Query: Empirical Study of Unsupervised Chinese Word Segmentation Methods for SMT on Large-scale Corpora

Relevant passages:
A Systematic Comparison of Various Statistical Alignment Models <=SEP=> We present and compare various methods for computing word alignments using statistical or heuristic models. We consider the five alignment models presented in Brown, Della Pietra, Della Pietra, and Mercer (1993), the hidden Markov alignment model, smoothing techniques, and refinements. These statistical models are compared with two heuristic models based on the Dice coefficient. We present different methods for combining word alignments to perform a symmetrization of directed statistical alignment models. As evaluation criterion, we use the quality of the resulting Viterbi alignment compared to a manually produced reference alignment. We evaluate the models on the German-English Verbmobil task and the French-English Hansards task. We perform a detailed analysis of various design decisions of our statistical alignment system and evaluate these on training corpora of various sizes. An important result is that refined alignment models with a first-order dependence and a fertility model yield significantly better results than simple heuristic models. In the Appendix, we present an efficient training algorithm for the alignment models presented.

Minimum Error Rate Training in Statistical Machine Translation <=SEP=> Often, the training procedure for statistical machine translation models is based on maximum likelihood or related criteria. A general problem of this approach is that there is only a loose relation to the final translation quality on unseen text. In this paper, we analyze various training criteria which directly optimize translation quality. These training criteria make use of recently proposed automatic evaluation metrics. We describe a new algorithm for efficient training an unsmoothed error count. We show that significantly better results can often be obtained if the final evaluation criterion is taken directly into account as part of the training procedure.

Bayesian Unsupervised Word Segmentation with Nested Pitman-Yor Language Modeling <=SEP=> In this paper, we propose a new Bayesian model for fully unsupervised word segmentation and an efficient blocked Gibbs sampler combined with dynamic programming for inference. Our model is a nested hierarchical Pitman-Yor language model, where Pitman-Yor spelling model is embedded in the word model. We confirmed that it significantly outperforms previous reported results in both phonetic transcripts and standard datasets for Chinese and Japanese word segmentation. Our model is also considered as a way to construct an accurate word n-gram language model directly from characters of arbitrary language, without any “word” indications.

The Second International Chinese Word Segmentation Bakeoff <=SEP=> The second international Chinese word segmentation bakeoff was held in the summer of 2005 to evaluate the current state of the art in word segmentation. Twenty three groups submitted 130 result sets over two tracks and four different corpora. We found that the technology has improved over the intervening two years, though the out-of-vocabulary problem is still or paramount importance.

The Mathematics of Statistical Machine Translation: Parameter Estimation <=SEP=> We describe a series o,f five statistical models o,f the translation process and give algorithms,for estimating the parameters o,f these models given a set o,f pairs o,f sentences that are translations o,f one another. We define a concept o,f word-by-word alignment between such pairs o,f sentences. For any given pair of such sentences each o,f our models assigns a probability to each of the possible word-by-word alignments. We give an algorithm for seeking the most probable o,f these alignments. Although the algorithm is suboptimal, the alignment thus obtained accounts well for the word-by-word relationships in the pair o,f sentences. We have a great deal o,f data in French and English from the proceedings o,f the Canadian Parliament. Accordingly, we have restricted our work to these two languages; but we,feel that because our algorithms have minimal linguistic content they would work well on other pairs o,f languages. We also ,feel, again because of the minimal linguistic content o,f our algorithms, that it is reasonable to argue that word-by-word alignments are inherent in any sufficiently large bilingual corpus.

