Dynamic Canonical and Microcanonical Transition Matrix Analyses of Critical Behavior

By monitoring the sampling of states with different magnetizations in transition matrix procedures a family of accurate and easily implemented techniques are constructed that automatically control the variation of the temperature or energy as the calculation proceeds. The accuracy of the method for a single Markov chain exceeds that of standard transition matrix procedures that accumulate elements from multiple chains.Comment: 17 pagess 10 figure

Hard Decision Combining-based Cooperative Spectrum Sensing in Cognitive Radio Systems

In this paper, we propose a hard decision combining-based cooperative spectrum sensing scheme to maximize the detection probability in cognitive radio systems. We maximize the detection probability by finding the optimum number of cooperating users for a given false alarm probability. To this end, we analytically derive a closed-form expression for the detection and false alarm probability in terms of the number of cooperating users. It is shown that the detection probability of cooperative sensing is maximized when the optimum number of users with good reporting channel condition and high interference to noise ratio are selected. The analytic results are verified by computer simulation.Seoul R&BS Progra

Channel Probing in the Uplink of OFDM-based Wireless Systems

In this paper, we consider a new channel probing scheme for opportunistic scheduling in the uplink of orthogonal frequency division multiplexing (OFDM)-based wireless systems. To reduce signaling overhead for the probing, we consider a twostep channel probing process; called pre-probing and mainprobing. Good subchannels are first estimated through the preprobing process using a probing signal transmitted through subcarriers spread out the whole bandwidth. Then, by sending a main-probing signal over only good subchannels, the proposed scheme can significantly reduce the probing signaling overhead without noticeable performance degradation compared to the full probing scheme. Finally, the performance of the proposed scheme is verified by computer simulation

I-gel as a first-line airway device in the emergency room for patients with out-of-hospital cardiac arrest

Aim. The optimal method for advanced airway management during cardiac arrest remains controversial. Most patients with out-of-hospital cardiac arrest (OHCA) in Korea are managed with a bag-valve mask by paramedics, while physicians perform advanced airway management in emergency departments (ED). Endotracheal intubation (ETI) has a risk of failure at the first attempt. By contrast, I-gel, a supraglottic airway device, is easier to insert than an endotracheal tube and shows a higher first-attempt success rate than ETI in out-of-hospital settings by paramedics in the United States. We reviewed the use of ETI and I-gel by ED physicians to assess the first attempt success rate in a hospital setting. Methods. We conducted a retrospective chart review of patients with non-traumatic OHCA who were managed with either ETI using a Macintosh laryngoscope, or I-gel in the ED of Korean hospital from January 2012 to January 2014. Results. Of 322 adult patients with non-traumatic OHCA, 160 received I-gel and 162 received ETI. The first-attempt success rate was higher in the I-gel group (96.9%) than in the ETI group (84.6%, p < 0.001). The time from arrival to obtaining advanced airway management was shorter in the I-gel group than in the ETI group. Conclusions. I-gel showed a better first-attempt success rate and shorter insertion time compared with ETI when performed by physicians in a hospital setting

Transition Matrix Monte Carlo Methods for Complex Systems

The aim of this thesis is to develop efficient transition matrix Monte Carlo simulation methods for complex systems(e.g., spin glasses) that enable one to construct the transition matrix from which the density of states is calculated with high accuracy. In this thesis, I explore a series of the transition matrix Monte Carlo techniques that are newly developed to generate the density of states with high accuracy for various systems that exhibit phase transitions. The Ising model and the Potts model are used to demonstrate the performance of each methods. Especially, the specific heat curve of the two-dimensional Ising model is evaluated and compared to the exact result as a stringent accuracy test in many cases. I extend the \emph{monovariate} multicanonical transition matrix Monte Carlo method to a \emph{bivariate} version for the calculation of the joint density of states which depends on the energy and a second variable associated with the order parameter. This bivariate version is applied to the Edward-Anderson spin glass model which is one of the most challenging model in the field of computer simulation. After presenting the theoretical basis of the transition matrix Monte Carlo method, I explain the regulated temperature method which populates the transition matrix by the Metropolis algorithm with continuously varying temperature according to a certain schedule. I introduce new techniques that can produce the optimized temperature schedule in the context of the two-dimensional Ising model. Next I proceed to present the multicanonical transition matrix Monte Carlo method in which the transition matrix is constructed through the multicanonical iteration procedure. Although this method itself is faster than other existing techniques such as the broad histogram method and Wang-Landau algorithm, its simulation speed can be further increased by the renormalization idea which utilizes the simulation results for a small system to obtain an accurate initial estimate of the density of states for a large system through the convolution procedures. Especially a novel procedure about how to apply the renormalization idea in multiple dimensions is presented. To study the critical behavior of the spin glasses, to my knowledge for the first time, I employ the \emph{bivariate} multicanonical sampling to construct the transition tensor from which the joint density of states can be calculated with high accuracy. I introduce a calculation technique that transforms the massive transition tensor to a normal transition matrix to avoid the cumbersome manipulation of tensors. Using the joint density of states, Landau free energies, the probability distribution functions of spin overlap and Binder parameters are calculated. Contrary to the majority of the previous reports in the literature, the results of my method provide evidences that nonzero temperature phase transition occurs in the two-dimensional Ising spin glass. For the $\pm J$ Ising spin glass, the critical temperature obtained by my method is $T_c/J \approx 0.45$ However, a definite conclusion can not be made due to small systems sizes and the limitted number of samples of random couplings

