Academic literature on the topic 'LS. Search engines'
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Journal articles on the topic "LS. Search engines"
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Diaz, MD, DrPH, James H. "Rodent-borne infectious disease outbreaks after flooding disasters: Epidemiology, management, and prevention." Journal of Emergency Management 13, no. 5 (September 1, 2015): 459. http://dx.doi.org/10.5055/jem.2015.0255.
Full textAbstract:
Objective: To alert clinicians to the climatic conditions that can precipitate outbreaks of the rodent-borne infectious diseases most often associated with flooding disasters, leptospirosis (LS), and the Hantavirus-caused diseases, hemorrhagic fever with renal syndrome (HFRS) and Hantavirus pulmonary syndrome (HPS); to describe the epidemiology and presenting clinical manifestations and outcomes of these rodent-borne infectious diseases; and to recommend both prophylactic therapies and effective control and prevention strategies for rodent-borne infectious diseases.Design: Internet search engines, including Google®, Google Scholar®, Pub Med, Medline, and Ovid, were queried with the key words as search terms to examine the latest scientific articles on rodent-borne infectious disease outbreaks in the United States and worldwide to describe the epidemiology and presenting clinical manifestations and outcomes of LS and Hantavirus outbreaks.Setting: Not applicable.Participants: Not applicable.Interventions: Not applicable.Main outcome measure: Rodent-borne infectious disease outbreaks following heavy rainfall and flooding disasters.Results: Heavy rainfall encourages excessive wild grass seed production that supports increased outdoor rodent population densities; and flooding forces rodents from their burrows near water sources into the built environment and closer to humans. Conclusions: Healthcare providers should maintain high levels of suspicion for LS in patients developing febrile illnesses after contaminated freshwater exposures following heavy rainfall, flooding, and evenfreshwater recreational events; and for Hantavirus-caused infectious diseases in patients with hemorrhagic fevers that progress rapidly to respiratory or renal failure following rodent exposures.
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Tahir, Muhammad, Muhammad Usman, Fazal Muhammad, Shams ur Rehman, Imran Khan, Muhammad Idrees, Muhammad Irfan, and Adam Glowacz. "Evaluation of Quality and Readability of Online Health Information on High Blood Pressure Using DISCERN and Flesch-Kincaid Tools." Applied Sciences 10, no. 9 (May 5, 2020): 3214. http://dx.doi.org/10.3390/app10093214.
Full textAbstract:
High Blood Pressure (BP) is a vital factor in the development of cardiovascular diseases worldwide. For more than a decade now, patients search for quality and easy-to-read Online Health Information (OHI) for symptoms, preventions, therapy and other medical conditions. In this paper, we evaluate the quality and readability of OHI about high BP. In order that the first 20 clicks of three top-rated search engines have been used to collect the pertinent data. Using the exclusion criteria, 25 unique websites are selected for evaluation. The quality of all included links is evaluated through DISCERN checklist, a questionnaire for assessing the quality of written information for a health problem. To enhance the reliability of evaluation, all links are separately assessed by two different groups—a group of Health Professional (HPs) and a group of Lay Subjects (LS). A readability test is performed using Flesch-Kincaid tool. Fleiss’ kappa has been calculated before considering average value of each group. After evaluation, the average DISCERN value of HPs is 49.43 ± 14.0 (fair quality) while for LS, it is 48.7 ± 12.2; the mean Flesch-Reading Ease Score (FRES) is 58.5 ± 11.1, which is fairly difficult to read and the Average Grade Level (AGL) is 8.8 ± 1.9. None of the websites scored more than 73 (90%). In both groups, only 4 (16%) websites achieved DISCERN score over 80%. Mann-Whitney and Cronbach’s alpha have been computed to check the statistical significance of the difference between two groups and internal consistency of DISCERN checklist, respectively. Normality and homoscedasticity tests have been performed to check the distribution of scores of both evaluating groups. In both groups, information category websites achieved high DISCERN score but their readability level is worse. Highest scoring websites have clear aim, succinct source and high quality of information on treatment options. High BP is a pervasive disease, yet most of the websites did not produce precise or high-quality information on treatment options.
