snu-aidas/HVMap-dataset huggingface dataset:
Classification of brain disease in magnetic resonance images using two-stage local feature fusion

BACKGROUND
Many classification methods have been proposed based on magnetic resonance images. Most methods rely on measures such as volume, the cerebral cortical thickness and grey matter density. These measures are susceptible to the performance of registration and limited in representation of anatomical structure. This paper proposes a two-stage local feature fusion method, in which deformable registration is not desired and anatomical information is represented from moderate scale.


METHODS
Keypoints are firstly extracted from scale-space to represent anatomical structure. Then, two kinds of local features are calculated around the keypoints, one for correspondence and the other for representation. Scores are assigned for keypoints to quantify their effect in classification. The sum of scores for all effective keypoints is used to determine which group the test subject belongs to.


RESULTS
We apply this method to magnetic resonance images of Alzheimer's disease and Parkinson's disease. The advantage of local feature in correspondence and representation contributes to the final classification. With the help of local feature (Scale Invariant Feature Transform, SIFT) in correspondence, the performance becomes better. Local feature (Histogram of Oriented Gradient, HOG) extracted from 16×16 cell block obtains better results compared with 4×4 and 8×8 cell block.


DISCUSSION
This paper presents a method which combines the effect of SIFT descriptor in correspondence and the representation ability of HOG descriptor in anatomical structure. This method has the potential in distinguishing patients with brain disease from controls.
Natural Language Processing using NLTK and WordNet

Natural Language Processing is a theoretically motivated range of computational techniques for analysing and representing naturally occurring texts at one or more levels of linguistic analysis for the purpose of achieving human-like language processing for a range of tasks or applications [1]. To perform natural language processing a variety of tools and platform have been developed, in our case we will discuss about NLTK for Python.The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for the Python programming language[2]. It provides easy-to-use interfaces to many corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning. In this paper we discuss different approaches for natural language processing using NLTK.
Understanding Stories with Large-Scale Common Sense

Story understanding systems need to be able to perform commonsense reasoning, specifically regarding characters’ goals and their associated actions. Some efforts have been made to form large-scale commonsense knowledge bases, but integrating that knowledge into story understanding systems remains a challenge. We have implemented the Aspire system, an application of large-scale commonsense knowledge to story understanding. Aspire extends Genesis, a rule-based story understanding system, with tens of thousands of goalrelated assertions from the commonsense semantic network ConceptNet. Aspire uses ConceptNet’s knowledge to infer plausible implicit character goals and story causal connections at a scale unprecedented in the space of story understanding. Genesis’s rule-based inference enables precise story analysis, while ConceptNet’s relatively inexact but widely applicable knowledge provides a significant breadth of coverage difficult to achieve solely using rules. Genesis uses Aspire’s inferences to answer questions about stories, and these answers were found to be plausible in a small study. Though we focus on Genesis and ConceptNet, demonstrating the value of supplementing precise reasoning systems with large-scale, scruffy commonsense knowledge is our primary contribution.
A comprehensive model of PMOS NBTI degradation

Negative bias temperature instability has become an important reliability concern for ultra-scaled Silicon IC technology with significant implications for both analog and digital circuit design. In this paper, we construct a comprehensive model for NBTI phenomena within the framework of the standard reaction–diffusion model. We demonstrate how to solve the reaction–diffusion equations in a way that emphasizes the physical aspects of the degradation process and allows easy generalization of the existing work. We also augment this basic reaction–diffusion model by including the temperature and field-dependence of the NBTI phenomena so that reliability projections can be made under arbitrary circuit operating conditions. 2004 Published by Elsevier Ltd.
Twenty-Five Years of Research on Women Farmers in Africa : Lessons and Implications for Agricultural Research Institutions with an Annotated Bibliography

