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A current bottleneck that prevents Machine Learning (ML) from being successful outside of a few restricted fields such as chess playing and highway driving is its impairment in ap- propriately using context to infer the meaning of what it is observing. This paper describes techniques to allow ML systems to derive meaning from context, derived from how the human cortex works. In particular, this paper shows how the multiplication a horizontal vector representing a Sparse Distributed Representation (SDR) of patterns in sensory data by a vertical vector representing a SDR of patterns in context data followed by a pattern recognition operation on the result- ing matrix results in the integration of relevant context and in the output of data containing meaning.

Recent discoveries clarified the role of Layers 2, 3 and 4 of the neocortex as recognizers and predictors of feedforward patterns. However, the roles of Layers 5 and 6 are still unclear. In this paper, I propose that the function of Layer 5 is to recognize patterns representing *needs* for manipulations: actions that can be both physical (e.g., motor actions) and mental (e.g., cognitive tasks such as mental rotations). Such manipulations are used to help us survive (e.g. fight, find food) and to disambiguate the local context of feedforward input (i.e., understanding to which object do sensorial stimuli belong to).

In this paper, the author examines the differences in handling complexity between the human brain and artificial intelligences. It will be shown how the current modularity and tendency to reduce complexity of most current AIs is a limit to their potential to reach artificial general intelligence (AGI). Finally, techniques to address these limitations and to properly address complexity are ad- dressed.

The interest in video anomaly detection systems that can detect different types of anomalies, such as violent behaviours in surveillance videos, has gained traction in recent years. The current approaches employ deep learning to perform anomaly detection in videos, but this approach has multiple problems. For example, deep learning in general has issues with noise, concept drift, explainability, and training data volumes. Additionally, anomaly detection in itself is a complex task and faces challenges such as unknownness, heterogeneity, and class imbalance. Anomaly detection using deep learning is therefore mainly constrained to generative models such as generative adversarial networks and autoencoders due to their unsupervised nature; however, even they suffer from general deep learning issues and are hard to properly train. In this paper, we explore the capabilities of the Hierarchical Temporal Memory (HTM) algorithm to perform anomaly detection in videos, as it has favorable properties such as noise tolerance and online learning which combats concept drift. We introduce a novel version of HTM, named GridHTM, which is a grid-based HTM architecture specifically for anomaly detection in complex videos such as surveillance footage. We have tested GridHTM using the VIRAT video surveillance dataset, and the subsequent evaluation results and online learning capabilities prove the great potential of using our system for real-time unsupervised anomaly detection in complex videos.

One of the main obstacles to perovskite solar cells (PSCs) entering the market is the doping-induced degradation of expensive hole transport materials (HTMs), which results in poor device stability. Although lithium bis(trifluoromethanesulfonyl)imide (Li-TFSI) and 4-tert-butylpyridine (4-tBp) as additives are commonly used in HTMs, they often lead to low device stability and reproducibility due to their hygroscopic and volatile nature. In this study, we incorporated the dilithium phthalocyanine (Li2Pc) molecule into the Spiro-OMeTAD precursor solution with Li-TFSI and 4-tBp to produce triple-cation PSCs with an n-i-p configuration operating with high efficiency and stability. The addition of the Li2Pc molecule not only improves the perovskite/Spiro-OMeTAD interface but also increases the 7C-7C stacking in the thin-film phase according to the absorption and Raman results. Based on space-charge-limited current, photoluminescence, time-resolved photoluminescence and lifetime analysis measurements, charge transfer is improved with the Li2Pc molecule and charge recombination losses are reduced. As a result, the control device showed a power conversion efficiency (PCE) of 20.0% with JSC = 24.6 mA/cm2 and fill factor (FF) = 72.7%, whereas the Li2Pc-doped device exhibited an improved PCE of 20.6% with JSC = 25.0 mA/cm2 and FF = 73.6%. The addition of Li2Pc resulted in more stable and high-efficiency solar cells that maintained approximately 90% of the initial efficiency after 40 days., Presidency of the Turkish Republic Department of Strategy and Budget [2016K12-2841]; Scientific and Technical Research Council of Turkey (TUEBITAK) [1649B032100473], The authors acknowledge to Presidency of the Turkish Republic Department of Strategy and Budget for the financial support (Project Nr: 2016K12-2841) and Scientific and Technical Research Council of Turkey (TUB.ITAK) for financial support of T. Yesil (Grant Nr.: 1649B032100473). The authors are grateful to Ege University Directorate of Library and Documentation and Corporate Development Planning and Monitoring Coordination Unit (EGE-P.IK) for proofreading support.

Hierarchical Temporal Memory (HTM) is an unsupervised learning algorithm inspired by the features of the neocortex that can be used to continuously process stream data and detect anomalies, without requiring a large amount of data for training nor requiring labeled data. HTM is also able to continuously learn from samples, providing a model that is always up-to-date with respect to observations. These characteristics make HTM particularly suitable for supporting online failure prediction in cloud systems, which are systems with a dynamically changing behavior that must be monitored to anticipate problems. This paper presents the first systematic study that assesses HTM in the context of failure prediction. The results that we obtained considering 72 configurations of HTM applied to 12 different types of faults introduced in the Clearwater cloud system show that HTM can help to predict failures with sufficient effectiveness (F-measure = 0.76), representing an interesting practical alternative to (semi-)supervised algorithms., For associated video presentation, see https://youtu.be/Y6hTjEYAa-w , for associated slides, see https://www.slideshare.net/OlivieroRiganelli/cloud-failure-prediction-with-hierarchical-temporal-memory-an-empirical-assessment . In Proc. of the IEEE International Conference on Machine Learning and Applications (ICMLA 2021)

Over the years, and with the emergence of various technological innovations, the relevance of automatic learning methods has increased exponentially, and they now play a key role in society. More specifically, Deep Learning (DL), with the ability to recognize audio, image, and time series predictions, has helped to solve various types of problems. This paper aims to introduce a new theory, Hierarchical Temporal Memory (HTM), that applies to stock market prediction. HTM is based on the biological functions of the brain as well as its learning mechanism. The results are of significant relevance and show a low percentage of errors in the predictions made over time. It can be noted that the learning curve of the algorithm is fast, identifying trends in the stock market for all seven data universes using the same network. Although the algorithm suffered at the time a pandemic was declared, it was able to adapt and return to good predictions. HTM proved to be a good continuous learning method for predicting time series datasets., This work is funded by “FCT—Fundação para a Ciência e Tecnologia” within the R&D Units Project Scope: UIDB/00319/2020. The grant of R.S. is supported by the European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internalization Programme (COMPETE 2020). [Project n. 039479. Funding Reference: POCI-01-0247- FEDER-039479].

