977 resultados para synchronous HMM


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The past several years have seen significant advances in the development of computational methods for the prediction of the structure and interactions of coiled-coil peptides. These methods are generally based on pairwise correlations of amino acids, helical propensity, thermal melts and the energetics of sidechain interactions, as well as statistical patterns based on Hidden Markov Model (HMM) and Support Vector Machine (SVM) techniques. These methods are complemented by a number of public databases that contain sequences, motifs, domains and other details of coiled-coil structures identified by various algorithms. Some of these computational methods have been developed to make predictions of coiled-coil structure on the basis of sequence information; however, structural predictions of the oligomerisation state of these peptides still remains largely an open question due to the dynamic behaviour of these molecules. This review focuses on existing in silico methods for the prediction of coiled-coil peptides of functional importance using sequence and/or three-dimensional structural data.

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The overall architectural pattern of the mature plant is established during embryogenesis. Very little is known about the molecular processes that underlie embryo morphogenesis. Last decade has, nevertheless, seen a burst of information on the subject. The synchronous somatic embryogenesis system of carrot is largely being used as the experimental system. Information on the molecular regulation of embryogenesis obtained with carrot somatic embryos as well as observations on sandalwood embryogenic system developed in our laboratory are summarized in this review. The basic experimental strategy of molecular analysis mostly relied on a comparison between genes and proteins being expressed in embryogenic and non-embryogenic cells as well as in the different stages of embryogenesis. Events such as expression of totipotency of cells and establishment of polarity which are so critical for embryo development have been characterized using the strategy, Several genes have been identified and cloned from the carrot system, These include sequences that encode certain extracellular proteins (EPs) that influence cell proliferation and embryogenesis in specific ways and sequences of the abscisic acid (ABA) inducible late embryogenesis abundant (LEA) proteins which are most abundant and differentially expressed mRNAs in somatic embryos. That LEAs are expressed in the somatic embryos of a tree flora also is evidenced from studies on sandalwood Several undescribed or novel sequences that are enhanced in embryos were identified. A sequence of this nature exists in sandalwood embryos was demonstrated using a Cuscuta haustorial (organ-specific) cDNA probe. Somatic embryogenesis systems have been used to assess the expression of genes isolated from non-embryogenic tissues. Particular attention has been focused on both cell cycle and histone genes.

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In the synchronous embryogenesis system of sandalwood developed in our laboratory, we observed that the early events of differentiation from freshly induced callus (stage 0) are accomplished in three distinct stages viz., preglobular masses (stage 1), globular embryos (stage 2), and bipolar embryos (stage 3). Transition from stage 0 to 1 was accomplished using 2,4-D and involves a stage specific appearance of two polypeptides of 15 and 30 kDa molecular weight. A 24 kDa polypeptide that was detected as a marked band in extracts of primary callus was not detected in stages 1, 2, and 3. Further, the tissue level of a 50 kDa glycoprotein decreased during transition from stage 2 to stage 3. However, the levels of glycoproteins in the medium were markedly higher in stage 0 cultures compared to those in stage 1. The activities of a protein kinase, glycosidase, and xylanase increased markedly with progressing embryogenesis. Our observations suggest that in addition to being controlled at the level of stage-specific gene expression, somatic embryogenesis in sandalwood is also regulated at the level of controls on cell wall flexibility and posttranslational changes in the pool of preexisting proteins.

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Information exchange (IE) is a critical component of the complex collaborative medication process in residential aged care facilities (RACFs). Designing information and communication technology (ICT) to support complex processes requires a profound understanding of the IE that underpins their execution. There is little existing research that investigates the complexity of IE in RACFs and its impact on ICT design. The aim of this study was thus to undertake an in-depth exploration of the IE process involved in medication management to identify its implications for the design of ICT. The study was undertaken at a large metropolitan facility in NSW, Australia. A total of three focus groups, eleven interviews and two observation sessions were conducted between July to August 2010. Process modelling was undertaken by translating the qualitative data via in-depth iterative inductive analysis. The findings highlight the complexity and collaborative nature of IE in RACF medication management. These models emphasize the need to: a) deal with temporal complexity; b) rely on an interdependent set of coordinative artefacts; and c) use synchronous communication channels for coordination. Taken together these are crucial aspects of the IE process in RACF medication management that need to be catered for when designing ICT in this critical area. This study provides important new evidence of the advantages of viewing process as a part of a system rather than as segregated tasks as a means of identifying the latent requirements for ICT design and that is able to support complex collaborative processes like medication management in RACFs. © 2012 IEEE.

