Assessment of rock mass quality significantly impacts the design and construction of underground and open-pit mines from the point of stability and economy.This study develops the novel Gromov-Hausdorff distance for r...Assessment of rock mass quality significantly impacts the design and construction of underground and open-pit mines from the point of stability and economy.This study develops the novel Gromov-Hausdorff distance for rock quality(GHDQR)methodology for rock mass quality rating based on multi-criteria grey metric space.It usually presents the quality of surrounding rock by classes(metric spaces)with specified properties and adequate interval-grey numbers.Measuring the distance between surrounding rock sample characteristics and existing classes represents the core of this study.The Gromov-Hausdorff distance is an especially useful discriminant function,i.e.,a classifier to calculate these distances,and assess the quality of the surrounding rock.The efficiency of the developed methodology is analyzed using the Mean Absolute Percentage Error(MAPE)technique.Seven existing methods,such as the Gaussian cloud method,Discriminant method,Mutation series method,Artificial neural network(ANN),Support vector machine(SVM),Grey wolf optimizer and Support vector classification method(GWO-SVC)and Rock mass rating method(RMR)are used for comparison with the proposed GHDQR method.The share of the highly accurate category of 85.71%clearly indicates compliance with actual values obtained by the compared methods.The results of comparisons showed that the model enables objective,efficient,and reliable assessment of rock mass quality.展开更多
The rock mass rating(RMR)has been used across the geotechnical industry for half a century.In contrast,the coal mine roof rating(CMRR)was specifically introduced to underground coal mines two decades ago to link geolo...The rock mass rating(RMR)has been used across the geotechnical industry for half a century.In contrast,the coal mine roof rating(CMRR)was specifically introduced to underground coal mines two decades ago to link geological characterization with geotechnical risk mitigation.The premise of CMRR is that strength properties of mine roof rock are influenced by defects typical of coal measures stratigraphy.The CMRR has been used in longwall pillar design,roof support methods,and evaluation of extended cuts,but is rarely evaluated.Here,the RMR and CMRR are applied to a longwall coal mine.Roof rock mass classifications were undertaken at 67 locations across the mine.Both classifications showed marked spatial variability in terms of roof conditions.Normal and reverse faulting occur across the mine,and while no clear relationships exist between rock mass character and faulting,a central graben zone showed heterogeneous rock mass properties,and divergence between CMRR and RMR.Overall,the CMRR data fell within the broad envelope of results reported for extended cuts at Australian and U.S.coal mines.The corollary is that the CMRR is useful,and should not be used in isolation,but rather as a component of a strata control programme.展开更多
Rock mass rating system(RMR) is based on the six parameters which was defined by Bieniawski(1989)[1]. Experts frequently relate joint and discontinuities and ground water conditions in linguistic terms with rough calc...Rock mass rating system(RMR) is based on the six parameters which was defined by Bieniawski(1989)[1]. Experts frequently relate joint and discontinuities and ground water conditions in linguistic terms with rough calculation. As a result, there is a sharp transition between two modules which create doubts.So, in this paper the proposed weights technique was applied for linguistic criteria. Then by using the fuzzy inference system and the multi-variable regression analysis, the accurate RMR is predicted. Before the performing of regression analysis, sensitivity analysis was applied for each of Bieniawski parameters.In this process, the best function was selected among linear, logarithmic, exponential and inverse functions and finally it was applied in the regression analysis for construction of a predictive equation. From the constructed regression equation the relative importance of the input parameters can also be observed. It should be noted that joint condition was identified as the most important effective parameter upon RMR. Finally, fuzzy and regression models were validated with the test datasets and it was found that the fuzzy model predicts more accurately RMR than regression models.展开更多
