scholarly journals Unavoidable Mathematics

2021 ◽  
Vol 9 (12) ◽  
pp. 1006-1011
Author(s):  
Rohitkumar R Upadhyay
Keyword(s):  
Real World ◽  
Search Engines ◽  
Weather Prediction ◽  
Real Life ◽  
Satellite Navigation ◽  
Popular Belief ◽  
Crime Prediction ◽  
Teachers And Parents ◽  
Advanced Applications

Abstract: Historically, most students really have been struggling with mathematics, which for the most part specifically makes them wonder if they will ever generally apply the knowledge in general sort of real world life, contrary to popular belief. Teachers and parents mostly particularly admit when they kind of really have been kind of kind of asked that students for all intents and purposes actually have very definitely for all intents and purposes few knowledge about the relevance of mathematics in real life, or so they thought. That essentially is why this paper really mostly is based on application of maths in particularly generally real life, or so they definitely thought, or so they really thought. In this paper the most common and pretty essential applications of mathematics in real life literally generally are discussed such as finance and banking, weather prediction, computers and its games, search engines (goggle), music and Transportation and logistics in a subtle way in a very major way. Apart from these some mostly advanced applications are also discussed actually such as satellite navigation, military and Defence and crime prediction in a particularly big way. Keywords: Mathematics, Real life, Finance and Banking, Satellite Navigation, Military and Defence

Advanced Applications on Bilingual Document Analysis and Processing Systems

2022 ◽  
pp. 625-674
Author(s):  
Shalini Puri ◽  
Satya Prakash Singh
Keyword(s):  
Feature Extraction ◽  
Real World ◽  
Classification System ◽  
Real Life ◽  
Document Analysis ◽  
Document Classification ◽  
Classification Systems ◽  
Post Processing ◽  
Dual Class ◽  
Advanced Applications

Today, rapid digitization requires efficient bilingual non-image and image document classification systems. Although many bilingual NLP and image-based systems provide solutions for real-world problems, they primarily focus on text extraction, identification, and recognition tasks with limited document types. This article discusses a journey of these systems and provides an overview of their methods, feature extraction techniques, document sets, classifiers, and accuracy for English-Hindi and other language pairs. The gaps found lead toward the idea of a generic and integrated bilingual English-Hindi document classification system, which classifies heterogeneous documents using a dual class feeder and two character corpora. Its non-image and image modules include pre- and post-processing stages and pre-and post-segmentation stages to classify documents into predefined classes. This article discusses many real-life applications on societal and commercial issues. The analytical results show important findings of existing and proposed systems.

Neuropsychology in the Real World

2014 ◽  
Vol 25 (4) ◽  
pp. 233-238 ◽  
Author(s):  
Martin Peper ◽  
Simone N. Loeffler
Keyword(s):  
Neuropsychological Assessment ◽  
Real World ◽  
Ecological Validity ◽  
Real Life ◽  
Emotional States ◽  
Context Sensitive ◽  
Traditional Assessment ◽  
Life Data ◽  
Real Life Data ◽  
Assessment And Treatment

Current ambulatory technologies are highly relevant for neuropsychological assessment and treatment as they provide a gateway to real life data. Ambulatory assessment of cognitive complaints, skills and emotional states in natural contexts provides information that has a greater ecological validity than traditional assessment approaches. This issue presents an overview of current technological and methodological innovations, opportunities, problems and limitations of these methods designed for the context-sensitive measurement of cognitive, emotional and behavioral function. The usefulness of selected ambulatory approaches is demonstrated and their relevance for an ecologically valid neuropsychology is highlighted.

scholarly journals AB1346-HPR REAL-WORLD EFFECTIVENESS AND PERCEIVED USEFULNESS OF SYMPTOM CHECKERS IN RHEUMATOLOGY: INTERIM REPORT FROM THE PROSPECTIVE MULTICENTER BETTER STUDY

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1961.1-1961
Author(s):  
J. Knitza ◽  
J. Mohn ◽  
C. Bergmann ◽  
E. Kampylafka ◽  
M. Hagen ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Real World ◽  
Search Engines ◽  
Correct Diagnosis ◽  
Perceived Usefulness ◽  
Symptom Duration ◽  
Research Support ◽  
Link Type ◽  
The Mean ◽  
Research Grant

