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Image to video person re-identification (IVPR), i.e., matching between pedestrian video and image, is an important task in practice. Although several methods have been presented for IVPR, most of these methods investigate the IVPR problem under the supervised setting, and require a large number of labeled image-video pairs for training. In this article, we study the IVPR problem under the semi-supervised setting, and propose a Kernel Analysis-synthesis Dictionary based heterogeneous Distance Learning (KADDL) approach. Specifically, KADDL first learns two pairs of kernel analysis-synthesis dictionaries from the labeled and unlabeled training image-video data in the kernel space. With the learned dictionary pairs, the heterogeneous image and video features can be transformed into coding coefficients of the same representation space, such that the gap between image and video can be bridged. Then, KADDL learns a discriminative distance metric over the transformed coding coefficients, to make the coding coefficients of positive image-video pair become similar, while those of negative image-video pair dissimilar. To make better use of the unlabeled data, we further designed a reliability-based semi-supervised strategy for KADDL. Experiments on several publicly available pedestrian sequence datasets demonstrate the effectiveness of the proposed approach.

Voice communication has been and remains one of the main ways of human communication and human-machine exchange. Today a construction of new perspective systems of processing and protection of speech information is impossible without modeling of effective mechanisms of speech transformation, creation of speech-like signals with the set properties.For this purpose a unique approach is proposed which deals with transformation of a halftone image of a speech signal spectrogram into a binary one, its subsequent modification in order to solve the problems of protection and processing of speech information, and the possibility of a reverse transition to a halftone image and subsequent synthesis of a new speech-like signal with the desired properties.An improvement of the model of speech formation, making use of the properties of auditory perception and taking into account the features of the formation of binary spectrograms can significantly reduce the amount of speech information without losing its semantic content and recognition and provide an opportunity to use a rich and well-tested arsenal of ways to recognize and process binary and halftone images and a number of other important advantages.The prospects of using image analysis-synthesis technologies in relation to narrow-band sonograms and other kind of images while solving the problems of acoustic steganography, digital noise cleaning and reconstruction of distorted phonograms, audio labeling of significant information, speech compression and restoration are also evaluated.

Blind image deblurring remains a challenging problem for modern artificial neural networks. Unlike other image restoration problems, deblurring networks fail behind the performance of existing deblurring algorithms in case of uniform and 3D blur models. This follows from the diverse and profound effect that the unknown blur-kernel has on the deblurring operator. We propose a new architecture which breaks the deblurring network into an analysis network which estimates the blur, and a synthesis network that uses this kernel to deblur the image. Unlike existing deblurring networks, this design allows us to explicitly incorporate the blur-kernel in the network's training. In addition, we introduce new cross-correlation layers that allow better blur estimations, as well as unique components that allow the estimate blur to control the action of the synthesis deblurring action. Evaluating the new approach over established benchmark datasets shows its ability to achieve state-of-the-art deblurring accuracy on various tests, as well as offer a major speedup in runtime.

The morphological approach is a successful analytical tool for development schematic, conceptual and preliminary design of new engineering systems in Aerospace. This investigation used a morphological approach to engineering solutions development as well as to tools for creating promising individual smart rescue system on conceptual design stage. The problem was solved in two stages. At a higher level of the hierarchy, the principle of action in morphological box was chosen. In the second phase, specific engineering solutions were explored. Analysis of engineering systems, solutions and solving technique and systems and their potential opportunities with technique provide correct guidelines to supply the reasonable decisions. Flight simulations, depending on different initial conditions, were performed using the LANE program.

