Coding Opportunities from Similar Data in Wireless Cooperation Diversity Systems

2011 ◽  
Author(s):  
Tobias Volkhausen ◽  
Kai Schinkothe ◽  
Holger Karl
Keyword(s):  
Similar Data ◽  
Diversity Systems ◽  
Wireless Cooperation ◽  
Cooperation Diversity

Ultrastructure of the basal body apparatus in epidermal cells of a sponge larva (Aplysilla SP: Demospongiae)

1992 ◽  
Vol 50 (1) ◽  
pp. 928-929
Author(s):  
R.L. Pinto ◽  
R.M. Woollacott
Keyword(s):  
Sodium Bicarbonate ◽  
Epoxy Resin ◽  
Basal Body ◽  
Phosphate Buffer ◽  
Similar Data ◽  
Basal Apparatus ◽  
Striated Rootlet ◽  
The Common ◽  
Basal Foot ◽  
Sexually Mature

The basal body and its associated rootlet are the organelles responsible for anchoring the flagellum or cilium in the cytoplasm. Structurally, the common denominators of the basal apparatus are the basal body, a basal foot from which microtubules or microfilaments emanate, and a striated rootlet. A study of the basal apparatus from cells of the epidermis of a sponge larva was initiated to provide a comparison with similar data on adult sponges.Sexually mature colonies of Aplysillasp were collected from Keehi Lagoon Marina, Honolulu, Hawaii. Larvae were fixed in 2.5% glutaraldehyde and 0.14 M NaCl in 0.2 M Millonig’s phosphate buffer (pH 7.4). Specimens were postfixed in 1% OsO4 in 1.25% sodium bicarbonate (pH 7.2) and embedded in epoxy resin. The larva ofAplysilla sp was previously described (as Dendrilla cactus) based on live observations and SEM by Woollacott and Hadfield.

Voice Therapy With Seniors: Attendance, Outcomes, and Associated Patient Characteristics

2019 ◽  
Vol 4 (5) ◽  
pp. 814-824 ◽  
Author(s):  
Bonnie E. Smith ◽  
Ruth Huntley Bahr ◽  
Hector N. Hernandez
Keyword(s):  
Outcome Data ◽  
Voice Therapy ◽  
Similar Data ◽  
Success Rates ◽  
Reflux Symptom Index ◽  
Voice Change ◽  
Related Factors ◽  
Symptom Index ◽  
Younger Patients ◽  
Unsuccessful Treatment

Purpose The purpose of this study was to determine the attendance and success rates for seniors in voice therapy, identify any contributing patient-related factors, and compare results to existing findings for younger patients. Method This retrospective study included information from the voice records of 50 seniors seen by the same speech-language pathologist in a private practice. Analysis of attendance and outcome data divided participants into 6 groups. Outcomes for Groups 1–3 (64% of patients) were considered successful (positive voice change), while outcomes for Groups 4–6 (36% of patients) were considered unsuccessful. These data were compared to similar data collected for younger adults in a previous study. Results The attendance and success rates for seniors in this study were higher than those previously reported for younger patients. Further consideration of patient factors revealed that reports of increased stress, Reflux Symptom Index scores > 13, and higher Voice Handicap Index functional subscale scores were significant in distinguishing between patients in the successful and unsuccessful treatment outcome groups. Conclusions The relatively high attendance and success rates among this sample of seniors suggest the desire to achieve voice improvement does not diminish with age, and chances for success in voice therapy among nonfrail seniors may be greater than for younger patients.

PENENTUAN DAERAH PRIORITAS PELAYANAN AKTA KELAHIRAN DENGAN METODE K-NN DAN K-MEANS

2020 ◽  
Vol 17 (1) ◽  
pp. 319-328
Author(s):  
Ade Muchlis Maulana Anwar ◽  
Prihastuti Harsani ◽  
Aries Maesya
Keyword(s):  
Nearest Neighbor ◽  
Information Gain ◽  
Birth Certificate ◽  
Population Data ◽  
Community Services ◽  
Birth Certificates ◽  
Similar Data ◽  
K Nearest Neighbor ◽  
Civil Registration ◽  
The Family