The purpose of this paper is to establish confidence in anticipated minimum bond strength for inflatable rock bolts by comparing the bond strength to variable geotechnical conditions using the rock mass rating(RMR) sy...The purpose of this paper is to establish confidence in anticipated minimum bond strength for inflatable rock bolts by comparing the bond strength to variable geotechnical conditions using the rock mass rating(RMR) system. To investigate a correlation between these parameters,the minimum bond strength of pull-out tested inflatable rock bolts was compared to the RMR of the rock in which these bolts were placed. Bond strength vs. RMR plots indicate that expected minimum bond strength is positively correlated with RMR; however,the correlation is not strong. Cumulative percent graphs indicate that 97% of pull-out tests result in a minimum bond strength of 3.3 and 1.7 ton/m in RMR P 45 and <45,respectively.Although lower bond strengths are more commonly encountered in low RMR ground,high bond strengths are possible as well,yielding higher variability in bond strengths in low RMR ground. Bond strength of friction bolts relies on contact between the rock bolt and drill hole. Experience in Nevada indicates that RMR is known to affect both the quality and consistency of drill holes which likely affects bond strength. Drilling and bolting in low RMR ground is more sensitive to drilling and bolting practices,and strategies for maximizing bond strength in these conditions are discussed.展开更多
To begin with, rating systems are a beneficial tool in determining the efficiency of a building’s ability to utilise its resources effectively. In this study, the two elements under comparison are the Building Rating...To begin with, rating systems are a beneficial tool in determining the efficiency of a building’s ability to utilise its resources effectively. In this study, the two elements under comparison are the Building Rating Systems (BRSs) and Occupant Rating Systems (ORSs). The main objective of this paper is to be able to examine the most commonly applied international and national BRS and ORS and, based on that, discover the possibility of developing an integration of both the BRS and ORS into one rating system. Quite simply, a BRS is a method by which buildings are assessed and given a score based on numerous features such as the efficiency of each of the services, total energy consumption, and alternate options of consumption. There are various BRSs that are implemented globally, each with its own set of criteria and specifications. Thus, based on the analysis of the benefits and drawbacks of both types of rating systems, it could be deduced that a well-rounded rating system with all technical and non-technical aspects combined would be beneficial to both the efficiency of the building as well as the building occupants’ health and well-being.展开更多
Given the importance of lithium-ion cell safety,a comprehensive review on the thermal stability of lithium-ion cells investigated by accelerating rate calorimetry(ARC),is provided in the present work.The operating mec...Given the importance of lithium-ion cell safety,a comprehensive review on the thermal stability of lithium-ion cells investigated by accelerating rate calorimetry(ARC),is provided in the present work.The operating mechanism of ARC is discussed first,including the usage and the reaction kinetics.Besides that,the thermal stability of the cathode/anode materials at elevated temperatures is revealed by examining the impacts of some significant factors,i.e.,the lithium content,particle size,material density,lithium salt,solvent,additive,binder and initial heating temperature.A comparison of the common cathode materials indicates that the presence of Mn and polyanion could significantly enhance the thermal stability of cathode materials,while the doping of Al also helps to restrain the reactivity.Except for their high capacity,some alloy materials demonstrate more competitive safety than traditional carbon anode materials.Furthermore,the thermal behaviors of full cells under abusive conditions are reviewed here.Due to the sensitivity of ARC to the kinetic parameters,a reaction kinetic modeling can be built on the basis of ARC profiles,to predict the thermal behaviors of cell components and cells.Herein,a shortcircuit modeling is exampled.展开更多
Due to the broadcast nature of wireless communications,users’data transmitted wirelessly is susceptible to security/privacy threats.Meanwhile,as a result of the limitation of spectrum resources,massive wireless conne...Due to the broadcast nature of wireless communications,users’data transmitted wirelessly is susceptible to security/privacy threats.Meanwhile,as a result of the limitation of spectrum resources,massive wireless connections will incur serious interference,which may damage the efficiency of data transmission.Therefore,improving both efficiency and secrecy of data transmission is of research significance.In this paper,we propose a wireless transmission scheme by taking both Secure Communication(SC)and Interference Management(IM)into account,namely SCIM.With this scheme,an SCIM signal is generated by the legitimate transmitter(Tx)and sent along with the desired signal,so that the SCIM signal can interact with and suppress the environmental interference at the legitimate receiver(Rx).Meanwhile,the SCIM signal may interfere with the eavesdropper in the coverage of legitimate transmission so as to deteriorate the eavesdropping performance.Therefore,the secrecy of desired transmission is improved.In this way,both the transmission efficiency and privacy are enhanced.Then,by taking various transmission preferences into account,we develop different implementations of SCIM,including Interference Suppression First SCIM(ISF-SCIM),Data Transmission First SCIM(DTF-SCIM),Anti-Eavesdropping First SCIM(AEF-SCIM),and Secrecy Rate Maximization SCIM(SRM-SCIM).Our in-depth simulation results have shown the proposed methods to effectively improve the efficiency and secrecy of the legitimate transmission.展开更多
