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Tytuł:
Applying Hunger Game Search (HGS) for selecting significant blood indicators for early prediction of ICU COVID-19 severity
Autorzy:
Sayed, Safynaz AbdEl-Fattah
ElKorany, Abeer
Sayed, Sabah
Powiązania:
https://bibliotekanauki.pl/articles/27312915.pdf
Data publikacji:
2023
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
ICU severity prediction
COVID-19
clinical blood tests
Hunger Game search
HGS
optimization algorithm
support vector machine
SVM
feature selection
Opis:
This paper introduces an early prognostic model for attempting to predict the severity of patients for ICU admission and detect the most significant features that affect the prediction process using clinical blood data. The proposed model predicts ICU admission for high-severity patients during the first two hours of hospital admission, which would help assist clinicians in decision-making and enable the efficient use of hospital resources. The Hunger Game search (HGS) meta-heuristic algorithm and a support vector machine (SVM) have been integrated to build the proposed prediction model. Furthermore, these have been used for selecting the most informative features from blood test data. Experiments have shown that using HGS for selecting features with the SVM classifier achieved excellent results as compared with four other meta-heuristic algorithms. The model that used the features that were selected by the HGS algorithm accomplished the topmost results (98.6 and 96.5%) for the best and mean accuracy, respectively, as compared to using all of the features that were selected by other popular optimization algorithms.
Źródło:
Computer Science; 2023, 24 (1); 113--136
1508-2806
2300-7036
Pojawia się w:
Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Claim modeling and insurance premium pricing under a bonus-malus system in motor insurance
Autorzy:
Ieosanurak, Weenakorn
Khomkham, Banphatree
Moumeesri, Adisak
Powiązania:
https://bibliotekanauki.pl/articles/24987758.pdf
Data publikacji:
2023
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
bonus malus system
claim severity
exponential-GaL distribution
motor insurance
number of claims
Poisson-GaL distribution
system bonus malus
rozkład wykładniczy
ubezpieczenie komunikacyne
Opis:
Accurately modeling claims data and determining appropriate insurance premiums are vital responsibilities for non-life insurance firms. This article presents novel models for claims that offer improved precision in fitting claim data, both in terms of claim frequency and severity. Specifically, we suggest the Poisson-GaL distribution for claim frequency and the exponential-GaL distribution for claim severity. The traditional method of assigning automobile premiums based on a bonus-malus system relies solely on the number of claims made. However, this may lead to unfair outcomes when an insured individual with a minor severity claim is charged the same premium as someone with a severe claim. The second aim of this article is to propose a new model for calculating bonus-malus premiums. Our proposed model takes into account both the number and size of claims, which follow the Poisson-GaL distribution and the exponential-GaL distribution, respectively. To calculate the premiums, we employ the Bayesian approach. Real-world data are used in practical examples to illustrate how the proposed model can be implemented. The results of our analysis indicate that the proposed premium model effectively resolves the issue of overcharging. Moreover, the proposed model produces premiums that are more tailored to policyholders’ claim histories, benefiting both the policyholders and the insurance companies. This advantage can contribute to the growth of the insurance industry and provide a competitive edge in the insurance market.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2023, 33, 4; 637--650
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comprehensive machine learning and deep learning approaches for Parkinsons disease classification and severity assessment
Kompleksowe metody uczenia maszynowego i uczenia głębokiego do klasyfikacji choroby Parkinsona i oceny jej nasilenia
Autorzy:
Majdoubi, Oumaima
Benba, Achraf
Hammouch, Ahmed
Powiązania:
https://bibliotekanauki.pl/articles/27315457.pdf
Data publikacji:
2023
Wydawca:
Politechnika Lubelska. Wydawnictwo Politechniki Lubelskiej
Tematy:
Parkinson's disease
severity assessment
machine learning
XGBoost
Gated Recurrent Unit (GRU)
comparative analysis
choroba Parkinsona
ocena ciężkości
uczenie maszynowe
analiza porównawcza
Opis:
In this study, we aimed to adopt a comprehensive approach to categorize and assess the severity of Parkinson's disease by leveraging techniques from both machine learning and deep learning. We thoroughly evaluated the effectiveness of various models, including XGBoost, Random Forest, Multi-Layer Perceptron (MLP), and Recurrent Neural Network (RNN), utilizing classification metrics. We generated detailed reports to facilitate a comprehensive comparative analysis of these models. Notably, XGBoost demonstrated the highest precision at 97.4%. Additionally, we took a step further by developing a Gated Recurrent Unit (GRU) model with the purpose of combining predictions from alternative models. We assessed its ability to predict the severity of the ailment. To quantify the precision levels of the models in disease classification, we calculated severity percentages. Furthermore, we created a Receiver Operating Characteristic (ROC) curve for the GRU model, simplifying the evaluation of its capability to distinguish among various severity levels. This comprehensive approach contributes to a more accurate and detailed understanding of Parkinson's disease severity assessment.
