Discovery learning approach to classic electrical machines principles

This paper aims at presenting the concept of Socratic interactions and discovery learning of classic electrical machines principles. The theories of electrical machines are by nature quite boring and abstract although there are a lot of experiments supported the theories. Traditional, students learnt the subject by drill and practice approach with standard textbooks. In the past two decades, computer is no doubt recognized to be the educational tool. The so-called “interactive” approach is applied to the learning process. Most of this approach applied to various subjects in different levels is mainly based on drill and practice. However, few packages are developed for electrical machine subject. In this paper, two different approaches “Rote Learning” and “Discovery Learning” applied to the interactive computer aided learning package of classic electric machine principles are discussed. Design of a discovery learning approach will also be presented

An Image-Based Measure for Evaluation of Mathematical Expression Recognition

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-38628-2_81Mathematical expression recognition is an active research field that is related to document image analysis and typesetting. In this study, we present a novel global performance evaluation measure for mathematical expression recognition based on image matching. Using an image representation for evaluation tries to overcome the representation ambiguity as human beings do. The results of a recent competition were used to perform several experiments in order to analyze the benefits and drawbacks of this measure.This work was partially supported by the Spanish MEC under the STraDA research project (TIN2012-37475-C02-01), the MITTRAL (TIN2009-14633-C03-01) project, the FPU grant (AP2009-4363), by the Generalitat Valenciana under the grant Prometeo/2009/014, and through the EU 7th Framework Programme grant tranScriptorium (Ref: 600707)Álvaro Muñoz, F.; Sánchez Peiró, JA.; Benedí Ruiz, JM. (2013). An Image-Based Measure for Evaluation of Mathematical Expression Recognition. En Pattern Recognition and Image Analysis. Springer. 682-690. https://doi.org/10.1007/978-3-642-38628-2_81S682690Álvaro, F., Sánchez, J.A., Benedí, J.M.: Unbiased evaluation of handwritten mathematical expression recognition. In: Proceedings of ICFHR, Italy, pp. 181–186 (2012)Chan, K.F., Yeung, D.Y.: Error detection, error correction and performance evaluation in on-line mathematical expression recognition. Pattern Recognition 34(8), 1671–1684 (2001)Chou, P.A.: Recognition of equations using a two-dimensional stochastic context-free grammar. In: Pearlman, W.A. (ed.) Visual Communications and Image Processing IV. SPIE Proceedings Series, vol. 1199, pp. 852–863 (1989)Garain, U., Chaudhuri, B.B.: A corpus for OCR research on mathematical expressions. Int. Journal on Document Analysis and Recognition 7, 241–259 (2005)Keysers, D., Deselaers, T., Gollan, C., Ney, H.: Deformation models for image recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence 29(8), 1422–1435 (2007)Mouchére, H., Viard-Gaudin, C., Garain, U., Kim, D.H., Kim, J.H.: ICFHR 2012 – Competition on Recognition of On-line Mathematical Expressions (CROHME 2012). In: Proceedings of ICFHR, Italy, pp. 807–812 (2012)Otsu, N.: A Threshold Selection Method from Gray-level Histograms. IEEE Transactions on Systems, Man and Cybernetics 9(1), 62–66 (1979)Sain, K., Dasgupta, A., Garain, U.: EMERS: a tree matching-based performance evaluation of mathematical expression recognition system. International Journal of Document Analysis and Recognition (2010)Toselli, A.H., Juan, A., Vidal, E.: Spontaneous Handwriting Recognition and Classification. In: Proceedings of ICPR, England, UK, pp. 433–436 (2004)Zanibbi, R., Blostein, D., Cordy, J.R.: Recognizing mathematical expressions using tree transformation. IEEE Trans. on Pattern Analysis and Machine Intelligence 24(11), 1–13 (2002)Zanibbi, R., Pillay, A., Mouchere, H., Viard-Gaudin, C., Blostein, D.: Stroke-based performance metrics for handwritten mathematical expressions. In: Proceedings of ICDAR, pp. 334–338 (2011

Predicting dementia diagnosis from cognitive footprints in electronic health records: a case-control study protocol

