Home Blood Pressure Measurement – Epidemiology and Clinical Application

Verenpaineen kotimittaus − epidemiologia ja kliininen käyttö Kohonnutta verenpainetta, maailmanlaajuisesti merkittävintä ennenaikaiselle kuolemalle altistavaa riskitekijää, ei voida tunnistaa tai hoitaa ilman tarkkoja ja käytännöllisiä verenpaineen mittausmenetelmiä. Verenpaineen kotimittaus on saavuttanut suuren suosion potilaiden keskuudessa. Lääkärit eivät ole kuitenkaan vielä täysin hyväksyneet verenpaineen kotimittausta, sillä riittävä todistusaineisto sen toimivuudesta ja eduista on puuttunut. Tämän tutkimuksen tarkoituksena oli osoittaa, että kotona mitattu verenpaine (kotipaine) on perinteistä vastaanotolla mitattua verenpainetta (vastaanottopaine) tarkempi, ja että se on tehokas myös kliinisessä käytössä. Tutkimme kotipaineen käyttöä verenpainetaudin diagnosoinnissa ja hoidossa. Lisäksi tarkastelimme kotipaineen yhteyttä verenpainetaudin aiheuttamiin kohde-elinvaurioihin. Ensimmäinen aineisto, joka oli edustava otos Suomen aikuisväestöstä, koostui 2 120 45–74-vuotiaasta tutkimushenkilöstä. Tutkittavat mittasivat kotipainettaan viikon ajan ja osallistuivat terveystarkastukseen, johon sisältyi kliinisen tutkimuksen ja haastattelun lisäksi sydänfilmin otto ja vastaanottopaineen mittaus. 758 tutkittavalle suoritettiin lisäksi kaulavaltimon seinämän intima-mediakerroksen paksuuden (valtimonkovettumataudin mittari) mittaus ja 237:lle valtimon pulssiaallon nopeuden (valtimojäykkyyden mittari) mittaus. Toisessa aineistossa, joka koostui 98 verenpainetautia sairastavasta potilaasta, hoitoa ohjattiin satunnaistamisesta riippuen joko ambulatorisen eli vuorokausirekisteröinnillä mitatun verenpaineen tai kotipaineen perusteella. Vastaanottopaine oli kotipainetta merkittävästi korkeampi (systolisen/diastolisen paineen keskiarvoero oli 8/3 mmHg) ja yksimielisyys verenpainetaudin diagnoosissa kahden menetelmän välillä oli korkeintaan kohtalainen (75 %). 593 tutkittavasta, joilla oli kohonnut verenpaine vastaanotolla, 38 %:lla oli normaali verenpaine kotona eli ns. valkotakkiverenpaine. Verenpainetauti voidaan siis ylidiagnosoida joka kolmannella potilaalla seulontatilanteessa. Valkotakkiverenpaine oli yhteydessä lievästi kohonneeseen verenpaineeseen, matalaan painoindeksiin ja tupakoimattomuuteen, muttei psykiatriseen sairastavuuteen. Valkotakkiverenpaine ei kuitenkaan vaikuttaisi olevan täysin vaaraton ilmiö ja voi ennustaa tulevaa verenpainetautia, sillä siitä kärsivien sydän- ja verisuonitautien riskitekijäprofiili oli normaalipaineisten ja todellisten verenpainetautisten riskitekijäprofiilien välissä. Kotipaineella oli vastaanottopainetta vahvempi yhteys verenpainetaudin aiheuttamiin kohde-elinvaurioihin (intima-mediakerroksen paksuus, pulssiaallon nopeus ja sydänfilmistä todettu vasemman kammion suureneminen). Kotipaine oli tehokas verenpainetaudin hoidon ohjaaja, sillä kotipaineeseen ja ambulatoriseen paineeseen, jota on pidetty verenpainemittauksen ”kultaisena standardina”, perustuva lääkehoidon ohjaus johti yhtä hyvään verenpaineen hallintaan. Tämän ja aikaisempien tutkimusten tulosten pohjalta voidaan todeta, että verenpaineen kotimittaus on selkeä parannus perinteiseen vastaanotolla tapahtuvaan verenpainemittaukseen verrattuna. Verenpaineen kotimittaus on käytännöllinen, tarkka ja laajasti saatavilla oleva menetelmä, josta voi tulla jopa ensisijainen vaihtoehto verenpainetautia diagnosoitaessa ja hoitaessa. Verenpaineen mittauskäytäntöön tarvitaan muutos, sillä näyttöön perustuvan lääketieteen perusteella vaikuttaa, että vastaanotolla tapahtuvaa verenpainemittausta tulisi käyttää vain seulontatarkoitukseen.

