U.S. Transportation Collection2019PDFTech ReportAbdel-Aty, Mohamed ACai, QingEluru, NaveenHasan, ... more U.S. Transportation Collection2019PDFTech ReportAbdel-Aty, Mohamed ACai, QingEluru, NaveenHasan, S.Chung, WhoibinRahman, SharikurGong, YaobangRahman, HasiburUniversity of Central Florida. Department of Civil and Environmental EngineeringFlorida. Department of TransportationUniversity of Central FloridaUnited StatesAdvanced traffic management systemsArterial highwaysDecision support systemsDynamic traffic assignmentExpresswaysFreewaysMicroscopic traffic flowTraffic simulationTravel timeIntegrated Active Traffic Management (IATM)Aimsun simulationMETANET modelBDV-24-977-22Final Deliverable, April 30, 2017-October 2019This project aimd at developing a decision support system (DSS) for Integrated Active Traffic Management (IATM) for both freeways/expressways and arterials/collectors. In order to achieve the objectives, the following tasks were performed. The research team first reviewed different traffic detection technologies to understand the output data characteristics and operation mechanisms. After initially checking data availability and roadway network, the Greater Downtown Orlando Metropolitan Area was selected as the study area. In the study area, the research team devoted great effort to collect different data sources to ensure sufficient data coverage on both freeways/expressways and arterials/collectors. The data sources included HERE, NPMRDS (National Performance Management Research Data Set), MVDS (Microwave Vehicle Detection System), AVI (Automatic Vehicle Identification), BlueTOAD, BlueMAC, etc. All data were processed to reflect traffic for the same segment at the same time and evaluated with the consideration of accuracy and availability. Fusion algorithms were developed to improve the data accuracy as well. The appropriate data were used to identify the critical roadways and segments which experienced serious traffic congestion and travel time unreliability. Around 600 miles roadways, with around 1,200 segments in total, were evaluated based on measures reflecting traffic efficiency and reliability. Two critical corridors (i.e., I-4 corridor in Downtown Orlando and SR-417 corridor in East Orlando) were selected for developing the DSS for IATM. By using Aimsun Next, the research team has developed a dynamic traffic assignment (DTA) simulation platform, involving multi-resolution modeling (MRM) framework. The platform is the largest DTA-based simulation network attempted in the United States. The microscopic simulation models were developed to test IATM control strategies. Based on the developed simulation platform, different IATM control strategies, including Variable Speed Limit (VSL), Queue Warning (QW), Ramp Metering (RM), and their combinations were tested under three different congestion levels on both corridors. Two METANET models were developed to predict traffic conditions. The DSS was developed for the IATM controls by balancing the traffic on both freeways/expressways and arterials/collectors. A total of 420 simulation runs were conducted to evaluate the developed DSS of IATM, and the generic rules of IATM controls were summarized for implementation. The results suggested that the developed DSS could successfully reduce traffic congestion and improve travel time reliability. It is intended that the results of the project would provide a solution to help operators select efficient and effective control strategies to simultaneously improve traffic conditions of freeways/expressways and arterials/collectors.105
Safety issues at school zones have been an important topic in the traffic safety field. This stud... more Safety issues at school zones have been an important topic in the traffic safety field. This study assesses the safety effects of different roadway countermeasure at school zones. Although several studies have evaluated the effectiveness of various traffic control devices (e.g., sign, flashing beacon), there is lack of studies proposing innovative operation and engineering countermeasures, which might have significant improvement of safety at school zones. In this study, the most crashâ€"prone school zone is identified based on crash rates in Orange and Seminole Counties in Florida. Afterward, a microsimulation network is built to evaluate different safety countermeasures. Three different countermeasures i.e., twoâ€"step speed reduction, decreasing the number of driveways, and replacing the twoâ€"way leftâ€"turn lane (TWLTL) with raised median are implemented in the microsimulation. Multiple surrogate safety measures are utilized as indicators for safety evaluation. The results show that both twoâ€"step speed reduction and decreasing driveway access significantly reduce crash risks compared with the base condition. Moreover, the combination of these two countermeasures outperform their individual effectiveness. On the other hand, for TWLTL to the raised median, the crash risk is higher than the base condition. The results of this study could help transportation planners and decision makers to understand the effect of these countermeasures prior to implementing them in the real field.
Spices are dried aromatic substances derived from plants and have demonstrated antimicrobial acti... more Spices are dried aromatic substances derived from plants and have demonstrated antimicrobial activity against pathogenic microorganisms. In the present study, a total of six spices turmeric (Curcuma longa), garlic (Allium sativum), black pepper (Piper nigrum), ginger (Zingiber officinale), clove (Syzygium aromaticum) and cinnamon (Cinnamomum verum) were evaluated for their antibacterial activity. Antibacterial activities of ethanol, propanol and water extracts were determined by agar well diffusion assay against previously isolated Klebsiella pneumoniae, Staphylococcus aureus from urine samples and Citrobacter spp. from throat swab samples. All spices examined in this study showed antibacterial activity in different types of extraction methods. Water, ethanol and propanol extracts exhibited anti-bacterial activity measured as zone of inhibition between 6 mm and 25 mm in diameter. Water extract of garlic (Allium sativum) showed the highest antibacterial activity (25mm) against clinic...