W tym badaniu naszym celem było przyjęcie kompleksowego podejścia do kategoryzacji i oceny ciężkości choroby Parkinsona poprzez wykorzystanie technik zarówno uczenia maszynowego, jak i głębokiego uczenia. Dokładnie oceniliśmy skuteczność różnych modeli, w tym XGBoost, Random Forest, Multi-Layer Perceptron (MLP) i Recurrent Neural Network (RNN), wykorzystując wskaźniki klasyfikacji. Wygenerowaliśmy szczegółowe raporty, aby ułatwić kompleksową analizę porównawczą tych modeli. Warto zauważyć, że XGBoost wykazał najwyższą precyzję na poziomie 97,4%. Ponadto poszliśmy o krok dalej, opracowując model Gated Recurrent Unit (GRU) w celu połączenia przewidywań z alternatywnych modeli. Oceniliśmy jego zdolność do przewidywania nasilenia dolegliwości. Aby określić ilościowo poziomy dokładności modeli w klasyfikacji chorób, obliczyliśmy wartości procentowe nasilenia. Ponadto stworzyliśmy krzywą charakterystyki operacyjnej odbiornika (ROC) dla modelu GRU, upraszczając ocenę jego zdolności do rozróżniania różnych poziomów nasilenia. To kompleksowe podejście przyczynia się do dokładniejszego i bardziej szczegółowego zrozumienia oceny ciężkości choroby Parkinsona.
Źródło:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska; 2023, 13, 4; 15--20
2083-0157
2391-6761
Pojawia się w:
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Investigating snowplow-related injury severity along mountainous roadway in Wyoming
Autorzy:
Haq, Muhammad Tahmidul
Reza, Imran
Ksaibati, Khaled
Powiązania:
https://bibliotekanauki.pl/articles/2204253.pdf
Data publikacji:
2023
Wydawca:
Fundacja Centrum Badań Socjologicznych
Tematy:
winter highway maintenance
snowplows
injury severity
mixed logit model
unobserved heterogeneity
Wyoming
environment
Opis:
Snow removal and deicing using snowplow trucks assist transportation agencies to enhance roadway safety and mobility. However, due to slower travel speeds during these operations, motorists often end up in crashes for poor visibility and disturbance of the snow. Despite the risk associated with snowplows, no previous study was found that exclusively investigate the factors associated with injury severity in snowplow-involved crashes. Therefore, this paper presents an extensive exploratory analysis and fills this knowledge gap by identifying the significant contributing factors affecting the occupant injury severity from the aspects of crashes with snowplow involvement. The study utilized eleven years (2010-2020) of historical snowplow-related crash data from Wyoming. Both the binary logit model and mixed binary logit model were developed to investigate the impacts of the various occupant, vehicle, crash, roadway, and environmental characteristics on the corresponding occupant injury severity. As one of the important findings from this research concludes that other vehicle drivers are more responsible than snowplow drivers contributing to more severe injuries in crashes involving snowplows. Recommendations suggested based on the modeling results are expected to help transportation agencies and policymakers take necessary actions in reducing snowplow-involved crashes by targeting appropriate strategies and proper resource allocation.
Źródło:
Journal of Sustainable Development of Transport and Logistics; 2023, 8, 1; 73--88
2520-2979
Pojawia się w:
Journal of Sustainable Development of Transport and Logistics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The relationship of biochemical parameters and radiological parameters in the evaluation of the clinical severity of acute pancreatitis in the emergency department – a retrospective analysis
Autorzy:
Tortum, Fatma
Tekin, Erdal
Aydın, Fahri
Özdal, Emine
Tatlısu, Kübra
Powiązania:
https://bibliotekanauki.pl/articles/25102374.pdf
Data publikacji:
2023-06-30
Wydawca:
Uniwersytet Rzeszowski. Wydawnictwo Uniwersytetu Rzeszowskiego
Tematy:
acute pancreatitis
amylase
computed tomography severity index
emergency department
lipase
Opis:
Introduction and aim. Computed tomography severity index (CTSI) and Balthazar score are among the most frequently used scorings in the determination of severe acute pancreatitis. The primary purpose of this study is evaluation of the effects of biochemical parameters, Balthazar score and CTSI on mortality in acute pancreatitis. At the same time, correlations with biochemical parameters, CTSI and Balthazar score were evaluated in patients with AP. Material and methods. In this study, the amylase, lipase, CRP, and procalcitonin values of patients diagnosed with acute pancreatitis were retrospectively recorded. Contrast-enhanced computed tomography (CECT) images obtained at the time of presentation to the emergency department or within seven days of admission were re-evaluated by two radiologists. The CTSI scores and Balthazar scores of the patients were calculated. Results. The study included 240 patients. The amylase level of the patients was positively correlated with the Balthazar score at a statistically significant level (R=0.189, p=0.003). In addition, the relationship between pancreatic scoring systems and mortality, the AUC value for CTSI was 0.9 (95% CI: 0.826-0.973) and was higher than other scoring systems. Conclusion. CTSI had better performance in the prediction of mortality in patients with acute pancreatitis.
