Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of the effect of image resolution on automatic face gender and age classification

In this paper, the effect of the image resolution for gender detection and age classification have been analyzed by conducting experiments with facial images that have 10 different image resolutions ranging from 2 × 1 to 329 × 264. K Nearest Neighbor (k-NN), Support Vector Machine (SVM) and Random Forests (RF) classifiers, which have been successfully used in several applications, have been employed to extract gender and age information from the images. Experiments for age classification and gender detection have been performed separately.
Seasonal changes in the age and structure of dissolved organic carbon in Siberian rivers and streams

We examined the age and structural composition of dissolved organic carbon (DOC) transported in the Kolyma River, two large tributaries and several small upland and lowland streams in 2003. The sampling took place under ice through the winter and included the spring flood period. Radiocarbon measurements of the DOC indicated that the bulk of the annual DOC flux was modern in origin (Δ14C > 100‰) and pyrolysis‐gas chromatography/mass spectroscopy techniques showed high concentration of terrestrial lignin monomers consistent with vigorous leaching of surface horizons during the spring thaw. By September 2003 however, little terrestrial lignin was present and the radiocarbon age became significantly older (Δ14C < 0‰) indicating that the mechanism of DOC generation transitions from surface to deeper soils or other terrestrial sources of old, previously stabilized C.
Light fields from digital hologram displays

The optical mechanism of forming reconstructed images in a hologram loaded on a DMD is identified by measuring the light fields at different distances from a hologram. The light field images make possible to identify the process of forming the reconstructed image, astigmatism, restoring the missing pattern of the hologram, the focusing behavior of Fresnel zone pattern, and depth resolution.
Networked architecture for hybrid electrical energy storage systems

A hybrid electrical energy storage (HEES) system that consists of multiple, heterogeneous electrical energy storage (EES) elements is a promising solution to achieve a cost-effective EES system because no storage element has ideal characteristics. The state-of-the-art HEES systems are based on a shared-bus charge transfer interconnect (CTI) architecture. Consequently, they are quite limited in scalability which is a function of the number of EES banks. This paper is the first introduction of a HEES system based on a networked CTI architecture, which is highly scalable and is capable of accommodating multiple, concurrent charge transfers. The paper starts by presenting a router architecture for the networked CTI and an effective on-line routing algorithm for multiple charge transfers. In the proposed algorithm, negotiated congestion (NC) routing for multiple charge transfers is performed and any lack of routing resources is addressed by merging two or more charge transfers while maximizing the overall energy efficiency by setting the optimal voltage level for the shared CTI. Examples of the proposed networked CTI are presented and the efficacy of the routing algorithm is demonstrated on a mesh-grid networked CTI.
Compressing Pattern Databases with Learning

A pattern database (PDB) is a heuristic function implemented as a lookup table. It stores the lengths of optimal solutions for instances of subproblems. Most previous PDBs had a distinct entry in the table for each subproblem instance. In this paper we apply learning techniques to compress PDBs by using neural networks and decision trees thereby reducing the amount of memory needed. Experiments on the sliding tile puzzles and the TopSpin puzzle show that our compressed PDBs significantly outperforms both uncompressed PDBs as well as previous compressing methods. Our full compressing system reduced the size of memory needed by a factor of up to 63 at a cost of no more than a factor of 2 in the search effort.
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This paper discusses how to reconfigure systems in which components have mismatches in their behavioural specifications. We are interesting in performing component substitution without stopping the system, though we assume components are not designed with reconfiguration capabilities in mind. We also assume that components may need to be adapted before interacting with the system. The contributions are the enumeration of requirements to allow runtime component substitution and different compatibility notions that are adequate to component substitution under behavioural adaptation. Finally, we illustrate these requirements and compatibility notions in a case-study of a client/server system where the server needs to be substituted by a new one. Classic compatibility notions fail to find a new server because the only available one implements a different behavioural interface. We show how our compatibility notions could be used in order to let the system keep on working.
Feature-based watermark localization in digital capture systems

The “Internet of Things” is an appealing concept aiming to assign digital identity to both physical and digital everyday objects. One way of achieving this goal is to embed the identity in the object itself by using digital watermarking. In the case of printed physical objects, such as consumer packages, this identity can be later read from a digital image of the watermarked object taken by a camera. In many cases, the object might occupy only a small portion of the the image and an attempt to read the watermark payload from the whole image can lead to unnecessary processing. This paper proposes a statistical learning-based algorithm for localizing watermarked physical objects taken by a digital camera. The algorithm is specifically designed and tested on watermarked consumer packages read by an off-the-shelf barcode imaging scanner. By employing simple noise-sensitive features borrowed from blind image steganalysis and a linear classifier, we are able to estimate probabilities of watermark presence in every part of the image significantly faster than running a watermark detector. These probabilities are used to pinpoint areas that are recommended for further processing. We compare our adaptive approach with a system designed to read watermarks from a set of fixed locations and achieve significant savings in processing time while improving overall detector robustness.
Assigning putative protein products to SAGE tags by determining their predisposition to associate with clusters which exhibit functional enrichment

