Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Improvement of OFDM Using Subcarrier Frequency Diversity

Orthogonal Frequency Division Multiplexing is a key contender for broadcasting standards, due to its immunity towards multipath fading and ease of implementation. Here a novel scheme to exploit the frequency diversity within OFDM subcarriers has been proposed which further increases the bit error rate performance. The diversity is achieved by circularly shifting the OFDM subcarrier coefficients in pseudorandom manner. Thus we notice a significant performance improvement without any additional bandwidth requirements.
Design of driving fatigue detection system based on hybrid measures using wavelet-packets transform

With the rapid development of urbanization and motorization in China, fatigue driving has become an increasingly serious road traffic problem. Driving fatigue affects drivers' alertness, decreasing an individual's ability to operate a vehicle safely and increasing the risk of human error that could lead to fatalities, which have been widely recognized as critical safety issues that cut across all modes in the transportation industry. In this paper, firstly, with a virtual driving system we developed, driving simulation experiments were designed to collect subjects' electroencephalogram (EEG) signals and mental fatigue data. To detect drivers' mental state in real time, wavelet-packets transform (WPT) was selected to extract continuous features; then, the subjective evaluation combined with video monitoring was used to evaluate driver's mental state in experiment accurately. At last, with fatigue feature as the input and fatigue state as the output, driving fatigue detection model can be constructed by classification methods. In this paper, Support Vector Machine (SVM) was used to build driving fatigue detection model to estimate mental fatigue state of EEG signal features, and the binary classification accuracy can be achieved up to 88.6207%.
Uncertainity in Mechanism Design

We consider a simple mechanism design problem with private values in which each agent perceives Knightian uncertainty over his opponents’ types. Uncertainty is formalized using incomplete preferences as in Bewley (1986). We show that the seller can extract all gains from trade with a direct mechanism in which truth-telling is a Nash equilibrium, in the sense that no buyer has a unilateral incentive to misrepresent his type. In a Nash equilibrium, however, truth-telling and mirepresenting can be incomparable alternatives. Thus we also consider an equilibrium concept in which truth-telling is optimal, that is, (weakly) preferred to other alternatives. In this case the full extraction of all gains from trade is feasible only if there is sufficient disagreement in beliefs. Otherwise, Vickrey mechanisms maximize the seller’s expected revenue. JEL Codes: D0, D5, D8, G1
Clique-perfectness and balancedness of some graph classes

A graph is clique-perfect if the maximum size of a clique-independent set (a set of pairwise disjoint maximal cliques) and the minimum size of a clique-transversal set (a set of vertices meeting every maximal clique) coincide for each induced subgraph. A graph is balanced if its clique-matrix contains no square submatrix of odd size with exactly two ones per row and column. In this work, we give linear-time recognition algorithms and minimal forbidden induced subgraph characterizations of clique-perfectness and balancedness of P4-tidy graphs and a linear-time algorithm for computing a maximum clique-independent set and a minimum clique-transversal set for any P4-tidy graph. We also give a minimal forbidden induced subgraph characterization and a linear-time recognition algorithm for balancedness of paw-free graphs. Finally, we show that clique-perfectness of diamond-free graphs can be decided in polynomial time by showing that a diamond-free graph is clique-perfect if and only if it is balanced.
GPUFLIC: Interactive and Accurate Dense Visualization of Unsteady Flows

The paper presents an efficient and accurate implementation of Unsteady Flow LIC (UFLIC) on the Graphics Processing Unit (GPU). We obtain the same, high quality texture representation of unsteady two-dimensional flows as the original, time-consuming method but leverage the features of today's commodity hardware to achieve interactive frame rates. Despite a remarkable number of recent contributions in the field of texture-based visualization of time-dependent vector fields, the present paper is the first to provide a faithful implementation of that prominent technique fully supported by the graphics pipeline.
Novel relations between the ergodic capacity and the average bit error rate

