Optimized Error Detection in Cloud User for Networking Services

Big sensor data is prevalent in both industry and scientific research applications where the data is generated with high volume and velocity it is difficult to process using on-hand database management tools or traditional data processing applications. Cloud computing provides a promising platform to support the addressing of this challenge as it provides a flexible stack of massive computing, storage, and software services in a scalable manner at low cost. Some techniques have been developed in recent years for processing sensor data on cloud, such as sensor-cloud. However, these techniques do not provide efficient support on fast detection and locating of errors in big sensor data sets. For fast data error detection in big sensor data sets, in this paper, we develop a novel data error detection approach which exploits the full computation potential of cloud platform and the network feature of WSN

PERFORMANCE EVALUATION OF SMART ANTENNA DOA ESTIMATION USING MUSIC & IMPROVED MUSIC ALGORITHMS

Array signal processing deals with the manipulation of signals for null steering to reduce interference and to point the major lobe towards the intended signal. High Resolution signal processing always involves high cost and high computational complexity. This paper shows the analysis of direction of arrival estimation in smart antenna systems using the high resolution multiple signal classification (MUSIC) and improved MUSIC algorithm. To show the simulations, MATLAB (R2011a) is used which offers a lot of instructions and functions which make the simulations more convenient. The simulations show what factors affects the accuracy, the resolution of the direction of arrival (DOA) estimation and the modifications made to the already existing algorithm to estimate arrival angles of coherent signals. There are many algorithms which can be used in DOA estimation which have made great achievements; the most classic algorithm among all is the MUSIC algorithm. As MUSIC algorithm is only limited to uncorrelated signals, Improved MUSIC algorithm is proposed which can be used for coherent signals also

Improving Impedance of Implantable Microwire Multi-Electrode Arrays by Ultrasonic Electroplating of Durable Platinum Black

Implantable microelectrode arrays (MEAs) have been a boon for neural stimulation and recording experiments. Commercially available MEAs have high impedances, due to their low surface area and small tip diameters, which are suitable for recording single unit activity. Lowering the electrode impedance, but preserving the small diameter, would provide a number of advantages, including reduced stimulation voltages, reduced stimulation artifacts and improved signal-to-noise ratio. Impedance reductions can be achieved by electroplating the MEAs with platinum (Pt) black, which increases the surface area but has little effect on the physical extent of the electrodes. However, because of the low durability of Pt black plating, this method has not been popular for chronic use. Sonicoplating (i.e. electroplating under ultrasonic agitation) has been shown to improve the durability of Pt black on the base metals of macro-electrodes used for cyclic voltammetry. This method has not previously been characterized for MEAs used in chronic neural implants. We show here that sonicoplating can lower the impedances of microwire multi-electrode arrays (MMEA) by an order of magnitude or more (depending on the time and voltage of electroplating), with better durability compared to pulsed plating or traditional DC methods. We also show the improved stimulation and recording performance that can be achieved in an in vivo implantation study with the sonicoplated low-impedance MMEAs, compared to high-impedance unplated electrodes

MANAGING AND STORAGE DETECTION OF EFFECTIVE RE PROTECT IN WSNS

Using the Copy Recognition procedure, it is designed to increase the recognition. Objective will a procedure for the Recognition of Distributed Copies with Random Selection of Witnesses to increase the probability of identifying cloning as an impact on the useful life of the network and reduce the advantages of buffering data storage. The loop structure facilitates the transmission of energy saving data through the path for both witnesses and for good. Theoretically, we show that the protocol is capable of achieving 100% of the possibility of identifying cloning with reliable controls. In particular, we use the location information of the sensors and the random selection tokens located at the location of the diamond ring to verify the sensors and also to report the detected cloning attacks. In addition, in many replication identification protocols that exist with the Random Witness Selection Scheme, the required caching of the sensors is generally determined by the density of the node. The complete simulation shows that can effectively extend the life of the network by effectively distributing traffic through the network. The current system does not ensure that at least one of the witnesses can see the identity of the sensor points to see if there is a clone attack or not. The performance of the ERCD is evaluated when it is possible to identify cloning, power consumption, age of the network and the capacity of the knowledge store. The broad results of the simulation show that ERCD protocol is capable of offering superior performance in terms of user recognition and network life with a reasonable data storage capacity

