Miracle-dz/UniFAR-FTUs huggingface dataset:
Closed-Loop Nonlinear Modeling of Wideband$SigmaDelta$Fractional-$N$Frequency Synthesizers

Wideband low-noise SigmaDelta fractional-N synthesizers pose several design challenges due to the nonlinear time-varying nature of synthesizer building blocks such as phase frequency detectors (PFDs), charge pump, and frequency dividers. Loop nonlinearities can increase close-in phase noise and enhance spurious tones due to intermodulation of high-frequency quantization noise and tonal content; therefore, an accurate simulation model is critical for successful implementation of loop parameters and bandwidth widening techniques. In this paper a closed-loop nonlinear simulation model for fractional-N synthesizers is presented. Inherent nonuniform sampling of the PFD is modeled through an event-driven dual-iteration-based technique. The proposed technique generates a vector of piecewise linear time-voltage pairs, defining the voltage-controlled oscillator (VCO) control voltage. This method also lends itself to modeling of cyclostationary thermal and flicker noise generated by time-varying charge-pump current pulses. A flexible third-order SigmaDelta modulated RF synthesizer core with integrated loop filter and LC-tank VCO is designed and fabricated in 0.13-mum CMOS process in order to validate the technique experimentally. The proposed modeling technique was able to predict in-band spur power levels with 1.8-dB accuracy, and spur frequency offsets with lower than 400-Hz accuracy with several programmable nonidealities enabled
Multi-Step Community Detection and Hierarchical Time Segmentation in Evolving Networks

Many complex systems composed of interacting objects like social networks or the web can be modeled as graphs. They can usually be divided in dense sub-graphs with few links between them, called communities and detecting this un-derlying community structure may have a major impact in the understanding of these systems. We focus here on evolving graphs, for which the usual approach is to represent the state of the system at different time steps and to compute communities independently on the graph obtained at each time step. We propose in this paper to use a different framework: instead of detecting communities on each time step, we detect a unique decomposition in communities that is relevant for (almost) every time step during a given period called the time window. We propose a definition of this new decomposition and two algorithms to detect it quickly. We validate both the approach and the algorithms on three evolving networks of different kinds showing that the quality loss at each time step is very low despite the constraint of maximization on several time steps. Since the time window length is a crucial parameter of our technique, we also propose an unsupervised hierarchical clustering algorithm to build automatically a hierarchical time segmentation into time windows. This clustering relies on a new similarity measure based on community structure. We show that it is very efficient in detecting meaningful windows.
A Simple Process Calculus for the analysis of Security Protocols

The spi calculus has been proved useful for reasoning about security protocols. It is however difficult to mechanize the equivalence checking in that framework due to the complexity caused by name passing communications. The paper proposes a calculus for the analysis of the security protocols (SPC for short) as a simplification of the spi calculus. SPC can explicitly express environment knowledge, protocol participants and their knowledge. We present its syntax and semantics, and specify some security properties in terms of equivalence relations. Finally two examples of formal verification is given.
The Way of LAPOR! Site’s Users Communicate Complaints in 2015: The Study of Systemic Functional Linguistics

: This study examines the use of language in the genre of the complaints in public messages on the LAPOR! site in 2015. The main objectives of this study are to explore the generic structure and the linguistics features used in the complaint messages using SFL approach, and to describe the achievement of social function of the complaints messages that can be indicated from the generic structure and the linguistics features used by the LAPOR! site’s users. This research used descriptive qualitative method because it aims to illustrate the use of language with the natural data without any manipulation of the researcher. The data in this study were 40 complaining messages that were given to the responsible authorities to make solutions. Therefore, the complaining messages on this website were categorized as direct complaints. The results of this study indicated that a complaint genre in LAPOR! site had 9 stages and had several lexicogrammatical features. Focusing on the achievement of social function, the entire of complaint messages can be understood as complaint activity, as reflected in its responses. The social function of complaint genre can be achieved because the complaint messages were supported by the effective generic structure and relevant linguistics features.
The Ionized Component of Intermediate-Velocity Cloud Complex L

We present the first full map of the H-alpha emission from the intermediate-velocity cloud Complex L. Kinematically resolved emission components from the ionized gas reveal a close spatial and velocity correspondence to that of the neutral gas as mapped by 21 cm line observations. Using a simple Gaussian component fitting technique, we compare the details of the emission from the two phases of Complex L. The mean velocity of the H-alpha and 21 cm emission are strongly correlated, but we find that the some of the ionized gas is systematically offset ~ -4 km/s relative to the neutral gas. Line widths are qualitatively comparable, but both emission components are too low signal-to-noise to study any differences between the phases. Finally, as with our previous study toward Complex K, we find I(H-alpha) is not strongly correlated to N(H I) along the same lines of sight through Complex L.
Radar Signal Automatic Classification Based on PCA

