Miracle-dz/UniFAR-FTUs huggingface dataset:
Strategic approach for Multiple-MLP Ensemble Re-RX algorithm

In this paper, we review all our work since 2012 and propose a strategic approach for the Multiple-MLP Ensemble Re- RX algorithm. We first describe the background and procedures of the Recursive-Rule Extraction (Re-RX) algorithm family and its variants, including the Multiple-MLP Ensemble Re-RX algorithm (“Multiple-MLP Ensemble”), which uses the Re-RX algorithm as its core. The proposed strategic approach consists of two processes: non-pruning for the trained neural network ensembles without continuous attributes and a relaxed rule generation scheme using continuous attributes to extract extremely accurate, comprehensible, and concise rules for multi-class mixed datasets (i.e., discrete attributes and continuous attributes). We conducted experiments to find rules for seven kinds of multi-class mixed datasets and compared the accuracy, comprehensibility, and conciseness for the Multiple-MLP Ensemble Re-RX algorithm. The strategic approach for the Multiple-MLP Ensemble Re-RX algorithm outperformed the original Multiple-MLP Ensemble Re- RX algorithm. These results confirm that the strategic approach for the Multiple-MLP Ensemble algorithm facilitates the migration from existing data systems toward new accurate analytic systems and Big Data.
Embedded Device Forensics and Security

While the increasing digitalization of our society and amalgamation of embedded devices into the ever-increasing facets of our daily life (e.g., in smart and intelligent vehicles, smart cities and smart nations, and critical infrastructure sectors) have resulted in improved productivity and quality of life, the trend has also resulted in a trend of increasing frequency and sophistication of cyber exploitation and cyber threats. Hence, there is a need for coordinated efforts from the research community to address resulting concerns using both cryptographic and non-cryptographic solutions, such as those presented in this special section.
Image Features Extraction Using The Dual-Tree Complex Wavelet Transform

In his/her daily round each man feels the necessity to use a database containing images. The user’s basic requirements reduce to the following. The image features extraction rate to be as much as possible, the accuracy degree to be high as well as the time for comparison between the image features to be minimum. Besides, for the needs of the modern image databases it is important the extracted features to be rotation and noise resistant. With the present paper we introduce a novel algorithm for image feature extraction using DT CWT for a CBIR system. The performed experiments show that the algorithm produces results which satisfy the conditions for feature extraction rate, feature vector length and high information concentration necessary for a CBIR system. Key-Words: The Dual-Tree Complex Wavelet Transform, DT CWT, wavelet transform, feature extraction, feature vector, image signature, DT CWT coefficients, wavelet coefficients, image decomposition
Simple nonlinear magnetic analysis for permanent-magnet motors

This paper presents a simple nonlinear magnetic analysis for a surface-mounted permanent-magnet synchronous motor as an assistant design tool of finite-element analysis (FEA). The equivalent magnetic circuit of the motor used in the proposed analysis is composed of the saturable permeance tips in the stator teeth for considering the local magnetic saturation. As a result, the proposed analysis is capable of calculating the flux distribution and the torque characteristics in the presence of magnetic saturation. The effectiveness of the proposed analysis is verified by comparing with three-dimensional (3-D) FEA in terms of the analytical accuracy. The computation time is greatly reduced as short as 1.5 s while the 3-D FEA requires as much as 32 min for the same evaluation.
Experiences in porting the SVP concurrency model to the 48-core Intel SCC using dedicated copy cores

The Single-chip Cloud Computer (SCC) is a 48-core experimental processor created by Intel Labs targeting the manycore research community. It has hardware support for sending short messages between cores, while large messages have to go through off-chip shared memory. In this paper we discuss our implementation of the SVP model of concurrency on this architecture, and how we deal with its distributed memory design and communication bottlenecks. We employ our previously developed copy core technique and show which approaches show scalable performance against our original implementation.
Impact of HGAPSO in Optimizing Tree Based Multicast Routing Protocol for MANETs

