Background: Diabetes Mellitus (DM) is a growing health issue in Bangladesh, with significant complications affecting the quality of life (QoL). This study aims to assess long-term complications, treatment patterns, an...Background: Diabetes Mellitus (DM) is a growing health issue in Bangladesh, with significant complications affecting the quality of life (QoL). This study aims to assess long-term complications, treatment patterns, and QoL of diabetic patients during COVID-19. Methods: A cross-sectional study was conducted on 385 diabetic patients (aged 18-80) from tertiary hospitals in Dhaka and Mymensingh between May and October 2022. Data were collected via a semi-structured questionnaire on sociodemographics, complications, treatment patterns, and QoL (SF-12 scale). Chi-square tests, ANOVA, and linear regression were used for inferential analysis. Results: The sample predominantly included middle-aged males (41 - 55 years) with type 2 diabetes. Diabetic retinopathy (34.5%), polyneuropathy (32.2%), and hypertension (52.3%) were the most common complications. Oral medications were used by 59.7% of patients, with 29.1% on insulin. Chi-square analysis showed a significant association between treatment adherence and complications (p β = 0.45, p Conclusion: Complications in diabetic patients significantly affect QoL in Bangladesh. Treatment adherence, especially with oral medications, positively impacts QoL. There is a need for improved access to diabetes care to manage complications and enhance the overall well-being of diabetic patients.展开更多
Self-consolidating concrete(SCC)is an important innovation in concrete technology due to its superior properties.However,predicting its compressive strength remains challenging due to variability in its composition an...Self-consolidating concrete(SCC)is an important innovation in concrete technology due to its superior properties.However,predicting its compressive strength remains challenging due to variability in its composition and uncertainties in prediction outcomes.This study combines machine learning(ML)models with conformal prediction(CP)to address these issues,offering prediction intervals that quantify uncertainty and reliability.A dataset of over 3000 samples with 17 input variables was used to train four ensemble methods,including Random Forest(RF),Gradient Boosting Regressor(GBR),Extreme gradient boosting(XGBoost),and light gradient boosting machine(LGBM),along with CP techniques,including cross-validation plus(CV+)and conformalized quantile regression(CQR)methods.Results demonstrate that LGBM and XGBoost outperform RF,improving R^(2) by 4.5%and 5.7%and reducing Root-mean-square Error(RMSE)by 24.6%and 24.8%,respectively.While CV+yielded narrower but constant intervals,CV+_Gamma and CQR provided adaptive intervals,highlighting trade-offs among precision,adaptability,and coverage reliability.The integration of CP offers a robust framework for uncertainty quantification in SCC strength prediction and marks a significant step forward in ML applications for concrete research.展开更多
The Global Health Network Conference 2022 addressed the critical need for expanded health research capabilities in low-and middle-income countries and low-resource settings,particularly in light of global health threa...The Global Health Network Conference 2022 addressed the critical need for expanded health research capabilities in low-and middle-income countries and low-resource settings,particularly in light of global health threats such as pandemics and climate change.This deficit often results in insufficient research to inform effective health interventions.Held in Cape Town,South Africa,the conference brought together a diverse group of health researchers,practitioners,and policymakers from over 50 countries to explore how health research can be embedded into every healthcare setting.The conference emphasized fostering leadership,integrating research findings into policy and practice,enabling research in all healthcare settings,and engaging communities through the research process.This article collates and considers the key findings and recommendations from the eight sessions.These sessions were designed to follow the research cycle,from setting the question to taking the findings into practice,with a focus on capacity building,data-driven decision-making,and tackling gender and societal disparities.Our aim is that by reporting these outputs we can share valuable experience and insights that can help research teams in their studies and through doing so,spark a shift in global health research through this remarkable collaborative effort in knowledge and methods sharing that continues through the Global Health Network community.The recommendations derived from this conference align with the World Health Organization's strategies for reinforcing health research systems and showcase the importance of empowering low-and middle-income countries to conduct research that addresses their unique health challenges.By advancing global health research through collaboration,innovation,and community involvement,the conference laid the groundwork for a comprehensive framework that supports the Sustainable Development Goals and promotes equitable healthcare for all.展开更多
The paper investigates a few of the major areas of the next generation technological advancement,“smart city planning concept”.The areas that the paper focuses are vehicle to grid(V2G),sun to vehicle(S2V),and vehicl...The paper investigates a few of the major areas of the next generation technological advancement,“smart city planning concept”.The areas that the paper focuses are vehicle to grid(V2G),sun to vehicle(S2V),and vehicle to infrastructure(V2I).For the bi-directional crowd energy single entity concept,V2G and building to grid(B2G)are the primary parts of distributed renewable generation(DRG)under smart living.This research includes an in-depth overview of this three major areas.Next,the research conducts a case analysis of V2G,S2V,and V2I along with their possible limitations in order to find out the novel solutions for future development both for academia and industry levels.Lastly,few possible solutions have been proposed to minimize the limitations and to develop the existing system for future expansion.展开更多
This paper provides a technical analysis of energy harvesting (EH) in the field of power and energy sector, including different aspects of harvesting energy, individual case history, control strategies of harvesting i...This paper provides a technical analysis of energy harvesting (EH) in the field of power and energy sector, including different aspects of harvesting energy, individual case history, control strategies of harvesting in the field of power and energy sector together with the current trend and future aspects of it. EH is comparatively a new concept which is growing very fast since the 20th century and catching new generation research approaches. This paper not only describes the past and current scenarios of harvesting energy with radio frequency (RF) and renewables but also gives author’s own anticipation of the upcoming future trends of it by comparing the case histories.展开更多