Automated histopathological image analysis offers exciting opportunities for the early diagnosis of several medical conditions including cancer. There are however stiff practical challenges: 1.) discriminative features from such images for separating diseased vs. healthy classes are not readily apparent, and 2.) distinct classes, e.g. healthy vs. stages of disease continue to share several geometric features. We propose a novel Analysis-synthesis model Learning with Shared Features algorithm (ALSF) for classifying such images more effectively. In ALSF, a joint analysis and synthesis learning model is introduced to learn the classifier and the feature extractor at the same time. In this way, the computation load in patch-level based image classification can be much reduced. Crucially, we integrate into this framework the learning of a low rank shared dictionary and a shared analysis operator, which more accurately represents both similarities and differences in histopathological images from distinct classes. ALSF is evaluated on two challenging databases: (1) kidney tissue images provided by the Animal Diagnosis Lab (ADL) at the Pennsylvania State University and (2) brain tumor images from The Cancer Genome Atlas (TCGA) database. Experimental results confirm that ALSF can offer benefits over state of the art alternatives., Comment: 2018 ISBI conference accepted paper

In this paper, we propose a novel coupled dictionary learning method, namely coupled analysis-synthesis dictionary learning, to improve the performance of person re-identification in the non-overlapping fields of different camera views. Most of the existing coupled dictionary learning methods train a coupled synthesis dictionary directly on the original feature spaces, which limits the representation ability of the dictionary. To handle the diversities of different original spaces, We first employ local Fisher discriminant analysis (LFDA) to learn a common feature space for close relationship of the same people in different views. In order to enhance the representation power of the coupled synthesis dictionary, we then learn a coupled analysis dictionary by transforming the common feature space into the coupled feature space. Experimental results on two publicly available VIPeR and CUHK01 datasets have validated the effectiveness of the proposed method.

One of the topics in multi-rate digital signal processing is the theory and design of M-band (or M-channel) analysis and synthesis quadrature mirror filter (QMF) banks for sub-band signal decomposition and coding. They are also called M-band maximally decimated critically sampled QMF banks. The analysis QMF bank consists of M uniform and equally spaced channel filters to decompose the input signal into M sub-band signals. The synthesis QMF bank consists of channel filters to reconstruct the original signal exactly from sub-band signals, or to recover a signal which is nearly perfect approximation of the original signal. Historically, discovering the 2-band QMF banks in 1976 stimulated and started research activities leading to extending the theory of near-perfect and perfect reconstruction QMF banks for arbitrary number of sub-bands, to developing a family of near-perfect modulated filter banks (or pseudo-QMF banks) and perfect reconstruction modulated filter banks based on the concept of time domain aliasing cancellation.

Concept generation involves both analysis and synthesis activities interchangeably. In current practice, these two activities are often loosely defined and randomly performed. This paper presents a new method, called the Analysis Synthesis Alternation (ASA) approach, which treats concept generation as a proposition-making process and adapts the formal logic definitions of analytic and synthetic propositions to generate new concepts via two stages: ideation and validation. Both stages involve systemic alternations between analytic and synthetic propositions, but the alterations are performed in reverse reasoning directions. Experiment shows that ASA outperforms traditional brainstorming technique in both novelty and functionality.

We describe tools for automatic identification and classification of diatoms that compare photographs with other photographs and drawings, via a model. Identification of diatoms, i.e. assigning a new specimen to one of the known species, has applications in many disciplines, including ecology, palaeoecology and forensic science. The model we build represents life cycle and natural variation of both shape and texture over multiple diatom species, derived automatically from photographs and/or drawings. The model can be used to automatically produce drawings of diatoms at any stage of their life cycle development. Similar drawings are traditionally used for diatom identification, and encapsulate visually salient diatom features. In this article, we describe the methods used for analysis of photographs and drawings, present our model of diatom shape and texture variation, and finish with results of identification experiments using photographs and drawings as well as a detailed evaluation.

This is the peer reviewed version of the following article: Julio C. Brégains; Francisco Ares "Analysis, synthesis, and diagnostics of antenna arrays through complex-valued neural networks", Microwave and Optical Technology Letters, 1512 - 1515 Volume: 48, Issue: 8, Aug. 2006, which has been published in final form at DOI: 10.1002/mop.21706. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving [Abstract] It is shown in this paper that when artificial neural networks are extended to be complex valued, they can be incorporated as a very powerful and effective tool in the analysis, synthesis, and diagnostics of antenna arrays.