Multicast communication in Mobile Ad-hoc Networks (MANETs) is emerging for wireless group communication which includes applications such as multipoint data dissemination and multiparty conferencing which made the analytical design and development of the MANETs in a very efficient manner. For MANETs there are several multicast routing protocols are proposed, but they perform well under specific scenarios only. The topology of a MANET changes adequately due to the random mobility of network nodes, unlike the wired network which is static. Due to the lack of redundancy in multipath and multicast structures, the multicast routing protocols are vulnerable to the component failure in ad-hoc networks. Due to this fact, route selection becomes a tragedy in MANETs. So it is the dire need to optimize the route selection procedure. HGAPSO is an emerging hybrid optimizing tool that is used to find an optimum solution among a population of possibilities. In this paper we attempt to propose a new HGAPSO (Hybrid Genetic Algorithm Particle Swarm Optimization) based optimized MAODV, which improves the performance in the routing messages for multicast applications.
A tweet summarization method based on a keyword graph

There are a huge number of posts on the micro blogs such as Twitter and thus it can be an important information source of various domains. However, the information density of each post, tweet, is too low because the length of tweets is too short. Due to the huge amount and low information density, it is hard to obtain useful information from Twitter such as the public opinion trend. Considering these characteristics of tweets, we propose a novel tweet summarization method. The proposed method first finds the strongly related groups of words based on keyword graphs. In the graphs, the frequent words are the vertexes and the co-occurrences are the edges. We use the maximum k-clique method to find strongly related groups of words, and summarize the tweets which include the words in groups. We confirmed the proposed method is effective for summarizing of tweets and is superior to the existing method with the experiments.
Digital Generation and Phasing of Transmitter Signals for SuperDARN Class Radars

It is planned that the TIGER N.Z. radar will be a digital evolution of the current analog system, where the phasing matrix for both transmitter and receiver arrays, and the receiver architecture will be implemented in Field Programmable Gate Array (FPGA) technology. Producing a fully digital system in FPGA technology allows a different solution to the current analog approach. An added challenge is the utilization of the DSP techniques such as multirate filters to enhance the performance of the implementation. In this paper we discuss our proposal for a digital SuperDARN radar. Our initial investigations are presented, which we believe not only demonstrate that the concept is feasible, but that a digital radar will provide many benefits to the SuperDARN community.
PIBA-DIBA or How to Blend the Digital with the Physical

Blended interaction often is about blending the physical with the digital. In contrast to common discussions of blending that focus on the commonality of the input domains we focus on the unique features of interacting with physical and digital artifacts. We propose PIBA-DIBA lists (Physical Is Better At – Digital Is Better At) that capture the strengths of using the physical and digital realms in blended interaction design. Thus, PIBA-DIBA lists can act as a collection of " optimality patterns " that are focused on the uniqueness of both realms and can help in the analysis, design and evaluation of blended interaction designs.
Locally computable approximations for spectral clustering and absorption times of random walks

We address the problem of determining a natural local neighbourhood or “cluster” associated to a given seed vertex in an undirected graph. We formulate the task in terms of absorption times of random walks from other vertices to the vertex of interest, and observe that these times are well approximated by the components of the principal eigenvector of the corresponding fundamental matrix of the graph’s adjacency matrix. We further present a locally computable gradient-descent method to estimate this Dirichlet-Fiedler vector, based on minimising the respective Rayleigh quotient. Experimental evaluation shows that the approximations behave well and yield well-defined local clusters.
Matrix-matrix multiplication on heterogeneous platforms

In this paper, we address the issue of implementing matrix-matrix multiplication on heterogeneous platforms. We target two different classes of heterogeneous computing resources: heterogeneous networks of workstations, and collections of heterogeneous clusters. Intuitively, the problem is to load balance the work with different-speed resources while minimizing the communication volume. We formally state this problem and prove its NP-completeness. Next we introduce a (polynomial) column-based heuristic, which turns out to be very satisfactory: we derive a theoretical performance guarantee for the heuristic, and we assess its practical usefulness through MPI experiments.
Motion segmentation using feature selection and subspace method based on shape space

