snu-aidas/HVMap-dataset huggingface dataset:
A Simple Introduction to Maximum Entropy Models for Natural Language Processing

Many problems in natural language processing can be viewed as lin guistic classi cation problems in which linguistic contexts are used to pre dict linguistic classes Maximum entropy models o er a clean way to com bine diverse pieces of contextual evidence in order to estimate the proba bility of a certain linguistic class occurring with a certain linguistic con text This report demonstrates the use of a particular maximum entropy model on an example problem and then proves some relevant mathemat ical facts about the model in a simple and accessible manner This report also describes an existing procedure called Generalized Iterative Scaling which estimates the parameters of this particular model The goal of this report is to provide enough detail to re implement the maximum entropy models described in Ratnaparkhi Reynar and Ratnaparkhi Ratnaparkhi and also to provide a simple explanation of the max imum entropy formalism Introduction Many problems in natural language processing NLP can be re formulated as statistical classi cation problems in which the task is to estimate the probability of class a occurring with context b or p a b Contexts in NLP tasks usually include words and the exact context depends on the nature of the task for some tasks the context b may consist of just a single word while for others b may consist of several words and their associated syntactic labels Large text corpora usually contain some information about the cooccurrence of a s and b s but never enough to completely specify p a b for all possible a b pairs since the words in b are typically sparse The problem is then to nd a method for using the sparse evidence about the a s and b s to reliably estimate a probability model p a b Consider the Principle of Maximum Entropy Jaynes Good which states that the correct distribution p a b is that which maximizes en tropy or uncertainty subject to the constraints which represent evidence i e the facts known to the experimenter Jaynes discusses its advan tages in making inferences on the basis of partial information we must use that probability distribution which has maximum entropy sub ject to whatever is known This is the only unbiased assignment we can make to use any other would amount to arbitrary assumption of information which by hypothesis we do not have More explicitly if A denotes the set of possible classes and B denotes the set of possible contexts p should maximize the entropy H p X
A second order accurate projection method for the incompressible Navier-Stokes equations on non-graded adaptive grids

We present an unconditionally stable second order accurate projection method for the incompressible Navier–Stokes equations on non-graded adaptive Cartesian grids. We employ quadtree and octree data structures as an efficient means to represent the grid. We use the supra-convergent Poisson solver of [C.-H. Min, F. Gibou, H. Ceniceros, A supra-convergent finite difference scheme for the variable coefficient Poisson equation on fully adaptive grids, CAM report 05-29, J. Comput. Phys. (in press)], a second order accurate semi-Lagrangian method to update the momentum equation, an unconditionally stable backward difference scheme to treat the diffusion term and a new method that guarantees the stability of the projection step on highly non-graded grids. We sample all the variables at the grid nodes, producing a scheme that is straightforward to implement. We propose two and three-dimensional examples to demonstrate second order accuracy for the velocity field and the divergence free condition in the L and L1 norms. 2006 Elsevier Inc. All rights reserved.
Quo Vadis , Atlas-Based Segmentation?
Biomedical Event Extraction using Abstract Meaning Representation

We propose a novel, Abstract Meaning Representation (AMR) based approach to identifying molecular events/interactions in biomedical text. Our key contributions are: (1) an empirical validation of our hypothesis that an event is a subgraph of the AMR graph, (2) a neural network-based model that identifies such an event subgraph given an AMR, and (3) a distant supervision based approach to gather additional training data. We evaluate our approach on the 2013 Genia Event Extraction dataset1 (Kim et al., 2013) and show promising results.
Building population mapping with aerial imagery and GIS data

Geospatial distribution of population at a scale of individual buildings is needed for analysis of people’s interaction with their local socio-economic and physical environments. High resolution aerial images are capable of capturing urban complexities and considered as a potential source for mapping urban features at this fine scale. This paper studies population mapping for individual buildings by using aerial imagery and other geographic data. Building footprints and heights are first determined from aerial images, digital terrain and surface models. City zoning maps allow the classification of the buildings as residential and non-residential. The use of additional ancillary geographic data further filters residential utility buildings out of the residential area and identifies houses and apartments. In the final step, census block population, which is publicly available from the U.S. Census, is disaggregated and mapped to individual residential buildings. This paper proposes a modified building population mapping model that takes into account the effects of different types of residential buildings. Detailed steps are described that lead to the identification of residential buildings from imagery and other GIS data layers. Estimated building populations are evaluated per census block with reference to the known census records. This paper presents and evaluates the results of building population mapping in areas of West Lafayette, Lafayette, and Wea Township, all in the state of Indiana, USA. © 2011 Published by Elsevier B.V.
Toward a Universal Cortical Algorithm: Examining Hierarchical Temporal Memory in Light of Frontal Cortical Function