One of the most difficult jobs in the post-genomic age is identifying a genetic disease from a massive amount of genetic data.Furthermore,the complicated genetic disease has a very diverse genotype,making it challengi...One of the most difficult jobs in the post-genomic age is identifying a genetic disease from a massive amount of genetic data.Furthermore,the complicated genetic disease has a very diverse genotype,making it challenging to find genetic markers.This is a challenging process since it must be completed effectively and efficiently.This research article focuses largely on which patients are more likely to have a genetic disorder based on numerous medical parameters.Using the patient’s medical history,we used a genetic disease prediction algorithm that predicts if the patient is likely to be diagnosed with a genetic disorder.To predict and categorize the patient with a genetic disease,we utilize several deep and machine learning techniques such as Artificial neural network(ANN),K-nearest neighbors(KNN),and Support vector machine(SVM).To enhance the accuracy of predicting the genetic disease in any patient,a highly efficient approach was utilized to control how the model can be used.To predict genetic disease,deep and machine learning approaches are performed.The most productive tool model provides more precise efficiency.The simulation results demonstrate that by using the proposed model with the ANN,we achieve the highest model performance of 85.7%,84.9%,84.3%accuracy of training,testing and validation respectively.This approach will undoubtedly transform genetic disorder prediction and give a real competitive strategy to save patients’lives.展开更多
Real-time disease prediction has emerged as the main focus of study in the field of computerized medicine.Intelligent disease identification framework can assist medical practitioners in diagnosing disease in a way th...Real-time disease prediction has emerged as the main focus of study in the field of computerized medicine.Intelligent disease identification framework can assist medical practitioners in diagnosing disease in a way that is reliable,consistent,and timely,successfully lowering mortality rates,particularly during endemics and pandemics.To prevent this pandemic’s rapid and widespread,it is vital to quickly identify,confine,and treat affected individuals.The need for auxiliary computer-aided diagnostic(CAD)systems has grown.Numerous recent studies have indicated that radiological pictures contained critical information regarding the COVID-19 virus.Utilizing advanced convolutional neural network(CNN)architectures in conjunction with radiological imaging makes it possible to provide rapid,accurate,and extremely useful susceptible classifications.This research work proposes a methodology for real-time detection of COVID-19 infections caused by the Corona Virus.The purpose of this study is to offer a two-way COVID-19(2WCD)diagnosis prediction deep learning system that is built on Transfer Learning Methodologies(TLM)and features customized fine-tuning on top of fully connected layered pre-trained CNN architectures.2WCD has applied modifications to pre-trained models for better performance.It is designed and implemented to improve the generalization ability of the classifier for binary and multi-class models.Along with the ability to differentiate COVID-19 and No-Patient in the binary class model and COVID-19,No-Patient,and Pneumonia in the multi-class model,our framework is augmented with a critical add-on for visually demonstrating infection in any tested radiological image by highlighting the affected region in the patient’s lung in a recognizable color pattern.The proposed system is shown to be extremely robust and reliable for real-time COVID-19 diagnostic prediction.It can also be used to forecast other lung-related disorders.As the system can assist medical practitioners in diagnosing the greatest number of patients in the shortestamount of time, radiologists can also be used or published online to assistany less-experienced individual in obtaining an accurate immediate screeningfor their radiological images.展开更多
In this paper,extensive efforts have been undertaken to design and develop a control system,which is incorporated with an energy storage device that can store energy from low-voltage renewable sources.The developed de...In this paper,extensive efforts have been undertaken to design and develop a control system,which is incorporated with an energy storage device that can store energy from low-voltage renewable sources.The developed device acts as a storage element,which can be used to charge small-scale batteries,cellular devices,and other applications in remote places where the grid connection is not available.The circuit is developed using a case-by-case analysis.In order to solve the low output voltage problem,a bipolar junction transistor-metal oxide semiconductor field-effect transistor(BJT-MOSFET)based switch control technology with the Arduino microcontroller has been implemented.The developed control system is extremely efficient in charging batteries through a supercapacitor for low-voltage sources.In this research,a small-scale 200-W portable vertical axis wind turbine is used at a wind speed of 3 m/s.The result shows the efficiency of the proposed system as compared with the conventional systems.The proposed system can be an important tool of the latest distributed energy generation technology which is an important part of a smart city.Lastly,the limitations and future scopes of the development of the control device are discussed for the future barrier.An important future scope identified is to integrate the Internet of Things based mobile interface for remote monitoring for any kind of pandemic situation like COVID-19.Now,it is high time to get our smart city concept aligned with the post COVID pandemic situation and get us prepared smartly for similar future occurrences.展开更多
This study examines the efficiency of investment trust companies(ITCs)from 2011 to 2020 using a meta-frontier two-stage network data envelopment analysis(DEA)based on the directional distance function(DDF).We improved...This study examines the efficiency of investment trust companies(ITCs)from 2011 to 2020 using a meta-frontier two-stage network data envelopment analysis(DEA)based on the directional distance function(DDF).We improved the accuracy of the efficiency measurement and added a network-based ranking component to rank the topperforming entities.In the group-specific technology assessment,foreign ITCs excel in investment efficiency.Meanwhile,in the meta-technology assessment,domestic ITCs outperform foreign ITCs in terms of both investment and operational efficiencies.Group-specific technology efficiency scores were found to be lower than or equal to the meta-technology efficiency scores for both the operational and investment stages.Based on the network-based ranking approach,Yuan Ta,a domestic ITC that ranked fourth in the operational stage and first in the investment stage,can be used as a reliable benchmark.This study will enable practitioners to gain a better understanding of the performance of ITCs operating under heterogeneous technologies.展开更多
This study utilizes mediation analysis and bootstrapping to analyze the mediating effect of capital structure on the association between managerial ability and firm performance.The dataset consists of 6384 firm-year o...This study utilizes mediation analysis and bootstrapping to analyze the mediating effect of capital structure on the association between managerial ability and firm performance.The dataset consists of 6384 firm-year observations from the Taiwan Residents electronics industry during 2005–2018.Our results indicate that(1)low(high)levels of debt are likely observed in firms with CEOs with high(low)ability,(2)managerial ability positively affects firm performance,and(3)capital structure mediates the positive relationship between managerial ability and firm performance.Overall,the findings may have limited generalizability due to the specific sample characteristics and provide convincing support for the importance of capital structure as a mediator in the managerial ability-firm performance nexus.Specifically,this study highlights the need for examining the effect of managerial ability on firm performance through a mediator.展开更多
