Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on the text sentiment classification about the social hot events on Weibo

The public comments on the social hot events on Weibo has attracted lots of attentions in recent years. To remedy the shortage of sentiment analysis about typical events on Weibo, the classification method based on sentiment dictionary is put forward in this paper, and the accuracy rate is close to 50%. This paper also proposed a sentiment classification method based on Naive Bayesian in order to improve the accuracy. We use TF as the weight of feature words and chi-square test to extract features of each category. The accuracy rate is commonly raised to more than 70%, it can reach to 80% when analyzing text of typical events.
Real-time Image Processing Manuscript No. Cascaded Online Boosting

In this paper, we propose a cascaded version of the online boosting algorithm to speed-up the execution time and guarantee real-time performance even when employing a large number of classifiers. This is the case for target tracking purposes in computer vision applications. We thus revise the on-line boosting framework by building on-the-fly a cascade of classifiers dynamically for each new frame. The procedure takes into account both the error and the computational requirements of the available features and populates the levels of the cascade accordingly to optimize the detection rate while retaining real-time performance. We demonstrate the effectiveness of our approach on standard datasets.
Annuities, Bequest and Portfolio Diversification

In this article, the diversification motives of the demand for annuities is analyzed. Using a model allowing for the uncertainty of both the human life length and the interest rate, the Decision Maker is supposed to choose an optimal portfolio to maximize a bequest. Conditions under which an increase in the risk of bond returns increase the demand for annuities are proposed and discussed. Moreover, it is shown that, contrary to previous claims, more risk adversion is associated with a lower demand for annuities.
Anthropometric Measurements, Physiological and Biomotoric Test to Identify Talented Basketball Athletes

This research was aimed at developing an equation model and software to identify talented basketball athletes. To this end, a quantitative research and development approach was employed. The research subjects were 145 student basketball players aged 10-12 in Surabaya. Data were analyzed using factor and discriminant analysis. This research resulted in the following equation: D = 3.420 + (0.22 Body Height) + (0.031 Sitting Height) + (0.020 Arm Span) + (0.153 Right Leg Length) + (0.204 Left Leg Length) + (0.111 Palm Length) + (0.247 Back Muscular Flexibility) + (0.007 Illinois Agility Run) + (0,067 Right Leg Vertical Jump) + (0.071 Left Leg Vertical Jump) + (0,011 Double Leg Vertical Jump) + (0.60 20Meter Sprint) + (0.044 Multistage Fitness Test) + (0.009 Ball Throwing). It was concluded that the developed equation and software could be used to identify talented basketball players.
Episodic Memory for Companion Dialogue

We present an episodic memory component for enhancing the dialogue of artificial companions with the capability to refer to, take up and comment on past interactions with the user, and to take into account in the dialogue long-term user preferences and interests. The proposed episodic memory is based on RDF representations of the agent's experiences and is linked to the agent's semantic memory containing the agent's knowledge base of ontological data and information about the user's interests.
Sympathy for the Devil: Detailing the Effects of Planning-Unit Size, Thematic Resolution of Reef Classes, and Socioeconomic Costs on Spatial Priorities for Marine Conservation

Spatial data characteristics have the potential to influence various aspects of prioritising biodiversity areas for systematic conservation planning. There has been some exploration of the combined effects of size of planning units and level of classification of physical environments on the pattern and extent of priority areas. However, these data characteristics have yet to be explicitly investigated in terms of their interaction with different socioeconomic cost data during the spatial prioritisation process. We quantify the individual and interacting effects of three factors—planning-unit size, thematic resolution of reef classes, and spatial variability of socioeconomic costs—on spatial priorities for marine conservation, in typical marine planning exercises that use reef classification maps as a proxy for biodiversity. We assess these factors by creating 20 unique prioritisation scenarios involving combinations of different levels of each factor. Because output data from these scenarios are analogous to ecological data, we applied ecological statistics to determine spatial similarities between reserve designs. All three factors influenced prioritisations to different extents, with cost variability having the largest influence, followed by planning-unit size and thematic resolution of reef classes. The effect of thematic resolution on spatial design depended on the variability of cost data used. In terms of incidental representation of conservation objectives derived from finer-resolution data, scenarios prioritised with uniform cost outperformed those prioritised with variable cost. Following our analyses, we make recommendations to help maximise the spatial and cost efficiency and potential effectiveness of future marine conservation plans in similar planning scenarios. We recommend that planners: employ the smallest planning-unit size practical; invest in data at the highest possible resolution; and, when planning across regional extents with the intention of incidentally representing fine-resolution features, prioritise the whole region with uniform costs rather than using coarse-resolution data on variable costs.
Canonical polyadic decomposition for unsupervised linear feature extraction from protein profiles

We propose a method for unsupervised linear feature extraction through tensor decomposition. The linear feature extraction can be formulated as a canonical polyadic decomposition (CPD) of a third-order tensor when transformation matrix is constrained to be equal to the Khatri-Rao product of two matrices. Therefore, standard algorithms for computing CPD decomposition can be used for feature extraction. The proposed method is validated on publicly available low-resolution mass spectra of cancerous and non-cancerous samples. Obtained results indicate that this approach could be of practical importance in analysis of protein expression profiles.
Evaluating the potential impact of the new Global Plan to Stop TB: Thailand, 2004-2005.

