A Novel Sampling Technique for Probabilistic Static Coverage Problems

2016 ◽  
Vol 138 (3) ◽  
Author(s):  
Binbin Zhang ◽  
Nagavenkat Adurthi ◽  
Rahul Rai ◽  
Puneet Singla
Keyword(s):  
Resource Allocation ◽  
San Francisco ◽  
Systems Engineering ◽  
Real Life ◽  
Sampling Technique ◽  
Superior Performance ◽  
Coverage Problem ◽  
Area Of Interest ◽  
Wide Range ◽  
Coverage Problems

Resource allocation in the presence of constraints is an important activity in many systems engineering problems such as surveillance, infrastructure planning, environmental monitoring, and cooperative task performance. The resources in many important problems are agents such as a person, machine, unmanned aerial vehicles (UAVs), infrastructures, and software. Effective execution of a given task is highly correlated with effective allocation of resources to execute the task. An important class of resource allocation problem in the presence of limited resources is static coverage problem. In static coverage problems, it is necessary to allocate resources (stationary configuration of agents) to cover an area of interest so that an event or spatial property of the area can be detected or monitored with high probability. In this paper, we outline a novel sampling algorithm for the static coverage problem in presence of probabilistic resource intensity allocation maps (RIAMs). The key intuition behind our sampling approach is to use the finite number of samples to generate an accurate representation of RIAM. The outlined sampling technique is based on an optimization framework that approximates the RIAM with piecewise linear surfaces on the Delaunay triangles and optimizes the sample placement locations to decrease the difference between the probability distribution and Delaunay triangle surface. Numerical results demonstrate that the algorithm is robust to the initial sample point locations and has superior performance in a wide range of theoretical problems and real-life applications. In a real-life application setting, we demonstrate the efficacy of the proposed algorithm to predict the position of wind stations for monitoring wind speeds across the U.S. The algorithm is also used to give recommendations on the placement of police cars in San Francisco and weather buoys in Pacific Ocean.

Home Learning in Times of COVID: Experiences of Parents

2020 ◽  
Vol 7 (1) ◽  
pp. 9 ◽  
Author(s):  
Shelina Bhamani ◽  
Areeba Zainab Makhdoom ◽  
Vardah Bharuchi ◽  
Nasreen Ali ◽  
Sidra Kaleem ◽  
...  
Keyword(s):  
Real Life ◽  
Sampling Technique ◽  
Online Classes ◽  
Google Docs ◽  
Learning Gap ◽  
Wide Range ◽  
Home Learning ◽  
Collection Data ◽  
Learning At Home ◽  
At Home

<p align="center"><em>The widespread prevalence of COVID-19 pandemic has affected academia and parents alike. Due to the sudden closure of schools, students are missing social interaction which is vital for better learning and grooming while most schools have started online classes. This has become a tough routine for the parents working online at home since they have to ensure their children’s education. The study presented was designed to explore the experiences of home learning in times of COVID-19. A descriptive qualitative study was planned to explore the experiences of parents about home learning and management during COVID-19 to get an insight into real-life experiences.  Purposive sampling technique was used for data collection.  Data were collected from 19 parents falling in the inclusion criteria. Considering the lockdown problem, the data were collected via Google docs form with open-ended questions related to COVID-19 and home learning. Three major themes emerged after the data analysis: impact of COVID on children learning; support given by schools; and strategies used by caregivers at home to support learning. It was analyzed that the entire nation and academicians around the world have come forward to support learning at home offering a wide range of free online avenues to support parents to facilitate home-learning. Furthermore, parents too have adapted quickly to address the learning gap that have emerged in their children’s learning in these challenging times. Measures should be adopted to provide essential learning skills to children at home. Centralized data dashboards and educational technology may be used to keep the students, parents and schools updated.</em></p>

scholarly journals Efficient Shared Execution Processing of k-Nearest Neighbor Joins in Road Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Hyung-Ju Cho
Keyword(s):  
Euclidean Distance ◽  
Nearest Neighbor ◽  
Real Life ◽  
Road Networks ◽  
Nearest Neighbors ◽  
Superior Performance ◽  
K Nearest Neighbor ◽  
Wide Range ◽  
Primitive Operation ◽  
Nested Loop

