Improving Cell Phone Based Gait Identification with Optimal Response Time Using Cloudlet Infrastructure

Author(s):  
Thang Hoang ◽  
Viet Vo ◽  
Chuyen Luong ◽  
Son Do ◽  
Deokjai Choi
Author(s):  
Yalda Ebadi ◽  
Donald L. Fisher ◽  
Shannon C. Roberts

Distraction is one of the main causes of traffic crashes. The effect of cell phones, a major contributor to cognitive distraction, on response time has tested in many simulator studies. Response time is not the only driving skill affected by cell phone conversations, however. Specifically, it is known that cell phone usage contributes to a reduction in hazard anticipation skills at intersections, and there are many other scenarios where cell phone conversations could have a detrimental effect. The objective of this study is to determine whether cognitive distractions associated with cell phone use affect hazard anticipation, not only at intersections but also in other scenarios which contain latent hazards. Twenty-four drivers navigated 18 scenarios on a driving simulator twice, with their eye movements continuously monitored. During one drive, participants performed a hands-free mock cell phone task while driving; on the other drive, they navigated through the virtual world without any additional tasks apart from the primary task of driving. The scenarios were classified into two types: intersection and non-intersection. Using a logistic regression model within the framework of generalized estimation equations, it was determined that the proportion of anticipatory glances toward potential hazards was reduced significantly for all scenarios when drivers were engaged in a mock cell phone task. Perhaps the most disturbing finding is that this was true both at work zones and at marked midblock crosswalks, scenarios which often endanger vulnerable road users. In summary, the study found a negative effect of cognitive distraction on latent hazard anticipation.


1995 ◽  
Vol 05 (03) ◽  
pp. 451-460
Author(s):  
I. W. CHAN ◽  
F. CHOI

We present a simple systolic algorithm for implementing dictionary machine based on the VLSI technology. Our design makes use of a dynamic. global tree rebalancing scheme to attain high system throughput. Our scheme is simple to implement and requires low sophistication in the design of processing nodes. Results from analysis and simulation show that our algorithm has optimal response time and achieves an average latency close to 1. This represents a significant improvement over many of the previous designs. Unlike most parallel dictionary machines reported in the literature, our approach requires no compression operations.


2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Ling Hsuan Huang ◽  
Yu-Ni Ho ◽  
Ming-Ta Tsai ◽  
Wei-Ting Wu ◽  
Fu-Jen Cheng

Ambulance response time is a prognostic factor for out-of-hospital cardiac arrest (OHCA), but the impact of ambulance response time under different situations remains unclear. We evaluated the threshold of ambulance response time for predicting survival to hospital discharge for patients with OHCA. A retrospective observational analysis was conducted using the emergency medical service (EMS) database (January 2015 to December 2019). Prehospital factors, underlying diseases, and OHCA outcomes were assessed. Receiver operating characteristic (ROC) curve analysis with Youden Index was performed to calculate optimal cut-off values for ambulance response time that predicted survival to hospital discharge. In all, 6742 cases of adult OHCA were analyzed. After adjustment for confounding factors, age (odds ratio [OR] = 0.983, 95% confidence interval [CI]: 0.975–0.992, p < 0.001 ), witness (OR = 3.022, 95% CI: 2.014–4.534, p < 0.001 ), public location (OR = 2.797, 95% CI: 2.062–3.793, p < 0.001 ), bystander cardiopulmonary resuscitation (CPR, OR = 1.363, 95% CI: 1.009–1.841, p = 0.044 ), EMT-paramedic response (EMT-P, OR = 1.713, 95% CI: 1.282–2.290, p < 0.001 ), and prehospital defibrillation using an automated external defibrillator ([AED] OR = 3.984, 95% CI: 2.920–5.435, p < 0.001 ) were statistically and significantly associated with survival to hospital discharge. The cut-off value was 6.2 min. If the location of OHCA was a public place or bystander CPR was provided, the threshold was prolonged to 7.2 min and 6.3 min, respectively. In the absence of a witness, EMT-P, or AED, the threshold was reduced to 4.2, 5, and 5 min, respectively. The adjusted OR of EMS response time for survival to hospital discharge was 1.217 (per minute shorter, CI: 1.140–1299, p < 0.001 ) and 1.992 (<6.2 min, 95% CI: 1.496–2.653, p < 0.001 ). The optimal response time threshold for survival to hospital discharge was 6.2 min. In the case of OHCA in public areas or with bystander CPR, the threshold was prolonged, and without witness, the optimal response time threshold was shortened.


2020 ◽  
Vol 48 (1) ◽  
pp. 35-36
Author(s):  
Ziv Scully ◽  
Lucas van Kreveld ◽  
Onno Boxma ◽  
Jan-Pieter Dorsman ◽  
Adam Wierman

2017 ◽  
Vol 13 (3) ◽  
pp. 47-72
Author(s):  
Damla Oguz ◽  
Shaoyi Yin ◽  
Belgin Ergenç ◽  
Abdelkader Hameurlain ◽  
Oguz Dikenelli

The goal of query optimization in query federation over linked data is to minimize the response time and the completion time. Communication time has the highest impact on them both. Static query optimization can end up with inefficient execution plans due to unpredictable data arrival rates and missing statistics. This study is an extension of adaptive join operator which always begins with symmetric hash join to minimize the response time, and can change the join method to bind join to minimize the completion time. The authors extend adaptive join operator with bind-bloom join to further reduce the communication time and, consequently, to minimize the completion time. They compare the new operator with symmetric hash join, bind join, bind-bloom join, and adaptive join operator with respect to the response time and the completion time. Performance evaluation shows that the extended operator provides optimal response time and further reduces the completion time. Moreover, it has the adaptation ability to different data arrival rates.


Author(s):  
Ziv Scully ◽  
Lucas van Kreveld ◽  
Onno Boxma ◽  
Jan-Pieter Dorsman ◽  
Adam Wierman

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