In state-of-the-art Pervasive Computing, it is envisioned that unlimited access to information wi... more In state-of-the-art Pervasive Computing, it is envisioned that unlimited access to information will be facilitated for anyone and anything. Wireless sensor networks will play a pivotal role in the stated vision. This reflects the phenomena where any situation can be sensed and analyzed anywhere. It makes heterogeneous context ubiquitous. Clustering context is one of the techniques to manage ubiquitous context information efficiently to maximize its potential. Logical-clustering is useful to share real-time context where sensors are physically distributed but logically clustered. This paper investigates the network performance of logical-clustering based on ns-3 simulations. In particular reliability, scalability, and reachability in terms of delay, jitter, and packet loss for the logically clustered network have been investigated. The performance study shows that jitter demonstrates 40 % and 44 % fluctuation for 200 % increase in the node per cluster and 100 % increase in the cluster size respectively. Packet loss exhibits only 18 % increase for 83 % increase in the packet flow-rate.
IMPORTANCE Trainees routinely participate in colonoscopy procedures, yet whether their involvemen... more IMPORTANCE Trainees routinely participate in colonoscopy procedures, yet whether their involvement is positively or negatively associated with procedural quality is unknown because prior studies involved small number of trainees and/or supervisors, lacked generalizability, and/or failed to adjust for potential confounders. OBJECTIVE To assess the association between trainee participation and colonoscopy quality metrics. DESIGN, SETTING, AND PARTICIPANTS This multicenter population-based cohort study was conducted at 21 academic and community hospitals between April 1, 2017, and October 31, 2018, among consecutive adult patients undergoing colonoscopy. Procedures performed by endoscopists who did not supervise trainees were excluded. Statistical analysis was performed from April 3, 2017, to October 31, 2018. EXPOSURE Participation by a trainee, defined as a resident or fellow enrolled in a gastroenterology or general surgery training program. MAIN OUTCOMES AND MEASURES The primary outcome was the adenoma detection rate (ADR), and secondary outcomes were sessile serrated polyp detection rate (ssPDR), polyp detection rate (PDR), cecal intubation rate (CIR), and perforation rate. RESULTS A total of 35 499 colonoscopies (18 989 women [53.5%]; mean [SD] patient age, 60.0 [14.1] years) were performed by 71 physicians (mean [SD] time in practice, 14.0 [9.3] years); 5941 colonoscopies (16.7%) involved trainees. There were no significant differences in the ADR (26.4% vs 27.3%; P = .19), CIR (96.7% vs 97.2%; P = .07), and perforation rate (0.05% vs 0.06%; P = .82) when trainees participated vs when they did not participate, whereas the the ssPDR (4.4% vs 5.2%;
Detailed analysis of the satellite derived water vapour for a five years period (1995-1999) prior... more Detailed analysis of the satellite derived water vapour for a five years period (1995-1999) prior to and during southwest monsoon is done over the Indian subcontinent and the adjoining seas. Three layer (1000 hPa – 700 hPa, 700 hPa –500 hPa and 500 hPa -300 hPa) and total moisture data available from NOAA/TOVS satellite are used for the analysis. These data are used to study the northward propagating intraseasonal oscillations in the tropical Indian Ocean during the summer monsoon season. Results indicate the presence of intraseasonal oscillations in the middle (700 hPa – 500 hPa) and the upper level (500 hPa – 300 hPa) water vapour. Wavelet analysis is applied to study the characteristics and time evolution of the intraseasonal oscillations especially over East Arabian Sea (EAS). Intraseasonal oscillations with periods ranging from 8-15 days, 15-30 and 30-60 days are seen over EAS. Heavy rainfall events over west coast of peninsular India are studied before...
While writing Bengali using English keyboard, users often make spelling mistakes. The accuracy of... more While writing Bengali using English keyboard, users often make spelling mistakes. The accuracy of any Bengali spell checker or paragraph correction module largely depends on the kind of error dataset it is based on. Manual generation of such error dataset is a cumbersome process. In this research, We present an algorithm for automatic misspelled Bengali word generation from correct word through analyzing Bengali writing pattern using QWERTY layout English keyboard. As part of our analysis, we have formed a list of most commonly used Bengali words, phonetically similar replaceable clusters, frequently mispressed replaceable clusters, frequently mispressed insertion prone clusters and some rules for Juktakkhar (constant letter clusters) handling while generating errors.
2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART), 2021
Due to the huge explanation of artificial intelligence, machine learning technology is being used... more Due to the huge explanation of artificial intelligence, machine learning technology is being used in various areas of our day-to-day life. In Dhaka city, there are lots of Restaurants. Sometimes many of us face a scenario where we go to a restaurant and order some food but the food is not that good or the price of the food is very high as compared to other restaurants. Apart from this, another major problem is the location of the restaurant. We cannot find the best restaurants around us based on our preferences. This research proposed a model by using a machine learning algorithm that will be able to suggest a suitable restaurant based on the user’s criteria. We have collected Dhaka city’s restaurant’s data from various websites, then we have used Weight-based score calculation and cosine similarity matrix to build our machine learning model. This recommendation system will also suggest similar restaurants based on the user’s selected restaurants.