Background:Symptom checkers (SC) promise to reduce diagnostic delay, misdiagnosis and effectively guide patients through healthcare systems. They are increasingly used, however little evidence exists about their real-life effectiveness.Objectives:The aim of this study was to evaluate the diagnostic accuracy, usage time, usability and perceived usefulness of two promising SC, ADA (www.ada.com) and Rheport (www.rheport.de). Furthermore, symptom duration and previous symptom checking was recorded.Methods:Cross-sectional interim clinical data from the first of three recruiting centers from the prospective, real-world, multicenter bETTeR-study (DKRS DRKS00017642) was used. Patients newly presenting to a secondary rheumatology outpatient clinic between September and December 2019 completed the ADA and Rheport SC. The time and answers were recorded and compared to the patient’s actual diagnosis. ADA provides up to 5 disease suggestions, Rheport calculates a risk score for rheumatic musculoskeletal diseases (RMDs) (≥1=RMD). For both SC the sensitivity, specificity was calculated regarding RMDs. Furthermore, patients completed a survey evaluating the SC usability using the system usability scale (SUS), perceived usefulness, previous symptom checking and symptom duration.Results:Of the 129 consecutive patients approached, 97 agreed to participate. 38% (37/97) of the presenting patients presented with an RMD (Figure 1). Mean symptom duration was 146 weeks and a mean number of 10 physician contacts occurred previously, to evaluate current symptoms. 56% (54/96) had previously checked their symptoms on the internet using search engines, spending a mean of 6 hours. Rheport showed a sensitivity of 49% (18/37) and specificity of 58% (35/60) concerning RMDs. ADA’s top 1 and top 5 disease suggestions concerning RMD showed a sensitivity of 43% (16/37) and 54% (20/37) and a specificity of 58% (35/60) and 52% (31/60), respectively. ADA listed the correct diagnosis of the patients with RMDs first or within the first 5 disease suggestions in 19% (7/37) and 30% (11/37), respectively. The average perceived usefulness for checking symptoms using ADA, internet search engines and Rheport was 3.0, 3.5 and 3.1 on a visual analog scale from 1-5 (5=very useful). 61% (59/96) and 64% (61/96) would recommend using ADA and Rheport, respectively. The mean SUS score of ADA and Rheport was 72/100 and 73/100. The mean usage time for ADA and Rheport was 8 and 9 minutes, respectively.Conclusion:This is the first prospective, real-world, multicenter study evaluating the diagnostic accuracy and other features of two currently used SC in rheumatology. These interim results suggest that diagnostic accuracy is limited, however SC are well accepted among patients and in some cases, correct diagnosis can be provided out of the pocket within few minutes, saving valuable time.Figure:Acknowledgments:This study was supported by an unrestricted research grant from Novartis.Disclosure of Interests:Johannes Knitza Grant/research support from: Research Grant: Novartis, Jacob Mohn: None declared, Christina Bergmann: None declared, Eleni Kampylafka Speakers bureau: Novartis, BMS, Janssen, Melanie Hagen: None declared, Daniela Bohr: None declared, Elizabeth Araujo Speakers bureau: Novartis, Lilly, Abbott, Matthias Englbrecht Grant/research support from: Roche Pharma, Chugai Pharma Europe, Consultant of: AbbVie, Roche Pharma, RheumaDatenRhePort GbR, Speakers bureau: AbbVie, Celgene, Chugai Pharma Europe, Lilly, Mundipharma, Novartis, Pfizer, Roche Pharma, UCB, David Simon Grant/research support from: Else Kröner-Memorial Scholarship, Novartis, Consultant of: Novartis, Lilly, Arnd Kleyer Consultant of: Lilly, Gilead, Novartis,Abbvie, Speakers bureau: Novartis, Lilly, Timo Meinderink: None declared, Wolfgang Vorbrüggen: None declared, Cay-Benedict von der Decken: None declared, Stefan Kleinert Shareholder of: Morphosys, Grant/research support from: Novartis, Consultant of: Novartis, Speakers bureau: Abbvie, Novartis, Celgene, Roche, Chugai, Janssen, Andreas Ramming Grant/research support from: Pfizer, Novartis, Consultant of: Boehringer Ingelheim, Novartis, Gilead, Pfizer, Speakers bureau: Boehringer Ingelheim, Roche, Janssen, Jörg Distler Grant/research support from: Boehringer Ingelheim, Consultant of: Boehringer Ingelheim, Paid instructor for: Boehringer Ingelheim, Speakers bureau: Boehringer Ingelheim, Peter Bartz-Bazzanella: None declared, Georg Schett Speakers bureau: AbbVie, BMS, Celgene, Janssen, Eli Lilly, Novartis, Roche and UCB, Axel Hueber Grant/research support from: Novartis, Lilly, Pfizer, Consultant of: Abbvie, BMS, Celgene, Gilead, GSK, Lilly, Novartis, Speakers bureau: GSK, Lilly, Novartis, Martin Welcker Grant/research support from: Abbvie, Novartis, UCB, Hexal, BMS, Lilly, Roche, Celgene, Sanofi, Consultant of: Abbvie, Actelion, Aescu, Amgen, Celgene, Hexal, Janssen, Medac, Novartis, Pfizer, Sanofi, UCB, Speakers bureau: Abbvie, Aescu, Amgen, Biogen, Berlin Chemie, Celgene, GSK, Hexal, Mylan, Novartis, Pfizer, UCB