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Rexie, J. A. M., Kumudha Raimond, Mythily Murugaaboopathy, D. Brindha, and Henock Mulugeta. "Lightweight Pattern Matching Method for DNA Sequencing in Internet of Medical Things." Computational Intelligence and Neuroscience 2022 (September 8, 2022): 1–16. http://dx.doi.org/10.1155/2022/6980335.
Full textAbstract:
An area of medical science, that is, gaining prominence, is DNA sequencing. Genetic mutations responsible for the disease have been detected using DNA sequencing. The research is focusing on pattern identification methodologies for dealing with DNA-sequencing problems relating to various applications. A few examples of such problems are alignment and assembly of short reads from next generation sequencing (NGS), comparing DNA sequences, and determining the frequency of a pattern in a sequence. The approximate matching of DNA sequences is also well suited for many applications equivalent to the exact matching of the sequence since the DNA sequences are often subject to mutation. Consequently, recognizing pattern similarity becomes necessary. Furthermore, it can also be used in virtually every application that calls for pattern matching, for example, spell-checking, spam filtering, and search engines. According to the traditional approach, finding a similar pattern in the case where the sequence length is ls and the pattern length is lp occurs in O (ls ∗ lp). This heavy processing is caused by comparing every character of the sequence repeatedly with the pattern. The research intended to reduce the time complexity of the pattern matching by introducing an approach named “optimized pattern similarity identification” (OPSI). This methodology constructs a table, entitled “shift beyond for avoiding redundant comparison” (SBARC), to bypass the characters in the texts that are already compared with the pattern. The table pertains to the information about the character distance to be skipped in the matching. OPSI discovers at most spots of similar patterns occur in the sequence (by ignoring è mismatches). The experiment resulted in the time complexity identified as O (ls. è). In comparison to the size of the pattern, the allowed number of mismatches will be much smaller. Aspects such as scalability, generalizability, and performance of the OPSI algorithm are discussed. In comparison with the hamming distance-based approximate pattern matching algorithm, the proposed algorithm is found to be 69% more efficient.
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Schiraldi, Luigi, Gianluca Sapino, Joachim Meuli, Michele Maruccia, Mario Cherubino, Wassim Raffoul, and Pietro G. di Summa. "Facial Fat Grafting (FFG): Worth the Risk? A Systematic Review of Complications and Critical Appraisal." Journal of Clinical Medicine 11, no. 16 (August 11, 2022): 4708. http://dx.doi.org/10.3390/jcm11164708.
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Autologous fat is ideal soft tissue filler. It is easily accessible, biocompatible, cheap, and it provides both volume augmentation and skin quality improvement. Fat grafting has been used since 1893, but it has only gained widespread popularity since the development of modern liposuction by Colemann and Illouz in the 1980s. Every year more than half a million facial fat grafting procedures are carried out worldwide and the trend is rapidly increasing. Overall, general complications associated with facial fat grafting are assumed to be around 2%. Is that true? Material and Methods: Until July 2021, a systematic search of the literature was performed interrogating PubMed search engines. The following algorithm was used for the research: (fat graft OR lipofilling) AND face AND complications. Exclusion criteria applied hierarchically were review articles, not reporting recipient site complications; not in English and paediatric population. Abstracts were manually screened by LS, GS, JM and PDS separately and subsequently matched for accuracy. Pertinent full-text articles were retrieved and analysed and data were extracted from the database. The flow chart of article selection is described following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Results: In total, 462 papers were identified by PubMed search. A total of 359 were excluded: 38 papers were not in English, 41 were review articles, 279 articles did not report recipient site complications and 1 was not on human subjects. Average complication rate ranged from 1.5% to 81.4%. A total of 298 adverse events were identified: 40 (13.4%) intravascular injections, 13 (4.3%) asymmetry, 57 (19.1%) irregularities, 22 (7.4%) graft hypertrophy, 21 (7%) fat necrosis, 73 (24.5%) prolonged oedema, 1 (0.3%) infection, 6 (2%) prolonged erythema, 15 (5%) telangiectasia and 50 (16.8%) cases of acne activation. Conclusions: FFG related side effects could be resumed in three categories: severe, moderate, and minor. Severe (13.4%) side effects such as intravascular injection or migration require neurological or neurosurgical management and often lead to permanent disability or death. Moderate (38.3%) side effects such as fat hypertrophy, necrosis, cyst formation, irregularities and asymmetries require a retouch operation. Minor (48.3%) side effects such as prolonged oedema or erythema require no surgical management. Despite the fact that the overall general complication rate of facial fat grafting is assumed to be around 2%, the real complication rate of facial fat grafting is unknown due to a lack of reporting and the absence of consensus on side effect definition and identification. More RCTs are necessary to further determine the real complication rate of this procedure.