This paper proposes an E-cosmetic function for digital images based on physics and physiologically-based image processing. A practical skin color and texture analysis/synthesis technique is introduced for this E-cosmetic function. Shading on the face is removed by a simple color vector analysis in the optical density domain as an inverse lighting technique. The image without shading is analyzed by a previously introduced technique that extracts hemoglobin and melanin components by independent component analysis. Experimental results using UV-B irradiation and the application of methyl nicotinate on the arms support the physiological validity of the analysis and the effectiveness of the proposed shading removal. We synthesized the way facial images changed due to tanning or alcohol consumption, and compared the synthesized images with images of actual changes in skin color. The comparison shows an excellent match between the synthesized and actual images of changes due to tanning and alcohol consumption. We also proposed a technique to synthesize the change of texture in pigment due to aging or the application of cosmetics. The pyramid-based texture analysis/synthesis technique was used for the spatial processing of texture. Using the proposed technique, we could realistically change the skin color and texture of a 50 year-old woman to that of a 20 year-old woman.

1 College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao 266590, China 2 Department of Mechanical Engineering, Ecole Polytechnique de Montreal, Station Centre-Ville, P.O. Box 6079, Montreal, QC, Canada H3C 3A7 3 School of Control Science and Engineering, Shandong University, Jinan 250061, China 4 Institute of Automation, Qufu Normal University, Qufu 273165, China

International audience; Vegetation analysis and reconstruction of remote sensing data are challenging problems. Using architectural tree models combined with model inputs estimated from aerial image analysis, this paper presents an analysis-synthesis approach for urban vegetation detection, modeling, and reconstruction. Tree species, height, and crown size information are extracted by aerial image analysis. These variables serve for model inversion to retrieve plant age, climatic growth conditions, and competition with neighbors. Functional-structural individual-based tree models are used to reconstruct and visualize virtual trees and their time evolutions realistically in a 3-D viewer rendering the models with geographical coordinates in the reconstructed scene. Our main contributions are: 1) a novel approach for generating plant models in 3-D reconstructed scenes based on the analysis of the geometric properties of the data, and 2) a modeling workflow for the reconstruction and growth simulation of vegetation in urban or natural environments

ASPIRIN, belladonna, digoxin, morphine, pyrethrum, quinine. The names read like a litany of the tonics, infusions, and other remedies people have turned to over the ages for their aches and pains. All are phytochemicals derived from plants or inspired by plant chemistry. Either as extracts or as purified compounds, such medicines have been used for centuries to protect or treat people, animals, and crops. Far from being old school, the field of photochemistry is being revitalized by sophisticated analysis, derivatization, and synthesis techniques. Armed with these tools and a new appreciation for the effectiveness of traditional remedies, companies are bringing a new clutch of phytochemicals to the market. The spur here is economic, particularly as costs soar for research into pharmaceuticals and crop protection chemicals. "Researchers are recognizing their limitations as well as the great expectations on research," says David Evans, an agrochemicals consultant who retired in 2003 as head of research and ...

This paper investigates shape estimation of articulated 3D objects for object-based analysis-synthesis coding based on the source model of ‘moving articulated 3D objects’. For shape estimation three steps are applied: shape-initialization, object-articulation and shape-adaptation. Here, a new algorithm for object-articulation is introduced. Object-articulation subdivides a rigid model object represented by a mesh of triangles into flexibly connected model object-components. For object articulation, neighboring triangles which exhibit similar 3D motion during the image sequence are clustered into patches. These patches are considered to be the model object-components. For 3D motion estimation of a single triangle, a more reliable algorithm is proposed. The reliability is measured by the probability of convergency to correct parameters. For improving the reliability both, a more robust technique is applied and the triangle and its neighborhood are evaluated by the estimation algorithm. For clustering, a frame to frame clustering method which considers clustering results obtained in previous frames is presented. The developed algorithm for object-articulation is incorporated in OBASC. Typical videophone test sequences were applied. Compared to OBASC based on the source model of ‘moving rigid 3D objects’, the transmission rate decreases from 63.5 to 53 kbit/s at a fixed image quality measured by SNR. Furthermore, a realistic object articulation of a model object ‘body’ into object-components ‘head’ and ‘shoulders’ can be achieved without a priori knowledge about the scene content.