Ergodic capacity and average bit error rate have been widely used to compare the performance of different wireless communication systems. As such recent scientific research and studies revealed strong impact of designing and implementing wireless technologies based on these two performance indicators. However and to the best of our knowledge, the direct links between these two performance indicators have not been explicitly proposed in the literature so far. In this paper, we propose novel relations between the ergodic capacity and the average bit error rate of an overall communication system using binary modulation schemes for signaling with a limited bandwidth and operating over generalized fading channels. More specifically, we show that these two performance measures can be represented in terms of each other, without the need to know the exact end-to-end statistical characterization of the communication channel. We validate the correctness and accuracy of our newly proposed relations and illustrated their usefulness by considering some classical examples.
An Ab Initio Solution Of Interdependence: Social Organization With First Principles

A special issue of Science, the National Academy of Sciences, the military, and economists have called for a new theory of interdependence, ι. Constructed around the notion of bistable social reality (i.e., complementarity between conjugate or Fourier pairs), we have developed a social physics of ι for organizations and systems of humans, machines and robots that has shown some validity. But because of the loss of meaning associated with understanding ι states or interactions between social Fourier pairs, we consider it high‐risk research.
Content-Based High-Resolution Remote Sensing Image Retrieval via Unsupervised Feature Learning and Collaborative Affinity Metric Fusion

With the urgent demand for automatic management of large numbers of high-resolution remote sensing images, content-based high-resolution remote sensing image retrieval (CB-HRRS-IR) has attracted much research interest. Accordingly, this paper proposes a novel high-resolution remote sensing image retrieval approach via multiple feature representation and collaborative affinity metric fusion (IRMFRCAMF). In IRMFRCAMF, we design four unsupervised convolutional neural networks with different layers to generate four types of unsupervised features from the fine level to the coarse level. In addition to these four types of unsupervised features, we also implement four traditional feature descriptors, including local binary pattern (LBP), gray level co-occurrence (GLCM), maximal response 8 (MR8), and scale-invariant feature transform (SIFT). In order to fully incorporate the complementary information among multiple features of one image and the mutual information across auxiliary images in the image dataset, this paper advocates collaborative affinity metric fusion to measure the similarity between images. The performance evaluation of high-resolution remote sensing image retrieval is implemented on two public datasets, the UC Merced (UCM) dataset and the Wuhan University (WH) dataset. Large numbers of experiments show that our proposed IRMFRCAMF can significantly outperform the state-of-the-art approaches.
Field Data Based Modeling of Sender Based Message Logging Protocols for Supercomputers Checkpointing

Checkpointing is today’s common mean for dealing with transient failures in supercomputers. However, the effectiveness of checkpointing and recovery protocols under the assumption that failures may happen during their operation is not well understood. We present an evaluation of the checkpointing and recovery based on Sender Based Message Logging protocols (SBML). We evaluate it by means of a model which is gathered from an extensive field data campaign performed on the SCOPE supercomputer at the University of Naples. A comprehensive model is built to evaluate reliability, scalability and performance of SBML. The proposed model takes into account failures during the checkpointing and recovery. Result provide insights on the limit of the number of nodes that can be allocated to the same job considering i) the overhead for the distributed coordination for rollback, and ii) network resources (e.g. bandwidth).
Depth From Motion and Optical Blur With an Unscented Kalman Filter

Space-variantly blurred images of a scene contain valuable depth information. In this paper, our objective is to recover the 3-D structure of a scene from motion blur/optical defocus. In the proposed approach, the difference of blur between two observations is used as a cue for recovering depth, within a recursive state estimation framework. For motion blur, we use an unblurred-blurred image pair. Since the relationship between the observation and the scale factor of the point spread function associated with the depth at a point is nonlinear, we propose and develop a formulation of unscented Kalman filter for depth estimation. There are no restrictions on the shape of the blur kernel. Furthermore, within the same formulation, we address a special and challenging scenario of depth from defocus with translational jitter. The effectiveness of our approach is evaluated on synthetic as well as real data, and its performance is also compared with contemporary techniques.
FairPlay: Fraud and Malware Detection in Google Play