Reduction and Analysis Methods of Indigo

Throughout history indigo was derived from various plants for example Dyer’s Woad (Isatis tinctoria L.) in Europe. In the 19th century were the synthetic dyes developed and nowadays indigo is mainly synthesized from by-products of fossil fuels. Indigo is a so-called vat dye, which means that it needs to be reduced to its water soluble leucoform before dyeing. Nowadays, most of the industrial reduction is performed chemically by sodium dithionite. However, this is considered environmentally unfavourable because of waste waters contaminating degradation products. Therefore there has been interest to find new possibilities to reduce indigo. Possible alternatives for the application of dithionite as the reducing agent are biologically induced reduction and electrochemical reduction. Glucose and other reducing sugars have recently been suggested as possible environmentally friendly alternatives as reducing agents for sulphur dyes and there have also been interest in using glucose to reduce indigo. In spite of the development of several types of processes, very little is known about the mechanism and kinetics associated with the reduction of indigo. This study aims at investigating the reduction and electrochemical analysis methods of indigo and give insight on the reduction mechanism of indigo. Anthraquinone as well as it’s derivative 1,8-dihydroxyanthraquinone were discovered to act as catalysts for the glucose induced reduction of indigo. Anthraquinone introduces a strong catalytic effect which is explained by invoking a molecular “wedge effect” during co-intercalation of Na+ and anthraquinone into the layered indigo crystal. The study includes also research on the extraction of plant-derived indigo from woad and the examination of the effect of this method to the yield and purity of indigo. The purity has been conventionally studied spectrophotometrically and a new hydrodynamic electrode system is introduced in this study. A vibrating probe is used in following electrochemically the leuco-indigo formation with glucose as a reducing agent.

Grounding in a wind power application

The subject of this master’s thesis is to research grounding in a particular wind power application. The aim is to define how the grounding from different points effects to the function of the whole system. The investigated subjects are generator voltage spikes, ground currents and system fault situations. The first part of this thesis represents power electronics, which is commonly used in wind power systems. The second part concentrates more to the grounding, electrical safety demands and potential fault situations. The object of the simulations is to investigate voltage spikes and fault situations. Measurements will be made with small-scale setup and in the last part simulation and measurement results are compared to each other and to a full-scale system.

A Development and Application of a Three-Dimensional Model for a CFB Gasifier

The developing energy markets and rising energy system costs have sparked the need to find new forms of energy production and increase the self-sufficiency of energy production. One alternative is gasification, whose principles have been known for decades, but it is only recently when the technology has become a true alternative. However, in order to meet the requirements of modern energy production methods, it is necessary to study the phenomenon thoroughly. In order to understand the gasification process better and optimize it from the viewpoint of ecology and energy efficiency, it is necessary to develop effective and reliable modeling tools for gasifiers. The main aims of this work have been to understand gasification as a process and furthermore to develop an existing three-dimensional circulating fluidized bed modeling tool for modeling of gasification. The model is applied to two gasification processes of 12 and 50 MWth. The results of modeling and measurements have been compared and subsequently reviewed. The work was done in co-operation with Lappeenranta University of Technology and Foster Wheeler Energia Oy.

Methods for construction and analysis of computational models in systems biology : applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis.

