutic measures and, consequently, prolong the survival and improve the quality of life of the patients. The objectives of this experiment were to locate the nodes responsible for draining the uterine body and horns and to try to establish the relationship between the uterus and the medial iliac lymph nodes to contribute to the early diagnosis and prognosis of uterine disorders. We studied 15 female dogs divided into two groups (5 dead and 10 intraoperative ovariohysterectomy bitches). The dye used was patent blue V (Patent Bleu V®). It was observed that the iliac lymph node chain receives much of the uterine (horns) drainage. This method should be considered for safer studies of uterine sanity. This information suggests that evaluating these lymph nodes will allow correlating changes in their physiological status with uterine pathologies.

BEM/FEM non-linear model applied to transient analysis with viscous damping

In this article a two-dimensional transient boundary element formulation based on the mass matrix approach is discussed. The implicit formulation of the method to deal with elastoplastic analysis is considered, as well as the way to deal with viscous damping effects. The time integration processes are based on the Newmark rhoand Houbolt methods, while the domain integrals for mass, elastoplastic and damping effects are carried out by the well known cell approximation technique. The boundary element algebraic relations are also coupled with finite element frame relations to solve stiffened domains. Some examples to illustrate the accuracy and efficiency of the proposed formulation are also presented.

Solution of aerospace problems using structured and unstructured strategies

Products developed at industries, institutes and research centers are expected to have high level of quality and performance, having a minimum waste, which require efficient and robust tools to numerically simulate stringent project conditions with great reliability. In this context, Computational Fluid Dynamics (CFD) plays an important role and the present work shows two numerical algorithms that are used in the CFD community to solve the Euler and Navier-Stokes equations applied to typical aerospace and aeronautical problems. Particularly, unstructured discretization of the spatial domain has gained special attention by the international community due to its ease in discretizing complex spatial domains. This work has the main objective of illustrating some advantages and disadvantages of numerical algorithms using structured and unstructured spatial discretization of the flow governing equations. Numerical methods include a finite volume formulation and the Euler and Navier-Stokes equations are applied to solve a transonic nozzle problem, a low supersonic airfoil problem and a hypersonic inlet problem. In a structured context, these problems are solved using MacCormack’s implicit algorithm with Steger and Warming’s flux vector splitting technique, while, in an unstructured context, Jameson and Mavriplis’ explicit algorithm is used. Convergence acceleration is obtained using a spatially variable time stepping procedure.