923 resultados para automated full waveform logging system


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In this paper, we present the results of an exploratory study that examined the problem of automating content analysis of student online discussion transcripts. We looked at the problem of coding discussion transcripts for the levels of cognitive presence, one of the three main constructs in the Community of Inquiry (CoI) model of distance education. Using Coh-Metrix and LIWC features, together with a set of custom features developed to capture discussion context, we developed a random forest classification system that achieved 70.3% classification accuracy and 0.63 Cohen's kappa, which is significantly higher than values reported in the previous studies. Besides improvement in classification accuracy, the developed system is also less sensitive to overfitting as it uses only 205 classification features, which is around 100 times less features than in similar systems based on bag-of-words features. We also provide an overview of the classification features most indicative of the different phases of cognitive presence that gives an additional insights into the nature of cognitive presence learning cycle. Overall, our results show great potential of the proposed approach, with an added benefit of providing further characterization of the cognitive presence coding scheme.

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The design and implementation of a complete gas sensor system for liquified petroleum gas (LPG) gas sensing are presented. The system consists of a SnO2 transducer, a lowcost heater, an application specific integrated circuit (ASIC) with front-end interface circuitry, and a microcontroller interface for data logging. The ASIC includes a relaxation-oscillator-based heater driver circuit that is capable of controlling the sensor operating temperature from 100degC to 425degC. The sensor readout circuit in the ASIC, which is based on the resistance to time conversion technique, has been designed to measure the gas sensor response over three orders of resistance change during its interaction with gases.

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Background Although thermal imaging can be a valuable technology in the prevention and management of diabetic foot disease, it is not yet widely used in clinical practice. Technological advancement in infrared imaging increases its application range. The aim was to explore the first steps in the applicability of high-resolution infrared thermal imaging for noninvasive automated detection of signs of diabetic foot disease. Methods The plantar foot surfaces of 15 diabetes patients were imaged with an infrared camera (resolution, 1.2 mm/pixel): 5 patients had no visible signs of foot complications, 5 patients had local complications (e.g., abundant callus or neuropathic ulcer), and 5 patients had difuse complications (e.g., Charcot foot, infected ulcer, or critical ischemia). Foot temperature was calculated as mean temperature across pixels for the whole foot and for specified regions of interest (ROIs). Results No diferences in mean temperature >1.5 °C between the ipsilateral and the contralateral foot were found in patients without complications. In patients with local complications, mean temperatures of the ipsilateral and the contralateral foot were similar, but temperature at the ROI was >2 °C higher compared with the corresponding region in the contralateral foot and to the mean of the whole ipsilateral foot. In patients with difuse complications, mean temperature diferences of >3 °C between ipsilateral and contralateral foot were found. Conclusions With an algorithm based on parameters that can be captured and analyzed with a high-resolution infrared camera and a computer, it is possible to detect signs of diabetic foot disease and to discriminate between no, local, or difuse diabetic foot complications. As such, an intelligent telemedicine monitoring system for noninvasive automated detection of signs of diabetic foot disease is one step closer. Future studies are essential to confirm and extend these promising early findings.

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Hydraulic instabilities represent a critical problem for Francis and Kaplan turbines, reducing their useful life due to increase of fatigue on the components and cavitation phenomena. Whereas an exhaustive list of publications on computational fluid-dynamic models of hydraulic instability is available, the possibility of applying diagnostic techniques based on vibration measurements has not been investigated sufficiently, also because the appropriate sensors seldom equip hydro turbine units. The aim of this study is to fill this knowledge gap and to exploit fully, for this purpose, the potentiality of combining cyclostationary analysis tools, able to describe complex dynamics such as those of fluid-structure interactions, with order tracking procedures, allowing domain transformations and consequently the separation of synchronous and non-synchronous components. This paper will focus on experimental data obtained on a full-scale Kaplan turbine unit, operating in a real power plant, tackling the issues of adapting such diagnostic tools for the analysis of hydraulic instabilities and proposing techniques and methodologies for a highly automated condition monitoring system. © 2015 Elsevier Ltd.