Kernel-Based Ranking. Methods for Learning and Performance Estimation

Machine learning provides tools for automated construction of predictive models in data intensive areas of engineering and science. The family of regularized kernel methods have in the recent years become one of the mainstream approaches to machine learning, due to a number of advantages the methods share. The approach provides theoretically well-founded solutions to the problems of under- and overfitting, allows learning from structured data, and has been empirically demonstrated to yield high predictive performance on a wide range of application domains. Historically, the problems of classification and regression have gained the majority of attention in the field. In this thesis we focus on another type of learning problem, that of learning to rank. In learning to rank, the aim is from a set of past observations to learn a ranking function that can order new objects according to how well they match some underlying criterion of goodness. As an important special case of the setting, we can recover the bipartite ranking problem, corresponding to maximizing the area under the ROC curve (AUC) in binary classification. Ranking applications appear in a large variety of settings, examples encountered in this thesis include document retrieval in web search, recommender systems, information extraction and automated parsing of natural language. We consider the pairwise approach to learning to rank, where ranking models are learned by minimizing the expected probability of ranking any two randomly drawn test examples incorrectly. The development of computationally efficient kernel methods, based on this approach, has in the past proven to be challenging. Moreover, it is not clear what techniques for estimating the predictive performance of learned models are the most reliable in the ranking setting, and how the techniques can be implemented efficiently. The contributions of this thesis are as follows. First, we develop RankRLS, a computationally efficient kernel method for learning to rank, that is based on minimizing a regularized pairwise least-squares loss. In addition to training methods, we introduce a variety of algorithms for tasks such as model selection, multi-output learning, and cross-validation, based on computational shortcuts from matrix algebra. Second, we improve the fastest known training method for the linear version of the RankSVM algorithm, which is one of the most well established methods for learning to rank. Third, we study the combination of the empirical kernel map and reduced set approximation, which allows the large-scale training of kernel machines using linear solvers, and propose computationally efficient solutions to cross-validation when using the approach. Next, we explore the problem of reliable cross-validation when using AUC as a performance criterion, through an extensive simulation study. We demonstrate that the proposed leave-pair-out cross-validation approach leads to more reliable performance estimation than commonly used alternative approaches. Finally, we present a case study on applying machine learning to information extraction from biomedical literature, which combines several of the approaches considered in the thesis. The thesis is divided into two parts. Part I provides the background for the research work and summarizes the most central results, Part II consists of the five original research articles that are the main contribution of this thesis.

Design of salient pole PM synchronous machines for a vehicle traction application – Analysis and

This doctoral thesis presents a study on the development of a liquid-cooled frame salient pole permanent-magnet-exited traction machine for a four-wheel-driven electric car. The emphasis of the thesis is put on a radial flux machine design in order to achieve a light-weight machine structure for traction applications. The design features combine electromagnetic and thermal design methods, because traction machine operation does not have a strict operating point. Arbitrary load cycles and the flexible supply require special attention in the design process. It is shown that accurate modelling of the machine magnetic state is essential for high-performance operation. The saturation effect related to the cross-saturation has to be taken carefully into account in order to achieve the desired operation. Two prototype machines have been designed and built for testing: one totally enclosed machine with a special magnet module pole arrangement and another through-ventilated machine with a more traditional embedded magnet structure. Both structures are built with magnetically salient structures in order to increase the torque production capability with the reluctance torque component. Both machine structures show potential for traction usage. However, the traditional embedded magnet design turns out to be mechanically the more secure one of these two machine options.

Tunable lumped-element bandpass filters for Cognitive Radio application

In this thesis the design of bandpass filters tunable at 400 MHz – 800 MHz was under research. Microwave filters are vital components which provide frequency selectivity in wide variety of electronic systems operating at high frequencies. Due to the occurrence of multi-frequency bands communication and diverse applications of wireless devices, requirement of tunable filters exists. The one of potential implementation of frequency-agile filters is frontends and spectrum sensors in Cognitive Radio (CR). The principle of CR is to detect and operate at a particular available spectrum without interfering with the primary user’s signals. This new method allows improving the efficiency of utilizing allocated spectrum such as TV band (400 MHz – 800 MHz). The focus of this work is development of sufficiently compact, low cost tunable filters with quite narrow bandwidth using currently available lumped-element components and PCB board technology. Filter design, different topologies and methods of tuning of bandpass filters are considered in this work. As a result, three types of topologies of bandpass filter were simulated and realised. They use digitally tunable capacitors (DTCs) for adjusting central frequency at TV "white space" spectrum. Measurements revealed that schematics presented in this work have proper output response and filters are successfully tuned by DTCs.