Semi-supervised clustering aims to improve clustering performance by considering user-provided si... more Semi-supervised clustering aims to improve clustering performance by considering user-provided side information in the form of pairwise constraints. We study the active learning problem of selecting must-link and cannot-link pairwise constraints for semi-supervised clustering. We consider active learning in an iterative framework; each iteration queries are selected based on the current clustering outcome and constraints available. We use the neighborhood framework where the pairwise points having the must-link belong to the same neigborhood and cannot-link pairwise points belong to the different neighborhood. If two points belong to the same neighborhood then they belong to the same cluster and viceversa. We will use the Glass Identification Data Set from the UCI machine learning repositories and investigate the improvement in clustering time using the Incremental Clustering.
Safety issues in school zone areas have been one of the most important topics in the traffic safe... more Safety issues in school zone areas have been one of the most important topics in the traffic safety field. This research project assesses the safety effects of different roadway countermeasures in school zone areas. Although many studies have evaluated the effectiveness of various traffic control devices (e.g., sign, flashing beacon, speed monitoring display), there is a lack of studies exploring different roadway countermeasures that might have significant impacts on the school zone safety. In this research project, the most crash-prone school zone was identified in Orange and Seminole Counties, Florida, based on crash rate, which is defined as crash per thousand daily vehicle miles traveled. The results showed that Westridge Middle and Sadler Elementary schools were the top two crash-prone school zones. Afterward, a microsimulation network was built in VISSIM to test different roadway countermeasures in the school zones. Before applying different countermeasures, the network was c...
Journal of Pre-College Engineering Education Research (J-PEER), 2021
Despite emphasis on authentic science, technology, engineering, mathematics, and computer science... more Despite emphasis on authentic science, technology, engineering, mathematics, and computer science (STEM+CS) projects in classrooms, research continues to demonstrate opportunity gaps in learning STEM+CS for students with disabilities. This study investigates how teachers verbally support students in two differently tracked classrooms to engage in engineering lessons that integrate science and computer science. Specifically, this study explores how the same elementary teachers both implicitly and explicitly support students across two classroom contexts, one class section with a larger proportion of students who were tracked into accelerated mathematics and another class section with a larger proportion of students with individualized educational plans (IEPs). Transcripts of whole-class discussion were analyzed for interdisciplinary instructional moves in which teachers verbally supported the integration of disciplines to help students to engage in interdisciplinary activities. Findings reveal that all of the interdisciplinary instructional moves were implicit for the class section with a large proportion of students in advanced mathematics while most were explicit for the class section with students with IEPs, and that most of the interdisciplinary instructional moves were added by the teachers rather than planned in the curriculum materials. Most commonly, teachers added interdisciplinary instructional moves between computer science and engineering. Implications of this study include recommendations for support that teachers need to engage in the important, but challenging, work of integrating science and computer science practices through engineering lessons within elementary science classrooms. This study adds to a growing understanding of equitable learning opportunities in interdisciplinary learning through engineering for elementary students.
Human vision is an important factor in the areas of image processing. Research has been done for ... more Human vision is an important factor in the areas of image processing. Research has been done for years to make automatic image handling but still human intervention cannot be denied and thus better human intervention is necessary. Two most important points are required to improve human vision which is light and pigment. Gamma encoder is the one which helps to improve the properties of human vision and thus to maintain visual quality gamma encrypting is necessary. It is to mention that all through the computer graphics RGB (Red, Green, and Blue) pigment space is vastly used. Moreover, for computer graphics RGB pigment space is called the most established choice to acquire desired pigment. RGB pigment space has a great effort on simplifying the design and architecture of a system. However, RGB struggles to deal effectively for the images those belong to the real- world. Images are captured using cameras, videos and other devices using different magnifications. In most cases during pro...
Safety issues at school zone areas have been one of the most important topics in the traffic safe... more Safety issues at school zone areas have been one of the most important topics in the traffic safety field. Although many studies have evaluated the effectiveness of various traffic control devices (e.g., sign, flashing beacon, speed monitoring display), there is a lack of studies exploring different roadway countermeasures and the relationship between school-related factors and crashes. In this study, the most crash-prone school zone was identified in Orange and Seminole Counties, Florida, based on crash rate. Afterward, a microsimulation network was built in VISSIM environment to test different roadway countermeasures in the school zones. Three different countermeasures: twostep speed reduction (TSR), decreasing the number of driveways (DD), and replacing the two-way left-turn lane (TWLTL) to the raised median (RM) were implemented in the microsimulation. Three surrogate safety measures: (1) time exposed time to collision (TET), (2) time integrated time to collision (TIT) and (3) time exposed rear-end crash risk index (TERCRI) were utilized in this study as indicators for safety evaluation. The higher value of surrogate safety measures indicates higher crash risk. The results showed that both TSR and DD reduced TET, TIT and TERCRI values significantly compare to the base condition. Moreover, the combination of TSR and DD countermeasures outperformed their individual effectiveness. The One-way ANOVA analysis showed that all the sub-scenarios were significantly different from each other. Sensitivity analysis result has proved that all the sub-scenarios in TSR and DD reduced TET, TIT and TERCRI values significantly for different value of TTC threshold. On the other hand, for converting the TWLTL to RM, the crash risk was higher than the base condition because of the turning movements of vehicle. The results of this study could help transportation planners and decision makers to understand the effect of these countermeasures to improve safety at school zones.