Population Data is individual data or aggregate data that is structured as a result of Population Registration and Civil Registration activities. Birth Certificate is a Civil Registration Deed as a result of recording the birth event of a baby whose birth is reported to be registered on the Family Card and given a Population Identification Number (NIK) as a basis for obtaining other community services. From the total number of integrated birth certificate reporting for the 2018 Population Administration Information System (SIAK) totaling 570,637 there were 503,946 reported late and only 66,691 were reported publicly. Clustering is a method used to classify data that is similar to others in one group or similar data to other groups. K-Nearest Neighbor is a method for classifying objects based on learning data that is the closest distance to the test data. k-means is a method used to divide a number of objects into groups based on existing categories by looking at the midpoint. In data mining preprocesses, data is cleaned by filling in the blank data with the most dominating data, and selecting attributes using the information gain method. Based on the k-nearest neighbor method to predict delays in reporting and the k-means method to classify priority areas of service with 10,000 birth certificate data on birth certificates in 2019 that have good enough performance to produce predictions with an accuracy of 74.00% and with K = 2 on k-means produces a index davies bouldin of 1,179.

ANALYTICAL EPIDEMIOLOGY OF GASTRIC CANCER IN THE REPUBLIC OF CRIMEA AND ITS CONFORMITY WITH ALL-RUSSIAN TRENDS

2018 ◽  
Vol 64 (5) ◽  
pp. 592-601
Author(s):  
Viktor Oleksenko ◽  
Kazim Aliev ◽  
I. Akinshevich ◽  
Ye. Chirva
Keyword(s):  
Gastric Cancer ◽  
Epidemiological Data ◽  
Mortality Rates ◽  
Similar Data ◽  
Results Of Treatment ◽  
Mortality Index ◽  
World Standard ◽  
The Russian Federation ◽  
The Republic ◽  
National Trends

Gastric cancer (GC) is one of the most common malignant tumor, both world-wide and in the Russian Federation (RF), possessing one of the highest mortality rates. The aim of current research was to analyze the main epidemiological data, the rates reflecting the diagnostics and results of treatment of GC patients in the Republic of Crimea (RC) and to compare with national trends. Using the extensive, intensive, standardized rates, estimated by world standard method, structural analysis of the epidemiology of GC in RC for the period from 2007 to 2016 was carried out. The obtained results made it possible to compare these data with the main GC rates in RF. Results of the study. The incidence of GC in RC decreased during 10 years, for men - 16,42 (4th place), for women - 6,68 (9th place) per 100 000 of the population. By 2021 a further decline in morbidity in men is expected to be 30,27% and a possible increase in the female incidence rate - by 17,54%. The average age of GC patients in RC was 66,5 years. Index accuracy was 0,75, which testified to satisfactory conditions of specialized treatment for this tumor. Mortality from GC at the 1st year of life in RC was higher than in RF - 56,0%, which was due to low active diagnostics - 3,6% and accordingly a high proportion of GC patients of IV stage - 43,3%. Ratio index in RC for 10 years was higher than in RF and increased from 3,5 to 4,4; prevalence rate of GC in RC was lower - 84,1 per 100 000 of the population in comparison with RF, GC mortality index - 15,3 per 100 000 of the population that was lower than in RF. The proportion of patients who have been observed for 5 years or more in RC was 57,3% that was more than in RF. Conclusions. The rates reflecting early diagnostics of GC in RC are worse than all-Russian ones, which makes it necessary to develop medical examination program for the population of RC for this malignancy. The growth of ratio index, the lower mortality rates and the greater proportion of people who have been observed for 5 years or more indicates the best results of treatment of patients with GC in RC compared with similar data in RF.

scholarly journals COVID Lockdowns, Social Distancing, and Fatal Car Crashes: More Deaths on Hobbesian Highways?