Źródło:
European Journal of Clinical and Experimental Medicine; 2023, 2; 277-282
2544-2406
2544-1361
Pojawia się w:
European Journal of Clinical and Experimental Medicine
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The use of basophil activation tests in clinical-laboratory investigations in patients with beta-lactam allergy (pilot study)
Zastosowanie testów aktywacji bazofilów w badaniach kliniczno-laboratoryjnych u pacjentów z alergią na beta-laktamy (badanie pilotażowe)
Autorzy:
Havrylyuk, Anna
Zubchenko, Svitlana
Lomikovska, Marta
Kril, Iryna
Lishchuk-Yakymovych, Khrystyna
Pukalyak, Roman
Chopyak, Valentyna
Powiązania:
https://bibliotekanauki.pl/articles/2215765.pdf
Data publikacji:
2023-03-01
Wydawca:
Oficyna Wydawnicza Mediton
Tematy:
beta-lactam allergy
clinical manifestations of allergy
CD63
expression
antibiotics cross-reactions
the prognosis of the severity of
allergy to antibiotics.
reakcja alergiczna na antybiotyki beta-laktamowe
kliniczne objawy alergii
ekspresja CD63
biotyki
prognozowanie skomplikowania alergii na antybiotyki
alergia krzyżowa na antybiotyki
Opis:
BACKGROUND: Beta (β)-lactam antibiotics (BLAs) are the first-line therapy for non-nosocomial and nosocomial bacterial infections and are most commonly reported to cause allergic reactions. Approximately 50% of all allergic patients in Europe and the USA suffer from drug allergies and BLA allergies. The AIM of the study was to assess cross-reactivity reactions between 2nd and 3rd generation cephalosporins in patients with a medical history of BLA reactions and the risk of adverse reactions to BLAs based on the results of the basophil activation test. MATERIALS AND METHODS: we examined 48 females and 8 males (in all 56 patients) aged 26 to 61 with primary reactions to BLAs and 24 healthy volunteers (control group). 19 (34%) patients were treated with amoxicillin, 18 (32,1%) patients were receiving amoxicillin+clavulanic acid, 6 (10,7%) patients were treated with cefuroxime, and 13 (23,2%) patients with ceftriaxone. Quantitative determination of the CD63 marker of basophil degranulation upon antigen stimulation in whole blood was performed with the use of Flow CAST (FK-CCR) (Bühlmann Laboratories AG, Switzerland). Based on the obtained ВАТ results, the patients were divided into two subgroups: the first group included 33 patients with positive stimulation index but lower CD63 expression (<10%), and the second group included 15 patients with a significantly higher level of CD63 expression (>10 %). THE RESULT: We showed that patients from the second subgroup had the highest level of CD63 expression and stimulation index when amoxicillin, whereas the level of CD63 expression and stimulation index were lower whith ceftriaxone; at the same time, the level of CD63 expression and stimulation index were the lowest with cefuroxime. The patients who treated with and reacted to amoxicillin, as shown by high BAT, also had high CD63 expresiion after ceftriaxone and cefuroxime stimulation. In the first subgroup, urticarial and bronchospasm disappeared within 3 hours of the onset of symptoms in 51.5% of patients, the symptoms persisted for 2-3 days in 42.4% of patients with urticaria and angioedema, whereas maculopapular exanthema persisted for more than a week in 6.1% of the patients. Patients from the first subgroup (with low CD63 expression) had a weak reaction to the culprit antibiotic. Patients from the second subgroup had the strongest reaction to culprit antibiotics: anaphylaxis – 60.0%; Stevens-Johnson syndrome – 6.7%. We established that in patients with hypersensitivity to antibiotics the higher the baseline test scores after in vitro stimulation, the more severe clinical symptoms. CONCLUSION: for patients with clinical manifestations of BLA in case of conflicting anamnesis data, it is recommended to establish true sensitization to antibiotics and to predict the occurrence of cross-reactions between penicillins and cephalosporins not only of the 2nd but also of the 3rd generation. The results of BAT for antibiotics can be used to formulate future antibacterial treatments recommendation.