The topic of investigation was the extension of a generic object-based analysis-synthesis coder (OBASC) using the source model of ‘moving flexible 3D objects’ for the encoding of moving images at very low data rates to a knowledge-based coder in case scene-specific knowledge can be acquired. According to the coding concept, the OBASC describes and encodes each moving object of an image sequence by three parameter sets defining its motion, shape and surface color. The parameter sets of each object are obtained by image analysis. Using the coded parameter sets, an image can be synthesized by model-based image synthesis. The coder switches to a knowledge-based coder as soon as scene-specific knowledge can be acquired. In the example given in this paper, an algorithm tries to detect faces within moving objects using template matching and feature extraction techniques. If a face is detected, the face model Candide is adapted to the image sequence and integrated into the 3D model object describing the moving object. Due to this knowledge of the scene, the head and shoulders scene can be more efficiently modeled and encoded. Furthermore, the knowledge of the scene contents is used for controlling the coder. When compared to OBASC, the knowledge-based coder reduces the bit-rate required for encoding head and shoulder scenes by 17%.

A new approach for the feasibility analysis of reactive distillation processes based on the reactive extractive curve maps (rExCM) concept is introduced. A method dedicated to reactive distillation feasibility analysis, and design has been developed in our team since 1999. From minimal information concerning the physicochemical properties of the system, three steps lead to the design of the unit and the specification of its operating conditions. Currently, the procedure permits the conceptual design of hybrid reactive column configuration with one or two feed plates, for any number of equilibrium reactions (provided that the degree of freedom of the system is equal to 2) occurring in liquid or vapor phase. This contribution focuses on the most recent developments: the generalization of the feasibility analysis step to double-feed processes thanks to the introduction of the rExCM concept. This methodology is illustrated through two examples: the emblematic methyl acetate example and the production of dimethyl methyl glutarate. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2346–2356, 2012

SUMMARY We synthesize the literature on auditors' evaluation of, and reporting on, internal control over financial reporting (ICOFR), as required by the Sarbanes-Oxley Act. The purpose of the synthesis is (1) to provide information on how and how well auditors perform the task, which serves as feedback to the Public Company Accounting Oversight Board on implementation issues and problems related to auditors' application of the professional standards on ICOFR; and (2) to identify gaps in the current literature and fruitful areas of future research. Consistent with Auditing Standard No. 5, we delineate five phases of the ICOFR audit: (1) planning; (2) scoping; (3) testing; (4) evaluation; and (5) reporting. We structure our synthesis using a framework that classifies the determinants of performance in each phase into five broad areas: (a) the auditor's attributes, (b) the client's attributes, (c) the interaction between the auditor and the client, (d) task attributes, and (e) environmental attributes. Key contributions include providing an ICOFR tasks taxonomy, proposing a model of the determinants of performance for each task, evaluating auditors' performance of the tasks in our taxonomy, highlighting findings and gaps of importance to regulators, and providing a road map for future research.

The topic of investigation was object-based analysis-synthesis coding (OBASC) using the source model of ‘moving rigid 3D objects’ for the encoding of moving images at very low data rates. According to the coding concept, each moving object of an image is described and encoded by three parameter sets defining its motion, shape and surface color. The parameter sets of each object are obtained by image analysis. They are coded using an object-dependent parameter coding. Using the coded parameter sets, an image can be synthesized by model-based image synthesis. In comparison to block-based hybrid coding, OBASC requires the additional transmission of shape parameters. The transmission of shape information avoids the mosquito and block artifacts of a block-based coder. Furthermore, important areas such as facial areas can be reconstructed with a significant image quality improvement. OBASC based on the source models of ‘moving flexible 2D objects’ and of ‘moving rigid 3D objects’ gives almost identical image quality for the same data rate. Therefore the use of more advanced source models like flexible 3D objects or 3D face models is expected to further improve image quality.

