Miracle-dz/UniFAR-FTUs huggingface dataset:
A System for Offline Cursive Handwritten Word Recognition

Cursive handwriting recognition is a difficult problem because of large variations in handwritten words as well as overlaps and interconnections between neighboring characters. In this thesis we introduce a new approach to this problem, called Hidden Markov Model with Multiple Observation Sequences (HMMMOS). A preprocessor extracts each word from a scanned-in document image and divides it into segments. A Neural Network (NN) classifier then finds the likelihoods of each possible character class given the segments and combinations of segments. These likelihoods, along with statistics computed from a lexicon, are used as input to a dynamic programming algorithm which recognizes the entire word. The dynamic programming algorithm can be viewed as a modified Viterbi algorithm for a Hidden Markov Model (HMM). Three types of Neural Networks are tried: a recurrent network, a Multilayer Perceptron (MLP), and a Hierarchical Mixture of Experts (HME) [Jordan & Jacobs 1994]. As an extension, the Viterbi algorithm for the HMM is implemented for a multiprocessor environment to speed up recognition. Thesis Supervisor: Michael Jordan Title: Professor, Department of Brain and Cognitive Science Acknowledgments This thesis would have been impossible without the help of my mentor at IBM Almaden Research Center, Dr. Jianchiang Mao. With his deep knowledge and keen insight about the topic, he guided me and served as an inspiration throughout the project. He taught me a lot about the process of doing research. And most importantly, he encouraged me to keep my focus and work hard every day. I salute my thesis advisor, Prof. Michael Jordan, for his patience, input, and support. Many colleagues at IBM made my task easier. Prasun Sinha gave very valuable input on my thesis drafts, and helped me at various stages in the project. My manager, K. M. Mohiuddin, was kind and always showed interest in my well-being and progress. An office-mate, Mary Mandl was ajoy to have around. Others who gave encouragement and a helping hand are Sandeep Gopisetty, Raymond Lorrie, Andras Kornai, Tom Truong, and Peter DeSouza. Special thanks to Andras and Mao for giving me rides from work when I missed the shuttle. I thank a friend from MIT, Beethoven Cheng, for helping me edit my drafts for grammar and style. I am grateful to Allen Luniewsky, the 6-A liaison between IBM and MIT, and Prof. Jerome Saltzer, the 6-A advisor for IBM, who made sure I was plugged in and ready to work on my thesis. Hurrah to my cheering squad of friends: Tom and Jane Letterman, Luong Tran, Jay Lulla, Yee Chuan Koh, and Chung-hsiu Ma. Finally, I thank my parents, Perfecto and Carmencita Abayan, and my sister Maureen, for always being there for me. I dedicate this work to them.
Opportunities and Challenges for Constraint Programming

Constraint programming has become an important technology for solving hard combinatorial problems in a diverse range of application domains. It has its roots in artificial intelligence, mathematical programming, op- erations research, and programming languages. This paper gives a perspective on where constraint programming is today, and discusses a number of opportunities and challenges that could provide focus for the research community into the future.
Engagement platforms: The role of emotions in fostering customer engagement and brand image in interactive media

Purpose The purpose of this paper is to explore the role of emotions in developing customer engagement and brand image during virtual service interactions. The authors explore the concept of engagement platforms (EPs) and how their extrinsic characteristics or cues (i.e. C2C interactions–and personalization-related cues) originate both non-transactional (i.e. customer engagement and brand image) and transactional (i.e. purchase intentions) responses. Specifically, the authors propose that customer emotions (i.e. pleasure, arousal and dominance) mediate the influence of EP cues on customer responses. The authors also analyze how the engagement developed during interactions in EPs contributes to brand image perceptions and the effect of these two concepts on purchase intentions. Design/methodology/approach Building on servicescapes and stimulus-organism-response theories, the present paper carries out two studies. Study 1 adopts an experimental approach to explore C2C interactions–and personalization-related cues. Study 2 focusses on the importance of customer emotions to foster engagement and brand image, and also analyzes their effect on purchase intentions. It employs structural equations modeling techniques. Both studies analyze the effect of customer engagement on brand image. Findings Findings corroborate that, during interactions in the platform, customer engagement with the firm influences brand image. Moreover, the pleasure and arousal experienced by customers influence their engagement while dominance modifies brand image. Finally, customer engagement and brand image have a positive effect on purchase behavior. Research limitations/implications This paper contributes to research demonstrating the key role of emotions in interactions with EPs. The authors demonstrate the importance of fostering pleasant and arousing experiences to enhance the level of customer engagement with the firm in first interactions. Dominance constitutes a key dimension to improve brand image in EPs. Finally, the research demonstrates that engagement develops customers’ transactional behaviors and not only non-transactional ones, as seen in previous literature. Originality/value In digital worlds, EPs emerge as touch points beyond purchase that allow individuals to integrate resources and co-create value between them and with the firm. Despite the interest of BCPs, few works have analyzed how interactions with these platforms and the elicited emotions contribute to developing customer engagement and brand image, key factors for understanding customer participation and behavior in interactive media.
Comparison of Diabetes Risk Score Estimates and Cardiometabolic Risk Profiles in a Middle-Aged Irish Population