In this work, easy and simple structured perovskite solar cells (PSCs) are designed and characterized. Our effort was to reduce the cost of the fabrication of such PSC devices, first by using an inexpensive starting precursor (aqueous methylamine solution) for the perovskite materials and second by design in a PSC structure free of the expensive hole transport layer (HTL). The CH3NH3PbI3 perovskite sols were deposited onto a conductive FTO glass using the spin coating technique followed by heating at 100 °C for 10 min. The structure of the films was characterized by X-ray diffraction (XRD) and their optical properties by UV–VIS spectrophotometry and photoluminescence (PL). The obtained phase confirmed the formation of a tetragonal perovskite structure. Two different solvents have been used, dimethylformamide (DMF) and dimethyl sulfoxide (DMSO). The effect of the type and the concentration of the used solvent DMF and DMSO on the performance of the solar cells have been investigated. It was found that a 40% concentration of the perovskite material resulted in the optimum film thickness that gives the best photoelectric performance. The DMF-based PSC assembled solar cell exhibited the best performance with an open circuit voltage of 750 mV, a photocurrent density of 12.5 mA/cm2, and an overall photon to electric conversion efficiency of 5.7%; all these results are higher than those of cells made with DMSO. This work was supported financially partially by the PHC Al Maqdisi Grant No. 37038WF and the Palestinian German Joint Research Project PALGER2015-34-012. The authors would like to thank Mr. Ahmad Ashour for his assistance in UV–VIS measurements. In this work, easy and simple structured perovskite solar cells (PSCs) are designed and characterized. Our effort was to reduce the cost of the fabrication of such PSC devices, first by using an inexpensive starting precursor (aqueous methylamine solution) for the perovskite materials and second by design in a PSC structure free of the expensive hole transport layer (HTL). The CH3NH3PbI3 perovskite sols were deposited onto a conductive FTO glass using the spin coating technique followed by heating at 100 °C for 10 min. The structure of the films was characterized by X-ray diffraction (XRD) and their optical properties by UV–VIS spectrophotometry and photoluminescence (PL). The obtained phase confirmed the formation of a tetragonal perovskite structure. Two different solvents have been used, dimethylformamide (DMF) and dimethyl sulfoxide (DMSO). The effect of the type and the concentration of the used solvent DMF and DMSO on the performance of the solar cells have been investigated. It was found that a 40% concentration of the perovskite material resulted in the optimum film thickness that gives the best photoelectric performance. The DMF-based PSC assembled solar cell exhibited the best performance with an open circuit voltage of 750 mV, a photocurrent density of 12.5 mA/cm2, and an overall photon to electric conversion efficiency of 5.7%; all these results are higher than those of cells made with DMSO.

Perovskite solar cells (PSCs) have shown a significant improvement in power conversion efficiency (PCE) in the last few years. However, instability of PSCs is still a barrier for successful industrialization. In particular, spiro-OMeTAD with additives, despite a popular choice for hole transport material (HTM) in PSCs, is one of the causes for device thermal instability. In this work, one of additives in HTM, 4-tert-butylpyridine (tBP) is proved to be a factor of device instability under thermal treatment. Simple solution engineering which excludes the use of tBP in the HTM results in better device stability. The origin of thermal stability improvement shown in this work is attributed to the suppression of morphological change of HTM. Further researches towards thermal stability of perovskite material and dopant-free HTM should be essential since tBP removal was not able to solve the thermal stability issue.

En esta investigación se implementa un modelo predictivo para la asignación elástica de recursos sobre un entorno NFV/SDN basado en herramientas de código abierto como OpenStack. Usando como referencia una arquitectura que puede implementarse en entornos de bajo costo mediante herramientas de código abierto, se adecúa una metodología de autoescalamiento basada en recomendaciones del 3GPP. Luego, utilizando el algoritmo HTM para predecir tendencias, se efectúan asignaciones proactivas de recursos según reglas de violación de umbral, definidas en un algoritmo de autoescalamiento que sintetiza la asignación elástica de recursos. Los datos que enriquecen el modelo predictivo se generan siguiendo la tendencia de la demanda de recursos de una red móvil real. Los resultados muestran que, a través del modelo propuesto, es posible reducir el tiempo entre identificar la necesidad de escalar y culminar el escalamiento, en comparación con soluciones conocidas de computación en la nube. Además, es posible mantener la disponibilidad del servicio mientras se mejora la latencia en el tiempo de conexión al mismo. diagramas, ilustraciones a color, tablas This research implements a predictive model for the elastic allocation of resources on an NFV/SDN environment based on open source tools such as OpenStack. Using as a reference an architecture that can be implemented in low-cost environments using open source tools, an autoscaling methodology based on 3GPP recommendations is adapted. Then, using HTM algorithm to predict trends, proactive resource allocations are made based on threshold violation rules defined in an autoscaling algorithm that synthesizes elastic resource allocation. The data that enrich the predictive model is generated following the trend of the demand for resources of a real mobile network. The results show that, through the proposed model, it is possible to reduce the time between identifying the need to scale and completing the scaling compared to known cloud computing solutions. In addition, it is possible to maintain the availability of the service while improving the latency in connection time to it. Maestría Magíster en Ingeniería - Telecomunicaciones Metodología cuantitativa con la implementación real de sistemas de cómputo. Redes y Sistemas de Telecomunicaciones

This paper presents a framework which makes use of Sentiment Analysis techniques for retrieving Real World Data (RWD) starting from scheduled and corrective maintenance data. The scope of the analysis is to automatically extract features from maintenance work orders, in order to calculate Key Performance Indicators of maintenance operations on medical devices, for Health Technologies Assessment purposes. Data are extracted from Computerized Maintenance Management System reports of healthcare facilities.

Methyl ammonium lead iodide (MAPbI(3)) perovskite materials, have a significant impact in the field of solar cells. The solar-to power conversion efficiency of PSC, achieved so far is quite high as compared to the organic solar cells and dye sensitized solar cells. in this study we report the synthesis of perovskite (MAPbI(3)), the hole transport material (HTM) Nickel oxide and their application in the fabrication of perovskite solar cell (PSC) at room temperature. NiO has been an effective HTM due to its wideband gap and better carrier mobility. Noticeably, the PSC exhibits a power conversion efficiency (PCE) of 14.04%, which is the best performance reported so far in the sandwich structure employing NiO as HTM, with Voc = 0.78 V, J(sc) = 40 mA/cm(2) and fill factor = 0.45. (C) 2019 Elsevier Ltd. All rights reserved.

Planar perovskite solar cells were fabricated on F-doped SnO2 (FTO) coated glass substrates, with 4,4&rsquo, ((1E,1&rsquo, E)-((1,2,4-thiadiazole-3,5-diyl)bis(azaneylylidene))bis(methaneylylidene))bis(N,N-di-p-tolylaniline) (bTAThDaz) as hole transport material. This imine was synthesized in one step reaction, starting from commercially available and relatively inexpensive reagents. Electrochemical, optical, electrical, thermal and structural studies including thermal images and current-voltage measurements of the full solar cell devices characterize the imine in details. HOMO-LUMO of bTAThDaz were investigated by cyclic voltammetry (CV) and energy-resolved electrochemical impedance spectroscopy (ER-EIS) and were found at &minus, 5.19 eV and &minus, 2.52 eV (CV) and at &minus, 5.5 eV and &minus, 2.3 eV (ER-EIS). The imine exhibited 5% weight loss at 156 &deg, C. The electrical behavior and photovoltaic performance of the perovskite solar cell was examined for FTO/TiO2/perovskite/bTAThDaz/Ag device architecture. Constructed devices exhibited good time and air stability together with quite small effect of hysteresis. The observed solar conversion efficiency was 14.4%.