Fraudulent behaviors in Google Android app market fuel search rank abuse and malware proliferation. We present FairPlay, a novel system that uncovers both malware and search rank fraud apps, by picking out trails that fraudsters leave behind. To identify suspicious apps, FairPlay PCF algorithm correlates review activities and uniquely combines detected review relations with linguistic and behavioral signals gleaned from longitudinal Google Play app data. We contribute a new longitudinal app dataset to the community, which consists of over 87K apps, 2.9M reviews, and 2.4M reviewers, collected over half a year. FairPlay achieves over 95% accuracy in classifying gold standard datasets of malware, fraudulent and legitimate apps. We show that 75% of the identified malware apps engage in search rank fraud. FairPlay discovers hundreds of fraudulent apps that currently evade Google Bouncer detection technology, and reveals a new type of attack campaign, where users are harassed into writing positive reviews, and install and review other apps.
How low can you go?: Understanding ecological footprint reduction in university students, faculty and staff

Purpose The purpose of this paper is to describe the impacts of an ecological footprint (EF) reduction campaign on the pro-environmental behavior of university students, faculty and staff. The campaign emphasized educating participants on specific actions that reduce resource use and the relative environmental benefit of each action. Design/methodology/approach This investigation used a pre-test–post-test design. At the beginning of an academic year, participants were invited to measure their baseline EF and take part in a footprint reduction campaign. At the end of the campaign, participants measured their EF again to see if they were able to reduce it by 10 per cent. Findings Participants in the footprint reduction campaign decreased their EF by 10 per cent. Students changed behaviors related to goods and services the most, resulting in a 16 per cent decrease in footprint for this behavior category. The most significant behavior change for faculty and staff was in the housing category with footprint reductions of 12 and 11 per cent, respectively. The most common behavioral changes in students were low- and no-cost options. Research limitations/implications Because of the general nature of the EF tool, estimates of resource use reduction are approximate. Data describing pro-environmental behaviors were self-reported by participants, making accuracy dependent on participant recollections. Originality/value This paper illustrates how providing quantitative, personalized and university-specific knowledge on the impact of personal lifestyles on natural resources can facilitate significant, measurable pro-environmental behavioral change for the entire campus community. It also provides direction on how to develop targeted sustainability campaigns for different audiences.
A Chance-Constrained Maximum Capture Location Problem

The paper presents a new model based on the basic Maximum Capture model, MAXCAP. The Chance – Constrained Maximum Capture model introduced a stochastic threshold constraint, which recognised the fact that a facility can be open only if a minimum level of demand is captured. A metaheuristic based on MAX – MIN ANT system and TABU search procedure is presented to solve the model. This is the first time that the MAX – MIN ANT system is adapted to solve a location problem. Computational experience and an application to 55 – node network are also presented. ♦ Department of Economics and Business, Universitat Pompeu Fabra, Ramon Trias Fargas, 25-27, 08005 Barcelona (Spain). Tel: 34-3-5421700, Fax: 34-3-5421746. E-mail: rosa.colome@econ.upf. es ♣ Department of Economics and Business, Universitat Pompeu Fabra, Ramon Trias Fargas, 25-27, 08005 Barcelona (Spain). Tel: 34-3-5421666, Fax: 34-3-5421746. E-mail: daniel.serra@econ.upf. es
Model based and service oriented interaction for ubiquitous environments

