Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel approach for combined Joint Call Admission Control and Dynamic Bandwidth Adaptation in heterogeneous wireless networks

Due to the fast evolution of mobile devices, a high penetration of notebooks and smart-phones, and the growing demand for high rate services, e.g. mobile video and P2P services, modern radio access networks require efficient means for call admission control and radio resource management. In particular, network operators, managing co-deployed, heterogeneous access technologies, are interested in an optimized utilization of their infrastructure while maximizing their revenue. For ensuring maximum operator gain and optimized system performance, we propose to handle diverse user service requests, ranging from voice only to bandwidth-consuming streaming services, collaboratively by a combined, heuristic Joint Call Admission Control (JCAC) and Dynamic Bandwidth Adaptation (DBA) approach. This approach aims at maximizing overall system utilization and, hence, the mobile network operator's revenues, while keeping the blocking and dropping rates at acceptably low levels, and ensuring that Quality of Service (QoS) demands of the diverse services are met. Therefore, we introduce a novel utility definition of services which is used in the proposed algorithms. It represents a generic measurement of the profit that is gained by the mobile network operator. The JCAC and DBA algorithms are realized tightly coupled and ensure that a maximum number of requested services can be supported by the cooperatively managed, wireless systems in the considered service area. Further, system utilization is optimized by improving the QoS characteristics of the already granted elastic services. In order to evaluate the algorithms for a given scenario of co-deployed Long Term Evolution (LTE) and High Speed Packet Access (HSPA) network nodes, an event-driven simulation platform based on OMNeT++ has been developed, including all relevant entities of 3GPP's SAE. The results show an improvement in the overall gained utility of the mobile network operator compared to standard approaches, and optimized system performance w.r. t. utilization as well as acceptable low blocking and dropping rates.
Multitechnique Characterization of a Polyaniline–Iron–Carbon Oxygen Reduction Catalyst

This paper summarizes a XANES, XPS, XRD, and Mo study of an oxygen reduction reaction (ORR) catalyst obtained via a heat treatment of polyaniline, iron, and carbon black. The catalyst was characterized at several critical synthesis stages and following heat treatment at various temperatures. The effect of sulfur during the synthesis was also investigated. XANES linear combination fitting (XANES-LCF) was used to determine the speciation of iron using 16 iron standards. The highest ORR activity was measured with a catalyst heat-treated at 900 °C, with the largest Fe−Nx content, as determined by the XANES-LCF, also characterized by the highest microporosity. An absence or a reduction in the amount of a sulfur-based oxidant in the aniline polymerization was found to lead to an increase in the amount of iron carbide formed during the heat treatment and a decrease in the number of Fe−N4 centers, thus attesting to an indirect beneficial role of sulfur in the catalyst synthesis. Using principal component analysis (PCA), a good correlation was found between the ORR activity and the presence of Fe−Nx structures.
Partially Precomputed A<formula formulatype="inline"> <tex Notation="TeX">$^{\ast}$</tex></formula>

A* is a commonly used technique for finding shortest paths for navigation in video games. We propose partially precomputed A* (PPA*), which is much faster than A* at runtime, and uses much less memory than completely precalculating all shortest paths with an algorithm such as Floyd-Warshall. At runtime, PPA* is very similar to A*, so it is simple and safe to integrate into existing video game code bases.
Resonant Laboratory and Candela : Spreading Your Visualization Ideas to the Masses

Visualization practitioners are constantly developing new, innovative ways to visualize data. However, while many of these new techniques are general enough to be useful to a wide audience, many of them do not make it into production in professional systems. There are many reasons that this happens. Academic researchers often don’t have the funding or time to continue work on tools once a paper has been published. Many tools aren’t engineered to handle real-world datasets—software that we see at conferences like IEEE VIS are often designed as demonstrations of research concepts, not as tools for real data analysts to use. Furthermore, connecting data to these tools is often non-trivial—to even try out a tool with their own data, users often have to follow complex setup procedures, including running shell scripts, moving files to special places, setting up servers or databases, or even programming. In recent years, we have seen dramatic improvements with regard to archiving and reusing basic information visualization techniques through efforts such as bl.ocks. org and Treevis [14]. However, while these archival demonstrations of techniques are giving new users exposure to the rich world of data visualization, actually connecting a dataset to one of these visualizations still requires a degree of expertise beyond most users. We have developed and informally tested two systems that can help solve these two inter-related problems. Candela is a framework and API for creating visualization components for the web that can wrap up new or existing visualizations as needed. Because Candela’s API generalizes the inputs to a visualization, we have also developed a system called Resonant Laboratory that makes it possible for novice users to connect arbitrary datasets to Candela visualizations. Together, these systems enable novice users to explore and share their data with the growing library of state-of-the-art visualization techniques.
Software metrics need to mature into software metrology (recommendations)