WPROWADZENIE: Antybiotyki beta(β)-laktamowe (BLA) są terapią pierwszego rzutu w pozaszpitalnych i szpitalnych zakażeniach bakteryjnych i są najczęściej zgłaszane jako wywołujące reakcje alergiczne. Około 50% wszystkich alergików w Europie i USA cierpi na alergie na leki, w tym na alergie na BLA. Celem badania była ocena reakcji krzyżowych między cefalosporyną II i III generacji u pacjentów z klinicznym wywiadem reakcji na BLA i ryzyka wystąpienia niepożądanych reakcji BLA na podstawie wyników testu aktywacji bazofilów. MATERIAŁ I METODY: przebadaliśmy 48 kobiet i 8 mężczyzn (razem 56) z pierwotnymi reakcjami BLA w wieku od 26 do 61 lat oraz 24 zdrowych ochotników (grupa kontrolna). Pacjentów 19 (34%) bylo leczonych amoksycyliną, 18 (32,1%) – amoksycylina + kwasem klawulanowym, 6 (10,7%) – cefuroksymem i 13 (23,2%) – ceftriaksonem. W celu oceny markera degranulacji bazofili CD 63 po stymulacji antygenem w pełnej krwi wykorzystano oznaczenie Flow CAST (FK-CCR) (Bühlmann Laboratories AG, Szwajcaria). Na podstawie wyników ВАТ pacjentów podzielono na dwie podgrupy: w pierwszej grupie było 33 pacjentów z dodatnim niższym wynikiem indeksu stymulacji (<10%), a w drugiej grupie było 15 pacjentów z istotnie wyższym poziomem CD63 ekspresja CD63 (>10%). WYNIK: Nasze wyniki wykazały, że pacjenci z drugiej podgrupy mieli najwyższe wyniki ekspresji CD63 i wskaźnika stymulacji dla amoksycyliny, następnie dla ceftriaksonu, a ostatni dla cefuroksymu. Byli leczeni amoksycyliną i odpowiadali na nią, jak wykazały wysokie wartości ekspresji CD63 w BAT, ci pacjenci mieli również wysoką ekspresję CD63 po stymulacji ceftriaksonem i cefuroksymem. W pierwszej podgrupie u 51,5% pacjentów pokrzywka i skurcz oskrzeli ustąpiły w ciągu 3 godzin od wystąpienia objawów, u 42,4% pacjentów z pokrzywką i obrzękiem naczynioruchowym objawy utrzymywały się przez 2-3 dni, a u 6,1% osutka plamkowo-grudkowa - przez ponad tydzień. Pacjenci z pierwszej podgrupy (z niską ekspresją CD63) wykazywali klinicznie słabe objawy reakcji. Po leczeniu antybiotykami pacjenci z drugiej podgrupy wykazywali silniejsze objawy: u 60,0% - anafilaksja; 6,7% - zespół Stevensa-Johnsona. Wykazaliśmy, że u pacjentów z reakcja nadwrażliwości na leczenie antybiotykami im wyższe wyjściowe wyniki testu po stymulacji in vitro, tym bardziej nasilone są ich objawy kliniczne. WNIOSEK: u pacjentów z klinicznymi objawami BLA w przypadku sprzecznych danych z wywiadu zaleca się ustalenie rzeczywistego uczulenia na antybiotyki i przewidywanie występowania reakcji krzyżowych między penicylinami i cefalosporynami nie tylko drugiej, ale i trzeciej generacji. Wyniki BAT z antybiotykami mogą być wykorzystane do opracowania zaleceń przyszłych terapii przeciwbakteryjnych.
Źródło:
Alergia Astma Immunologia - przegląd kliniczny; 2023, 28, 1; 8-16
1427-3101
Pojawia się w:
Alergia Astma Immunologia - przegląd kliniczny
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A distributed big data analytics model for traffic accidents classification and recognition based on SparkMlLib cores
Autorzy:
Mallahi, Imad El
Riffi, Jamal
Tairi, Hamid
Ez-Zahout, Abderrahmane
Mahraz, Mohamed Adnane
Powiązania:
https://bibliotekanauki.pl/articles/27314355.pdf
Data publikacji:
2022
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
big data
machine learning
traffic accident
severity prediction
convolutional neural network
Opis:
This paper focuses on the issue of big data analytics for traffic accident prediction based on SparkMllib cores; however, Spark’s Machine Learning Pipelines provide a helpful and suitable API that helps to create and tune classification and prediction models to decision-making concerning traffic accidents. Data scientists have recently focused on classification and prediction techniques for traffic accidents; data analytics techniques for feature extraction have also continued to evolve. Analysis of a huge volume of received data requires considerable processing time. Practically, the implementation of such processes in real-time systems requires a high computation speed. Processing speed plays an important role in traffic accident recognition in real-time systems. It requires the use of modern technologies and fast algorithms that increase the acceleration in extracting the feature parameters from traffic accidents. Problems with overclocking during the digital processing of traffic accidents have yet to be completely resolved. Our proposed model is based on advanced processing by the Spark MlLib core. We call on the real-time data streaming API on spark to continuously gather real-time data from multiple external data sources in the form of data streams. Secondly, the data streams are treated as unbound tables. After this, we call the random forest algorithm continuously to extract the feature parameters from a traffic accident. The use of this proposed method makes it possible to increase the speed factor on processors. Experiment results showed that the proposed method successfully extracts the accident features and achieves a seamless classification performance compared to other conventional traffic accident recognition algorithms. Finally, we share all detected accidents with details onto online applications with other users.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2022, 16, 4; 62--71
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An analysis of influential factors associated with rural crashes in a developing country: a case study of Iran
Autorzy:
Sheykhfard, Abbas
Haghighi, Farshidreza
Abbasalipoor, Reza
Powiązania:
https://bibliotekanauki.pl/articles/2173931.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
rural roads
severity of crashes
crashes
injury-fatal crashes
logit model