We investigate the k-nearest neighbor (kNN) join in road networks to determine the k-nearest neighbors (NNs) from a dataset S to every object in another dataset R. The kNN join is a primitive operation and is widely used in many data mining applications. However, it is an expensive operation because it combines the kNN query and the join operation, whereas most existing methods assume the use of the Euclidean distance metric. We alternatively consider the problem of processing kNN joins in road networks where the distance between two points is the length of the shortest path connecting them. We propose a shared execution-based approach called the group-nested loop (GNL) method that can efficiently evaluate kNN joins in road networks by exploiting grouping and shared execution. The GNL method can be easily implemented using existing kNN query algorithms. Extensive experiments using several real-life roadmaps confirm the superior performance and effectiveness of the proposed method in a wide range of problem settings.

A Sequential Sampling Algorithm for Multistage Static Coverage Problems

2018 ◽  
Vol 18 (2) ◽  
Author(s):  
Binbin Zhang ◽  
Jida Huang ◽  
Rahul Rai ◽  
Hemanth Manjunatha
Keyword(s):  
Optimization Problems ◽  
Sequential Sampling ◽  
Minimum Energy ◽  
Pattern Search ◽  
Coverage Problem ◽  
Sampling Algorithm ◽  
System Designer ◽  
Area Of Interest ◽  
Coverage Problems ◽  
Multiple Stages

In many system-engineering problems, such as surveillance, environmental monitoring, and cooperative task performance, it is critical to allocate limited resources within a restricted area optimally. Static coverage problem (SCP) is an important class of the resource allocation problem. SCP focuses on covering an area of interest so that the activities in that area can be detected with high probabilities. In many practical settings, primarily due to financial constraints, a system designer has to allocate resources in multiple stages. In each stage, the system designer can assign a fixed number of resources, i.e., agents. In the multistage formulation, agent locations for the next stage are dependent on previous-stage agent locations. Such multistage static coverage problems are nontrivial to solve. In this paper, we propose an efficient sequential sampling algorithm to solve the multistage static coverage problem (MSCP) in the presence of resource intensity allocation maps (RIAMs) distribution functions that abstract the event that we want to detect/monitor in a given area. The agent's location in the successive stage is determined by formulating it as an optimization problem. Three different objective functions have been developed and proposed in this paper: (1) L2 difference, (2) sequential minimum energy design (SMED), and (3) the weighted L2 and SMED. Pattern search (PS), an efficient heuristic algorithm has been used as optimization algorithm to arrive at the solutions for the formulated optimization problems. The developed approach has been tested on two- and higher dimensional functions. The results analyzing real-life applications of windmill placement inside a wind farm in multiple stages are also presented.

A Sequential Sampling Algorithm for Multi-Stage Static Coverage Problems

2016 ◽  
Author(s):  
Hemanth Manjunatha ◽  
Jida Huang ◽  
Binbin Zhang ◽  
Rahul Rai
Keyword(s):  
Heuristic Algorithms ◽  
Sequential Sampling ◽  
Minimum Energy ◽  
Pattern Search ◽  
Coverage Problem ◽  
Sampling Algorithm ◽  
System Designer ◽  
Area Of Interest ◽  
Multi Stage ◽  
Coverage Problems

