A Survey and Classification of Software Testing Tools

Software testing is one of the essential parts in software engineering process. The objective of the study was to describe software testing tools and the corresponding use. The thesis contains examples of software testing tools usage. The study was conducted as a literature study, with focus on current software testing practices and quality assurance standards. In the paper a tool classifier was employed, and testing tools presented in study were classified according to it. We found that it is difficult to distinguish current available tools by certain testing activities as many of them contain functionality that exceeds scopes of a single testing type.

Energy harvesting methods for wireless sensor nodes in heavy-duty vehicles

The number of autonomous wireless sensor and control nodes has been increasing rapidly during the last decade. Until recently, these wireless nodes have been powered with batteries, which have lead to a short life cycle and high maintenance need. Due to these battery-related problems, new energy sources have been studied to power wireless nodes. One solution is energy harvesting, i.e. extracting energy from the ambient environment. Energy harvesting can provide a long-lasting power source for sensor nodes, with no need for maintenance. In this thesis, various energy harvesting technologies are studied whilst focusing on the theory of each technology and the state-of-the-art solutions of published studies and commercial solutions. In addition to energy harvesting, energy storage and energy management solutions are also studied as a subsystem of a whole energy source solution. Wireless nodes are also used in heavy-duty vehicles. Therefore a reliable, long-lasting and maintenance-free power source is also needed in this kind of environment. A forestry harvester has been used as a case study to study the feasibility of energy harvesting in a forestry harvester’s sliding boom. The energy harvester should be able to produce few milliwatts to power the target system, an independent limit switch.

Financier’s credit risk: A Performance-Based Classification Model

The purpose of this study is to view credit risk from the financier’s point of view in a theoretical framework. Results and aspects of the previous studies regarding measuring credit risk with accounting based scoring models are also examined. The theoretical framework and previous studies are then used to support the empirical analysis which aims to develop a credit risk measure for a bank’s internal use or a risk management tool for a company to indicate its credit risk to the financier. The study covers a sample of Finnish companies from 12 different industries and four different company categories and employs their accounting information from 2004 to 2008. The empirical analysis consists of six stage methodology process which uses measures of profitability, liquidity, capital structure and cash flow to determine financier’s credit risk, define five significant risk classes and produce risk classification model. The study is confidential until 15.10.2012.

Classification, comorbidity, heredity, and risk factors of female sexual dysfunctions