Background To compare diabetes risk assessment tools in estimating risk of developing type 2 diabetes (T2DM) and to evaluate cardiometabolic risk profiles in a middle-aged Irish population. Methods Future risk of developing T2DM was estimated using 7 risk scores, including clinical measures with or without anthropometric, biological and lifestyle data, in the cross-sectional Mitchelstown cohort of 2,047 middle-aged men and women. Cardiometabolic phenotypes including markers of glucose metabolism, inflammatory and lipid profiles were determined. Results Estimates of subjects at risk for developing T2DM varied considerably according to the risk assessment tool used (0.3% to 20%), with higher proportions of males at risk (0–29.2% vs. 0.1–13.4%, for men and women, respectively). Extrapolated to the Irish population of similar age, the overall number of adults at high risk of developing T2DM ranges from 3,378 to 236,632. Numbers of non-optimal metabolic features were generally greater among those at high risk of developing T2DM. However, cardiometabolic profile characterisation revealed that only those classified at high risk by the Griffin (UK Cambridge) score displayed a more pro-inflammatory, obese, hypertensive, dysglycaemic and insulin resistant metabolic phenotype. Conclusions Most diabetes risk scores examined offer limited ability to identify subjects with metabolic abnormalities and at risk of developing T2DM. Our results highlight the need to validate diabetes risk scoring tools for each population studied and the potential for developing an Irish diabetes risk score, which may help to promote self awareness and identify high risk individuals and diabetes hot spots for targeted public health interventions.
Enhancing Information Retrieval with Adapted Word Embedding

Recent developments on word embedding provide a novel source of information for term-to-term similarity. A recurring question now is whether the provided term associations can be properly integrated in the traditional information retrieval models while preserving their robustness and effectiveness. In this paper, we propose addressing the question of combining the term-to-term similarity of word embedding with IR models. The retrieval models in the approach are enhanced by altering the basic components of document retrieval, i.e. term frequency (tf) and document frequency (df). In addition, we target the study of the meaning of the term relatedness of word embedding models and its applicability in IR. This research topic consists of first explore of reliable similarity thresholds of word embedding vectors to indicate ? related terms? and second, identification of the linguistic types of the terms relatedness.
Between practices and demands: ambiguities, controversies and constraints in the emergence of active citizenship in Turkey

Abstract This article discusses the emergence of active citizenship in Turkey in the light of two working definitions that provide different outcomes in terms of research objectives and aims. On the one side, we define active citizenship as a practice stimulated by public institutions through public policy with the aim of promoting civic and political engagement in order to shape participatory policy processes and ultimately improve the democratic bases of policy-making. On the other side, we define active citizenship as a demand, which becomes particularly important where the civil society expresses certain claims through different means using both traditional and alternative channels of mobilization. In our discussion, we have examined different macro-processes and macro-events that have been key in bringing about different formulations of active citizenship. Using a case study method – where we overview different contextual elements/dynamics that bring to the fore various elements of civic and political engagement and civic and political participation during the past 15 years – we argue that, in a context where the expression of active citizenship is volatile and constrained, further research should take into account different top-down and bottom-up dynamics that bring about different challenges for the study of this subject in Turkey.
Modular Inversion Hidden Number Problem - Correction and Improvements

The Modular Inversion Hidden Number Problem (MIHNP) was introduced by Boneh, Halevi and Howgrave-Graham in Asiacrypt 2001 (BHH’01). They provided two heuristics in Method I, two-third of the output bits are required to solve the problem, whereas the more efficient heuristic (Method II) requires only one-third of the bits of the output. After more than a decade, here we identify that the claim in Method II is actually not correct and a detailed calculation justifies that this method too requires two-third of the bits of the output, contrary to the claim in BHH’01. Further, we show that using the same relations as in Boneh et al., one can reconstruct the lattice so that the problem can be heuristically solved by the knowledge of five-eighth of the bits. Finally, we could accumulate additional relations to solve the problem heuristically with only half of the output bits in asymptotic sense. Experimental results support the claim corresponding to our heuristics.
Adaptive Update Policy for Proactive Management of Deadline Miss Ratio and Data Freshness in Real-Time Database Models

