The study aims to formulate a solution for identifying the safest route between any two inputted Geographical locations.Using the New York City dataset,which provides us with location tagged crime statistics;we are im...The study aims to formulate a solution for identifying the safest route between any two inputted Geographical locations.Using the New York City dataset,which provides us with location tagged crime statistics;we are implementing different clustering algorithms and analysed the results comparatively to discover the best-suited one.The results unveil the fact that the K-Means algorithm best suits for our needs and delivered the best results.Moreover,a comparative analysis has been performed among various clustering techniques to obtain best results.we compared all the achieved results and using the conclusions we have developed a user-friendly application to provide safe route to users.The successful implementation would hopefully aid us to curb the ever-increasing crime rates;as it aims to provide the user with a beforehand knowledge of the route they are about to take.A warning that the path is marked high on danger index would convey the basic hint for the user to decide which path to prefer.Thus,addressing a social problem which needs to be eradicated from our modern era.展开更多
Although severe and chronic mental disorders are common among Asian Americans in residential treatment programs, little has been known about the prevalence and predictors of co-occurring substance use in this populati...Although severe and chronic mental disorders are common among Asian Americans in residential treatment programs, little has been known about the prevalence and predictors of co-occurring substance use in this population. The purpose of this study was to examine predictors of co-occurring substance use among Asian Americans with mental disorders in residential treatment programs. This cross-sectional study included 375 clinical records of Asian Americans from residential treatment programs between 2007 and 2011. Demographic variables, principal psychiatric diagnoses, and data on alcohol, stimulant, and marijuana use were obtained from the clinical records. Separate binary logistic regression analyses were used to examine the demographic and diagnostic contributions to the risk of each type of substance use. Findings of this study indicated that the prevalence of co-occurring substance use was about 53% in Asian Americans with mental disorders. Binary logistic regression analyses revealed that male gender, older age, and depressive disorder predicted more alcohol use, but homelessness and schizophrenia predicted less alcohol use. Male gender, homelessness, and smoking predicted more stimulant use. Male gender and younger age predicted more marijuana use. Based on the findings of this study, awareness about co-occurring substance use problems of ethnic minority psychiatric clients should be increased and appropriate substance use prevention and treatment programs should be developed and provided for high-risk groups.展开更多
基金This research was supported by X-mind Corps program of National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT(No.2019H1D8A1105622)the Soonchunhyang University Research Fund.
文摘The study aims to formulate a solution for identifying the safest route between any two inputted Geographical locations.Using the New York City dataset,which provides us with location tagged crime statistics;we are implementing different clustering algorithms and analysed the results comparatively to discover the best-suited one.The results unveil the fact that the K-Means algorithm best suits for our needs and delivered the best results.Moreover,a comparative analysis has been performed among various clustering techniques to obtain best results.we compared all the achieved results and using the conclusions we have developed a user-friendly application to provide safe route to users.The successful implementation would hopefully aid us to curb the ever-increasing crime rates;as it aims to provide the user with a beforehand knowledge of the route they are about to take.A warning that the path is marked high on danger index would convey the basic hint for the user to decide which path to prefer.Thus,addressing a social problem which needs to be eradicated from our modern era.
文摘Although severe and chronic mental disorders are common among Asian Americans in residential treatment programs, little has been known about the prevalence and predictors of co-occurring substance use in this population. The purpose of this study was to examine predictors of co-occurring substance use among Asian Americans with mental disorders in residential treatment programs. This cross-sectional study included 375 clinical records of Asian Americans from residential treatment programs between 2007 and 2011. Demographic variables, principal psychiatric diagnoses, and data on alcohol, stimulant, and marijuana use were obtained from the clinical records. Separate binary logistic regression analyses were used to examine the demographic and diagnostic contributions to the risk of each type of substance use. Findings of this study indicated that the prevalence of co-occurring substance use was about 53% in Asian Americans with mental disorders. Binary logistic regression analyses revealed that male gender, older age, and depressive disorder predicted more alcohol use, but homelessness and schizophrenia predicted less alcohol use. Male gender, homelessness, and smoking predicted more stimulant use. Male gender and younger age predicted more marijuana use. Based on the findings of this study, awareness about co-occurring substance use problems of ethnic minority psychiatric clients should be increased and appropriate substance use prevention and treatment programs should be developed and provided for high-risk groups.
