Hierarchical ALS algorithm with constraint used in UBSS

2013 ◽  
pp. 435-438
Keyword(s):  
Als Algorithm

The Universal ALS Algorithm

Resuscitation ◽  
1997 ◽  
Vol 34 (2) ◽  
pp. 109-111 ◽  
Author(s):  
W. Kloeck ◽  
R. Cummins ◽  
D. Chamberlain ◽  
L. Bossaert ◽  
V. Callanan ◽  
...  
Keyword(s):  
Als Algorithm

scholarly journals CHALLENGES IN IDENTIFYING PERSONS WITH NEURODEGENERATIVE DISEASES USING HEALTH ADMINISTRATIVE DATABASES

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S16-S16
Author(s):  
Laura C Maclagan ◽  
Serena Soleimani ◽  
Agessandro Abrahao ◽  
Lorne Zinman ◽  
Michael A Campitelli ◽  
...  
Keyword(s):  
Health Service ◽  
Neurodegenerative Diseases ◽  
Medical Records ◽  
Health Service Utilization ◽  
Population Level ◽  
Administrative Databases ◽  
Diagnosis Codes ◽  
Service Patterns ◽  
Als Algorithm ◽  
Lateral Sclerosis

Abstract Health administrative databases can be used to quantify prevalence and incidence of neurodegenerative diseases and their impact on health service utilization outcomes at the population level. Algorithms based on diagnosis codes and health service patterns can be used to identify persons suspected to have a neurodegenerative disease. Previous studies have developed and validated algorithms to identify persons with Alzheimer’s and related dementias using primary care medical records as the reference standard, however, little previous work has focused on developing algorithms for rare neurodegenerative diseases including amyotrophic lateral sclerosis (ALS). This session will discuss challenges in developing algorithms to identify persons with neurodegenerative diseases accurately and opportunities to improve existing definitions using novel data sources including electronic medical record databases. Preliminary findings regarding the development of an ALS algorithm will be presented.

scholarly journals A Recommendation Engine for Predicting Movie Ratings Using a Big Data Approach

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1215
Author(s):  
Mazhar Javed Awan ◽  
Rafia Asad Khan ◽  
Haitham Nobanee ◽  
Awais Yasin ◽  
Syed Muhammad Anwar ◽  
...  
Keyword(s):  
Big Data ◽  
Collaborative Filtering ◽  
Recommendation System ◽  
Robust Clustering ◽  
Search Data ◽  
Filtering Technique ◽  
Streaming Services ◽  
Movie Recommendation ◽  
Movie Ratings ◽  
Als Algorithm

In this era of big data, the amount of video content has dramatically increased with an exponential broadening of video streaming services. Hence, it has become very strenuous for end-users to search for their desired videos. Therefore, to attain an accurate and robust clustering of information, a hybrid algorithm was used to introduce a recommender engine with collaborative filtering using Apache Spark and machine learning (ML) libraries. In this study, we implemented a movie recommendation system based on a collaborative filtering approach using the alternating least squared (ALS) model to predict the best-rated movies. Our proposed system uses the last search data of a user regarding movie category and references this to instruct the recommender engine, thereby making a list of predictions for top ratings. The proposed study used a model-based approach of matrix factorization, the ALS algorithm along with a collaborative filtering technique, which solved the cold start, sparse, and scalability problems. In particular, we performed experimental analysis and successfully obtained minimum root mean squared errors (oRMSEs) of 0.8959 to 0.97613, approximately. Moreover, our proposed movie recommendation system showed an accuracy of 97% and predicted the top 1000 ratings for movies.

scholarly journals Channel Estimation for Intelligent Reflecting Surface Assisted mmWave Communications

2021 ◽  
Author(s):  
Dong Chen ◽  
Youhua Fu ◽  
Chen Liu ◽  
Hong Wang
Keyword(s):  
Channel Estimation ◽  
Least Squares ◽  
Millimeter Wave ◽  
Communication Systems ◽  
Regularization Parameter ◽  
Estimation Error ◽  
Error Performance ◽  
Selection Scheme ◽  
Als Algorithm ◽  
Reflecting Surface

Abstract Intelligent reflecting surface (IRS) consists of a large number of low-cost passive reflective elements, which can assist millimeter wave communications to solve the problems of weak penetration and short propagation distance. However, it is challenging to obtain channel state information (CSI) in IRS-aided millimeter wave communication systems. To solve this challenge, this paper proposes a regular alternating least squares (RALS) algorithm based on the canonical/parallel factor (CP) decomposition. Compared with the traditional alternate least squares (ALS) algorithm, the proposed RALS algorithm has better convergence performance, thus solving the problem of divergence or slow convergence of the conventional ALS algorithm. Besides, in order to improve the accuracy of the channel estimation, the convex optimization theory is invoked to devise the regularization parameters, and a regularization parameter selection scheme is developed to ensure that the proposed algorithm obtains the optimal solution. The simulation results verify the theoretical analysis and prove the superiority of the proposed RALS algorithm in terms of estimation error performance.