INTRODUCTION: Dementia is a group of disabling disorders that can be devastating for persons living with it and for their families. Data-informed decision-making strategies to identify individuals at high risk of dementia are essential to facilitate large-scale prevention and early intervention. This population-based case-control study aims to develop and validate a clinical algorithm for predicting dementia diagnosis, based on the cognitive footprint in personal and medical history. METHODS AND ANALYSIS: We will use territory-wide electronic health records from the Clinical Data Analysis and Reporting System (CDARS) in Hong Kong between 1 January 2001 and 31 December 2018. All individuals who were at least 65 years old by the end of 2018 will be identified from CDARS. A random sample of control individuals who did not receive any diagnosis of dementia will be matched with those who did receive such a diagnosis by age, gender and index date with 1:1 ratio. Exposure to potential protective/risk factors will be included in both conventional logistic regression and machine-learning models. Established risk factors of interest will include diabetes mellitus, midlife hypertension, midlife obesity, depression, head injuries and low education. Exploratory risk factors will include vascular disease, infectious disease and medication. The prediction accuracy of several state-of-the-art machine-learning algorithms will be compared. ETHICS AND DISSEMINATION: This study was approved by Institutional Review Board of The University of Hong Kong/Hospital Authority Hong Kong West Cluster (UW 18-225). Patients' records are anonymised to protect privacy. Study results will be disseminated through peer-reviewed publications. Codes of the resulted dementia risk prediction algorithm will be made publicly available at the website of the Tools to Inform Policy: Chinese Communities' Action in Response to Dementia project (https://www.tip-card.hku.hk/)

Flat histogram simulation of lattice polymer systems

We demonstrate the use of a new algorithm called the Flat Histogram sampling algorithm for the simulation of lattice polymer systems. Thermodynamics properties, such as average energy or entropy and other physical quantities such as end-to-end distance or radius of gyration can be easily calculated using this method. Ground-state energy can also be determined. We also explore the accuracy and limitations of this method. Key words: Monte Carlo algorithms, flat histogram sampling, HP model, lattice polymer systemsComment: 7 RevTeX two-column page

First ancient mitochondrial human genome from a prepastoralist Southern African

The oldest contemporary human mitochondrial lineages arose in Africa. The earliest divergent extant maternal offshoot, namely haplogroup L0d, is represented by click-­‐speaking forager peoples of Southern Africa. Broadly defined as Khoesan, contemporary Khoesan are today largely restricted to the semi-­‐ desert regions of Namibia and Botswana, while archeological, historical and genetic evidence promotes a once broader southerly dispersal of click-­‐speaking peoples including southward migrating pastoralists and indigenous marine-­‐foragers. Today extinct, no genetic data has been recovered from the indigenous peoples that once sustained life along the southern coastal waters of Africa pre-­‐pastoral arrival. In this study we generate a complete mitochondrial genome from a 2,330 year old male skeleton, confirmed via osteological and archeological analysis as practicing a marine-­‐based forager existence. The ancient mtDNA represents a new L0d2c lineage (L0d2c1c) that is today, unlike its Khoe-­‐language based sister-­‐ clades (L0d2c1a and L0d2c1b) most closely related to contemporary indigenous San-­‐speakers (specifically Ju). Providing the first genomic evidence that pre-­‐pastoral Southern African marine foragers carried the earliest diverged maternal modern human lineages, this study emphasizes the significance of Southern African archeological remains in defining early modern human origins.J. Craig Venter Family Foundation, La Jolla, CA, U.S.A. and the Max Planck Society (within the laboratory of Svante Pääbo).http://gbe.oxfordjournals.orghb201

Structure optimization in an off-lattice protein model

We study an off-lattice protein toy model with two species of monomers interacting through modified Lennard-Jones interactions. Low energy configurations are optimized using the pruned-enriched-Rosenbluth method (PERM), hitherto employed to native state searches only for off lattice models. For 2 dimensions we found states with lower energy than previously proposed putative ground states, for all chain lengths $\ge 13$. This indicates that PERM has the potential to produce native states also for more realistic protein models. For $d=3$, where no published ground states exist, we present some putative lowest energy states for future comparison with other methods.Comment: 4 pages, 2 figure