Female sexual dysfunctions, including desire, arousal, orgasm and pain problems, have been shown to be highly prevalent among women around the world. The etiology of these dysfunctions is unclear but associations with health, age, psychological problems, and relationship factors have been identified. Genetic effects explain individual variation in orgasm function to some extent but until now quantitative behavior genetic analyses have not been applied to other sexual functions. In addition, behavior genetics can be applied to exploring the cause of any observed comorbidity between the dysfunctions. Discovering more about the etiology of the dysfunctions may further improve the classification systems which are currently under intense debate. The aims of the present thesis were to evaluate the psychometric properties of a Finnish-language version of a commonly used questionnaire for measuring female sexual function, the Female Sexual Function Index (FSFI), in order to investigate prevalence, comorbidity, and classification, and to explore the balance of genetic and environmental factors in the etiology as well as the associations of a number of biopsychosocial factors with female sexual functions. Female sexual functions were studied through survey methods in a population based sample of Finnish twins and their female siblings. There were two waves of data collection. The first data collection targeted 5,000 female twins aged 33–43 years and the second 7,680 female twins aged 18–33 and their over 18–year-old female siblings (n = 3,983). There was no overlap between the data collections. The combined overall response rate for both data collections was 53% (n = 8,868), with a better response rate in the second (57%) compared to the first (45%). In order to measure female sexual function, the FSFI was used. It includes 19 items which measure female sexual function during the previous four weeks in six subdomains; desire, subjective arousal, lubrication, orgasm, sexual satisfaction, and pain. In line with earlier research in clinical populations, a six factor solution of the Finnish-language version of the FSFI received supported. The internal consistencies of the scales were good to excellent. Some questions about how to avoid overestimating the prevalence of extreme dysfunctions due to women being allocated the score of zero if they had had no sexual activity during the preceding four weeks were raised. The prevalence of female sexual dysfunctions per se ranged from 11% for lubrication dysfunction to 55% for desire dysfunction. The prevalence rates for sexual dysfunction with concomitant sexual distress, in other words, sexual disorders were notably lower ranging from 7% for lubrication disorder to 23% for desire disorder. The comorbidity between the dysfunctions was substantial most notably between arousal and lubrication dysfunction even if these two dysfunctions showed distinct patterns of associations with the other dysfunctions. Genetic influences on individual variation in the six subdomains of FSFI were modest but significant ranging from 3–11% for additive genetic effects and 5–18% for nonadditive genetic effects. The rest of the variation in sexual functions was explained by nonshared environmental influences. A correlated factor model, including additive and nonadditive genetic effects and nonshared environmental effects had the best fit. All in all, every correlation between the genetic factors was significant except between lubrication and pain. All correlations between the nonshared environment factors were significant showing that there is a substantial overlap in genetic and nonshared environmental influences between the dysfunctions. In general, psychological problems, poor satisfaction with the relationship, sexual distress, and poor partner compatibility were associated with more sexual dysfunctions. Age was confounded with relationship length but had over and above relationship length a negative effect on desire and sexual satisfaction and a positive effect on orgasm and pain functions. Alcohol consumption in general was associated with better desire, arousal, lubrication, and orgasm function. Women pregnant with their first child had fewer pain problems than nulliparous nonpregnant women. Multiparous pregnant women had more orgasm problems compared to multiparous nonpregnant women. Having children was associated with less orgasm and pain problems. The conclusions were that desire, subjective arousal, lubrication, orgasm, sexual satisfaction, and pain are separate entities that have distinct associations with a number of different biopsychosocial factors. However, there is also considerable comorbidity between the dysfunctions which are explained by overlap in additive genetic, nonadditive genetic and nonshared environmental influences. Sexual dysfunctions are highly prevalent and are not always associated with sexual distress and this relationship might be moderated by a good relationship and compatibility with partner. Regarding classification, the results supports separate diagnoses for subjective arousal and genital arousal as well as the inclusion of pain under sexual dysfunctions.

The Cellular Oxygen Sensor PHD2 in Cancer Growth

Adequate supply of oxygen is essential for the survival of multicellular organisms. However, in several conditions the supply of oxygen can be disturbed and the tissue oxygenation is compromised. This condition is termed hypoxia. Oxygen homeostasis is maintained by the regulation of both the use and delivery of oxygen through complex, sensitive and cell-type specific transcriptional responses to hypoxia. This is mainly achieved by one master regulator, a transcription factor called hypoxiainducible factor 1 (HIF-1). The amount of HIF-1 is under tight oxygen-dependent control by a family of oxygen-dependent prolyl hydroxylase domain proteins (PHDs) that function as the cellular oxygen sensors. Three family members (PHD1-3) are known to regulate HIF of which the PHD2 isoform is thought to be the main regulator of HIF-1. The supply of oxygen can be disturbed in pathophysiological conditions, such as ischemic disorders and cancer. Cancer cells in the hypoxic parts of the tumors exploit the ability of HIF-1 to turn on the mechanisms for their survival, resistance to treatment, and escape from the oxygen- and nutrient-deprived environment. In this study, the expression and regulation of PHD2 were studied in normal and cancerous tissues, and its significance in tumor growth. The results show that the expression of PHD2 is induced in hypoxic cells. It is overexpressed in head and neck squamous cell carcinomas and colon adenocarcinomas. Although PHD2 normally resides in the cytoplasm, nuclear translocation of PHD2 was also seen in a subset of tumor cells. Together with the overexpression, the nuclear localization correlated with the aggressiveness of the tumors. The nuclear localization of PHD2 caused an increase in the anchorage-independent growth of cancer cells. This study provides information on the role of PHD2, the main regulator of HIF expression, in cancer progression. This knowledge may prove to be valuable in targeting the HIF pathway in cancer treatment.

