Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationships between tropical sea surface temperature and top‐of‐atmosphere radiation

To assess climate sensitivity from Earth radiation observations of limited duration and observed sea surface temperatures (SSTs) requires a closed and therefore global domain, equilibrium between the fields, and robust methods of dealing with noise. Noise arises from natural variability in the atmosphere and observational noise in precessing satellite observations. This paper explores the meaning of results that use only the tropical region. We compute correlations and regressions between tropical SSTs and top‐of‐atmosphere (TOA) longwave, shortwave and net radiation using a variety of methods to test robustness of results. The main changes in SSTs throughout the tropics are associated with El Niño Southern Oscillation (ENSO) events in which the dominant changes in energy into an atmospheric column come from ocean heat exchange through evaporation, latent heat release in precipitation, and redistribution of that heat through atmospheric winds. These changes can be an order of magnitude larger than the net TOA radiation changes, and their effects are teleconnected globally, and especially into the subtropics. Atmospheric model results are explored and found to be consistent with observations. From 1985 to 1999 the largest perturbation in TOA radiative fluxes was from the eruption of Mount Pinatubo and clearly models which do not include that forcing will not simulate the effects. Consequently, regressions of radiation with SSTs in the tropics may have nothing to say about climate sensitivity.
A De-identification Method for Bilingual Clinical Texts of Various Note Types

De-identification of personal health information is essential in order not to require written patient informed consent. Previous de-identification methods were proposed using natural language processing technology in order to remove the identifiers in clinical narrative text, although these methods only focused on narrative text written in English. In this study, we propose a regular expression-based de-identification method used to address bilingual clinical records written in Korean and English. To develop and validate regular expression rules, we obtained training and validation datasets composed of 6,039 clinical notes of 20 types and 5,000 notes of 33 types, respectively. Fifteen regular expression rules were constructed using the development dataset and those rules achieved 99.87% precision and 96.25% recall for the validation dataset. Our de-identification method successfully removed the identifiers in diverse types of bilingual clinical narrative texts. This method will thus assist physicians to more easily perform retrospective research. Graphical Abstract
Determination of total hydrocarbons levels in some marine organisms from some towns within the Rivers State of Nigeria

The total hydrocarbon (THC) content of three marine organisms; Periwinkles ( Pachyelina aurita ), mussels ( Mylitus edulis ) and mangrove Oysters ( Cassostrea gasar ) from polluted and unpolluted (i.e. control) sampling stations in parts of the Niger Delta area has been assessed. Statistical results revealed that the THC levels in periwinkles, mussels and mangrove oysters in polluted areas vary significantly at 95% confidence level from those from the control station. The results also show that the ability to accumulate total hydrocarbons varies with each organism investigated. Oysters were observed to accumulate the highest concentration of THC while periwinkles were the least. Journal of Applied Sciences and Environmental Management Vol. 9(3) 2005: 59-61
Fast Proximity Queries with Swept Sphere Volumes

: We present novel algorithms for fast proximity queries using swept sphere volumes. The set of proximity queries includes collision detection and both exact and approximate separation distance computation. We introduce a new family of bounding volumes that correspond to a core primitive shape grown outward by some o(cid:11)set. The set of core primitive shapes includes a point, line, and rectangle. This family of bounding volumes provides varying tightness of (cid:12)t to the underlying geometry. Furthermore, we describe e(cid:14)cient and accurate algorithms to perform di(cid:11)erent queries using these bounding volumes. We present a novel analysis of proximity queries that highlights the relationship between collision detection and distance computation. We also present traversal techniques for accelerating distance queries. These algorithms have been used to perform proximity queries for applications including virtual prototyping, dynamic simulation, and motion planning on complex models. As compared to earlier algorithms based on bounding volume hierarchies for separation distance and approximate distance computation, our algorithms (cid:3) Supported in part by ARO Contract DAAH04-96-1-0257, NSF Career Award CCR-9625217, NSF grants EIA-9806027 and DMI-9900157, ONR Young Investigator Award and Intel.
Cybernetic Transportation Systems Design and Development: Simulation Software cybercars

The growing number of vehicles saturates cities in terms of congestion and pollution. A Cybernetic Transportation System (CTS) appears to be a way to resolve those problems. Based on a network of clean driverless vehicles (the cybercars), CTS aims to improve safety and organization of urban transport by providing a door-to-door complement to efficient and fast mass transport. The simulation software presented in this paper has a goal to facilitate the development of such a transportation system. It simulates several cybercars in a dynamic virtual 3D environment, and provides sensors information in real vehicles. As it is easy to create scenarios containing various static and moving obstacles, evaluation of control algorithms in several situations is its main feature. The adopted architecture for the simulation tool also enables evaluation of road traffic scenarios constructed on various levels of interaction or cooperation among cybercars.
An Algorithm Based Fault Tolerant Scheme for Elliptic Curve Public-Key Cryptography

