Hydrogen production from cassava processing wastewater in an anaerobic fixed bed reactor with bamboo as a support material

Attempting to associate waste treatment to the production of clean and renewable energy, this research sought to evaluate the biological production of hydrogen using wastewater from the cassava starch treatment industry, generated during the processes of extraction and purification of starch. This experiment was carried out in a continuous anaerobic reactor with a working volume of 3L, with bamboo stems as the support medium. The system was operated at a temperature of 36°C, an initial pH of 6.0 and under variations of organic load. The highest rate of hydrogen production, of 1.1 L.d-1.L-1, was obtained with application of an organic loading rate of 35 g.L-1.d-1, in terms of total sugar content and hydraulic retention time of 3h, with a prevalence of butyric and acetic acids as final products of the fermentation process. Low C/N ratios contributed to the excessive growth of the biomass, causing a reduction of up to 35% in hydrogen production, low percentages of H2 and high concentrations of CO2in the biogas.

Memristive Computing

Memristive computing refers to the utilization of the memristor, the fourth fundamental passive circuit element, in computational tasks. The existence of the memristor was theoretically predicted in 1971 by Leon O. Chua, but experimentally validated only in 2008 by HP Labs. A memristor is essentially a nonvolatile nanoscale programmable resistor — indeed, memory resistor — whose resistance, or memristance to be precise, is changed by applying a voltage across, or current through, the device. Memristive computing is a new area of research, and many of its fundamental questions still remain open. For example, it is yet unclear which applications would benefit the most from the inherent nonlinear dynamics of memristors. In any case, these dynamics should be exploited to allow memristors to perform computation in a natural way instead of attempting to emulate existing technologies such as CMOS logic. Examples of such methods of computation presented in this thesis are memristive stateful logic operations, memristive multiplication based on the translinear principle, and the exploitation of nonlinear dynamics to construct chaotic memristive circuits. This thesis considers memristive computing at various levels of abstraction. The first part of the thesis analyses the physical properties and the current-voltage behaviour of a single device. The middle part presents memristor programming methods, and describes microcircuits for logic and analog operations. The final chapters discuss memristive computing in largescale applications. In particular, cellular neural networks, and associative memory architectures are proposed as applications that significantly benefit from memristive implementation. The work presents several new results on memristor modeling and programming, memristive logic, analog arithmetic operations on memristors, and applications of memristors. The main conclusion of this thesis is that memristive computing will be advantageous in large-scale, highly parallel mixed-mode processing architectures. This can be justified by the following two arguments. First, since processing can be performed directly within memristive memory architectures, the required circuitry, processing time, and possibly also power consumption can be reduced compared to a conventional CMOS implementation. Second, intrachip communication can be naturally implemented by a memristive crossbar structure.

Optimizing Customer Energy Invoice Calculation with Parallel Computation

Diplomityön tarkoituksena on optimoida asiakkaiden sähkölaskun laskeminen hajautetun laskennan avulla. Älykkäiden etäluettavien energiamittareiden tullessa jokaiseen kotitalouteen, energiayhtiöt velvoitetaan laskemaan asiakkaiden sähkölaskut tuntiperusteiseen mittaustietoon perustuen. Kasvava tiedonmäärä lisää myös tarvittavien laskutehtävien määrää. Työssä arvioidaan vaihtoehtoja hajautetun laskennan toteuttamiseksi ja luodaan tarkempi katsaus pilvilaskennan mahdollisuuksiin. Lisäksi ajettiin simulaatioita, joiden avulla arvioitiin rinnakkaislaskennan ja peräkkäislaskennan eroja. Sähkölaskujen oikeinlaskemisen tueksi kehitettiin mittauspuu-algoritmi.

Application of capillary electrophoretic methods for determining carbohydrates and aliphatic carboxylic acids formed during wood processing

Knowledge of the behaviour of cellulose, hemicelluloses, and lignin during wood and pulp processing is essential for understanding and controlling the processes. Determination of monosaccharide composition gives information about the structural polysaccharide composition of wood material and helps when determining the quality of fibrous products. In addition, monitoring of the acidic degradation products gives information of the extent of degradation of lignin and polysaccharides. This work describes two capillary electrophoretic methods developed for the analysis of monosaccharides and for the determination of aliphatic carboxylic acids from alkaline oxidation solutions of lignin and wood. Capillary electrophoresis (CE), in its many variants is an alternative separation technique to chromatographic methods. In capillary zone electrophoresis (CZE) the fused silica capillary is filled with an electrolyte solution. An applied voltage generates a field across the capillary. The movement of the ions under electric field is based on the charge and hydrodynamic radius of ions. Carbohydrates contain hydroxyl groups that are ionised only in strongly alkaline conditions. After ionisation, the structures are suitable for electrophoretic analysis and identification through either indirect UV detection or electrochemical detection. The current work presents a new capillary zone electrophoretic method, relying on in-capillary reaction and direct UV detection at the wavelength of 270 nm. The method has been used for the simultaneous separation of neutral carbohydrates, including mono- and disaccharides and sugar alcohols. The in-capillary reaction produces negatively charged and UV-absorbing compounds. The optimised method was applied to real samples. The methodology is fast since no other sample preparation, except dilution, is required. A new method for aliphatic carboxylic acids in highly alkaline process liquids was developed. The goal was to develop a method for the simultaneous analysis of the dicarboxylic acids, hydroxy acids and volatile acids that are oxidation and degradation products of lignin and wood polysaccharides. The CZE method was applied to three process cases. First, the fate of lignin under alkaline oxidation conditions was monitored by determining the level of carboxylic acids from process solutions. In the second application, the degradation of spruce wood using alkaline and catalysed alkaline oxidation were compared by determining carboxylic acids from the process solutions. In addition, the effectiveness of membrane filtration and preparative liquid chromatography in the enrichment of hydroxy acids from black liquor was evaluated, by analysing the effluents with capillary electrophoresis.