A cross-cultural test of the Maluma-Takete phenomenon. <=SEP=> 

Occupational therapy interventions for employment and education for adults with serious mental illness: a systematic review. <=SEP=> In this systematic review, we investigated research literature evaluating the effectiveness of occupational therapy interventions focusing on participation and performance in occupations related to paid and unpaid employment and education for people with serious mental illness. The review included occupation- and activity-based interventions and interventions addressing performance skills, aspects of the environment, activity demands, and client factors. The results indicate that strong evidence exists for the effectiveness of supported employment using individual placement and support to result in competitive employment. These outcomes are stronger when combined with cognitive or social skills training. Supported education programs emphasizing goal setting, skill development, and cognitive training result in increased participation in educational pursuits. The evidence for instrumental activities of daily living interventions that targeted specific homemaking occupations and supported parenting was limited but positive. Environmental cognitive supports, such as signs, and other compensatory strategies are useful in managing maladaptive behavior.

THE FUNCTIONAL APPROACH TO THE STUDY OF ATTITUDES <=SEP=> At the psychological level the reasons for holding or for changing attitudes are found in the functions they perform for the individual, specifically the functions of adjustment, ego defense, value expression, and knowledge. The conditions necessary to arouse or modify an attitude vary according to the motivational basis of the attitude. Ego-defensive attitudes, for example, can be aroused by threats, appeals to hatred and repressed impulses, and authoritarian suggestion, and can be changed by removal of threat, catharsis, and self-insight. Expressive attitudes are aroused by cues associated with the individual's values and by the need to reassert his self-image and can be changed by showing the appropriateness of the new or modified beliefs to the self-concept Brain washing is primarily directed at the value-expressive function and operates by controlling all environmental supports of old values. Changing attitudes may involve generalization of change to related areas of belief and feeling. Minimal generalization seems to be the rule among adults; for example, in politics voting for an opposition candidate does not have much effect upon party identification. The author is Professor of Psychology at the University of Michigan, former president of the Society for the Psychological Study of Social Issues, and coeditor of Research Methods in the Behavioral Sciences and Public Opinion and Propaganda.

Cachexia: a new definition. <=SEP=> On December 13th and 14th a group of scientists and clinicians met in Washington, DC, for the cachexia consensus conference. At the present time, there is no widely agreed upon operational definition of cachexia. The lack of a definition accepted by clinician and researchers has limited identification and treatment of cachectic patient as well as the development and approval of potential therapeutic agents. The definition that emerged is: "cachexia, is a complex metabolic syndrome associated with underlying illness and characterized by loss of muscle with or without loss of fat mass. The prominent clinical feature of cachexia is weight loss in adults (corrected for fluid retention) or growth failure in children (excluding endocrine disorders). Anorexia, inflammation, insulin resistance and increased muscle protein breakdown are frequently associated with cachexia. Cachexia is distinct from starvation, age-related loss of muscle mass, primary depression, malabsorption and hyperthyroidism and is associated with increased morbidity. While this definition has not been tested in epidemiological or intervention studies, a consensus operational definition provides an opportunity for increased research.

Automatic linkage of vital records. <=SEP=> The term record linkage has been used to indicate the bringing together of two or more separately re?orded pieces of information concerning a particular individual or family (I). Defined in this broad manner, it includes almost any use of a file of records to determine what has subsequently happened to people about whom one has some prior information, The various facts concerning an individual which in any modern society are recorded routinely would, if brought together, form an extensively documented history of his 1ife. In theory at least, an understanding might be derived from such collective histories concerning many of the factors which operate to influence the welfare of human populations, factors about which we are at present almost entirely in ignorance. Of course, much of the recorded information is in a relatively inaccessible form; but, even when circumstances have been most favorable, as in the registrations of births, deaths, and marriages, and in the census, there has been little recognition of the special value of the records as a source of statistics when they are brought together so as to relate the successive events in the lives of particular individuals and families. The chief reason for this lies in the high cost of searching manually for large numbers of single documents among vast accumulations of files. It is obvious that the searching could be mechanized, but as yet there has been no clear demonstration that machines can carry out the record linkages rapidly enough, cheaply enough, and with sufficient accuracy to make this practicable. The need for various follow-up studies such as might be carried out with the aid of record linkage have been discussed in detail elsewhere (I, 2), and there are numerous examples o{ important surveys which could be greatly extended in scope if existing record files were more readily linkable (3). Our special interest in the techniques of record linkage relates to their possible use (i) for keeping track of large groups of individuals who have been exposed to low levels of radiation, in order to determine the causes of their eventual deaths (see 4, chap. 8, para. 48; 5), and (ii) for assessing the relative importance of repeated natural mutations on the one hand, and of fertility differentials on the other, in maintaining the frequency of genetic defects in human populations (see 4, chap. 6, para. 36c). Our own studies (6) were started as part of a plan to look for possible differentials of family fertility in relation to the presence or absence of hereditary disease (through the use of vital records and a register of hm-sdicapped children). The first step has been the development of a method for linking birth records to marriage records automatically with a Datatron 205 computer. For this purpose use has been made of the records of births which occurred in the Canadian province of British Columbia during the year 1955 (34, 138 births) and of the marriages which took place in the same province over the 10-year period 1946-55 (114,47 1 marriages). Fortunately, these records were already in punch-card form as a part of Canada’s National Index, and from them could be extracted most of the necessary information on names and other