This correspondence investigates object-based analysis-synthesis coding (OBASC) for the encoding of moving images at very low data rates. According to the source model, each moving object of an image is described and encoded by three parameter sets defining its motion, shape, and surface color. The parameter sets of each object are obtained by model-based image analysis. They are coded by an object-dependent parameter coding. Using the coded parameter sets, an image can be synthesized by model-based image synthesis. Here, OBASC based on the source model of "moving flexible 3-D objects with 3-D motion" (F3D) is introduced. The efficiency of this source model F3D is compared to the efficiency of OBASC based on the source model of "moving rigid 3-D objects with 3-D motion" (R3D). Compared to R3D, F3D requires the additional transmission of flexible-shape parameters. Therefore, the source model F3D is only applied in those areas of the image which cannot be described by the source model R3D. The new source model F3D reduces the bit rate from 64 to 56 kb/s, providing the same picture quality measured by the SNR of the encoded color parameters. >

A binaural sinusoids+noise synthesis model is proposed for reproducing interior aircraft sounds. First, a method for spectral and spatial characterization of binaural interior aircraft sounds is presented. This characterization relies on a stationarity hypothesis and involves four estimators: left and right power spectra, interaural coherence and interaural phase difference. Then we present two extensions of the classical sinusoids+noise model for the analysis and synthesis of stationary binaural sounds. First, we propose a binaural estimator using relevant information in both left and right channels for peak detection. Second, the residual modeling is extended to integrate two interaural spatial cues, namely coherence and phase difference. The resulting binaural sinusoids+noise model is evaluated on a recorded aircraft sound.

A simulation method for the test of one input fire detection algorithm is presented. A signal model is described, capable of synthesising time variant random signal sequences with similar statistical properties, as observed for signals of smoke- and temperature-measuring devices in reality. The time varying model parameters are derived from recorded signals in realistic environmental conditions. The necessary analysis method is discussed. The simulation method is equally well suited for synthesising signal sequences in the ‘fire-’ and ‘nonfire’ case, which is necessary for the detectivity test of a detection algorithm. A fast transputer implementation yields acceptable calculation times even for estimates of the false alarm rate, corresponding to years observation time in reality.

Wire robots (also called Tendon-based parallel manipulators) use a movable end-effector which is connected to a machine frame by motor driven tendons. Since tendons can transmit only pulling forces, at least m = n + 1 cables are needed to tense a system having n degrees-of-freedom. The resulting redundancy gives m − n degrees-of-freedom in the wire force distribution, making workspace analysis a complex and computationally expensive task. Discrete methods are widely used to solve this problem, but their drawback is that intermediate points on the discrete calculation grid are neglected which may lead to false results. This paper provides detailed algorithms for continuous workspace analysis for wire robots which avoid the discretization and have additional advantages. Especially, it is easy to extend the analysis methods to methods usable for the workspace synthesis.Copyright © 2008 by ASME

This paper presents a model of asymptotically reliable serial production lines and develops a theory for its ana.lysis and synthesis along with a case study of a specific application. As far as the a.nalysis is concerned, a complete asymptotic theory is developed for calculation of the average production rate a.nd steady state buffer occupancy. As far as the synthesis is concerned, a new method of optimal design, referred to as dynamic balancing, is derived and applied to specific synthesis problems. As for the case study, the paper gives the results of the performance analysis of a. pa.int shop operation in a modern automobile assembly plant and shows that the difference between the actual and theoretical data is within 3%. Improvement measures, developed on the basis of the theory presented, brought about 11% increase in the pa.int shop production rate.