crash data collected
drogi wiejskie
ciężkość wypadków
awarie
wypadki śmiertelne
model logiczny
Opis:
Road traffic deaths continue to rise, reaching 1.35 million in recent years. Road traffic injuries are the eighth leading cause of death for people of all ages. Note that there is a wide difference in the crash rate between developed and developing countries and that developed countries report much lower crash rates than developing and underdeveloped countries. World Health Organization reports that over 80% of fatal road crashes occur in developing countries, while developed countries account for about 7% of the total. The rate of road crashes in developing countries is higher than the global average, despite some measures reducing deaths over the last decade. Numerous studies have been carried out on the safety of urban roads. However, comprehensive research evaluating influential factors associated with rural crashes in developing countries is still neglected. Therefore, it is crucial to understand how factors influence the severity of rural road crashes. In the present study, rural roads in Mazandaran province were considered a case study. The Crash data collected from the Iranian Legal Medicine Organization covers 2018 to 2021, including 2047 rural crashes. Dependent variables were classified as damage crashes and injury-fatal crashes. Besides, independent variables such as driver specifications, crash specifications, environment specifications, traffic specifications, and geometrical road specifications were considered parameters. The logit model data indicate that factors associated with driver and crash specifications influence rural crashes. The type of crashes is the most critical factor influencing the severity of crashes, on which the fatal rate depends. The findings suggested that implementing solutions that minimize the effect of the factors associated with injury and death on rural roads can reduce the severity of crashes on rural roads that share the same safety issues as the case study. Further studies can also be conducted on the safety and mechanics of the vehicle by focusing the research on the types of vehicles and the sources of the damage.
Źródło:
Archives of Transport; 2022, 63, 3; 53--65
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An assessment of machine learning and data balancing techniques for evaluating downgrade truck crash severity prediction in Wyoming
Autorzy:
Ampadu, Vincent-Michael Kwesi
Haq, Muhammad Tahmidul
Ksaibati, Khaled
Powiązania:
https://bibliotekanauki.pl/articles/2176018.pdf
Data publikacji:
2022
Wydawca:
Fundacja Centrum Badań Socjologicznych
Tematy:
crash severity
performance
extreme gradient boosting tree
adaptive boosting tree
random forest
gradient boost decision tree
adaptive synthetic algorithm
Opis:
This study involved the investigation of various machine learning methods, including four classification tree-based ML models, namely the Adaptive Boosting tree, Random Forest, Gradient Boost Decision Tree, Extreme Gradient Boosting tree, and three non-tree-based ML models, namely Support Vector Machines, Multi-layer Perceptron and k-Nearest Neighbors for predicting the level of severity of large truck crashes on Wyoming road networks. The accuracy of these seven methods was then compared. The Final ROC AUC score for the optimized random forest model is 95.296 %. The next highest performing model was the k-NN with 92.780 %, M.L.P. with 87.817 %, XGBoost with 86.542 %, Gradboost with 74.824 %, SVM with 72.648 % and AdaBoost with 67.232 %. Based on the analysis, the top 10 predictors of severity were obtained from the feature importance plot. These may be classified into whether safety equipment was used, whether airbags were deployed, the gender of the driver and whether alcohol was involved.
Źródło:
Journal of Sustainable Development of Transport and Logistics; 2022, 7, 2; 6--24
2520-2979
Pojawia się w:
Journal of Sustainable Development of Transport and Logistics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Comprehensive evaluation of trend analysis of extreme drought events in the Ceyhan River Basin, Turkey
Autorzy:
Esit, Musa
Yuce, Mehmet Ishak
Powiązania:
https://bibliotekanauki.pl/articles/2142336.pdf
Data publikacji:
2022
Wydawca:
Instytut Meteorologii i Gospodarki Wodnej - Państwowy Instytut Badawczy
Tematy:
climate change
drought severity
drought duration
trend
Ceyhan Basin
Opis:
The investigation of extreme meteorological drought events is crucial for disaster preparedness and regional water management. In this study, trends in extreme drought events, namely annual maximum drought severity (AMDS) and annual maximum drought duration (AMDD), were examined for the Ceyhan Basin. The analyses of extreme events were conducted using the standard precipitation index (SPI) index for multiple-time scales of 1, 3, 6, 9, and 12 months for 23 meteorological stations located in the Ceyhan Basin, Turkey. The Wallis-Moore and Wald-Wolfowitz methods were employed to determine the homogeneity of the data sets, whereas trend analyses were conducted using Mann-Kendall and Spearman Rho tests. The magnitude of trends was defined by Sen’s slope and linear regression, and change points were detected using the standard normal homogeneity test, Buishand’s range test, and Pettitt’s test. Although increasing trends were detected in most of the stations, only in nine of them, statistically significant results were noted at a significance level of 95%. The results of this paper provide valuable information to water resource management decision-makers in the Ceyhan River Basin for evaluating the effect of droughts and preparing for drought mitigation measures to avoid future drought risks.