scholarly journals Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems

2021 ◽  
Author(s):  
Amarildo Likmeta ◽  
Alberto Maria Metelli ◽  
Giorgia Ramponi ◽  
Andrea Tirinzoni ◽  
Matteo Giuliani ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Real World ◽  
Real Life ◽  
User Preferences ◽  
Inverse Reinforcement Learning ◽  
Water Release ◽  
Reward Function ◽  
Model Free ◽  
Conflicting Objectives ◽  
Multiple Experts

AbstractIn real-world applications, inferring the intentions of expert agents (e.g., human operators) can be fundamental to understand how possibly conflicting objectives are managed, helping to interpret the demonstrated behavior. In this paper, we discuss how inverse reinforcement learning (IRL) can be employed to retrieve the reward function implicitly optimized by expert agents acting in real applications. Scaling IRL to real-world cases has proved challenging as typically only a fixed dataset of demonstrations is available and further interactions with the environment are not allowed. For this reason, we resort to a class of truly batch model-free IRL algorithms and we present three application scenarios: (1) the high-level decision-making problem in the highway driving scenario, and (2) inferring the user preferences in a social network (Twitter), and (3) the management of the water release in the Como Lake. For each of these scenarios, we provide formalization, experiments and a discussion to interpret the obtained results.

scholarly journals Improving the performance of a radio-frequency localization system in adverse outdoor applications

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Marcelo N. de Sousa ◽  
Ricardo Sant’Ana ◽  
Rigel P. Fernandes ◽  
Julio Cesar Duarte ◽  
José A. Apolinário ◽  
...  
Keyword(s):  
Random Forest ◽  
Ray Tracing ◽  
Real World ◽  
Practical Implication ◽  
Real Life ◽  
Simulated Data ◽  
Real Data ◽  
Gradient Boosting ◽  
Real World Data ◽  
Localization Accuracy

AbstractIn outdoor RF localization systems, particularly where line of sight can not be guaranteed or where multipath effects are severe, information about the terrain may improve the position estimate’s performance. Given the difficulties in obtaining real data, a ray-tracing fingerprint is a viable option. Nevertheless, although presenting good simulation results, the performance of systems trained with simulated features only suffer degradation when employed to process real-life data. This work intends to improve the localization accuracy when using ray-tracing fingerprints and a few field data obtained from an adverse environment where a large number of measurements is not an option. We employ a machine learning (ML) algorithm to explore the multipath information. We selected algorithms random forest and gradient boosting; both considered efficient tools in the literature. In a strict simulation scenario (simulated data for training, validating, and testing), we obtained the same good results found in the literature (error around 2 m). In a real-world system (simulated data for training, real data for validating and testing), both ML algorithms resulted in a mean positioning error around 100 ,m. We have also obtained experimental results for noisy (artificially added Gaussian noise) and mismatched (with a null subset of) features. From the simulations carried out in this work, our study revealed that enhancing the ML model with a few real-world data improves localization’s overall performance. From the machine ML algorithms employed herein, we also observed that, under noisy conditions, the random forest algorithm achieved a slightly better result than the gradient boosting algorithm. However, they achieved similar results in a mismatch experiment. This work’s practical implication is that multipath information, once rejected in old localization techniques, now represents a significant source of information whenever we have prior knowledge to train the ML algorithm.

scholarly journals An Adaptive Game-Based Learning Strategy for Children Road Safety Education and Practice in Virtual Space