Financial Stock Market Forecast using Data Mining Techniques <=SEP=> The automated computer programs using data mining and predictive technologies do a fare amount of trades in the markets. Data mining is well founded on the theory that the historic data holds the essential memory for predicting the future direction. This technology is designed to help investors discover hidden patterns from the historic data that have probable predictive capability in their investment decisions. The prediction of stock markets is regarded as a challenging task of financial time series prediction. Data analysis is one way of predicting if future stocks prices will increase or decrease. Five methods of analyzing stocks were combined to predict if the day's closing price would increase or decrease. These methods were Typical Price (TP), Bollinger Bands, Relative Strength Index (RSI), CMI and Moving Average (MA). This paper discussed various techniques which are able to predict with future closing stock price will increase or decrease better than level of significance. Also, it investigated various global events and their issues predicting on stock markets. It supports numerically and graphically.

A method for classifying medical images using transfer learning: A pilot study on histopathology of breast cancer <=SEP=> The advance of deep learning has made huge changes in computer vision and produced various off-the-shelf trained models. Particularly, Convolutional Neural Network (CNN) has been widely used to build image classification model which allow researchers transfer the pre-trained learning model for other classifications. We propose a transfer learning method to detect breast cancer using histopathology images based on Google's Inception v3 model which were initially trained for the classification of non-medical images. The pilot study shows the feasibility of transfer learning in the detection of breast cancer with AUC of 0.93.

Data Management for Journalism <=SEP=> We describe the power and potential of data journalism, where news stories are reported and published with data and dynamic visualizations. We discuss the challenges facing data journalism today and how recent data management tools such as Google Fusion Tables have helped in the newsroom. We then describe some of the challenges that need to be addressed in order for data journalism to reach its full

Escape loneliness by going digital: a quantitative and qualitative evaluation of a Dutch experiment in using ECT to overcome loneliness among older adults. <=SEP=> BACKGROUND
This study evaluates the outcomes of an Internet-at-home intervention experiment that intended to decrease loneliness among chronically ill and physically handicapped older adults through introducing them to the use of an electronic communication facility.


METHOD
To determine the effectiveness of the experiment in terms of reducing loneliness, 15 older adults were interviewed three times: shortly before the start, two years later and immediately after termination of the experiment, while their loneliness scores at zero and post-measurement were compared with those of a control group.


RESULTS
Both the participants and the control persons experienced a reduction in loneliness over time. However, the reduction was only significant for the intervention participants. Moreover, the changes in loneliness were significantly greater among the participants compared to the control persons. When looking more in detail, the effect of the experiment was only significant regarding emotional loneliness and among the highest educated. Findings of the qualitative research enabled us to understand the mechanisms through which the intervention helped alleviate loneliness. E-mail was found to facilitate social contact. Furthermore, the computer and Internet were often used to pass the time, taking people's minds off their loneliness. Unexpectedly, the intervention also improved people's self-confidence.


CONCLUSION
The decline in loneliness is likely to be greater if persons under more favorable circumstances are selected and if more social functions of the Internet are used.