In this technical note,a novel rating scale(abdominal integral index)was introduced for assessing the conditions of the working laparoscopic space based on linear measurements to select the optimal one or two-stage su...In this technical note,a novel rating scale(abdominal integral index)was introduced for assessing the conditions of the working laparoscopic space based on linear measurements to select the optimal one or two-stage surgical treatment for super-obesity.Patients with the same height and similar BMI values had different rating scale scores,reflecting different conditions of laparoscopic bariatric surgery.The rating scale helps surgeons and patients make a safe option for surgery,depending on the experience of the surgeon and technical laparoscopic conditions.展开更多
In this work,we design a multisensory IoT-based online vitals monitor(hereinafter referred to as the VITALS)to sense four bedside physiological parameters including pulse(heart)rate,body temperature,blood pressure,and...In this work,we design a multisensory IoT-based online vitals monitor(hereinafter referred to as the VITALS)to sense four bedside physiological parameters including pulse(heart)rate,body temperature,blood pressure,and periph-eral oxygen saturation.Then,the proposed system constantly transfers these signals to the analytics system which aids in enhancing diagnostics at an earlier stage as well as monitoring after recovery.The core hardware of the VITALS includes commercial off-the-shelf sensing devices/medical equipment,a powerful microcontroller,a reliable wireless communication module,and a big data analytics system.It extracts human vital signs in a pre-programmed interval of 30 min and sends them to big data analytics system through the WiFi module for further analysis.We use Apache Kafka(to gather live data streams from connected sen-sors),Apache Spark(to categorize the patient vitals and notify the medical pro-fessionals while identifying abnormalities in physiological parameters),Hadoop Distributed File System(HDFS)(to archive data streams for further analysis and long-term storage),Spark SQL,Hive and Matplotlib(to support caregivers to access/visualize appropriate information from collected data streams and to explore/understand the health status of the individuals).In addition,we develop a mobile application to send statistical graphs to doctors and patients to enable them to monitor health conditions remotely.Our proposed system is implemented on three patients for 7 days to check the effectiveness of sensing,data processing,and data transmission mechanisms.To validate the system accuracy,we compare the data values collected from established sensors with the measured readouts using a commercial healthcare monitor,the Welch Allyn®Spot Check.Our pro-posed system provides improved care solutions,especially for those whose access to care services is limited.展开更多
This study employs a bibliometric and systematic approach to examine the impact of credit ratings as a measure of financial performance for companies listed in the S&P 500 index.The study identified a knowledge ga...This study employs a bibliometric and systematic approach to examine the impact of credit ratings as a measure of financial performance for companies listed in the S&P 500 index.The study identified a knowledge gap as only two researches were found,one suggesting and another using credit ratings to measure financial performance.Most researches use leverage,profitability,liquidity,and Share Return measures to explain financial performance.The empirical analysis uses the data of 2,398 observations of 240 companies rated by S&P Global Ratings for the period 2009-2013,applying a Generalized Method of Moments(GMM)methodology to estimate the models due to its ability to address potential endogeneity issues.The study considers Return on Assets(ROA)and Tobin’s Q as dependent variables.It incorporates credit ratings(CRWLTA)along with variables such as Total Debt to Total Assets(TDTA),Total Shareholder Return(TSR),EBITDA Interest coverage(EBITDAICOV),Quick Ratio(QR),Altman’s Z-Score(AZS),as well as macroeconomic factors like Gross Domestic Product(GDP)growth,inflation(Consumer Price Index-CPI),and the Federal Reserve Interest Rate(FDRI)as independent variables.The study argues that credit ratings,which incorporate historical data and confidential information about companies’strategies,provide reliable forward-looking creditworthiness assessments to the market.It is supported by specialized rating agencies that employ their methodologies.However,the findings suggested that CRWLTA,had a negative relationship with Q Tobin,although it was not statistically significant,and a negative relationship with ROA that was on the verge of significance.展开更多