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3661
Author(s):  
Noman Khan ◽  
Khan Muhammad ◽  
Tanveer Hussain ◽  
Mansoor Nasir ◽  
Muhammad Munsif ◽  
...  
Keyword(s):  
Real World ◽  
Road Safety ◽  
Learning Strategy ◽  
Real Life ◽  
Safety Training ◽  
Virtual Space ◽  
Safety Education ◽  
Average Output ◽  
Training Environment ◽  
The Road

Virtual reality (VR) has been widely used as a tool to assist people by letting them learn and simulate situations that are too dangerous and risky to practice in real life, and one of these is road safety training for children. Traditional video- and presentation-based road safety training has average output results as it lacks physical practice and the involvement of children during training, without any practical testing examination to check the learned abilities of a child before their exposure to real-world environments. Therefore, in this paper, we propose a 3D realistic open-ended VR and Kinect sensor-based training setup using the Unity game engine, wherein children are educated and involved in road safety exercises. The proposed system applies the concepts of VR in a game-like setting to let the children learn about traffic rules and practice them in their homes without any risk of being exposed to the outside environment. Thus, with our interactive and immersive training environment, we aim to minimize road accidents involving children and contribute to the generic domain of healthcare. Furthermore, the proposed framework evaluates the overall performance of the students in a virtual environment (VE) to develop their road-awareness skills. To ensure safety, the proposed system has an extra examination layer for children’s abilities evaluation, whereby a child is considered fit for real-world practice in cases where they fulfil certain criteria by achieving set scores. To show the robustness and stability of the proposed system, we conduct four types of subjective activities by involving a group of ten students with average grades in their classes. The experimental results show the positive effect of the proposed system in improving the road crossing behavior of the children.

PALOMAGE, a French real-world cohort of elderly women beyond age 70 with advanced breast cancer receiving palbociclib: Baseline characteristics and safety evaluation.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1012-1012
Author(s):  
Philippe Caillet ◽  
Marina Pulido ◽  
Etienne Brain ◽  
Claire Falandry ◽  
Isabelle Desmoulins ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Advanced Breast Cancer ◽  
Real World ◽  
Older Patients ◽  
Systemic Treatment ◽  
Safety Data ◽  
Real Life ◽  
Advanced Breast ◽  
Baseline Characteristics ◽  
Grade 3

1012 Background: Advanced breast cancer (ABC) is common in older patients, resulting from the high incidence of breast cancer beyond age 70. This population is often limited in clinical trials. Endocrine therapy (ET) combined with a CDK4/6 inhibitor is the standard of care in ABC overexpressing hormonal receptors (HR+). Data specific to older patients are scarce in the literature, deserving further research. Methods: PALOMAGE is an ongoing French prospective study evaluating palbociclib (PAL) + ET in real life setting in women aged ≥70 with HR+ HER2- ABC, split in 2 cohorts: ET sensitive patients with no prior systemic treatment for ABC (cohort A), and ET resistant patients and/or with prior systemic treatment for ABC (cohort B). Data collected include clinical characteristics, quality of life (EORTC QLQ-C30 and ELD14) and geriatric description [G8 and Geriatric-COre DatasEt (G-CODE)]. This analysis reports on baseline characteristics and safety data for the whole population. Results: From 10/2018 to 10/2020, 400 and 407 patients were included in cohort A and B, respectively. The median age was 79 years (69-98), 15.1% with an age > 85. ECOG performance status (PS) was ≥2 in 17.9% patients, 68.3% had a G8 score ≤14 suggesting frailty, 32.1% had bone only metastasis, and 44% had visceral disease. 35.8% of patients in cohort B had no prior treatment for ABC. Safety data were available for 787 patients. The median follow-up was 6.7 months (IC95% = 6.1-7.6). At start of treatment, full dose of PAL (125 mg) was used in 76% of the patients: 62.6%, 68.7% and 71.6% of patients aged ≥ 80, those with ECOG PS ≥2 and those with a G8 score ≤14, respectively. In the safety population, 70% had ≥1 adverse event (AE), including 43.1% grade 3/4 AE, and 22.9% ≥ 1 serious AE. Most frequent AE reported were neutropenia (43.2%), anemia (17.5%), asthenia (16.3%) and thrombocytopenia (13.6%). Grade 3/4 neutropenia was observed in 32.3% of patients, with febrile neutropenia in 1.1%. Grade 3/4 AE PAL-related were reported in 40.1%, 31.4% of patients aged < 80, ≥80, respectively. Regarding PAL, 23.4% of patients had a dose reduction and 41.8% had a temporary or permanent discontinuation due to AE. Safety data were similar in both cohorts. Geriatric data and impact on safety will be presented. Conclusions: PALOMAGE is a unique large real-world cohort focusing on older patients treated with PAL in France. These preliminary data do not suggest any new safety signal, matching data derived from PALOMA trials. The occurrence of less grade3/4 AE related to PAL in patients aged 80 and beyond might reflect the 30% decrease of PAL dose upfront. Effectiveness analyses are eagerly awaited. Clinical trial information: EUPAS23012 .