OBJECTIVE WHO's new Global Plan to Stop TB 2006-2015 advises countries with a high burden of tuberculosis (TB) to expand case-finding in the private sector as well as services for patients with HIV and multidrug-resistant TB (MDR-TB). The objective of this study was to evaluate these strategies in Thailand using data from the Thailand TB Active Surveillance Network, a demonstration project begun in 2004. METHODS In October 2004, we began contacting public and private health-care facilities monthly to record data about people diagnosed with TB, assist with patient care, provide HIV counselling and testing, and obtain sputum samples for culture and susceptibility testing. The catchment area included 3.6 million people in four provinces. We compared results from October 2004-September 2005 (referred to as 2005) to baseline data from October 2002-September 2003 (referred to as 2003). FINDINGS In 2005, we ascertained 5841 TB cases (164/100 000), including 2320 new smear-positive cases (65/100 000). Compared with routine passive surveillance in 2003, active surveillance increased reporting of all TB cases by 19% and of new smear-positive cases by 13%. Private facilities diagnosed 634 (11%) of all TB cases. In 2005, 1392 (24%) cases were known to be HIV positive. The proportion of cases with an unknown HIV status decreased from 66% (3226/4904) in 2003 to 23% (1329/5841) in 2005 (P< 0.01). Of 4656 pulmonary cases, mycobacterial culture was performed in 3024 (65%) and MDR-TB diagnosed in 60 (1%). CONCLUSION In Thailand, piloting the new WHO strategy increased case-finding and collaboration with the private sector, and improved HIV services for TB patients and the diagnosis of MDR-TB. Further analysis of treatment outcomes and costs is needed to assess this programme's impact and cost effectiveness.
Implementation of the WirelessHART MAC layer in the OPNET simulator

WirelessHART standard is the first international standard for Industrial Wireless Sensor Networks (IWSN) approved by International Electrotechnical Commission (IEC), and, as such, it is worthwhile to implement on simulator platforms. Based on the study of WirelessHART standard, this paper is a primary implementation of the Medium Access Control layer of WirelessHART standard. To our best knowledge, this is the first comprehensive implementation of WirelessHART using the OPNET simulator. This paper also proposes the improvement of shared slot access method by using slotted Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA), which outperforms the existing slotted ALOHA by increasing the throughput for 2% and reducing the packet loss. Flexible dedicated slot assignment has also been proposed to reduce the packet loss rate caused by influences of the physical channel.
High Accuracy Autonomous Image Georeferencing Using a GPS/Inertial-Aided Digital Imaging System

This paper describes the implementation of a GPS/Inertial integrated navigation system, the GI-Eye, that is designed to automatically georeference imagery collected from a digital camera without requiring any ground control for registration. This is accomplished through the use of Wide-Area DGPS (WADGPS) GPS updates, combined with NAVSYS’ tightly coupled GPS/inertial alignment software to provide both the precise location and the precise attitude of the digital image when the data is collected. Using this information, the GI-Eye system can georeference features extracted from airborne imagery to meter-level accuracy. The system design has been used in both airborne and ground-based survey applications, with the resulting imagery and associated navigation data used to geolocate reference points and to produce ortho-rectified and registered airborne imagery. In this paper, flight test results of the GI-Eye are included demonstrating the precision geolocation performance and the ability to perform autonomous image rectification and georegistration without requiring any ground control points.
A game theoretic investigation for high interaction honeypots

Honeypots are traps designed to resemble easy-to-compromise computer systems in order to deceive botmasters. Such security traps help security professionals to collect valuable information about botmasters' techniques and true identities. Depending on the complexity of services provided by honeypots, botmasters might be able to detect these traps by performing a series of tests. In particular, to detect honeypots, botmasters can command compromised machines to perform specific actions such as targeting sensor machines controlled by them. If honeypots were designed to completely ignore these commands, then they can easily be detected by the botmasters. On the other hand, full participation by honeypots in such activities has its associated costs and may lead to legal liabilities. This raises the need for finding the optimal response strategy needed by the honeypot in order to prolong its stay within the botnet without sacrificing liability. In this paper, we address the problem of honeypot detection by botmasters. In particular, we present a Bayesian game theoretic framework that models the interaction between honeypots and botmasters as a non-zero-sum noncooperative game with uncertainty. The game solution illustrates the optimal response available for both players. Simulation results are conducted to show the botmasters' behavior update and possible interactions between the game players. The obtained results can be utilized by security professionals to determine their best response to these kind of probes by botmasters.
Integration and Interoperability – Standardisation is the Key

