A novel algorithm for software defined networks model to enhance the quality of services and scalability in wireless network

Software defined networks (SDN) have replaced the traditional network architecture by separating the control from forwarding planes. SDN technology utilizes computer resources to provide worldwide effective service than the aggregation of single internet resources usage. Breakdown while resource allocation is a major concern in cloud computing due to the diverse and highly complex architecture of resources. These resources breakdowns cause delays in job completion and have a negative influence on attaining quality of service (QoS). In order to promote error-free task scheduling, this study represents a promising fault-tolerance scheduling technique. For optimum QoS, the suggested restricted Boltzmann machine (RBM) approach takes into account the most important characteristics like current consumption of the resources and rate of failure. The proposed approach's efficiency is verified using the MATLAB toolbox by employing widely used measures such as resource consumption, average processing time, throughput and rate of success.

Hydraulic Fracturing as Game Changer to Maximize Waterflooding Efficiency in a Brownfield

Primary production mechanism of a clean sandstone reservoir in a brownfield for oil production has been recently changed from natural depletion to waterflooding. Despite the apparently moderate petro-physical properties of the formation, injector wells performances were observed to be extremely poor, mainly due to: high drilling-induced formation damage and Fluids interaction within the reservoir (injection across the oil rim section). Several stimulation technologies have been applied to improve wells injection capability for pressure support optimization. Re-perforation via abrasive jetting, perforations wash through coiled tubing and various acid formulations via bullheading were attempted without achieving any significant increase in injectivity. Considering the modest rock permeability, the need to access a wider formation area to improve oil sweep efficiency and the crucial requirement to re-pressurize the reservoir, an additional card was played as last resort: hydraulic fracturing. This technique was not new to the area and already experimented by different operators. Several producer wells in different layers were hydraulic fracturing stimulated with proppant and/or acid in the past with a good rate of success. Why not to try then? Given the past experience on the same field with hydraulic fracturing in oil producers and accounting for well integrity and potential injectivity, one was chosen as suitable candidate. Offset wells hystorical data were used to build a hydraulic fracturing reservoir model and plan for the activity in details; operator and service providers engaged in a Frac Well On Paper activity in order to reduce any margin of error during field operations. An approach that proved successful. From there, the first trial well was planned and performed successfully. 4 other hydraulic fracturing jobs on 4 wells followed at close distance in time with different, but steadily comforting, results. Injection was improved from negligible initial values up to 2000 mc/day for the post-stimulation condition, exceeding the preliminary expectations. This paper introduces the steps taken to start the hydraulic fracturing campaign, the decision process that led to the design of the treatment, an overview of the execution phases, results well by well and lessons learned to optimize future campaigns.

A Survey of HISs with Information Systems Success Model

Hospital Information System (HIS) is a form of healthcare information system that is globalized and applied in the medical sector. Researchers, doctors, and management are all interested in the rate of success of HISs; therefore it's a continuous study topic. At this research, we created a new tool to assess the success rate of HIS in a medical center based on the perspectives of users. The research was place in Ebnesina and Mashhad, Persia, at the Dr. Hejazi Mental Center and Educational Facility. A self-administered standardized questionnaire based on Information Systems Success Model (ISSM) was used to gather data, and it included seven factors: systems quality, data quality, quality of service, system use, applicability, fulfillment, and positive externalities. An advisory group checked the content's legitimacy. Cronbach alpha was used to test the consistency and stability of dimensions. To examine the importance of relationships between variables, Correlation and regression was determined. On the basis of user feedback, the HIS rate of success has been established. The research included a approximately 125 participants. A content validity index (CVI) of 0.8 and a validity ratio (CVR) of 0.86 were used by an advisory committee to verify the item. The instruments have an overall Cronbach's alpha of 0.9. Between the analyzed dimensions, the Pearson’s correlation coefficient revealed substantial positive connections. In the institution under investigation, the HIS rate of success averaged 65 percent. (CI: 64 percent, 67 percent). The greatest success rates were found in the aspects of "effectiveness," "systems quality," and "positive externalities." Future research might employ the tool used in this research to evaluate HIS. In this research, a technique for calculating the HIS rate of success depending on user feedback was established. This strategy enables institutional HIS chances of success to be compared. Our results also highlight the perspectives of HIS clients in a developing economy.