scholarly journals OCTAVVS: A Graphical Toolbox for High-Throughput Preprocessing and Analysis of Vibrational Spectroscopy Imaging Data

2020 ◽  
Vol 3 (2) ◽  
pp. 34
Author(s):  
Carl Troein ◽  
Syahril Siregar ◽  
Michiel Op De Beeck ◽  
Carsten Peterson ◽  
Anders Tunlid ◽  
...  
Keyword(s):  
Vibrational Spectroscopy ◽  
Hyperspectral Image ◽  
Atmospheric Correction ◽  
Region Of Interest ◽  
Mie Scattering ◽  
Multivariate Curve Resolution ◽  
Imaging Data ◽  
Large Sets ◽  
Heterogeneous Samples ◽  
Als Algorithm

Modern vibrational spectroscopy techniques enable the rapid collection of thousands of spectra in a single hyperspectral image, allowing researchers to study spatially heterogeneous samples at micrometer resolution. A number of algorithms have been developed to correct for effects such as atmospheric absorption, light scattering by cellular structures and varying baseline levels. After preprocessing, spectra are commonly decomposed and clustered to reveal informative patterns and subtle spectral changes. Several of these steps are slow, labor-intensive and require programming skills to make use of published algorithms and code. We here present a free and platform-independent graphical toolbox that allows rapid preprocessing of large sets of spectroscopic images, including atmospheric correction and a new algorithm for resonant Mie scattering with improved speed. The software also includes modules for decomposition into constituent spectra using the popular Multivariate Curve Resolution–Alternating Least Squares (MCR-ALS) algorithm, augmented by region-of-interest selection, as well as clustering and cluster annotation.

Simultaneous determination of aromatic amino acids in different systems using three-way calibration based on the PARAFAC-ALS algorithm coupled with EEM fluorescence: exploration of second-order advantages

2014 ◽  
Vol 6 (16) ◽  
pp. 6358-6368 ◽  
Author(s):  
Chao Kang ◽  
Hai-Long Wu ◽  
Shou-Xia Xiang ◽  
Li-Xia Xie ◽  
Ya-Juan Liu ◽  
...  
Keyword(s):  
Amino Acids ◽  
Simultaneous Determination ◽  
Efficient Method ◽  
Aromatic Amino Acids ◽  
Second Order ◽  
Als Algorithm ◽  
Eem Fluorescence

An efficient method is proposed for determination of aromatic amino acids in different systems simultaneously, even in the presence of three uncalibrated interferents.

scholarly journals Short-term immediate post-shock pacing in adult advanced life support – a feasibility study of modified ALS algorithm

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
W Telec ◽  
T Klosiewicz ◽  
R Zalewski ◽  
J Zukowska ◽  
A Baszko ◽  
...  
Keyword(s):  
Life Support ◽  
Negative Impact ◽  
Advanced Life Support ◽  
Control Group ◽  
Additional Element ◽  
Advanced Airway ◽  
Post Shock ◽  
Transcutaneous Pacing ◽  
Als Algorithm ◽  
High Degree

Abstract Introduction It is well known that the majority of patients remains transiently pulseless after successfull defibrillation shock during routine advanced cardiovascular life support (ACLS). The post-shock asystole is longer than 120 seconds in as many as 25% of patients. Not only asystole, but also profound postshock bradycardia and high degree AV blocks are described as common. The need for post-shock pacing (PSP) in adult ACLS is unknown, but there is extensive use of that feature in implantable cardioverters – defibrillators (ICD). PSP feature is widely used in these devices. The wide utilisation of PSP in ICD patients warrants the research towards any possible benefit of it during ACLS measures. Material and methods We performed high-fidelity simulation study including 60 paramedic at 20 scenarios. The participants were asked to perform routine resuscitation scenarios according to the AHA ACLS algorithm. In the control group paramedics had to resume compressions after each shock. In experimental group simultaneously with the compressions, transcutaneous pacing with 200 mA output and rate of 80 ppm was delivered. Several parameters were monitored: chest compression fraction, compressions depth and rate, percent of recoiled compression, compressions on correct depth, and other. Results There were no statistically significant differences between both groups in respect of compressions depth and rate, time needed to achieve advanced airway, initiate and achieve intravenous line, administer medications (Table 1). The detailed results are presented in Table 1. Discussion According to the best of the authors knowledge, this is the first study describing the feasibility of PSP in resuscitation. The quality of resuscitation depends on adherence to the protocol. Any additional element in the protocol can negatively affect the outcome. In the presented study we present that major ACLS steps are delivered without significant delay when PSP is utilised. Conclusions The implementation of PSP had no negative impact on adherence to ACLS protocol. The authors see the need for further intensive research in this area. Figure 1. Design of the study. Funding Acknowledgement Type of funding source: None

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