It is critical in many system-engineering problems (such as surveillance, environmental monitoring, and cooperative task performance) to optimally allocate resources in the presence of limited resources. Static coverage problem is an important class of the resource allocation problems that focuses on covering an area of interest so that the activities in the area of interest can be detected/monitored with higher probability. In many practical settings (primarily due to financial constraints) a system designer has to allocate resources in multiple stages. In each stage, the system designer can assign a fixed number of resources (agents). In the multi-stage formulation, the agents locations for the next stage are dependent on all the agents location in the previous stages. Such multi-stage static coverage problems are non-trivial to solve. In this paper, we propose a robust and efficient sequential sampling algorithm to solve the multi-stage static coverage problem in the presence of probabilistic resource intensity allocation maps (RIAMs). The agents locations are determined by formulating this problem as an optimization problem in the successive stage . Three different objective functions are compared and discussed from the aspects of decreasing L2 difference and Sequential Minimum Energy Design (SMED). It is shown that utilizing SMED objective function leads to a better approximation of the RIAMs. Two heuristic algorithms, i.e. cuckoo search, and pattern search, are used as optimization algorithms. Numerical functions and real-life applications are provided to demonstrate the robustness and efficiency of the proposed approach.

Analysis of Hybrid Dynamical Systems With Uncertainty in Initial Conditions

2015 ◽  
Author(s):  
Yuhua He ◽  
Arpan Mukherjee ◽  
Rahul Rai
Keyword(s):  
Dynamical Systems ◽  
Systems Engineering ◽  
Initial Conditions ◽  
Real Life ◽  
Parametric Uncertainty ◽  
Superior Performance ◽  
Hybrid Dynamical Systems ◽  
Unscented Transform ◽  
Output Variability ◽  
Novel Method

Hybrid dynamical systems (HDS) models are backbone of modeling a myriad of systems found in systems engineering, buildings, manufacturing, auto-pilot control, and chemical processes domains among others. Uncertainty quantification (UQ) techniques to ascertain output variability in HDS with parametric uncertainty is relatively understudied topic. In this paper, we present a novel method to enable UQ of HDSs. Specifically, we outline a computational pipeline to solve different types of Stochastic Hybrid Systems (SHS) with uncertainty in initial conditions. The developed method is based on a numerical integration technique Conjugate Unscented Transform (CUT) and discrete UQ technique. The developed method has been applied to different range of problems including theoretical problems and real life mechanical systems modeled in Simulink environment. Performance of the proposed method has been compared against Monte Carlo and Unscented Transform methods. Results indicate superior performance of the proposed technique over the existing methods.

Unexpectedness

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
John-Carlos Perea ◽  
Jacob E. Perea
Keyword(s):  
American Indian ◽  
San Francisco ◽  
Interdisciplinary Research ◽  
Ethnic Studies ◽  
College Of Education ◽  
Present Moment ◽  
State University ◽  
Research Projects ◽  
Short Survey ◽  
Wide Range

The concepts of expectation, anomaly, and unexpectedness that Philip J. Deloria developed in Indians in Unexpected Places (2004) have shaped a wide range of interdisciplinary research projects. In the process, those terms have changed the ways it is possible to think about American Indian representation, cosmopolitanism, and agency. This article revisits my own work in this area and provides a short survey of related scholarship in order to reassess the concept of unexpectedness in the present moment and to consider the ways my deployment of it might change in order to better meet the needs of my students. To begin a process of engaging intergenerational perspectives on this subject, the article concludes with an interview with Dr. Jacob E. Perea, dean emeritus of the Graduate College of Education at San Francisco State University and a veteran of the 1969 student strikes that founded the College of Ethnic Studies at San Francisco State University.