n this chapter, we engage in the ongoing debate in the global HIS field, around issues of integration and interoperability – how these are different, how they may complement each other, and how integration and interoperability, respectively, could be achieved. We argue that, standardisation is the key to understand and to achieve integration and interoperability in HIS, and information systems more broadly. Furthermore, we argue that within the perspective of the management-oriented enterprise architecture, we develop in this book; the IHIA – as we have labelled it, makes it crucial for data standards. In this chapter, we first position the debate(s) around integration and interoperability in HIS, taking examples from the development of the DHIS2 and its integration and/ or interoperability with medical records and human resource management systems. After discussing concepts of vertical and horizontal integration, in the last part of the chapter, data standardisation is linked to cases of development of the DHIS2 'data warehouse'. Integration is a term with different meanings in different contexts – from being a very precise term in mathematics, as the art of calculating integrals, to a more ambiguous term in social sciences and everyday speech, as in cultural, ethnic, or religious integration. Similarly, in our field of HIS, meanings of integration will vary according to 'who you are' , your role in the organisation, your relation to the health sector, and the perspectives on the HIS. While managers and health services providers would think that integration of information and routines are needed to perform certain tasks; ICT staff, software developers and more technically-oriented personnel would think that coordination of the software applications and protocols for communication are needed to achieve that. During an electronic forum debate on integration, in the RHINO network meeting in Mexico, 2009, it turned out that, while some saw integration strictly as a technical term related to collating several software applications into 'one system, ' regarded as a negative and an old fashioned approach; others used integration to describe approaches to get health programmes to collaborate and unify their data collection forms and routines. Those who understood the term integration as refering to a technical approach to make 'one big system' , were against the notion of integration understood in this way. They would rather go for the concept of interoperability, 3 Integration and Interoperability – Standardisation is the Key
Constructing a Reusable Linguistic Resource for a Polyglot Speech Synthesis

This paper is about constructing sharable linguistic information to be used across languages for a Text-to-Speech (TTS) system. The data is obtained from existing resources. The focus of the paper is the phonetic and linguistic aspects. A monolingual TTS architecture is introduced with descriptions on each stage of processing. A multilingual TTS architecture is also introduced. Language dependent and language independent information required in the general TTS engine is described. Finally we will propose layer of communication between the pooled language information and a TTS engine in order to make it available for information reuse where possible for different languages.
Scanning and Filling: Ultra-Dense SNP Genotyping Combining Genotyping-By-Sequencing, SNP Array and Whole-Genome Resequencing Data

Genotyping-by-sequencing (GBS) represents a highly cost-effective high-throughput genotyping approach. By nature, however, GBS is subject to generating sizeable amounts of missing data and these will need to be imputed for many downstream analyses. The extent to which such missing data can be tolerated in calling SNPs has not been explored widely. In this work, we first explore the use of imputation to fill in missing genotypes in GBS datasets. Importantly, we use whole genome resequencing data to assess the accuracy of the imputed data. Using a panel of 301 soybean accessions, we show that over 62,000 SNPs could be called when tolerating up to 80% missing data, a five-fold increase over the number called when tolerating up to 20% missing data. At all levels of missing data examined (between 20% and 80%), the resulting SNP datasets were of uniformly high accuracy (96–98%). We then used imputation to combine complementary SNP datasets derived from GBS and a SNP array (SoySNP50K). We thus produced an enhanced dataset of >100,000 SNPs and the genotypes at the previously untyped loci were again imputed with a high level of accuracy (95%). Of the >4,000,000 SNPs identified through resequencing 23 accessions (among the 301 used in the GBS analysis), 1.4 million tag SNPs were used as a reference to impute this large set of SNPs on the entire panel of 301 accessions. These previously untyped loci could be imputed with around 90% accuracy. Finally, we used the 100K SNP dataset (GBS + SoySNP50K) to perform a GWAS on seed oil content within this collection of soybean accessions. Both the number of significant marker-trait associations and the peak significance levels were improved considerably using this enhanced catalog of SNPs relative to a smaller catalog resulting from GBS alone at ≤20% missing data. Our results demonstrate that imputation can be used to fill in both missing genotypes and untyped loci with very high accuracy and that this leads to more powerful genetic analyses.
Comparative Study of Clustering based Routing Protocols for Wireless Sensor Network

A wireless sensor network consists of large number of sensor nodes deployed on a large field and has limited battery lifetime which get depleted at a faster rate due to their communication and computation operation.These sensor nodes has the ability of sensing, computing and transmitting data from the harsh environment. Many communication protocols are designed to make efficient and effective utilization of energy.A comparative study of clustering based routing protocols has been done which gives an overview of the performance of protocols on some factors like cluster stability, latency, energy efficiency and load balancing etc
Multi-Layer Deformable Models for medical image segmentation