Motion segmentation using feature correspondences can be regarded as a combinatorial problem. A motion segmentation algorithm using feature selection and subspace method is proposed to solve the combinatorial problem. Feature selection is carried out as computation of a basis of the linear space that represents the shape of objects. Features can be selected from "each" object "without segmentation information" by keeping the correspondence of basis vectors to features. Only four or less features of each object are used; the combination in segmentation is reduced by feature selection. Thus the combinatorial problem can be solved without optimization. The remaining features in selection are classified using the subspace method based on the segmentation result of selected features. Experiments are done to consider the usefulness of the proposed method.
An unsplit convolutional perfectly matched layer technique improved at grazing incidence for the viscoelastic wave equation

SUMMARY In the context of the simulation of wave propagation, the perfectly matched layer (PML) absorbing boundary layer has proven to be efficient to absorb non-grazing incidence waves. However, the classical discrete PML cannot efficiently absorb waves reaching the absorbing layer at grazing incidence. This is observed, for instance, in the case of thin mesh slices, or in the case of sources located close to the absorbing boundaries or receivers located at large offset. In order to improve the PML efficiency at grazing incidence we derive an unsplit convolutional PML (CPML) for a fourth-order staggered finite-difference numerical scheme applied to the 3-D viscoelastic seismic wave equation. The time marching equations of the standard linear solid mechanisms used do not need to be split and only the memory variables associated with velocity derivatives are stored at each time step. This is important in the case of more than one damping mechanism. Memory storage is reduced by more than 70 per cent in the PML regions in 3-D simulations compared to split PMLs optimized at grazing incidence. We validate the technique based on a benchmark performed in a thin mesh slice.
Validation of an FFQ to assess short-term antioxidant intake against 30 d food records and plasma biomarkers

Abstract Objective To validate a brief FFQ developed for capturing short-term antioxidant intake in a sample of US college students. Design A seventy-four-item antioxidant FFQ was developed based on major antioxidant sources in the American diet. The FFQ was validated against 30 d food records (FR) and plasma antioxidant concentrations. The reliability of the FFQ was evaluated by two FFQ administered at a 1-month interval. Settings University of Connecticut, CT, USA. Subjects Sixty healthy college students. Results Estimates of dietary antioxidants from the FFQ were moderately to highly correlated with those estimated from the 30 d FR (r = 0·29–0·80; P < 0·05) except for γ-tocopherol and β-cryptoxanthin. Total antioxidant capacity from diet only or from diet and supplements estimated by the 30 d FR and FFQ were highly correlated (r = 0·67 and 0·71, respectively; P < 0·0001). The FFQ categorized 91 % of participants into the same or adjacent tertiles of antioxidant intake as the 30 d FR. Most dietary carotenoids estimated from the FFQ were correlated with plasma levels (P < 0·05). Correlation coefficients for test–retest reliability ranged from 0·39 to 0·86. More than 94 % of the participants were classified in the same or adjacent tertiles between the two administrations of the FFQ. Conclusions The brief FFQ demonstrated reasonable validity for capturing a comprehensive antioxidant intake profile. This FFQ is applicable in epidemiological or clinical studies to capture short-term antioxidant intake or to simply document the variations of antioxidant intake in intervention trials. Cross-validation studies are warranted in other target populations.
Behavior therapy and sibutramine for the treatment of adolescent obesity: a randomized controlled trial.