Game-Based Resource Allocation Mechanism in B5G HetNets with Incomplete Information

2020 ◽  
Vol 10 (5) ◽  
pp. 1557
Author(s):  
Weijia Feng ◽  
Xiaohui Li
Keyword(s):  
Resource Allocation ◽  
Incomplete Information ◽  
Stackelberg Game ◽  
Superior Performance ◽  
Channel Gain ◽  
Mobile Users ◽  
Pricing Strategies ◽  
Game Equilibrium ◽  
Allocation Process ◽  
Realistic Situation

Ultra-dense and highly heterogeneous network (HetNet) deployments make the allocation of limited wireless resources among ubiquitous Internet of Things (IoT) devices an unprecedented challenge in 5G and beyond (B5G) networks. The interactions among mobile users and HetNets remain to be analyzed, where mobile users choose optimal networks to access and the HetNets adopt proper methods for allocating their own network resource. Existing works always need complete information among mobile users and HetNets. However, it is not practical in a realistic situation where important individual information is protected and will not be public to others. This paper proposes a distributed pricing and resource allocation scheme based on a Stackelberg game with incomplete information. The proposed model proves to be more practical by solving the problem that important information of either mobile users or HetNets is difficult to acquire during the resource allocation process. Considering the unknowability of channel gain information, the follower game among users is modeled as an incomplete information game, and channel gain is regarded as the type of each player. Given the pricing strategies of networks, users will adjust their bandwidth requesting strategies to maximize their expected utility. While based on the sub-equilibrium obtained in the follower game, networks will correspondingly update their pricing strategies to be optimal. The existence and uniqueness of Bayesian Nash equilibrium is proved. A probabilistic prediction method realizes the feasibility of the incomplete information game, and a reverse deduction method is utilized to obtain the game equilibrium. Simulation results show the superior performance of the proposed method.

scholarly journals A Systematic Review and Qualitative Synthesis Resulting in a Typology of Elementary Classroom Movement Integration Interventions

2020 ◽  
Vol 6 (1) ◽  
Author(s):  
Spyridoula Vazou ◽  
Collin A. Webster ◽  
Gregory Stewart ◽  
Priscila Candal ◽  
Cate A. Egan ◽  
...  
Keyword(s):  
Physical Activity ◽  
Teacher Collaboration ◽  
A Priori ◽  
Real Life ◽  
Dose Intensity ◽  
Routine Practice ◽  
Qualitative Synthesis ◽  
Wide Range ◽  
Meta Analyses ◽  
Movement Integration

Abstract Background/Objective Movement integration (MI) involves infusing physical activity into normal classroom time. A wide range of MI interventions have succeeded in increasing children’s participation in physical activity. However, no previous research has attempted to unpack the various MI intervention approaches. Therefore, this study aimed to systematically review, qualitatively analyze, and develop a typology of MI interventions conducted in primary/elementary school settings. Subjects/Methods Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed to identify published MI interventions. Irrelevant records were removed first by title, then by abstract, and finally by full texts of articles, resulting in 72 studies being retained for qualitative analysis. A deductive approach, using previous MI research as an a priori analytic framework, alongside inductive techniques were used to analyze the data. Results Four types of MI interventions were identified and labeled based on their design: student-driven, teacher-driven, researcher-teacher collaboration, and researcher-driven. Each type was further refined based on the MI strategies (movement breaks, active lessons, other: opening activity, transitions, reward, awareness), the level of intrapersonal and institutional support (training, resources), and the delivery (dose, intensity, type, fidelity). Nearly half of the interventions were researcher-driven, which may undermine the sustainability of MI as a routine practice by teachers in schools. An imbalance is evident on the MI strategies, with transitions, opening and awareness activities, and rewards being limitedly studied. Delivery should be further examined with a strong focus on reporting fidelity. Conclusions There are distinct approaches that are most often employed to promote the use of MI and these approaches may often lack a minimum standard for reporting MI intervention details. This typology may be useful to effectively translate the evidence into practice in real-life settings to better understand and study MI interventions.