scholarly journals Experimentally-induced and real-world acute anxiety have no effect on goal-directed behaviour

2019 ◽  
Author(s):  
CM Gillan ◽  
MM Vaghi ◽  
FH Hezemans ◽  
Grothe S van Ghesel ◽  
J Dafflon ◽  
...  
Keyword(s):  
Individual Differences ◽  
Anxiety Disorders ◽  
Healthy Volunteers ◽  
Real World ◽  
Real Life ◽  
Stressful Events ◽  
Panic Attacks ◽  
Healthy Individuals ◽  
Correlational Design ◽  
Acute Anxiety

AbstractCompulsivity is associated with failures in goal-directed control, an important cognitive faculty that protects against developing habits. But might this effect be explained by co-occurring anxiety? Previous studies have found goal-directed deficits in other anxiety disorders, and to some extent when healthy individuals are stressed, suggesting this is plausible. We carried out a causal test of this hypothesis in two experiments (between-subject N=88; within-subject N=50) that used the inhalation of hypercapnic gas (7.5% CO2) to induce an acute state of anxiety in healthy volunteers. In both experiments, we successfully induced anxiety, assessed physiologically and psychologically, but this did not affect goal-directed performance. In a third experiment (N=1413), we used a correlational design to test if real-life anxiety-provoking events (panic attacks, stressful events) impair goal-directed control. While small effects were observed, none survived controlling for individual differences in compulsivity. These data suggest that anxiety has no meaningful impact on goal-directed control.

scholarly journals From Literacy to Information Literacy: Reading for Understanding in the Real World

2021 ◽  
pp. 254-267
Author(s):  
John Royce
Keyword(s):  
Information Literacy ◽  
Real World ◽  
Real Life ◽  
The Internet ◽  
Good Readers ◽  
The Real ◽  
Life Problems ◽  
Complicated Process ◽  
Process Failure ◽  
Vital Component

Good readers evaluate as they go along, open to triggers and alarms which warn that something is not quite right, or that something has not been understood. Evaluation is a vital component of information literacy, a keystone for reading with understanding. It is also a complex, complicated process. Failure to evaluate well may prove expensive. The nature and amount of information on the Internet make evaluation skills ever more necessary. Looking at research studies in reading and in evaluation, real-life problems are suggested for teaching, modelling and discussion, to bring greater awareness to good, and to less good, readers.

scholarly journals Real-Life Continuous Flash Suppression - Rendering The Real World Unconscious Using Augmented Reality Goggles

2018 ◽  
Author(s):  
Uri Korisky ◽  
Rony Hirschhorn ◽  
Liad Mudrik
Keyword(s):  
Augmented Reality ◽  
Real World ◽  
Three Dimensional ◽  
Real Life ◽  
Continuous Flash Suppression ◽  
Future Studies ◽  
The Real ◽  
Dominant Eye ◽  
Novel Variant ◽  
Real Objects

Notice: a peer-reviewed version of this preprint has been published in Behavior Research Methods and is available freely at http://link.springer.com/article/10.3758/s13428-018-1162-0Continuous Flash Suppression (CFS) is a popular method for suppressing visual stimuli from awareness for relatively long periods. Thus far, it has only been used for suppressing two-dimensional images presented on-screen. We present a novel variant of CFS, termed ‘real-life CFS’, with which the actual immediate surroundings of an observer – including three-dimensional, real life objects – can be rendered unconscious. Real-life CFS uses augmented reality goggles to present subjects with CFS masks to their dominant eye, leaving their non-dominant eye exposed to the real world. In three experiments we demonstrate that real objects can indeed be suppressed from awareness using real-life CFS, and that duration suppression is comparable that obtained using the classic, on-screen CFS. We further provide an example for an experimental code, which can be modified for future studies using ‘real-life CFS’. This opens the gate for new questions in the study of consciousness and its functions.

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