This paper examines the safety benefit of connected vehicles (CV) and the connected vehicles lowe... more This paper examines the safety benefit of connected vehicles (CV) and the connected vehicles lower level automation (CVLLA) on arterials’ using micro-simulation. Examining the lower level of automation is more realistic in the foreseeable future. This study considered two automated features: automated braking and lane keeping assistance which are available in the market. Driving behaviors of CV and CVLLA were proposed by considering car following models that approximate the decision processes of CV and CVLLA using C++ programming interface in VISSIM. The safety impact of both segment and intersection crash risks were quantified under various market penetration rates (MPRs) of CV and CVLLA based on surrogate safety assessment techniques. Two surrogate measures of safety: Time Exposed Time-to-Collision (TET) and Time Integrated Time-to-Collision (TIT) were considered to explore the segment crash risk and the results suggest that both CV and CVLLA reduce segment crash risk significantly compared to the baseline scenario. Furthermore, the intersection crash risk was evaluated through the number of conflicts extracted from microsimulation using the Surrogate Safety Assessment Model (SSAM). Towards that end, a binary logistic regression model was developed to quantify the crash risk in terms of observed conflicts obtained in the intersection influence areas. The logistic regression results clearly showed that both CV and CVLLA have lower intersection crash risks compared to the base scenario (non-CV scenario). Finally, in terms of both segment and intersection crash risks, CVLLA significantly outperformed CV when MPRs were equal or higher than 60%.
Internet of Things (IoT) is on the verge of experiencing a paradigm shift, the focus of which is ... more Internet of Things (IoT) is on the verge of experiencing a paradigm shift, the focus of which is the integration of people, services, context information, and things in the Connected Society, thus ...
Transportation Research Part C: Emerging Technologies, 2021
Abstract Connected and automated vehicles (CAVs) are expected to improve both traffic safety and ... more Abstract Connected and automated vehicles (CAVs) are expected to improve both traffic safety and efficiency by reducing the human driver errors. Recently, many researchers have focused on the simulation-based studies in order to evaluate the benefits of CAVs due to the lack of real-world data. However, none of the previous studies have attempted to differentiate the benefits of CAVs over automated vehicles (AVs) by incorporating multiple preceding vehicle information (i.e., acceleration, position, etc.). This paper aims to fill the existing gap by utilizing separate car-following models for both CAVs and AVs in order to approximate their driving behavior in the Aimsun Next simulation platform. Additionally, a different car-following model is used for the connected vehicles (CVs) without automation by addressing the human driver compliance factor. This study also utilizes mixed penetration of CAV and CV with no automation. A well calibrated and validated simulation testbed is developed for SR417 in Orlando, Florida which is the base scenario in this study. To this end, the impact of CAVs, AVs, and CVs are evaluated based on both traffic efficiency (i.e., travel time) and safety (i.e., traffic conflicts) under various market penetration rates (MPRs). The traffic efficiency results show that travel time is significantly reduced for any MPRs of CAVs, AVs, and the mixture of CVs and CAVs compared to the base scenario. A generalized estimating equation (GEE) model is developed to quantify the travel time improvement for CAVs, AVs, and the mixture of CVs and CAVs. The results suggest at least 20% penetration is required for CAVs to get travel time improvement while 40% penetration is needed for AVs. Also, CAV significantly outperforms AV for the same MPRs. For the safety assessment, traffic conflicts are estimated by using different surrogate measures i.e., time-to-collision (TTC) and time exposed time-to-collision (TET). The results imply that crash risk is significantly reduced for CAVs, AVs, and the mixture of CVs and CAVs scenarios compared to the base condition. A Bayesian zero-inflated negative binomial model is developed in order to model the number of traffic conflicts as a function of MPRs of CAVs, AVs, mixture of CVs and CAVs, and traffic parameters. The results confirm that CAVs are more efficient in reducing crash risk compared to AVs for the same MPR. The mix penetration rate of CV (60%) and CAV (20%) shows almost similar reduction of crash risk with the 80% MPR of AV. Also, crash risk analysis based on different vehicle types shows that CAVs driving behavior is safer compared to the AVs. Finally, the results of this study indicate a significant improvement of both traffic efficiency and safety by implementing CAV with multivehicle communication system on the freeway segments.