Important applications, like e-commerce, online stock trading, traffic control demand real-time data services. Conventional database perform poor at these applications. A database for real-time data services has to support timing constraints and temporal consistency in addition to supporting characteristics of a conventional database system. In other words, it is desirable to execute transactions within its deadline using updated data reflecting the current world status. In order to achieve these objectives, the Quality of Service (QoS) metrics like miss ratio, data freshness, perceived freshness and Quality of Data (QoD) management schemes along with architectures for effective QoS management are introduced in Literature. These architectures accommodate the unpredictable change in user transactions and maintain QoS metrics by changing the update pattern of data items, which are periodically updated to reflect the real world status. In this study, we present architecture with an improved update policy and propose an algorithm to change the update pattern in such a manner that the system is able to maintain QoS metrics even under busty traffic conditions. The simulation results show that the proposed model can keep QoS metrics, like miss ratio and perceived freshness within limits under busty traffic conditions [1].
HDL Implementation of Low Density Parity Check ( LDPC ) Decoder

AbstractLow-Density Parity-Check (LDPC) codes are one of the most promising error-correcting codes approaching Shannon capacity and have been adopted in many applications. These codes offer huge advantages in terms of coding gain, throughput and power dissipation. Error correction algorithms are often implemented in hardware for fast processing to meet the real-time needs of communication systems. However hardware implementation of LDPC decoders using traditional Hardware Description Language (HDL) based approach is a complex and time consuming task. In this paper HDL Implementation of Low Density Parity Check Decoder architecture is presented with different rates i.e. 1/2, 2/3, 3/4, 4/7, 8/9, 9/10 and variable data lengths i.e. 8, 16, 32, 64, 128, 256 bits and consequent changeable precision factor.
A New Method To Monitor Airborne Inoculum of the Fungal Plant Pathogens Mycosphaerella brassicicola andBotrytis cinerea

ABSTRACT We describe a new microtiter immunospore trapping device (MTIST device) that uses a suction system to directly trap air particulates by impaction in microtiter wells. This device can be used for rapid detection and immunoquantification of ascospores ofMycosphaerella brassicicola and conidia of Botrytis cinerea by an enzyme-linked immunosorbent assay (ELISA) under controlled environmental conditions. For ascospores ofM. brassicicola correlation coefficients (r2) of 0.943 and 0.9514 were observed for the number of MTIST device-impacted ascospores per microtiter well and the absorbance values determined by ELISA, respectively. These values were not affected when a mixed fungal spore population was used. There was a relationship between the number of MTIST device-trapped ascospores of M. brassicicola per liter of air sampled and the amount of disease expressed on exposed plants ofBrassica oleracea (Brussels sprouts). Similarly, when the MTIST device was used to trap conidia of B. cinerea, a correlation coefficient of 0.8797 was obtained for the absorbance values generated by the ELISA and the observed number of conidia per microtiter well. The relative collection efficiency of the MTIST device in controlled plant growth chambers with limited airflow was 1.7 times greater than the relative collection efficiency of a Burkard 7-day volumetric spore trap for collection of M. brassicicola ascospores. The MTIST device can be used to rapidly differentiate, determine, and accurately quantify target organisms in a microflora. The MTIST device is a portable, robust, inexpensive system that can be used to perform multiple tests in a single sampling period, and it should be useful for monitoring airborne particulates and microorganisms in a range of environments.
Phase partitioning and volatility of secondary organic aerosol components formed from-pinene ozonolysis and OH oxidation : the importance of accretion products and Citation

We measured a large suite of gasand particlephase multi-functional organic compounds with a Filter Inlet for Gases and AEROsols (FIGAERO) coupled to a highresolution time-of-flight chemical ionization mass spectrometer (HR-ToF-CIMS) developed at the University of Washington. The instrument was deployed on environmental simulation chambers to study monoterpene oxidation as a secondary organic aerosol (SOA) source. We focus here on results from experiments utilizing an ionization method most selective towards acids (acetate negative ion proton transfer), but our conclusions are based on more general physical and chemical properties of the SOA. Hundreds of compounds were observed in both gas and particle phases, the latter being detected by temperature-programmed thermal desorption of collected particles. Particulate organic compounds detected by the FIGAERO–HR-ToF-CIMS are highly correlated with, and explain at least 25–50 % of, the organic aerosol mass measured by an Aerodyne aerosol mass spectrometer (AMS). Reproducible multi-modal structures in the thermograms for individual compounds of a given elemental composition reveal a significant SOA mass contribution from high molecular weight organics and/or oligomers (i.e., multiphase accretion reaction products). Approximately 50 % of the HR-ToF-CIMS particle-phase mass is associated with compounds having effective vapor pressures 4 or more orders of magnitude lower than commonly measured monoterpene oxidation products. The relative importance of these accretion-type and other extremely low volatility products appears to vary with photochemical conditions. We present a desorption-temperature-based framework for apportionment of thermogram signals into volatility bins. The volatilitybased apportionment greatly improves agreement between measured and modeled gas-particle partitioning for select major and minor components of the SOA, consistent with thermal decomposition during desorption causing the conversion of lower volatility components into the detected higher volatility compounds. Published by Copernicus Publications on behalf of the European Geosciences Union. 7766 F. D. Lopez-Hilfiker et al.: Importance of accretion products and other low volatility compounds
The Impact of Instrument-Specific Musical Training on Rhythm Perception and Production