With the development of intrusion detection, a number of the intelligence algorithms (e.g., artificial neural networks) are introduced to enhance the performance of the intrusion detection systems. However, many intelligence algorithms should be trained before being used, and retrained regularly, which is not applicable for continuous online learning and analyzing. In this paper, a new online intrusion scenario discovery framework is proposed and the intelligence algorithm HTM (Hierarchical Temporal Memory) is employed to improve the performance of the online learning ability of the system. The proposed framework can discover and model intrusion scenarios, and the constructed model keeps evolving with the variance of the data. Additionally, a series of data preprocessing methods are introduced to enhance its adaptability to the noisy and twisted data. The experimental results show that the framework is effective in intrusion scenario discovery, and the discovered scenario is more concise and accurate than our previous work.

Planar perovskite solar cells were fabricated on F-doped SnO2 (FTO) coated glass substrates, with 4,4’-((1E,1’E)-((1,2,4-thiadiazole-3,5-diyl)bis(azaneylylidene))bis(methaneylylidene))bis(N,N-di-p-tolylaniline) (bTAThDaz) as hole transport material. This imine was synthesized in one step reaction, starting from commercially available and relatively inexpensive reagents. Electrochemical, optical, electrical, thermal and structural studies including thermal images and current-voltage measurements of the full solar cell devices characterize the imine in details. HOMO-LUMO of bTAThDaz were investigated by cyclic voltammetry (CV) and energy-resolved electrochemical impedance spectroscopy (ER-EIS) and were found at −5.19 eV and −2.52 eV (CV) and at −5.5 eV and −2.3 eV (ER-EIS). The imine exhibited 5% weight loss at 156 °C. The electrical behavior and photovoltaic performance of the perovskite solar cell was examined for FTO/TiO2/perovskite/bTAThDaz/Ag device architecture. Constructed devices exhibited good time and air stability together with quite small effect of hysteresis. The observed solar conversion efficiency was 14.4%.

Perovskite solar cells are today one of the hottest topics in photovoltaic devices. Compared to traditional c-Si, thin-film CIGS or CdTe solar cells, the fabrication of this type of solar cell is much cheaper, because production does not require ownership of a very expensive equipment and instrumentation. However, it has to be taken into account it has some initial issues as well as other newly developed technologies in the early stages of preparation for a commercial production. This paper deals with a newly synthesized hole transport material as a replacement of commercially available high-cost Spiro-OMETAD transport material. This commercial material has two main issues. Firstly, its production is very expensive and secondly it does not perform a function of a passivation layer for a sensitive perovskite layer. Our newly developed molecule has a positive effect on achieving long-term stable perovskite along with much cheaper production. The produced perovskite solar cell does not achieve highest power conversion efficiency, but they still look promising inf the view of long-term consistent performance.

The Clinical Engineering Division of the International Federation for Medical and Biological Engineering (IFMBE/CED), chaired by Ernesto Iadanza in the period 2015–18, has done its part in advancing clinical engineering in Italy by having many contacts and participations in Italian events and conferences in the last years. To further confirm this, the third edition of the International Conference of Clinical Engineering and Health Technology Management (ICEHTMC, 2019, http://www.icehtmc.com ) will be held in Rome in October 2019, in combination with the Global Clinical Engineering Day (October 21). There is no doubt that today Italy is having a big impact on the worldwide clinical engineering, for example, also exporting at European Union level its coding system for medical devices. Very good signals arrive from academia, with more and more students choosing this path and with excellent figures in their placement after graduation. Nevertheless, there is still a lot to do—both on the legislative level and on the organizational level—before seeing a clinical engineer sitting at all the tables of healthcare top managers.

The electronic properties of Triphenylamine (TPA) in gas phase and adsorbed on gold(111) have been simulated with Quantum Espresso using Density Functional Theory (DFT). To better understand how the presence of a gold surface affects sunlight absorption in the system, partial Density Of States (pDOS) and Near Edge X-ray Absorption Fine Structure (NEXAFS) of the system have been calculated. To describe the electronic excitation, three different methods have been used, No Core Hole (NCH), Full Core Hole (FCH) and Half Core Hole (HCH) approximation. The excitation of the TPA molecule was made in the nitrogen (N) atom and in the four different carbon (C) atoms with different electronic environments, C-ipso, C-ortho, C-meta and C-para. When using the HCH method, the absorbing atom must be described by a pseudopotential (PP) which includes half of a hole in the 1s orbital. This PP has been generated and a detailed summary of the process is described. The TPA/gold system relaxes to a position with the central N atom of TPA above an gold (Au) atom in the second layer of the surface and at a distance of 3.66 Angstrom, to the first layer. TPA keeps its symmetry with only small differences in the length of atomic bonds when adsorbed. The most striking result of this study is how the band gap of TPA is affected by the gold layer. From the pDOS we can observe that TPA in gas phase has a clear band gap of 2.2 eV with C-ortho dominating in the valence region and the four carbons dominating in the first unoccupied states. When depositing the molecule on the surface of Au(111), the band gap is essentially gone and a number of states appear between the previous highest occupied and lowest unoccupied molecular orbital in TPA. These new states align in energy with three clusters of states of the gold suggesting an interaction between the molecule and the surface. In the generated NEXAFS of nitrogen and carbon in TPA gas phase, one can observe a small pre-peak before the first unoccupied state. This is reinforced when adsorbing the molecule, which generates a pre-peak of approximately 3 eV in width. The pre-peak is connected to the new peaks seen in pDOS, correlating with experimental results on the same system.

We demonstrate for the first-time liquid exfoliated few layers of 2D Black phosphorus (BP) nanosheets as a hole transporting material (HTM) for perovskite based solar cells. The photoelectron spectroscopy in air (PESA) measurements confirm the low laying valence band level of BP nanosheets (−5.2 eV) favourable for hole injection from CH3NH3PbI3 (MAPbI3). Our results show that ∼25% improvement in power conversion efficiency (PCE) of η = 16.4% for BP nanosheets + Spiro-OMeTAD as an HTM as compared to spiro-OMeTAD (η = 13.1%). When BP nanosheets are exclusively utilised as an HTM, a PCE of η = 7.88% is noted, an improvement over the 4% PCE values observed for HTM free devices. Photoluminescence (PL) quenching of MAPbI3 and impedance measurements further confirm the charge extraction ability of BP nanosheets. The structural and optical characterization of liquid exfoliated BP nanosheets is discussed in detail with the aid of transmission electron microscopy, Raman spectroscopy, absorption spectroscopy and photo-electron spectroscopy. NRF (Natl Research Foundation, S’pore) MOE (Min. of Education, S’pore) Accepted version

International audience; Perovskite solar cells (PSC) based on metal-organic halide perovskites have emerged as one of the most promising photovoltaic technologies. Power conversion efficiency (PCE) has increased remarkably over the last few years from less than 10% up to certified efficiencies exceeding 23%. Selective interfacial layers play a critical role in charge extraction processes. In order to obtain high efficiencies, a hole transporting material (HTM) is required. Huge research efforts have been made to design efficient and low-cost materials. Carbazole-based HTMs are among the most promising new HTMs, in particular when they are substituted with dimethoxydiphenylamine (DMPA) units. This review gives an overview of the different classes of DMPA-containing carbazole-based HTMs and highlights the synthetic pathways, the structure-property relationship and the photovoltaic performances obtained in PSC devices. The relevance of structural variations and chemical doping processes is discussed with regard to efficiency and stability issues.

