scholarly journals Prediction of the number of heatstroke patients transported by ambulance in Japan’s 47 prefectures: proposal of heat acclimatization consideration

2021 ◽  
Vol 3 (12) ◽  
pp. 125002
Author(s):  
Kazutaka Oka ◽  
Yasuaki Hijioka
Keyword(s):  
Composite Index ◽  
Secondary Data ◽  
Weather Conditions ◽  
Exponential Model ◽  
Meteorological Variables ◽  
Maximum Temperature ◽  
Heat Acclimatization ◽  
Relative Temperature ◽  
Explanatory Variables ◽  
Single Temperature

Abstract The incidence of heatstroke is affected by various meteorological variables. However, previous studies in Japan have mainly investigated and adopted a single temperature metric or composite index for their analyses. Herein, we conducted a time series study through multivariate analysis of different weather conditions simultaneously, in order to analyze the relative importance of meteorological variables to determine the number of heatstroke patients transported by ambulance in all of Japan’s 47 prefectures. We proposed a method that considers heat acclimatization, which has been found to impact the heatstroke, by manipulating certain meteorological variables. For the heatstroke data, we utilized the secondary data provided by the Fire and Disaster Management Agency, Japan. The time period considered was from May 2015 to September 2019. All calculations were performed using R 3.5.1. For the analysis, the machine learning method of random forest (RF) was applied. The results showed that the relative temperature (RelTemp), which represents heat acclimatization, had the highest ranking among all the meteorological variables studied. Then, we developed the exponential model and the RF model to predict the number of heatstroke patients transported by ambulance by adopting the highly ranked meteorological variables including RelTemp as explanatory variables. To confirm the effectiveness of heat acclimatization, we also developed the exponential model and the RF model both without RelTemp (instead, with maximum temperature). According to the results, the R2 values of the exponential and the RF models, including RelTemp, were 0.76 and 0.74, respectively, and those of the exponential and the RF models, excluding RelTemp, were 0.68 and 0.67, respectively. We confirmed the effectiveness of considering heat acclimatization via RelTemp and found that the exponential model with RelTemp provided the higher accuracy. Better predictions by the exponential model with RelTemp would contribute to better preemptive allocation of ambulances and medical staff in medical facilities.

scholarly journals Potential influence of meteorological variables on forest fire risk in Serbia during the period 2000-2017

2019 ◽  
Vol 11 (1) ◽  
pp. 414-425 ◽  
Author(s):  
I. Tošić ◽  
D. Mladjan ◽  
M. B. Gavrilov ◽  
S. Živanović ◽  
M. G. Radaković ◽  
...  
Keyword(s):  
Wind Speed ◽  
Relative Humidity ◽  
Forest Fires ◽  
Fire Risk ◽  
Weather Conditions ◽  
Meteorological Variables ◽  
Maximum Temperature ◽  
Air Temperatures ◽  
Input Variables ◽  
Forest Fire Risk

Abstract To examine potential relationships between meteorological variables and forest fires in Serbia, daily temperature, precipitation, relative humidity and wind speed data for 15 meteorological stations across Serbia were used to construct fire indices. The daily values of the Ångström and Nesterov indices were calculated for the period 2000–2017. A high number of forest fires occurred in 2007 and 2012 in Serbia, during a period of extremely high air temperatures in 2007, followed by the longest heat wave and the worst drought in 2012. In order to identify the ideal weather conditions for fire break outs, different combinations of input variables, e.g., meteorological variables (mean temperature, precipitation, relative humidity, maximum temperature, minimum temperature and wind speed), fire danger indices or a combination of both, for the Belgrade area during the period 1986–2017, were tested. It was found that using relative humidity or precipitation as a predictor only generates a satisfactory model for forecasting of number of forest fires.

Analisis Kinerja Keuangan Perusahaan dengan Menggunakan Pendekatan Economic Value Added (EVA) dan Market Value Added (MVA) (Studi Kasus pada PT Astra International, Tbk. Periode Tahun 20082012)

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Abdul Hamid
Keyword(s):  
Financial Performance ◽  
Financial Services ◽  
Stock Price ◽  
Economic Value ◽  
Composite Index ◽  
Value Added ◽  
Secondary Data ◽  
Study Approach ◽  
Market Value Added ◽  
The Interest Rate

