Miracle-dz/UniFAR-FTUs huggingface dataset:
Mode analysis and optimum design of bidirectional CLLC resonant converter for high-frequency isolation of DC distribution systems

This paper points out the low accuracy of the traditional fundamental harmonic approximation (FHA) in predicting the gain characteristics and resonant behaviors of the full-bridge isolated bidirectional CLLC resonant converter, which results in great impediments in optimally designing the resonant tank parameters. Given these drawbacks of FHA for CLLC converter, this paper proposes a novel operation mode analysis for CLLC resonant converter. Compared with traditional FHA, the operation mode analysis not only explains the appearance of various operation modes, but also provides the accurate description of the gain characteristics and resonant behaviors. Based on the operation mode analysis and the typical application in dc distribution systems for CLLC resonant converter, the influence of multiple factors for CLLC resonant converter is clarified and an optimal design methodology is developed further. Applying this design method, the converter can minimize the conduction loss while the required gain of a fixed switching frequency range is maintained. At last, the experiment results verify the correctness of the operation mode analysis and the excellent performance of CLLC resonant converter constructed by the proposed design methodology.
Lower Bounds on Rate of Convergence of Cutting Plane Methods

In a recent paper Joachims [1] presented SVM-Perf, a cutting plane method (CPM) for training linear Support Vector Machines (SVMs) which converges to an e accurate solution in O(1/e2) iterations. By tightening the analysis, Teo et al. [2] showed that O(1/e) iterations suffice. Given the impressive convergence speed of CPM on a number of practical problems, it was conjectured that these rates could be further improved. In this paper we disprove this conjecture. We present counter examples which are not only applicable for training linear SVMs with hinge loss, but also hold for support vector methods which optimize a multivariate performance score. However, surprisingly, these problems are not inherently hard. By exploiting the structure of the objective function we can devise an algorithm that converges in O(1/√e) iterations.
Training a supra-segmental parametric F0 model without interpolating F0

Combining multiple intonation models at different linguistic levels is an effective way to improve the naturalness of the predicted F0. In many of these approaches, the intonation models for suprasegmental levels are based on a parametrization of the log-F0 contours over the units of that level. However, many of these parametrisations are not stable when applied to discontinuous signals. Therefore, the F0 signal has to be interpolated. These interpolated values introduce a distortion in the coefficients that degrades the quality of the model. This paper proposes two methods that eliminate the need for such interpolation, one based on regularization and the other on factor analysis. Subjective evaluations show that, for a Discrete-cosine-transform (DCT) syllable-level model, both approaches result in a significant improvement w.r. t. a baseline using interpolated F0. The approach based on regularization yields the best results.
Dynamic spectrum access for energy-constrained CR: single channel versus switched multichannel

In energy-constrained cognitive radio networks (CRNs), the choice on single channel access versus switched multichannel access is critical for energy saving and sustainable network operation. In this study, the authors study and compare the energy efficiency of switched (probabilistic) multichannel access (pMCA) and fixed single-channel access (SCA) in CRNs. In pMCA, a secondary user (SU) switches channel with certain probability whenever it encounters a busy channel. In SCA on the other hand, the SU stays on the same channel for its usage and waits for its availability. Via an analytical framework the authors derive the channel utilisation and energy efficiency of the two schemes. From the results the authors examine the primary user (PU) traffic dependent optimum switching probability in pMCA and the regime of PU activity dynamics where SCA outperforms pMCA.
Techniques in Computer Forensics: A Recovery Perspective

Computer forensics has recently gained significant popularity with many local law enforcement agencies. It is currently employed in fraud, theft, drug enforcement and almost every other enforcement activity. The research paper includes the types of attempts to destroy or tamper the files by the culprits and unleashes various recovery techniques, and their significance in different situations from those attempts, which destroy files or inflict physical damage to the computer. The paper also presents the nature and immediate need of enhancing the existing automated forensics tools. The paper gives a quick glance of various methods used by culprits to destroy the information in the electronic storage media and their corresponding forensic approach done by the computer forensic experts in the perspective of recovery.
The effect of dam construction on the movement of dwarf caimans, Paleosuchus trigonatus and Paleosuchus palpebrosus, in Brazilian Amazonia