Semantic Foggy Scene Understanding with Synthetic Data <=SEP=> This work addresses the problem of semantic foggy scene understanding (SFSU). Although extensive research has been performed on image dehazing and on semantic scene understanding with clear-weather images, little attention has been paid to SFSU. Due to the difficulty of collecting and annotating foggy images, we choose to generate synthetic fog on real images that depict clear-weather outdoor scenes, and then leverage these partially synthetic data for SFSU by employing state-of-the-art convolutional neural networks (CNN). In particular, a complete pipeline to add synthetic fog to real, clear-weather images using incomplete depth information is developed. We apply our fog synthesis on the Cityscapes dataset and generate Foggy Cityscapes with 20,550 images. SFSU is tackled in two ways: (1) with typical supervised learning, and (2) with a novel type of semi-supervised learning, which combines (1) with an unsupervised supervision transfer from clear-weather images to their synthetic foggy counterparts. In addition, we carefully study the usefulness of image dehazing for SFSU. For evaluation, we present Foggy Driving, a dataset with 101 real-world images depicting foggy driving scenes, which come with ground truth annotations for semantic segmentation and object detection. Extensive experiments show that (1) supervised learning with our synthetic data significantly improves the performance of state-of-the-art CNN for SFSU on Foggy Driving; (2) our semi-supervised learning strategy further improves performance; and (3) image dehazing marginally advances SFSU with our learning strategy. The datasets, models and code are made publicly available.

An architecture-based approach to self-adaptive software <=SEP=> CONSIDER THE FOLLOWING SCEnario. A fleet of unmanned air vehicles undertakes a mission to disable an enemy airfield. Pre-mission intelligence indicates that the airfield is not defended, and mission planning proceeds accordingly. While the UAVs are en route to the target, new intelligence indicates that a mobile surface-to-air missile launcher now guards the airfield. The UAVs autonomously replan their mission, dividing into two groups—a SAM-suppression unit and an airfield-suppression unit—and proceed to accomplish their objectives. During the flight, specialized algorithms for detecting and recognizing SAM launchers automatically upload and are integrated into the SAM-suppression unit’s software. In this scenario, new software components are dynamically inserted into fielded, heterogeneous systems without requiring system restart, or indeed, any downtime. Mission replanning relies on analyses that include feedback from current performance. Furthermore, such replanning can take place autonomously, can involve multiple, distributed, cooperating planners, and where major changes are demanded and require human approval or guidance, can cooperate with mission analysts. Throughout, system integrity requires the assurance of consistency, correctness, and coordination of changes. Other applications for fleets of UAVs might include environment and land-use monitoring, freeway-traffic management, fire fighting, airborne cellular-telephone relay stations, and damage surveys in times of natural disaster. How wasteful to construct afresh a specific software platform for each new UAV application! Far better if software architects can simply adapt the platform to the application at hand, and better yet, if the platform itself adapts on demand even while serving some other purpose. For example, an irborne sensor platform designed for environmental and land-use monitoring could prove useful for damage surveys following an earthquake or hurricane, provided someone could change the software quickly enough and with sufficient assurance that the new system would perform as intended. Software engineering aims for the systematic, principled design and deployment of applications that fulfill software’s original promise—applications that retain full plasticity throughout their lifecycle and that are as easy to modify in the field as they are on the drawing board. Software engineers have pursued many techniques for achieving this goal: specification languages, high-level programming languages, and object-oriented analysis and design, to name just a few. However, while each contributes to the goal, the sum total still falls short. Self-adaptive software will provide the key. Many disciplines will contribute to its progress, but wholesale advances require a sysSELF-ADAPTIVE SOFTWARE REQUIRES HIGH DEPENDABILITY, ROBUSTNESS, ADAPTABILITY, AND AVAILABILITY. THIS ARTICLE DESCRIBES AN INFRASTRUCTURE SUPPORTING TWO SIMULTANEOUS PROCESSES IN SELF-ADAPTIVE SOFTWARE: SYSTEM EVOLUTION, THE CONSISTENT APPLICATION OF CHANGE OVER TIME, AND SYSTEM ADAPTATION, THE CYCLE OF DETECTING CHANGING CIRCUMSTANCES AND PLANNING AND DEPLOYING RESPONSIVE MODIFICATIONS.

