INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Historically, gold, unlike other payment channels, was employed to support trading acquisitions w... more Historically, gold, unlike other payment channels, was employed to support trading acquisitions worldwide. We forecast future gold prices based on twenty-two market variables using a machine learning technique. In order to analyze these data, one machine learning approach, random forest regression, was applied. Numerous states have kept and increased their gold reserves while being progressive and rich. In reality, central banks throughout the world keep precious metals like gold on hand to ensure foreign debt service in addition to stabilizing inflation. The primary goal of this research is to anticipate the increase and fall in routine gold rates, which will assist investors in deciding whether to purchase or sell gold. Logistics forecasting is critical to the fiscal performance of an organization. The secondary market is derived by examining the dataset including the previous year's gold price. There is concern that these high prices will not be sustainable and will fall desp...
Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. How... more Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. However, diagnostic test shortages are prevalent globally and continue to occur in the US with the onset of new COVID-19 variants, demonstrating an unprecedented need for improving our current methods for mass surveillance testing. By targeting surveillance testing towards individuals who are most likely to be infected and, thus, increasing testing positivity rate (i.e., percent positive in the surveillance group), fewer tests are needed to capture the same number of positive cases. Here, we developed an Intelligent Testing Allocation (ITA) method by leveraging data from the CovIdentify study (6,765 participants) and the MyPHD study (8,580 participants), including smartwatch data from 1,265 individuals of whom 126 tested positive for COVID-19. Our rigorous model and parameter search uncovered the optimal time periods and aggregate metrics for monitoring continuous digital biomarkers to incr...
The large amount of biomedical data derived from wearable sensors, electronic health records, and... more The large amount of biomedical data derived from wearable sensors, electronic health records, and molecular profiling (e.g., genomics data) is rapidly transforming our healthcare systems. The increasing scale and scope of biomedical data not only is generating enormous opportunities for improving health outcomes but also raises new challenges ranging from data acquisition and storage to data analysis and utilization. To meet these challenges, we developed the Personal Health Dashboard (PHD), which utilizes state-of-the-art security and scalability technologies to provide an end-to-end solution for big biomedical data analytics. The PHD platform is an open-source software framework that can be easily configured and deployed to any big data health project to store, organize, and process complex biomedical data sets, support real-time data analysis at both the individual level and the cohort level, and ensure participant privacy at every step. In addition to presenting the system, we i...
Motivation A major drawback of executing genomic applications on cloud computing facilities is th... more Motivation A major drawback of executing genomic applications on cloud computing facilities is the lack of tools to predict which instance type is the most appropriate, often resulting in an over- or under- matching of resources. Determining the right configuration before actually running the applications will save money and time. Here, we introduce Hummingbird, a tool for predicting performance of computing instances with varying memory and CPU on multiple cloud platforms. Results Our experiments on three major genomic data pipelines, including GATK HaplotypeCaller, GATK Mutect2 and ENCODE ATAC-seq, showed that Hummingbird was able to address applications in command line specified in JSON format or workflow description language (WDL) format, and accurately predicted the fastest, the cheapest and the most cost-efficient compute instances in an economic manner. Availability and implementation Hummingbird is available as an open source tool at: https://github.com/StanfordBioinformatic...
In this paper A mobile application has been developed that can fetch various information about a ... more In this paper A mobile application has been developed that can fetch various information about a car through various sensors interfaced with a microcontroller NodeMCU and the collected data uploaded to the cloud through raspberry pi server. NodeMCU sends signals to Raspberry pi to store the data in the cloud so that the mobile application developed may receive all these sensory signals and alert the passengers and driver. The proposed model also includes a feature to detect an accident and send the location of the accident to the user assigned person and local police station as a mobile message. In addition, the mobile application shall alert the driver to keep away from high speed vehicles coming from the rear side, present location of the car through google API, identify the road condition through pi camera interfacing and advise the upper speed limit, spray liquid nitrogen to reduce the temperature of tyres in the safe range of temperature, detect the driver status of drowsiness ...
This paper dispenses on the accord of the study and analysis of Electro Cardiogram Processing by ... more This paper dispenses on the accord of the study and analysis of Electro Cardiogram Processing by MATLAB tool effectively. Examination of the ECG signal implies on the generation of ECG signal which pertains to the waves that are produced by an electrical impulse or wave that travels through the heart. It estimates the heat rhythm as well as the rate. The work is allocated on MATLAB coding which is indeed instrumental to provide data to the patients or subjects without any physiological involvement. Through the graphical representation procured through MATLAB coding, the anatomy and physiology of cardio vascular exploration can be done. Further requisite and obligatory informations that are inevitable like heart attack, abnormal heart rhythms can be disclosed. Subjects can easily differentiate the original data obtained along with the graphs obtained which also provides coherent information about the exact transposition of their reports. Thus, working with MATLAB along with their sim...
