Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

The European Position Paper on Rhinosinusitis and Nasal Polyps 2020 is the update of similar evidence based position papers published in 2005 and 2007 and 2012. The core objective of the EPOS2020 guideline is to provide revised, up-to-date and clear evidence-based recommendations and integrated care pathways in ARS and CRS. EPOS2020 provides an update on the literature published and studies undertaken in the eight years since the EPOS2012 position paper was published and addresses areas not extensively covered in EPOS2012 such as paediatric CRS and sinus surgery. EPOS2020 also involves new stakeholders, including pharmacists and patients, and addresses new target users who have become more involved in the management and treatment of rhinosinusitis since the publication of the last EPOS document, including pharmacists, nurses, specialised care givers and indeed patients themselves, who employ increasing self-management of their condition using over the counter treatments. The document provides suggestions for future research in this area and offers updated guidance for definitions and outcome measurements in research in different settings. EPOS2020 contains chapters on definitions and classification where we have defined a large number of terms and indicated preferred terms. A new classification of CRS into primary and secondary CRS and further division into localized and diffuse disease, based on anatomic distribution is proposed. There are extensive chapters on epidemiology and predisposing factors, inflammatory mechanisms, (differential) diagnosis of facial pain, allergic rhinitis, genetics, cystic fibrosis, aspirin exacerbated respiratory disease, immunodeficiencies, allergic fungal rhinosinusitis and the relationship between upper and lower airways. The chapters on paediatric acute and chronic rhinosinusitis are totally rewritten. All available evidence for the management of acute rhinosinusitis and chronic rhinosinusitis with or without nasal polyps in adults and children is systematically reviewed and integrated care pathways based on the evidence are proposed. Despite considerable increases in the amount of quality publications in recent years, a large number of practical clinical questions remain. It was agreed that the best way to address these was to conduct a Delphi exercise . The results have been integrated into the respective sections. Last but not least, advice for patients and pharmacists and a new list of research needs are included. The full document can be downloaded for free on the website of this journal: http://www.rhinologyjournal.com.

/pdf/european-position-paper-on-rhinosinusitis-and-nasal-polyps-mj734vsl7p.pdf

European Position Paper on Rhinosinusitis and Nasal Polyps 2020

Transfer learning aims at improving the performance of target learners on target domains by transferring the knowledge contained in different but related source domains. In this way, the dependence on a large number of target-domain data can be reduced for constructing target learners. Due to the wide application prospects, transfer learning has become a popular and promising area in machine learning. Although there are already some valuable and impressive surveys on transfer learning, these surveys introduce approaches in a relatively isolated way and lack the recent advances in transfer learning. Due to the rapid expansion of the transfer learning area, it is both necessary and challenging to comprehensively review the relevant studies. This survey attempts to connect and systematize the existing transfer learning research studies, as well as to summarize and interpret the mechanisms and the strategies of transfer learning in a comprehensive way, which may help readers have a better understanding of the current research status and ideas. Unlike previous surveys, this survey article reviews more than 40 representative transfer learning approaches, especially homogeneous transfer learning approaches, from the perspectives of data and model. The applications of transfer learning are also briefly introduced. In order to show the performance of different transfer learning models, over 20 representative transfer learning models are used for experiments. The models are performed on three different data sets, that is, Amazon Reviews, Reuters-21578, and Office-31, and the experimental results demonstrate the importance of selecting appropriate transfer learning models for different applications in practice.

A Comprehensive Survey on Transfer Learning

Independent Component Analysis.