U.S. Transportation Collection2019PDFTech ReportAbdel-Aty, Mohamed ACai, QingEluru, NaveenHasan, ... more U.S. Transportation Collection2019PDFTech ReportAbdel-Aty, Mohamed ACai, QingEluru, NaveenHasan, S.Chung, WhoibinRahman, SharikurGong, YaobangRahman, HasiburUniversity of Central Florida. Department of Civil and Environmental EngineeringFlorida. Department of TransportationUniversity of Central FloridaUnited StatesAdvanced traffic management systemsArterial highwaysDecision support systemsDynamic traffic assignmentExpresswaysFreewaysMicroscopic traffic flowTraffic simulationTravel timeIntegrated Active Traffic Management (IATM)Aimsun simulationMETANET modelBDV-24-977-22Final Deliverable, April 30, 2017-October 2019This project aimd at developing a decision support system (DSS) for Integrated Active Traffic Management (IATM) for both freeways/expressways and arterials/collectors. In order to achieve the objectives, the following tasks were performed. The research team first reviewed different traffic detection technologies to understand the output data characteristics and operation mechanisms. After initially checking data availability and roadway network, the Greater Downtown Orlando Metropolitan Area was selected as the study area. In the study area, the research team devoted great effort to collect different data sources to ensure sufficient data coverage on both freeways/expressways and arterials/collectors. The data sources included HERE, NPMRDS (National Performance Management Research Data Set), MVDS (Microwave Vehicle Detection System), AVI (Automatic Vehicle Identification), BlueTOAD, BlueMAC, etc. All data were processed to reflect traffic for the same segment at the same time and evaluated with the consideration of accuracy and availability. Fusion algorithms were developed to improve the data accuracy as well. The appropriate data were used to identify the critical roadways and segments which experienced serious traffic congestion and travel time unreliability. Around 600 miles roadways, with around 1,200 segments in total, were evaluated based on measures reflecting traffic efficiency and reliability. Two critical corridors (i.e., I-4 corridor in Downtown Orlando and SR-417 corridor in East Orlando) were selected for developing the DSS for IATM. By using Aimsun Next, the research team has developed a dynamic traffic assignment (DTA) simulation platform, involving multi-resolution modeling (MRM) framework. The platform is the largest DTA-based simulation network attempted in the United States. The microscopic simulation models were developed to test IATM control strategies. Based on the developed simulation platform, different IATM control strategies, including Variable Speed Limit (VSL), Queue Warning (QW), Ramp Metering (RM), and their combinations were tested under three different congestion levels on both corridors. Two METANET models were developed to predict traffic conditions. The DSS was developed for the IATM controls by balancing the traffic on both freeways/expressways and arterials/collectors. A total of 420 simulation runs were conducted to evaluate the developed DSS of IATM, and the generic rules of IATM controls were summarized for implementation. The results suggested that the developed DSS could successfully reduce traffic congestion and improve travel time reliability. It is intended that the results of the project would provide a solution to help operators select efficient and effective control strategies to simultaneously improve traffic conditions of freeways/expressways and arterials/collectors.105
Safety issues at school zones have been an important topic in the traffic safety field. This stud... more Safety issues at school zones have been an important topic in the traffic safety field. This study assesses the safety effects of different roadway countermeasure at school zones. Although several studies have evaluated the effectiveness of various traffic control devices (e.g., sign, flashing beacon), there is lack of studies proposing innovative operation and engineering countermeasures, which might have significant improvement of safety at school zones. In this study, the most crashâ€"prone school zone is identified based on crash rates in Orange and Seminole Counties in Florida. Afterward, a microsimulation network is built to evaluate different safety countermeasures. Three different countermeasures i.e., twoâ€"step speed reduction, decreasing the number of driveways, and replacing the twoâ€"way leftâ€"turn lane (TWLTL) with raised median are implemented in the microsimulation. Multiple surrogate safety measures are utilized as indicators for safety evaluation. The results show that both twoâ€"step speed reduction and decreasing driveway access significantly reduce crash risks compared with the base condition. Moreover, the combination of these two countermeasures outperform their individual effectiveness. On the other hand, for TWLTL to the raised median, the crash risk is higher than the base condition. The results of this study could help transportation planners and decision makers to understand the effect of these countermeasures prior to implementing them in the real field.
Spices are dried aromatic substances derived from plants and have demonstrated antimicrobial acti... more Spices are dried aromatic substances derived from plants and have demonstrated antimicrobial activity against pathogenic microorganisms. In the present study, a total of six spices turmeric (Curcuma longa), garlic (Allium sativum), black pepper (Piper nigrum), ginger (Zingiber officinale), clove (Syzygium aromaticum) and cinnamon (Cinnamomum verum) were evaluated for their antibacterial activity. Antibacterial activities of ethanol, propanol and water extracts were determined by agar well diffusion assay against previously isolated Klebsiella pneumoniae, Staphylococcus aureus from urine samples and Citrobacter spp. from throat swab samples. All spices examined in this study showed antibacterial activity in different types of extraction methods. Water, ethanol and propanol extracts exhibited anti-bacterial activity measured as zone of inhibition between 6 mm and 25 mm in diameter. Water extract of garlic (Allium sativum) showed the highest antibacterial activity (25mm) against clinic...