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Historically, gold, unlike other payment channels, was employed to support trading acquisitions w... more Historically, gold, unlike other payment channels, was employed to support trading acquisitions worldwide. We forecast future gold prices based on twenty-two market variables using a machine learning technique. In order to analyze these data, one machine learning approach, random forest regression, was applied. Numerous states have kept and increased their gold reserves while being progressive and rich. In reality, central banks throughout the world keep precious metals like gold on hand to ensure foreign debt service in addition to stabilizing inflation. The primary goal of this research is to anticipate the increase and fall in routine gold rates, which will assist investors in deciding whether to purchase or sell gold. Logistics forecasting is critical to the fiscal performance of an organization. The secondary market is derived by examining the dataset including the previous year's gold price. There is concern that these high prices will not be sustainable and will fall desp...
Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. How... more Mass surveillance testing can help control outbreaks of infectious diseases such as COVID-19. However, diagnostic test shortages are prevalent globally and continue to occur in the US with the onset of new COVID-19 variants, demonstrating an unprecedented need for improving our current methods for mass surveillance testing. By targeting surveillance testing towards individuals who are most likely to be infected and, thus, increasing testing positivity rate (i.e., percent positive in the surveillance group), fewer tests are needed to capture the same number of positive cases. Here, we developed an Intelligent Testing Allocation (ITA) method by leveraging data from the CovIdentify study (6,765 participants) and the MyPHD study (8,580 participants), including smartwatch data from 1,265 individuals of whom 126 tested positive for COVID-19. Our rigorous model and parameter search uncovered the optimal time periods and aggregate metrics for monitoring continuous digital biomarkers to incr...
The large amount of biomedical data derived from wearable sensors, electronic health records, and... more The large amount of biomedical data derived from wearable sensors, electronic health records, and molecular profiling (e.g., genomics data) is rapidly transforming our healthcare systems. The increasing scale and scope of biomedical data not only is generating enormous opportunities for improving health outcomes but also raises new challenges ranging from data acquisition and storage to data analysis and utilization. To meet these challenges, we developed the Personal Health Dashboard (PHD), which utilizes state-of-the-art security and scalability technologies to provide an end-to-end solution for big biomedical data analytics. The PHD platform is an open-source software framework that can be easily configured and deployed to any big data health project to store, organize, and process complex biomedical data sets, support real-time data analysis at both the individual level and the cohort level, and ensure participant privacy at every step. In addition to presenting the system, we i...
Motivation A major drawback of executing genomic applications on cloud computing facilities is th... more Motivation A major drawback of executing genomic applications on cloud computing facilities is the lack of tools to predict which instance type is the most appropriate, often resulting in an over- or under- matching of resources. Determining the right configuration before actually running the applications will save money and time. Here, we introduce Hummingbird, a tool for predicting performance of computing instances with varying memory and CPU on multiple cloud platforms. Results Our experiments on three major genomic data pipelines, including GATK HaplotypeCaller, GATK Mutect2 and ENCODE ATAC-seq, showed that Hummingbird was able to address applications in command line specified in JSON format or workflow description language (WDL) format, and accurately predicted the fastest, the cheapest and the most cost-efficient compute instances in an economic manner. Availability and implementation Hummingbird is available as an open source tool at: https://github.com/StanfordBioinformatic...
In this paper A mobile application has been developed that can fetch various information about a ... more In this paper A mobile application has been developed that can fetch various information about a car through various sensors interfaced with a microcontroller NodeMCU and the collected data uploaded to the cloud through raspberry pi server. NodeMCU sends signals to Raspberry pi to store the data in the cloud so that the mobile application developed may receive all these sensory signals and alert the passengers and driver. The proposed model also includes a feature to detect an accident and send the location of the accident to the user assigned person and local police station as a mobile message. In addition, the mobile application shall alert the driver to keep away from high speed vehicles coming from the rear side, present location of the car through google API, identify the road condition through pi camera interfacing and advise the upper speed limit, spray liquid nitrogen to reduce the temperature of tyres in the safe range of temperature, detect the driver status of drowsiness ...
This paper dispenses on the accord of the study and analysis of Electro Cardiogram Processing by ... more This paper dispenses on the accord of the study and analysis of Electro Cardiogram Processing by MATLAB tool effectively. Examination of the ECG signal implies on the generation of ECG signal which pertains to the waves that are produced by an electrical impulse or wave that travels through the heart. It estimates the heat rhythm as well as the rate. The work is allocated on MATLAB coding which is indeed instrumental to provide data to the patients or subjects without any physiological involvement. Through the graphical representation procured through MATLAB coding, the anatomy and physiology of cardio vascular exploration can be done. Further requisite and obligatory informations that are inevitable like heart attack, abnormal heart rhythms can be disclosed. Subjects can easily differentiate the original data obtained along with the graphs obtained which also provides coherent information about the exact transposition of their reports. Thus, working with MATLAB along with their sim...
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Papers by Utsab Ray