Representations One aspect of frontal cortical function that has been given less attention than it is due, both in this review and in the literature in general, is the biological basis of the generation and manipulation of abstract frontal representations. Response properties of some PFC cells have been shown to correspond with abstract rules (Wallis et al, 2001), and models such as those of Norman & Shallice (1980, 1986; Shallice, 1982; Shallice & Burgess, 1991, 1996), Grafman (2002) and Fuster (1997) have emphasized the requirement that frontal cortex dynamically generate and manipulate abstract
Content-Based, Collaborative Recommendation

The problem of recommending items from some fixed database has been studied extensively, and two main paradigms have emerged. In content-based recommendation one tries to recommend items similar to those a given user has liked in the past, whereas in collaborative recommendation one identifies users whose tastes are similar to those of the given user and recommends items they have liked. Our approach in Fab has been to combine these two methods. Here, we explain how a hybrid system can incorporate the advantages of both methods while inheriting the disadvantages of neither. In addition to what one might call the “generic advantages” inherent in any hybrid system, the particular design of the Fab architecture brings two additional benefits. First, two scaling problems common to all Web services are addressed—an increasing number of users and an increasing number of documents. Second, the system automatically identifies emergent communities of interest in the user population, enabling enhanced group awareness and communications. Here we describe the two approaches for contentbased and collaborative recommendation, explain how a hybrid system can be created, and then describe Fab, an implementation of such a system. For more details on both the implemented architecture and the experimental design the reader is referred to [1]. The content-based approach to recommendation has its roots in the information retrieval (IR) community, and employs many of the same techniques. Text documents are recommended based on a comparison between their content and a user profile. Data
A strategic framework for good governance through e-governance optimization: A case study of Punjab in India

Purpose – The purpose of this paper is to attempt to find out whether the new information and communication technologies can make a significant contribution to the achievement of the objective of good governance. The study identifies the factors responsible for creating a conducive environment for effective and successful implementation of e-governance for achieving good governance and the possible barriers in the implementation of e governance applications. Based on the comprehensive analysis it proposes a strategic policy framework for good governance in Punjab in India. Punjab is a developed state ranked amongst some of the top states of India in terms of per capita income and infrastructure. Design/methodology/approach – The study designs a framework for good governance by getting the shared vision of all stakeholders about providing good quality administration and governance in the Indian context through “Participatory Stakeholder Assessment”. The study uses descriptive statistics, perception gap, ANOVA and factor analysis to identify the key factors for good governance, the priorities of public regarding e-services, the policy makers’ perspectives regarding good governance to be achieved through e-governance. Findings – The study captures the good governance factors mainly contributing to the shared vision. The study further highlights that most Indian citizens in Punjab today believe in the power of information and communication technology (ICT) and want to access e-governance services. Major factors causing pain and harassment to the citizens in getting the services from various government departments include: unreasonable delay, multiple visits even for small services; poor public infrastructure and its maintenance in government offices. In the understanding of citizens the most important factors for the success of e-governance services are: overall convenience and experience of the citizens; reduction in the corruption levels by improvement in the transparency of government functioning and awareness about the availability of service amongst general masses. Originality/value – The present study has evolved a shared vision of all stakeholders on good governance in the Indian context. It has opened up many new possibilities for the governments, not only to use ICTs and help them in prioritizing the governance areas for focused attention, but also help to understand the mindset of the modern citizenry, their priorities and what they consider as good governance. The study will help policy makers focus on these factors for enhancing speedy delivery of prioritized services and promote good governance in developing countries similar to India.
' s personal copy Core , animal reminder , and contamination disgust : Three kinds of disgust with distinct personality , behavioral , physiological , and clinical correlates