Copper oxide (CuxO) films are considered to be an attractive hole-transporting material (HTM) in the inverted planar heterojunction perovskite solar cells due to their unique optoelectronic properties, including intrinsic p-type conductivity, high mobility, low-thermal emittance, and energy band level matching with the perovskite (PS) material. In this study, the potential of reactive sputtered CuxO thin films with a thickness of around 100 nm has been extensively investigated as a promising HTM for effective and stable perovskite solar cells. The as-deposited and annealed films have been characterized by using X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Photoluminescence (PL), UV-Vis spectroscopy, and Hall-effect measurement techniques. The significant change in structural and optoelectronic properties has been observed as an impact of the thermal annealing process. The phase conversion from Cu2O to CuO, including grain size increment, was observed upon thermal annealing. The transmittance and optical bandgap were found to vary with the films’ crystallographic transformation. The predominant p-type conductivity and optimum annealing time for higher mobility have been confirmed from the Hall measurement. Films’ optoelectrical properties were implemented in the complete perovskite solar cell for numerical analysis. The simulation results show that a 40 min annealed CuxO film yields the highest efficiency of 22.56% with a maximum open-circuit voltage of 1.06 V.

This paper proposes a geometric error model for the three-axis machine tool using the homogeneous transformation matrix. An error-prediction model for the three-axis CNC machine tools is presented. This model takes the geometric errors into consideration, using the homogeneous coordinate transformation matrix(HTM) to analyze the geometric error model, which can change the tool's complex position and orientation changes in space into matrix calculations to make the model simpler and more intuitive. A simple method using the cubic polynomial functions to fit the geometric error components is proposed. Using this method, the high-order, non-linear spatial geometric problem can be transformed into algebraic equation. To large extent, the difficulty of calculation is reduced. The QC20 ball-bar is used to measure, analyze and separate all the geometric error components. A new kind of particle swarm algorithm based on the genetic algorithm is developed to solve the algebra equation.

Current laboratory-scale fabrication of perovskite solar cells involves the use of toxic solvents in the different fabrication steps. The aim of this research is to find a nontoxic alternative to chlorobenzene used for the deposition of hole transport material (HTM) spiro-OMeTAD. The initial selection of the solvents compatible with industrial manufacturing was performed based on the Hansen solubility model and further verified in a series of solubility tests, because the additives used in the HTM ink, such as lithium bis(trifluoromethanesulfonimidate) (Li-TFSI) and tert-butylpyridine (4-TBP), also have a significant influence on the properties of the final solution. Furthermore, selected solvents were tested on the compatibility with the underlying perovskite layer, which should remain unaffected after the spiro-OMeTAD deposition. A final selection of solvents was tested by the manufacturing of the complete perovskite solar cells. Power conversion efficiency (PCE) and layer quality, as well as possible health issues and environmental concerns, influenced the final selection for future potential industrial processing. The research demonstrated that replacement of chlorobenzene (CB) by p-xylene leads to identical PCEs of the devices, thereby showing that a toxic solvent can be replaced by a nontoxic and industrially compatible one. To prove that the selected solvent is suitable for future large-area coatings, the coatability of the ink was tested in blade-coating deposition. Devices manufactured using blade coating demonstrated identical PCEs to spin-coated devices, which is final proof of the suitability of the selected solvent system.

Financial institutions manage numerous portfolios whose risk must be managed continuously, and the large amounts of data that has to be processed renders this a considerable effort. As such, a system that autonomously detects anomalies in the risk measures of financial portfolios, would be of great value. To this end, the two econometric models ARMA-GARCH and EWMA, and the two machine learning based algorithms LSTM and HTM, were evaluated for the task of performing unsupervised anomaly detection on the streaming time series of portfolio risk measures. Three datasets of returns and Value-at-Risk series were synthesized and one dataset of real-world Value-at-Risk series had labels handcrafted for the experiments in this thesis. The results revealed that the LSTM has great potential in this domain, due to an ability to adapt to different types of time series and for being effective at finding a wide range of anomalies. However, the EWMA had the benefit of being faster and more interpretable, but lacked the ability to capture anomalous trends. The ARMA-GARCH was found to have difficulties in finding a good fit to the time series of risk measures, resulting in poor performance, and the HTM was outperformed by the other algorithms in every regard, due to an inability to learn the autoregressive behaviour of the time series. Finansiella institutioner hanterar otaliga portföljer vars risk måste hanteras kontinuerligt, och den stora mängden data som måste processeras gör detta till ett omfattande uppgift. Därför skulle ett system som autonomt kan upptäcka avvikelser i de finansiella portföljernas riskmått, vara av stort värde. I detta syftet undersöks två ekonometriska modeller, ARMA-GARCH och EWMA, samt två maskininlärningsmodeller, LSTM och HTM, för ändamålet att kunna utföra så kallad oövervakad avvikelsedetektering på den strömande tidsseriedata av portföljriskmått. Tre dataset syntetiserades med avkastningar och Value-at-Risk serier, och ett dataset med verkliga Value-at-Risk serier fick handgjorda etiketter till experimenten i denna avhandling. Resultaten visade att LSTM har stor potential i denna domänen, tack vare sin förmåga att anpassa sig till olika typer av tidsserier och för att effektivt lyckas finna varierade sorters anomalier. Däremot så hade EWMA fördelen av att vara den snabbaste och enklaste att tolka, men den saknade förmågan att finna avvikande trender. ARMA-GARCH hade svårigheter med att modellera tidsserier utav riskmått, vilket resulterade i att den preseterade dåligt. HTM blev utpresterad utav de andra algoritmerna i samtliga hänseenden, på grund utav dess oförmåga att lära sig tidsserierna autoregressiva beteende.

A tetra-n-butoxy zinc phthalocyanine (n-BuO)4ZnPc has been synthesized in a single step, starting from commercial precursors, and easily purified. The molecule can be solution processed to form an effective and inexpensive hole transport layer for organic and perovskite solar cells. These appealing features are suggested by the results of a series of chemical, optical, and voltammetric characterizations of the molecule, supported by the results of ab initio simulations. Preliminary measurements of (n-BuO)4ZnPc-methylammonium lead triiodide perovskite-based devices confirm such suggestion and indicate that the interface between the photoactive layer and the hole transporting layer is characterized by hole-extracting and electron-blocking properties, potentially competitive with those of other standards de facto in the field of organic hole transport materials, like the expensive Spiro-OMeTAD.

In this work a biomimetic sensor based on the heat-transfer method(HTM) and molecularly imprinted polymers(MIPs) has been developed as a paper-based lab-on-chip device. These microfluidic paper-based analytical devices (μPADs) are considerably smaller, faster and cheaper compared to its lab-sized predecessors. They can be used, disposed after usage and easily replaced for a new test without the requirement of expensive equipment. This makes it the ideal sensor for detecting molecules in point-of-care testing. This work is funded by the BIOMAT project which is carried out under Interreg V-A grensregio Vlaanderen - Nederland and is supported by the European Union and The European Regional Development Fund and with financial support of province of Limburg - Belgium.

This Master's Thesis focuses on the recent Cortical Learn-ing Algorithm (CLA), designed for temporal anomaly detection. It is here applied to the problem of anomaly detec-tion in user behavior of web services, which is getting moreand more important in a network security context. CLA is here compared to more traditional state-of-the-art algorithms of anomaly detection: Hidden Markov Models (HMMs) and t-stide (an N-gram-based anomaly detector), which are among the few algorithms compatible withthe online processing constraint of this problem. It is observed that on the synthetic dataset used forthis comparison, CLA performs signicantly better thanthe other two algorithms in terms of precision of the detection. The two other algorithms don't seem to be able tohandle this task at all. It appears that this anomaly de-tection problem (outlier detection in short sequences overa large alphabet) is considerably different from what hasbeen extensively studied up to now.