.................................................................................................................... iv Acknowledgments ...................................................................................................... iv Introduction ............................................................................................................... 1 Labor ..........................................................................................................................2 Gender Division of Labor .................................................................................... 2 Household Labor Availability ............................................................................... 6 Agricultural Labor Markets .................................................................................. 8 Conclusions: Labor and Gender .......................................................................... 9 Land ........................................................................................................................ 10 Access to Land ................................................................................................... 10 Security of Land ................................................................................................ 11 Changing Access to Land ................................................................................... 11 Access to Other Inputs .............................................................................................. 12 Access to Credit ................................................................................................. 13 Access to Fertilizer ............................................................................................. 14 Access to Extension and Information ................................................................. 15 Access to Mechanization .................................................................................... 16 Gender Issues in Access to Inputs: Summary...................................................... 16 Outputs .................................................................................................................... 17 Household Decision-Making .................................................................................... 18 Cooperative Bargaining and Collective Models .................................................. 19 Noncooperative Bargaining Models ................................................................... 19 Conclusions .............................................................................................................. 21 References ................................................................................................................. 23 Annotated Bibliography ............................................................................................ 27
Pressure characteristics at the stump/socket interface in transtibial amputees using an adaptive prosthetic foot.

BACKGROUND
The technological advances that have been made in developing highly functional prostheses are promising for very active patients but we do not yet know whether they cause an increase in biomechanical load along with possibly negative consequences for pressure conditions in the socket. Therefore, this study monitored the socket pressure at specific locations of the stump when using a microprocessor-controlled adaptive prosthetic ankle under different walking conditions.


METHODS
Twelve unilateral transtibial amputees between 43 and 59 years of age were provided with the Proprio-Foot (Ossur) and underwent an instrumented 3D gait analysis in level, stair, and incline walking, including synchronous data capturing of socket pressure. Peak pressures and pressure time integrals (PTI) at three different locations were compared for five walking conditions with and without using the device's ankle adaptation mode.


FINDINGS
Highest peak pressures of 2.4 k Pa/kg were found for incline ascent at the calf muscle as compared to 2.1 k Pa/kg in level walking with large inter-individual variance. In stair ascent a strong correlation was found between maximum knee moment and socket pressure. The most significant pressure changes relative to level walking were seen in ramp descent anteriorly towards the stump end, with PTI values being almost twice as high as those in level walking. Adapting the angle of the prosthesis on stairs and ramps modified the pressure data such that they were closer to those in level walking.


INTERPRETATION
Pressure at the stump depends on the knee moments involved in each walking condition. Adapting the prosthetic ankle angle is a valuable means of modifying joint kinetics and thereby the pressure distribution at the stump. However, large inter-individual differences in local pressures underline the importance of individual socket fitting.
Predicting hospital admission at emergency department triage using machine learning

OBJECTIVE
To predict hospital admission at the time of ED triage using patient history in addition to information collected at triage.


METHODS
This retrospective study included all adult ED visits between March 2014 and July 2017 from one academic and two community emergency rooms that resulted in either admission or discharge. A total of 972 variables were extracted per patient visit. Samples were randomly partitioned into training (80%), validation (10%), and test (10%) sets. We trained a series of nine binary classifiers using logistic regression (LR), gradient boosting (XGBoost), and deep neural networks (DNN) on three dataset types: one using only triage information, one using only patient history, and one using the full set of variables. Next, we tested the potential benefit of additional training samples by training models on increasing fractions of our data. Lastly, variables of importance were identified using information gain as a metric to create a low-dimensional model.


RESULTS
A total of 560,486 patient visits were included in the study, with an overall admission risk of 29.7%. Models trained on triage information yielded a test AUC of 0.87 for LR (95% CI 0.86-0.87), 0.87 for XGBoost (95% CI 0.87-0.88) and 0.87 for DNN (95% CI 0.87-0.88). Models trained on patient history yielded an AUC of 0.86 for LR (95% CI 0.86-0.87), 0.87 for XGBoost (95% CI 0.87-0.87) and 0.87 for DNN (95% CI 0.87-0.88). Models trained on the full set of variables yielded an AUC of 0.91 for LR (95% CI 0.91-0.91), 0.92 for XGBoost (95% CI 0.92-0.93) and 0.92 for DNN (95% CI 0.92-0.92). All algorithms reached maximum performance at 50% of the training set or less. A low-dimensional XGBoost model built on ESI level, outpatient medication counts, demographics, and hospital usage statistics yielded an AUC of 0.91 (95% CI 0.91-0.91).