Run-of-the-river hydroelectric dams cause changes in seasonal inundation of the floodplains, and this may cause displacement of semi-aquatic vertebrates present before dam construction. This study evaluated the movement of crocodilians before and after the filling of the Santo Antônio hydroelectric reservoir on the Madeira River in the Brazilian Amazon, which occurred in November 2011. We radio-tracked four adult male Paleosuchus palpebrosus and four adult male Paleosuchus trigonatus before and after the formation of the reservoir between 2011 and 2013. The home ranges of the P. palpebrosus varied from < 1 km2 to 91 km2 and the home ranges of the P. trigonatus varied from < 1km2 to 5 km2. The species responded differently to time since filling and water level in weekly movement and home range. However, overall the dam appears to have had little effect on the use of space by the individuals that were present before dam construction.
Newer anticoagulants can be used off-label.

A 77-year-old man with ischemic cardiomyopathy and an ejection fraction of 25% presents with a recurrent embolic-looking stroke while taking aspirin and clopidogrel for a coronary stent placed 6 months ago. Computed tomographic angiography of the head and neck is unrevealing. Telemetry reveals a normal sinus rhythm. Renal functions are normal. (1) Should one of the newer oral anticoagulant agents be prescribed for this patient? Off-label use of new oral anticoagulants What is the diagnosis? Stroke neurologists make use of inductive reasoning, a probabilistic exercise, to determine stroke mechanism. Where ≥1 possible mechanism exists, we typically adopt the philosophy of Occam’s razor, assuming that 1 mechanism is dominant. The ensuing approach to preventive treatment rationally follows the determination of stroke mechanism. The appearance of an embolic-looking stroke on brain imaging usually implies a wedge-shaped cortical infarct or multiple scattered infarcts in one or multiple arterial territories. Embolic stroke may be of arterial, cardiac or less commonly, venous origin (paradoxical embolism). From the case history, we infer that arteroembolic stroke arising from a ruptured atherosclerotic plaque is less likely given the unrevealing computed tomographic angiogram. We have no immediate evidence of atrial fibrillation (AF), and we assume that the echocardiographic assessment done to determine the low ejection fraction does not show any alternate source …
Intelligent contextual data stream monitoring

Contextual data monitoring plays an important role in increasing the quality of life of humans. Sensors observing specific activities report contextual data to a central system capable of situational reasoning. The system responds to any event related to the observed phenomenon. We propose an intelligent mechanism that builds on top of sensors measurements and derives the appropriate decisions for immediate identification of events. The mechanism adopts multivariate data fusion, time-series prediction, and consensus theory for aggregating measurements. We adopt Fuzzy Logic for handling the induced uncertainty in the decision making on the derived alerts. Simulations over real contextual data showcase the advantages and disadvantages of our monitoring mechanism.
Recent developments in high integration multi-standard CMOS transceivers for personal communication systems

Issues associated with the integration of transceiver components on a single silicon substrate are discussed. In particular, recently proposed receiver and transmitter architectures for high integration are examined on the promise of providing multistandard capability. In addition, existing barriers to lower power transceiver operation are examined as well as some proposed directions for future integrated transceiver research and development.
A wide-area bird monitoring system using geographically distributed base stations

In the proposed bird monitoring system, a bird-tag, equipped with GPS, is attached on the bird body. Base stations are geographically distributed in a wide interest area to receive the GPS data sets from bird-tags using low power wireless transmission system. A data center collects the GPS data from the base stations to track the position of each bird. Simple evaluation shows that the life of the bird-tag can be nearly one year by using the proposed power saving methods. Simple analysis shows that the real-time bird tracking performance is greatly improved by the proposed position estimation method using the concept of the monitoring coverage of each base station. The real-world testbed of the proposed monitoring system is described. The preliminary experimental results show that the monitoring coverage of each base station is as far as 7 km.
Strain Rate Sensitivity of Ultrafine Grained FCC- and BCC-Type Metals