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Hoang, Nhat-Duc, and Anh-Duc Pham. "Estimating Concrete Workability Based on Slump Test with Least Squares Support Vector Regression." Journal of Construction Engineering 2016 (December 6, 2016): 1–8. http://dx.doi.org/10.1155/2016/5089683.
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Concrete workability, quantified by concrete slump, is an important property of a concrete mixture. Concrete slump is generally known to affect the consistency, flowability, pumpability, compactibility, and harshness of a concrete mix. Hence, an accurate prediction of this property is a practical need of construction engineers. This research proposes a machine learning model for predicting concrete slump based on the Least Squares Support Vector Regression (LS-SVR). LS-SVR is employed to model the nonlinear mapping between the mix components and slump values. Since the learning process of the LS-SVR necessitates two hyperparameters, the regularization and the kernel parameters, the grid search method is employed search for the most desirable set of hyperparameters. Furthermore, to construct the hybrid model, this research collected a dataset including actual concrete slump tests from a hydroelectric dam construction project in Vietnam. Experimental results show that the proposed model is capable of predicting concrete slump accurately.
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Fluminhan, Carmem Silvia Lima, Ana Paula Ambrósio Zanelato Marques, and Klaus Schlünzen Junior. "THE POTENTIAL OF LESSON STUDY AND SELF-EFFICACY TO ENHANCE TEACHER PROFESSIONAL DEVELOPMENT: a systematic literature review." TICs & EaD em Foco 8, no. 2 (August 30, 2022): 66–84. http://dx.doi.org/10.18817/ticseademfoco.v8i2.628.
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Empirical evidence suggests that collaborative contexts have an impact on teacher self-efficacy. Lesson Study (LS), known as a professional development model that fosters collaboration and inquiry-based features, could foster a positive effect on self-efficacy. However, our knowledge about how these conceptual frameworks correlate is limited. In order to shed light on the theme, a systematic literature review was conducted to investigate the relationship between LS and self-efficacy to improve teaching and learning. Four international databases were consulted (Web of Science, SCOPUS, ERIC and SciELO), and a total of eight studies met the inclusion criteria. The search was conducted in April, 2022 using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement checklist. The identified studies were qualitatively synthesized. The results provided striking evidence that LS has the potential to foster collaboration, improved teacher content knowledge, enhance outcome expectancies and increase teachers´ self-efficacy, which, in turn, is a predictor of student academic achievement. On the other hand, it was revealed that lack of time and resources may contribute to insufficient outcome. Few studies were retrieved through the search engine. Finally, suggestions were proposed for future research.
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Cheng, Min-Yuan, and Nhat-Duc Hoang. "A Self-Adaptive Fuzzy Inference Model Based on Least Squares SVM for Estimating Compressive Strength of Rubberized Concrete." International Journal of Information Technology & Decision Making 15, no. 03 (May 2016): 603–19. http://dx.doi.org/10.1142/s0219622016500140.
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This paper presents an AI approach named as self-Adaptive fuzzy least squares support vector machines inference model (SFLSIM) for predicting compressive strength of rubberized concrete. The SFLSIM consists of a fuzzification process for converting crisp input data into membership grades and an inference engine which is constructed based on least squares support vector machines (LS-SVM). Moreover, the proposed inference model integrates differential evolution (DE) to adaptively search for the most appropriate profiles of fuzzy membership functions (MFs) as well as the LS-SVM’s tuning parameters. In this study, 70 concrete mix samples are utilized to train and test the SFLSIM. According to experimental results, the SFLSIM can achieve a comparatively low MAPE which is less than 2%.