The uncertainty in solar energy is different from conventional,dispatchable generation fuels and difficult to incorporate into the standard system operating procedures.In the first part of this work,the machine learni...The uncertainty in solar energy is different from conventional,dispatchable generation fuels and difficult to incorporate into the standard system operating procedures.In the first part of this work,the machine learning algorithm is used to train models based on solar irradiance data and different meteorological weather information to predict the solar irradiance for different cities to validate the forecasting model.Again,the intermittent and inertialess nature of photovoltaic(PV)systems can produce significant power oscillations that can cause significant problems with dynamic stability of the power system and also limit the penetration capacity of PV into the grid.In the second part,it is shown that the residue-based power oscillation damping(POD)controller obviously improves the inter-area oscillation damping.The validity and effectiveness of the proposed controller are demonstrated on the three-machine two-area test system that combines the conventional synchronous generator and flexible alternating current transmission systems(FACTS)device using simulations.This report overall puts an in-depth analysis with regard to the challenges of solar resources with integrating,planning,operating,and particularly the stability of the rest of the power grid,including existing generation resources,customer requirements,and the transmission system itself that will lead to an improved decision making in resource allocations and grid stability.展开更多
This paper investigates the role of Fibonacci retracements levels,a popular technical analysis indicator,in predicting stock prices of leading U.S.energy companies and energy cryptocurrencies.The study methodology foc...This paper investigates the role of Fibonacci retracements levels,a popular technical analysis indicator,in predicting stock prices of leading U.S.energy companies and energy cryptocurrencies.The study methodology focuses on applying Fibonacci retracements as a system compared with the buy-and-hold strategy.Daily crypto and stock prices were obtained from the Standard&Poor’s composite 1500 energy index and CoinMarketCap between November 2017 and January 2020.This study also examined if the combined Fibonacci retracements and the price crossover strategy result in a higher return per unit of risk.Our findings revealed that Fibonacci retracement captures energy stock price changes better than cryptos.Furthermore,most price violations were frequent during price falls compared to price increases,supporting that the Fibonacci instrument does not capture price movements during up and downtrends,respectively.Also,fewer consecutive retracement breaks were observed when the price violations were examined 3 days before the current break.Furthermore,the Fibonacci-based strategy resulted in higher returns relative to the naïve buy-and-hold model.Finally,complementing Fibonacci with the price cross strategy did not improve the results and led to fewer or no trades for some constituents.This study’s overall findings elucidate that,despite significant drops in oil prices,speculators(traders)can implement profitable strategies when using technical analysis indicators,like the Fibonacci retracement tool,with or without price crossover rules.展开更多
This paper presents a robust multi-stage security solution based on fusion,encryption,and watermarking processes to transmit color healthcare images,efficiently.The presented solution depends on the features of discre...This paper presents a robust multi-stage security solution based on fusion,encryption,and watermarking processes to transmit color healthcare images,efficiently.The presented solution depends on the features of discrete cosine transform(DCT),lifting wavelet transform(LWT),and singular value decomposition(SVD).The primary objective of this proposed solution is to ensure robustness for the color medical watermarked images against transmission attacks.During watermark embedding,the host color medical image is transformed into four sub-bands by employing three stages of LWT.The resulting low-frequency sub-band is then transformed by employing three stages of DCT followed by SVD operation.Furthermore,a fusion process is used for combining different watermarks into a single watermark image.This single fused image is then ciphered using Deoxyribose Nucleic Acid(DNA)encryption to strengthen the security.Then,the DNA-ciphered fused watermark is embedded in the host medical image by applying the suggested watermarking technique to obtain the watermarked image.The main contribution of this work is embedding multiple watermarks to prevent identity theft.In the presence of different multimedia attacks,several simulation tests on different colormedical images have been performed.The results prove that the proposed security solution achieves a decent imperceptibility quality with high Peak Signal-to-Noise Ratio(PSNR)values and high correlation between the extracted and original watermark images.Moreover,the watermark image extraction process succeeds in achieving high efficiency in the presence of attacks compared with related works.展开更多
Aim of the Study: To compare effect of asthma care by pharmacist intervention versus routine care on asthma control. Patients and Methods: A 2-month randomised, controlled trial was conducted in outpatient clinics of ...Aim of the Study: To compare effect of asthma care by pharmacist intervention versus routine care on asthma control. Patients and Methods: A 2-month randomised, controlled trial was conducted in outpatient clinics of Ain Shams University Hospitals, Cairo, Egypt. Patients were randomly assigned to receive routine care or a pre-defined pharmacist intervention. This intervention was mainly focused on patient education, improving inhalation technique and medication assessment. Primary outcome was the level of asthma control, as assessed by the Asthma Control Questionnaire (ACQ). Results: By the end of the study, intervention patients who received a written action plan significantly improved their ACQ results than routine care group who did not receive a plan (p < 0.0001). Inhalation technique and adherence to controller medication were significantly better in the intervention group. Conclusion: The present study results provide supportive evidence concerning pharmacists’ favourable effects on asthma patient care and support pharmacists as valuable members of the health care team.展开更多
The nanotechnology revolution affected positively Architecture. Using nanotechnology is considered one of the most successful modern methods to achieve sustainable buildings with high functional efficiency. The discip...The nanotechnology revolution affected positively Architecture. Using nanotechnology is considered one of the most successful modern methods to achieve sustainable buildings with high functional efficiency. The discipline is Nano architecture, which uses Nanomaterials, products, or even Nano-shapes in the treatment of structure and construction.<span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">Despite the economic and urban advantages of using nanotechnology in the field of architecture and urbanism, we note that using nanotechnology is limited to some buildings uses in the city centers until now such as Administrative, commercial, educational, health, and recreational buildings or residential buildings. In spite of that, we found that nanotechnology was not used in priority buildings as “nuclear power plants” as it is considered one of the most eligible buildings to rely on nanotechnology to achieve safety, security, and functional efficiency requirements which have a great impact on advancing the movement of urban development.