Źródło:
Meteorology Hydrology and Water Management. Research and Operational Applications; 2022, 10, 2; 1--22
2299-3835
2353-5652
Pojawia się w:
Meteorology Hydrology and Water Management. Research and Operational Applications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Extracting relevant predictors of the severity of mental illnesses from clinical information using regularisation regression models
Autorzy:
Kaushik, Sakshi
Sabharwal, Alka
Grover, Gurprit
Powiązania:
https://bibliotekanauki.pl/articles/2107145.pdf
Data publikacji:
2022-06-14
Wydawca:
Główny Urząd Statystyczny
Tematy:
adaptive LASSO
group LASSO
mental disorder
multicollinearity
random forest imputation
ridge regression
severity of an illness
Opis:
Mental disorders are common non-communicable diseases whose occurrence rises at epidemic rates globally. The determination of the severity of a mental illness has important clinical implications and it serves as a prognostic factor for effective intervention planning and management. This paper aims to identify the relevant predictors of the severity of mental illnesses (measured by psychiatric rating scales) from a wide range of clinical variables consisting of information on both laboratory test results and psychiatric factors . The laboratory test results collectively indicate the measurements of 23 components derived from vital signs and blood tests results for the evaluation of the complete blood count. The 8 psychiatric factors known to affect the severity of mental illnesses are considered, viz. the family history, course and onset of an illness, etc. Retrospective data of 78 patients diagnosed with mental and behavioural disorders were collected from the Lady Hardinge Medical College & Smt. S.K, Hospital in New Delhi, India. The observations missing in the data are imputed using the non-parametric random forest algorithm. The multicollinearity is detected based on the variance inflation factor. Owing to the presence of multicollinearity, regularisation techniques such as ridge regression and extensions of the least absolute shrinkage and selection operator (LASSO), viz. adaptive and group LASSO are used for fitting the regression model. Optimal tuning parameter λ is obtained through 13-fold cross-validation. It was observed that the coefficients of the quantitative predictors extracted by the adaptive LASSO and the group of predictors extracted by the group LASSO were comparable to the coefficients obtained through ridge regression.
Źródło:
Statistics in Transition new series; 2022, 23, 2; 129-152
1234-7655
Pojawia się w:
Statistics in Transition new series
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Right to Interpretation in Relation to Unauthorised Border Crossing and Its Criminalisation
Autorzy:
Nikolajová Kupferschmidtová, Elena
Powiązania:
https://bibliotekanauki.pl/articles/2147707.pdf
Data publikacji:
2022-10-11
Wydawca:
Wyższa Szkoła Policji w Szczytnie
Tematy:
illegal migration
third-country nationals
EU
crime
severity of punishment
illegal border crossing
police
Opis:
The presented study offers an insight into the issue of penalties imposed within selected EU Member States for the unauthorised crossing of the borders of the respective Member States and the right of third-country nationals to communicate in their own language. The right to communicate in one‘s language as a procedural guarantee applies to a third-country national only in cases of necessary interpretation before the competent authorities. However, the question remains whether the respective rights can also be applied to the translation of documents in proceedings, in particular in cases where the Member State concerned impose fines for crossing the national border illegally. At the same time, interpretation into the mother tongue remains an unanswered question. National legislation regulating the above-mentioned issue varies greatly across the EU Member States. Thus, the primary objective of the present study is to point out the diversity of severity of penalties imposed in the selected EU countries and to describe the impact it might have on providing language assistance for communication between third-country nationals and competent authorities.
W prezentowanym opracowaniu przybliżono problematykę kar nakładanych w wybranych państwach członkowskich UE za nieuprawnione przekraczanie granic poszczególnych państw członkowskich oraz prawa obywateli państw trzecich do porozumiewania się w ich własnym języku. Prawo do porozumiewania się we własnym języku jako gwarancja proceduralna ma zastosowanie do obywatela państwa trzeciego tylko w przypadkach konieczności tłumaczenia ustnego przed właściwymi organami. Pozostaje jednak pytanie, czy odpowiednie prawa można zastosować również do tłumaczenia dokumentów w postępowaniu, w szczególności w przypadkach, gdy dane państwo członkowskie nakłada grzywny za nielegalne przekroczenie granicy państwowej. Jednocześnie kwestią bez odpowiedzi pozostaje tłumaczenie ustne na język ojczysty. Przepisy krajowe regulujące powyższą kwestię różnią się znacznie w poszczególnych państwach członkowskich UE. Dlatego głównym celem niniejszego opracowania jest zwrócenie uwagi na zróżnicowanie surowości kar nakładanych w wybranych krajach UE oraz przedstawienie wpływu, jaki może to mieć na zapewnienie pomocy językowej w komunikacji między obywatelami państw trzecich a właściwymi organami.