RWTH Aachen University, Diss., 2017; 1 Online-Ressource (vi, 162 Seiten) : Illustrationen, Diagramme(2017)., The electrical conductivity relaxation technique is a widely used method to determine the oxygen transport parameters of mixed ionic-electronic conductors. In recent years, it has been modified to investigate the hydration behavior of proton conducting mixed conductors, giving access to up to four transport parameters in a single relaxation experiment, the diffusion coefficients and surface reaction rates of hydrogen and oxygen. In this work, the transport properties of the fluorite type protonic conductor lanthanum tungstate have been investigated by means of electrical conductivity relaxation. The experiments were performed in a temperature range from 650 °C to 950 °C, in a pO2 range from 3 mbar to 100 mbar and in a pH2O range from 10 mbar to 100 mbar and in dry atmosphere. At high temperatures, the conductivity relaxation curve follows the expected two-fold non-monotonic behavior upon hydration. At low temperatures, however, the contribution of the fast hydrogen kinetic decreases and by a further decrease of the temperature, the relaxation shows two-fold monotonic behavior. The power factors - the contribution of each single fold relaxation curve to the resulting two-fold relaxation curve, which is a superposition - have been derived to explain the behavior mentioned above. The activation energy of the oxygen incorporation is rather low. Hence, oxidation experiments were performed in dry atmospheres in order to investigate if the origin of the oxygen species is relevant. The results revealed higher activation energies, which was expected, but also higher absolute values of the surface reaction rate and the diffusion coefficient. Oxidation experiments with increasing humidity revealed that the increased diffusivity cannot be attributed to the total concentrations of electron holes and proton interstitials. First experiments using spectroscopic relaxation, which is dependent on the concentration of hydroxy-anions only, were performed. Absorption bands, however, have not yet been observed., Published by Aachen

The organometal perovskite solar cells have shown stupendous development and have reached a power conversion efficiency (PCE) of 22.1%. However, the toxicity of lead in perovskite solar cells is a major challenge towards their incorporation into photovoltaic devices and thus needs to be addressed. Tin perovskite (CH3NH3SnI3) have attracted a lot of attention recently and could be a viable alternative material to replace lead perovskite in thin film solar cells. A detail understanding of effects of each component of a solar cell on its output performance is needed to further develop the technology. In this work, we performed a numerical simulation of a planar heterojunction tin based perovskite solar cell using SCAPS (Solar Cell Capacitance Simulator). Results revealed that thickness and defect density of the absorber material strongly influence the PCE of the device. Various types of hole transporting material (HTM) were compared and analysed to improve the performance of the solar cell. Parameters such as hole mobility and acceptor density of HTM also signified dependence on PCE of the device. These results indicate the possibility to design, fabricate and enhance the performance of tin based perovskite solar cells.

A biomimetic paper-based lab-on-chip device based on the heat transfer method(HTM) was developed. This work applied molecularly imprinted polymers(MIPs) as a biomimetic functional interface. In order to deliver the sample to the functional interface an optimal wick design is needed. Several designs were tested to determine the flow rate, flow duration and amount of volume needed. HTM and camera recording were used to acquire test results. The final wick design allows for easy integration of the biomimetic layer. The paper-based lab-on-chip will allow the rapid on-site testing of potentially polluted fluids. Special Research Funds BOF of Hasselt University.

Various studies have utilized different artificial neural networks (ANN) for weather forecasting. This thesis examines how well the official implementation of a novel online ANN called the Hierarchical Temporal Memory (HTM) can forecast the weather and detect anomalies in the weather data. Created by Numenta (www.numenta.com), the HTM emulates the brain's neocortical structures and processes to mimic its capabilities of memory retention. By using sparse distributed representations instead of binary representations as its foundation for information storage and representation, it is able to learn complex patterns in noisy data sets that can be used to make predictions and detect anomalies in streamed data. Numenta has officially implemented the theory of HTM in an open- source Python platform called NuPIC. Although there are slight differences between the theory of HTM and its implementation, the most important factor about NuPIC is the addition of several purely engineered algorithms. Two of the most notable additions, are an algorithm that enables NuPIC to make the final decisions in cases when more than one possible prediction is possible, and an algorithm that makes it possible to simultaneously input multiple metrics to NuPIC. The weather data that was to be predicted consisted of several weather factors, wind direction, wind speed, atmospheric pressure, precipitation, temperature, and relative humidity measurements spanning over a period of 12 years. Originally, the goal was to input the data sets simultaneously. However, because the functionality responsible for enabling this feature was malfunctioning at the time of the thesis work, every weather data set had to be input separately. The results showed that NuPIC was able to make decent forecasts, but was for the most part outperformed by a simple technique that made predictions by calculating the average of the last few days. The main reasons for this was due to the weather's lack of similarity between past and current conditions, and NuPIC's inability to generalize its knowledge in order to factor weather trends in its predictions. Although there is also a minor issue with the current engineered prediction algorithm, the results indicate that prediction is not NuPIC's strongest suit. NuPIC was completely unable to detect any noteworthy anomalies in the weather data, which again is most likely due to the weather data's chaotic nature. Despite the negative results, there were also some positive ones. An unrelated experiment that detected anomalies in the oil price, revealed that NuPIC was able to detect anomalies that were linked to major real world economic and/or geopolitical events. This indicates that the quality of NuPIC's results are highly dependant on the properties of the data set that it is given. Data sets that conform to NuPIC's strengths can lead to both decent predictions and anomaly detections, while those that do not produce poor results. Master i Informatikk MAMN-INF INF399

International audience; Hybrid organometal halide perovskites have attracted much attention these past four years as the new active layer for photovoltaic applications. Researches are now intensively focused on the stability issues of these solar cells, the process of fabrication and the design of innovative materials to produce efficient perovskite devices. In this review, we highlight the recent progress demonstrated in 2015 in the design of new π-conjugated organic materials used as hole transporters in such solar cells. Indeed, several of these " synthetic metals " have been proposed to play this role during the last few years, in an attempt to replace the conventional 2,2 1 ,7,7 1-tetrakis-(N,N-di-4-methoxyphenylamino)-9,9 1-spirobifluorene (Spiro-OMeTAD) reference. Organic compounds have the benefits of low production costs and the abundance of raw materials, but they are also crucial components in order to address some of the stability issues usually encountered by this type of technology. We especially point out the main design rules to reach high efficiencies.

This paper introduces a two-stage approach to the detection of people eating and/or drinking for the purposes of surveillance of daily life. With the sole use of wearable accelerometer sensor attached to somebody’s (man or a woman) wrists, this two-stage approach consists of feature extraction followed by classification. At the first stage, based on the limb’s three dimensional kinematics movement model and the Extended Kalman Filter (EKF), the realtime arm movement features described by Euler angles are extracted from the raw accelerometer measurement data. In the latter stage, the Hierarchical Temporal Memory (HTM) network is adopted to classify the extracted features of the eating/drinking activities based on the space and time varying property of the features, by making use of the powerful modelling capability of HTM network on dynamic signals which is varying with both space and time. The proposed approach is tested through the real eating and drinking activities using the three dimensional accelerometers. Experimental results show that the EKF and HTM based two-stage approach can perform the activity detection successfully with very high accuracy.