In this paper, an algorithm based fault tolerant (ABFT) scheme for Elliptic Curve Cryptography (ECC) public-key cipher is presented. By adding 2n+1 check sums, the proposed scheme is able to detect and correct up to three errors which may occur during the massive computation process or/and data transmission process for total n*n groups of data. The other advantage of the proposed fault tolerant scheme include: (1). It maintains almost the same throughput when there is no error detected. (2). It does not require additional arithmetic units to create check sums and error detection. (3). It can be easily implemented by software or hardware.
Using Ontologies for Medical Image Retrieval - An Experiment

An aqueous composition for the treatment of surfaces such as metals particularly aluminum, comprises a tetraalkyl silicate or a monomeric or oligomeric hydrolysis product thereof, and an inorganic passenger powder below 100 nm diameter such as fumed silica, both in dispersion in a fluid aqueous medium. The composition can be applied as a conversion coating to improve the adhesion of subsequently applied paint, lacquer or adhesive. Non-aqueous intermediate products comprising the silicate component and passenger powder can be diluted with water to make the coating composition.
Accumulation over the Greenland ice sheet from historical and recent records

Water accumulation, defined as precipitation minus evaporation, was estimated over all of Greenland as part of a program to understand changes in ice sheet mass and elevation. Over 360 historical and recent point accumulation estimates on the Greenland ice sheet were evaluated, and 276 estimates that were judged to be high quality were used to develop the accumulation map. The data set includes 99 points developed as part of four investigations of the past 5–15 years; these are judged to have the greatest accuracy. Using kriging, the average accumulation over Greenland is estimated to be ∼30 g cm−2 yr−1. For the interior part of the ice sheet above 1800 m elevation, where most of the data were acquired, the average accumulation is also estimated to be ∼30 g cm−2 yr−1. There are still many areas on the ice sheet, including northwest, southeast, and southern Greenland, where accumulation is highly uncertain, exceeding the mean ice sheet uncertainty at a point of ∼20–25%. In these regions, further sampling will be required to reduce uncertainty in both regional and ice-sheet-wide accumulation.
The SAR image segmentation superpixel-based with optimized spatial information

In this paper, we propose a method of image segmentation, which is based on superpixel and optimized spatial feature. In this paper, the superpixels are taken into account, which can reduce computational burden, and the result of over-segmentation can also be benefit for segmentation results. The main idea of this paper is based on the conventional fuzzy c-means (FCM). The conventional FCM has a better performance. However, it is sensitive to noise. In order to overcome this shortage, we incorporate spatial information of superpixels into the conventional FCM. In order to obtain the better performance, influential degree of spatial information is applied to the conventional FCM to improve segmentation performance Experimental results show that the proposed method achieves excellent performance.
Cloud-Based Architectures for Auto-Scalable Web Geoportals towards the Cloudification of the GeoVITe Swiss Academic Geoportal

Cloud computing has redefined the way in which Spatial Data Infrastructures (SDI) and Web geoportals are designed, managed, and maintained. The cloudification of a geoportal represents the migration of a full-stack geoportal application to an internet-based private or public cloud. This work introduces two generic and open cloud-based architectures for auto-scalable Web geoportals, illustrated with the use case of the cloudification efforts of the Swiss academic geoportal GeoVITe. The presented cloud-based architectural designs for auto-scalable Web geoportals consider the most important functional and non-functional requirements and are adapted to both public and private clouds. The availability of such generic cloud-based architectures advances the cloudification of academic SDIs and geoportals.
Tunable Word-Level Index Compression for Versioned Corpora

This paper presents a tunable index compression scheme for supporting time-travel phrase queries over large versioned corpora such as web archives. Support for phrase queries makes maintenance of word positions necessary, thus increasing the index size significantly. We propose to fuse the word positions in many neighboring versions of a document, and thus exploit the typically high level of redundancy and compressibility to shrink the index size. The resulting compression scheme called FUSION, can be tuned to trade off compression for query-processing overheads. Our experiments on the revision history of Wikipedia demonstrate the effectiveness of our method.
Deep photo: model-based photograph enhancement and viewing

In this paper, we introduce a novel system for browsing, enhancing, and manipulating casual outdoor photographs by combining them with already existing georeferenced digital terrain and urban models. A simple interactive registration process is used to align a photograph with such a model. Once the photograph and the model have been registered, an abundance of information, such as depth, texture, and GIS data, becomes immediately available to our system. This information, in turn, enables a variety of operations, ranging from dehazing and relighting the photograph, to novel view synthesis, and overlaying with geographic information. We describe the implementation of a number of these applications and discuss possible extensions. Our results show that augmenting photographs with already available 3D models of the world supports a wide variety of new ways for us to experience and interact with our everyday snapshots.
Autonomic Brokerage Service for an End-to-End Cloud Networking Service Level Agreement

