Miracle-dz/UniFAR-FTUs huggingface dataset:
How much training is optimal in adaptive PSAM over markov rayleigh fading channels

To mitigate the effects of time-varying fading, Pilot Symbol Assisted Modulation (PSAM) has been introduced in [1], through which the transmitter periodically inserts known symbols or pilots in the data frame. The channel estimates obtained from these pilots are then employed in the coherent demodulation of data symbols. A novel PSAM scheme was introduced in [2] that adapts the transmitter's coded modulation strategy to the quality of the channel estimate at the receiver without requiring any channel-feedback from the latter. In our work, we study the performance of this non-feedback adaptive PSAM scheme using clustering techniques. More precisely, instead of using one pilot per data frame, we send a cluster of pilots consecutively in the beginning of every data transmission interval. The performance of this scheme is measured in terms of achievable rates using binary signaling and modeling the fading process as a Gauss-Markov process. We show through numerical computations that our new strategy provides higher achievable rates at certain levels of SNR and fading correlation, and we provide numerical answers to how much training is “optimal” for the strategy. Finally, we show how the methodology may be extended to high-order Gauss-Markov fading models, with which pilot clustering is expected to yield even higher benefits.
A Resilient and Collaborative Replacement Framework for Per-Flow Monitoring

In the context of a collaborating surveillance system for active TCP sessions handled by an networking device, we consider two problems. The first is the problem of protecting the flow table of per-flow monitoring from overflow and the second is developing an efficient framework estimating the number of active flows and identifying ”heavy hitter” TCP sessions, to reduce the overhead of data exchanged. Our approaches are sensitive to the limited hardware and software resources allocated for this purpose in the linecards in addition to the very high data rates that modern line cards handle; specifically we are interested in cooperatively maintaining a per-flow state with a low cost which has resiliency on dynamic traffic mix. We investigate a traditional timeout processing mechanism to manage the flow table for per-flow monitoring efficiently, called Timeout-Based Purging (TBP), our “clock”-like flow replacement algorithms using a straightforward replacement policy, called “clock”, and finally hybrid approaches combining these two. The effectiveness of our approaches on Internet traces is demonstrated. Our experiments show that our schemes can significantly reduce both false positives and false negatives regardless of both the conditions of flow table occupancy, even under SYN flooding. Our hybrid schemes estimate the number of active flows accurately, and confine the heavy hitters without additional state.
The role of visual cues and whole-body rotations in helicopter hovering control

Helicopters in flight are unstable, and hovering at one spot requires the pilot to do a considerable amount of active control. To date, it is still under discussion which sensory cues helicopter pilots use for this stabilization task, and how these cues are combined. Here we investigated how cues from different sensory modalities (visual cues and body cues) are used when humans stabilize a simulated helicopter at a target location in a closed perception-action loop. Participants were seated inside a closed cabin on a Stewart platform equipped with a projection screen. They had to stabilize a simulated helicopter on a target spot. To investigate the influence of individual visual cues on the stabilization, a minimalistic visual scene was used. Two spheres in the scene represented the location of the target and the position of the helicopter. Optical flow was provided by world-stationary random dots, and a horizon was produced by a black ground plane and white sky. We measured stabilization performance in ten different conditions: black background, horizon, optical flow, both horizon and optical flow, and horizontal stripes; all of these both with and without platform rotation cueing. Physical pitch and roll body rotations were presented by tilting the platform exactly as the simulated helicopter tilted. Our results show that all manipulated cues – horizon, optical flow, and platform rotations – can help the participants to stabilize a simulated helicopter. In particular, adding physical rotation cues to visual stimulation in a simulator can significantly improve the ability of trained participants to stabilize the simulated helicopter at a target location.
A statistically principled approach to histogram segmentation

This paper outlines a statistically principled approach to clustering one dimensional data. Given a dataset, the idea is to fit a density function that is as simple as possible, but still compatible with the data. Simplicity is measured in terms of a standard smoothness functional. Data-compatibility is given a precise meaning in terms of distribution-free statistics based on the empirical distribution function. The main advantages of this approach are that (i) it involves a single decision-parameter which has a clear statistical interpretation, and (ii) there is no need to make a priori assumptions about the number or shape of the clusters.
Net energy analysis of Jatropha press-cake utilization