Characterization of Double-Stranded RNA and Fungal Virus From Diaporthe Phaseolorum Var. Caulivora.

Fifty-two isolates of Diaporthe phaseolorum var. caulivora originating from eight different states of the United States were collected and grown on potato dextrose broth for 2-3 wk. Double-stranded RNA was extracted by two cycles of cellulose (CF-11) chromatography and electrophoresed on 6% polyacrylamide gel. Among all isolates tested, 28 (54%) contained at least one molecule of dsRNA. Molecular sizes of dsRNA ranged from 0.4 to 4.5 Kb, and seven different sizes of dsRNA were detected. The 4.5 Kb dsRNA did not have sequence homology with smaller dsRNAs (2.1, 1.8, and 1.4 Kb), suggesting that the smaller dsRNAs are not deletion products of the 4.5 Kb dsRNA. The dsRNAs were located in the cytoplasm of the fungi. The dsRNA of D. p. caulivora was apparently not associated with pathogenicity, toxin production, growth rate, or phenol oxidase activity. Isometric virus particles about 30-40 nm in diameter were detected from a virulent isolate. The viral genome was composed of one double-stranded RNA molecule with a molecular size of 4.5 Kb. The molecular size of viral dsRNA was the same as that extracted from mycelia. Three polypeptides (93 Kd, 90 Kd, and 88 Kd) were associated with the virus particles. Polyclonal antibodies generated to virus particles reacted to all three viral polypeptides. These data suggest that this virus, designated as DpcV, is a possible member of the Totoviridae. To compare southern and northern isolates of this pathogen, fourteen selected isolates representing six southern states (AR, FL, GA, LA, MS, and TN) and two northern states (IO and OH) were compared for colony morphology, mycelial growth at 22 and 30 C, type of perithecia formation, phenol oxidase activity, pathogenicity, and phenol-soluble polypeptides by two-dimensional electrophoresis. Southern isolates showed more variable colony morphology, mycelial growth at both temperatures, phenol oxidase activity, type of perithecia formation, and level of pathogenicity to soybean cultivar Bedford than northern isolates. Greater genetic diversity was observed among southern isolates than among northern isolates in polypeptide analysis. However, polypeptide analysis by two-dimensional electrophoresis indicated a strong genetic relationship between the two populations, suggesting that the fungi causing southern and northern stem canker are the same fungus

Adaptive Pilot Signaling in the Uplink of OFDM-Based Wireless Systems

Orthogonal frequency division multiplexing (OFDM) has been considered as one of key transmission technologies for high-speed wireless communication systems. For channel-adaptive transmission of OFDM signal, base stations transmit a common pilot signal in the downlink, but mobile stations transmit individual pilot signal in the uplink. As a consequence, the uplink may suffer from poorer channel estimation accuracy than the downlink. This problem can be alleviated by increasing the pilot signal density. But this reduces the time and frequency resources for the data transmission, deteriorating the actual transmission throughput. In this paper, we propose an adaptive pilot signaling scheme that adjusts the pilot density in response to the change of channel characteristics. Simulation results show that the proposed scheme can remarkably reduce the pilot overhead without performance degradation, compared to conventional schemes

Indexing and Retrieving Photographic Images Using a Combination of Geo-Location and Content-Based Features

This paper presents a novel method that automatically indexes searches for relevant images using a combination of geo-coded information and content-based visual features. Photographic images are labeled with their corresponding GPS (Global Positioning System) coordinates and UTC time (Coordinated Universal Time) information at the moment of capture, which are then utilized to create spatial and temporal indexes for photograph retrieval. Assessing the performance in terms of average precision and F-score with real-world image collections revealed that the proposed approach significantly improved and enhanced the retrieval process compared to searches based on visual content alone. Combining content and context information thus offers a useful and meaningful new approach to searching and managing large image collections