In state-of-the-art Pervasive Computing, it is envisioned that unlimited access to information wi... more In state-of-the-art Pervasive Computing, it is envisioned that unlimited access to information will be facilitated for anyone and anything. Wireless sensor networks will play a pivotal role in the stated vision. This reflects the phenomena where any situation can be sensed and analyzed anywhere. It makes heterogeneous context ubiquitous. Clustering context is one of the techniques to manage ubiquitous context information efficiently to maximize its potential. Logical-clustering is useful to share real-time context where sensors are physically distributed but logically clustered. This paper investigates the network performance of logical-clustering based on ns-3 simulations. In particular reliability, scalability, and reachability in terms of delay, jitter, and packet loss for the logically clustered network have been investigated. The performance study shows that jitter demonstrates 40 % and 44 % fluctuation for 200 % increase in the node per cluster and 100 % increase in the cluster size respectively. Packet loss exhibits only 18 % increase for 83 % increase in the packet flow-rate.
IMPORTANCE Trainees routinely participate in colonoscopy procedures, yet whether their involvemen... more IMPORTANCE Trainees routinely participate in colonoscopy procedures, yet whether their involvement is positively or negatively associated with procedural quality is unknown because prior studies involved small number of trainees and/or supervisors, lacked generalizability, and/or failed to adjust for potential confounders. OBJECTIVE To assess the association between trainee participation and colonoscopy quality metrics. DESIGN, SETTING, AND PARTICIPANTS This multicenter population-based cohort study was conducted at 21 academic and community hospitals between April 1, 2017, and October 31, 2018, among consecutive adult patients undergoing colonoscopy. Procedures performed by endoscopists who did not supervise trainees were excluded. Statistical analysis was performed from April 3, 2017, to October 31, 2018. EXPOSURE Participation by a trainee, defined as a resident or fellow enrolled in a gastroenterology or general surgery training program. MAIN OUTCOMES AND MEASURES The primary outcome was the adenoma detection rate (ADR), and secondary outcomes were sessile serrated polyp detection rate (ssPDR), polyp detection rate (PDR), cecal intubation rate (CIR), and perforation rate. RESULTS A total of 35 499 colonoscopies (18 989 women [53.5%]; mean [SD] patient age, 60.0 [14.1] years) were performed by 71 physicians (mean [SD] time in practice, 14.0 [9.3] years); 5941 colonoscopies (16.7%) involved trainees. There were no significant differences in the ADR (26.4% vs 27.3%; P = .19), CIR (96.7% vs 97.2%; P = .07), and perforation rate (0.05% vs 0.06%; P = .82) when trainees participated vs when they did not participate, whereas the the ssPDR (4.4% vs 5.2%;
Detailed analysis of the satellite derived water vapour for a five years period (1995-1999) prior... more Detailed analysis of the satellite derived water vapour for a five years period (1995-1999) prior to and during southwest monsoon is done over the Indian subcontinent and the adjoining seas. Three layer (1000 hPa – 700 hPa, 700 hPa –500 hPa and 500 hPa -300 hPa) and total moisture data available from NOAA/TOVS satellite are used for the analysis. These data are used to study the northward propagating intraseasonal oscillations in the tropical Indian Ocean during the summer monsoon season. Results indicate the presence of intraseasonal oscillations in the middle (700 hPa – 500 hPa) and the upper level (500 hPa – 300 hPa) water vapour. Wavelet analysis is applied to study the characteristics and time evolution of the intraseasonal oscillations especially over East Arabian Sea (EAS). Intraseasonal oscillations with periods ranging from 8-15 days, 15-30 and 30-60 days are seen over EAS. Heavy rainfall events over west coast of peninsular India are studied before...
While writing Bengali using English keyboard, users often make spelling mistakes. The accuracy of... more While writing Bengali using English keyboard, users often make spelling mistakes. The accuracy of any Bengali spell checker or paragraph correction module largely depends on the kind of error dataset it is based on. Manual generation of such error dataset is a cumbersome process. In this research, We present an algorithm for automatic misspelled Bengali word generation from correct word through analyzing Bengali writing pattern using QWERTY layout English keyboard. As part of our analysis, we have formed a list of most commonly used Bengali words, phonetically similar replaceable clusters, frequently mispressed replaceable clusters, frequently mispressed insertion prone clusters and some rules for Juktakkhar (constant letter clusters) handling while generating errors.
2021 10th International Conference on System Modeling & Advancement in Research Trends (SMART), 2021
Due to the huge explanation of artificial intelligence, machine learning technology is being used... more Due to the huge explanation of artificial intelligence, machine learning technology is being used in various areas of our day-to-day life. In Dhaka city, there are lots of Restaurants. Sometimes many of us face a scenario where we go to a restaurant and order some food but the food is not that good or the price of the food is very high as compared to other restaurants. Apart from this, another major problem is the location of the restaurant. We cannot find the best restaurants around us based on our preferences. This research proposed a model by using a machine learning algorithm that will be able to suggest a suitable restaurant based on the user’s criteria. We have collected Dhaka city’s restaurant’s data from various websites, then we have used Weight-based score calculation and cosine similarity matrix to build our machine learning model. This recommendation system will also suggest similar restaurants based on the user’s selected restaurants.