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Hoang, Nhat-Duc, Anh-Duc Pham, and Minh-Tu Cao. "A Novel Time Series Prediction Approach Based on a Hybridization of Least Squares Support Vector Regression and Swarm Intelligence." Applied Computational Intelligence and Soft Computing 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/754809.
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This research aims at establishing a novel hybrid artificial intelligence (AI) approach, named as firefly-tuned least squares support vector regression for time series prediction(FLSVRTSP). The proposed model utilizes the least squares support vector regression (LS-SVR) as a supervised learning technique to generalize the mapping function between input and output of time series data. In order to optimize the LS-SVR’s tuning parameters, theFLSVRTSPincorporates the firefly algorithm (FA) as the search engine. Consequently, the newly construction model can learn from historical data and carry out prediction autonomously without any prior knowledge in parameter setting. Experimental results and comparison have demonstrated that theFLSVRTSPhas achieved a significant improvement in forecasting accuracy when predicting both artificial and real-world time series data. Hence, the proposed hybrid approach is a promising alternative for assisting decision-makers to better cope with time series prediction.
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Saksuriya, Payakorn, and Chulin Likasiri. "Hybrid Heuristic for Vehicle Routing Problem with Time Windows and Compatibility Constraints in Home Healthcare System." Applied Sciences 12, no. 13 (June 26, 2022): 6486. http://dx.doi.org/10.3390/app12136486.
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This work involves a heuristic for solving vehicle routing problems with time windows (VRPTW) with general compatibility-matching between customer/patient and server/caretaker constraints to capture the nature of systems such as caretakers’ home visiting systems or home healthcare (HHC) systems. Since any variation of VRPTW is more complicated than regular VRP, a specific, custom-made heuristic is needed to solve the problem. The heuristic proposed in this work is an efficient hybrid of a novice Local Search (LS), Ruin and Recreate procedure (R&R) and Particle Swarm Optimization (PSO). The proposed LS acts as the initial solution finder as well as the engine for finding a feasible/local optimum. While PSO helps in moving from current best solution to the next best solution, the R&R part allows the solution to be over-optimized and LS moves the solution back on the feasible side. To test our heuristic, we solved 56 benchmark instances of 25, 50, and 100 customers and found that our heuristics can find 52, 21, and 18 optimal cases, respectively. To further investigate the proficiency of our heuristic, we modified the benchmark instances to include compatibility constraints. The results show that our heuristic can reach the optimal solutions in 5 out of 56 instances.
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FERRO, M. C., and S. LIASOVICH. "THE USE OF CORPUS IN TEACHING RUSSIAN AS FOREIGN LANGUAGE: THE REVIEW OF THE EXPERIENCE OF ITALIAN AND OF BELARUSIAN STUDIES AND NEW "SEAH" RESOURCES." Herald of Polotsk State University. Series A. Humanity sciences 66, no. 1 (February 10, 2023): 177–83. http://dx.doi.org/10.52928/2070-1608-2023-66-1-177-183.
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The article provides a detailed overview of the development of corpus linguistics applied to Russian language and a review of the most significant Italian and Belarusian publications on the use of corpora for the descriptive analysis of the Russian language and the teaching of Russian as LS. In this panorama, the author emphasises the innovative character and potential that the Ru_Seah corpus constitutes both on the Russian corpus linguistics front and for teaching Russian as a foreign language. The paper considers the experience of creating a professionally oriented Russian-language text corpus for students of Architecture and Construction using the Sketch Engine corpus manager as part of the SEAH project. It describes the aims and objectives of the project and the approach to the selection of material for the corpus. The paper explains the balance of the corpus, the inclusion of texts of different genres and styles in the corpus. It also deals with the elements of the search engine in relation to the annotation of the text corpus. The structure of educational modules compiled using the SEAH linguistic corpus is considered.