High-throughput mapping of regulatory DNA

Quantifying the effects of cis-regulatory DNA on gene expression is a major challenge. Here, we present the multiplexed editing regulatory assay (MERA), a high-throughput CRISPR-Cas9–based approach that analyzes the functional impact of the regulatory genome in its native context. MERA tiles thousands of mutations across ~40 kb of cis-regulatory genomic space and uses knock-in green fluorescent protein (GFP) reporters to read out gene activity. Using this approach, we obtain quantitative information on the contribution of cis-regulatory regions to gene expression. We identify proximal and distal regulatory elements necessary for expression of four embryonic stem cell–specific genes. We show a consistent contribution of neighboring gene promoters to gene expression and identify unmarked regulatory elements (UREs) that control gene expression but do not have typical enhancer epigenetic or chromatin features. We compare thousands of functional and nonfunctional genotypes at a genomic location and identify the base pair–resolution functional motifs of regulatory elements.National Institutes of Health (U.S.) (1U01HG007037

A View of Tropical Cyclones from Above: The Tropical Cyclone Intensity Experiment

Tropical cyclone (TC) outflow and its relationship to TC intensity change and structure were investigated in the Office of Naval Research Tropical Cyclone Intensity (TCI) field program during 2015 using dropsondes deployed from the innovative new High-Definition Sounding System (HDSS) and remotely sensed observations from the Hurricane Imaging Radiometer (HIRAD), both on board the NASA WB-57 that flew in the lower stratosphere. Three noteworthy hurricanes were intensively observed with unprecedented horizontal resolution: Joaquin in the Atlantic and Marty and Patricia in the eastern North Pacific. Nearly 800 dropsondes were deployed from the WB-57 flight level of ∼60,000 ft (∼18 km), recording atmospheric conditions from the lower stratosphere to the surface, while HIRAD measured the surface winds in a 50-km-wide swath with a horizontal resolution of 2 km. Dropsonde transects with 4–10-km spacing through the inner cores of Hurricanes Patricia, Joaquin, and Marty depict the large horizontal and vertical gradients in winds and thermodynamic properties. An innovative technique utilizing GPS positions of the HDSS reveals the vortex tilt in detail not possible before. In four TCI flights over Joaquin, systematic measurements of a major hurricane’s outflow layer were made at high spatial resolution for the first time. Dropsondes deployed at 4-km intervals as the WB-57 flew over the center of Hurricane Patricia reveal in unprecedented detail the inner-core structure and upper-tropospheric outflow associated with this historic hurricane. Analyses and numerical modeling studies are in progress to understand and predict the complex factors that influenced Joaquin’s and Patricia’s unusual intensity changes

Utility of positron emission tomography-computed tomography in patients with chronic lymphocytic leukemia following B-cell receptor pathway inhibitor therapy

The utility of positron emission tomography-computed tomography (PET-CT) in distinguishing Richter’s transformation versus chronic lymphocytic leukemia (CLL) progression after ibrutinib and/or idelalisib was assessed in a post hoc analysis of a phase II study of venetoclax. Patients underwent PET-CT at screening and were not enrolled/treated if Richter’s transformation was confirmed pathologically. Of 167 patients screened, 57 met criteria for biopsy after PET-CT. Of 35 patients who underwent biopsy, eight had Richter’s transformation, two had another malignancy, and 25 had CLL. A PET-CT maximum standardized uptake value (SUVmax) ≥10 had 71% sensitivity and 50% specificity for detecting Richter’s transformation [Odds Ratio (OR): 2.5, 95%CI: 0.4-15; P=0.318]. Response rate to venetoclax was similar for screening SUVma

Mortality and pulmonary complications in patients undergoing surgery with perioperative SARS-CoV-2 infection: an international cohort study