Classification of Parkinson’s disease patients based on spectrogram using local binary pattern descriptors

Extreme learning machine is an algorithm that has shown a good performance facing classification and regression problems. It has gained great acceptance by the scientific community due to the simplicity of the model and its sola great generalization capacity. This work proposes the use of extreme learning machine neural networks to carry out the classification between Parkinson’s disease patients and healthy individuals. The descriptor used corresponds to the feature vector generated applying the local binary Pattern algorithm to the grayscale spectrograms. The spectrograms are obtained from the audio signal samples from the considered repository. Experiments are conducted with single hidden layer and multilayer extreme learning machine networks comparing the results of each structure. Results show that hierarchical extreme learning machine with three hidden layers has a better general performance over multilayer extreme learning machine networks and a single hidden layer extreme learning machine. The rate of success obtained is within the ranges presented in the literature. However, the hierarchical network training time is considerably faster compared to multilayer networks of three or two hidden layers.

Study about Tuberculosis in Thailand: An approach to Treatment, GIS and Sichon Model

In this study, we seek to identify geographical areas where ongoing tuberculosis epidemiological characteristics is occurring by linking Geographic Information Systems (GIS) technology in Thailand. In addition, we seek to assess how the directly observed treatment short-course (DOTS) program improved new tuberculosis diagnosis and treatment successes in Sichon District, Nakhon Si Thammarat province, Thailand from 2014 to 2016. The assessment program included seven indicators, and the results revealed that 73 new cases of tuberculosis were admitted for treatment on average every year, with rates of risk group screening findings of 4.28, 5.23, and 6.04 %, respectively. Patients who come to the hospital for diagnosis make up most of the demographic. However, only a minor proportion of patients are identified through community-based primary screening. In the years 2013-2016, the mortality rate of TB cases is expected to rise by 10.25 %, 4.25 %, and 5.56 %, respectively. The elderly and HIV-positive patients comprise most of the TB mortality population. When completing the DOTS program at a hospital, however, the rate of success has fallen short of the targets. Furthermore, the screening technique excludes the target group. As a result, people suffering tuberculosis are reported to be slower and more susceptible to symptoms. As a result, researchers advise that the DOTS program be supported by enhancing treatment follow-up to improve the effectiveness of TB treatment and collaboration with health care worker (HCW).

A Comprehensive Study on Various Statistical Techniques for Prediction of Movie Success

The film industry is one of the most popular entertainment industries and one of the biggest markets for business. Among the contributing factors to this would be the success of a movie in terms of its popularity as well as its box office performance. Hence, we create a comprehensive comparison between the various machine learning models to predict the rate of success of a movie. The effectiveness of these models along with their statistical significance is studied to conclude which of these models is the best predictor. Some insights regarding factors that affect the success of the movies are also found. The models studied include some Regression models, Machine Learning models, a Time Series model and a Neural Network with the Neural Network being the best performing model with an accuracy of about 86%. Additionally, as part of the testing data for the movies released in 2020 are analysed.

Effectiveness of snap traps on capturing rodent and small mammals in rural area of two provinces (Yogyakarta and West Java) in Indonesia