If software engineering is to mature into a recognized engineering discipline, it needs to be supported by measures, measurement methods and well tested descriptive and quantitative models. Other disciplines have developed a considerable body of knowledge with respect to measures, measurement instruments and quantitative models using measurement results to analyze relationships across objects and attributes. How does software engineering compare to other fields in this respect? This position paper highlights some current high-level ambiguities in the domain of software metrics, whereas this term is often interpreted with what would be considered multiple definitions; similarly for the expression metrics validation which is used in many ways with different meanings, leaving practitioners confused and researchers with considerable challenge in leveraging other researchers’ contributions on similarly named but distinct issues. To reach maturity, the software engineering knowledge are, referred to as software metrics must mature into software metrology as in other disciplines. This position paper concludes with recommendations for paths to be explored in order to tackle this issue with contributions from the metrology discipline.
A Balancing Act: Whose Interests Do Bias Response Teams Serve?

Abstract:Using the organizational dimension of the multicontextual model for diverse learning environments, this study examined the philosophies and perspectives of bias response team leaders at 19 institutions. Through semi-structured interviews, administrators described theoretical approaches to bias response work that were primarily educational in nature and that aligned with institutional values. However, in the practice of responding to bias, administrators found themselves employing punitive frameworks, managing institutional public relations, and, on occasion, providing educational efforts. This tension between theory and practice created a balancing act for administrators to manage and multiple groups to which they perceived themselves as accountable.
Analysis of Parallel Sub-swarm PSO with the Same Total Particle Numbers

In this paper, we re-visit the parallel PSO schemes and adopt a different perspective to parallelize PSO. In the adopted scheme, the original particle swarm is divided into several sub-swarms under the condition that the total particle numbers are the same, thus keeping nearly the same computational tasks. Each slave processor then individually runs a part of the sub-swarms. Experiments are also conducted to show the property and the performance of the scheme.
Alliances with Competitors: How to Combine and Protect Key Resources?

Our study addresses two main questions: First, what types of alliances do firms tend to create when combining different kinds of resources? Second, what governance mechanisms do firms set up to coordinate and protect resources when they use them for different alliances? We examine 227 alliances between competitors in Asia, North America, and Europe. We first identify two types of alliances: scale alliances in which the partner firms contribute similar resources, and link alliances in which the partners contribute complementary resources. We find that firms contributing R&D and production resources tend to form scale alliances, while firms contributing marketing resources tend to enter into link alliances. We also find that firms are more likely to choose stronger protection mechanisms for link alliances, which create greater appropriation risks, while they tend to seek higher levels of coordination in scale alliances.
Electronic transaction fraud detection based on improved PSO algorithm

Aiming to the problem of how to find the cheating samples of the Electronic transaction, using method of assigning the value on every particle base on the environment, the improved particle swarm optimization (PSO) algorithm is presented to handle this problem. Though the theoretical derivation, the cheating sample is detected in optimization cost and the adaptability and correctness of the algorithm is proofed. The correctness of theoretical derivation is also verified by the experiment.
A recommender system for on-line course enrolment: an initial study

In this paper we report on our work to date concerning the development of a course recommender system for University College Dublin's on-line enrollment application. We outline the factors that influence student choices and propose solutions to address some of the key considerations that are identified. We empirically evaluate our approach using historical student enrolment data and show that promising performance is achieved with our initial design.
Oral Administration of Achyranthis radix Extract Prevents TMA-induced Allergic Contact Dermatitis by Regulating Th2 Cytokine and Chemokine Production in Vivo

Allergic contact dermatitis (ACD) remains a major skin disease in many countries, necessitating the discovery of novel and effective anti-ACD agents. In this study, we investigated the preventive effects of Achyranthis radix extract (AcRE) on trimellitic anhydride (TMA)-induced dermatitis and the potential mechanism of action involved. Oral administration of AcRE and prednisolone (PS) significantly suppressed TMA-induced increases in ear and epidermal thickness, and IgE expression. In addition, abnormal expression of IL-1β and TNF-α protein and mRNA was also significantly attenuated by oral administration of AcRE. Treatment with AcRE also significantly suppressed TMA-induced IL-4 and IL-13 cytokines and mRNA expression in vivo. Moreover, AcRE strongly suppressed TMA-induced IL-4 and IL-5 production in draining lymph nodes, as well as OVA-induced IL-4 and IL-5 expression in primary cultured splenocytes. Interestingly, AcRE suppressed IL-4-induced STAT6 phosphorylation in both primary cultured splenocytes and HaCaT cells, and TMA-induced GATA3 mRNA expression ex vivo. AcRE also suppressed TMA-mediated CCL11 and IL-4-induced CCL26 mRNA expression and infiltration of CCR3 positive cells. The major compounds from AcRE were identified as gentisic acid (0.64 ± 0.2 μg/g dry weight of AcRE), protocatechuic acid (2.69 ± 0.1 μg/g dry weight of AcRE), 4-hydroxybenzoic acid (5.59 ± 0.3 μg/g dry weight of AcRE), caffeic acid (4.21 ± 0.1 μg/g dry weight of AcRE), and ferulic acid (14.78 ± 0.4 ± 0.3 μg/g dry weight of AcRE). Taken together, these results suggest that AcRE has potential for development as an agent to prevent and treat allergic contact dermatitis.
Development of a Titanium Plate for Mandibular Angle Fractures with a Bone Defect in the Lower Border: Finite Element Analysis and Mechanical Test