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Lignin is a hydrophobic polymer that is synthesised in the secondary cell walls of all vascular plants. It enables water conduction through the stem, supports the upright growth habit and protects against invading pathogens. In addition, lignin hinders the utilisation of the cellulosic cell walls of plants in pulp and paper industry and as forage. Lignin precursors are synthesised in the cytoplasm through the phenylpropanoid pathway, transported into the cell wall and oxidised by peroxidases or laccases to phenoxy radicals that couple to form the lignin polymer. This study was conducted to characterise the lignin biosynthetic pathway in Norway spruce (Picea abies (L.) Karst.). We focused on the less well-known polymerisation stage, to identify the enzymes and the regulatory mechanisms that are involved. Available data for lignin biosynthesis in gymnosperms is scarce and, for example, the latest improvements in precursor biosynthesis have only been verified in herbaceous plants. Therefore, we also wanted to study in detail the roles of individual gene family members during developmental and stress-induced lignification, using EST sequencing and real-time RT-PCR. We used, as a model, a Norway spruce tissue culture line that produces extracellular lignin into the culture medium, and showed that lignin polymerisation in the tissue culture depends on peroxidase activity. We identified in the culture medium a significant NADH oxidase activity that could generate H2O2 for peroxidases. Two basic culture medium peroxidases were shown to have high affinity to coniferyl alcohol. Conservation of the putative substrate-binding amino acids was observed when the spruce peroxidase sequences were compared with other peroxidases with high affinity to coniferyl alcohol. We also used different peroxidase fractions to produce synthetic in vitro lignins from coniferyl alcohol; however, the linkage pattern of the suspension culture lignin could not be reproduced in vitro with the purified peroxidases, nor with the full complement of culture medium proteins. This emphasised the importance of the precursor radical concentration in the reaction zone, which is controlled by the cells through the secretion of both the lignin precursors and the oxidative enzymes to the apoplast. In addition, we identified basic peroxidases that were reversibly bound to the lignin precipitate. They could be involved, for example, in the oxidation of polymeric lignin, which is required for polymer growth. The dibenzodioxocin substructure was used as a marker for polymer oxidation in the in vitro polymerisation studies, as it is a typical substructure in wood lignin and in the suspension culture lignin. Using immunolocalisation, we found the structure mainly in the S2+S3 layers of the secondary cell walls of Norway spruce tracheids. The structure was primarily formed during the late phases of lignification. Contrary to the earlier assumptions, it appears to be a terminal structure in the lignin macromolecule. Most lignin biosynthetic enzymes are encoded for by several genes, all of which may not participate in lignin biosynthesis. In order to identify the gene family members that are responsible for developmental lignification, ESTs were sequenced from the lignin-forming tissue culture and developing xylem of spruce. Expression of the identified lignin biosynthetic genes was studied using real-time RT-PCR. Candidate genes for developmental lignification were identified by a coordinated, high expression of certain genes within the gene families in all lignin-forming tissues. However, such coordinated expression was not found for peroxidase genes. We also studied stress-induced lignification either during compression wood formation by bending the stems or after Heterobasidion annosum infection. Based on gene expression profiles, stress-induced monolignol biosynthesis appeared similar to the developmental process, and only single PAL and C3H genes were specifically up-regulated by stress. On the contrary, the up-regulated peroxidase genes differed between developmental and stress-induced lignification, indicating specific responses.

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This paper presents a novel crop detection system applied to the challenging task of field sweet pepper (capsicum) detection. The field-grown sweet pepper crop presents several challenges for robotic systems such as the high degree of occlusion and the fact that the crop can have a similar colour to the background (green on green). To overcome these issues, we propose a two-stage system that performs per-pixel segmentation followed by region detection. The output of the segmentation is used to search for highly probable regions and declares these to be sweet pepper. We propose the novel use of the local binary pattern (LBP) to perform crop segmentation. This feature improves the accuracy of crop segmentation from an AUC of 0.10, for previously proposed features, to 0.56. Using the LBP feature as the basis for our two-stage algorithm, we are able to detect 69.2% of field grown sweet peppers in three sites. This is an impressive result given that the average detection accuracy of people viewing the same colour imagery is 66.8%.

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Generating discriminative input features is a key requirement for achieving highly accurate classifiers. The process of generating features from raw data is known as feature engineering and it can take significant manual effort. In this paper we propose automated feature engineering to derive a suite of additional features from a given set of basic features with the aim of both improving classifier accuracy through discriminative features, and to assist data scientists through automation. Our implementation is specific to HTTP computer network traffic. To measure the effectiveness of our proposal, we compare the performance of a supervised machine learning classifier built with automated feature engineering versus one using human-guided features. The classifier addresses a problem in computer network security, namely the detection of HTTP tunnels. We use Bro to process network traffic into base features and then apply automated feature engineering to calculate a larger set of derived features. The derived features are calculated without favour to any base feature and include entropy, length and N-grams for all string features, and counts and averages over time for all numeric features. Feature selection is then used to find the most relevant subset of these features. Testing showed that both classifiers achieved a detection rate above 99.93% at a false positive rate below 0.01%. For our datasets, we conclude that automated feature engineering can provide the advantages of increasing classifier development speed and reducing development technical difficulties through the removal of manual feature engineering. These are achieved while also maintaining classification accuracy.