The dependence of the strain rate sensitivity (SRS) of α-Fe and Al 99.5, as typical representatives of fcc- and bcc-type metals, on the testing temperature and with respect to the microstructure is investigated. In particular, the differences between conventional grain size (CG) and ultrafine grain size (UFG) are pointed out. UFG Al 99.5 generally shows an elevated SRS compared to CG Al 99.5. In case of α-Fe the SRS of the UFG state is decreased at room temperature, but increased at 200 °C, compared to the CG state. It is shown that the SRS also influences the ductility of UFG-metals in tensile tests.
Identity, sense of community and connectedness in a community of mobile language learners

Abstract Mobility can affect a learner's participation in different communities that support language learning. In this paper we report on our experience with supporting a course in which language students are encouraged to travel to a country where the target language is spoken. On the one hand, students who travel abroad get in contact with local communities,which can promote their learning of the language and the culture. On the other hand, they risk losing contact with their classmates and the support that they provide. In this context we introduced a mobile community blog with the aim of extending the learning arena and promoting the sharing of knowledge among the students, independently of their location. This paper discusses the design considerations for the blog and describes its use to support students' sense of community. An evaluation and analysis of the usage of the blog is presented. These results suggest that the learners lack an identity within the community of language learners and there was no sense of community among the members. Reflecting on these results, we suggest that while a blog might be an appropriate tool for promoting knowledge sharing, it lacks functionalities to promote connectedness among learners and foster their identity as a community.
Impact of Technology Scaling on Bridging Fault Modeling and Detection in CMOS Circuits

Bridging faults are one of the most commonly observed failure mechanisms in contemporary integrated circuits (ICs). Several defects, such as gate oxide short, shorts between two different nodes may cause bridging faults (BF). BFs are known to cause intermediate logic levels and therefore are hard to detect by logic testing. In this article, we investigate the impact of technology scaling on BF detection. Theoretical analysis and HSPICE simulations carried out in four different technologies (0.18 μm, 0.25 μm, 0.35 μm, 0.8 μm) show that the detection of BFs is becoming increasingly harder with technology scaling. Fast and accurate calculations of the intermediate bridging voltages on the basis of BF model are presented. CMOS inverters were analyzed to find the impact of technology scaling on BF behavior. The results obtained with the developed model indicate close relationship with the results obtained by HSPICE simulations.
Mapping parallel graph algorithms to throughput-oriented architectures

ion by enlisting the threads within each warp to cooperatively traverse the edges in elements in the active vertex frontier. This approach is more than twice as fast as previous GPU approaches that were used to schedule threads for simultaneous graph traversals for large graphs of both low and high diameter. Furthermore, our approach scales to graphs with millions of vertices using a single GPU whereas previous approaches used large clusters to solve problems of similar size in greater amounts of time. Finally, our abstraction can efficiently implement more complicated algorithms. We show that an implementation of betweenness centrality that leverages our abstraction achieves an average speedup of 7.66x and 5.82x over the Galois and Ligra multi-core graph frameworks, a 3.07x speedup over the Gunrock GPU graph framework, and an average speedup of 2.24x over a heavily optimized on-line GPU implementation of betweenness centrality. The literature on parallel implementations of graph algorithms is beginning to shift from manual, hand-tuned implementations of specific algorithms to libraries that provide abstractions for certain classes of parallel algorithms. The appropriate choice of an abstraction depends on the problem that needs to be solved, the way in which each abstraction is mapped to hardware, and the graph being analyzed. We consider the definition of new abstractions and the unification existing abstractions into a general parallel graph analytics framework to be an exciting area of future work.
Generic Coverage Verification Without Location Information Using Dimension Reduction