Identification of research trends in the field of separation processes. Application of epidemiological model, citation analysis, text mining, and technical analysis of the financial markets

Choice of industrial development options and the relevant allocation of the research funds become more and more difficult because of the increasing R&D costs and pressure for shorter development period. Forecast of the research progress is based on the analysis of the publications activity in the field of interest as well as on the dynamics of its change. Moreover, allocation of funds is hindered by exponential growth in the number of publications and patents. Thematic clusters become more and more difficult to identify, and their evolution hard to follow. The existing approaches of research field structuring and identification of its development are very limited. They do not identify the thematic clusters with adequate precision while the identified trends are often ambiguous. Therefore, there is a clear need to develop methods and tools, which are able to identify developing fields of research. The main objective of this Thesis is to develop tools and methods helping in the identification of the promising research topics in the field of separation processes. Two structuring methods as well as three approaches for identification of the development trends have been proposed. The proposed methods have been applied to the analysis of the research on distillation and filtration. The results show that the developed methods are universal and could be used to study of the various fields of research. The identified thematic clusters and the forecasted trends of their development have been confirmed in almost all tested cases. It proves the universality of the proposed methods. The results allow for identification of the fast-growing scientific fields as well as the topics characterized by stagnant or diminishing research activity.

Statistical analysis of survey-based event history data with application to modeling of unemployment duration

Longitudinal surveys are increasingly used to collect event history data on person-specific processes such as transitions between labour market states. Surveybased event history data pose a number of challenges for statistical analysis. These challenges include survey errors due to sampling, non-response, attrition and measurement. This study deals with non-response, attrition and measurement errors in event history data and the bias caused by them in event history analysis. The study also discusses some choices faced by a researcher using longitudinal survey data for event history analysis and demonstrates their effects. These choices include, whether a design-based or a model-based approach is taken, which subset of data to use and, if a design-based approach is taken, which weights to use. The study takes advantage of the possibility to use combined longitudinal survey register data. The Finnish subset of European Community Household Panel (FI ECHP) survey for waves 1–5 were linked at person-level with longitudinal register data. Unemployment spells were used as study variables of interest. Lastly, a simulation study was conducted in order to assess the statistical properties of the Inverse Probability of Censoring Weighting (IPCW) method in a survey data context. The study shows how combined longitudinal survey register data can be used to analyse and compare the non-response and attrition processes, test the missingness mechanism type and estimate the size of bias due to non-response and attrition. In our empirical analysis, initial non-response turned out to be a more important source of bias than attrition. Reported unemployment spells were subject to seam effects, omissions, and, to a lesser extent, overreporting. The use of proxy interviews tended to cause spell omissions. An often-ignored phenomenon classification error in reported spell outcomes, was also found in the data. Neither the Missing At Random (MAR) assumption about non-response and attrition mechanisms, nor the classical assumptions about measurement errors, turned out to be valid. Both measurement errors in spell durations and spell outcomes were found to cause bias in estimates from event history models. Low measurement accuracy affected the estimates of baseline hazard most. The design-based estimates based on data from respondents to all waves of interest and weighted by the last wave weights displayed the largest bias. Using all the available data, including the spells by attriters until the time of attrition, helped to reduce attrition bias. Lastly, the simulation study showed that the IPCW correction to design weights reduces bias due to dependent censoring in design-based Kaplan-Meier and Cox proportional hazard model estimators. The study discusses implications of the results for survey organisations collecting event history data, researchers using surveys for event history analysis, and researchers who develop methods to correct for non-sampling biases in event history data.

Stochastic approximation methods in stochastic optimization

Stochastic approximation methods for stochastic optimization are considered. Reviewed the main methods of stochastic approximation: stochastic quasi-gradient algorithm, Kiefer-Wolfowitz algorithm and adaptive rules for them, simultaneous perturbation stochastic approximation (SPSA) algorithm. Suggested the model and the solution of the retailer's profit optimization problem and considered an application of the SQG-algorithm for the optimization problems with objective functions given in the form of ordinary differential equation.

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).