Applications of analysis, synthesis and optimization of floating-drift klystron in high level of parameters have been revised. Heuristic approach, which allows carry out synthesis of an optimum clot in klystron and realize the corresponding regime at producing of device with the record electronic efficiency of 90 %, is given. Our result also showed that the amplification's band could be in several times increased when reduce electronic efficiency to 60% in that band

We present a system for Internet communication that enhances traditional text-based chatting with real-time analysis and synthesis of the chat parties' facial expressions. It is composed of three main modules: a real-time facial expression analysis component, a 3D agent with facial expression synthesis and text-to-speech capabilities - a talking head, and a communication module. So far we have realized a prototype to find out attractive ways of communication on the Internet and are currently experimenting on how to utilize this new type of modalities in chat communication.

A novel Gaussian beam method, and a hybrid method, are developed for the efficient analysis of large reflector antenna systems, and large planar phased arrays, respectively. Several numerical results illustrating the speed and accuracy of these methods are described in this paper.

A unified analysis of monolithic microwave active inductors based on an amplifier-feedback topological description is introduced. Active inductors are classified based on the gain and feedback elements constituent to their design. Small signal, large signal and noise behavior are considered in the generic case. An illustrative example of the synthesis procedure for, as well as the measured results of a novel topology are presented.

For object-based analysis-synthesis coding (OBASC) of moving images, each moving object is described by three parameter sets defining its motion, shape and surface color. They are coded using an object-dependent parameter coding. Compared to block-based hybrid coding, OBASC requires the additional transmission of shape parameters. This is only justified, if it increases the overall coding efficiency. The efficiency of the block-based and the object-based coders depends to a large extend on the size of the moving objects. Objects smaller than 256 pels should be coded by a block-based coder whereas larger objects are preferably coded by an object-based coder. >

In this paper, different techniques for the creation of time coherent figurative animations from a video input are presented. The animations are generated using an analysis-synthesis approach. Information of the scene is extracted using only a 2D RGB image. No markers or depth planes are needed. After the analysis, the image is drawn again using the extracted information. To guarantee temporal coherence when redrawing the image, different alternatives have been explored: matching and interpolation on the parameters domain and gradient descent parameter update. All methods and variations are described and illustrated with images.

This paper presents an overview of the different works around gesture conducted at LIMSI Laboratory. Different kinds of capture devices are available, which allow us to deal with 2D or 3D gestures. Depending on projects, gestures are studied alone (monomodality), or combined with other modalities (speech). Different approaches are used, from analysis and synthesis to recognition and interpretation, along with knowledge representation.

A systematic approach to the description and analysis of robot's flexural characteristics is presented. Relations are derived for computing the total compliance matrix and deflection of the arm when considering the finite link stiffness, joint compliance and possible gear backlashes. The schema is applicable for serial, parallel or multi-arm structures. >

For object—oriented analysis—synthesis coding an image analysis algorithm is required which automatically generates the parameter sets which describe moving 3D objects in an image sequence. Areas changed between two consecutive images are detected by means of change detecti()n. Special processing is carried out to compute areas which coincide with object boundaries and to eliminate areas which represent illumination changes. These areas are segmented into silhouettes of moving objects and uncovered background. The border of an ob ject silhouette is interpreted as the outermost contour of an object. These contours in combination with a simple function giving the z—distance between them provide a first estimiate for 3D shape of a model object. In order to improve the efficiency of motion analysis a concept for combining model objects with new parts of moving objects is proposed. Results of an automatic image analysis based on moving 3D objects are shown using video telephone test sequences.