CONCLUSION
Machine learning can robustly predict hospital admission using triage information and patient history. The addition of historical information improves predictive performance significantly compared to using triage information alone, highlighting the need to incorporate these variables into prediction models.
Formal Analysis of Graphical Security Models

Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. May not music be described as the mathematics of the sense, mathematics as music of the reason? The musician feels mathematics, the mathematician thinks music: music the dream, mathematics the working life. Summary The increasing usage of computer-based systems in almost every aspect of our daily life makes more and more dangerous the threat posed by potential attackers , and more and more rewarding a successful attack. Moreover, the complexity of these systems is also increasing, including physical devices, software components and human actors interacting with each other to form so-called socio-technical systems. The importance of socio-technical systems to modern societies requires verifying their security properties formally, while their inherent complexity makes manual analyses impracticable. Graphical models for security offer an unrivalled opportunity to describe socio-technical systems, for they allow to represent different aspects like human behaviour, computation and physical phenomena in an abstract yet uniform manner. Moreover, these models can be assigned a formal semantics, thereby allowing formal verification of their properties. Finally, their appealing graphical notations enable to communicate security concerns in an understandable way also to non-experts, often in charge of the decision making. This dissertation argues that automated techniques can be developed on graphical security models to evaluate qualitative and quantitative security properties of socio-technical systems and to synthesise optimal attack and defence strategies. In support to this claim we develop analysis techniques for widely-used graphical security models such as attack trees and attack-defence trees. Our analyses cope with the optimisation of multiple parameters of an attack and defence scenario. Improving on the literature, in case of conflicting parameters such as probability and cost we compute the set of optimal solutions …
DendroPy: a Python library for phylogenetic computing

UNLABELLED
DendroPy is a cross-platform library for the Python programming language that provides for object-oriented reading, writing, simulation and manipulation of phylogenetic data, with an emphasis on phylogenetic tree operations. DendroPy uses a splits-hash mapping to perform rapid calculations of tree distances, similarities and shape under various metrics. It contains rich simulation routines to generate trees under a number of different phylogenetic and coalescent models. DendroPy's data simulation and manipulation facilities, in conjunction with its support of a broad range of phylogenetic data formats (NEXUS, Newick, PHYLIP, FASTA, NeXML, etc.), allow it to serve a useful role in various phyloinformatics and phylogeographic pipelines.


AVAILABILITY
The stable release of the library is available for download and automated installation through the Python Package Index site (http://pypi.python.org/pypi/DendroPy), while the active development source code repository is available to the public from GitHub (http://github.com/jeetsukumaran/DendroPy).
Conceptualizing Context for Pervasive Advertising

Profile-driven personalization based on socio-demographics is currently regarded as the most convenient base for successful personalized advertising. However, signs point to the dormant power of context recognition: Advertising systems that can adapt to the situational context of a consumer will rapidly gain importance. While technologies that can sense the environment are increasingly advanced, questions such as what to sense and how to adapt to a consumer’s context are largely unanswered. In this chapter, we analyze the purchase context of a retail outlet and conceptualize it such that adaptive pervasive advertising applications really deliver on their potential: showing the right message at the right time to the right recipient. full version published as: Bauer, Christine & Spiekermann, Sarah (2011). Conceptualizing Context for Pervasive Advertising. In Müller, Jörg, Alt, Florian, & Michelis, Daniel (Eds.), Pervasive Advertising (pp. 159-183). London: Springer.
Mathematical modelling of infectious diseases.

INTRODUCTION
Mathematical models allow us to extrapolate from current information about the state and progress of an outbreak, to predict the future and, most importantly, to quantify the uncertainty in these predictions. Here, we illustrate these principles in relation to the current H1N1 epidemic.


SOURCES OF DATA
Many sources of data are used in mathematical modelling, with some forms of model requiring vastly more data than others. However, a good estimation of the number of cases is vitally important.