This study is a qualitative study using a case study approach to the PT. Astra International, Tbk. The object of this research is PT. Astra International, Tbk. PT. Astra International, Tbk is a company engaged in six business sectors, namely: automotive,financial services, heavy equipment, mining and energy, agribusiness, information technology, infrastructure and logistics. Researchers chose PT. Astra International, Tbk as research objects due in the year 2012, PT. Astra International, Tbk managed to rank first in the list of 100 Best Companies to Go Public by the 2011 financial performance of Fortune magazines Indonesia. The data used in this research is secondary data, the financial statements. Astra International, Tbk 20082012. Other secondary data used is the interest rate of Bank Indonesia Certificates (SBI), the Jakarta Composite Index (JCI), and thecompanys stock price began the year 20082012. This study aims to determine the companys financial performance by the use of EVA and MVA approach, therefore the data analysis technique used is the EVA and MVA. Based on the value EVA of the year 2008 2012, PT. Astra International, Tbk has good financial performance that managed to meet the expectations of the company and the investors. Based on the value of MVA during the years 20082012, PT. Astra International, Tbk managed to create wealth and prosperity for companies and investors. It concluded that financial performance. AstraInternational, Tbk for five years was satisfactory.

scholarly journals AnANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions

2021 ◽  
Vol 11 (11) ◽  
pp. 4757
Author(s):  
Aleksandra Bączkiewicz ◽  
Jarosław Wątróbski ◽  
Wojciech Sałabun ◽  
Joanna Kołodziejczyk
Keyword(s):  
Atmospheric Pressure ◽  
Real Life ◽  
Real Data ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Air Masses ◽  
Weather Forecasts ◽  
Life Problems ◽  
The World ◽  
The City

Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.

Weather effects on intrahabitat movements of the western green lizard, Lacerta bilineata (Daudin, 1802), at its northern distribution range border: a radio-tracking study

2000 ◽  
Vol 78 (10) ◽  
pp. 1831-1839 ◽  
Author(s):  
P Sound ◽  
M Veith
Keyword(s):  
Activity Patterns ◽  
Strong Dependence ◽  
Weather Conditions ◽  
Distribution Range ◽  
Maximum Temperature ◽  
Second Phase ◽  
Northern Distribution ◽  
Radio Transmitters ◽  
Movement Parameters ◽  
Bad Weather

Daily activity patterns of male western green lizards, Lacerta bilineata (Daudin, 1802), at the edge of their northern distribution range in western Germany after the breeding season from June to October were recorded using implanted radio transmitters. Different activity indices discriminating between stimulation, duration, and length of movement were correlated with actual weather conditions (d0) and with weather conditions on the 2 previous days (d-1 and d-2). The lizards' dependence on weather showed two different phases throughout the study period. During the first period and in the period preceding a drastic change of weather in midsummer, weather had no significant influence on movement parameters. After that event, temperatures dropped and a strong dependence on weather of all movement parameters except those indicating displacements became apparent. Thresholds for 50% activity during this second phase were a maximum temperature of 17°C and a minimum humidity of 35%. Two days after periods of bad weather, the influence of weather conditions increased again. This can be explained by physiological deficits that require compensation during the period of marginal weather conditions prior to hibernation. Displacement movements were significantly longer than home-range movements and were neither triggered nor modulated by the weather. They must therefore represent activities such as patrolling territory boundaries.

scholarly journals Impact of Liquidity on Rural and Community Banks Profitability in The Eastern Region of Ghana

2021 ◽  
Vol 1 (3) ◽  
pp. 129-148
Author(s):  
Osumanu Alhassan ◽  
Oscar Opoku Agyemang Opoku
Keyword(s):  
Secondary Data ◽  
Easy Access ◽  
Eastern Region ◽  
Community Banks ◽  
Loan Portfolio ◽  
Explanatory Variables ◽  
Financial Climate ◽  
Information And Communication ◽  
The Impact

Despite the major role played by rural and community banks in economic development and in the financial climate, their performance over a decade now have not been up to expectations. They continue to experience huge challenges due to innovations in technology as well as globalization which create opportunities for growth. The study was to examine the impact of liquidity on rural and community banks in the Eastern Region of Ghana selected from eleven (11) banks for the period of ten years from 2007 – 2016. The study used panel data and secondary data to collate the ratios from all the selected rural and community banks. A regression model was developed with Return on Asset as the dependent variable accompanied with other six explanatory variables. It was revealed that quality of loan portfolio ratio; capital ratio and loan to total assets had significant and positive relationship with profitability. It was also revealed that shocks in all the liquidity variables had one or other implications on profitability. Finally, based on finding seven, which states that cost to income has negative and significant effect on profitability, the study recommended that management must adopt information and communication technology to reduce cost and easy access to banks’ product in the form of Automated Teller Machine.  