2020 ◽  
Vol 4 (3-4) ◽  
pp. 238-259 ◽  
Author(s):  
Marshall W. Meyer
Keyword(s):  
World War Ii ◽  
Traffic Safety ◽  
Motor Vehicle ◽  
Road Traffic ◽  
Research Question ◽  
Traffic Volume ◽  
Similar Data ◽  
World War ◽  
Social Distancing ◽  
The Usa

Abstract Research Question What happened to US traffic safety during the first US COVID-19 lockdown, and why was the pattern the opposite of that observed in previous sudden declines of traffic volume? Data National and local statistics on US traffic volume, traffic fatalities, injury accidents, speeding violations, running of stop signs, and other indicators of vehicular driving behavior, both in 2020 and in previous US economic recessions affecting the volume of road traffic. Methods Comparative analysis of the similarities and differences between the data for the COVID-19 lockdown in parts of the USA in March 2020 and similar data for the 2008–2009 global economic crisis, as well as other US cases of major reductions in traffic volume. Findings The volume of traffic contracted sharply once a COVID-19 national emergency was declared and most states issued stay-at-home orders, but motor vehicle fatality rates, injury accidents, and speeding violations went up, and remained elevated even as traffic began returning toward normal. This pattern does not fit post-World War II recessions where fatality rates declined with the volume of traffic nor does the 2020 pattern match the pattern during World War II when traffic dropped substantially with little change in motor vehicle fatality rates. Conclusions The findings are consistent with a theory of social distancing on highways undermining compliance with social norms, a social cost of COVID which, if not corrected, poses potential long-term increases in non-compliance and dangerous driving.

Prediction of Joint Rain Attenuation Statistics Induced on Earth–Satellite Multiple Site Diversity Systems Using Gaussian Copula

2017 ◽  
Vol 16 ◽  
pp. 95-98 ◽  
Author(s):  
Arsim Kelmendi ◽  
Charilaos Kourogiorgas ◽  
Andrej Hrovat ◽  
Athanasios D. Panagopoulos ◽  
Gorazd Kandus ◽  
...  
Keyword(s):  
Earth Satellite ◽  
Rain Attenuation ◽  
Gaussian Copula ◽  
Multiple Site ◽  
Diversity Systems ◽  
Site Diversity

scholarly journals Hospital length of stay for COVID-19 patients: Data-driven methods for forward planning

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Bindu Vekaria ◽  
Christopher Overton ◽  
Arkadiusz Wiśniowski ◽  
Shazaad Ahmad ◽  
Andrea Aparicio-Castro ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Hospital Admission ◽  
Failure Time ◽  
National Level ◽  
Hospital Length ◽  
Survival Model ◽  
Data Driven ◽  
Hospital Length Of Stay ◽  
Similar Data ◽  
Model Complex

Abstract Background Predicting hospital length of stay (LoS) for patients with COVID-19 infection is essential to ensure that adequate bed capacity can be provided without unnecessarily restricting care for patients with other conditions. Here, we demonstrate the utility of three complementary methods for predicting LoS using UK national- and hospital-level data. Method On a national scale, relevant patients were identified from the COVID-19 Hospitalisation in England Surveillance System (CHESS) reports. An Accelerated Failure Time (AFT) survival model and a truncation corrected method (TC), both with underlying Weibull distributions, were fitted to the data to estimate LoS from hospital admission date to an outcome (death or discharge) and from hospital admission date to Intensive Care Unit (ICU) admission date. In a second approach we fit a multi-state (MS) survival model to data directly from the Manchester University NHS Foundation Trust (MFT). We develop a planning tool that uses LoS estimates from these models to predict bed occupancy. Results All methods produced similar overall estimates of LoS for overall hospital stay, given a patient is not admitted to ICU (8.4, 9.1 and 8.0 days for AFT, TC and MS, respectively). Estimates differ more significantly between the local and national level when considering ICU. National estimates for ICU LoS from AFT and TC were 12.4 and 13.4 days, whereas in local data the MS method produced estimates of 18.9 days. Conclusions Given the complexity and partiality of different data sources and the rapidly evolving nature of the COVID-19 pandemic, it is most appropriate to use multiple analysis methods on multiple datasets. The AFT method accounts for censored cases, but does not allow for simultaneous consideration of different outcomes. The TC method does not include censored cases, instead correcting for truncation in the data, but does consider these different outcomes. The MS method can model complex pathways to different outcomes whilst accounting for censoring, but cannot handle non-random case missingness. Overall, we conclude that data-driven modelling approaches of LoS using these methods is useful in epidemic planning and management, and should be considered for widespread adoption throughout healthcare systems internationally where similar data resources exist.

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