Application of cerium oxide thin films grown by atomic layer deposition for soot removal

The objective of the thesis is to study cerium oxide thin films grown by the atomic layer deposition (ALD) for soot removal. Cerium oxide is one of the most important heterogeneous catalysts and can be used in particulate filters and sensors in a diesel exhaust pipe. Its redox/oxidation properties are a key factor in soot oxidation. Thus, the cerium oxide coating can help to keep particulate filters and sensors clean permanently. The literature part of the thesis focuses on the soot removal, introducing the origin and structure of soot, reviewing emissions standards for diesel particulate matter, and presenting methods and catalysts for soot removal. In the experimental part the optimal ALD conditions for cerium oxide were found, the structural properties of cerium oxide thin films were analyzed, and the catalytic activity of the cerium oxide for soot oxidation was investigated. Studying ALD growth conditions of cerium oxide films and determining their critical thickness range are important to maximize the catalytic performance operating at comparatively low temperature. It was found that the cerium oxide film deposited at 300 °C with 2000 ALD cycles had the highest catalytic activity. Although the activity was still moderate and did not decrease the soot oxidation temperature enough for a real-life application. The cerium oxide thin film deposited at 300 °C has a different crystal structure, surface morphology and elemental composition with a higher Ce3+ concentration compared to the films deposited at lower temperatures. The different properties of the cerium oxide thin film deposited at 300 °C increase the catalytic activity most likely due to higher surface area and addition of the oxygen vacancies.

Letters from the War of Ecosystems – An Analysis of Independent Software Vendors in Mobile Application Marketplaces

The recent emergence of a new generation of mobile application marketplaces has changed the business in the mobile ecosystems. The marketplaces have gathered over a million applications by hundreds of thousands of application developers and publishers. Thus, software ecosystems—consisting of developers, consumers and the orchestrator—have emerged as a part of the mobile ecosystem. This dissertation addresses the new challenges faced by mobile application developers in the new ecosystems through empirical methods. By using the theories of two-sided markets and business ecosystems as the basis, the thesis assesses monetization and value creation in the market as well as the impact of electronic Word-of-Mouth (eWOM) and developer multihoming— i. e. contributing for more than one platform—in the ecosystems. The data for the study was collected with web crawling from the three biggest marketplaces: Apple App Store, Google Play and Windows Phone Store. The dissertation consists of six individual articles. The results of the studies show a gap in monetization among the studied applications, while a majority of applications are produced by small or micro-enterprises. The study finds only weak support for the impact of eWOM on the sales of an application in the studied ecosystem. Finally, the study reveals a clear difference in the multi-homing rates between the top application developers and the rest. This has, as discussed in the thesis, an impact on the future market analyses—it seems that the smart device market can sustain several parallel application marketplaces.

Virtual Runtime Application Partitions for Resource Management in Massively Parallel Architectures

This thesis presents a novel design paradigm, called Virtual Runtime Application Partitions (VRAP), to judiciously utilize the on-chip resources. As the dark silicon era approaches, where the power considerations will allow only a fraction chip to be powered on, judicious resource management will become a key consideration in future designs. Most of the works on resource management treat only the physical components (i.e. computation, communication, and memory blocks) as resources and manipulate the component to application mapping to optimize various parameters (e.g. energy efficiency). To further enhance the optimization potential, in addition to the physical resources we propose to manipulate abstract resources (i.e. voltage/frequency operating point, the fault-tolerance strength, the degree of parallelism, and the configuration architecture). The proposed framework (i.e. VRAP) encapsulates methods, algorithms, and hardware blocks to provide each application with the abstract resources tailored to its needs. To test the efficacy of this concept, we have developed three distinct self adaptive environments: (i) Private Operating Environment (POE), (ii) Private Reliability Environment (PRE), and (iii) Private Configuration Environment (PCE) that collectively ensure that each application meets its deadlines using minimal platform resources. In this work several novel architectural enhancements, algorithms and policies are presented to realize the virtual runtime application partitions efficiently. Considering the future design trends, we have chosen Coarse Grained Reconfigurable Architectures (CGRAs) and Network on Chips (NoCs) to test the feasibility of our approach. Specifically, we have chosen Dynamically Reconfigurable Resource Array (DRRA) and McNoC as the representative CGRA and NoC platforms. The proposed techniques are compared and evaluated using a variety of quantitative experiments. Synthesis and simulation results demonstrate VRAP significantly enhances the energy and power efficiency compared to state of the art.