Transactional memory (TM) has emerged as a promising synchronization abstraction for multi-core architectures. Unlike traditional lock-based approaches, TM shifts the burden of implementing threads synchronization from the programmer to an underlying framework using hardware (HTM) and/or software (STM) components. Although TM can be leveraged to implement transactional data structures (i.e., those where multiple operations are allowed to execute atomically, all-or-nothing, according to the transaction paradigm), its intensive speculation may result in significantly lower performance than the optimized concurrent data structures. This poor performance motivates the need to find other, more effective, alternatives for designing transactional data structures without losing the simple programming abstraction proposed by TM. To do so, we identified three major challenges that need to be addressed to design efficient transactional data structures. The first challenge is composability, namely allowing an atomic execution of two or more data structure operations in the same way as TM provides, but without its high overheads. The second challenge is integration, which enables the execution of data structure operations within generic transactions that may contain other memory- based operations. The last challenge is modeling, which encompasses the necessity of defining a unified formal methodology to reason about the correctness of transactional data structures. In this dissertation, we propose different approaches to address the above challenges. First, we address the composability challenge by introducing an optimistic methodology to effi- ciently convert concurrent data structures into transactional ones. Second, we address the integration challenge by injecting the semantic operations of those transactional data struc- ture into TM frameworks, and by presenting two novel STM algorithms in order to enhance the overall performance of those frameworks. Finally, we address the modeling challenge by presenting two models for concurrent and transactional data structures designs. • Our first main contribution in this dissertation is Optimistic transactional boosting (OTB), a methodology to design transactional versions of the highly concurrent optimistic (i.e., lazy) data structures. An earlier (pessimistic) boosting proposal added a layer of abstract locks on top of existing concurrent data structures. Instead, we propose an optimistic boosting methodology, which allows greater data structure-specific optimizations, easier integration with TM frameworks, and lower restrictions on the operations than the original (more pessimistic) boosting methodology. Based on the proposed OTB methodology, we implement the transactional version of two list-based data structures (i.e., set and priority queue). Then, we present TxCF-Tree, a balanced tree whose design is optimized to support transactional accesses. The core optimizations of TxCF-Tree's operations are: providing a traversal phase that does not use any lock and/or speculation and deferring the lock acquisition or physical modification to the transaction's commit phase; isolating the structural operations (such as re-balancing) in an interference-less housekeeping thread; and minimizing the interference between structural operations and the critical path of semantic operations (i.e., additions and removals on the tree). • Our second main contribution is to integrate OTB with both STM and HTM algorithms. For STM, we extend the design of both DEUCE, a Java STM framework, and RSTM, a C++ STM framework, to support the integration with OTB. Using our extension, programmers can include both OTB data structure operations and traditional memory reads/writes in the same transaction. Results show that OTB performance is closer to the optimal lazy (non-transactional) data structures than the original boosting algorithm. On the HTM side, we introduce a methodology to inject semantic operations into the well-known hybrid transactional memory algorithms (e.g., HTM-GL, HyNOrec, and NOre- cRH). In addition, we enhance the proposed semantically-enabled HTM algorithms with a lightweight adaptation mechanism that allows bypassing the HTM paths if the overhead of the semantic operations causes repeated HTM aborts. Experiments on micro- and macro- benchmarks confirm that our proposals outperform the other TM solutions in almost all the tested workloads. • Our third main contribution is to enhance the performance of TM frameworks in gen- eral by introducing two novel STM algorithms. Remote Transaction Commit (RTC) is a mechanism for executing commit phases of STM transactions in dedicated server cores. RTC shows significant improvements compared to its corresponding validation based STM algorithm (up to 4x better) as it decreases the overhead of spin locking during commit, in terms of cache misses, blocking of lock holders, and CAS operations. Remote Inval- idation (RInval) applies the same idea of RTC on invalidation based STM algorithms. Furthermore, it allows more concurrency by executing commit and invalidation routines concurrently in different servers. RInval performs up to 10x better than its corresponding invalidation based STM algorithm (InvalSTM), and up to 2x better than its corresponding validation-based algorithm (NOrec). • Our fourth and final main contribution is to provide a theoretical model for concurrent and transactional data structures. We exploit the similarities of the OTB-based data structures and provide a unified model to reason about the correctness of those designs. Specifically, we extend a recent approach that models data structures with concurrent readers and a single writer (called SWMR), and we propose two novel models that additionally allow multiple writers and transactional execution. Those models are more practical because they cover a wider set of data structures than the original SWMR model. Ph. D.

This work concentrates on the effective synthesis of hole transportingg materials for the application in perovskite solar cells. Novel materials were synthesized utilizing "click" reaction. 13 branched hydrazones, 2 hydrazone polymers and 6 diphenylamine substituted carbazole twin molecules were synthesized and properties investigated. Perovskite solar cells with 1,2-bis[3,6-(4,4-dimethoxydiphenylamino)-9H-carbazol-9-methyl]benzene shows up to 16.91% efficiency. It is one of the best results for the small molecule hole transporting materials., Šiame darbe pristatyta efektyvi skyles transportuojančių medžiagų perovskitiniams saulės elementams sintezė. Naujos medžiagos buvo gautos naudojantis "klik" chemijos metodu. Buvo susintetinti ir ištirti 13 šakotos struktūros hidrazonų, 2 hidrazonų polimerai bei 6 karbazolilfragmentą turinčios molekulės. Su 1,2-bis[3,6-(4,4-dimetoksidifenilamino)-9H-karbazol-9-metil]benzenu pasiektas vienas geriausių saulės šviesos konversijos efektyvumų (16,91%) perovskitiniuose saulės elementuose su mažamolekulinėmis skyles transportuojančiomis medžiagomis.

With the rapid deplition of fossil fuel the use alternative energy sources is becoming ever more important. Hybrid organic-inorganic sollar cells have seen a lot of development over the past few years and could potentially replace the traditional and significantly more expensive inorganic solar cells. This is due to the discovery of the light absorbing qualities of class of materials called perovskites. To further increase the efficiency of perovskite solar cells as well as decrease their cost, new hole transporting materials are needed. Hydrazones are a well known class of organic molecular hole transporting materials which are relatively inexpensive, easy to synthesize and have good photophysical properties. This work encompases the synthesis and the study of thermal, optoelectric and electrochemical properties of new di- and tetrahydrazone triphenylamine and methoxytriphenylamine derivatives as well as a discussion thereof. Preliminary test result of experimental solar cells fabricated using the synthesized materials are also presented., Senkant iškąstinio kuro atsargoms alternatyvių energijos šaltinių išnaudojimas tampa vis aktualesniu. Hibridinės saulės celės yra pastaruoju metu sparčiai besivystanti saulės celių atmaina potencialiai galinti pakeisti brangesnes, neorganines saulės celes. Toks postumis siejamas su perovskitų – šviesą sugeriančių medžiagų klasės, taikimo pradžia. Norint dar labiau pagerinti hibridinių saulės celių našumą ir sumažinti kainą reikalingi nauji, pasižymintys skyliniu laidumu junginiai. Hidrazonai yra organinių molekulinių p-tipo puslaidininkių klasė pasižyminti santikinai žema kaina, nesudėtinga sinteze bei geromis fotoelektrinėmis savybėmis. Šitame darbe aprašyta naujų di- bei tetrahidrazono fragmentą turinčių trifenilamino bei metoksitrifenilamino darinių sintezė. Pateikti ir aptariami atliktų terminių, optoelektrinių bei elektrocheminių savybių tyrimų rezultatai. Taip pat pateikti duomenys apie pirminius eksperimentinių saulės celių, sukonstruotų naudojant susintetintus junginius, bandymus.