</span><span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">From this standpoint, the research recommends the necessity of following a methodology to activate the establishment of nuclear power plants with such technology to preserve the safety of construction, reduce energy consumption, conserve economic resources and reduce pollution. The research is exposed to highlight a set of case studies that used such an effective technique and conclude a group of criteria that are recommended to be followed in the implementation and construction of the Dabaa plant in Egypt to achieve a sustainable nuclear power plant. So the research objective aims to adopt the idea of applying nanotechnology in various uses, whether it is in the city center or the outskirt of the city in order to develop these urban cities and transform them into smart sustainable environmental cities depending on nanotechnology aspects to achieve new sustainability scenario that accommodates the objectives of sustainability, with the support of new technologies. From this point of view, the research presents a proposal that includes a set of points that are recommended to be followed based on nanotechnology to achieve sustainability in the implementation of the Dabaa nuclear power plant in Egypt;which will have a great impact in advancing the movement of urban development in Egypt through improving the envelope of an urban typology, using nanotechnology materials on the fa<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">ç</span>ades, roofs, and external renovations </span><span style="white-space:normal;font-family:;" "=""></span><span style="white-space:normal;font-family:;" "="">with suitable constructive systems and in an easier way.</span>展开更多
COVID-19 has significantly impacted the growth prediction of a pandemic,and it is critical in determining how to battle and track the disease progression.In this case,COVID-19 data is a time-series dataset that can be...COVID-19 has significantly impacted the growth prediction of a pandemic,and it is critical in determining how to battle and track the disease progression.In this case,COVID-19 data is a time-series dataset that can be projected using different methodologies.Thus,this work aims to gauge the spread of the outbreak severity over time.Furthermore,data analytics and Machine Learning(ML)techniques are employed to gain a broader understanding of virus infections.We have simulated,adjusted,and fitted several statistical time-series forecasting models,linearML models,and nonlinear ML models.Examples of these models are Logistic Regression,Lasso,Ridge,ElasticNet,Huber Regressor,Lasso Lars,Passive Aggressive Regressor,K-Neighbors Regressor,Decision Tree Regressor,Extra Trees Regressor,Support Vector Regressions(SVR),AdaBoost Regressor,Random Forest Regressor,Bagging Regressor,AuoRegression,MovingAverage,Gradient Boosting Regressor,Autoregressive Moving Average(ARMA),Auto-Regressive Integrated Moving Averages(ARIMA),SimpleExpSmoothing,Exponential Smoothing,Holt-Winters,Simple Moving Average,Weighted Moving Average,Croston,and naive Bayes.Furthermore,our suggested methodology includes the development and evaluation of ensemble models built on top of the best-performing statistical and ML-based prediction methods.A third stage in the proposed system is to examine three different implementations to determine which model delivers the best performance.Then,this best method is used for future forecasts,and consequently,we can collect the most accurate and dependable predictions.展开更多
Countries implement corporate communication initiatives to improve their international relations,achieve different business objectives,and reinforce their brands.Nation branding activities are mainly based on internat...Countries implement corporate communication initiatives to improve their international relations,achieve different business objectives,and reinforce their brands.Nation branding activities are mainly based on international events:sport,culture,social issues.This paper evaluates the Expo 2020 Dubai’s impact on the United Arab Emirates’brand.We conducted a literature review about nation branding,and then we resorted to 15 indicators to analyze how the most important newspapers from some of the most influential countries(United States,Russia,France,and Germany)covered this event from a journalistic and corporate communication perspective.Our results proved that 82 articles were published about this topic,and the most common criteria respected were quoting organizers(n=61),using the Expo’s logo(n=45)and the image of a falcon(n=43).We concluded that most media companies focused on facts related to the Expo and did references to the country’s identity(values,flag,falcon),but most of them did not include links to the Dubai Expo’s and UAE public authorities’websites.展开更多
This study examines how controlling shareholders influence firm performance through the mediating role of firm efficiency in transforming inputs into outputs.To achieve this objective,it conducts a mediation analysis ...This study examines how controlling shareholders influence firm performance through the mediating role of firm efficiency in transforming inputs into outputs.To achieve this objective,it conducts a mediation analysis with 5,000 bootstraps on a dataset of 2,849 firm-year observations of publicly listed firms in Malaysia from 2009 to 2019.The findings reveal a positive relationship between controlling shareholdings and firm performance,with both total and indirect effects having this positive relationship.Moreover,while controlling shareholdings improve firm performance,firm efficiency partially mediates this relationship.Thus,improved firm efficiency plays a critical role in understanding the relationship between governance by controlling shareholders and enhanced firm performance.In summary,this study contributes to the existing literature by expanding our understanding of the complex relationship between controlling shareholdings,firm efficiency,and firm performance.In addition,the findings shed light on the importance of indirect channels in shaping organizational outcomes.As such,this study provides a valuable direction for future research in this area.展开更多
The central concept of strategic benchmarking is resource management efficiency,which ultimately results in profitability.However,little is known about performance measurement from resource-based perspectives.This stu...The central concept of strategic benchmarking is resource management efficiency,which ultimately results in profitability.However,little is known about performance measurement from resource-based perspectives.This study uses the data envelopment analysis(DEA)model with a dynamic network structure to measure the resource management and profitability efficiencies of 287 US commercial banks from 2010 to 2020.Furthermore,we provide frontier projections and incorporate five variables,namely capital adequacy,asset quality,management quality,earning ability,and liquidity(i.e.,the CAMEL ratings).The results revealed that the room for improvement in bank performance is 55.4%.In addition,we found that the CAMEL ratings of efficient banks are generally higher than those of inefficient banks,and management quality,earnings quality,and liquidity ratios positively contribute to bank performance.Moreover,big banks are generally more efficient than small banks.Overall,this study continues the current heated debate on performance measurement in the banking industry,with a particular focus on the DEA application to answer the fundamental question of why resource management efficiency reflects benchmark firms and provides insights into how efficient management of CAMEL ratings would help in improving their performance.展开更多