This paper introduces an efficient approach to radar signal automatic classification by extracted fusion feature entropy. In this approach, wavelet packet reconstruct coefficient features are extracted from given radar signals in frequency domain based on wavelet packet decomposition. Then, these features are fused with the principal component analysis and a single characteristic feature vector which can effectively represent difference radar signals is obtained. Aiming at the single fusion feature, its energy entropy and symbolization probability entropy are extracted and extracted fusion feature entropy are used to classify emitter radar signal with fuzzy c-mean clustering algorithm. Simulation experiment show that the proposed approach is verified to be highly accurate and robust even in the low SNR, and the classification algorithm needs only very small memory space to store the reference information and can fast implement radar signal classification.
A visualization method for hand cleanness using fluorescent spectrum

The goal of this study is to develop a method for the visualization of the distribution of the contamination of the human hands by using fluorescent spectrum. To archive this, we first found the optimal combinations of the excitation and the emission wavelengths that accurately predict the contamination level. This optimization was conducted using the excitation-emission matrices of the contamination components wiped from hands. Then, we visualized the distribution of the contamination on hands by using the spectral imaging of the hands measured with the optimal wavelength combinations. This result suggests that the proposed method can detect and visualize the contaminated areas of the hands.
Time series forecasting using a perturbative intelligent system

The Perturbative Time-delay Added Evolutionary Forecasting (P-TAEF) method for time series prediction is inspired in the Perturbation Theory, a concept already commonly used in other areas of science (physics, mathematics, etc), and evolutionary computing. This methodology is shown and an experimental investigation is conducted with some relevant time series and the results achieved are discussed and compared with previous results found in the literature.
Mobile Robot Vision Tracking System Using Dead Reckoning & Active Beacons

Abstract This paper presents a new vision tracking system for mobile robot by integrating information received from encoders, inertial sensors, and active beacons. The proposed system accurately determines mobile robot position and orientation using relative and absolute position estimates, and rotates the camera towards the target during locomotion. Among the implemented sensors, the encoder data give relatively accurate robot motion information except when wheels slip. On the other hand inertial sensors have the problem of integration of noisy data, while active beacons are slow when compared to other sensors. The designed system compensates the sensors limitations and slip error by switching between two Kalman filters, built for slip and no-slip cases. Each Kalman filter uses different sensors combination and estimates robot motion respectively. The slip detector is used to detect the slip condition by comparing the data from the accelerometer and encoder to select the either Kalman filter as the output of the system. Based on the proposed sensor fusion method, a vision tracking system is implemented on a two-wheeled robot. The experimental results depict that proposed system is able to locate robot position with significantly reduced position errors and successful tracking of the target for various environments and robot motion scenarios.
Students' Interactions in Online Asynchronous Discussion Forum: A Social Network Analysis

Existing learning management systems (LMS) provide limited information regarding the communication structure of group, level of participation, identifying who is central actors and other structural characteristics of the discussion forum. The instructors of an online class are not provided with those structural indicators that would allow them to evaluate the participation and interaction among students in their classes. In many instances, only statistical information, such as frequency of postings is encompassed, but this is not a very useful measurement for the interaction activity. This paper discusses the analysis of students’ interactions in an online asynchronous discussion forum (OADF) using social network analysis (SNA) method. The visual objects that represent these online interactions are demonstrated and explained. The findings showed that social network analysis provide more meaningful students’ interactions analysis in term of information of communication structures. This approach can be used by instructors to assess social interactions in terms of network structure parameters.
The neuropsychological impact of sports-related concussion: A meta-analysis

There is increasing interest in the potential neuropsychological impact of sports-related concussion. A meta-analysis of the relevant literature was conducted to determine the impact of sports-related concussion across six cognitive domains. The analysis was based on 21 studies involving 790 cases of concussion and 2014 control cases. The overall effect of concussion (d = 0.49) was comparable to the effect found in the non-sports-related mild traumatic brain injury population (d = 0.54; Belanger et al., 2005). Using sports-concussed participants with a history of prior head injury appears to inflate the effect sizes associated with the current sports-related concussion. Acute effects (within 24 hr of injury) of concussion were greatest for delayed memory, memory acquisition, and global cognitive functioning (d = 1.00, 1.03, and 1.42, respectively). However, no residual neuropsychological impairments were found when testing was completed beyond 7 days postinjury. These findings were moderated by cognitive domain and comparison group (control group versus preconcussion self-control). Specifically, delayed memory in studies utilizing a control group remained problematic at 7 days. The implications and limitations of these findings are discussed. (JINS, 2005, 11, 345–357.)
Control of the C. albicans Cell Wall Damage Response by Transcriptional Regulator Cas5