AREAS OF AGREEMENT
Mathematical models, and the statistical tools that underpin them, are now a fundamental element in planning control and mitigation measures against any future epidemic of an infectious disease. Well-parameterized mathematical models allow us to test a variety of possible control strategies in computer simulations before applying them in reality.


AREAS OF CONTROVERSY
The interaction between modellers and public-health practitioners and the level of detail needed for models to be of use.


GROWING POINTS
The need for stronger statistical links between models and data.


AREAS TIMELY FOR DEVELOPING RESEARCH
Greater appreciation by the medical community of the uses and limitations of models and a greater appreciation by modellers of the constraints on public-health resources.
Modern Intrusion Detection, Data Mining, and Degrees of Attack Guilt

This chapter examines the state of modern intrusion detection, with a particular emphasis on the emerging approach of data mining. The discussion paralleIs two important aspects of intrusion detection: general detection strategy (misuse detection versus anomaly detection) and data source (individual hosts versus network trafik). Misuse detection attempts to match known patterns of intrusion , while anomaly detection searches for deviations from normal behavior . Between the two approaches, only anomaly detection has the ability to detect unknown attacks. A particularly promising approach to anomaly detection combines association mining with other forms of machine learning such as classification. Moreover, the data source that an intrusion detection system employs significantly impacts the types of attacks it can detect. There is a tradeoff in the level of detailed information available verD. Barbará et al. (ed .), Applications of Data Mining in Computer Security © Kluwer Academic Publishers 2002 s
A Case Study on Barriers and Enhancements of the PET Bottle-to-Bottle Recycling Systems in Germany and Sweden

Problem: The demand of beverages in PET bottles is constantly increasing. In this context, environmental, technological and regulatory aspects set a stronger focus on recycling. Generally, the reuse of recycled material from post-consumer PET bottles in bottle-to-bottle applications is seen as least environmentally harmful. However, closedloop systems are not widely implemented in Europe. Previous research mainly focuses on open-loop recycling systems and generally lacks discussion about the current German and Swedish systems and their challenges. Furthermore, previous studies lack theoretical and practical enhancements for bottle-to-bottle recycling from a managerial perspective. Purpose: The purpose of this study is to compare the PET bottle recycling systems in Germany and Sweden, analyse the main barriers and develop enhancements for closedloop systems. Method: This qualitative study employs a case study strategy about the two cases of Germany and Sweden. In total, 14 semi-structured interviews are conducted with respondents from different industry sectors within the PET bottle recycling systems. The empirical data is categorised and then analysed by pattern matching with the developed theoretical framework. Conclusion: Due to the theoretical and practical commitment to closed-loop recycling, the Swedish PET bottle recycling system outperforms the Germany system. In Germany, bottle-to-bottle recycling is currently performed on a smaller scale without a unified system. The main barriers for bottle-to-bottle recycling are distinguished into (1) quality and material factors, (2) regulatory and legal factors, (3) economic and market factors and (4) factors influenced by consumers. The enhancements for the systems are (1) quality and material factors, (2) regulatory and legal factors, (3) recollection factors and (4) expanding factors. Lastly, the authors provide further recommendations, which are (1) a recycling content symbol on bottle labels, (2) a council for bottle quality in Germany, (3) a quality seal for the holistic systems, (4) a reduction of transportation in Sweden and (5) an increase of consumer awareness on PET bottle consumption.
Managing Portfolios of Development Projects in a Complex Environment How the UN assign priorities to Programs at the Country
Web Caching with Consistent Hashing

A key performance measure for the World Wide Web is the speed with which content is served to users. As traffic on the Web increases, users are faced with increasing delays and failures in data delivery. Web caching is one of the key strategies that has been explored to improve performance. An important issue in many caching systems is how to decide what is cached where at any given time. Solutions have included multicast queries and directory schemes. In this paper, we offer a new Web caching strategy based on consistent hashing. Consistent hashing provides an alternative to multicast and directory schemes, and has several other advantages in load balancing and fault tolerance. Its performance was analyzed theoretically in previous work; in this paper we describe the implementation of a consistent-hashing-based system and experiments that support our thesis that it can provide performance improvements.  1999 Published by Elsevier Science B.V. All rights reserved.