In the Hierarchical Temporal Memory (HTM) paradigm the effect of overlap between inputs on the activation of columns in the spatial pooler is studied. Numerical results suggest that similar inputs are represented by similar sets of columns and dissimilar inputs are represented by dissimilar sets of columns. It is shown that the spatial pooler produces these results under certain conditions for the connectivity and proximal thresholds. Following the discussion of the initialization of parameters for the thresholds, corresponding qualitative arguments about the learning dynamics of the spatial pooler are discussed., {"references":["B. Bobier and M.Wirth, \"Content-based image retrieval using hierarchical\ntemporal memory,\" in Proc. 16th ACM Int. Conf. on Multimedia, 2008,\npp. 925-928.","P. Gabrielsson, R. Konig, and U. Johansson, \"Evolving hierarchical\ntemporal memory-based trading models,\" in EvoApplications\n2013-Applications of Evolutionary Computing, Vienna, April 3-5,\n2013.","J. Hawkins, S. Ahmad, and D. Dubinsky, \"Hierarchical temporal memory\nincluding HTM cortical learning algorithms,\" Numenta, Redwood City,\nCA, Tech. Rep. ver. 0.2.1, 2011.","D.O. Hebb, \"The first stage of perception: growth of the assembly,\" in\nThe Organization of Behavior, New York, Wiley, 1949, intro. and ch. 4,\npp. xi-xix, 60-78.","D. Maltoni, \"Pattern recognition by hierarchical temporal memory,\" DEIS\nUniv. Bologna, Tech. Rep., pp. 1-46, Apr. 13, 2011.","V. Mountcastle, \"The columnar organization of the neocortex,\" Brain, vol.\n120(4), pp. 701-722, 1997.","A.J. Perea, J.E. Merono, and M.J. Aguilera, \"Application of Numenta\nhierarchical temporal memory for land-use classification,\" S. Afr. J. Sci.,\nvol. 105, pp. 370-375, Sept./Oct. 2009.","J. Thornton and A. Srbic, \"Spatial pooling for greyscale images,\" Int. J.\nMach. Learn. & Cyber., vol. 4, pp. 207-216, 2013.","J. van Doremalen and L. Boves, \"Spoken digit recognition using a\nhierarchical temporal memory,\" Interspeech, pp. 2566-2569, Brisbane,\nSept. 22-26, 2008."]}

Many hospitals do not have a well-planned process to prioritize purchasing requests. Obviously, this problem is due to the lack of a fair evaluation of the requirements as well as absence of the cooperation of the hospital management staff. Therefore, it is essential to have a systematic and a comprehensive acquisition program to prevent a number of potential problems. This article presents a solution for the prioritization problem of purchasing requests of medical equipment by adopting a framework that combines Quality Function Deployment with Fuzzy logic system. The validation of the proposed model was carried out on 20 requests for purchasing medical equipment in a public hospital. The results indicate that the Quality Function Deployment-Fuzzy method can efficiently address the priority of requests considering a wide range of criteria. In addition, it can also provide the stability of process assurance

Preventive maintenance is a core function of clinical engineering, and it is essential to guarantee the correct functioning of the equipment. The management and control of maintenance activities are equally important to perform maintenance. As the variety of medical equipment increases, accordingly the size of maintenance activities increases, the need for better management and control become essential. This paper aims to develop a new model for preventive maintenance priority of medical equipment using quality function deployment as a new concept in maintenance of medical equipment. We developed a three-domain framework model consisting of requirement, function, and concept. The requirement domain is the house of quality matrix. The second domain is the design matrix. Finally, the concept domain generates a prioritization index for preventive maintenance considering the weights of critical criteria. According to the final scores of those criteria, the prioritization action of medical equipment is carried out. Our model proposes five levels of priority for preventive maintenance. The model was tested on 200 pieces of medical equipment belonging to 17 different departments of two hospitals in Piedmont province, Italy. The dataset includes 70 different types of equipment. The results show a high correlation between risk-based criteria and the prioritization list.

This thesis presents tools for Transactional Memory (TM) applications that cover multiple TM systems (Software, Hardware, and hybrid TM) and use information of all different layers of the TM software stack. Therefore, this thesis addresses a number of challenges to extract static information, information about the run time behavior, and expert-level knowledge to develop these new methods and strategies for the optimization of TM applications.

The main intention of this thesis is to give the basic information about the implementation of a node of one of the neural network algorithms. The main purpose of this thesis is to design, implement and analyze the node of the HTM (Hierarchical Temporal Memory) algorithm suggested by Jeff Hawkins [1]. In this document, a design implementation of HTM algorithm node based on Verilog hardware description language and MATLAB programming language is given. The node of HTM algorithm is implemented using Xilinx Spartan-3e FPGA (Field Programmable Gate Array) kit. The simulation results obtained with Xilinx ISE (Integrated Software Environment) 10.1 software are also provided.

El proyecto consiste en un maquetador de html partiendo de un documento en formato .doc o directamente en htm creado desde windows, el cual seleccionará desde un explorador de archivos que solo permite la subida de documentos windows o htm dependiendo de que hayamos seleccionado y una vez que estemos seguros que documento queremos lo subiremos al servidor, desde donde se trabajará con él y nos lo mostrara ya en el editor de contenido donde podrá crear o modificar un documento htm dentro de un entorno de trabajo con múltiples herramientas de trabajo como modificación de las fuentes, creación y modificación de hipervínculos, creación de tablas, corrector ortográfico, etc...

The primary objective of this paper was to construct a "kinematic parameter-independent modeling of three-axis machine tools for geometric error measurement" technique. Improving the accuracy of the geometric error for three-axis machine tools is one of the machine tools- core techniques. This paper first applied the traditional method of HTM to deduce the geometric error model for three-axis machine tools. This geometric error model was related to the three-axis kinematic parameters where the overall errors was relative to the machine reference coordinate system. Given that the measurement of the linear axis in this model should be on the ideal motion axis, there were practical difficulties. Through a measurement method consolidating translational errors and rotational errors in the geometric error model, we simplified the three-axis geometric error model to a kinematic parameter-independent model. Finally, based on the new measurement method corresponding to this error model, we established a truly practical and more accurate error measuring technique for three-axis machine tools., {"references":["A.H. Slocum, \"Precision Machine Design\", in: Prentice-Hall, Englewood\nCliffs, 1992.","V.B. Kreng, C.R. Liu, C.N. Chu, \"A kinematic model for machine tool\naccuracy characterization\", International Journal of Advanced\nManufacturing Technology, vol. 9, pp. 79-86, 1994.","V. Kiridena, P.M. Ferreira, \"Mapping the effects of positioning errors on\nthe volumetric accuracy of five-axis CNC machine tools\", International\nJournal of Machine Tools & Manufacture, vol. 33, no. 3, pp. 417-437,\n1993.","V.S.B. Kiridena, P.M. Ferreira, \"Kinematic modeling of quasistatic\nerrors of three-axis machining centers\", International Journal of Machine\nTools & Manufacture, vol. 34, no. 1, pp. 85-100, 1994.","A.K. Srivastava, S.C. Veldhuis and M.A. Elbestawit, \"Modelling\ngeometric and thermal errors in a five-axis CNC machine tool\",\nInternational Journal of Machine Tools & Manufacture, vol. 35, no. 9,\npp. 1321-1337, 1995.","K. Lau, Q. Ma, X. Chu, Y. Liu and S. Olson, \"An advanced\n6-degreeof-freedom laser system for quick CNC machine and CMM\nerror mapping and compensation\", Automated Precision, Inc.,\nGaithersburg, MD 20879, USA, 2001.","P.M. Ferreira and C.R. Liu, \"A method for estimating and compensating\nquasistatic errors of machine tools\", Journal of Engineering for Industry,\nvol. 115, pp. 149-157, 1993.","J. Ni, \"CNC machine accuracy enhancement through real-time error\ncompensation\", Journal of Manufacturing Science and Engineering, vol.\n119, pp. 717-725, 1997.","LaserTRACER™ - highest measuring accuracy for machine tool error\ncompensation , white paper, Optical Gaging Products, Inc (OGP), 2009."]}