CONTEXT Adolescent obesity is becoming a national public health problem. Weight-loss medications including sibutramine facilitate weight control in adults and could be used with obese adolescents in combination with behavior therapy (BT). OBJECTIVE To examine whether increased weight loss in obese adolescents is induced when sibutramine is added to a family-based, behavioral weight control program. DESIGN, SETTING, AND PARTICIPANTS Randomized, double-blind, placebo-controlled trial consisting of 82 adolescents aged 13 to 17 years with a body mass index (BMI) of 32 to 44 conducted from March 1999 to August 2002 at a university-based clinic for 6 months, followed by open-label treatment during months 7 to 12. INTERVENTIONS For the first 6 months, participants received either BT and sibutramine or BT and placebo. From months 7 to 12, all participants received sibutramine in open-label treatment. MAIN OUTCOME MEASURES Percentage change in BMI; systolic and diastolic blood pressure and pulse; and hunger. RESULTS In intention-to-treat analysis at month 6, participants in the BT and sibutramine group lost a mean (SD) of 7.8 kg (6.3 kg) and had an 8.5% (6.8%) reduction in BMI, which was significantly more than weight loss of 3.2 kg (6.1 kg) and reduction in BMI of 4.0% (5.4%) in the BT and placebo group. Significantly greater reductions in hunger (P =.002) also were reported by participants who received BT and sibutramine. From months 7 to 12, adolescents initially treated with sibutramine gained 0.8 kg (10.5 kg) with continued use of the medication, whereas those who switched from placebo to sibutramine lost an additional 1.3 kg (5.4 kg). Medication dose was reduced (n = 23) or discontinued (n = 10) to manage increases in blood pressure, pulse rate, or other symptoms. CONCLUSIONS The addition of sibutramine to a comprehensive behavioral program induced significantly more weight loss than did BT and placebo. Until more extensive safety and efficacy data are available, medications for weight loss should be used only on an experimental basis in adolescents and children.
The work-related well-being of social workers: Framing job demands, psychological well-being, and work engagement

Summary Social workers’ occupational health has become a central theme in the psychosocial literature. This study aimed at exploring how specific job demands and psychological well-being are related to work engagement. A sample of 140 Italian social workers was analyzed in accordance with the job demands–resources model. Participants were asked to complete a written questionnaire containing several measurement scales. Findings Multiple regression analyses showed that social workers’ psychological well-being was positively related to work engagement. Moderation analyses also indicated that, when psychological well-being was high (vs. low), job demands were associated to higher levels of work engagement, thus highlighting the buffering role of psychological well-being as a specific personal resource. When job demands were high (vs. low), the psychological well-being appeared to be strongly related to lowest levels of work engagement, showing that high job demands could reduce the fostering role of psychological well-being on social workers’ work engagement. Applications While administration of job demands may often be difficult in social work contexts, managers should be encouraged, as part of a systemic approach to training, to promote specific measures for improving social workers’ psychological well-being as a personal resource for promoting work engagement.
Navigation Analysis and Navigation Design in OOH and UWE ?

This technical report supplements the paper entitled ’Conceptual Navigation Analysis: a device and platform independent navigation specification’. It presents how a navigation analysis model can be integrated in two well-known user-centered conceptual modeling approaches, namely OO-H and UWE. Our aim with this integration process is to illustrate how other user-oriented hypermedia modeling proposals might also include a similar navigation analysis model as part of their specification. Also, this paper discusses the kind of restrictions that the provision of a navigation analysis model may impose on underlying design navigation models. We claim that a navigation analysis model such as the one presented in the main paper might substitute, or at least complement, the domain structural model on which most hypermedia modeling proposals are currently basing its navigation definition.
Fluid Flow Complexity in Fracture Networks: Analysis with Graph Theory and LBM