In this work, a Multi-Layer Deformable Model (MLDM) for medical image segmentation is proposed. In contrast to common deformable model based segmentation approaches our new method incorporates a multi-layer geometric model that allows a sampling of the organ's interior. An adaptation logic processes the additional information gained from interior layers in order to fit the model to the data. The deformation is coupled with a dynamic internal energy function represented by a link-oriented flexibility in order to allow the model to accurately adapt to cavities. Exploiting the additional depth information, our approach detects low contrasted transitions between organs more reliably and recovers better from bad model initialization than existing methods. Our approach has been evaluated using representative CT data sets of the liver as well as CT bladder scans. Evaluation using ground truth data showed that our multi-layer technique yields superior results in contrast to common single surface segmentation. Since the amount of layers is flexible, the most interior regions which only carry little regional information can be excluded from optimization. Together with the linear nature of MLDM optimization our approach outperforms other volumetric segmentation methods in terms of speed.
BISE – STATE OF THE ART in hand with a very slow integration of the different stakeholders within the healthcare system

E-Health is often understood as a means of optimizing work procedures in medical and non-medical areas of healthcare. Increasingly, e-Health is concerned with the attempt of key stakeholders to provide access to healthcare information and services using Internet to make patients actively involved in their treatment. Initial studies have shown that the use of such information sources has a positive effect on a patient’s course of illness and can benefit involved stakeholders. Nevertheless, the risks for patients using Internet-based sources have also begun to emerge, such as the difficulty of guaranteeing authenticity of information. This article provides an overview of the state of research in the field of Internet-based health information.
PASTEL: Parasitic Matching-Driven Placement and Routing of Capacitor Arrays With Generalized Ratios in Charge-Redistribution SAR-ADCs

The charge-redistribution data converter topology is constructed from an array of parallel-connected capacitors with a specific capacitor ratio, and is a fundamental component of successive approximation register (SAR)-analog-to-digital converter (ADC) architectures. This paper presents complementary placement and routing algorithms for such capacitor arrays with the goal of nonlinearity minimization in the target SAR-ADC architecture. Starting from a state-of-the-art static nonlinearity model and its accompanying placement method, generalizations are made for both binary- and nonbinary-weighted capacitor ratios. Taking the generalized nonlinearity model and capacitor routing complexity into consideration, an improved placement method was developed, augmented with a matching-based routing technique driven by routing length adjustment. Analytical results compare the new methodology to the state-of-the-art, achieving superior resolution, linearity, and area.
De novo mutations in Congenital Heart Disease with Neurodevelopmental and Other Birth Defects

Congenital heart disease (CHD) patients have increased prevalence of extra-cardiac congenital anomalies (CA) and risk of neurodevelopmental disabilities (NDD). Exome sequencing of 1,213 CHD parent-offspring trios identified an excess of protein-damaging de novo mutations, especially in genes highly expressed in developing heart and brain. These mutations accounted for 20% of patients with CHD, NDD and CA but only 2% with isolated CHD. Mutations altered genes involved in morphogenesis, chromatin modification, and transcriptional regulation, including Homsy et al. Page 2 Science. Author manuscript; available in PMC 2016 June 02. A uhor M anscript
A novel image zero-watermarking scheme based on DWT-BN-SVD

This paper presents, a novel watermarking scheme for digital images which overcomes the problems associated with singular value decomposition. Here, the singular values of the host image are modified using the principal components of the watermark in the DWT domain for providing copyright protection as well as reliability. This method accomplishes with an incorporation of fractional singular values in the scheme for finding the optimum scaling factors for efficient robustness and the fidelity of the scheme. By using this method we could eliminate the false positive problem and diagonal line problem which were found in the traditional singular value decomposition, the proposed scheme is tested under various forms of image processing attacks like noise addition, median filtering, JPEG compression, Geometric cropping Experimental results are provided to illustrate that the proposed scheme succeeded in providing copyright protection.
Classical solutions and stability results for Stokesian Hele-Shaw flows

In this paper we study a mathematical model for the motion of a Stokesian fluid in a Hele-Shaw cell surrounded by a gas at uniform pressure. The model is based on a non-Newtonian version of Darcy’s law for the bulk fluid, as suggested in [9, 12]. Besides a general existence and uniqueness result for classical solutions, it is also shown that classical solutions exist globally and tend to circles exponentially fast, provided the initial data is sufficiently close to a circle. Finally, our analysis discloses the influence of surface tension and the effective viscosity on the rate of convergence. Mathematics Subject Classification (2000). 35J65, 35K55, 35R35, 42A45, 76A05.