scholarly journals Impact of meteorological factors on number of new COVID-19 cases in Pune

2021 ◽  
Vol 8 (9) ◽  
pp. 4307
Author(s):  
Saurabh Mahajan ◽  
Ravi Devarakonda ◽  
Gautam Mukherjee ◽  
Nisha Verma ◽  
Kumar Pushkar
Keyword(s):  
Meteorological Data ◽  
Secondary Data ◽  
Significant Negative Correlation ◽  
Meteorological Variables ◽  
Strong Positive Correlation ◽  
Daily Number ◽  
Average Temperature ◽  
Time Period ◽  
Indian Meteorological Department ◽  
The Impact

Background: Coronaviruses are a family of viruses that can result in different types of illnesses, most commonly, as Severe acute respiratory syndrome (SARS). Researches have shown that the atmospheric variables and the density of population have affected the transmission of the disease. Meteorological variables like temperature, humidity among others have found to affect the rise of pandemic in positive or negative ways.  Respiratory virus illnesses have shown seasonal variability since the time they have been discovered and managed. This study investigated the relationship between the meteorological variables of temperature, humidity and precipitation in the spread of COVID-19 disease in the city of Pune.Methods: This record based descriptive study is conducted after secondary data analysis of number of new cases of COVID-19 per day from the period 01 May to 24 December 2020 in Pune. Meteorological data of maximum (Tmax), minimum (Tmin) and daily average temperature (Tavg), humidity and precipitation were daily noted from Indian meteorological department website. Trend was identified plotting the daily number of clinically diagnosed cases over time period. Pearson’s correlation was used to estimate association between meteorological variables and daily detected fresh cases of COVID-19 disease.  Results: Analysis revealed significant negative correlation (r=-0.3563, p<0.005) between daily detected number of cases and maximum daily temperature. A strong positive correlation was seen between humidity and daily number of cases (r=0.5541, p<0.005).Conclusions: The findings of this study will aid in forecasting epidemics and in preparing for the impact of climate change on the COVID epidemiology through the implementation of public health preventive measures.

scholarly journals CAUSE ANALYSIS OF CONTRACT AMENDMENT IN THE X DRY DAM CONSTRUCTION PROJECT IN INDONESIA

Neutron ◽  
2020 ◽  
Vol 20 (01) ◽  
pp. 33-40
Author(s):  
Novika Candra Fertilia ◽  
Hana Sary Ayuningtias
Keyword(s):  
Quantitative Research ◽  
Secondary Data ◽  
Weather Conditions ◽  
Influential Factors ◽  
Land Acquisition ◽  
Dam Construction ◽  
Quantitative Research Methods ◽  
Importance Index ◽  
S Curve ◽  
The Government

The government is building two dams to pursue flood capacity in Jakarta, one of which is the X Dry Dam project. There were obstacles during the construction of this project, which resulted in several changes in the form of contract amendments. The purpose of this study is to determine the most influential factors that cause contract amendments and give suggestions for that factors, so the next contract amendment can be minimized and the project can run according to the costs and time that has been set. In this study, the authors use quantitative research methods by distributing questionnaires to respondents who are staff at the contractor. Secondary data used is the S curve. This research uses 4 stages of the questionnaire by using the reliability test using SPSS version 25 software and data analysis of importance index (II). From the results of this study are the X Dry Dam Project has 5 factors that most influence the occurrence of contract amendments that are land acquisition (53.33%), severe weather conditions (52.19%), society refusal of the project (48.84%), lacking design process planning (42.12%), and schedule /estimated time by the owner is too fast (40.28%).

scholarly journals How Does the Budget Deficit Affect Inflation Rate – Evidence from Western Balkans Countries

2020 ◽  
Vol 9 (1) ◽  
pp. 01-10
Author(s):  
Esat Ali Durguti
Keyword(s):  
Time Series ◽  
Budget Deficit ◽  
Inflation Rate ◽  
Multivariate Time Series ◽  
Secondary Data ◽  
Western Balkans ◽  
Vector Error Correction ◽  
Explanatory Variables ◽  
Vector Error ◽  
Point Increase