Quaternion algebra has been used to apply the fractional Fourier transform(FrFT)to color images in a comprehensive approach.However,the discrete fractional random transform(DFRNT)with adequate basic randomness remains...Quaternion algebra has been used to apply the fractional Fourier transform(FrFT)to color images in a comprehensive approach.However,the discrete fractional random transform(DFRNT)with adequate basic randomness remains to be examined.This paper presents a novel multistage privacy system for color medical images based on discrete quaternion fractional Fourier transform(DQFrFT)watermarking and three-dimensional chaotic logistic map(3D-CLM)encryption.First,we describe quaternion DFRNT(QDFRNT),which generalizes DFRNT to handle quaternion signals effectively,and then use QDFRNT to perform color medical image adaptive watermarking.To efficiently evaluate QDFRNT,this study derives the relationship between the QDFRNT of a quaternion signal and the four components of the DFRNT signal.Moreover,it uses the human vision system's(HVS)masking qualities of edge,texture,and color tone immediately from the color host image to adaptively modify the watermark strength for each block in the color medical image using the QDFRNT-based adaptive watermarking and support vector machine(SVM)techniques.The limitations of watermark embedding are also explained to conserve watermarking energy.Second,3D-CLM encryption is employed to improve the system's security and efficiency,allowing it to be used as a multistage privacy system.The proposed security system is effective against many types of channel noise attacks,according to simulation results.展开更多
文摘Background: Diabetes Mellitus (DM) is a growing health issue in Bangladesh, with significant complications affecting the quality of life (QoL). This study aims to assess long-term complications, treatment patterns, and QoL of diabetic patients during COVID-19. Methods: A cross-sectional study was conducted on 385 diabetic patients (aged 18-80) from tertiary hospitals in Dhaka and Mymensingh between May and October 2022. Data were collected via a semi-structured questionnaire on sociodemographics, complications, treatment patterns, and QoL (SF-12 scale). Chi-square tests, ANOVA, and linear regression were used for inferential analysis. Results: The sample predominantly included middle-aged males (41 - 55 years) with type 2 diabetes. Diabetic retinopathy (34.5%), polyneuropathy (32.2%), and hypertension (52.3%) were the most common complications. Oral medications were used by 59.7% of patients, with 29.1% on insulin. Chi-square analysis showed a significant association between treatment adherence and complications (p β = 0.45, p Conclusion: Complications in diabetic patients significantly affect QoL in Bangladesh. Treatment adherence, especially with oral medications, positively impacts QoL. There is a need for improved access to diabetes care to manage complications and enhance the overall well-being of diabetic patients.
基金financially supported by the Natural Sciences and Engineering Research Council of Canada(NSERCGrant No.ALLRP 576708-22)ten industrial partners.
文摘Self-consolidating concrete(SCC)is an important innovation in concrete technology due to its superior properties.However,predicting its compressive strength remains challenging due to variability in its composition and uncertainties in prediction outcomes.This study combines machine learning(ML)models with conformal prediction(CP)to address these issues,offering prediction intervals that quantify uncertainty and reliability.A dataset of over 3000 samples with 17 input variables was used to train four ensemble methods,including Random Forest(RF),Gradient Boosting Regressor(GBR),Extreme gradient boosting(XGBoost),and light gradient boosting machine(LGBM),along with CP techniques,including cross-validation plus(CV+)and conformalized quantile regression(CQR)methods.Results demonstrate that LGBM and XGBoost outperform RF,improving R^(2) by 4.5%and 5.7%and reducing Root-mean-square Error(RMSE)by 24.6%and 24.8%,respectively.While CV+yielded narrower but constant intervals,CV+_Gamma and CQR provided adaptive intervals,highlighting trade-offs among precision,adaptability,and coverage reliability.The integration of CP offers a robust framework for uncertainty quantification in SCC strength prediction and marks a significant step forward in ML applications for concrete research.
文摘The Global Health Network Conference 2022 addressed the critical need for expanded health research capabilities in low-and middle-income countries and low-resource settings,particularly in light of global health threats such as pandemics and climate change.This deficit often results in insufficient research to inform effective health interventions.Held in Cape Town,South Africa,the conference brought together a diverse group of health researchers,practitioners,and policymakers from over 50 countries to explore how health research can be embedded into every healthcare setting.The conference emphasized fostering leadership,integrating research findings into policy and practice,enabling research in all healthcare settings,and engaging communities through the research process.This article collates and considers the key findings and recommendations from the eight sessions.These sessions were designed to follow the research cycle,from setting the question to taking the findings into practice,with a focus on capacity building,data-driven decision-making,and tackling gender and societal disparities.Our aim is that by reporting these outputs we can share valuable experience and insights that can help research teams in their studies and through doing so,spark a shift in global health research through this remarkable collaborative effort in knowledge and methods sharing that continues through the Global Health Network community.The recommendations derived from this conference align with the World Health Organization's strategies for reinforcing health research systems and showcase the importance of empowering low-and middle-income countries to conduct research that addresses their unique health challenges.By advancing global health research through collaboration,innovation,and community involvement,the conference laid the groundwork for a comprehensive framework that supports the Sustainable Development Goals and promotes equitable healthcare for all.
文摘The paper investigates a few of the major areas of the next generation technological advancement,“smart city planning concept”.The areas that the paper focuses are vehicle to grid(V2G),sun to vehicle(S2V),and vehicle to infrastructure(V2I).For the bi-directional crowd energy single entity concept,V2G and building to grid(B2G)are the primary parts of distributed renewable generation(DRG)under smart living.This research includes an in-depth overview of this three major areas.Next,the research conducts a case analysis of V2G,S2V,and V2I along with their possible limitations in order to find out the novel solutions for future development both for academia and industry levels.Lastly,few possible solutions have been proposed to minimize the limitations and to develop the existing system for future expansion.
文摘This paper provides a technical analysis of energy harvesting (EH) in the field of power and energy sector, including different aspects of harvesting energy, individual case history, control strategies of harvesting in the field of power and energy sector together with the current trend and future aspects of it. EH is comparatively a new concept which is growing very fast since the 20th century and catching new generation research approaches. This paper not only describes the past and current scenarios of harvesting energy with radio frequency (RF) and renewables but also gives author’s own anticipation of the upcoming future trends of it by comparing the case histories.