Approach and Avoidance Achievement Goals and Intrinsic Motivation : A Mediational Analysis <=SEP=> Most contemporary achievement goal conceptualizations consist of a performance goal versus mastery goal dichotomy. The present research offers an alternative framework by partitioning the performance goal orientation into independent approach and avoidance motivational orientations. Two experiments investigated the predictive utility of the proposed approach-avoidance achievement goal conceptualization in the intrinsic motivation domain. Results from both experiments supported the proposed framework; only performance goals grounded in the avoidance of failure undermined intrinsic motivation. Task involvement was validated as a mediator of the observed effects on intrinsic motivation. Ramifications for the achievement goal approach to achievement motivation and future research avenues are discussed.

Intrinsic cancer subtypes-next steps into personalized medicine <=SEP=> Recent technological advances have significantly improved our understanding of tumor biology by means of high-throughput mutation and transcriptome analyses. The application of genomics has revealed the mutational landscape and the specific deregulated pathways in different tumor types. At a transcriptional level, multiple gene expression signatures have been developed to identify biologically distinct subgroups of tumors. By supervised analysis, several prognostic signatures have been generated, some of them being commercially available. However, an unsupervised approach is required to discover a priori unknown molecular subtypes, the so-called intrinsic subtypes. Moreover, an integrative analysis of the molecular events associated with tumor biology has been translated into a better tumor classification. This molecular characterization confers new opportunities for therapeutic strategies in the management of cancer patients. However, the applicability of these new molecular classifications is limited because of several issues such as technological validation and cost. Further comparison with well-established clinical and pathological features is expected to accelerate clinical translation. In this review, we will focus on the data reported on molecular classification in the most common tumor types such as breast, colorectal and lung carcinoma, with special emphasis on recent data regarding tumor intrinsic subtypes. Likewise, we will review the potential applicability of these new classifications in the clinical routine.

3-D Deep Learning Approach for Remote Sensing Image Classification <=SEP=> Recently, a variety of approaches have been enriching the field of remote sensing (RS) image processing and analysis. Unfortunately, existing methods remain limited to the rich spatiospectral content of today’s large data sets. It would seem intriguing to resort to deep learning (DL)-based approaches at this stage with regard to their ability to offer accurate semantic interpretation of the data. However, the specificity introduced by the coexistence of spectral and spatial content in the RS data sets widens the scope of the challenges presented to adapt DL methods to these contexts. Therefore, the aim of this paper is first to explore the performance of DL architectures for the RS hyperspectral data set classification and second to introduce a new 3-D DL approach that enables a joint spectral and spatial information process. A set of 3-D schemes is proposed and evaluated. Experimental results based on well-known hyperspectral data sets demonstrate that the proposed method is able to achieve a better classification rate than state-of-the-art methods with lower computational costs.

Determination of differential leakage factors in electrical machines with non-symmetrical full and dead-coil windings <=SEP=> In this paper Görges polygons are used in conjunction with masses geometry to find an easy and affordable way to compute the differential leakage factor of non symmetrical full and dead coil winding. By following the traditional way, the use of the Ossanna's infinite series which has to be obviously truncated under the bound of a predetermined accuracy is mandatory. In the presented method no infinite series is instead required. An example is then shown and discussed to demonstrate practically the effectiveness of the proposed method.