In dem vorliegenden Beitrag werden die in ausgewählten EU-Mitgliedstaaten verhängten Strafen für das unerlaubte Überschreiten der Grenzen der einzelnen Mitgliedstaaten und das Recht von Drittstaatsangehörigen, in ihrer eigenen Sprache zu kommunizieren, näher untersucht. Das Recht auf Kommunikation in der eigenen Sprache als Verfahrensgarantie gilt für einen Drittstaatsangehörigen nur in den Fällen, in denen ein Dolmetschen vor den zuständigen Behörden erforderlich ist. Es stellt sich jedoch die Frage, ob die einschlägigen Rechte auch auf die Übersetzung von Schriftstücken in Verfahren angewandt werden können, insbesondere in Fällen, in denen der betreffende Mitgliedstaat Geldbußen für das illegale Überschreiten der nationalen Grenze verhängt. Gleichzeitig bleibt die Frage der Verdolmetschung in die Muttersprache unbeantwortet. Die nationalen Vorschriften zu diesem Thema sind in den einzelnen EU-Mitgliedstaaten sehr unterschiedlich. Daher besteht das Hauptziel dieses Beitrags darin, die Unterschiede in der Schwere der in ausgewählten EU-Ländern verhängten Bußgelder aufzuzeigen und zu veranschaulichen, welche Auswirkungen dies auf die Bereitstellung von sprachlicher Unterstützung für die Kommunikation zwischen Drittstaatsangehörigen und den zuständigen Behörden haben kann.
В представленном исследовании подробно рассматривается вопрос о санкциях, применяемых в отдельных государствах-членах ЕС за несанкционированное пересечение границ отдельных государств-членов, и о праве граждан третьих стран на общение на родном языке. Право на общение на родном языке как процессуальная гарантия распространяется на гражданина третьей страны только в тех случаях, когда требуется устный перевод в компетентных органах. Однако остается вопрос, можно ли применять соответствующие права также для перевода документов в ходе судебного разбирательства, в частности, в случаях, когда соответствующее государство-член ЕС налагает штрафы за незаконное пересечение национальной границы. Одновременно перевод на родной язык остается вопросом без ответа. Национальные правила, регулирующие этот вопрос, значительно различаются в разных странах-членах ЕС. Поэтому основная цель данной работы - обратить внимание на различия в размере штрафов, налагаемых в отдельных странах ЕС, и представить, какое влияние это может оказывать на предоставление языковой помощи при общении между гражданами третьих стран и компетентными органами.
Źródło:
Internal Security; 2022, 14(1); 47-62
2080-5268
Pojawia się w:
Internal Security
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Segmentation and estimation of claim severity in motor third-party liability insurance through contrast analysis
Autorzy:
Reiff, Marian
Šoltés, Erik
Komara, Silvia
Šoltésová, Tatiana
Zelinová, Silvia
Powiązania:
https://bibliotekanauki.pl/articles/22443156.pdf
Data publikacji:
2022
Wydawca:
Instytut Badań Gospodarczych
Tematy:
general linear model
claim severity
motor third party liability insurance
least squares means
contrast analysis
Opis:
Research background: Using the marginal means and contrast analysis of the target variable, e.g., claim severity (CS), the actuary can perform an in-depth analysis of the portfolio and fully use the general linear models potential. These analyses are mainly used in natural sciences, medicine, and psychology, but so far, it has not been given adequate attention in the actuarial field. Purpose of the article: The article's primary purpose is to point out the possibilities of contrast analysis for the segmentation of policyholders and estimation of CS in motor third-party liability insurance. The article focuses on using contrast analysis to redefine individual relevant factors to ensure the segmentation of policyholders in terms of actuarial fairness and statistical correctness. The aim of the article is also to reveal the possibilities of using contrast analysis for adequate segmentation in case of interaction of factors and the subsequent estimation of CS. Methods: The article uses the general linear model and associated least squares means. Contrast analysis is being implemented through testing and estimating linear combinations of model parameters. Equations of estimable functions reveal how to interpret the results correctly. Findings & value added: The article shows that contrast analysis is a valuable tool for segmenting policyholders in motor insurance. The segmentation's validity is statistically verifiable and is well applicable to the main effects. Suppose the significance of cross effects is proved during segmentation. In that case, the actuary must take into account the risk that even if the partial segmentation factors are set adequately, statistically proven, this may not apply to the interaction of these factors. The article also provides a procedure for segmentation in case of interaction of factors and the procedure for estimation of the segment's CS. Empirical research has shown that CS is significantly influenced by weight, engine power, age and brand of the car, policyholder's age, and district. The pattern of age's influence on CS differs in different categories of car brands. The significantly highest CS was revealed in the youngest age category and the category of luxury car brands.