文摘One of the most difficult jobs in the post-genomic age is identifying a genetic disease from a massive amount of genetic data.Furthermore,the complicated genetic disease has a very diverse genotype,making it challenging to find genetic markers.This is a challenging process since it must be completed effectively and efficiently.This research article focuses largely on which patients are more likely to have a genetic disorder based on numerous medical parameters.Using the patient’s medical history,we used a genetic disease prediction algorithm that predicts if the patient is likely to be diagnosed with a genetic disorder.To predict and categorize the patient with a genetic disease,we utilize several deep and machine learning techniques such as Artificial neural network(ANN),K-nearest neighbors(KNN),and Support vector machine(SVM).To enhance the accuracy of predicting the genetic disease in any patient,a highly efficient approach was utilized to control how the model can be used.To predict genetic disease,deep and machine learning approaches are performed.The most productive tool model provides more precise efficiency.The simulation results demonstrate that by using the proposed model with the ANN,we achieve the highest model performance of 85.7%,84.9%,84.3%accuracy of training,testing and validation respectively.This approach will undoubtedly transform genetic disorder prediction and give a real competitive strategy to save patients’lives.
基金This work was funded by the Researchers Supporting Project Number(RSP-2021/300),King Saud University,Riyadh,Saudi Arabia.
文摘Real-time disease prediction has emerged as the main focus of study in the field of computerized medicine.Intelligent disease identification framework can assist medical practitioners in diagnosing disease in a way that is reliable,consistent,and timely,successfully lowering mortality rates,particularly during endemics and pandemics.To prevent this pandemic’s rapid and widespread,it is vital to quickly identify,confine,and treat affected individuals.The need for auxiliary computer-aided diagnostic(CAD)systems has grown.Numerous recent studies have indicated that radiological pictures contained critical information regarding the COVID-19 virus.Utilizing advanced convolutional neural network(CNN)architectures in conjunction with radiological imaging makes it possible to provide rapid,accurate,and extremely useful susceptible classifications.This research work proposes a methodology for real-time detection of COVID-19 infections caused by the Corona Virus.The purpose of this study is to offer a two-way COVID-19(2WCD)diagnosis prediction deep learning system that is built on Transfer Learning Methodologies(TLM)and features customized fine-tuning on top of fully connected layered pre-trained CNN architectures.2WCD has applied modifications to pre-trained models for better performance.It is designed and implemented to improve the generalization ability of the classifier for binary and multi-class models.Along with the ability to differentiate COVID-19 and No-Patient in the binary class model and COVID-19,No-Patient,and Pneumonia in the multi-class model,our framework is augmented with a critical add-on for visually demonstrating infection in any tested radiological image by highlighting the affected region in the patient’s lung in a recognizable color pattern.The proposed system is shown to be extremely robust and reliable for real-time COVID-19 diagnostic prediction.It can also be used to forecast other lung-related disorders.As the system can assist medical practitioners in diagnosing the greatest number of patients in the shortestamount of time, radiologists can also be used or published online to assistany less-experienced individual in obtaining an accurate immediate screeningfor their radiological images.
文摘In this paper,extensive efforts have been undertaken to design and develop a control system,which is incorporated with an energy storage device that can store energy from low-voltage renewable sources.The developed device acts as a storage element,which can be used to charge small-scale batteries,cellular devices,and other applications in remote places where the grid connection is not available.The circuit is developed using a case-by-case analysis.In order to solve the low output voltage problem,a bipolar junction transistor-metal oxide semiconductor field-effect transistor(BJT-MOSFET)based switch control technology with the Arduino microcontroller has been implemented.The developed control system is extremely efficient in charging batteries through a supercapacitor for low-voltage sources.In this research,a small-scale 200-W portable vertical axis wind turbine is used at a wind speed of 3 m/s.The result shows the efficiency of the proposed system as compared with the conventional systems.The proposed system can be an important tool of the latest distributed energy generation technology which is an important part of a smart city.Lastly,the limitations and future scopes of the development of the control device are discussed for the future barrier.An important future scope identified is to integrate the Internet of Things based mobile interface for remote monitoring for any kind of pandemic situation like COVID-19.Now,it is high time to get our smart city concept aligned with the post COVID pandemic situation and get us prepared smartly for similar future occurrences.
文摘This study examines the efficiency of investment trust companies(ITCs)from 2011 to 2020 using a meta-frontier two-stage network data envelopment analysis(DEA)based on the directional distance function(DDF).We improved the accuracy of the efficiency measurement and added a network-based ranking component to rank the topperforming entities.In the group-specific technology assessment,foreign ITCs excel in investment efficiency.Meanwhile,in the meta-technology assessment,domestic ITCs outperform foreign ITCs in terms of both investment and operational efficiencies.Group-specific technology efficiency scores were found to be lower than or equal to the meta-technology efficiency scores for both the operational and investment stages.Based on the network-based ranking approach,Yuan Ta,a domestic ITC that ranked fourth in the operational stage and first in the investment stage,can be used as a reliable benchmark.This study will enable practitioners to gain a better understanding of the performance of ITCs operating under heterogeneous technologies.
基金Funding was provided by Universiti Malaysia Pahang(Grant No.RDU1903110).
文摘This study utilizes mediation analysis and bootstrapping to analyze the mediating effect of capital structure on the association between managerial ability and firm performance.The dataset consists of 6384 firm-year observations from the Taiwan Residents electronics industry during 2005–2018.Our results indicate that(1)low(high)levels of debt are likely observed in firms with CEOs with high(low)ability,(2)managerial ability positively affects firm performance,and(3)capital structure mediates the positive relationship between managerial ability and firm performance.Overall,the findings may have limited generalizability due to the specific sample characteristics and provide convincing support for the importance of capital structure as a mediator in the managerial ability-firm performance nexus.Specifically,this study highlights the need for examining the effect of managerial ability on firm performance through a mediator.