Today, cloud networking which is the ability to connect the user with his cloud services and to interconnect these services within an inter-cloud approach, is one of the recent research areas in the cloud computing research communities. The main drawback of cloud networking consists in the lack of Quality of Service (QoS) assurance and management in conformance with a corresponding Service Level Agreement (SLA). In this paper, we propose a framework for self-establishing an end-to-end service level agreement between a Cloud Service User (CSU) and multiple Cloud Service Providers (CSPs) in a cloud networking environment using brokerage service. We focus on QoS parameters for NaaS and IaaS services. This framework ensures a self-establishing of the proposed SLA using autonomic cloud managers. Moreover, videoconferencing is a very demanding application in terms of bandwidth, delay and CPU resources that we have to guarantee. Therefore, we propose to use our cloud networking architecture and framework to provide the cloud videoconferencing application with QoS guarantee. We simulate the corresponding scenario using the CloudSim toolkit to evaluate its performance. The results reveal a high scalability, and a good video conferencing delay.
An Image Mining System for Gender Classification & Age Prediction Based on Facial Features

: Over the recent years, a great deal of effort has been made to age estimation & gender recognition from face images. It has been reported that age can be accurately estimated under controlled environment such as frontal faces, no expression, and static lighting conditions. However, it is not straightforward to achieve the same accuracy level in real-world environment because of considerable variations in camera settings, facial poses, and illumination conditions. In this paper, we apply features based approach for gender recognition & histogram base matching for age prediction to get desired objectives. Through real-world age estimation experiments, we demonstrate the usefulness of our proposed method.
Building medical ethics education to improve Japanese medical students' attitudes toward respecting patients' rights.

In medical education, it is important for medical students to develop their ethics to respect patients' rights. Some physicians might make light of patients' rights, because the increased awareness of such rights might make it more difficult for them to conduct medical practice. In the present study, predictors significantly associated with "a sense of resistance to patients' rights" were examined using anonymous self-administered questionnaires. For these predictors, we produced original items with reference to the concept of ethical development and the teachings of Mencius. The subjects were medical students at the Kitasato University School of Medicine, a private university in Japan. A total of 518 students were analyzed (response rate, 78.4%). The average age of enrolled subjects was 22.5 ± 2.7 years (average age ± standard deviation). The average age of 308 male subjects was 22.7 ± 2.8 years, while that of 210 female subjects was 22.1 ± 2.5 years. The item, "Excessive measures to pass the national examination for medical practitioners," was significantly associated with "a sense of resistance to patients' rights. " However, other items, including basic attributes such as age and gender, were not significant predictors. If students spent their school time only focusing on the national examination, they would lose the opportunity to receive the ethical education that would allow them to respect patients' rights. That ethical development cannot easily be evaluated with written exams. Thus, along with the acquisition of medical knowledge, educational programs to promote medical students' ethics should be developed.
Mapping Security Requirements to Identify Critical Security Areas of Focus in PaaS Cloud Models

Information Technology experts cite security and privacy concerns as the major challenges in the adoption of cloud computing. On Platform-as-a-Service (PaaS) clouds, customers are faced with challenges of selecting service providers and evaluating security implementations based on their security needs and requirements. This study aims to enable cloud customers the ability to quantify their security requirements in order to identify critical areas in PaaS cloud architectures were security provisions offered by CSPs could be assessed. With the use of an adaptive security mapping matrix, the study uses a quantitative approach to presents findings of numeric data that shows critical architectures within the PaaS environment where security can be evaluated and security controls assessed to meet these security requirements. The matrix can be adapted across different types of PaaS cloud models based on individual security requirements and service level objectives identified by PaaS cloud customers.
A Kernel-Based Sentiment Classification Approach for Chinese Sentences

There has been a large growth of online opinioned customer reviews in the recent years. Classifying such reviews into polarized ones would be beneficial in business intelligence and other application domains. This paper aims at finding a solution for the sentiment classification at a fine-grained level, namely the sentence level. The challenge is that because a sentiment expression is more free-style, it is more difficult to determine classification features. Therefore, we propose a kernel-based machine learning approach to make it feasible for incorporating multiple features from lexical and syntactic levels. The experiment results have shown that our approach is effective and outperforms the very competitive n-gram method.
Eye Feature Detection Towards Automatic Strabismus Screening