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This paper deals with low maximum-likelihood (ML)-decoding complexity, full-rate and full-diversity space-time block codes (STBCs), which also offer large coding gain, for the 2 transmit antenna, 2 receive antenna (2 x 2) and the 4 transmit antenna, 2 receive antenna (4 x 2) MIMO systems. Presently, the best known STBC for the 2 2 system is the Golden code and that for the 4 x 2 system is the DjABBA code. Following the approach by Biglieri, Hong, and Viterbo, a new STBC is presented in this paper for the 2 x 2 system. This code matches the Golden code in performance and ML-decoding complexity for square QAM constellations while it has lower ML-decoding complexity with the same performance for non-rectangular QAM constellations. This code is also shown to be information-lossless and diversity-multiplexing gain (DMG) tradeoff optimal. This design procedure is then extended to the 4 x 2 system and a code, which outperforms the DjABBA code for QAM constellations with lower ML-decoding complexity, is presented. So far, the Golden code has been reported to have an ML-decoding complexity of the order of for square QAM of size. In this paper, a scheme that reduces its ML-decoding complexity to M-2 root M is presented.

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The red genes of phage lambda specify two proteins, exonuclease and beta protein, which are essential for its general genetic recombination in recA- cells. These proteins seem to occur in vivo as an equimolar complex. In addition, beta protein forms a complex with another polypeptide, probably of phage origin, of Mr 70,000. The 70-kDa protein appears to be neither a precursor nor an aggregated form of either exonuclease or beta protein, since antibodies directed against the latter two proteins failed to react with 70-kDa protein on Ouchterlony double diffusion analysis. beta protein promotes Mg2+-dependent renaturation of complementary strands (Kmiec, E., and Holloman, W. K. (1981) J. Biol. Chem. 256, 12636-12639). To look for other pairing activities of beta protein, we developed methods of purification to free it of associated exonuclease. Exonuclease-free beta protein appeared unable to cause the pairing of a single strand with duplex DNA; however, like Escherichia coli single strand binding protein (SSB), beta protein stimulated formation of joint molecules by recA protein from linear duplex DNA and homologous circular single strands. Like recA protein, but unlike SSB, beta protein promoted the joining of the complementary single-stranded ends of phage lambda DNA. beta protein specifically protected single-stranded DNA from digestion by pancreatic DNase. The half-time for renaturation catalyzed by beta protein was independent of DNA concentration, unlike renaturation promoted by SSB and spontaneous renaturation, which are second order reactions. Thus, beta protein resembles recA protein in its ability to bring single-stranded DNA molecules together and resembles SSB in its ability to reduce secondary structure in single-stranded DNA.

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With the development of wearable and mobile computing technology, more and more people start using sleep-tracking tools to collect personal sleep data on a daily basis aiming at understanding and improving their sleep. While sleep quality is influenced by many factors in a person’s lifestyle context, such as exercise, diet and steps walked, existing tools simply visualize sleep data per se on a dashboard rather than analyse those data in combination with contextual factors. Hence many people find it difficult to make sense of their sleep data. In this paper, we present a cloud-based intelligent computing system named SleepExplorer that incorporates sleep domain knowledge and association rule mining for automated analysis on personal sleep data in light of contextual factors. Experiments show that the same contextual factors can play a distinct role in sleep of different people, and SleepExplorer could help users discover factors that are most relevant to their personal sleep.

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This paper presents an experimental investigation on the lateral impact performance of axially loaded concrete-filled double-skin tube (CFDST) columns. These columns have desirable structural and constructional properties and have been used as columns in building, legs of off shore platforms and as bridge piers. Since they could be vulnerable to impact from passing vessels or vehicles, it is necessary to understand their behaviour under lateral impact loads. With this in mind, an experimental method employing an innovative instrumented horizontal impact testing system (HITS) was developed to apply lateral impact loads whilst the column maintained a static axial pre-loading to examine the failure mechanism and key response parameters of the column. These included the time histories of impact force, reaction forces, global lateral deflection and permanent local buckling profile. Eight full scale columns were tested for key parameters including the axial load level and impact location. Based on the test data, the failure mode, peak impact force, impact duration, peak reaction forces, reaction force duration, column maximum and residual global deflections and column local buckling length, depth and width under varying conditions are analysed and discussed. It is evident that the innovative HITS can successfully test structural columns under the combination of axial pre-loading and impact loading. The findings on the lateral impact response of the CFDST columns can serve as a benchmark reference for their future analysis and design.