The study was conducted to determine the effectiveness of snap traps on capturing the rodents and small mammals in two provinces (Yogyakarta and West Java). A small rural area surrounded by large scale ricecrops which indicate rodent damage seasonally was selected as the study site. The trappings were executed during the period of November 2018 – August 2020. Consecutive trappings were performed in two regions using snap traps baited with fresh salty fish and roasted coconut. Around 40-65 traps were set in West Java study sites and 60-65 traps in Yogyakarta for every single trap night, respectively. We checked the captured animals in the early morning and collected them for identification and sexing. In the late afternoon we continued with cleaning of the traps and put in the new same type of bait. A total of 517 animals were obtained with the proportion of the two sexes was almost the same (45.45% males:54.40% females). Based on the physical characteristics, those captured animals were three rodent species (Rattus argentiventer, Rattus tanezumi, Bandicota indica) and one species of insectivore (Suncus murinus). Regarding trapping rate of success, Yogyakarta denoted average values (21.38% in the first trapping and 26.04% from the second trapping) compared to West Java which was only accounted for half of them (11.31% and 11.24% from the first and second trapping, respectively). The heterogeneous habitat configuration probably allowed this situation to occur in Yogyakarta. Moreover, rodent control activities in West Java were implemented more intensively compared to Yogyakarta.

Safety in training for ultrasound guided internal jugular vein CVC placement: a propensity score analysis

Background Central venous catheter (CVC) placement is a routine procedure but is potentially associated with severe complications. Relatively small studies investigated if the use of ultrasound is effective in bridging the skill gap between proficient and not proficient operators, while patient safety during training remains a controversial topic. The first aim of this study was to evaluate if resident proficiency affects the failure rate in CVC positioning under ultrasound guidance. In addition, it aimed to investigate the different rate of complications between proficient and non proficient residents. Methods We conducted a cohort study including CVC placed by residents at the University Hospital of Padova, from November 1, 2012 to July 9, 2020 comparing proficient and non proficient residents. To avoid bias the two cohorts were matched using propensity score. Results A total of 356 residents positioned 2310 CVC during the 8 year study period. Among them, two groups of 1060 CVCs each were matched with a propensity score analysis. There was no difference in the failure rate among the groups (2.8 vs 2.7%, p-value 0.895). Moreover, cohorts had the same rate of hematomas, catheter tip malposition, arterial puncture and pneumothorax. No cases of hemothorax were reported. Conclusions We found the same rate of success and incidence of adverse complications among cohorts, meaning that the process of skill acquisition is safe as long as appropriate training and direct supervision by a senior consultant are available.

Building innovation capabilities through human resources practices

Purpose Considering the distressingly low rate of success in introducing radical new products, the purpose of this paper is to reinforce the importance of taking human resources beyond administrative activity leading to stronger innovation performance and the greater use of its people. In particular, this paper highlights three persistent fallacies in human resource practices: need for creativity; efficiency of bottom-up efforts; and monetary incentives for product innovations and to learn from innovative organizations about how to deal with these fallacies. Design/methodology/approach This paper details the correlation between culture, confidence, support mechanisms through HR, and innovation by reviewing innovation cases in high-performing organizations. Findings Problem definition, pragmatism and leadership represent critical innovation determinants. As a strategic partner HR can offer support to tackle the three described fallacies of product innovations. Originality/value This paper suggests a practical means for helping HR professionals to better understand how some simple organizational rules can effectively build innovation capabilities.

The Role of Noninvasive Respiratory Management in Patients with Severe COVID-19 Pneumonia

Acute hypoxemic respiratory failure is the principal cause of hospitalization, invasive mechanical ventilation and death in severe COVID-19 infection. Nearly half of intubated patients with COVID-19 eventually die. High-Flow Nasal Oxygen (HFNO) and Noninvasive Ventilation (NIV) constitute valuable tools to avert endotracheal intubation in patients with severe COVID-19 pneumonia who do not respond to conventional oxygen treatment. Sparing Intensive Care Unit beds and reducing intubation-related complications may save lives in the pandemic era. The main drawback of HFNO and/or NIV is intubation delay. Cautious selection of patients with severe hypoxemia due to COVID-19 disease, close monitoring and appropriate employment and titration of HFNO and/or NIV can increase the rate of success and eliminate the risk of intubation delay. At the same time, all precautions to protect the healthcare personnel from viral transmission should be taken. In this review, we summarize the evidence supporting the application of HFNO and NIV in severe COVID-19 hypoxemic respiratory failure, analyse the risks associated with their use and provide a path for their proper implementation.