This paper presents the results of the evaluations conducted on the alternative pathways considered in net energy analysis of Jatropha press-cake utilization as biofuel feedstock. Biogasification and thermal gasification are the two alternative pathways specifically being considered in this particular study. An Energy Return on Investment (EROI) was introduced in this study as the primary tool for net energy analysis respectively. EROI was able to further evaluate the economic variability and potentials of utilizing Jatropha press-cake as the feedstock for generating renewable biofuels. The by-products of the two alternative pathways being evaluated is not yet considered in this study. However it is highly recommended for future research that by-products must be considered in net energy analysis.
Approximate quantum error correction, random codes, and quantum channel capacity

We work out a theory of approximate quantum error correction that allows us to derive a general lower bound for the entanglement fidelity of a quantum code. The lower bound is given in terms of Kraus operators of the quantum noise. This result is then used to analyze the average error correcting performance of codes that are randomly drawn from unitarily invariant code ensembles. Our results confirm that random codes of sufficiently large block size are highly suitable for quantum error correction. Moreover, employing a lemma of Bennett, Shor, Smolin, and Thapliyal, we prove that random coding attains information rates of the regularized coherent information.
An open platform for mixed-criticality Real-time Ethernet

For more than one decade, researchers have considered Ethernet as a natural replacement to legacy fieldbuses in modern distributed applications. However, Ethernet components require special modifications and hardware support to provide strict timing guarantees. In general, the high-cost of deploying hardware components limits the experimental validation of proposed solutions in real-world applications. Despite the vast literature, only a few solutions report real implementations, and they are all closed to the research community, hindering further development for constantly evolving applications. This paper introduces Atacama, an on-going effort on deploying the first hardware-accelerated and open-source framework for mixed-criticality communication on multi-hop networks. Specialized modules exploit the principles of traditional fieldbus systems to coordinate communication tasks on real-time stations, and can be easily integrated to and coexist with Commercial Off The Shelf (COTS) devices operating with best-effort traffic. Experimental characterization of implemented prototypes report minimal jitter on 1Gbps links, and show that real-time guarantees are resilient to injected best-effort traffic. The framework is available as an open-source project, enabling researchers to verify the results, explore, test, and deploy new networking solutions for modern distributed systems in real-world scenarios.
Improving the printing quality of an inkjet printhead using MIMO model predictive control

Drop-on-Demand inkjet printing is considered one of the most promising printing technologies that offers several advantages including high speed, quiet operation and compatibility with a variety of substrates. That makes it an important manufacturing technology serving a wide variety of markets. Though the performance criteria imposed by today's applications are quite tight already, the future performance requirements will be even more challenging. However, the attainable performance is limited by two operational issues that are generally encountered, namely residual vibrations and cross-talk. This paper presents an approach based on a MIMO Model Predictive Control (MPC) with which the input waveform is designed to improve the printing quality of a piezoelectric inkjet printer. The narrow-gap model is employed to predict the response of the ink channel under the application of the piezo input. Simulation and experimental results are presented to investigate the performance of the proposed approach.
Reference, Centers and Transitions in Spoken Spanish *

The goal of this paper is to examine the relationship between Centering transitions (Grosz et al., 1995) and choice of referring expression. For that purpose, Centering analyses were carried out in two different corpora of spoken Spanish. The corpus analysis confirms reports in previous literature about what is the typical choice of referring expression. In some cases, however, the referring expression chosen violates expectation, or does not follow what other researchers have found (e.g., a proper name is used when a pronoun is expected). In those cases, the most likely explanation is that other constraints related to spoken language are at play (turn-taking and grounding).
Using the Groebner basis algorithm to find proofs of unsatisfiability

A propositional proof system can be viewed as a non-deterministic algorithm for the (co-NP complete) unsatisfiabilit y problem. Many such proof systems, such as resolution, are rdso used as the basis for heuristics which deterministicrdly search for short proofs in the system. We discuss a propositional proof system baaed on algebraic rea soning, which we call the Groebner proof system because of a tight connection to the Groebner basis algorithm. For an appropriate measure of proof size, we show that (a degree-limited implement =ation of ) the Groebner basis algorithm finds a Groebner proof of a tautology in time polynomial in the size of the smallest such proof, In other words, urdike most proof systems, the non-deterministic algorithm can be converted to a deterministic one without loss in power. We then compare the power of the Groebner proof system to more studied systems. We show that the Groebner system polynomially simulates Horn clause resolution, quasi-polynomially simulates tree-like resolution, and weakly exponentially simulates resolution. Thus, Groebnerproofs will have better than worst-case behaviour on the same classes of inputs that resolution does. On the other hand, there are simple tautologies which have polynomialsize Groebner proofs but which require exponential-size resolution proofs. We also compare the Groebner proof system to the similar Nullstellensatz proof system introduced in [BIK+94]. We show a family of tautologies that have degree 3 (and hence polynomirdsize) Groebner refutations, but which require @(W degree Nullst ellensat z refutations. Thus, there is an exponential separation between the two systems. These results suggest that the Groebner basis algorithm might replace mmlutian M s bseie far hem.ietics far NP.emnple&e pmh *Research supported by Office of Naval Research AASERT grant #Noo14 -94 – 1 – 0997 tResemch partially done while at ICSI supported by NSERC and NSF Post-doctoral Fellowships $Rese~& Supported by NSF YI Award CCR-92-570979, SIOan Research Fellowship BR-3311, grant #93025 of the joint USCzechoslovak Science and Technology Program, and USA-Israel BSF Grant 92-00043 lems. We have done some preliminary experiments comparing [CW]’S implementation of the Groebner basis algorithm to [KS]’S implementation of the Putnam-Davis procedure for unsatisfiability. ~S]’s program is superior on the instances tested. However, the difference is small enough to hope that further optimization of the Groebner basis algorithm for unsatisfiabilit y could make it the method of choice.
Online systemc emulation acceleration