The fact that genes associated with parts of cellular machinery can be collectively controlled means that it is theoretically possible to assign phenotypic function to certain genes by analysis of their expression profiles. However the multi-faceted nature of genetic function, and the complexities of the signal and noise interactions that are inherent in a cell, means that whilst illustrations of such mediated control (for example the repression of translational machinery) have been well studied it is difficult to use them to reliably ascertain genetic function for individual genes. In this paper the Gene Ontology is used to classify and then compare clusters from different sets of SAGE samples to discover which tags have a strong predisposition to reside in a particular type, or types, of cluster. This predisposition is then used to resolve ambiguities in tag assignment that have arisen by using sequence homology to predict protein products.
JML Support for Primitive Arbitrary Precision Numeric Types: Definition and Semantics

The Java Modeling Language (JML) is a notation for specifying and describing the detailed design and implementation of Java modules. An important language design goal of JML has been to preserve the semantics of Java to the extent possible. Thus, in particular, Java numeric expressions have the same meaning in JML. We illustrate how such a semantics fails to match the expectations of specification authors and readers who generally think in terms of arbitrary precision arithmetic (rather than the fixed precision provided by Java). As a result, an unusually high number of published JML specifications are invalid or inconsistent, including cases from the security critical area of smart card applications. We briefly examine JML’s ancestry and language design principles; this helps to explain the origin of the semantic gap between user expectations and the current meaning given to JML numeric expressions. With the objective of better matching user expectations we introduce JMLb, a variant of JML supporting primitive arbitrary precision numeric types as well as “math modes” to control the semantics of arithmetic expressions. This is done in a manner that is consistent with JML’s language design goals. A semantics of JMLb expressions is given by means of an embedding into PVS. The problem presented here will arise in the design of most interface specification languages that must deal with, e.g., mathematical integers in specifications and their fix precision approximations in code. We examine how the problem may manifest itself in other languages (such as Eiffel, Spark and the UML/OCL-Java notation of the KeY project) and comment on the applicability of our solution.
Crossvalidation in Brain Imaging Analysis

Crossvalidation is a method for estimating predictive performance and adjudicating between multiple models. On each of k folds of the process, k-1 of k independent subsets of the data (training set) are used to fit the parameters of each model and the left-out subset (test set) is used to estimate predictive performance. The method is statistically efficient, because training data are reused for testing and performance estimates combined across folds. The method requires no assumptions, provides nearly unbiased (slightly conservative) estimates of predictive performance, and is generally applicable because it amounts to a direct empirical test of each model.
Professional learning enhanced by technology for elementary school teachers for Culture and Mathematics: A design research project

Design research or experiment is a relatively new research methodology in education and other areas. A design for professional learning for elementary teachers to recognise and use cultural mathematics in schools has been developed and will be tested through three phases. In addition, a design for technology delivery has also been developed and will be assessed. Evaluation at each phase will lead to improvements in the designs. The design takes account of three ecological areas of Papua New Guin .
PhenoScanner: a database of human genotype–phenotype associations

Abstract Summary: PhenoScanner is a curated database of publicly available results from large-scale genetic association studies. This tool aims to facilitate ‘phenome scans’, the cross-referencing of genetic variants with many phenotypes, to help aid understanding of disease pathways and biology. The database currently contains over 350 million association results and over 10 million unique genetic variants, mostly single nucleotide polymorphisms. It is accompanied by a web-based tool that queries the database for associations with user-specified variants, providing results according to the same effect and non-effect alleles for each input variant. The tool provides the option of searching for trait associations with proxies of the input variants, calculated using the European samples from 1000 Genomes and Hapmap. Availability and Implementation: PhenoScanner is available at www.phenoscanner. medschl.cam. ac.uk. Contact: jrs95@medschl.cam. ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
Structurally discriminative graphical models for automatic speech recognition - results from the 2001 Johns Hopkins Summer Workshop