Efficacy and tolerability of trastuzumab emtansine in advanced human epidermal growth factor receptor 2–positive breast cancer

© 2018, Hong Kong Academy of Medicine Press. All rights reserved. Introduction: The management of human epidermal growth factor receptor 2 (HER2)–positive breast cancer has changed dramatically with the introduction and widespread use of HER2-targeted therapies. There is, however, relatively limited real-world information about the effectiveness and safety of trastuzumab emtansine (T-DM1) in Hong Kong Chinese patients. We assessed the efficacy and toxicity profiles among local patients with HER2-positive advanced breast cancer who had received T-DM1 therapy in the second-line setting and beyond. Methods: This retrospective study involved five local centres that provide service for over 80% of the breast cancer population in Hong Kong. The study period was from December 2013 to December 2015. Patients were included if they had recurrent or metastatic histologically confirmed HER2+ breast cancer who had progressed after at least one line of anti-HER2 therapy including trastuzumab. Patients were excluded if they received T-DM1 as first-line treatment for recurrent or metastatic HER2+ breast cancer. Patient charts including biochemical and haematological profiles were reviewed for background information, T-DM1 response, and toxicity data. Adverse events were documented during chemotherapy and 28 days after the last dose of medication. Results: Among 37 patients being included in this study, 28 (75.7%) had two or more lines of anti-HER2 agents and 26 (70.3%) had received two or more lines of palliative chemotherapy. Response assessment revealed that three (8.1%) patients had a complete response, eight (21.6%) a partial response, 11 (29.7%) a stable disease, and 12 (32.4%) a progressive disease; three patients could not be assessed. The median duration of response was 17.3 (95% confidence interval, 8.4-24.8) months. The clinical benefit rate (complete response + partial response + stable disease, ≥12 weeks) was 37.8% (95% confidence interval, 22.2%-53.5%). The median progression-free survival was 6.0 (95% confidence interval, 3.3-9.8) months and the median overall survival had not been reached by the data cut-off date. Grade 3 or 4 toxicities included thrombocytopaenia (13.5%), raised alanine transaminase (8.1%), anaemia (5.4%), and hypokalaemia (2.7%). No patient died as a result of toxicities. Conclusions: In patients with HER2-positive advanced breast cancer who have been heavily pretreated with anti-HER2 agents and cytotoxic chemotherapy, T-DM1 is well tolerated and provided a meaningful progression-free survival of 6 months and an overall survival that has not been reached. Further studies to identify appropriate patient subgroups are warranted.Link_to_subscribed_fulltex

A hybrid noise suppression filter for accuracy enhancement of commercial speech recognizers in varying noisy conditions

Commercial speech recognizers have made possible many speech control applications such as wheelchair, tone-phone, multifunctional robotic arms and remote controls, for the disabled and paraplegic. However, they have a limitation in common in that recognition errors are likely to be produced when background noise surrounds the spoken command, thereby creating potential dangers for the disabled if recognition errors exist in the control systems. In this paper, a hybrid noise suppression filter is proposed to inter-face with the commercial speech recognizers in order to enhance the recognition accuracy under variant noisy conditions. It intends to decrease the recognition errors when the commercial speech recognizers are working under a noisy environment. It is based on a sigmoid function which can effectively enhance noisy speech using simple computational operations, while a robust estimator based on an adaptive-network-based fuzzy inference system is used to determine the appropriate operational parameters for the sigmoid function in order to produce effective speech enhancement under variant noisy conditions.The proposed hybrid noise suppression filter has the following advantages for commercial speech recognizers: (i) it is not possible to tune the inbuilt parameters on the commercial speech recognizers in order to obtain better accuracy; (ii) existing noise suppression filters are too complicated to be implemented for real-time speech recognition; and (iii) existing sigmoid function based filters can operate only in a single-noisy condition, but not under varying noisy conditions. The performance of the hybrid noise suppression filter was evaluated by interfacing it with a commercial speech recognizer, commonly used in electronic products. Experimental results show that improvement in terms of recognition accuracy and computational time can be achieved by the hybrid noise suppression filter when the commercial recognizer is working under various noisy environments in factories