Wireless sensor networks (WSNs) have recently emerged as a key sensing technology with diverse civilian and military applications. In these networks, a large number of small sensors or nodes perform distributed sensing of a target field. Each node is capable of sensing events of interest within its sensing range and communicating with neighboring nodes. The target field is said to be <formula formulatype="inline"><tex Notation="TeX">$k$</tex></formula>-covered if every point in it is within the sensing range of at least <formula formulatype="inline"> <tex Notation="TeX">$k$</tex></formula> sensors, where <formula formulatype="inline"> <tex Notation="TeX">$k$</tex></formula> is any positive integer. We present a comprehensive framework for verifying <formula formulatype="inline"><tex Notation="TeX">$k$</tex></formula>-coverage of a <formula formulatype="inline"> <tex Notation="TeX">$d$</tex></formula>-dimensional target field for an arbitrary positive integer <formula formulatype="inline"><tex Notation="TeX">$k$</tex> </formula> and <formula formulatype="inline"><tex Notation="TeX">$d \in \{1, 2, 3\}$</tex></formula>. Our framework uses a divide-and-conquer approach based on the technique of dimension reduction, in which the <formula formulatype="inline"> <tex Notation="TeX">$k$</tex></formula>-coverage verification problem in <formula formulatype="inline"><tex Notation="TeX">$d$</tex></formula> dimensions is reduced to a number of coverage verification problems in <formula formulatype="inline"> <tex Notation="TeX">$(d-1)$</tex></formula> dimensions, which are then recursively solved. Our framework leads to a distributed polynomial-time coverage verification algorithm that does not require knowledge of the locations of nodes or directional information, which is difficult to obtain in WSNs. Each node can execute the algorithm using only the distances between adjacent nodes within its transmission range and their sensing radii. We analytically prove that the scheme detects a coverage hole if and only if the target field has a coverage hole.
Slow vasomotor fluctuation in fMRI of anesthetized child brain

Signal intensity changes in fMRI during rest caused by vasomotor fluctuations were investigated in this work. Resting‐state baseline fluctuations were evaluated in 12 children anesthetized with thiopental. Five subjects had fluctuations related to subvoxel motion. In seven subjects without significant motion, slow signal fluctuation at 0.025–0.041 Hz near one or more primary sensory cortices was observed. In each subject the amplitude and frequency of the fluctuations were stable. It is hypothesized that thiopental, which reduces blood pressure and flow in the cortex, alters the feedback in neurovascular coupling leading to an increase in the magnitude and a reduction in the frequency of these fluctuations. The use of anesthesia in fMRI may provide new insight into neural connectivity and the coupling of blood flow and neural metabolism. Magn Reson Med 44:373–378, 2000. © 2000 Wiley‐Liss, Inc.
A Normative Model for Behavioral Differentiation

In multi-agent systems simulations, reproducing realistic behaviors is a crucial issue. Their variety and consistency are important factors, usually not specifically considered. In this paper, we propose a behavioral differentiation model designed (1) to generate various and consistent behaviors, and (2) to control the determinism of this generation. Based on a normative system and a nondeterministic generation engine, it allows users adapting it easily to their various needs. Finally, we show its application to the traffic simulation software developed and used at Renault, SCANeR(c) II.
The global cancer genomics consortium's symposium: new era of molecular medicine and epigenetic cancer medicine - cross section of genomics and epigenetics