To address the need for a simpler parallel programming model, Transactional Memory (TM) has been developed and promises good parallel performance with easy-to-write parallel code. Unlike lock-based approaches, with TM, programmers do not need to explicitly specify and manage the synchronization among threads. However, programmers simply mark code segments as transactions, and the TM system manages the concurrency control for them. TM can be implemented either in software (STM) or hardware (HTM). STMs are more flexible but suffer from serious performance overheads whereas HTMs are faster but limited due to hardware space constrains. We present an implementation of a HTM system, based on an existing protocol (Scalable-TCC), over a full-system simulator. We provide a memory system that allows for a configurable number of cache entries, associativity, cache-line size, and all the access timings in the memory hierarchy. Combined with a powerful statistics system that provides all the necessary information to extract conclusions from the transactional executions. We evaluate our HTM system using applications that cover a wide range of transactional behaviours and demonstrate that it scales efficiently up to 32 processors.

To address the need for a simpler parallel programming model, Transactional Memory (TM) has been developed and promises good parallel performance with easy-to-write parallel code. Unlike lock-based approaches, with TM, programmers do not need to explicitly specify and manage the synchronization among threads. However, programmers simply mark code segments as transactions, and the TM system manages the concurrency control for them. TM can be implemented either in software (STM) or hardware (HTM). STMs are more flexible but suffer from serious performance overheads whereas HTMs are faster but limited due to hardware space constrains. We present an implementation of a HTM system, based on an existing protocol (Scalable-TCC), over a full-system simulator. We provide a memory system that allows for a configurable number of cache entries, associativity, cache-line size, and all the access timings in the memory hierarchy. Combined with a powerful statistics system that provides all the necessary information to extract conclusions from the transactional executions. We evaluate our HTM system using applications that cover a wide range of transactional behaviours and demonstrate that it scales efficiently up to 32 processors.

Clinical Engineering (CE) Departments are in charge of healthcare technology management in healthcare facilities. The workload is proportional to the number of activities, the number and complexity of biomedical instrumentation, and the technology intensity of the facility. Clinical engineers and Biomedical equipment technicians work together in order to perform the different activities and to obtain customer satisfaction. This paper describes a model that can be used to estimate the number of engineers and technicians required to start a new CE Department. The estimation is obtained by means of simulation. Starting by several inputs that describe the facility and the quantity and characteristics of the instruments the model is able to provide the number of Clinical engineers and Biomedical equipment technicians.

Health technology management consists of several decision processes including the acquisition of new technology. The purchasing of a new device requires the selection of one among several products taking into account different criteria. When the technology is characterized by large amount of parameters the choice becomes problematical and a support tool is needed. In 2003 Sloane et al [1] published a study in which they demonstrated the potentialities of the analytic hierarchy process (AHP) to support the selection of a biomedical instrumentation. The work presented here describes the application of AHP to support the quality assessment for the selection of pacemakers and implantable defibrillators and shows that the method is indeed very appropriate for that task.

Black liquors are presently combusted in recovery boilers where the inorganic cooking chemicals are recovered and the energy in the organic material is converted to steam and electricity. A new technology, developed by Chemrec AB, is black liquor gasification (BLG). BLG has more to offer compared to the recovery boiler process, in terms of on-site generation of electric power, liquid fuel and process chemicals. A prerequisite for both optimization of existing processes and the commercialization of BLG is better understanding of the physical and chemical processes involved including interactions with the refractory lining. The chemistry in the BLG process is very complex and to minimize extensive and expensive time-consuming studies otherwise required accurate and reliable model descriptions are needed for a full understanding of most chemical and physical processes as well as for up-scaling of the new BLG processes. However, by using these calculated model results in practice, the errors in the state of the art thermochemical data have to be considered. An extensive literature review was therefore performed to update the data needed for unary, binary and higher order systems. The results from the review reviled that there is a significant range of uncertainty for several condensed phases and a few gas species. This resulted in experimental re-determinations of the binary phase diagrams sodium carbonate-sodium sulfide (Na2CO3-Na2S) and sodium sulfate-sodium sulfide (Na2SO4-Na2S) using High Temperature Microscopy (HTM), High Temperature X-ray Diffraction (HT-XRD) and Differential Thermal Analysis (DTA). For the Na2CO3-Na2S system, measurements were carried out in dry inert atmosphere at temperatures from 25 to 1200 °C. To examine the influence of pure CO2 atmosphere on the melting behavior, HTM experiments in the same temperature interval were made. The results include re-determination of liquidus curves, in the Na2CO3 rich area, melting points of the pure components as well as determination of the extent of the solid solution, Na2CO3(ss), area. The thermal stability of Na2SO3 was studied and the binary phase diagram Na2SO4-Na2S was re-determined. The results indicate that Na2SO3 can exist for a short time up to 750 °C, before it melts. It was also proved that a solid/solid transformation, not reported earlier, occurs at 675 ± 10 °C. At around 700 °C, Na2SO3 gradually breaks down within a few hours, to finally form the solid phases Na2SO4 and Na2S. From HTM measurements a metastable phase diagram including Na2SO3, as well as an equilibrium phase diagram have been constructed for the binary system Na2SO4-Na2S. Improved data on Na2S was experimentally obtained by using solid-state EMF measurements. The equilibrium constant for Na2S(s) was determined to be log Kf(Na2S(s)) (± 0.05) = 216.28 – 4750(T/K)–1 – 28.28878 ln (T/K). Gibbs energy of formation for Na2S(s) was obtained as ΔfG°(Na2S(s))/(kJ mol–1) (± 1.0) = 90.9 – 4.1407(T/K) + 0.5415849(T/K) ln (T/K). The standard enthalpy of formation of Na2S(s) was evaluated to be ΔfH°(Na2S(s), 298.15 K)/(kJ mol–1) (± 1.0) = – 369.0. The standard entropy was evaluated to be S°(Na2S(s), 298.15 K)/(J mol–1 K–1) (± 2.0) = 97.0. Analyses of used refractory material from the Chemrec gasifier were also performed in order to elucidate the stability of the refractory lining. Scanning electron microscopy (SEM) analysis revealed that the chemical attack was limited to 250-300 μm, of the surface directly exposed to the gasification atmosphere and the smelt. From XRD analysis it was found that the phases in this surface layer of the refractory were dominated by sodiumaluminosilicates, mainly Na1.55Al1.55Si0.45O4.