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We are addressing the novel problem of jointly evaluating multiple speech patterns for automatic speech recognition and training. We propose solutions based on both the non-parametric dynamic time warping (DTW) algorithm, and the parametric hidden Markov model (HMM). We show that a hybrid approach is quite effective for the application of noisy speech recognition. We extend the concept to HMM training wherein some patterns may be noisy or distorted. Utilizing the concept of ``virtual pattern'' developed for joint evaluation, we propose selective iterative training of HMMs. Evaluating these algorithms for burst/transient noisy speech and isolated word recognition, significant improvement in recognition accuracy is obtained using the new algorithms over those which do not utilize the joint evaluation strategy.

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Detect and Avoid (DAA) technology is widely acknowledged as a critical enabler for unsegregated Remote Piloted Aircraft (RPA) operations, particularly Beyond Visual Line of Sight (BVLOS). Image-based DAA, in the visible spectrum, is a promising technological option for addressing the challenges DAA presents. Two impediments to progress for this approach are the scarcity of available video footage to train and test algorithms, in conjunction with testing regimes and specifications which facilitate repeatable, statistically valid, performance assessment. This paper includes three key contributions undertaken to address these impediments. In the first instance, we detail our progress towards the creation of a large hybrid collision and near-collision encounter database. Second, we explore the suitability of techniques employed by the biometric research community (Speaker Verification and Language Identification), for DAA performance optimisation and assessment. These techniques include Detection Error Trade-off (DET) curves, Equal Error Rates (EER), and the Detection Cost Function (DCF). Finally, the hybrid database and the speech-based techniques are combined and employed in the assessment of a contemporary, image based DAA system. This system includes stabilisation, morphological filtering and a Hidden Markov Model (HMM) temporal filter.

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In our earlier work [1], we employed MVDR (minimum variance distortionless response) based spectral estimation instead of modified-linear prediction method [2] in pitch modification. Here, we use the Bauer method of MVDR spectral factorization, leading to a causal inverse filter rather than a noncausal filter setup with MVDR spectral estimation [1]. Further, this is employed to obtain source (or residual) signal from pitch synchronous speech frames. The residual signal is resampled using DCT/IDCT depending on the target pitch scale factor. Finally, forward filters realized from the above factorization are used to get pitch modified speech. The modified speech is evaluated subjectively by 10 listeners and mean opinion scores (MOS) are tabulated. Further, modified bark spectral distortion measure is also computed for objective evaluation of performance. We find that the proposed algorithm performs better compared to time domain pitch synchronous overlap [3] and modified-LP method [2]. A good MOS score is achieved with the proposed algorithm compared to [1] with a causal inverse and forward filter setup.

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We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.

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Exploring emotions is a defining feature of psychotherapy. This study explores how therapists explore emotions when they cannot see or hear their clients. In analysing 1,279 sessions of online text-based Cognitive Behavioural Therapy (CBT) we focused on therapists’ commiserations (e.g., “I’m sorry to hear that”) and their affective inferences (e.g., “that sounds very scary for you”). Both practices routinely prefaced moves to pursue a range of therapeutic activities, many of which did not prioritise sustained focus on the emotion that had just been oriented to. By separating message composition from message transmission, the modality used for these therapy sessions enabled therapists to combine orientations to emotion with attempts to shift the focus of discussion. Our analysis finds that although physically co-present and computer-mediated psychotherapy share a common focus on emotional experience, the modality used for therapy can be relevant in the design and use of these orientations. Data are in British English.