Field-programmable gate arrays (FPGAs) have recently been used as platforms to emulate SystemC descriptions. Emulation supports in-system testing using real input and output. We previously showed emulation speed to be competitive with SystemC simulations on a PC when the emulator uses acceleration engines. A limit on the number of acceleration engines that can fit on an emulation platform creates new online problems involving runtime decisions as to when to load a SystemC process into an acceleration engine. We define the online SystemC emulation acceleration problem. In contrast to previous works that focus on statically improving SystemC (and the more general event-driven) simulations, we utilize online heuristics to manage the use of a limited number of SystemC acceleration engines in an emulation framework, where the kernel must adapt and react to dynamically changing process and event queues. We test several online heuristics and show 9x improvement over microprocessor-only emulation and 5x over statically preloaded acceleration engines. We further improve emulation performance by 10-20% by adding kernel bypass connections between acceleration engines and by adapting the online heuristics to make use of those connections.
Phonetic Consequences of Speech Disfluency

Abstract : Unlike read or laboratory speech, spontaneous speech contains high rates of disfluencies (e.g., repetitions, repairs, filled pauses). Such events reflect production problems frequently encountered in everyday conversation. Analyses of American English show that disfluency affects a variety of phonetic aspects of speech, including segment durations, intonation, voice quality, vowel quality, and coarticulation patterns. These effects provide clues about production processes, and can guide methods for disfluency processing in speech recognition applications.
Role of therapeutic drug monitoring of voriconazole in the treatment of invasive fungal infections.

BACKGROUND Voriconazole is a broad-spectrum, second-generation triazole antifungal agent with demonstrated efficacy in the treatment of invasive fungal infections caused by Aspergillus spp. and Candida spp. Given the characteristically poor prognosis of patients with invasive fungal infections and the protracted duration of treatment required, therapeutic monitoring of voriconazole is, in theory, an attractive method to optimize antifungal therapy. OBJECTIVE To determine the utility of therapeutic drug monitoring for voriconazole. METHODS A previously published decision-making algorithm was used to assess the currently available literature on therapeutic drug monitoring of voriconazole. RESULTS Several analytical methods can be used to quantify plasma or serum concentrations of voriconazole. Reasons for therapeutic monitoring of this drug include wide variability both within and between individuals secondary to drug properties, drug-drug interactions, and disease states. Furthermore, voriconazole follows nonlinear pharmacokinetics with saturable hepatic clearance. Another potential factor in favour of therapeutic drug monitoring for voriconazole is genetic polymorphism of CYP2C19, whereby patients who are homozygous for poor metabolism (about 19% of non-Indian Asians) can have 4-fold greater exposure to voriconazole. The concentrations of this drug are also greater in patients with hepatic impairment. Drug-drug interactions with other substrates of CYP2C9, CYP2C19, and CYP3A4 can also alter voriconazole concentrations. However, the correlations between plasma concentrations of voriconazole and its efficacy and toxicity are not well defined. Although lower and upper target thresholds of 0.25-2 mg/L and 4-6 mg/L, respectively, have been suggested, studies to date have not been appropriately designed or powered to reveal any definitive association. CONCLUSIONS Routine therapeutic drug monitoring of voriconazole is not recommended except in certain circumstances, such as lack of response to therapy or evidence of toxicity, in which case selective monitoring of voriconazole concentrations may be of clinical utility.
NUYA: An encrypted mechanism for securing cloud data from data mining attacks