The fungal cell wall is vital for growth, development, and interaction of cells with their environment. The response to cell wall damage is well understood from studies in the budding yeast Saccharomyces cerevisiae, where numerous cell wall integrity (CWI) genes are activated by transcription factor ScRlm1. Prior evidence suggests the hypothesis that both response and regulation may be conserved in the major fungal pathogen Candida albicans. We have tested this hypothesis by using a new C. albicans genetic resource: we have screened mutants defective in putative transcription factor genes for sensitivity to the cell wall biosynthesis inhibitor caspofungin. We find that the zinc finger protein CaCas5, which lacks a unique ortholog in S. cerevisiae, governs expression of many CWI genes. CaRlm1 has a modest role in this response. The transcriptional coactivator CaAda2 is also required for expression of many CaCas5-dependent genes, as expected if CaCas5 recruits CaAda2 to activate target gene transcription. Many caspofungin-induced C. albicans genes specify endoplasmic reticulum and secretion functions. Such genes are not induced in S. cerevisiae, but promote its growth in caspofungin. We have used a new resource to identify a key C. albicans transcriptional regulator of CWI genes and antifungal sensitivity. Our gene expression findings indicate that both divergent and conserved response genes may have significant functional roles. Our strategy may be broadly useful for identification of pathogen-specific regulatory pathways and critical response genes.
DDO 88: A Galaxy-sized Hole in the Interstellar Medium

We present an H I and optical study of the gas-rich dwarf irregular galaxy DDO 88. Although the global optical and H I parameters of DDO 88 are normal for its morphological type, it hosts a large (3 kpc diameter) and unusually complete ring of enhanced H I emission. The normal appearance of this galaxy in the optical and the outer regions of the H I give no hint of the presence of the striking H I ring in the inner regions. The gas ring is located at approximately one-third of the total H I radius and one-half the optically defined Holmberg radius, and contains 30% of the total H I of the galaxy. The ring surrounds a central depression in the H I distribution. If the H I ring and central depression in the gas were formed by the energy input from winds and supernova explosions of massive stars formed in a starburst, as is thought often to be the case, the star-forming event would have formed 0.1%–1% of the total stellar mass of the galaxy. However, the UBV colors in the H I hole are not bluer than the rest of the galaxy, as would be expected if an unusual star-forming event had taken place there recently, although there is an old (∼1–3 Gyr), red cluster near the center of the hole that is massive enough to have produced the hole in the H I. An age estimate for the ring is uncertain, however, because it is not observed to be expanding. An expansion model produces a lower estimate of 0.5 Gyr, but the presence of faint star formation regions associated with the ring indicates a much younger age. We also estimate that the ring could have dispersed by now if it is older than 0.5 Gyr. This implies that the ring is younger than 0.5 Gyr. A younger age would indicate that the red cluster did not produce the hole and ring. Therefore, uncertainties prevent us from concluding that the cluster and the H I hole are definitely related. If this ring and the depression in the gas that it surrounds were not formed by stellar winds and supernovae, this would indicate that some other, currently unidentified, mechanism is operating.
Robust and Efficient Covert Channel Communications in Operating Systems: Design, Implementation and Evaluation

Covert channel has been studied for years due to its ability to divulge sensitive information in computer systems. Constructing covert communication scenarios is the first step to learn the threat of a channel. There are several challenges in the existing design of covert channel communications: lacking general communicating model description, low transmission accuracy and weak anti-interference ability. In this paper, we explore how to construct robust and efficient covert channel communications in operating systems. Firstly, we design three general covert communicating protocol models: the Basic Protocol (BP), the Two-Channel Transmission Protocol (TCTP) and the Self-Adaptive Protocol (SAP). Then we implement them in Linux operating systems. To simulate real attack scenarios, a toy Trojan program extracting passwords to cooperate with the covert protocols is presented. To identify potential covert channels in Linux kernel, we use Directed Information Flow Graph (DIFG) to analyze the source code and choose last_pid and temporary files channels in our implementation. Finally we evaluate the transmitting rate and accuracy of the three protocols. The results demonstrate that without special protective measures, the TCTP can achieve rather high accuracy and rate (100% and 31bps in our lab). When equipped with some restricting or interfering mechanisms, the SAP can achieve 97% accuracy and 18bps rate. This result reveals that attackers can bypass countermeasures to steal sensitive data from victims by well-designed covert protocols.
The impact of antenna diversity in packet data systems with scheduling