This tried and tested book was first published by Stephen Rowland in 1986. Ernest Duebendorfer was involved in the second edition of 1994, and now Ilsa Schiefelbein has joined the team for the third edition. The philosophy and general content of this edition remains substantially the same as in previous versions, but the presentation has been thoroughly updated. All the figures have been redrafted, the tear-out maps and exercises are now gathered at the end …

Analysis‐synthesis consists of constructing synthetic sounds from natural sounds by algorithmic synthesis methods. The models used for this purpose are of two kinds: physical models which take into account the physical characteristics of the instrument and signal models which take into account perceptual criteria. By combining physical and signal models hybrid models can be constructed taking advantage of the positive aspects of both methods. In this presentation I show how hybrid models can be adapted to specific instruments producing both sustained and plucked sounds. In these cases signal models are used to model the nonlinear source signal. The parameters of these models are obtained from perceptual criteria such as the spectral centroid or the tristimulus. The source signal is further injected into the physical model which consists of a digital wave guide model. The parameters of the physical model are extracted from the natural sound by analysis based on linear time‐frequency representations such as...

In solving design problems designers use a combination of analytical serial thinking and holistic synthetic thinking. This can be seen both in how the process is described by design theorists and in the practical activities which designers undertake. In common with most other forms of design, the industrial design work which will be described is mainly concerned with defining the physical form of objects and this requires visual thinking. The whole process involves modelling the design ideas using various techniques, and for the visual thinking they are externalized in the form of drawings and three-dimensional representations. Using drawings is the quickest and most fluid modelling technique, and such drawings will often reveal the combination of analytical and holistic processes which the designer employs. Project work from Coventry's Industrial Design Transportation course is used to demonstrate such strategies.

Traditional speech analysis/synthesis techniques are designed to produce synthesized speech with a spectrum (or waveform) that is as close as possible to the original. It is suggested, instead, that representations of the synthetic and the original speech be matched at the auditory nerve level. This concept has been used in conjunction with the sinusoidal representation of speech analysis/synthesis suggested by McAulay and Quatieri [6]. Based on informal listening, the synthesized speech is natural, including some tonal artifact, and highly intelligible for various kinds of speech material, in both quiet and noisy environments. The inherent dominance property of the auditory nerve representation reduces the number of sinusoidal components needed for synthesis by approximately 70 percent, offering a potential for reduced data rate.

Methamphetamine has been marketed illicitly since the 1960s. Much of the street material was illicitly synthesized. Although methamphetamine quality was variable in the past decade, it has emerged since 1978 as the only street stimulant which is likely to contain what it purports to contain. Although there is a small volume of legitimate methamphetamine still made by the pharmaceutical industry, most material analyzed by street-drug laboratories appears to have been illegitimately synthesized and not diverted. For a decade, relatively little methamphetamine was submitted to street-drug analytical labs. In recent years, although the absolute volume of methamphetamine submissions changed little, this drug made up the bulk of alleged stimulant samples submitted to such facilities because of the paucity of amphetamine submissions. Methamphetamine synthesis and use appears to constitute a small but continuing portion of the illicit drug market.

A group of 18 normal speaking Ss and 18 children with developmental articulatory speech defects were matched and exposed to three series of tape recorded utterances which were associated with 47 minimal triplet words. In condition I, each child heard one word from each of the 47 triplets; progressively fragmented words were given in conditions II and III. The child repeated the words or completed the mutilated members of the triplets and pointed to one of three pictures depicting each of the. triplets. The groups did not differ in condition I. The speech defective children, however, were inferior to the normal Ss in perceptual integration of fragmented words. These findings were discussed in terms of phonemic ‘cloze’ and suggestions for further research were offered.

The requirements of a commercial speech-telephone system are considered from first principles and shown to lead naturally to the idea of analysis-synthesis telephony when bandwidth is the main criterion of cost, i.e. in practice, for long distances. The more thoroughly the analysis-synthesis principle is exploited the greater is the resulting potential band economy; the price paid is a restriction in versatility, but not any inherent loss in quality of the reproduced speech. The vocoder, first developed in America before the recent war, is an example of an analysis-synthesis system. Details are given of British Post Office experience in the design and performance of vocoders. Using a high-quality microphone, an articulation efficiency approximately the same as the highest reached on an ordinary commercial circuit has been reliably achieved, though the rather ?inhuman? quality of the synthesized speech may be a disadvantage in some circumstances. A brief review of transmission systems which might be suitable for the vocoder is also given.