Implementing gateway monitoring service for infrastructure sensor networks

Wireless sensor networks and its applications have been widely researched and implemented in both commercial and non commercial areas. The usage of wireless sensor network has developed its market from military usage to daily use of human livings. Wireless sensor network applications from monitoring prospect are used in home monitoring, farm fields and habitant monitoring to buildings structural monitoring. As the usage boundaries of wireless sensor networks and its applications are emerging there are definite ongoing research, such as lifetime for wireless sensor network, security of sensor nodes and expanding the applications with modern day scenarios of applications as web services. The main focus in this thesis work is to study and implement monitoring application for infrastructure based sensor network and expand its usability as web service to facilitate mobile clients. The developed application is implemented for wireless sensor nodes information collection and monitoring purpose enabling home or office environment remote monitoring for a user.

Electrical Equivalent Circuit for Dry Bacteriorhodopsin Sensor

Bacteriorhodopsin (BR) is a photosensitive protein which functions as a light-driven proton pump. Due to its photoactivity, BR could be used in photosensing and information processing which has inspired researchers to study the photoelectric response and the appropriate measurement instrumentation for BR. In this thesis, the measurement instrumentation connected to a dry BR sensor was confirmed to affect the photovoltage response measured by using voltage amplifiers. Changing of the input impedance of the measurement instrumentation was shown to alter a part of the measured photovoltage response. The photocurrent measurements using transimpedance amplifier and the presented electrical equivalent circuit were used to show that the photocurrent measurements have no significant effect on the photoelectric response. The photocurrent was shown to be a derivate of the photovoltage response measured from the dry BR sensor when it was compared to the response measured with a voltage amplifier. This confirmed that another part of the photovoltage response was not affected by the measurement instrumentation. The time-variant behavior of the dry BR sensor was confirmed in both the photocurrent and the photovoltage measurements. This was caused by the fact that the capacitance of the dry BR sensor changes with the excitation light intensity.

Laserkeilainperustainen puulajiluokitus - puu- ja metsikkötekijöiden, opetusaineiston koon, laserintesiteetin normalisoinnin sekä keilainmallin vaikutus

Seloste artikkelista: Korpela, I., Ørka, H. O., Maltamo, M., Tokola, T. & Hyyppä, J. / Tree species classification using airborne LiDAR - effects of stand and tree parameters, downsizing of training set, intensity normalization, and sensor type. Silva Fennica 44 (2010) : 2, 319-339.

Heat flux measurement inside internal combustion engine with gradient heat flux sensor.

This master’s thesis is devoted to study different heat flux measurement techniques such as differential temperature sensors, semi-infinite surface temperature methods, calorimetric sensors and gradient heat flux sensors. The possibility to use Gradient Heat Flux Sensors (GHFS) to measure heat flux in the combustion chamber of compression ignited reciprocating internal combustion engines was considered in more detail. A. Mityakov conducted an experiment, where Gradient Heat Flux Sensor was placed in four stroke diesel engine Indenor XL4D to measure heat flux in the combustion chamber. The results which were obtained from the experiment were compared with model’s numerical output. This model (a one – dimensional single zone model) was implemented with help of MathCAD and the result of this implementation is graph of heat flux in combustion chamber in relation to the crank angle. The values of heat flux throughout the cycle obtained with aid of heat flux sensor and theoretically were sufficiently similar, but not identical. Such deviation is rather common for this type of experiment.

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.

Synthesis, characterization and chemical sensor application of conducting polymers