This paper examines the prediction of film ratings.Firstly,in the data feature engineering,feature construction is performed based on the original features of the film dataset.Secondly,the clustering algorithm is util...This paper examines the prediction of film ratings.Firstly,in the data feature engineering,feature construction is performed based on the original features of the film dataset.Secondly,the clustering algorithm is utilized to remove singular film samples,and feature selections are carried out.When solving the problem that film samples of the target domain are unlabelled,it is impossible to train a model and address the inconsistency in the feature dimension for film samples from the source domain.Therefore,the domain adaptive transfer learning model combined with dimensionality reduction algorithms is adopted in this paper.At the same time,in order to reduce the prediction error of models,the stacking ensemble learning model for regression is also used.Finally,through comparative experiments,the effectiveness of the proposed method is verified,which proves to be better predicting film ratings in the target domain.展开更多
With the advancements in internet facilities,people are more inclined towards the use of online services.The service providers shelve their items for e-users.These users post their feedbacks,reviews,ratings,etc.after ...With the advancements in internet facilities,people are more inclined towards the use of online services.The service providers shelve their items for e-users.These users post their feedbacks,reviews,ratings,etc.after the use of the item.The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items.Sentiment Analysis(SA)is a technique that performs such decision analysis.This research targets the ranking and rating through sentiment analysis of these reviews,on different aspects.As a case study,Songs are opted to design and test the decision model.Different aspects of songs namely music,lyrics,song,voice and video are picked.For the reason,reviews of 20 songs are scraped from YouTube,pre-processed and formed a dataset.Different machine learning algorithms—Naïve Bayes(NB),Gradient Boost Tree,Logistic Regression LR,K-Nearest Neighbors(KNN)and Artificial Neural Network(ANN)are applied.ANN performed the best with 74.99%accuracy.Results are validated using K-Fold.展开更多
In this work, we have studied the vacancy formation energy of TiN alloy of structure B2 of size 10 × 10 × 10 for nitrogen percentages of 45%, 50% and 55% under the influence of temperature at 1320 K, 1420 K ...In this work, we have studied the vacancy formation energy of TiN alloy of structure B2 of size 10 × 10 × 10 for nitrogen percentages of 45%, 50% and 55% under the influence of temperature at 1320 K, 1420 K and 1520 K using the Modified Embedded Atom Method MEAM under the calculation code LAMMPS version 2020. This study has enabled us to understand the behavior of the TiN alloy under different nitrogen percentages in terms of total energy, vacancy formation energy, crystalline parameter, occupancy rate and order parameter. For total energy, we have shown that as temperature increases, total energy decreases, making it easier to obtain TiN at higher temperatures;reaching the value of -7344.9169 eV for the 55% nitrogen structure for the temperature of 1420 K. For the energy of formation, we have shown that the compounds obtained at 1320 K and 1520 K have a more considerable energy of formation than that obtained at 1420 K. The study of fractions and the order parameter showed us that the structure of TiN with 55% nitrogen is less likely, as the composition obtained is at most 53.35%.展开更多
文摘Assessment of rock mass quality significantly impacts the design and construction of underground and open-pit mines from the point of stability and economy.This study develops the novel Gromov-Hausdorff distance for rock quality(GHDQR)methodology for rock mass quality rating based on multi-criteria grey metric space.It usually presents the quality of surrounding rock by classes(metric spaces)with specified properties and adequate interval-grey numbers.Measuring the distance between surrounding rock sample characteristics and existing classes represents the core of this study.The Gromov-Hausdorff distance is an especially useful discriminant function,i.e.,a classifier to calculate these distances,and assess the quality of the surrounding rock.The efficiency of the developed methodology is analyzed using the Mean Absolute Percentage Error(MAPE)technique.Seven existing methods,such as the Gaussian cloud method,Discriminant method,Mutation series method,Artificial neural network(ANN),Support vector machine(SVM),Grey wolf optimizer and Support vector classification method(GWO-SVC)and Rock mass rating method(RMR)are used for comparison with the proposed GHDQR method.The share of the highly accurate category of 85.71%clearly indicates compliance with actual values obtained by the compared methods.The results of comparisons showed that the model enables objective,efficient,and reliable assessment of rock mass quality.
基金Staff at Vale Australia,in particular Lachlan Cunningham and Priscilla Page,are thanked for facilitating underground access to the Carborough Downs Mine.The research was kindly supported by Moultrie Group and Golder Associates.