ABSTRACT Objectives The aim of the present study was to develop a plate to treat mandibular angle fractures using the finite element method and mechanical testing. Material and Methods A three-dimensional model of a fractured mandible was generated using Rhinoceros 4.0 software. The models were exported to ANSYS®, in which a static application of displacement (3 mm) was performed in the first molar region. Three groups were assessed according to the method of internal fixation (2 mm system): two non-locking plates; two locking plates and a new design locking plate. The computational model was transferred to an in vitro experiment with polyurethane mandibles. Each group contained five samples and was subjected to a linear loading test in a universal testing machine. Results A balanced distribution of stress was associated with the new plate design. This plate modified the mechanical behavior of the fractured region, with less displacement between the fractured segments. In the mechanical test, the group with two locking plates exhibited greater resistance to the 3 mm displacement, with a statistically significant difference when compared with the new plate group (ANOVA, P = 0.016). Conclusions The new plate exhibited a more balanced distribution of stress. However, the group with two locking plates exhibited greater mechanical resistance.
ALGORITHM FOR REMOTE SENSING OF TROPOSPHERIC AEROSOL OVER DARK TARGETS FROM MODIS : Collections 005 and 051 : Revision 2 ; Feb 2009 Product ID : MOD 04 / MYD 04

on frequent visits to NASA/GSFC *deceased This document updates the 1996 MOD04 Algorithm Theoretical Basis Document (ATBD-96), describing the algorithms for simultaneous remote sensing of aerosol properties over land and ocean from spectral reflectance observed by EOS-MODIS (both Terra and Aqua). The Collection 5 (C005) algorithm retrieves the aerosol optical depth (AOD or τ−proportional to the aerosol total loading in the vertical column) and proxies for the size distribution (such as Fine-Weighting (FW or η)) of the ambient (undisturbed) aerosol, over most of the globe (oceans and the moist parts of the continents) on a daily basis. These aerosol products are primarily intended for radiative budget and climate applications, but are expected to be relevant for hydrological, oceanographic and air quality applications. The combined ocean/land algorithm takes advantage of the MODIS wide spectral range and high spatial resolution with daily global coverage (e.g., 500 m at 0.47 to 2.12 µm with 250 m at 0.66 and 0.86 µm and 1 km at 1.38 µm). These unique MODIS characteristics allow excellent cloud rejection while maintaining high statistics of cloud free pixels. The wide spectral range permits resolution of aerosol size distribution. The land algorithm described here is a complete overhaul from that described in the ATBD-96. The C005 overland algorithm continues to derive only over sufficiently dark surfaces, but has new surface reflectance parameterizations, aerosol optical models, and assumptions relating to how the 2.12 µm channel relates to surface and surface properties. The C005 ocean algorithm is generally described by the ATBD-96, but we add here a chapter describing the changes to it. Co-located sunphotometer validation is provided for both land and ocean products. The gas (ozone, water vapor and carbon dioxide) absorption corrections to the reflectance are described here. Finally, we include a section describing the structure of the operational product files (i.e. MOD04/MYD04-C005).
Scalable nano-patterning of graphenes using laser shock

Nano-patterning of graphene film by a novel approach making use of laser ablation generated pressure is presented in this paper. Arrays of nanoscale holes were fabricated by applying laser shock pressure on graphene film suspended on well trenches in silicon substrate. Round holes with diameters ranging from 50 to 200 nm on graphene film were successfully punched. The critical pressure was found to be dependent on the diameter of holes. The smaller the diameters, the higher the critical pressure, which was also captured by the molecular dynamic (MD) simulations. The laser shock based approach presented in this paper provides an effective way to pattern graphene film with nanoscale features in an easy, fast, and scalable manner.
Microalgae Isolation and Selection for Prospective Biodiesel Production