Semi-supervised clustering aims to improve clustering performance by considering user-provided si... more Semi-supervised clustering aims to improve clustering performance by considering user-provided side information in the form of pairwise constraints. We study the active learning problem of selecting must-link and cannot-link pairwise constraints for semi-supervised clustering. We consider active learning in an iterative framework; each iteration queries are selected based on the current clustering outcome and constraints available. We use the neighborhood framework where the pairwise points having the must-link belong to the same neigborhood and cannot-link pairwise points belong to the different neighborhood. If two points belong to the same neighborhood then they belong to the same cluster and viceversa. We will use the Glass Identification Data Set from the UCI machine learning repositories and investigate the improvement in clustering time using the Incremental Clustering.
Safety issues in school zone areas have been one of the most important topics in the traffic safe... more Safety issues in school zone areas have been one of the most important topics in the traffic safety field. This research project assesses the safety effects of different roadway countermeasures in school zone areas. Although many studies have evaluated the effectiveness of various traffic control devices (e.g., sign, flashing beacon, speed monitoring display), there is a lack of studies exploring different roadway countermeasures that might have significant impacts on the school zone safety. In this research project, the most crash-prone school zone was identified in Orange and Seminole Counties, Florida, based on crash rate, which is defined as crash per thousand daily vehicle miles traveled. The results showed that Westridge Middle and Sadler Elementary schools were the top two crash-prone school zones. Afterward, a microsimulation network was built in VISSIM to test different roadway countermeasures in the school zones. Before applying different countermeasures, the network was c...
Journal of Pre-College Engineering Education Research (J-PEER), 2021
Despite emphasis on authentic science, technology, engineering, mathematics, and computer science... more Despite emphasis on authentic science, technology, engineering, mathematics, and computer science (STEM+CS) projects in classrooms, research continues to demonstrate opportunity gaps in learning STEM+CS for students with disabilities. This study investigates how teachers verbally support students in two differently tracked classrooms to engage in engineering lessons that integrate science and computer science. Specifically, this study explores how the same elementary teachers both implicitly and explicitly support students across two classroom contexts, one class section with a larger proportion of students who were tracked into accelerated mathematics and another class section with a larger proportion of students with individualized educational plans (IEPs). Transcripts of whole-class discussion were analyzed for interdisciplinary instructional moves in which teachers verbally supported the integration of disciplines to help students to engage in interdisciplinary activities. Findings reveal that all of the interdisciplinary instructional moves were implicit for the class section with a large proportion of students in advanced mathematics while most were explicit for the class section with students with IEPs, and that most of the interdisciplinary instructional moves were added by the teachers rather than planned in the curriculum materials. Most commonly, teachers added interdisciplinary instructional moves between computer science and engineering. Implications of this study include recommendations for support that teachers need to engage in the important, but challenging, work of integrating science and computer science practices through engineering lessons within elementary science classrooms. This study adds to a growing understanding of equitable learning opportunities in interdisciplinary learning through engineering for elementary students.
Human vision is an important factor in the areas of image processing. Research has been done for ... more Human vision is an important factor in the areas of image processing. Research has been done for years to make automatic image handling but still human intervention cannot be denied and thus better human intervention is necessary. Two most important points are required to improve human vision which is light and pigment. Gamma encoder is the one which helps to improve the properties of human vision and thus to maintain visual quality gamma encrypting is necessary. It is to mention that all through the computer graphics RGB (Red, Green, and Blue) pigment space is vastly used. Moreover, for computer graphics RGB pigment space is called the most established choice to acquire desired pigment. RGB pigment space has a great effort on simplifying the design and architecture of a system. However, RGB struggles to deal effectively for the images those belong to the real- world. Images are captured using cameras, videos and other devices using different magnifications. In most cases during pro...
Safety issues at school zone areas have been one of the most important topics in the traffic safe... more Safety issues at school zone areas have been one of the most important topics in the traffic safety field. Although many studies have evaluated the effectiveness of various traffic control devices (e.g., sign, flashing beacon, speed monitoring display), there is a lack of studies exploring different roadway countermeasures and the relationship between school-related factors and crashes. In this study, the most crash-prone school zone was identified in Orange and Seminole Counties, Florida, based on crash rate. Afterward, a microsimulation network was built in VISSIM environment to test different roadway countermeasures in the school zones. Three different countermeasures: twostep speed reduction (TSR), decreasing the number of driveways (DD), and replacing the two-way left-turn lane (TWLTL) to the raised median (RM) were implemented in the microsimulation. Three surrogate safety measures: (1) time exposed time to collision (TET), (2) time integrated time to collision (TIT) and (3) time exposed rear-end crash risk index (TERCRI) were utilized in this study as indicators for safety evaluation. The higher value of surrogate safety measures indicates higher crash risk. The results showed that both TSR and DD reduced TET, TIT and TERCRI values significantly compare to the base condition. Moreover, the combination of TSR and DD countermeasures outperformed their individual effectiveness. The One-way ANOVA analysis showed that all the sub-scenarios were significantly different from each other. Sensitivity analysis result has proved that all the sub-scenarios in TSR and DD reduced TET, TIT and TERCRI values significantly for different value of TTC threshold. On the other hand, for converting the TWLTL to RM, the crash risk was higher than the base condition because of the turning movements of vehicle. The results of this study could help transportation planners and decision makers to understand the effect of these countermeasures to improve safety at school zones.