文摘The rock mass rating(RMR)has been used across the geotechnical industry for half a century.In contrast,the coal mine roof rating(CMRR)was specifically introduced to underground coal mines two decades ago to link geological characterization with geotechnical risk mitigation.The premise of CMRR is that strength properties of mine roof rock are influenced by defects typical of coal measures stratigraphy.The CMRR has been used in longwall pillar design,roof support methods,and evaluation of extended cuts,but is rarely evaluated.Here,the RMR and CMRR are applied to a longwall coal mine.Roof rock mass classifications were undertaken at 67 locations across the mine.Both classifications showed marked spatial variability in terms of roof conditions.Normal and reverse faulting occur across the mine,and while no clear relationships exist between rock mass character and faulting,a central graben zone showed heterogeneous rock mass properties,and divergence between CMRR and RMR.Overall,the CMRR data fell within the broad envelope of results reported for extended cuts at Australian and U.S.coal mines.The corollary is that the CMRR is useful,and should not be used in isolation,but rather as a component of a strata control programme.
文摘Rock mass rating system(RMR) is based on the six parameters which was defined by Bieniawski(1989)[1]. Experts frequently relate joint and discontinuities and ground water conditions in linguistic terms with rough calculation. As a result, there is a sharp transition between two modules which create doubts.So, in this paper the proposed weights technique was applied for linguistic criteria. Then by using the fuzzy inference system and the multi-variable regression analysis, the accurate RMR is predicted. Before the performing of regression analysis, sensitivity analysis was applied for each of Bieniawski parameters.In this process, the best function was selected among linear, logarithmic, exponential and inverse functions and finally it was applied in the regression analysis for construction of a predictive equation. From the constructed regression equation the relative importance of the input parameters can also be observed. It should be noted that joint condition was identified as the most important effective parameter upon RMR. Finally, fuzzy and regression models were validated with the test datasets and it was found that the fuzzy model predicts more accurately RMR than regression models.
文摘The purpose of this paper is to establish confidence in anticipated minimum bond strength for inflatable rock bolts by comparing the bond strength to variable geotechnical conditions using the rock mass rating(RMR) system. To investigate a correlation between these parameters,the minimum bond strength of pull-out tested inflatable rock bolts was compared to the RMR of the rock in which these bolts were placed. Bond strength vs. RMR plots indicate that expected minimum bond strength is positively correlated with RMR; however,the correlation is not strong. Cumulative percent graphs indicate that 97% of pull-out tests result in a minimum bond strength of 3.3 and 1.7 ton/m in RMR P 45 and <45,respectively.Although lower bond strengths are more commonly encountered in low RMR ground,high bond strengths are possible as well,yielding higher variability in bond strengths in low RMR ground. Bond strength of friction bolts relies on contact between the rock bolt and drill hole. Experience in Nevada indicates that RMR is known to affect both the quality and consistency of drill holes which likely affects bond strength. Drilling and bolting in low RMR ground is more sensitive to drilling and bolting practices,and strategies for maximizing bond strength in these conditions are discussed.
文摘To begin with, rating systems are a beneficial tool in determining the efficiency of a building’s ability to utilise its resources effectively. In this study, the two elements under comparison are the Building Rating Systems (BRSs) and Occupant Rating Systems (ORSs). The main objective of this paper is to be able to examine the most commonly applied international and national BRS and ORS and, based on that, discover the possibility of developing an integration of both the BRS and ORS into one rating system. Quite simply, a BRS is a method by which buildings are assessed and given a score based on numerous features such as the efficiency of each of the services, total energy consumption, and alternate options of consumption. There are various BRSs that are implemented globally, each with its own set of criteria and specifications. Thus, based on the analysis of the benefits and drawbacks of both types of rating systems, it could be deduced that a well-rounded rating system with all technical and non-technical aspects combined would be beneficial to both the efficiency of the building as well as the building occupants’ health and well-being.