Polymeric materials that conduct electricity are highly interesting for fundamental studies and beneficial for modern applications in e.g. solar cells, organic field effect transistors (OFETs) as well as in chemical and bio‐sensing. Therefore, it is important to characterize this class of materials with a wide variety of methods. This work summarizes the use of electrochemistry also in combination with spectroscopic methods in synthesis and characterization of electrically conducting polymers and other π‐conjugated systems. The materials studied in this work are intended for organic electronic devices and chemical sensors. Additionally, an important part of the presented work, concerns rational approaches to the development of water‐based inks containing conducting particles. Electrochemical synthesis and electroactivity of conducting polymers can be greatly enhanced in room temperature ionic liquids (RTILs) in comparison to conventional electrolytes. Therefore, poly(para‐phyenylene) (PPP) was electrochemically synthesized in the two representative RTILs: bmimPF6 and bmiTf2N (imidazolium and pyrrolidinium‐based salts, respectively). It was found that the electrochemical synthesis of PPP was significantly enhanced in bmimPF6. Additionally, the results from doping studies of PPP films indicate improved electroactivity in bmimPF6 during oxidation (p‐doping) and in bmiTf2N in the case of reduction (n‐doping). These findings were supported by in situ infrared spectroscopy studies. Conducting poly(benzimidazobenzophenanthroline) (BBL) is a material which can provide relatively high field‐effect mobility of charge carriers in OFET devices. The main disadvantage of this n‐type semiconductor is its limited processability. Therefore in this work BBL was functionalized with poly(ethylene oxide) PEO, varying the length of side chains enabling water dispersions of the studied polymer. It was found that functionalization did not distract the electrochemical activity of the BBL backbone while the processability was improved significantly in comparison to conventional BBL. Another objective was to study highly processable poly(3,4‐ethylenedioxythiophene) poly(styrenesulfonate) (PEDOT:PSS) water‐based inks for controlled patterning scaled‐down to nearly a nanodomain with the intention to fabricate various chemical sensors. Developed PEDOT:PSS inks greatly improved printing of nanoarrays and with further modification with quaternary ammonium cations enabled fabrication of PEDOT:PSS‐based chemical sensors for lead (II) ions with enhanced adhesion and stability in aqueous environments. This opens new possibilities for development of PEDOT:PSS films that can be used in bio‐related applications. Polycyclic aromatic hydrocarbons (PAHs) are a broad group of π‐conjugated materials consisting of aromatic rings in the range from naphthalene to even hundred rings in one molecule. The research on this type of materials is intriguing, due to their interesting optical properties and resemblance of graphene. The objective was to use electrochemical synthesis to yield relatively large PAHs and fabricate electroactive films that could be used as template material in chemical sensors. Spectroscopic, electrochemical and electrical investigations evidence formation of highly stable films with fast redox response, consisting of molecules with 40 to 60 carbon atoms. Additionally, this approach in synthesis, starting from relatively small PAH molecules was successfully used in chemical sensor for lead (II).

Probabilistic position and orientation estimation of rigid objects using an RGB-D sensor

The recent emergence of low-cost RGB-D sensors has brought new opportunities for robotics by providing affordable devices that can provide synchronized images with both color and depth information. In this thesis, recent work on pose estimation utilizing RGBD sensors is reviewed. Also, a pose recognition system for rigid objects using RGB-D data is implemented. The implementation uses half-edge primitives extracted from the RGB-D images for pose estimation. The system is based on the probabilistic object representation framework by Detry et al., which utilizes Nonparametric Belief Propagation for pose inference. Experiments are performed on household objects to evaluate the performance and robustness of the system.

Support vector machines in spectral data classification

Työssä käydään läpi tukivektorikoneiden teoreettista pohjaa sekä tutkitaan eri parametrien vaikutusta spektridatan luokitteluun.

Service offering classification for logistics services

This thesis studies the development of service offering model that creates added-value for customers in the field of logistics services. The study focusses on offering classification and structures of model. The purpose of model is to provide value-added solutions for customers and enable superior service experience. The aim of thesis is to define what customers expect from logistics solution provider and what value customers appreciate so greatly that they could invest in value-added services. Value propositions, costs structures of offerings and appropriate pricing methods are studied. First, literature review of creating solution business model and customer value is conducted. Customer value is found out with customer interviews and qualitative empiric data is used. To exploit expertise knowledge of logistics, innovation workshop tool is utilized. Customers and experts are involved in the design process of model. As a result of thesis, three-level value-added service offering model is created based on empiric and theoretical data. Offerings with value propositions are proposed and the level of model reflects the deepness of customer-provider relationship and the amount of added value. Performance efficiency improvements and cost savings create the most added value for customers. Value-based pricing methods, such as performance-based models are suggested to apply. Results indicate the interest of benefitting networks and partnership in field of logistics services. Networks development is proposed to be investigated further.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.