Cloud Computing is a vast infrastructural and rising pool, which provides huge storage of data in one sphere. Organizations, now a days are in the marathon of equipping the whole system in a cloud form. The attackers evaluating data for a long time to extract the valued information to perform data mining based attacks on the cloud. In the recent architectures the data is sited in a single or distributed cloud provider. It gives the opportunity to the cloud providers and attackers to unauthorized access from cloud and also gives the chance to analyze the client data for a long time to extract the sensitive information, which is responsible for the privacy violation of clients. This paper proposes an approach that firstly maintains the confidentiality, integrity, and authentication for the stored data in cloud. Secondly, it presents distributed storage cloud architecture, which includes the description of trusted computing work group (TCG) and trusted platform module (TPM). It provides hardware authentication for trustworthy computing platform and also uses Kerberos authentication to avoid software attacks. This proposed approach establishes file locality by clustering the related data based on their physical distance and effective matching with client applications. It supports efficient clustering and reduces communication cost in large-scale cloud computing applications.
A template-based method for the estimation of Event Related Potentials using the Bayesian linear model

In this work a method for the estimation of Event Related Potentials (ERPs) using the linear model is presented. The method consists of two stages. In the first stage, a template is constructed using the averaged ERP. From this template the design matrix of the linear model is extracted. The second stage is related to the estimation of the coefficients of the linear model. In this stage the bayesian approach is used. However, in our problem the posterior distribution is not easily evaluated and there is need to resort in approximation techniques. One such approach is the Variational Bayesian Methodology. In our study, two prior distributions are used to estimate the ERP. This results in two estimation algorithms having different properties for the coefficients of the linear model. The proposed method is tested in simulated and real ERP data.
Experimental Evaluation of Alkaline Batteries's Capacity for Low Power Consuming Applications

The technology advances over the recent years brought on market many portable consumer and telecommunication electronic devices, most of which utilize low-power embedded systems. Significant part of these devices is nowadays supplied from the primary batteries, among which the alkaline ones are the most widespread. The paper presents the real-life discharge curves and measurement results of available energy for various commercially available off-the-shelf alkaline batteries under continues and intermittent discharge. The specifics of the paper is that it focuses the battery discharge profiles, which are typical for the portable devices based on low-power micro controllers in general and Wireless Sensor Network (WSN) nodes in particular. Therefore, provided in the paper data is valuable both for engineers for estimating their devices' lifetimes and for researchers for evaluating battery models or estimating performance for energy efficiency improvement mechanisms. Besides, the presented results reveal importance of battery characteristics consideration for lifetime improvement and demonstrate need for energy-source aware optimization algorithms for battery supplied systems in general and for WSN especially.
A scalable auto-tuning framework for compiler optimization

We describe a scalable and general-purpose framework for auto-tuning compiler-generated code. We combine Active Harmony's parallel search backend with the CHiLL compiler transformation framework to generate in parallel a set of alternative implementations of computation kernels and automatically select the one with the best-performing implementation. The resulting system achieves performance of compiler-generated code comparable to the fully automated version of the ATLAS library for the tested kernels. Performance for various kernels is 1.4 to 3.6 times faster than the native Intel compiler without search. Our search algorithm simultaneously evaluates different combinations of compiler optimizations and converges to solutions in only a few tens of search-steps.
One feature doesn't fit all: characterizing topological features of targets in signaling networks

A key challenge facing drug discovery is the identification of target(s) in a signaling network whose perturbation results in a desired therapeutic outcome. Recent studies have shown that analysis of biological networks based on topology can facilitate target identification by providing valuable information on characteristics of targets. In this paper, we present an algorithm called Differ that discovers the discriminative topological features (dtf) from a signaling network to distinguish the targets from the non-targets. Our empirical study on five signaling networks reveals that the majority of dtfs are able to identify most of the known targets in these networks. Furthermore, they are distinct for different networks. That is, no single topological feature can characterise targets in all signaling networks. This is in contrast to the findings in [28] where bridging nodes are considered to be good targets with low lethality across several ppi networks.
Accelerating user satisfaction in semantic e-commerce

Semantic web links together and defines various parameters leading to user/customer satisfaction. Therefore it is important to identify the aspects of various customer satisfaction areas in online businesses, which can support semantic web. When recollecting about parameters in e-commerce, we will come automatically to the question: 'What are then these parameters ? Where do they lead to? There is a simple way of answering this question: Customer satisfaction. This means a high quality website, performing well in an expected way and comes out with a meaningful result can lead to customer satisfaction has to be semantic.