This paper examines the safety benefit of connected vehicles (CV) and the connected vehicles lowe... more This paper examines the safety benefit of connected vehicles (CV) and the connected vehicles lower level automation (CVLLA) on arterials’ using micro-simulation. Examining the lower level of automation is more realistic in the foreseeable future. This study considered two automated features: automated braking and lane keeping assistance which are available in the market. Driving behaviors of CV and CVLLA were proposed by considering car following models that approximate the decision processes of CV and CVLLA using C++ programming interface in VISSIM. The safety impact of both segment and intersection crash risks were quantified under various market penetration rates (MPRs) of CV and CVLLA based on surrogate safety assessment techniques. Two surrogate measures of safety: Time Exposed Time-to-Collision (TET) and Time Integrated Time-to-Collision (TIT) were considered to explore the segment crash risk and the results suggest that both CV and CVLLA reduce segment crash risk significantly compared to the baseline scenario. Furthermore, the intersection crash risk was evaluated through the number of conflicts extracted from microsimulation using the Surrogate Safety Assessment Model (SSAM). Towards that end, a binary logistic regression model was developed to quantify the crash risk in terms of observed conflicts obtained in the intersection influence areas. The logistic regression results clearly showed that both CV and CVLLA have lower intersection crash risks compared to the base scenario (non-CV scenario). Finally, in terms of both segment and intersection crash risks, CVLLA significantly outperformed CV when MPRs were equal or higher than 60%.
Internet of Things (IoT) is on the verge of experiencing a paradigm shift, the focus of which is ... more Internet of Things (IoT) is on the verge of experiencing a paradigm shift, the focus of which is the integration of people, services, context information, and things in the Connected Society, thus ...
Transportation Research Part C: Emerging Technologies, 2021
Abstract Connected and automated vehicles (CAVs) are expected to improve both traffic safety and ... more Abstract Connected and automated vehicles (CAVs) are expected to improve both traffic safety and efficiency by reducing the human driver errors. Recently, many researchers have focused on the simulation-based studies in order to evaluate the benefits of CAVs due to the lack of real-world data. However, none of the previous studies have attempted to differentiate the benefits of CAVs over automated vehicles (AVs) by incorporating multiple preceding vehicle information (i.e., acceleration, position, etc.). This paper aims to fill the existing gap by utilizing separate car-following models for both CAVs and AVs in order to approximate their driving behavior in the Aimsun Next simulation platform. Additionally, a different car-following model is used for the connected vehicles (CVs) without automation by addressing the human driver compliance factor. This study also utilizes mixed penetration of CAV and CV with no automation. A well calibrated and validated simulation testbed is developed for SR417 in Orlando, Florida which is the base scenario in this study. To this end, the impact of CAVs, AVs, and CVs are evaluated based on both traffic efficiency (i.e., travel time) and safety (i.e., traffic conflicts) under various market penetration rates (MPRs). The traffic efficiency results show that travel time is significantly reduced for any MPRs of CAVs, AVs, and the mixture of CVs and CAVs compared to the base scenario. A generalized estimating equation (GEE) model is developed to quantify the travel time improvement for CAVs, AVs, and the mixture of CVs and CAVs. The results suggest at least 20% penetration is required for CAVs to get travel time improvement while 40% penetration is needed for AVs. Also, CAV significantly outperforms AV for the same MPRs. For the safety assessment, traffic conflicts are estimated by using different surrogate measures i.e., time-to-collision (TTC) and time exposed time-to-collision (TET). The results imply that crash risk is significantly reduced for CAVs, AVs, and the mixture of CVs and CAVs scenarios compared to the base condition. A Bayesian zero-inflated negative binomial model is developed in order to model the number of traffic conflicts as a function of MPRs of CAVs, AVs, mixture of CVs and CAVs, and traffic parameters. The results confirm that CAVs are more efficient in reducing crash risk compared to AVs for the same MPR. The mix penetration rate of CV (60%) and CAV (20%) shows almost similar reduction of crash risk with the 80% MPR of AV. Also, crash risk analysis based on different vehicle types shows that CAVs driving behavior is safer compared to the AVs. Finally, the results of this study indicate a significant improvement of both traffic efficiency and safety by implementing CAV with multivehicle communication system on the freeway segments.
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Papers by Hasibur Rahman