Strabismus is an eye defect which, if left untreated, can result in inability to attain binocular vision or blindness in the affected eye. Early detection is critical for successful treatment. Current methods for detection involve going to an eye specialist or going to a lab with specialized equipment and lighting setup. These options can be expensive and thus aren't always available to all people. The purpose of this project was to determine the feasibility of a software-only solution that could be deployed to photo studios as a low-cost early screening mechanism. The eventual goal is to be able to detect signs of strabismus from a single high resolution portrait photograph of an infant. The strabismus screening algorithm consists of two phases. In the first phase the locations of certain eye features such as pupil center, eye corners, specular highlights, etc are determined. In the second phase the locations of the highlights in both eyes are examined in relation to the pupil centers. The success of the project depends heavily on the accuracy of eye feature detection and is the focus of our work. Several existing computer vision algorithms for detecting various eye features were investigated and the ones that would handle the requirements best for implementation were chosen. So far a good degree of detection accuracy (roughly 80%) has been achieved and currently the eye detection and corner detection routines are being fine tuned to improve detection accuracy even more.
Measuring the impact of menopausal symptoms on quality of life.

OBJECTIVE--To examine the impact of menopausal symptoms on the overall quality of life of women. DESIGN--Data collection with a questionnaire administered by an interviewer, incorporating two different quality of life measurement techniques (time trade off and rating scale). SETTING--Specialist menopause clinic and two general practices in Oxford. SUBJECTS--63 women aged 45-60 years recruited opportunistically during a clinic or appointment with a general practitioner; no exclusion criteria. RESULTS--Subjects gave very low quality of life ratings for health states with menopausal symptoms. The time trade off method of measuring preferences for these health states (on a scale from 0 to 1, where preference for full health is given as 1) yielded utility values of 0.64 for severe menopausal symptoms and 0.85 for mild symptoms. The rating scale measurement technique yielded even lower values: utilities of 0.30 and 0.65 were obtained for severe and mild symptoms respectively. Kappa scores indicated that the two methods produced results that were poorly related but not contradictory. Comparison of quality of life ratings before and after treatment with hormone replacement therapy showed significant improvements: with the rating scale measurement technique mean increases in utility values after the relief of severe and mild menopausal symptoms were 0.56 and 0.18 respectively. CONCLUSIONS--Quality of life may be severely compromised in women with menopausal symptoms, and perceived improvements in quality of life in users of hormone replacement therapy seem to be substantial. This emphasises the need to include quality of life measurements when assessing outcomes of hormone replacement therapy. Several limitations may exist with widely applied measurement techniques, calling for the development of appropriate and well validated instruments for measuring quality of life associated with reduced health states.
Trend Change(s) in Coastal Management Plans: the integration of short and medium term perspectives in the spatial planning process

ABSTRACT Alves, F.L. , Sousa, L.P., Esteves, T.C. , Oliveira, E.R. , Antunes, I.C. , Fernandes, M.L. , Carvalho, L. , Barroso, S. , Pereira, M. , 2014. Trend Change(s) in Coastal Management Plans: the integration of short and medium term perspectives in the spatial planning process. In: Green, A.N. and Cooper, J.A. G. (eds.), Proceedings 13th International Coastal Symposium (Durban, South Africa), Journal of Coastal Research, Special Issue No. 70, pp. 437–442, ISSN 0749-0208. Spatial planning can be seen as an interdisciplinary science that ensures sustainable development and land use, since it integrates policy, social, cultural, economic and environmental management issues. Marine and coastal spatial planning is particularly challenging due to their vulnerable, dynamic and complex nature and to the problems associated with sea level rise, erosion processes and land-use pressures in the coastal zone. Coastal erosion, flooding and shoreline retreat are serious problems along the coast of mainland Portugal. By using an innovative approach of coastal zone spatial planning, this study developed an Integrated Coastal Zone Management Plan for the Portuguese central region (stretch Ovar - Marinha Grande), where alternative planning policies to the previous ones were suggested. The study revealed that socio-economic analysis and the identification and valuation of ecosystems services and land use need to be incorporated in spatial planning to support decision-making favouring sustainable development. According to these approaches the Coastal Plan was developed considering three environmental scenarios to respond to the coastal erosion trends, based on a development model for the coastal region. In addition, the scenarios consider the public investments constraints (national budget) expected in the next decade and the short and medium term of the Plan. This Plan is differentiated from the previous by attempting to lessen further coastal erosion through the integration of different jurisdictions, legislations and directive measures and applying them to the terrain. This strategy shows itself as relevant to promote further forward-thinking Plans for other Portuguese coastal areas.
APHRODITE: an Anomaly-based Architecture for False Positive Reduction

We present APHRODITE, an architecture designed to reduce false positives in network intrusion detection systems. APHRODITE works by detecting anomalies in the output traffic, and by correlating them with the alerts raised by the NIDS working on the input traffic. Benchmarks show a substantial reduction of false positives and that APHRODITE is effective also after a “quick setup�? , i.e. in the realistic case in which it has not been “trained�? and set up optimally.