Reflexive model of research-based theatre – processing innovation at the crossroads of theatre, reflection and practice-based innovation activities

Contemporary organisations have to embrace the notion of doing ‘more with less’. This challenges knowledge production within companies and public organisations, forcing them to reorganise their structures and rethink what knowledge production actually means in the context of innovation and how knowledge is actually produced among various professional groups within the organisation in their everyday actions. Innovations are vital for organisational survival, and ‘ordinary’ employees and customers are central but too-often ignored producers of knowledge for contemporary organisations. Broader levels of participation and reflexive practices are needed. This dissertation discusses the missing links between innovation research conducted in the context of industrial management, arts, and culture; applied drama and theatre practices (specifically post-Boalian approaches); and learning – especially organising reflection – in organisational settings. This dissertation (1) explores and extends the role of research-based theatre to organising reflection and reflexive practices in the context of practice-based innovation, (2) develops a reflexive model of RBT for investigating and developing practice-based organisational process innovations in order to contribute to the development of a tool for innovation management and analysis, and (3) operationalises this model within private- and publicsector organisations. The proposed novel reflexive model of research-based theatre for investigating and developing practice-based organisational process innovations extends existing methods and offers a different way of organising reflection and reflexive practices in the context of general innovation management. The model was developed through five participatory action research processes conducted in four different organisations. The results provide learning steps – a reflection path – for understanding complex organisational life, people, and relations amid renewal and change actions. The proposed model provides a new approach to organising and cultivating reflexivity in practice-based innovation activities via research-based theatre. The results can be utilised as a guideline when processing practice-based innovation within private or public organisations. The model helps innovation managers to construct, together with their employees, temporary communities where they can learn together through reflecting on their own and each others’ experiences and to break down assumptions related to their own perspectives. The results include recommendations for practical development steps applicable in various organisations with regard to (i) application of research-based theatre and (ii) related general innovation management. The dissertation thus contributes to the development of novel learning approaches in knowledge production. Keywords: practice-based innovation, research-based theatre, learning, reflection, mode 2b knowledge production

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.

The Shadow Moiré method using the phase shifting technique and digital image processing: computational implementation and application to the 3D-reconstruction of a buckled plate

The Shadow Moiré fringe patterns are level lines of equal depth generated by interference between a master grid and its shadow projected on the surface. In simplistic approach, the minimum error is about the order of the master grid pitch, that is, always larger than 0,1 mm, resulting in an experimental technique of low precision. The use of a phase shift increases the accuracy of the Shadow Moiré technique. The current work uses the phase shifting method to determine the surfaces three-dimensional shape using isothamic fringe patterns and digital image processing. The current study presents the method and applies it to images obtained by simulation for error evaluation, as well as to a buckled plate, obtaining excellent results. The method hands itself particularly useful to decrease the errors in the interpretation of the Moiré fringes that can adversely affect the calculations of displacements in pieces containing many concave and convex regions in relatively small areas.

Inverse convection problem of simultaneous estimation of two boundary heat fluxes in parallel plate channels

This paper deals with the use of the conjugate gradient method of function estimation for the simultaneous identification of two unknown boundary heat fluxes in parallel plate channels. The fluid flow is assumed to be laminar and hydrodynamically developed. Temperature measurements taken inside the channel are used in the inverse analysis. The accuracy of the present solution approach is examined by using simulated measurements containing random errors, for strict cases involving functional forms with discontinuities and sharp-corners for the unknown functions. Three different types of inverse problems are addressed in the paper, involving the estimation of: (i) Spatially dependent heat fluxes; (ii) Time-dependent heat fluxes; and (iii) Time and spatially dependent heat fluxes.

Numerical Simulation of the Cavitation in the Hydrodynamic Lubrication of Journal Bearings: a Parallel Algorithm

In this paper we present an algorithm for the numerical simulation of the cavitation in the hydrodynamic lubrication of journal bearings. Despite the fact that this physical process is usually modelled as a free boundary problem, we adopted the equivalent variational inequality formulation. We propose a two-level iterative algorithm, where the outer iteration is associated to the penalty method, used to transform the variational inequality into a variational equation, and the inner iteration is associated to the conjugate gradient method, used to solve the linear system generated by applying the finite element method to the variational equation. This inner part was implemented using the element by element strategy, which is easily parallelized. We analyse the behavior of two physical parameters and discuss some numerical results. Also, we analyse some results related to the performance of a parallel implementation of the algorithm.