Background: The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on postoperative recovery needs to be understood to inform clinical decision making during and after the COVID-19 pandemic. This study reports 30-day mortality and pulmonary complication rates in patients with perioperative SARS-CoV-2 infection. Methods: This international, multicentre, cohort study at 235 hospitals in 24 countries included all patients undergoing surgery who had SARS-CoV-2 infection confirmed within 7 days before or 30 days after surgery. The primary outcome measure was 30-day postoperative mortality and was assessed in all enrolled patients. The main secondary outcome measure was pulmonary complications, defined as pneumonia, acute respiratory distress syndrome, or unexpected postoperative ventilation. Findings: This analysis includes 1128 patients who had surgery between Jan 1 and March 31, 2020, of whom 835 (74·0%) had emergency surgery and 280 (24·8%) had elective surgery. SARS-CoV-2 infection was confirmed preoperatively in 294 (26·1%) patients. 30-day mortality was 23·8% (268 of 1128). Pulmonary complications occurred in 577 (51·2%) of 1128 patients; 30-day mortality in these patients was 38·0% (219 of 577), accounting for 81·7% (219 of 268) of all deaths. In adjusted analyses, 30-day mortality was associated with male sex (odds ratio 1·75 [95% CI 1·28–2·40], p\textless0·0001), age 70 years or older versus younger than 70 years (2·30 [1·65–3·22], p\textless0·0001), American Society of Anesthesiologists grades 3–5 versus grades 1–2 (2·35 [1·57–3·53], p\textless0·0001), malignant versus benign or obstetric diagnosis (1·55 [1·01–2·39], p=0·046), emergency versus elective surgery (1·67 [1·06–2·63], p=0·026), and major versus minor surgery (1·52 [1·01–2·31], p=0·047). Interpretation: Postoperative pulmonary complications occur in half of patients with perioperative SARS-CoV-2 infection and are associated with high mortality. Thresholds for surgery during the COVID-19 pandemic should be higher than during normal practice, particularly in men aged 70 years and older. Consideration should be given for postponing non-urgent procedures and promoting non-operative treatment to delay or avoid the need for surgery. Funding: National Institute for Health Research (NIHR), Association of Coloproctology of Great Britain and Ireland, Bowel and Cancer Research, Bowel Disease Research Foundation, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, NIHR Academy, Sarcoma UK, Vascular Society for Great Britain and Ireland, and Yorkshire Cancer Research

Probabilistic Verification of Global and Mesoscale Ensemble Forecasts of Tropical Cyclogenesis

Abstract Probabilistic forecasts of tropical cyclogenesis have been evaluated for two samples: a near-homogeneous sample of ECMWF and Weather Research and Forecasting (WRF) Model–ensemble Kalman filter (EnKF) ensemble forecasts during the National Science Foundation’s (NSF) Pre-Depression Investigation of Cloud-systems in the Tropics (PREDICT) field campaign (15 August–30 September 2010) and ECMWF ensemble forecasts during the 2010–12 Atlantic hurricane seasons. Quantitative criteria for tropical cyclone (TC) formation were first determined from model analyses based on threshold values of lower-tropospheric circulation, local thickness anomaly, and minimum sea level pressure. A binary verification was then performed for all ensemble forecasts with initial-time tropical disturbances. During the PREDICT period, the ECMWF and WRF–EnKF had similar verification statistics, with reliability diagrams of positive slope flatter than unity, and relative operating characteristic (ROC) curves that demonstrate skill. For the 2010–12 ECMWF ensemble forecasts, the equitable threat score was small and positive, with skill mostly lost after 5 days. The reliability diagrams for 1–5-day forecasts were monotonic increasing, though an overly large number of short-range ensemble forecasts predicted a low probability of a TC when a TC was verified. The ROC curves exhibited similar skill for forecasts out to 5 days. The reliability curves were sensitive to parameters such as time tolerance and threshold values, and insensitive to cases that originated from African easterly waves versus those that did not. Qualitative investigations revealed case-to-case variability in the probabilistic predictions. While the sample size was limited, the ensembles showed the potential for probabilistic prediction out to 5 days, though it appeared that the model struggled with developing a warm core in the short-range forecast

Synergistic applications of autonomous underwater vehicles and regional ocean modeling system in coastal ocean forecasting

The potential for using synergistic combinations of measurements from autonomous underwater vehicles (AUVs) and output from three-dimensional numerical models for studying the central California coastal region is demonstrated. Two case studies are used to illustrate the approach. In the first, propeller-driven AUV observations revealed a subsurface salinity minimum in northern Monterey Bay. A Regional Ocean Modeling System (ROMS) reanalysis of the three-dimensional flow in the region suggested an offshore source for this water and particular propagation pathways from the south and west into the bay. In the second case study, the effectiveness of assimilating observations in improving the ROMS reanalysis fields is investigated. A significant improvement, especially in the salinity fields, is demonstrated through a single glider deployed outside the intensive observational domain. These results suggest that investigation of more sophisticated techniques for using data and models together is warranted. Such techniques include increasing model resolution in areas of interest identified by observing platforms and using model-based targeted observing techniques to identify areas of uncertainty in the flow to guide placement of observational assets