Źródło:
Equilibrium. Quarterly Journal of Economics and Economic Policy; 2022, 17, 3; 803-842
1689-765X
2353-3293
Pojawia się w:
Equilibrium. Quarterly Journal of Economics and Economic Policy
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Deep-Learning-Based Bug Priority Prediction Using RNN-LSTM Neural Networks
Autorzy:
Bani-Salameh, Hani
Sallam, Mohammed
Al shboul, Bashar
Powiązania:
https://bibliotekanauki.pl/articles/1818480.pdf
Data publikacji:
2021
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
assigning
priority
bug tracking systems
bug priority
bug severity
closed-source
data mining
machine learning
ML
deep learning
RNN-LSTM
SVM
KNN
Opis:
Context: Predicting the priority of bug reports is an important activity in software maintenance. Bug priority refers to the order in which a bug or defect should be resolved. A huge number of bug reports are submitted every day. Manual filtering of bug reports and assigning priority to each report is a heavy process, which requires time, resources, and expertise. In many cases mistakes happen when priority is assigned manually, which prevents the developers from finishing their tasks, fixing bugs, and improve the quality. Objective: Bugs are widespread and there is a noticeable increase in the number of bug reports that are submitted by the users and teams’ members with the presence of limited resources, which raises the fact that there is a need for a model that focuses on detecting the priority of bug reports, and allows developers to find the highest priority bug reports. This paper presents a model that focuses on predicting and assigning a priority level (high or low) for each bug report. Method: This model considers a set of factors (indicators) such as component name, summary, assignee, and reporter that possibly affect the priority level of a bug report. The factors are extracted as features from a dataset built using bug reports that are taken from closed-source projects stored in the JIRA bug tracking system, which are used then to train and test the framework. Also, this work presents a tool that helps developers to assign a priority level for the bug report automatically and based on the LSTM’s model prediction. Results: Our experiments consisted of applying a 5-layer deep learning RNN-LSTM neural network and comparing the results with Support Vector Machine (SVM) and K-nearest neighbors (KNN) to predict the priority of bug reports. The performance of the proposed RNN-LSTM model has been analyzed over the JIRA dataset with more than 2000 bug reports. The proposed model has been found 90% accurate in comparison with KNN (74%) and SVM (87%). On average, RNN-LSTM improves the F-measure by 3% compared to SVM and 15.2% compared to KNN. Conclusion: It concluded that LSTM predicts and assigns the priority of the bug more accurately and effectively than the other ML algorithms (KNN and SVM). LSTM significantly improves the average F-measure in comparison to the other classifiers. The study showed that LSTM reported the best performance results based on all performance measures (Accuracy = 0.908, AUC = 0.95, F-measure = 0.892).
Źródło:
e-Informatica Software Engineering Journal; 2021, 15, 1; 29--45
1897-7979
Pojawia się w:
e-Informatica Software Engineering Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evaluation of ISS, RTS, CASS and TRISS scoring systems for predicting outcomes of blunt trauma abdomen
Autorzy:
Alam, Arshad
Gupta, Arun
Gupta, Nikhil
Yelamanchi, Raghav
Bansal, Lalit
Durga, C
Powiązania:
https://bibliotekanauki.pl/articles/1391304.pdf
Data publikacji:
2021
Wydawca:
Index Copernicus International
Tematy:
blunt trauma abdomen
Clinical Abdominal Scoring System
Injury Severity Score
Revised Trauma Score
Trauma and Injury Severity Score
Opis:
Introduction: Trauma is the leading cause of mortality in people below the age of 45 years. Abdominal trauma constitutes one-fourth of the trauma burden. Scoring systems in trauma are necessary for grading the severity of the injury and prior mobilization of resources in anticipation. Aim: The aim of this study was to evaluate RTS, ISS, CASS and TRISS scoring systems in blunt trauma abdomen. Materials and methods: A prospective single-center study was conducted on 43 patients of blunt trauma abdomen. Revised trauma score (RTS), Injury Severity Score (ISS), Clinical Abdominal Scoring System (CASS) and Trauma and Injury Severity Score (TRISS) were calculated and compared with the outcomes such as need for surgical intervention, post-operative complications and mortality. Results: The majority of the study subjects were males (83.7%). The most common etiology for blunt trauma abdomen as per this study was road traffic accident (72.1%). Spleen was the most commonly injured organ as per the study. CASS and TRISS were significant in predicting the need for operative intervention. Only ISS significantly predicted post-operative complications. All scores except CASS significantly predicted mortality. Conclusions: Among the scoring systems studied CASS and TRISS predicted the need for operative intervention with good accuracy. For the prediction of post-operative complications, only the ISS score showed statistical significance. ISS, RTS and TRISS predicted mortality with good accuracy but the superiority of one score over the other could not be proved.
Źródło:
Polish Journal of Surgery; 2021, 93, 2; 9-15
0032-373X
2299-2847
Pojawia się w:
Polish Journal of Surgery
Dostawca treści:
Biblioteka Nauki
Artykuł
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