NewsVallum: Semantics-Aware Text and Image Processing for Fake News Detection system <=SEP=> As a consequence of the social revolution we faced on the Web, news and information we daily enjoy may come from different and diverse sources which are not necessarily the traditional ones such as newspapers, either in their paper or online version, television, radio, etc. Everyone on the Web is allowed to produce and share news which can soon become viral if they follow the new media channels represented by social networks. This freedom in producing and sharing news comes with a counter-effect: the proliferation of fake news. Unfortunately, they can be very effective and may influence people and, more generally, the public opinion. We propose a combined approach of natural language and image processing that takes into account the semantics encoded within both text and images coming with news together with contextual information that may help in the classification of a news as fake or not.

Towards Know-how Mapping Using Goal Modeling <=SEP=> In organizing the knowledge in a field of study, it is common to use classification techniques to organize concepts and approaches along dimensions of interest. In technology domains, an advance often appears in the form of a new way or method for achieving an objective. This paper proposes to use goal modeling to map the means-ends knowledge (“know-how”) in a domain. A know-how map highlights the structure of recognized problems and known solutions in the domain, thus facilitating gap identification and prompting new research and innovation. We contrast the proposed goal-oriented approach with a claim-oriented approach, using Web Page Ranking as a sample domain.

Controlling Home Appliances Remotely through Voice Command <=SEP=> the main concern in systems development is the integration of technologies to increase customer satisfaction. Research presented in this paper focuses mainly in three things first to understand the speech or voice of user second is to control the home appliances through voice call and third is to finds intrusion in the house. The user can make a voice call in order to perform certain actions such as switching lights on/off, getting the status of any appliance etc. And when system finds intrusion it sends an alert voice message to preconfigured cell when the user is away from the place. The proposed system is implemented using voice Global System for Mobile Communications (GSM) and wireless technology based on .NET framework and Attention (AT) commands. Microsoft speech reorganization engine, speech SDK 5.1 is used to understand the voice command of user. As it is wireless so more cost effective and easy to use. The GSM technology used in system provide the everywhere access of the system for security. Experimental results show that the system is more secure and cost effective as compared to existing systems. We conclude that this system provides solution for the problems faced by home owner in daily life and make their life easy and comfortable by proposing cost effective and reliable solution. Keywords-component; Voice GSM; Voice message; radio friquencey (RF); AT commands.

RFID Coverage Extension Using Microstrip-Patch Antenna Array [Wireless Corner] <=SEP=> In this paper, a UHF-band 2 times 2 microstrip phased-array antenna is designed and implemented to extend the coverage of an RFID reader system. The phased-array antenna has four microstrip-patch antennas, three Wilkinson power dividers, and a transmission-line phase shifter. These are printed on a dielectric substrate with a dielectric constant of 4.5. The array has dimensions of 34 cm times 45 cm, operating at a frequency of 867 MHz, as specified in RFID Gen2 protocol European standards. The phased-array antenna has a measured directivity of 12.1 dB, and the main-beam direction can be steered to angles of plusmn 40deg, with a HPBW of 90deg. The phased-array antenna is used as the receiving antenna in a commercial reader system. Experimental results indicate that the coverage of the RFID system with the phased-array antenna is superior to the coverage with a conventional broader-beamwidth microstrip-patch antenna. The proposed system can also be used for a wireless positioning system.

N-Fold Inspection: A Requirements Analysis Technique <=SEP=> N-fold inspection uses traditional inspections of the user requirements document (URD) but replicates the inspection activities using N independent teams. A pilot study was conducted to explore the usefulness of N-fold inspection during requirements analysis. A comparison of N-fold inspection with other development techniques reveals that N-fold inspection is a cost-effective method for finding faults in the URD and may be a valid technique in the development of mission-critical software systems.