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Sudden cardiac arrest (CA) is one of the leading causes of death in Europe. It has been estimated that about 40 % of CA victims have ventricular fibrillation (VF) at the time of the first heart rhythm analysis. The treatment for VF is immediate cardiopulmonary resuscitation (CPR) and rapid defibrillation. The automated external defibrillator (AED) and the concept of public access defibrillation (PAD) may be a key to shortening defibrillation delays. Recent studies have shown that PAD programs are associated with high survival rates from VF when devices have been placed in certain risk sites and used by trained laypersons. Today many public places are equipped with AEDs. The purpose of this study was to find new ways of utilizing layperson defibrillation and promote the concept of public access defibrillation (PAD). The study explored the use of AEDs by non-medical first responders in Finland and cabin crew on board a commercial aircraft. A simulated study was performed to explore the role of dispatcher assistance in layperson CPR and defibrillation. A 15-year follow-up study of 59 one-year survivors after successful out-of-hospital resuscitation was performed to evaluate the long-term quality of life of the CA patients. Although there are many AEDs in use by non-medical first responders in Finland, the results of the study showed that there are large variations between individual first response units. This is considered to be caused by the lack of national standards and regulations that would define a full integration of first-responder programmes into the Emergency Medical Services system. The goal of rapid defibrillation in five minutes after the onset of CA is difficult to achieve in Finland due to sparse population and long distances. Local PAD programs may shorten the defibrillation delays. Dispatcher assistance in defibrillation by a layperson not trained to use an AED seems feasible and does not compromise the performance of CPR. In a simulated study, the quality of mouth-to-mouth ventilation performed by laypersons was found to be better after CPR training compared with performance with dispatcher assistance before training. Training was not found to have an influence on the quality of compressions or defibrillation compared with dispatcher assistance of untrained laypersons. The target groups for CPR and defibrillation training need further evaluation. The placements of the AEDs in public areas should be known by the emergency response center and the location should be marked with an international sign. The finding that once a good neurological outcome after CA is achieved, it can be maintained for more than 10 years, encourages further efforts to improve the survival of CA patients.

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We present a case study of formal verification of full-wave rectifier for analog and mixed signal designs. We have used the Checkmate tool from CMU [1], which is a public domain formal verification tool for hybrid systems. Due to the restriction imposed by Checkmate it necessitates to make the changes in the Checkmate implementation to implement the complex and non-linear system. Full-wave rectifier has been implemented by using the Checkmate custom blocks and the Simulink blocks from MATLAB from Math works. After establishing the required changes in the Checkmate implementation we are able to efficiently verify, the safety properties of the full-wave rectifier.

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A switched rectifier DC voltage source three-level neutral-point-clamped (NPC) converter topology is proposed here to alleviate the inverter from capacitor voltage balancing in three-level drive systems. The proposed configuration requires only one DC link with a voltage of half of that needed in a conventional NPC inverter. To obtain a rated DC link voltage, the rectifier DC source is alternately connected in parallel to one of the two series capacitors using two switches and two diodes with device voltage ratings of half the total DC bus voltage. The frequency at which the voltage source is switched is independent of the inverter and will not affect its operation since the switched voltage source in this configuration balances the capacitors automatically. The proposed configuration can also be used as a conventional two-level inverter in the lower modulation index range, thereby increasing the reliability of the drivesystem. A space-vector-based PWM scheme is used to verify this proposed topology on a laboratory system.

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Background: MHC/HLA class II molecules are important components of the immune system and play a critical role in processes such as phagocytosis. Understanding peptide recognition properties of the hundreds of MHC class II alleles is essential to appreciate determinants of antigenicity and ultimately to predict epitopes. While there are several methods for epitope prediction, each differing in their success rates, there are no reports so far in the literature to systematically characterize the binding sites at the structural level and infer recognition profiles from them. Results: Here we report a new approach to compare the binding sites of MHC class II molecules using their three dimensional structures. We use a specifically tuned version of our recent algorithm, PocketMatch. We show that our methodology is useful for classification of MHC class II molecules based on similarities or differences among their binding sites. A new module has been used to define binding sites in MHC molecules. Comparison of binding sites of 103 MHC molecules, both at the whole groove and individual sub-pocket levels has been carried out, and their clustering patterns analyzed. While clusters largely agree with serotypic classification, deviations from it and several new insights are obtained from our study. We also present how differences in sub-pockets of molecules associated with a pair of autoimmune diseases, narcolepsy and rheumatoid arthritis, were captured by PocketMatch(13). Conclusion: The systematic framework for understanding structuralvariations in MHC class II molecules enables large scale comparison of binding grooves and sub-pockets, which is likely to have direct implications towards predicting epitopes and understanding peptide binding preferences.