As the operational domain of autonomous vehicles expands, encountering occlusions during navigation becomes unavoidable. Most of the existing research on occlusion-aware motion planning focuses only on the longitudinal motion of the ego vehicle and neglects its lateral motion, resulting in output motion that can be overly conservative. This paper proposes a motion planner capable of actively adjusting the ego vehicle’s lateral position to minimize occlusions. The proposed planner is applicable in various scenarios and can function under perception uncertainty. This work also extends our previously proposed 3D visibility estimation approach for addressing occlusions caused by objects which are not present in HD maps. The proposed planner first generates candidate trajectories. The current and future visibility of each trajectory is then estimated using live LiDAR data and HD maps. These estimated visibilities are converted into visibility costs, which are then used to determine the optimal output trajectory in conjunction with other planning costs. The proposed planner is tested in three scenarios using the CARLA simulator: an occluded T-junction crossing, turning at a low-visibility corner and preparing to pass a parked vehicle, using live localization and object detection results. The experimental results reveal that the proposed planner allows the ego vehicle to minimize occlusions by diverging from the center of the lane and, consequently, to discover occluded vehicles earlier than a baseline planner in most situations. Moreover, occlusions caused by a parked vehicle not present in the HD maps were estimated correctly using our extended visibility estimation method.

https://ieeexplore.ieee.org/ielx7/6287639/6514899/09784942.pdf

Occlusion-aware Motion Planning with Visibility Maximization via Active Lateral Position Adjustment

A prototype of a Japanese-Korean realtime speech translation system.

PURPOSE: To decrease the number of collation words and to make vocabulary larger by previously determining the backward phoneme chain score of inputted voices, evaluating the results of word collation and the phoneme chain score of the top of the words and excluding a part of the predicted word groups CONSTITUTION: The results 1a of the acoustic analyses of the input voices are stored in a storage section 3 for the results of the sound analyses A switching section 5 first sends the results of the analyses in the same order as the order of the inputted voices to a time base inversion section 7 and sends the input voices to a word collation section 25 after the end of the calculation of the backward phoneme chain scores This time base inversion section 7 inverts the time base of the results of the analyses A phoneme chain pattern collation section 9 collates the results 7a of the backward acoustic analyses and the respective phoneme chain patterns and successively stores the backward phoneme chain scores into a storage section 13 A collated word determining section 19 evaluates the goodness of the hit of the collation by the backward phoneme chain scores 13a and the results 25a of the word collation given from the word collation section 25 and sends only the predicted words of the high evaluation to a collated word standard pattern forming section 21 The rest are excluded from the object for collation COPYRIGHT: (C)1995,JPO

Continuous voice recognition method and device

We propose a method of detecting the task incompletion in spoken dialog systems using N-gram-based dialog features. We used a database created during a field test in which inexperienced users used a client-server music retrieval system with a spoken dialog interface on their own PCs. The dialog for a music retrieval task consisted of a sequence of user and system tags that related their utterances and behaviors. The dialogs were manually classified into two classes: completed and uncompleted music retrieval tasks. We then detected dialogs that did not complete the task using a Support Vector Machine with N-gram feature vectors and interaction parameters trained using manually classified dialogs. Off-line and on-line detection experiments were conducted on a large amount of real data, and the results show that our proposed method achieved good classification performance.

On-line detection of task incompletion for spoken dialog systems using utterance and behavior tag N-gram vectors

Since time precision in finding delays between channels is one of the most important issues in estimating direction of arrival (DOA) from multichannel signals, a zero‐crossing analysis is proposed as a fine and robust time‐domain preprocessing for the DOA finding. As for the preliminary evaluation of noise robustness using zero‐crossing information, how the zero‐crossing points are affected is investigated, i.e., how far the zero‐crossing points move from the original points, under the presence of noise. For test speech, a 48‐kHz sampling of a male voice (upsampled from an 8‐kHz signal) is used after an adding machine generated white noise so that the SNR of the signal becomes 0 to 20 dB. The robustness of the zero‐crossing analysis can be concluded from the summarized results: (1) the mean value of the distance is less than 100 μs throughout the SNR; and (2) the standard deviation of the distribution becomes large as the SNR decreases; the standard deviation is less than 0.125 even under the condition of 0 dB SNR.

Kazuya Takeda

Papers

Occlusion-aware Motion Planning with Visibility Maximization via Active Lateral Position Adjustment

A prototype of a Japanese-Korean realtime speech translation system.

Continuous voice recognition method and device

On-line detection of task incompletion for spoken dialog systems using utterance and behavior tag N-gram vectors

On the use of the zero‐crossing analysis for multi‐channel signal processing