基金supported by NSERC,Tesla Motors,the National Natural Science Foundation of China (No.52204213,52272396)the China Postdoctoral Science Foundation (No.2022M711602)+2 种基金the Opening Fund of State Key Laboratory of Fire Science (SKLFS) (No.HZ2022-KF07)the Jiangsu Project Plan for Outstanding Talents Team in Six Research Fields (No.TD-XNYQC-002)the support of the China Scholarship Council。
文摘Given the importance of lithium-ion cell safety,a comprehensive review on the thermal stability of lithium-ion cells investigated by accelerating rate calorimetry(ARC),is provided in the present work.The operating mechanism of ARC is discussed first,including the usage and the reaction kinetics.Besides that,the thermal stability of the cathode/anode materials at elevated temperatures is revealed by examining the impacts of some significant factors,i.e.,the lithium content,particle size,material density,lithium salt,solvent,additive,binder and initial heating temperature.A comparison of the common cathode materials indicates that the presence of Mn and polyanion could significantly enhance the thermal stability of cathode materials,while the doping of Al also helps to restrain the reactivity.Except for their high capacity,some alloy materials demonstrate more competitive safety than traditional carbon anode materials.Furthermore,the thermal behaviors of full cells under abusive conditions are reviewed here.Due to the sensitivity of ARC to the kinetic parameters,a reaction kinetic modeling can be built on the basis of ARC profiles,to predict the thermal behaviors of cell components and cells.Herein,a shortcircuit modeling is exampled.
基金supported in part by the Natural Science Foundation of Shaanxi Province under Grant Number 2021JM-143the Fundamental Research Funds for the Central Universities under Grant Number JB211502+5 种基金the Project of Key Laboratory of Science and Technology on Communication Network under Grant Number 6142104200412the National Natural Science Foundation of China under Grant Number 61672410the Academy of Finland under Grant Number 308087the China 111 project under Grant Number B16037JSPS KAKENHI under Grant Number JP20K14742and the Project of Cyber Security Establishment with Inter University Cooperation.
文摘Due to the broadcast nature of wireless communications,users’data transmitted wirelessly is susceptible to security/privacy threats.Meanwhile,as a result of the limitation of spectrum resources,massive wireless connections will incur serious interference,which may damage the efficiency of data transmission.Therefore,improving both efficiency and secrecy of data transmission is of research significance.In this paper,we propose a wireless transmission scheme by taking both Secure Communication(SC)and Interference Management(IM)into account,namely SCIM.With this scheme,an SCIM signal is generated by the legitimate transmitter(Tx)and sent along with the desired signal,so that the SCIM signal can interact with and suppress the environmental interference at the legitimate receiver(Rx).Meanwhile,the SCIM signal may interfere with the eavesdropper in the coverage of legitimate transmission so as to deteriorate the eavesdropping performance.Therefore,the secrecy of desired transmission is improved.In this way,both the transmission efficiency and privacy are enhanced.Then,by taking various transmission preferences into account,we develop different implementations of SCIM,including Interference Suppression First SCIM(ISF-SCIM),Data Transmission First SCIM(DTF-SCIM),Anti-Eavesdropping First SCIM(AEF-SCIM),and Secrecy Rate Maximization SCIM(SRM-SCIM).Our in-depth simulation results have shown the proposed methods to effectively improve the efficiency and secrecy of the legitimate transmission.
文摘In this technical note,a novel rating scale(abdominal integral index)was introduced for assessing the conditions of the working laparoscopic space based on linear measurements to select the optimal one or two-stage surgical treatment for super-obesity.Patients with the same height and similar BMI values had different rating scale scores,reflecting different conditions of laparoscopic bariatric surgery.The rating scale helps surgeons and patients make a safe option for surgery,depending on the experience of the surgeon and technical laparoscopic conditions.
文摘In this work,we design a multisensory IoT-based online vitals monitor(hereinafter referred to as the VITALS)to sense four bedside physiological parameters including pulse(heart)rate,body temperature,blood pressure,and periph-eral oxygen saturation.Then,the proposed system constantly transfers these signals to the analytics system which aids in enhancing diagnostics at an earlier stage as well as monitoring after recovery.The core hardware of the VITALS includes commercial off-the-shelf sensing devices/medical equipment,a powerful microcontroller,a reliable wireless communication module,and a big data analytics system.It extracts human vital signs in a pre-programmed interval of 30 min and sends them to big data analytics system through the WiFi module for further analysis.We use Apache Kafka(to gather live data streams from connected sen-sors),Apache Spark(to categorize the patient vitals and notify the medical pro-fessionals while identifying abnormalities in physiological parameters),Hadoop Distributed File System(HDFS)(to archive data streams for further analysis and long-term storage),Spark SQL,Hive and Matplotlib(to support caregivers to access/visualize appropriate information from collected data streams and to explore/understand the health status of the individuals).In addition,we develop a mobile application to send statistical graphs to doctors and patients to enable them to monitor health conditions remotely.Our proposed system is implemented on three patients for 7 days to check the effectiveness of sensing,data processing,and data transmission mechanisms.To validate the system accuracy,we compare the data values collected from established sensors with the measured readouts using a commercial healthcare monitor,the Welch Allyn®Spot Check.Our pro-posed system provides improved care solutions,especially for those whose access to care services is limited.