A Benchmark for Open Link Prediction <=SEP=> Knowledge graphs (KG) and open information extraction systems (OIE) both represent information by a set of (subject, relation, object)-triples. In KGs, arguments and relations are taken from a closed vocabulary, i.e., entities are disambiguated and relations are assumed to be semantically distinct. In OIE, arguments and relations are extracted from natural language text. There is no predefined or closed vocabulary, many different mentions may refer to the same entity, and relations can be semantically close but not equal, e.g. “visited by” and “frequently visited by”. The set of OIE triples can be viewed as an open knowledge graph (OKG). In this paper, we study the problem of open link prediction: Given a mention of an entity and an open relation (e.g., “A. Einstein” and “is a native of”), predict correct entity mentions (e.g., “Imperial Germany”) using solely the OKG. Models that aim to solve the open link prediction task sucessfully need to be able to reason about different entity mentions, as well as the relations between them, in a fully automatic, unsupervised way. As a benchmark for this task we design an OKG dataset, an evaluation protocol and present and evaluate a number of baseline models. In particular, we compare a token-based co-occurrence model, a non token-based link prediction model, and several token-based link prediction models. Our results indicate that the latter combination is beneficial.

Dioxin characterisation , formation and minimisation during municipal solid waste ( MSW ) incineration : review <=SEP=> The present review discusses the current views on methods to minimise dioxins, namely polychlorinated dibenzodioxins (PCDDs) and dibenzofurans (PCDFs), formation in MSW incineration systems. The structure of this group of compounds is discussed initially and then the toxic equivalence scale is presented for the most common isomers and congeners in the dioxin family. The current status on dioxin limits imposed in various countries and by various organisations is presented. A detailed analysis of the theories leading to dioxin formation in MSW incineration is given, since, this has been one of the most controversial areas of dioxin chemistry for the past 20 years. Three dioxin formation theories were considered possible for a long time; (i) from PCDD/PCDFs originally present in the furnace feedstock; (ii) from precursor compounds (foundation formatting molecules which could react rapidly with other groups in the system to form dioxins) in the MSW feed; (iii) from de novo synthesis of smaller, relatively innocuous chemical molecules combining together to form the dioxins. Methods (ii) and (iii) are based on heterogeneously catalysed reactions. Some researchers are considering possible homogeneous thermal reaction formation of dioxin. This review demonstrates that with the advanced modern MSW combustion systems, option (i) is a most unlikely route and also methods (ii) and (iii) are quite feasible. Based on thermodynamic and kinetic data in the literature, the rate and extent of the formation of dioxins and their precursors by certain mechanisms can definitely be contributing to routes (ii) and (iii). Since even the most advanced MSW combustion systems do not produce complete combustion, predominantly because of inadequate feed preparation and turbulence, some de novo synthesis of precursors can also take place. These ‘de novo precursors’ could be carried through the combustion unit adsorbed or absorbed on particulate material such as soot and dust, but also these precursors could be formed during the cooling process by heterogeneous catalytic reactions and go on to form dioxins. The maximum rate of formation of PCDD/PCDFs from both sources lies in the temperature range 300–400 ◦C. This knowledge of formation rates and mechanisms provides the basis of designing combustion systems. A two stage approach is adopted; firstly, system design to achieve complete combustion and minimise formation; secondly, end-of-pipe treatment systems to remove dioxins. In the first case, combustion temperature should be above 1000 ◦C, combustion residence time should be greater than 1 s, combustion chamber turbulence should be represented by a Reynolds number greater than 50,000, good MSW feed preparation and controlled feed rate are also critical. In the second category, very rapid gas cooling from 400 to 250 ◦C should be achieved, semi-dry lime scrubbing and Abbreviations:AC, activated carbon; ACSS, activated carbon scrubbing solution; APCD, air pollution control device; APME, Association of Plastics Manufacturers in Europe; ASME, American Society of Mechanical Engineers; BF, bag filter; BPM, best practical means; COT, UK Committee on Toxicology of Chemicals in Food, Consumer Products and Environment; CTZ, critical temperature zone; DOE, Department of the Environment, UK; DIAC, direct injec tion of activated carbon; DS, dry scrubber; DSI, dry sorbent injection; EADON, toxic equivalence factors proposed by Eadon method; EEC, European Economi c Community; EGB, electro granular bed; ESP, electrostatic precipitator; FF, fabric filter; FRG, Federal Republic of Germany; GCP, good combustion pr actice; HMIP, Her Majesty’s Inspectorate on Pollution, UK; HOC, hearth-oven coke; HRGC, high resolution gas chromatography; HRMS, high resolution mass spectrometry; IARC, International Agency for Research on Cancer; Kow, octanol-water partition coefficient; MSW, municipal solid waste; MSWI, municipal solid waste incinerator; NATO, Northern Atlantic Treaty Organisation; NOAEL, no observed adverse effect level; OCDD, octachlorinated dibenzodio xin; OCDF, octachlorinated dibenzofuran; PCB, polychlorinated biphenyls; PCCS, programmable computer control system; PCDD, polychlorinated dibenzodiox in; PCDF, polychlorinated dibenzofuran; PCP, pentachlorophenol; RDF, refuse derived fuel; SCR, selective catalytic reduction/reactor; SDA, spray dry abs orber; TALuft, Technische Airbildung Luft; TCDD, tetrachlorinated dibenzodioxin; TCDF, tetrachlorinated dibenzofuran; TDI, tolerable daily intake; TEF, toxi c equivalence factor; TEQ, toxic equivalence; USEPA, United States Environmental Protection Agency; WHO, World Health Organisation; WQ, water quench; WS, wet scrubber E-mail address:kemckayg@ust.hk (G. McKay). 1385-8947/02/$ – see front matter © 2002 Elsevier Science B.V. All rights reserved. PII: S1385-8947(01)00228-5 344 G. McKay / Chemical Engineering Journal 86 (2002) 343–368 bag filtration coupled with activated carbon injection adsorption as end-of-pipe treatments can all play a role in prevention or minimisation of dioxins in the final flue gas emission to the atmosphere. © 2002 Elsevier Science B.V. All rights reserved.