文摘The uncertainty in solar energy is different from conventional,dispatchable generation fuels and difficult to incorporate into the standard system operating procedures.In the first part of this work,the machine learning algorithm is used to train models based on solar irradiance data and different meteorological weather information to predict the solar irradiance for different cities to validate the forecasting model.Again,the intermittent and inertialess nature of photovoltaic(PV)systems can produce significant power oscillations that can cause significant problems with dynamic stability of the power system and also limit the penetration capacity of PV into the grid.In the second part,it is shown that the residue-based power oscillation damping(POD)controller obviously improves the inter-area oscillation damping.The validity and effectiveness of the proposed controller are demonstrated on the three-machine two-area test system that combines the conventional synchronous generator and flexible alternating current transmission systems(FACTS)device using simulations.This report overall puts an in-depth analysis with regard to the challenges of solar resources with integrating,planning,operating,and particularly the stability of the rest of the power grid,including existing generation resources,customer requirements,and the transmission system itself that will lead to an improved decision making in resource allocations and grid stability.
文摘This paper investigates the role of Fibonacci retracements levels,a popular technical analysis indicator,in predicting stock prices of leading U.S.energy companies and energy cryptocurrencies.The study methodology focuses on applying Fibonacci retracements as a system compared with the buy-and-hold strategy.Daily crypto and stock prices were obtained from the Standard&Poor’s composite 1500 energy index and CoinMarketCap between November 2017 and January 2020.This study also examined if the combined Fibonacci retracements and the price crossover strategy result in a higher return per unit of risk.Our findings revealed that Fibonacci retracement captures energy stock price changes better than cryptos.Furthermore,most price violations were frequent during price falls compared to price increases,supporting that the Fibonacci instrument does not capture price movements during up and downtrends,respectively.Also,fewer consecutive retracement breaks were observed when the price violations were examined 3 days before the current break.Furthermore,the Fibonacci-based strategy resulted in higher returns relative to the naïve buy-and-hold model.Finally,complementing Fibonacci with the price cross strategy did not improve the results and led to fewer or no trades for some constituents.This study’s overall findings elucidate that,despite significant drops in oil prices,speculators(traders)can implement profitable strategies when using technical analysis indicators,like the Fibonacci retracement tool,with or without price crossover rules.
文摘This paper presents a robust multi-stage security solution based on fusion,encryption,and watermarking processes to transmit color healthcare images,efficiently.The presented solution depends on the features of discrete cosine transform(DCT),lifting wavelet transform(LWT),and singular value decomposition(SVD).The primary objective of this proposed solution is to ensure robustness for the color medical watermarked images against transmission attacks.During watermark embedding,the host color medical image is transformed into four sub-bands by employing three stages of LWT.The resulting low-frequency sub-band is then transformed by employing three stages of DCT followed by SVD operation.Furthermore,a fusion process is used for combining different watermarks into a single watermark image.This single fused image is then ciphered using Deoxyribose Nucleic Acid(DNA)encryption to strengthen the security.Then,the DNA-ciphered fused watermark is embedded in the host medical image by applying the suggested watermarking technique to obtain the watermarked image.The main contribution of this work is embedding multiple watermarks to prevent identity theft.In the presence of different multimedia attacks,several simulation tests on different colormedical images have been performed.The results prove that the proposed security solution achieves a decent imperceptibility quality with high Peak Signal-to-Noise Ratio(PSNR)values and high correlation between the extracted and original watermark images.Moreover,the watermark image extraction process succeeds in achieving high efficiency in the presence of attacks compared with related works.
文摘Aim of the Study: To compare effect of asthma care by pharmacist intervention versus routine care on asthma control. Patients and Methods: A 2-month randomised, controlled trial was conducted in outpatient clinics of Ain Shams University Hospitals, Cairo, Egypt. Patients were randomly assigned to receive routine care or a pre-defined pharmacist intervention. This intervention was mainly focused on patient education, improving inhalation technique and medication assessment. Primary outcome was the level of asthma control, as assessed by the Asthma Control Questionnaire (ACQ). Results: By the end of the study, intervention patients who received a written action plan significantly improved their ACQ results than routine care group who did not receive a plan (p < 0.0001). Inhalation technique and adherence to controller medication were significantly better in the intervention group. Conclusion: The present study results provide supportive evidence concerning pharmacists’ favourable effects on asthma patient care and support pharmacists as valuable members of the health care team.
文摘The nanotechnology revolution affected positively Architecture. Using nanotechnology is considered one of the most successful modern methods to achieve sustainable buildings with high functional efficiency. The discipline is Nano architecture, which uses Nanomaterials, products, or even Nano-shapes in the treatment of structure and construction.<span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">Despite the economic and urban advantages of using nanotechnology in the field of architecture and urbanism, we note that using nanotechnology is limited to some buildings uses in the city centers until now such as Administrative, commercial, educational, health, and recreational buildings or residential buildings. In spite of that, we found that nanotechnology was not used in priority buildings as “nuclear power plants” as it is considered one of the most eligible buildings to rely on nanotechnology to achieve safety, security, and functional efficiency requirements which have a great impact on advancing the movement of urban development.</span><span style="white-space:normal;font-family:;" "=""> </span><span style="white-space:normal;font-family:;" "="">From this standpoint, the research recommends the necessity of following a methodology to activate the establishment of nuclear power plants with such technology to preserve the safety of construction, reduce energy consumption, conserve economic resources and reduce pollution. The research is exposed to highlight a set of case studies that used such an effective technique and conclude a group of criteria that are recommended to be followed in the implementation and construction of the Dabaa plant in Egypt to achieve a sustainable nuclear power plant. So the research objective aims to adopt the idea of applying nanotechnology in various uses, whether it is in the city center or the outskirt of the city in order to develop these urban cities and transform them into smart sustainable environmental cities depending on nanotechnology aspects to achieve new sustainability scenario that accommodates the objectives of sustainability, with the support of new technologies. From this point of view, the research presents a proposal that includes a set of points that are recommended to be followed based on nanotechnology to achieve sustainability in the implementation of the Dabaa nuclear power plant in Egypt;which will have a great impact in advancing the movement of urban development in Egypt through improving the envelope of an urban typology, using nanotechnology materials on the fa<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">ç</span>ades, roofs, and external renovations </span><span style="white-space:normal;font-family:;" "=""></span><span style="white-space:normal;font-family:;" "="">with suitable constructive systems and in an easier way.</span>
基金The authors extend their appreciation to the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the project number RI-44-0525.