We examined the relationships between sensitivity to three kinds of disgust (core, animalreminder, and contamination) and personality traits, behavioral avoidance, physiological responding, and anxiety disorder symptoms. Study 1 revealed that these disgusts are particularly associated with neuroticism and behavioral inhibition. Moreover, the three disgusts showed a theoretically consistent pattern of relations on four disgust-relevant behavioral avoidance tasks in Study 2. Similar results were found in Study 3 such that core disgust was significantly related to increased physiological responding during exposure to vomit, while animal-reminder disgust was specifically related to physiological responding during exposure to blood. Lastly, Study 4 revealed that each of the three disgusts showed a different pattern of relations with fear of contamination, fear of animals, and fear of blood– injury relevant stimuli. These findings provide support for the convergent and divergent validity of core, animal-reminder, and contamination disgust. These findings also highlight the possibility that the three kinds of disgust may manifest as a function of different psychological mechanisms (i.e., oral incorporation, mortality defense, disease avoidance) that may give rise to different clinical conditions. However, empirical examination of the mechanisms that underlie the three disgusts will require further refinement of the psychometric properties of the disgust scale. 2008 Elsevier Inc. All rights reserved.
Body Image and Personality in Aesthetic Plastic Surgery : A Case-Control Study

Introduction: The amount of research on the relationship between plastic surgery and psychological features, such as personality disorders and indexes of body image dissatisfaction, has increased significantly in the last years. Aim: The aim of the present study was to examine these psychological features among Italian patients who underwent aesthetic plastic surgery, testing the mediating role of the mass media influence on the relationship between them and the choice of aesthetic plastic surgery. The Personality Diagnostic Questionnaire 4+ (PDQ-4+) and the Body Uneasiness Test (BUT) were administered to patients who underwent aesthetic plastic surgery (N = 111) and participants who had no history of aesthetic plastic surgical procedures (N = 149). Results: Results showed that aesthetic patients reported higher indexes of body image disturbance than controls. No significant differences between aesthetic participants and controls were found in all three cluster B personality disorders. Moreover, the effect of body image dissatisfaction on the choice to undergo aesthetic plastic surgery was partially mediated by the influence of mass media. Conclusions: In conclusion, the present study confirmed the importance of body dissatisfaction as a predictor of the choice to undergo aesthetic surgery and highlighted the influence of media messages regarding physical appearance.
Broadcast Encryption

We introduce new theoretical measures for the qualitative and quantitative assessment of encryption schemes designed for broadcast transmissions. The goal is to allow a central broadcast site to broadcast secure transmissions to an arbitrary set of recipients while minimizing key management related transmissions. We present several schemes that allow a center to broadcast a secret to any subset of privileged users out of a universe of size so that coalitions of users not in the privileged set cannot learn the secret. The most interesting scheme requires every user to store keys and the center to broadcast messages regardless of the size of the privileged set. This scheme is resilient to any coalition of users. We also present a scheme that is resilient with probability against a random subset of users. This scheme requires every user to store keys and the center to broadcast messages. Preliminary version appeared in Advances in Cryptology CRYPTO ’93 Proceedings, Lecture Notes in Computer Science, Vol. 773, 1994, pp. 480–491. Dept. of Computer Science, School of Mathematics, Tel Aviv University, Tel Aviv, Israel, and Algorithmic Research Ltd. E-mail fiat@math.tau.ac.il. Incumbent of the Morris and Rose Goldman Career Development Chair, Dept. of Applied Mathematics and Computer Science, Weizmann Institute of Science, Rehovot 76100, Israel. Research supported by an Alon Fellowship and a grant from the Israel Science Foundation administered by the Israeli Academy of Sciences. E-mail: naor@wisdom.weizmann.ac.il.
Diagnostic Performance of a Smartphone‐Based Photoplethysmographic Application for Atrial Fibrillation Screening in a Primary Care Setting

BACKGROUND
Diagnosing atrial fibrillation (AF) before ischemic stroke occurs is a priority for stroke prevention in AF. Smartphone camera-based photoplethysmographic (PPG) pulse waveform measurement discriminates between different heart rhythms, but its ability to diagnose AF in real-world situations has not been adequately investigated. We sought to assess the diagnostic performance of a standalone smartphone PPG application, Cardiio Rhythm, for AF screening in primary care setting.