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Sequence design and resource allocation for a symbol-asynchronous chip-synchronous code division multiple access (CDMA) system is considered in this paper. A simple lower bound on the minimum sum-power required for a non-oversized system, based on the best achievable for a non-spread system, and an analogous upper bound on the sum rate are first summarised. Subsequently, an algorithm of Sundaresan and Padakandla is shown to achieve the lower bound on minimum sum power (upper bound on sum rate, respectively). Analogous to the synchronous case, by splitting oversized users in a system with processing gain N, a system with no oversized users is easily obtained, and the lower bound on sum power (upper bound on sum rate, respectively) is shown to be achieved by using N orthogonal sequences. The total number of splits is at most N - 1.

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Infrared Earth sensors are used in spacecraft for attitude sensing. Their accuracy is limited by systematic and random errors. Dominant sources of systematic errors are analyzed for a typical scanning infrared Earth sensor used in a remote-sensing satellite in a 900-km sun-synchronous orbit. The errors considered arise from 1) seasonable variation of infrared radiation, 2) oblate shape of the Earth, 3) ambient temperature of sensors, 4) changes in spin/scan period, and 5) misalignment of the axis of the sensors. Simple relations are derived using least-squares curve fitting for onboard correction of these errors. With these, it is possible to improve the accuracy of attitude determination by eight fold and achieve performance comparable to ground-based post-facto attitude computation.

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A novel method for the construction of tricyclo[5.3.1.0(1,5)]undecane and tricyclo[6.3.1.0(1,6)]dodecane frame work has been developed. Thus the alcohols 6, 18, 21 and 29 undergo Lewis acid-catalysed rearrangement to the tricyclic ketones 5, 19, 22 and 30. Dehydrogenation of 22 to the enone 23 proves the synchronous anti-migration of the methanobridge during the skeletal rearrangement. Finally, one carbon homologation of the ketones 5 and 19 leads to the syntheses of 2-norcedrene 4 and some analogues of funebrene 20 and 30.

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Joint decoding of multiple speech patterns so as to improve speech recognition performance is important, especially in the presence of noise. In this paper, we propose a Multi-Pattern Viterbi algorithm (MPVA) to jointly decode and recognize multiple speech patterns for automatic speech recognition (ASR). The MPVA is a generalization of the Viterbi Algorithm to jointly decode multiple patterns given a Hidden Markov Model (HMM). Unlike the previously proposed two stage Constrained Multi-Pattern Viterbi Algorithm (CMPVA),the MPVA is a single stage algorithm. MPVA has the advantage that it cart be extended to connected word recognition (CWR) and continuous speech recognition (CSR) problems. MPVA is shown to provide better speech recognition performance than the earlier techniques: using only two repetitions of noisy speech patterns (-5 dB SNR, 10% burst noise), the word error rate using MPVA decreased by 28.5%, when compared to using individual decoding. (C) 2010 Elsevier B.V. All rights reserved.

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The operation of a stand-alone, as opposed to grid connected generation system, using a slip-ring induction machine as the electrical generator, is considered. In contrast to an alternator, a slip-ring induction machine can run at variable speed and still deliver constant frequency power to loads. This feature enables optimization of the system when the prime mover is inherently variable speed in nature eg. wind turbines, as well as diesel driven systems, where there is scope for economizing on fuel consumption. Experimental results from a system driven by a 44 bhp diesel engine are presented. Operation at subsynchronous as well as super-synchronous speeds is examined. The measurement facilitates the understanding of the system as well as its design.

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This paper presents the detailed dynamic digital simulation for the study of phenomenon of torsional interaction between HVDC-Turbine generator shaft, dynamics using the novel converter model presented in [ 1 ] The system model includes detailed representation of the synchronous generator and the shaft dynamics, the ac and dc network transients. The results of a case study indicate the various factors that influence the torsional interaction.