文摘This study employs a bibliometric and systematic approach to examine the impact of credit ratings as a measure of financial performance for companies listed in the S&P 500 index.The study identified a knowledge gap as only two researches were found,one suggesting and another using credit ratings to measure financial performance.Most researches use leverage,profitability,liquidity,and Share Return measures to explain financial performance.The empirical analysis uses the data of 2,398 observations of 240 companies rated by S&P Global Ratings for the period 2009-2013,applying a Generalized Method of Moments(GMM)methodology to estimate the models due to its ability to address potential endogeneity issues.The study considers Return on Assets(ROA)and Tobin’s Q as dependent variables.It incorporates credit ratings(CRWLTA)along with variables such as Total Debt to Total Assets(TDTA),Total Shareholder Return(TSR),EBITDA Interest coverage(EBITDAICOV),Quick Ratio(QR),Altman’s Z-Score(AZS),as well as macroeconomic factors like Gross Domestic Product(GDP)growth,inflation(Consumer Price Index-CPI),and the Federal Reserve Interest Rate(FDRI)as independent variables.The study argues that credit ratings,which incorporate historical data and confidential information about companies’strategies,provide reliable forward-looking creditworthiness assessments to the market.It is supported by specialized rating agencies that employ their methodologies.However,the findings suggested that CRWLTA,had a negative relationship with Q Tobin,although it was not statistically significant,and a negative relationship with ROA that was on the verge of significance.
基金Supported by the Scientific Research Foundation of Liaoning Provincial Department of Education(No.LJKZ0139).
文摘This paper examines the prediction of film ratings.Firstly,in the data feature engineering,feature construction is performed based on the original features of the film dataset.Secondly,the clustering algorithm is utilized to remove singular film samples,and feature selections are carried out.When solving the problem that film samples of the target domain are unlabelled,it is impossible to train a model and address the inconsistency in the feature dimension for film samples from the source domain.Therefore,the domain adaptive transfer learning model combined with dimensionality reduction algorithms is adopted in this paper.At the same time,in order to reduce the prediction error of models,the stacking ensemble learning model for regression is also used.Finally,through comparative experiments,the effectiveness of the proposed method is verified,which proves to be better predicting film ratings in the target domain.
文摘With the advancements in internet facilities,people are more inclined towards the use of online services.The service providers shelve their items for e-users.These users post their feedbacks,reviews,ratings,etc.after the use of the item.The enormous increase in these reviews has raised the need for an automated system to analyze these reviews to rate these items.Sentiment Analysis(SA)is a technique that performs such decision analysis.This research targets the ranking and rating through sentiment analysis of these reviews,on different aspects.As a case study,Songs are opted to design and test the decision model.Different aspects of songs namely music,lyrics,song,voice and video are picked.For the reason,reviews of 20 songs are scraped from YouTube,pre-processed and formed a dataset.Different machine learning algorithms—Naïve Bayes(NB),Gradient Boost Tree,Logistic Regression LR,K-Nearest Neighbors(KNN)and Artificial Neural Network(ANN)are applied.ANN performed the best with 74.99%accuracy.Results are validated using K-Fold.
文摘In this work, we have studied the vacancy formation energy of TiN alloy of structure B2 of size 10 × 10 × 10 for nitrogen percentages of 45%, 50% and 55% under the influence of temperature at 1320 K, 1420 K and 1520 K using the Modified Embedded Atom Method MEAM under the calculation code LAMMPS version 2020. This study has enabled us to understand the behavior of the TiN alloy under different nitrogen percentages in terms of total energy, vacancy formation energy, crystalline parameter, occupancy rate and order parameter. For total energy, we have shown that as temperature increases, total energy decreases, making it easier to obtain TiN at higher temperatures;reaching the value of -7344.9169 eV for the 55% nitrogen structure for the temperature of 1420 K. For the energy of formation, we have shown that the compounds obtained at 1320 K and 1520 K have a more considerable energy of formation than that obtained at 1420 K. The study of fractions and the order parameter showed us that the structure of TiN with 55% nitrogen is less likely, as the composition obtained is at most 53.35%.