In recent years there has been growing interest in discriminative parameter training techniques, resulting from notable improvements in speech recognition performance on tasks ranging in size from digit recognition to Switchboard. Typified by Maximum Mutual Information training, these methods assume a fixed statistical modeling structure, and then optimize only the associated numerical parameters (such as means, variances, and transition matrices). In this paper, we explore the significantly different methodology of discriminative structure learning. Here, the fundamental dependency relationships between random variables in a probabilistic model are learned in a discriminative fashion, and are learned separately from the numerical parameters. Tn order to apply the principles of structural discriminability, we adopt the framework of graphical models, which allows an arbitrary set of variables with arbitrary conditional independence relationships to be modeled at each time frame. We present results using a new graphical modeling toolkit (described in a companion paper) from the recent 2001 Johns Hopkins Summer Workshop. These results indicate that significant gains result from discriminative structural analysis of both conventional MFCC and novel AM-FM features on the Aurora continuous digits task.
Chemoprevention of Chemically Induced Skin Tumorigenesis by Ligand Activation of Peroxisome Proliferator–Activated Receptor-β/δ and Inhibition of Cyclooxygenase 2

Ligand activation of peroxisome proliferator–activated receptor-β/δ (PPARβ/δ) and inhibition of cyclooxygenase-2 (COX2) activity by nonsteroidal anti-inflammatory drugs (NSAID) can both attenuate skin tumorigenesis. The present study examined the hypothesis that combining ligand activation of PPARβ/δ with inhibition of COX2 activity will increase the efficacy of chemoprevention of chemically induced skin tumorigenesis over that observed with either approach alone. To test this hypothesis, wild-type and Pparβ/δ-null mice were initiated with 7,12-dimethylbenz[a]anthracene (DMBA), topically treated with 12-O-tetradecanoylphorbol-13-acetate to promote tumorigenesis, and then immediately treated with topical application of the PPARβ/δ ligand GW0742, dietary administration of the COX2 inhibitor nimesulide, or both GW0742 and nimesulide. Ligand activation of PPARβ/δ with GW0742 caused a PPARβ/δ-dependent delay in the onset of tumor formation. Nimesulide also delayed the onset of tumor formation and caused inhibition of tumor multiplicity (46%) in wild-type mice but not in Pparβ/δ-null mice. Combining ligand activation of PPARβ/δ with dietary nimesulide resulted in a further decrease of tumor multiplicity (58%) in wild-type mice but not in Pparβ/δ-null mice. Biochemical and molecular analysis of skin and tumor samples show that these effects were due to the modulation of terminal differentiation, attenuation of inflammatory signaling, and induction of apoptosis through both PPARβ/δ-dependent and PPARβ/δ-independent mechanisms. Increased levels and activity of PPARβ/δ by nimesulide were also observed. These studies support the hypothesis that combining ligand activation of PPARβ/δ with inhibition of COX2 activity increases the efficacy of preventing chemically induced skin tumorigenesis as compared with either approach alone. Mol Cancer Ther; 9(12); 3267–77. ©2010 AACR.
Both Sides of Corporate Diversification: The Value Impacts of Geographic and Industrial Diversification

This paper examines the effect of geographic and industrial diversification on firm value for a sample of over 20,000 firm-year observations of U.S. corporations from 1987-1993. Our" multivariate tests indicate the average value of a firm with international operations is 2.2% higher than comparable domestic single activity firms, while the average value of a firm with activities in multiple industrial segments is 5.4% lower than a portfolio of comparable focused domestic firms in similar activities. More importantly, we demonstrate that failure to control simultaneously for both dimensions of diversification results in over-estimation of the negative value impact of industrial diversification, but has little impact on estimates of the positive value impact of geographic diversification.
A Multidimensional Companding Scheme for Source Coding with a Perceptually Relevant Distortion Measure

In this thesis, we develop a multidimensional companding scheme for the preceptual distortion measure by S. van de Par [1]. The scheme is asymptotically optimal in the sense that it has a vanishing rate-loss with increasing vector dimension. The compressor operates in the frequency domain: in its simplest form, it pointwise multiplies the Discrete Fourier Transform (DFT) of the windowed input signal by the square-root of the inverse of the masking threshold, and then goes back into the time domain with the inverse DFT. The expander is based on numerical methods: we do one iteration in a fixed-point equation, and then we fine-tune the result using Broyden’s method. Additionally, we will show simulations which corroborate the approximations and results of the theoretical derivations. [1] S. van de Par, A. Kohlrausch, R. Heusdens, J. Jensen, and S. Jensen. A perceptual model for sinusoidal audio coding based on spectral integration. EURASIP Journal on Applied Signal Processing, 2005(9):1292–1304, June 2005.
EdgES: the Common Boundary between Service and Desktop Grids

Service grids and desktop grids are both promoted by their supportive communities as great solutions for solving the available compute power problem and helping to balance loads across network systems. Little work, however, has been undertaken to blend these two technologies together. In this paper we introduce a new EU project, that is building technological bridges to facilitate service and desktop grid interoperability. We provide a taxonomy and background into service grids, such as EGEE and desktop grids or volunteer computing platforms, such as BOINC and XtremWeb. We then describe our approach for identifying translation technologies between service and desktop grids. The individual themes discuss the actual bridging technologies employed and the distributed data issues surrounding deployment.
Inside the Selection Box: Visualising active learning selection strategies