Studies comparing musicians and non-musicians have shown that musical training can improve rhythmic perception and production. These findings tell us that training can result in rhythm processing advantages, but they do not tell us whether practicing a particular instrument could lead to specific effects on rhythm perception or production. The current study used a battery of four rhythm perception and production tasks that were designed to test both higher- and lower-level aspects of rhythm processing. Four groups of musicians (drummers, singers, pianists, string players) and a control group of non-musicians were tested. Within-task differences in performance showed that factors such as meter, metrical complexity, tempo, and beat phase significantly affected the ability to perceive and synchronize taps to a rhythm or beat. Musicians showed better performance on all rhythm tasks compared to non-musicians. Interestingly, our results revealed no significant differences between musician groups for the vast majority of task measures. This was despite the fact that all musicians were selected to have the majority of their training on the target instrument, had on average more than 10 years of experience on their instrument, and were currently practicing. These results suggest that general musical experience is more important than specialized musical experience with regards to perception and production of rhythms.
EFFECTS OF USING LIGHT-WEIGHT CONCRETE ON INDOOR RADON CONCENTRATION IN HIGH-RISE BUILDINGS

Light-weight concrete (LWC) (or drywall construction) has been used for partition walls in public housing in Hong Kong for about 10 years. A previous laboratory investigation showed that all types of LWC had considerably smaller Rn exhalation rates than those from normal concrete (NC), and could thus theoretically reduce the indoor Rn concentrations and the correspond- ing radiation dose from Rn. In the present investigation, a survey of Rn exhalation rates and indoor Rn concentrations at 39 dwelling sites built using LWC were carried out using charcoal canisters and g-spectroscopy. The mean Rn exhalation rate and the mean Rn concentration were around 1.6 mBq.s -1 . m -2 and 19 Bq.m -3 , respectively, which were significantly smaller than the corresponding values of 12 mBq.s -1 . m -2 and 33 Bq.m -3 for NC sites. The statistical t-test showed that both the mean Rn exhalation rate and the mean Rn concentration for NC and LWC sites walls were different at the 100% confidence level. The Rn exhalation rate from an LWC surface was, on average, only about 14% of that from an NC surface, while the Rn concentration in an LWC site was, on average, about 58% of that in an NC site, which were significant. A person living at an LWC site receives an average annual equivalent dose smaller than one living at an NC site by an amount as large as 1 mSv. Therefore, the use of LWC for partition walls can be a simple and economical way to reduce the indoor Rn concentrations and the corresponding radiation dose from Rn. Furthermore, the mean Rn concentration theoretically predicted from the mean Rn exhalation rate agreed excellently with that from measurements.
Bright X-Ray Flares in Orion Young Stars from COUP: Evidence for Star-Disk Magnetic Fields?

We have analyzed a number of intense X-ray flares observed in the Chandra Orion Ultradeep Project (COUP), a 13 day observation of the Orion Nebula Cluster (ONC), concentrating on the events with the highest statistics (in terms of photon flux and event duration). Analysis of the flare decay allows to determine the physical parameters of the flaring structure, particularly its size and (using the peak temperature and emission measure of the event) the peak density, pressure, and minimum confining magnetic field. A total of 32 events, representing the most powerful ≃1% of COUP flares, have sufficient statistics and are sufficiently well resolved to grant a detailed analysis. A broad range of decay times are present in the sample of flares, with τlc (the 1/e decay time) ranging from 10 to 400 ks. Peak flare temperatures are often very high, with half of the flares in the sample showing temperatures in excess of 100 MK. Significant sustained heating is present in the majority of the flares. The magnetic structures that are found, from the analysis of the flare's decay, to confine the plasma are in a number of cases very long, with semilengths up to ≃1012 cm, implying the presence of magnetic fields of hundreds of G (necessary to confine the hot flaring plasma) extending to comparable distance from the stellar photosphere. These very large sizes for the flaring structures (length L ≫ R*) are not found in more evolved stars, where, almost invariably, the same type of analysis results in structures with L ≤ R*. As the majority of young stars in the ONC are surrounded by disks, we speculate that the large magnetic structures that confine the flaring plasma are actually the same type of structures that channel the plasma in the magnetospheric accretion paradigm, connecting the star's photosphere with the accretion disk.