The Global Cancer Genomics Consortium (GCGC) colleagues continue to function together as an interactive multidisciplinary team of cancer biologists and oncologists with interests in genomics and building a bidirectional bridge between cancer clinics and laboratories while taking advantage of shared resources among its member scientists. The GCGC includes member scientists from six institutions in Lisbon, United Kingdom, Japan, India and United States, and was formed in December 2010 for a period of five years. Driven by valuable lessons learned from the previous symposiums, the fourth GCGC Symposium focused on a cross section of genomic and epigenetic cancer medicine and it's for this reason we chose the conference theme - New Era of Molecular Medicine and Epigenetic Cancer Medicine: Cross Section of Genomics and Epigenetics. This year's symposium was co-organized by the Organization for Oncology and Translational Research (OOTR) at the Shiran Hall, Kyoto University, Kyoto, Japan, from November 14 and 15, 2014. The symposium attracted around 80 participants from 14 countries, and counted with 23 invited platform speakers. Scientific sessions included eight platform sessions and one poster session, and three plenary lectures. The symposium focused on cancer stem cells and self-renewal, cancer transcriptome, tumor heterogeneity, tumor biology, breast cancer genomics, targeted therapeutics and personalized medicine. The issues of cancer stem cells and tumor heterogeneity were echoed in most of the scientific presentations. The meeting concluded with an oral presentation by the best poster awardee and closing remarks by meeting co-chairs.
An efficient algorithm in the HLA time management

The HLA time management is an important factor that limits the scalability of distributed simulations. An efficient algorithm of greatest available logical time (GALT) is thus much critical for the time management in an RTI to support large-scale simulations. The concept of GALT in IEEE 1516 was also called lower bound time stamp (LBTS) in HLA 1.3. The computation of GALT in the HLA time management is different from that of LBTS in traditional parallel discrete event simulation (PDES). In this paper, an algorithm about GALT is presented and its correctness is proved. Its efficiency is also explained by applying it to RTI1.3-NG. In fact, the algorithm has been implemented in our RTI to support thousands of federates in our cluster systems. In addition, a real-world example is introduced to explain the correctness of the algorithm proving, and the reason of our RTI supporting large-scale simulations.
Determination of S‐100 and Glial Fibrillary Acidic Protein Concentrations in Cerebrospinal Fluid After Brain Infarction

Background and Purpose We initiated the present study to evaluate the clinical value of consecutive concentration determinations of S-100 and glial fibrillary acidic proteins in cerebrospinal fluid from patients with brain infarction. Methods We took sequential samples of cerebrospinal fluid from 28 patients within 48 hours, at 7 days, and at 18-21 days after the ictus. We measured astroglial protein concentrations using an enzyme-linked immunosorbent assay and also determined size of the infarction (computed tomography), clinical state of the patient (simplified activities of daily living test), blood-brain barrier dysfunction (cerebrospinal fluid/serum albumin ratio), and a myelin marker (myelin basic protein). Results We found a transient increase of both proteins in the cerebrospinal fluid during the first week after the ischemic stroke (p<0.05). This increment was significantly correlated with the size of the infarction and the clinical state of the patients. Conclusions Transient release of astroglial proteins into the cerebrospinal fluid possibly reflects initial focal ischemic damage and, in the later phase, ongoing destruction of astroglial cells in the penumbra zone. We suggest that determinations of cerebrospinal fluid astroglial protein concentrations can be used to estimate ischemic brain damage, which should be of particular value in clinical trials of pharmacological agents, such as calcium antagonists, on stroke patients.
Discovery of Periodic Patterns in Spatiotemporal Sequences

In many applications that track and analyze spatiotemporal data, movements obey periodic patterns; the objects follow the same routes (approximately) over regular time intervals. For example, people wake up at the same time and follow more or less the same route to their work everyday. The discovery of hidden periodic patterns in spatiotemporal data could unveil important information to the data analyst. Existing approaches for discovering periodic patterns focus on symbol sequences. However, these methods cannot directly be applied to a spatiotemporal sequence because of the fuzziness of spatial locations in the sequence. In this paper, we define the problem of mining periodic patterns in spatiotemporal data and propose an effective and efficient algorithm for retrieving maximal periodic patterns. In addition, we study two interesting variants of the problem. The first is the retrieval of periodic patterns that are frequent only during a continuous subinterval of the whole history. The second problem is the discovery of periodic patterns, whose instances may be shifted or distorted. We demonstrate how our mining technique can be adapted for these variants. Finally, we present a comprehensive experimental evaluation, where we show the effectiveness and efficiency of the proposed techniques