It has been observed through simulations of some specific scheduling algorithms that multiuser diversity gains in packet data systems with channel-aware scheduling can be reduced in the presence of any form of link diversity, such as transmit antenna diversity or wideband multipath diversity. We establish that asymptotically, in the limit of large number of transmit antennas and users, the maximum throughput achieved by any optimal scheduling algorithm in the presence of transmit diversity under signal-to-noise-ratio-only feedback can be infinitely worse than that of a system with no diversity. Our results are general and are independent of any particular scheduling algorithm.
Chromatic phenomena in the algebra of BP_{*}BP-comodules

This paper begins with an exposition of the author's research on the category of BP_*BP-comodules, much of which is joint with Neil Strickland. The main result of that work is that the category of E(n)_*E(n)-comodules is equivalent to a localization of the category of BP_*BP-comodules (the localization is L_n, analogous to the topological L_n). The main new result in this paper is that, analogously, the stable homotopy category of E(n)_*E(n)-comodules is equivalent to a localization (the finite localization L_n^f this time, not L_n) of the stable homotopy category of BP_*BP-comodules. These stable homotopy categories were constructed in previous work of the author, and are supposed to model stable homotopy theory; it is like stable homotopy theory where there are no differentials in the Adams-Novikov spectral sequence. Our result embeds the Miller-Ravenel and Hovey-Sadofsky change of rings theorems as special cases of more general isomorphisms.
Predictors of psychological adjustment after bereavement

Background: The impact of spousal bereavement on mental health varies among the widowed. More information is needed on factors influencing bereavement outcome. Method: We conducted a cross-sectional study on a sample of 216 widowed individuals. Initial non-response was high, with only 8% of all approached persons participating in the study. The influence of demographic and psychosocial predictors on four general outcome measures (depression, anxiety, somatization, and quality of life) and one loss-related outcome (complicated grief) was studied by means of backward linear regression analysis. Further analyses were performed to explore the possibility of a buffer effect. Results: Depressive symptomatology was best predicted by: age, duration of widowhood, perceived non-supportiveness, physical disorders, and mastery. The other outcome measures were predicted by the same predictors supplemented by gender and education. Mastery interacted with the number of physical disorders while perceived social support interacted with duration of widowhood and age. Conclusions: Enhancement of mastery should probably be one of the components of effective support for widowed individuals most vulnerable to psychiatric complications. The widowed could furthermore benefit from social support. Obviously, these suggestions need to be further examined in longitudinal research with more representative samples.
Modeling Viral Evolutionary Dynamics after Telaprevir-Based Treatment

For patients infected with hepatitis C virus (HCV), the combination of the direct-acting antiviral agent telaprevir, pegylated-interferon alfa (Peg-IFN), and ribavirin (RBV) significantly increases the chances of sustained virologic response (SVR) over treatment with Peg-IFN and RBV alone. If patients do not achieve SVR with telaprevir-based treatment, their viral population is often significantly enriched with telaprevir-resistant variants at the end of treatment. We sought to quantify the evolutionary dynamics of these post-treatment resistant variant populations. Previous estimates of these dynamics were limited by analyzing only population sequence data (20% sensitivity, qualitative resistance information) from 388 patients enrolled in Phase 3 clinical studies. Here we add clonal sequence analysis (5% sensitivity, quantitative) for a subset of these patients. We developed a computational model which integrates both the qualitative and quantitative sequence data, and which forms a framework for future analyses of drug resistance. The model was qualified by showing that deep-sequence data (1% sensitivity) from a subset of these patients are consistent with model predictions. When determining the median time for viral populations to revert to 20% resistance in these patients, the model predicts 8.3 (95% CI: 7.6, 8.4) months versus 10.7 (9.9, 12.8) months estimated using solely population sequence data for genotype 1a, and 1.0 (0.0, 1.4) months versus 0.9 (0.0, 2.7) months for genotype 1b. For each individual patient, the time to revert to 20% resistance predicted by the model was typically comparable to or faster than that estimated using solely population sequence data. Furthermore, the model predicts a median of 11.0 and 2.1 months after treatment failure for viral populations to revert to 99% wild-type in patients with HCV genotypes 1a or 1b, respectively. Our modeling approach provides a framework for projecting accurate, quantitative assessment of HCV resistance dynamics from a data set consisting of largely qualitative information.