Biodiesel production from microalgae is being widely developed at different scales as a potential source of renewable energy with both economic and environmental benefits. Although many microalgae species have been identified and isolated for lipid production, there is currently no consensus as to which species provide the highest productivity. Different species are expected to function best at different aquatic, geographical and climatic conditions. In addition, other value-added products are now being considered for commercial production which necessitates the selection of the most capable algae strains suitable for multiple-product algae biorefineries. Here we present and review practical issues of several simple and robust methods for microalgae isolation and selection for traits that maybe most relevant for commercial biodiesel production. A combination of conventional and modern techniques is likely to be the most efficient route from isolation to large-scale cultivation.
Using mobile communication as a tool for national growth and development

Mobile communication emergence has brought a whole palette of new possibilities in information sharing not only for individual development but also for national growth. New mobile information devices such as Personal Digital Assistants, Smart-phones, i -phones and the like put forward several advantages for personal assistance to the mobile users. They can present up-to-date spatial/non-spatial information in a very individual, dynamic, and flexible way for the mobile users. Mobile communication devices can provide and run many other services and applications which are aimed at presenting to the mobile users the right information in the right moment and at the right place. This improves the economics and strengthens the national growth and development. The evaluations of mobile communication development projects are required in order to have a better understand on its impact on nations’ economic, politics and social growth. The research identifies the roles of mobile communication as a means for partnering with the private and public organisations in order to provide better services and awareness for the national growth and development.
An Alternative Framework of Anisotropic Diffusion for Image Denoising

This paper deals with an anisotropic diffusion based noise removal technique which utilizes the new diffusion function based on tangent sigmoid function. A local edge indicator function based on local structure tensor is also used in the proposed technique, to reduce the noise and detection of edges in digital images. From the experimental results, we observe that the proposed method is better and near to the other state-of-the-art approaches, in terms of both qualitatively and quantitatively. Numerical tests were performed on various images, which are corrupted by Gaussian noise and results illustrate that the proposed approach is more efficient than existing one.
Usage of computer mouse characteristics for identification in web browsing

User behavioural characteristics such as mouse dynamics are present in the web browsing process. Identification of an unauthorized user based on user model containing mouse dynamics patterns might be useful for personalized system. This paper proposes a user modelling process specialized for user identification in browsing the web. We conducted our study in a running e-shop. The experiment is designed to track mouse dynamics characteristics and user's personality profile. We present the results of distinctiveness of individual characteristics among visitors and performance of the identification method.
Accurate Prediction of Transition Energies in Organic Molecules

Least squares support vector machines (LSSVM) has been carried out in order to obtain a statistically meaningful analysis of the extended set of molecules. The combined HF with LSSVM correction approach ? LSSVM/HF? has been applied to evaluate the transition energies of organic molecules. After LSSVM correction, the RMS deviations of the calculated transition energies reduce from 0.91 to 0.26 eV for HF methods. And, this LSSVM/HF is a excellent method to predict transition energies and extend the reliably and efficiently of calculated transition energies.
Speckle modeling and reduction in synthetic aperture radar imagery

A new mathematical framework for modeling speckled imagery is introduced based on embedding the spatial correlation properties of speckled imagery, obtained from statistical optics, into a Markov-random-field (MRP) framework. The model is then used to perform speckle-noise reduction through the utilization of a global energy-minimization algorithm, which consists of simulated annealing in conjunction with the metropolis sampler algorithm. Comparative experimental results using both simulated as well as real synthetic-aperture-radar (SAR) imagery show that the proposed speckle-reduction technique outperforms existing speckle-noise filtering methods. This success is attributable to the ability of the proposed model to capture the physical spatial statistics of speckle within the confines of a MRF framework.
Bounds on Rényi and Shannon Entropies for Finite Mixtures of Multivariate Skew-Normal Distributions: Application to Swordfish (Xiphias gladius Linnaeus)

Mixture models are in high demand for machine-learning analysis due to their computational tractability, and because they serve as a good approximation for continuous densities. Predominantly, entropy applications have been developed in the context of a mixture of normal densities. In this paper, we consider a novel class of skew-normal mixture models, whose components capture skewness due to their flexibility. We find upper and lower bounds for Shannon and Renyi entropies for this model. Using such a pair of bounds, a confidence interval for the approximate entropy value can be calculated. In addition, an asymptotic expression for Renyi entropy by Stirling’s approximation is given, and upper and lower bounds are reported using multinomial coefficients and some properties and inequalities of L p metric spaces. Simulation studies are then applied to a swordfish (Xiphias gladius Linnaeus) length dataset.