Through this research, embedded synthetic fracture networks in rock masses are studied. To analysis the fluid flow complexity in fracture networks with respect to the variation of connectivity patterns, two different approaches are employed, namely, the Lattice Boltzmann method and graph theory. The Lattice Boltzmann method is used to show the sensitivity of the permeability and fluid velocity distribution to synthetic fracture networks' connectivity patterns. Furthermore, the fracture networks are mapped into the graphs, and the characteristics of these graphs are compared to the main spatial fracture networks. Among different characteristics of networks, we distinguish the modularity of networks and sub-graphs distributions. We map the flow regimes into the proper regions of the network's modularity space. Also, for each type of fluid regime, corresponding motifs shapes are scaled. Implemented power law distributions of fracture length in spatial fracture networks yielded the same node's degree distribution in transformed networks. Two general spatial networks are considered: random networks and networks with "hubness" properties mimicking a spatial damage zone (both with power law distribution of fracture length). In the first case, the fractures are embedded in uniformly distributed fracture sets; the second case covers spatial fracture zones. We prove numerically that the abnormal change (transition) in permeability is controlled by the hub growth rate. Also, comparing LBM results with the characteristic mean length of transformed networks' links shows a reverse relationship between the aforementioned parameters. In addition, the abnormalities in advection through nodes are presented.
Visual modelling of role-based security policies in distributed multimedia applications

The management of distributed multimedia systems is simplified when it is based on policies. The latter should be platform independent and expressed in terms of roles. Usually, they are defined through languages that conceptualize the hardware characteristics providing powerful abstraction on the technical components of a system. Unluckily, these languages are very difficult to use for nonexpert users. To support all the different types of users visual languages have been proposed. Following this paradigm, we propose a visual language hierarchy and a tool for specifying and implementing access and security policies according to the RBAC model.
Evaluating a Genetically Encoded Optical Sensor of Neural Activity Using Electrophysiology in Intact Adult Fruit Flies

Genetically encoded optical indicators hold the promise of enabling non-invasive monitoring of activity in identified neurons in behaving organisms. However, the interpretation of images of brain activity produced using such sensors is not straightforward. Several recent studies of sensory coding used G-CaMP 1.3—a calcium sensor—as an indicator of neural activity; some of these studies characterized the imaged neurons as having narrow tuning curves, a conclusion not always supported by parallel electrophysiological studies. To better understand the possible cause of these conflicting results, we performed simultaneous in vivo 2-photon imaging and electrophysiological recording of G-CaMP 1.3 expressing neurons in the antennal lobe (AL) of intact fruitflies. We find that G-CaMP has a relatively high threshold, that its signal often fails to capture spiking response kinetics, and that it can miss even high instantaneous rates of activity if those are not sustained. While G-CaMP can be misleading, it is clearly useful for the identification of promising neural targets: when electrical activity is well above the sensor's detection threshold, its signal is fairly well correlated with mean firing rate and G-CaMP does not appear to alter significantly the responses of neurons that express it. The methods we present should enable any genetically encoded sensor, activator, or silencer to be evaluated in an intact neural circuit in vivo in Drosophila.
Endoplasmic Reticulum Stress and the Unfolded Protein Response in Cellular Models of Parkinson's Disease

6-Hydroxydopamine, 1-methyl-4-phenyl-pyridinium (MPP+), and rotenone cause the death of dopaminergic neurons in vitro and in vivo and are widely used to model Parkinson's disease. To identify regulated genes in such models, we performed serial analysis of gene expression on neuronal PC12 cells exposed to 6-hydroxydopamine. This revealed a striking increase in transcripts associated with the unfolded protein response. Immunoblotting confirmed phosphorylation of the key endoplasmic reticulum stress kinases IRE1α and PERK (PKR-like ER kinase) and induction of their downstream targets. There was a similar response to MPP+ and rotenone, but not to other apoptotic initiators. As evidence that endoplasmic reticulum stress contributes to neuronal death, sympathetic neurons from PERK null mice in which the capacity to respond to endoplasmic reticulum stress is compromised were more sensitive to 6-hydroxydopamine. Our findings, coupled with evidence from familial forms of Parkinson's disease, raise the possibility of widespread involvement of endoplasmic reticulum stress and the unfolded protein response in the pathophysiology of this disease.