The main purpose of this study is to investigate if determinants that we selected in our analysis have any effects on inflation rate in Western Balkans Countries[1] by using panel data for the period of 2001-2017, in yearly basis in total of 102 observation. The study used quantitative analysis approach and secondary data by applying the multivariate time series, respectively vector error correction model [VECM]. Multivariate time series was applied to investigate whether the budget deficit and other explanatory variable have any significant impact on inflation rate. The results from our analysis shows that three of four determinates that we used are significant on inflation rate. The model summaries statistics for inflation rate which shows that inflation rate has a moderate correlation with explanatory variables that we used in our model, that explanatory variables explain 45.5 percent of dependent variable and we can conclude that a model is a proper and fit. The results suggest that one percent point increase in budget deficit to GDP ratio is associated with about a 9.34 percent point increase in inflation rate.  The overall inference is that the ratios that we selected has a significant influence on the inflation rate in Western Balkans Countries.      [1] Western Balkans Countries: Albania, Bosnia & Hercegovina, Kosovo, Montenegro, North Macedonia and Serbia.

scholarly journals ROUTINE, EXTREME AND ENGINEERING METEOROLOGY ANALYSIS FOR KARACHI COASTAL AREA

2020 ◽  
Vol 4 (1) ◽  
pp. 15-22
Author(s):  
Muhammad Taqui ◽  
Jabir Hussain Syed ◽  
Ghulam Hassan Askari
Keyword(s):  
Climate Change ◽  
Coastal Area ◽  
Meteorological Parameters ◽  
Meteorological Data ◽  
Weather Conditions ◽  
Meteorological Station ◽  
Annual Precipitation ◽  
Maximum Temperature ◽  
Intergovernmental Panel ◽  
Interdisciplinary Field

Pakistan’s largest city, Karachi, which is industrial centre and economic hub needs focus in research and development of every field of Engineering, Science and Technology. Urbanization and industrialization is resulting bad weather conditions which prolongs until a climate change. Since, Meteorology serves as interdisciplinary field of study, an analytical study of real and region-specific meteorological data is conducted which focuses on routine, extreme and engineering meteorology of metropolitan city Karachi. Results of study endorse the meteorological parameters relationship and establish the variability of those parameters for Karachi Coastal Area. The rise of temperature, decreasing trend of atmospheric pressure, increment in precipitation and fall in relative humidity depict the effects of urbanization and industrialization. The recorded extreme maximum temperature of 45.50C (on June 11, 1988) and the extreme minimum temperature of 4.5 0C(on January 1, 2007) is observed at Karachi south meteorological station. The estimated temperature rise in 32 years is 0.9 0C, which is crossing the Intergovernmental Panel on Climate Change (IPCC) predicted/estimated limit of 2oC rise per century. The maximum annual precipitation of 487.0mm appearing in 1994 and the minimum annual precipitation of 2.5mm appearing in 1987 is observed at same station which is representative meteorological station for Karachi Coast. Further Engineering meteorological parameters for heating ventilation air condition (HVAC) system design for industrial purpose are deduced as supporting data for coastal area site study for industrial as well as any follow-up engineering work in the specified region.

scholarly journals Effects of Corporate Entrepreneurship Dimensions on Organizational Performance: Case of Small and Medium Enterprises in Holeta Town, Ethiopia

2021 ◽  
Vol 7 (4) ◽  
pp. 234
Author(s):  
Gemechu Abdissa ◽  
Abebe Ayalew ◽  
Csaba Bálint Illés ◽  
Anna Dunay
Keyword(s):  
Organizational Performance ◽  
Business Performance ◽  
Small And Medium Enterprises ◽  
Secondary Data ◽  
Corporate Entrepreneurship ◽  
Business Environment ◽  
Explanatory Variables ◽  
Market Shares ◽  
Medium Enterprises ◽  
The Town

Small and medium enterprises are paying the lion’s share in the innovation-based economy of today’s competitive business environment. To this effect, this study observed the effects of corporate entrepreneurship (CE) dimensions on the performance of SMEs in the town of Holeta, Ethiopia. We used both descriptive and survey research designs to meet the specified target of the study. The researchers employed both primary and secondary data sources; the former were collected from 173 participants using both primary and secondary data. The result of this study indicates that all of the explanatory variables used were statistically significant and had a positive relationship with the performance of SMEs. Thus, we recommend that owners of small and medium enterprises pay special attention to practicing CE to increase their business performance, sustainability, and competitiveness. Entrepreneurs should also come up with new and attractive product and service features to take high market shares. Furthermore, forecasting potential challenges for firms and devising possible ways of solving the situation in advance can safeguard businesses from failure.

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