文摘COVID-19 has significantly impacted the growth prediction of a pandemic,and it is critical in determining how to battle and track the disease progression.In this case,COVID-19 data is a time-series dataset that can be projected using different methodologies.Thus,this work aims to gauge the spread of the outbreak severity over time.Furthermore,data analytics and Machine Learning(ML)techniques are employed to gain a broader understanding of virus infections.We have simulated,adjusted,and fitted several statistical time-series forecasting models,linearML models,and nonlinear ML models.Examples of these models are Logistic Regression,Lasso,Ridge,ElasticNet,Huber Regressor,Lasso Lars,Passive Aggressive Regressor,K-Neighbors Regressor,Decision Tree Regressor,Extra Trees Regressor,Support Vector Regressions(SVR),AdaBoost Regressor,Random Forest Regressor,Bagging Regressor,AuoRegression,MovingAverage,Gradient Boosting Regressor,Autoregressive Moving Average(ARMA),Auto-Regressive Integrated Moving Averages(ARIMA),SimpleExpSmoothing,Exponential Smoothing,Holt-Winters,Simple Moving Average,Weighted Moving Average,Croston,and naive Bayes.Furthermore,our suggested methodology includes the development and evaluation of ensemble models built on top of the best-performing statistical and ML-based prediction methods.A third stage in the proposed system is to examine three different implementations to determine which model delivers the best performance.Then,this best method is used for future forecasts,and consequently,we can collect the most accurate and dependable predictions.
文摘Countries implement corporate communication initiatives to improve their international relations,achieve different business objectives,and reinforce their brands.Nation branding activities are mainly based on international events:sport,culture,social issues.This paper evaluates the Expo 2020 Dubai’s impact on the United Arab Emirates’brand.We conducted a literature review about nation branding,and then we resorted to 15 indicators to analyze how the most important newspapers from some of the most influential countries(United States,Russia,France,and Germany)covered this event from a journalistic and corporate communication perspective.Our results proved that 82 articles were published about this topic,and the most common criteria respected were quoting organizers(n=61),using the Expo’s logo(n=45)and the image of a falcon(n=43).We concluded that most media companies focused on facts related to the Expo and did references to the country’s identity(values,flag,falcon),but most of them did not include links to the Dubai Expo’s and UAE public authorities’websites.
基金Universiti Malaysia Pahang for its financial support to this research(University Research Grant Scheme RDU223303).
文摘This study examines how controlling shareholders influence firm performance through the mediating role of firm efficiency in transforming inputs into outputs.To achieve this objective,it conducts a mediation analysis with 5,000 bootstraps on a dataset of 2,849 firm-year observations of publicly listed firms in Malaysia from 2009 to 2019.The findings reveal a positive relationship between controlling shareholdings and firm performance,with both total and indirect effects having this positive relationship.Moreover,while controlling shareholdings improve firm performance,firm efficiency partially mediates this relationship.Thus,improved firm efficiency plays a critical role in understanding the relationship between governance by controlling shareholders and enhanced firm performance.In summary,this study contributes to the existing literature by expanding our understanding of the complex relationship between controlling shareholdings,firm efficiency,and firm performance.In addition,the findings shed light on the importance of indirect channels in shaping organizational outcomes.As such,this study provides a valuable direction for future research in this area.
基金provided by Ministry of Science and Technology(Grant No.MOST 107-2410-H-034-056-MY3).
文摘The central concept of strategic benchmarking is resource management efficiency,which ultimately results in profitability.However,little is known about performance measurement from resource-based perspectives.This study uses the data envelopment analysis(DEA)model with a dynamic network structure to measure the resource management and profitability efficiencies of 287 US commercial banks from 2010 to 2020.Furthermore,we provide frontier projections and incorporate five variables,namely capital adequacy,asset quality,management quality,earning ability,and liquidity(i.e.,the CAMEL ratings).The results revealed that the room for improvement in bank performance is 55.4%.In addition,we found that the CAMEL ratings of efficient banks are generally higher than those of inefficient banks,and management quality,earnings quality,and liquidity ratios positively contribute to bank performance.Moreover,big banks are generally more efficient than small banks.Overall,this study continues the current heated debate on performance measurement in the banking industry,with a particular focus on the DEA application to answer the fundamental question of why resource management efficiency reflects benchmark firms and provides insights into how efficient management of CAMEL ratings would help in improving their performance.
基金Project supported by the Princess Nourah bint Abdulrahman University Researchers Supporting Project(No.PNURSP2023R66)。
文摘Quaternion algebra has been used to apply the fractional Fourier transform(FrFT)to color images in a comprehensive approach.However,the discrete fractional random transform(DFRNT)with adequate basic randomness remains to be examined.This paper presents a novel multistage privacy system for color medical images based on discrete quaternion fractional Fourier transform(DQFrFT)watermarking and three-dimensional chaotic logistic map(3D-CLM)encryption.First,we describe quaternion DFRNT(QDFRNT),which generalizes DFRNT to handle quaternion signals effectively,and then use QDFRNT to perform color medical image adaptive watermarking.To efficiently evaluate QDFRNT,this study derives the relationship between the QDFRNT of a quaternion signal and the four components of the DFRNT signal.Moreover,it uses the human vision system's(HVS)masking qualities of edge,texture,and color tone immediately from the color host image to adaptively modify the watermark strength for each block in the color medical image using the QDFRNT-based adaptive watermarking and support vector machine(SVM)techniques.The limitations of watermark embedding are also explained to conserve watermarking energy.Second,3D-CLM encryption is employed to improve the system's security and efficiency,allowing it to be used as a multistage privacy system.The proposed security system is effective against many types of channel noise attacks,according to simulation results.