Compressive sensing <=SEP=> 1 Scope The Shannon/Nyquist sampling theorem tells us that in order to not lose information when uniformly sampling a signal we must sample at least two times faster than its bandwidth. In many applications, including digital image and video cameras, the Nyquist rate can be so high that we end up with too many samples and must compress in order to store or transmit them. In other applications, including imaging systems (medical scanners, radars) and high-speed analog-to-digital converters, increasing the sampling rate or density beyond the current state-of-the-art is very expensive. In this lecture, we will learn about a new technique that tackles these issues using compressive sensing [1, 2]. We will replace the conventional sampling and reconstruction operations with a more general linear measurement scheme coupled with an optimization in order to acquire certain kinds of signals at a rate significantly below Nyquist.

Formal Specification with the Java Modeling Language <=SEP=> This text is a general, self contained, and tool independent introduction into the Java Modeling Language, JML. It appears in a book about the KeY approach and tool, because JML is the dominating starting point of KeY style Java verification. However, this chapter does not depend on KeY, nor any other specific tool, nor on any specific verification methodology. With this text, the authors aim to provide, for the time being, the definitive, general JML tutorial. Other chapters in this book discuss the particular usage of JML in KeY style verification.1 In this chapter, however, we only refer to KeY in very few places, without relying on it. This introduction is written for all readers with an interest in formal specification of software in general, and anyone who wants to learn about the JML approach to specification in particular. A preliminary version of this chapter appeared as a technical report [Huisman et al., 2014].

Low complexity photo sensor dead pixel detection algorithm <=SEP=> Although the number of pixels in image sensors is increasing exponentially, production techniques have only been able to linearly reduce the probability that a pixel will be defective. The result is a rapidly increasing probability that a sensor will contain one or more defective pixels. The defect pixel detection and defect pixel correction are operated separately but the former must employ before the latter is in use. Traditional detection scheme, which finds the defect pixels during manufacturing, is not able to discover the spread defect pixels years late. Consequently, the lifetime and robust defect pixel detection technique, which identifies the fault pixels when camera is in use, is more practical and developed. The paper presents a two stages dead pixel detection technique without complicated mathematic computations so that the embedded devices can easily implement it. Using six dead pixel types are tested and the experimental result indicates that it can be accelerated more than four times the detection time.