Visualisations can be used to provide developers with insights into the inner workings of interactive machine learning techniques. In active learning, an inherently interactive machine learning technique, the design of selection strategies is the key research question and this paper demonstrates how spring model based visualisations can be used to provide insight into the precise operation of various selection strategies. Using sample datasets, this paper provides detailed examples of the differences between a range of selection strategies.
Eventual Consistent Databases : State of the Art Mawahib

One of the challenges of cloud programming is to achieve the right balance between the availability and consistency in a distributed database. Cloud computing environments, particularly cloud databases, are rapidly increasing in importance, acceptance and usage in major applications, which need the partition-tolerance and availability for scalability purposes, but sacrifice the consistency side (CAP theorem). In these environments, the data accessed by users is stored in a highly available storage system, thus the use of paradigms such as eventual consistency became more widespread. In this paper, we review the state-of-the-art database systems using eventual consistency from both industry and research. Based on this review, we discuss the advantages and disadvantages of eventual consistency, and identify the future research challenges on the databases using eventual consistency. TYPE OF PAPER AND
A Novel Web Service Directory Framework for Mobile Environments

Mobile devices are evolving as a new computing platform and a common means to provide access and process digital information. In the move to achieve ubiquitous computing, the role of mobile devices and web services cannot be understated. Mobile devices are predominantly in use for accessing web services. The same mobile devices are now becoming a feasible option for small and medium size enterprises to host and provide personalized web services to clients. The motivation being the minimal infrastructure requirements and configuration costs. Technology today enables the provision of web services over hand-held mobile devices, realizing a web based service-oriented architecture in a mobile environment. For this, an efficient service discovery mechanism is required. It is difficult to adapt traditional approaches of managing web service directory for mobile environments, this is mainly due to the dynamic arrivals/departures of mobile devices in network zones. In this paper, we propose a model for web services in mobile environments to maintain a service directory using the XMPP (eXtensible Messaging and Presence Protocol). The proposed model enables mobile devices to manage web service directory without requiring high-end computers and high management cost. This paper presents proposed architecture, design concept, system components and workflow of the framework. Moreover, a comparative study of the proposed approach and the traditional UDDI (Universal Description, Discovery, and Integration) registry is presented.
Biometric Methods for Advanced Strategic Data Sharing Protocols

This paper will present new ways of using biometric pattern for creation of cryptographic protocols, dedicated for strategic information sharing and distribution. Such methods allow to protect confidential data, and perform intelligent and secure information management in different decision structures. Development of such algorithms will enable reconstruction of secured information exclusively by authorized parties, which received accessing grants for secret information reconstruction.
SNP (–617C>A) in ARE-Like Loci of the NRF2 Gene: A New Biomarker for Prognosis of Lung Adenocarcinoma in Japanese Non-Smoking Women

Purpose The transcription factor NRF2 plays a pivotal role in protecting normal cells from external toxic challenges and oxidative stress, whereas it can also endow cancer cells resistance to anticancer drugs. At present little information is available about the genetic polymorphisms of the NRF2 gene and their clinical relevance. We aimed to investigate the single nucleotide polymorphisms in the NRF2 gene as a prognostic biomarker in lung cancer. Experimental Design We prepared genomic DNA samples from 387 Japanese patients with primary lung cancer and detected SNP (c.–617C>A; rs6721961) in the ARE-like loci of the human NRF2 gene by the rapid genetic testing method we developed in this study. We then analyzed the association between the SNP in the NRF2 gene and patients’ overall survival. Results Patients harboring wild-type (WT) homozygous (c.–617C/C), SNP heterozygous (c.–617C/A), and SNP homozygous (c.–617A/A) alleles numbered 216 (55.8%), 147 (38.0%), and 24 (6.2%), respectively. Multivariate logistic regression models revealed that SNP homozygote (c.–617A/A) was significantly related to gender. Its frequency was four-fold higher in female patients than in males (10.8% female vs 2.7% male) and was associated with female non-smokers with adenocarcinoma. Interestingly, lung cancer patients carrying NRF2 SNP homozygous alleles (c.–617A/A) and the 309T (WT) allele in the MDM2 gene exhibited remarkable survival over 1,700 days after surgical operation (log-rank p = 0.021). Conclusion SNP homozygous (c.–617A/A) alleles in the NRF2 gene are associated with female non-smokers with adenocarcinoma and regarded as a prognostic biomarker for assessing overall survival of patients with lung adenocarcinoma.