The goal of ubiquitous computing, as first envisioned by Mark Weiser and afterwards pursued and developed by Gregory D. Abowd and Elizabeth D. Mynatt among many others, is to provide the computing service the user needs in the situation, place and configuration she needs it [23, 1]. Human-Computer Interaction in ubiquitous systems should therefore be as natural as possible. This can be achieved by using interaction modes that are perceived as more natural than others, by supporting multimodal interaction and also by implementing context-awareness. One main characteristic of ubiquitous environments is the presence and usage of many different interactive devices. In Weiser's vision, those are for example tabs, pads and boards [23]. Today, smart watches, smartphones, laptops, personal computers and tablets are ubiquitous in our lives. Multi-touch displays and tables, big display walls or screens and many other interactive devices, such as smart glasses, are becoming more common, too. A challenge in ubiquitous computing is to realize the interconnection between these devices, as this is the "key to his vision", described by Ebling & Baker in their assessment of Weiser's vision 20 years after it's first publication [7]. Most of the interactive technologies used today are not out of the box compatible with each other and plug and play usage is not supported.
Sparsity-promoting controller design for VSC-based microgrids

In this paper, we study the issue of decentralized voltage control for inverter-based microgrids. Such a network includes multiple distributed energy resources (DER) that are electronically interfaced with the AC network via voltage-sourced converters (VSC). A microgrid should be able to operate being both connected to the main utility grid and in the autonomous mode, which demands advanced voltage and frequency control compared to traditional rotating generators, the dynamic of VSCs are much faster and dependent on the converters' control design. The fast dynamic response and potentially large number of DERs in the microgrid make decentralized control a preferred structure. We design decentralized controllers using sparsity promoting optimal control. The approach enables us to compare different communication topologies such as neighbor-to-neighbor and purely local control. We evaluate our approach on numerical examples.
Possible Protective Effect of Kombucha Tea Ferment on Cadmium Chloride Induced Liver and Kidney Damage in Irradiated Rats

Kombucha Tea Ferment (KT), was given to male albino rats, (1ml/Kg of body weight), via gavages, during 2 weeks before intraperitoneal administration of 3.5 mg/Kg body weight CdCl2 and/or whole body γ-irradiation with 4Gy, and during 4 weeks after each treatment. Hepatic and nephritic pathological changes included significant increases of serum alanine transaminase (ALT), aspartate transaminase (AST), and alkaline phosphatase (ALP) activities, and creatinine and urea contents with significant decrease in serum total antioxidant capacity (TAC). Increase in oxidative stress markers in liver and kidney tissues expressed by significant increase in malondialdehyde (MDA) and nitric oxide (NO) contents associated to significant depletion in superoxide dismutase (SOD) and catalase (CAT) activities, and reduced glutathione (GSH) content were recorded. KT administration results in recovery of all the pathological changes. It could be concluded that KT might protect liver and kidney from oxidative damage induced by exposure to cadmium and/ or γ-irradiation. Keywords—Cadmium, Kombucha, radiation, rats
Lip Processing and Modeling based on Spatial Fuzzy Clustering in Color Images

In this paper, a robust pre-processing algorithm based on spatial fuzzy clustering for a model based lip contour extraction is presented. This transformation aims at increasing discrimination between lips and skin to enhance the lip contour detection. For each pixel in the transformed data, a and b components of CIELAB color space are used as features in spatial fuzzy clustering phase. The employed clustering method takes into account both the distributions of data in feature space and the spatial interactions between neighboring pixels during clustering. Then, an elliptical and a Gaussian mask delete the pixels around lip that were previously clustered as lip pixels. Finally, a model is fitted upon the lip for extracting the lip contour. To show the effectiveness of the proposed method, pseudo hue segmentation and spatial fuzzy c-mean clustering were implemented and compared to our method. The results on VidTIMIT and M2VTS databases show that the novel scheme is able to extract the lip contour even in the situations that the nose and neck appeared in the lip region. Empirical results showed our method outperformed the present state-of-art methods.
Changes in Rumen Microbial Community Composition during Adaption to an In Vitro System and the Impact of Different Forages