A university fund for Article Processing Charges - experiences from Lund University

Presentation at the Nordic Perspectives on Open Access and Open Science seminar, Helsinki, October 15, 2013

Seismic motion simulation based on Cassino Parallel Manipulator

In this paper we present a study of feasibility by using Cassino Parallel Manipulator (CaPaMan) as an earthquake simulator. We propose a suitable formulation to simulate the frequency, amplitude and acceleration magnitude of seismic motion by means of the movable platform motion by giving a suitable input motion. In this paper we have reported numerical simulations that simulate the three principal earthquake types for a seismic motion: one at the epicenter (having a vertical motion), another far from the epicenter (with the motion on a horizontal plane), and a combined general motion (with a vertical and horizontal motion).

Energy-efficient control strategies for variable speed driven parallel pumping systems based on pump operation point monitoring with frequency converters

The pumping processes requiring wide range of flow are often equipped with parallelconnected centrifugal pumps. In parallel pumping systems, the use of variable speed control allows that the required output for the process can be delivered with a varying number of operated pump units and selected rotational speed references. However, the optimization of the parallel-connected rotational speed controlled pump units often requires adaptive modelling of both parallel pump characteristics and the surrounding system in varying operation conditions. The available information required for the system modelling in typical parallel pumping applications such as waste water treatment and various cooling and water delivery pumping tasks can be limited, and the lack of real-time operation point monitoring often sets limits for accurate energy efficiency optimization. Hence, alternatives for easily implementable control strategies which can be adopted with minimum system data are necessary. This doctoral thesis concentrates on the methods that allow the energy efficient use of variable speed controlled parallel pumps in system scenarios in which the parallel pump units consist of a centrifugal pump, an electric motor, and a frequency converter. Firstly, the suitable operation conditions for variable speed controlled parallel pumps are studied. Secondly, methods for determining the output of each parallel pump unit using characteristic curve-based operation point estimation with frequency converter are discussed. Thirdly, the implementation of the control strategy based on real-time pump operation point estimation and sub-optimization of each parallel pump unit is studied. The findings of the thesis support the idea that the energy efficiency of the pumping can be increased without the installation of new, more efficient components in the systems by simply adopting suitable control strategies. An easily implementable and adaptive control strategy for variable speed controlled parallel pumping systems can be created by utilizing the pump operation point estimation available in modern frequency converters. Hence, additional real-time flow metering, start-up measurements, and detailed system model are unnecessary, and the pumping task can be fulfilled by determining a speed reference for each parallel-pump unit which suggests the energy efficient operation of the pumping system.

Customer knowledge processing in maintenance business: case study

The purpose of the study is to examine and increase knowledge on customer knowledge processing in B2B context from sales perspective. Further objectives include identifying possible inhibiting and enabling factors in each phase of the process. The theoretical framework is based on customer knowledge management literature. The study is a qualitative study, in which the research method utilized is a case study. The empirical part was implemented in a case company by conducting in-depth interviews with the company’s value-selling champions located internationally. Context was maintenance business. Altogether 17 interviews were conducted. The empirical findings indicate that customer knowledge processing has not been clearly defined within the maintenance business line. Main inhibiting factors in acquiring customer knowledge are lack of time and vast amount of customer knowledge received. Enabling factors recognized are good customer relationships and sales representatives’ communication skills. Internal dissemination of knowledge is mainly inhibited by lack of time and restrictions in customer relationship management systems. Enabling factors are composition of the sales team and updated customer knowledge. Inhibiting utilization is lack of goals to utilize the customer knowledge and a low quality of the knowledge. Moreover, customer knowledge is not systematically updated nor analysed. Management of customer knowledge is based on the CRM system. As implications of the study, it is suggested for the case company to define customer knowledge processing in order to support maintenance business process.

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.

QUALITY OF PROCESSING TOMATO FRUITS IN COMPETITION WITH Solanum americanum

ABSTRACT Five experiments were conducted to evaluate the hypothesis that Solanum americanum density and time of coexistence affect the quality of processing tomato fruit. The tomato crop was established using either the direct drilling or the transplanting technique. The factors evaluated consisted of weed density (from 0 up to 6 plants m-2) and time of weed interference (early bloom stage, full flowering stage, fruit filling, and harvest time). The effects of competition on tomato fruit quality were analysed using a multiple model. Tomato variables evaluated included industrial fruit types (which depended on ripeness and disease infection) and soluble solids level(obrix). Tomato fruit quality is dependent on the factors tested. Under low densities (< 6 plants m-2) of S. americanum there was a small impact on the quality of the tomato fruits. The percentage of grade A (mature fruit with red color and without pathogen infection) tomato fruits is the variable most affect by the independent variables. The impact of these independent variables on the percentage of grade C (green and/or with more than 15% disease infection) tomato yield was of smaller magnitude and in an inverse trend as the observed for grade A. The level of soluble solids was influenced by the weed interference on only two experiments, but the impact was of small magnitude. The impact of the results on current and future crop management practices is discussed.