METHODS AND RESULTS
Patients with hypertension, with diabetes mellitus, and/or aged ≥65 years were recruited. A single-lead ECG was recorded by using the AliveCor heart monitor with tracings reviewed subsequently by 2 cardiologists to provide the reference standard. PPG measurements were performed by using the Cardiio Rhythm smartphone application. AF was diagnosed in 28 (2.76%) of 1013 participants. The diagnostic sensitivity of the Cardiio Rhythm for AF detection was 92.9% (95% CI] 77-99%) and was higher than that of the AliveCor automated algorithm (71.4% [95% CI 51-87%]). The specificities of Cardiio Rhythm and the AliveCor automated algorithm were comparable (97.7% [95% CI: 97-99%] versus 99.4% [95% CI 99-100%]). The positive predictive value of the Cardiio Rhythm was lower than that of the AliveCor automated algorithm (53.1% [95% CI 38-67%] versus 76.9% [95% CI 56-91%]); both had a very high negative predictive value (99.8% [95% CI 99-100%] versus 99.2% [95% CI 98-100%]).


CONCLUSIONS
The Cardiio Rhythm smartphone PPG application provides an accurate and reliable means to detect AF in patients at risk of developing AF and has the potential to enable population-based screening for AF.
Young adults' experiences of seeking online information about diabetes and mental health in the age of social media

BACKGROUND
The Internet is a primary source of health information for many. Since the widespread adoption of social media, user-generated health-related content has proliferated, particularly around long-term health issues such as diabetes and common mental health disorders (CMHDs).


OBJECTIVE
To explore perceptions and experiences of engaging with health information online in a sample of young adults familiar with social media environments and variously engaged in consuming user-generated content.


METHODS
Forty semi-structured interviews were conducted with young adults, aged 18-30, with experience of diabetes or CMHDs. Data were analysed following a thematic networks approach to explore key themes around online information-seeking and content consumption practices.


RESULTS
Although participants primarily discussed well-rehearsed approaches to health information-seeking online, particularly reliance on search engines, their accounts also reflected active engagement with health-related content on social media sites. Navigating between professionally produced websites and user-generated content, many of the young adults seemed to appreciate different forms of health knowledge emanating from varied sources. Participants described negotiating health content based on social media practices and features and assessing content heuristically. Some also discussed habitual consumption of content related to their condition as integrated into their everyday social media use.


CONCLUSION
Technologies such as Facebook, Twitter and YouTube offer opportunities to consume and assess content which users deem relevant and useful. As users and organizations continue to colonize social media platforms, opportunities are increasing for health communication and intervention. However, how such innovations are adopted is dependent on their alignment with users' expectations and consumption practices.
Forecasting the behavior of multivariate time series using neural networks

Abstract--This pal~er presents a neural network approach to multivariate time-series anal.lwis. Real world observations ~?/flottr /.'ices in three cities have been used as a benchmark in our ev~eriments, l"eed/orward connectionist networks have bt,t,tl ~k,.signed to model flottr l , ices over the period/iom ..lltgttsl 1972 to Novt,mher 1980./or the cities ~?[Blt[]ith~. :lliltneapoli.s, and Kansas Cit): Remarkable sttccess has heen achieved ill training the lletworks to leatvt the price CllrlV [i," each t?/these cities and in m a k i l l g acc l t ra le price predictions. Our r¢,~lt/l.s show that the it¢ltral network al~proat'h is a leading contender with the statistical modeling apl,oaches.
Creating Constructivist Learning Environments on the Web: The Challenge in Higher Education

Australian universities have traditionally relied on government funding to support undergraduate teaching. As the government has adopted the ‘user-pays’ principle, universities have been forced to look outside their traditional market to expand the undergraduate, post-graduate and international offerings. Alternate delivery methods in many universities have utilised web-based instruction as a basis for this move because of three perceptions: access by the target market is reasonably significant, it is a cost-effective method of delivery, and it provides global access. Since the mid sixties, the trend for both on-campus teaching and teaching at a distance has been to use behaviourist instructional strategies for subject development, which rely on the development of a set of instructional sequences with predetermined outcomes. These models, whilst applicable in a behaviourist environment, are not serving instructional designers well when the theoretical foundation for the subject outcomes is based on a constructivist approach to learning, since the constructivist group of theories places less emphasis on the sequence of instruction and more emphasis on the design of the learning environment. (Jonassen, 1994. p 35). In a web-based environment this proves to be even more challenging. This paper will review current research in design goals for web-based constructivist learning environments, and a move towards the development of models. The design of two web-based subjects will be explored in the context of the design goals developed by Duffy and Cunningham (1996 p 177) who have produced some basic assumptions that they call “metaphors we teach by”. The author seeks to examine the seven goals for their relevance to the instructional designer through the examination of their relevance to the web-based subjects, both of which were framed in constructivist theory.