This study examined ruminal microbial community composition alterations during initial adaption to and following incubation in a rumen simulation system (Rusitec) using grass or corn silage as substrates. Samples were collected from fermenter liquids at 0, 2, 4, 12, 24, and 48 h and from feed residues at 0, 24, and 48 h after initiation of incubation (period 1) and on day 13 (period 2). Microbial DNA was extracted and real-time qPCR was used to quantify differences in the abundance of protozoa, methanogens, total bacteria, Fibrobacter succinogenes, Ruminococcus albus, Ruminobacter amylophilus, Prevotella bryantii, Selenomonas ruminantium, and Clostridium aminophilum. We found that forage source and sampling time significantly influenced the ruminal microbial community. The gene copy numbers of most microbial species (except C. aminophilum) decreased in period 1; however, adaption continued through period 2 for several species. The addition of fresh substrate in period 2 led to increasing copy numbers of all microbial species during the first 2–4 h in the fermenter liquid except protozoa, which showed a postprandial decrease. Corn silage enhanced the growth of R. amylophilus and F. succinogenes, and grass silage enhanced R. albus, P. bryantii, and C. aminophilum. No effect of forage source was detected on total bacteria, protozoa, S. ruminantium, or methanogens or on total gas production, although grass silage enhanced methane production. This study showed that the Rusitec provides a stable system after an adaption phase that should last longer than 48 h, and that the forage source influenced several microbial species.
Real-time quality control for crowdsourcing relevance evaluation

In recent years, crowdsourcing has become an effective method in many fields, such as relevance evaluation of search engine results. However, the problems of bad workers and quality control always stand among the major challenges within the realm. Based on our experiments carried out in TREC 2011 Crowdsourcing track, this paper demonstrates a realtime strategy in recruiting workers and monitoring the quality of their relevance and rank judgments. The effectiveness of our strategy has been verified by empirical results.
Effect of common single nucleotide polymorphisms in COX-1 gene on related metabolic activity in diabetic patients treated with acetylsalicylic acid

Introduction The objective of this study was to investigate the effect of common single nucleotide genomic polymorphisms in the cyclooxygenase-1 (COX-1) gene on the thromboxane A2 (TxA2) metabolite concentrations in serum and urine, as well as on prostaglandin F2α (PGF2α) urinary excretion in the diabetic population on acetylsalicylic acid (ASA) therapy. Material and methods The study cohort consisted of 284 Caucasians with diabetes type 2 who had been taking ASA tablets at the dose of 75 mg/day for at least 3 months. Genotyping for the 4 selected SNPs within the COX-1 gene (two nonsynonymous-coding variants, rs3842787 [C50T, P17L] and rs5789 [C174A, L237M]; and two other synonymous SNPs, rs3842788 [G128A, Q41Q] and rs5788 [C644A]) was performed using the Sequenom iPLEX platform. Results No statistically significant results were observed for the investigated SNPs and measured metabolites in the investigated cohort of patients. Statistically significant differences in S-TxB2 could however be observed for rs5788 in the subgroup of patients with very high S-TxB2 concentrations. In particular, more patients who were carriers of the minor allele for this polymorphism were observed in the group with S-TxB2 levels > 95th percentile, when compared with similar carriers in the group with S-TxB2 < 95th percentile (20% vs. 1.1%, respectively, p < 0.001, Mann-Whitney test). Conclusions The results of our study suggest that the four investigated common SNPs in the COX1 gene are not associated with obviously altered TxA2 metabolism and PGF2α synthesis in the investigated diabetic cohort treated with ASA.
Design of an improved fuzzy logic based model for prediction of car following behavior

Nowadays, car following models, as the most popular microscopic traffic flow modeling, are increasingly being used by transportation experts to evaluate new Intelligent Transportation System (ITS) applications. This paper presents a car following model that was developed using a fuzzy inference system (FIS) to simulate and predict the future behavior of a Driver-Vehicle- Unit (DVU). This model was developed based on a new idea for estimating the instantaneous reaction of DVU, as an input of fuzzy model. The model's performance was evaluated based on field data. The results showed that fuzzy model based on instantaneous reaction delay outperformed the other car following models. The proposed model can be used in Driver Assistant Devices, Safe Distance Keeping Observers, Collision Prevention Systems and other ITS applications.