Structural design and gait research of a new bionic quadruped robot

2021 ◽  
pp. 095440542199566
Author(s):  
Jiu-Peng Chen ◽  
Hong-Jun San ◽  
Xing Wu ◽  
Bin-Zhou Xiong
Keyword(s):  
Stability Margin ◽  
Static Stability ◽  
Quadruped Robot ◽  
Superior Performance ◽  
Linkage Mechanism ◽  
Wide Range ◽  
Planning Algorithm ◽  
Planning Experiment ◽  
Strength And Stiffness ◽  
Foot Trajectory

Quadruped bionic robot has a strong adaptability to the environment, compared with wheeled and tracked robots, it has superior motion performance, and has a wide range of application prospects in rescue and disaster relief, ground mine clearance, mountain transportation, so it has become a research hotspot all over the world. Leg structure is an important embodiment of the superior performance of quadruped robot, and it is also the key and difficult point of design. This article proposes a novel quadruped robot with waist structure, which can complete a variety of gait forms. Based on the theory of linkage mechanism, a novel leg structure is designed with anti-parallelogram mechanism, which improves the strength and stiffness of the robot. Using D-H description method, the kinematics analysis of this quadruped robot single leg is carried out. On this basis, in order to ensure the foot contact with the ground and achieve zero impact, polynomial programming is used to plan the foot trajectory of swing phase and support phase. Based on the static stability margin, the optimal static gait of the quadruped robot is planned. A co-simulation study has been carried out to investigate further the validity and effectiveness of the quadruped robot on gait. The simulation results clearly show the robot can walk steadily and its input and output meet the expected requirements. The solid prototype platform is built, and the trajectory planning experiment of single leg is carried out, and the foot trajectory of single leg is obtained by using laser tracker. The gait planning algorithm is applied to the whole robot, and the results show that the robot can walk according to the scheduled gait, which proves the effectiveness of the proposed algorithm.

scholarly journals Estimating the number of usability problems affecting medical devices: modelling the discovery matrix

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Vincent Vandewalle ◽  
Alexandre Caron ◽  
Coralie Delettrez ◽  
Renaud Périchon ◽  
Sylvia Pelayo ◽  
...  
Keyword(s):  
Medical Devices ◽  
Market Access ◽  
Real Life ◽  
Usability Testing ◽  
Probability Of Detection ◽  
Usability Problems ◽  
Usability Problem ◽  
Wide Range ◽  
The Matrix ◽  
Problem Detection

Abstract Background Usability testing of medical devices are mandatory for market access. The testings’ goal is to identify usability problems that could cause harm to the user or limit the device’s effectiveness. In practice, human factor engineers study participants under actual conditions of use and list the problems encountered. This results in a binary discovery matrix in which each row corresponds to a participant, and each column corresponds to a usability problem. One of the main challenges in usability testing is estimating the total number of problems, in order to assess the completeness of the discovery process. Today’s margin-based methods fit the column sums to a binomial model of problem detection. However, the discovery matrix actually observed is truncated because of undiscovered problems, which corresponds to fitting the marginal sums without the zeros. Margin-based methods fail to overcome the bias related to truncation of the matrix. The objective of the present study was to develop and test a matrix-based method for estimating the total number of usability problems. Methods The matrix-based model was based on the full discovery matrix (including unobserved columns) and not solely on a summary of the data (e.g. the margins). This model also circumvents a drawback of margin-based methods by simultaneously estimating the model’s parameters and the total number of problems. Furthermore, the matrix-based method takes account of a heterogeneous probability of detection, which reflects a real-life setting. As suggested in the usability literature, we assumed that the probability of detection had a logit-normal distribution. Results We assessed the matrix-based method’s performance in a range of settings reflecting real-life usability testing and with heterogeneous probabilities of problem detection. In our simulations, the matrix-based method improved the estimation of the number of problems (in terms of bias, consistency, and coverage probability) in a wide range of settings. We also applied our method to five real datasets from usability testing. Conclusions Estimation models (and particularly matrix-based models) are of value in estimating and monitoring the detection process during usability testing. Matrix-based models have a solid mathematical grounding and, with a view to facilitating the decision-making process for both regulators and device manufacturers, should be incorporated into current standards.

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