Systematically and quantitatively determining patterns in consumer flow is an important problem in marketing research. Identifying these patterns can facilitate an understanding of where and when ...consumers purchase products and services at physical retail shops. Collecting data on real consumers who shop at retail stores is one of the most challenging and expensive aspects of these studies. This article introduces ConvenienceProbe, a phone-based data collection system for retail trade-area analysis. The proposed method targets local residents shopping at neighborhood convenience stores. This study deploys and tests the system by collecting real customer flow data in neighborhood convenience stores. Results show that the consumer flow data collected from the ConvenienceProbe system is comparable to that from a traditional face-to-face interview method.
This study presents several extensions to our previous work on the PipeProbe system, a mobile sensor system for identifying the spatial topology of hidden water pipelines (i.e., non-moldable pipes ...such as copper and PVC) behind walls or under floors Lai et al. 2010. The PipeProbe system works by dropping a tiny wireless sensor capsule into the source of a water pipeline. As the PipeProbe capsule traverses the pipelines, it gathers and transmits pressure and angular velocity readings. Through spatiotemporal analysis of these sensor readings, the proposed algorithm locates all turning points in the pipelines and maps their 3D spatial topology. This study expands upon previous research by developing new sensing techniques that identify variable-diameter pipes and differentiate 90-degree pipe turns from 45-degree pipe bends.
PipeProbe Lai, Tsung-te (Ted); Chen, Yu-han (Tiffany); Huang, Polly ...
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems,
11/2010
Conference Proceeding
This paper presents PipeProbe, a mobile sensor system for determining the spatial topology of hidden water pipelines behind walls. PipeProbe works by dropping a tiny wireless sensor capsule into the ...source of the water pipelines. As the PipeProbe capsule traverses the pipelines, it gathers and transmits pressure and angular velocity readings. Through spatio-temporal analysis on the sensor readings, our algorithm locates all turning points in the pipelines and maps their 3D spatial topology. We evaluated the PipeProbe system by developing a prototype and using data collected in our experimental testbed. Results show that the PipeProbe system successfully located and estimated 90% of all pipe tube lengths within 8-cm accuracy on average tube lengths of 76 cm. PipeProbe also successfully located 90% of all turning points within 15-cm accuracy on average length paths of 335cm.
Demo Ravindranath, Lenin; Chen, Tiffany Yu-Han; Das, Somak ...
Proceedings of the 10th international conference on Mobile systems, applications, and services,
06/2012
Conference Proceeding
Smartphones now are equipped with a variety of sensors including inertial sensors (accelerometers and gyroscopes) and multiple position sensors (GPS, WiFi, and cellular radios). These powerful ...capabilities have made smartphones an attractive platform for tasking applications. Tasking applications are rapid developing mobile applications which process data from multiple sensors continuously to determine user's context (such as location or activity) and take certain actions based on pre-defined conditions. Examples of such applications include location-based reminders, notifying when friends are nearby, changing the ring-mode of a phone automatically depending on the location, automatically tracking and storing movement tracks when driving, and inferring the number of steps walked each day. However, today, developing tasking applications is non-trivial for two reasons: poor abstractions and poor programming support 1.
We address these shortcomings through Code In The Air (CITA), a system that simplifies the development of tasking applications. CITA achieves this by providing an activity composition framework and a tasking execution framework that allows developers and end-users to easily write and compose tasks.
Since its recognition in December 2019, covid-19 has rapidly spread globally causing a pandemic. Pre-existing comorbidities such as hypertension, diabetes, and cardiovascular disease are associated ...with a greater severity and higher fatality rate of covid-19. Furthermore, COVID-19 contributes to cardiovascular complications, including acute myocardial injury as a result of acute coronary syndrome, myocarditis, stress-cardiomyopathy, arrhythmias, cardiogenic shock, and cardiac arrest. The cardiovascular interactions of COVID-19 have similarities to that of severe acute respiratory syndrome, Middle East respiratory syndrome and influenza. Specific cardiovascular considerations are also necessary in supportive treatment with anticoagulation, the continued use of renin-angiotensin-aldosterone system inhibitors, arrhythmia monitoring, immunosuppression or modulation, and mechanical circulatory support.
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 67-72).
...This thesis describes the design, implementation, and evaluation of Ada, a context-sensing service for mobile devices. Ada explores new points in the accuracy-energy-responsiveness design space for mobile context sensing. The service exports an API that allows a client to express interest in one or more context types (mode-of-movement, indoor/outdoor, and entry/exit to/from named regions), and subscribe to specific modes within each context (e.g., "walking" or "running", but not any other movement mode). Each context type in Ada can be in one of a set of mutually exclusive states. Each context has a detector that returns its estimate of the mode. To achieve high accuracy and low energy consumption, the detectors take both the existing context and the desired subscriptions into account, adjusting both the types of sensors and the sampling rates. To accurately determine the movement mode, Ada uses a new peak frequency feature from acceleration magnitudes, combining it with two other features. We present results from trace-driven experiments over carefully labeled data from real users, finding that our mode-of-movement detector achieves an accuracy of 93%, out-performing previous proposals like UCLA (55%), EEMSS (83%) and SociableSense (72%), while consuming between 2 and 3x less energy.
by Yu-Han Chen.
S.M.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.
Cataloged from PDF version of thesis.
Includes bibliographical references ...(pages 123-131).
Cameras of good quality are now available on handheld and wearable mobile devices. The high resolution of these cameras coupled with pervasive wireless connectivity and advanced computer vision algorithms makes it feasible to develop new ways to interact with mobile video. Two important examples are interactive object recognition and search-by-content. Interactive recognition continuously locates objects in a video stream, recognizes them, and labels them with information associated with the objects in the user's view. Example use cases include an augmented shopping application that recognizes products or brands to inform customers about the items they buy and a driver assistance application that recognizes vehicles and signs to improve driver safety. Interactive search-by-content allows users to discover videos using textual queries (e.g., "child dog play"). Instead of requiring broadcasters to manually annotate videos with meta-data tags, our search system uses vision algorithms to automatically produce textual tags. These two services must be highly interactive because users expect timely feedback for their interactions and changes in content. However, achieving high interactivity without sacrificing accuracy or efficiency is challenging. The required computer vision algorithms use computationally intensive deep neural networks and must run at a frame rate of 30 frames per second. Recognizing an object scales with the size of the corpus of objects, and is infeasible on a mobile device. Off-loading recognition operations to servers introduces network and processing delay; when this delay is higher than a frame-time, it degrades recognition accuracy. This dissertation presents two systems that study the trade-off between accuracy and efficiency for interactive recognition and search, and demonstrate how to achieve both goals. Glimpse enables interactive object recognition for camera-equipped mobile devices. Because the algorithms for object recognition entail significant computation, Glimpse runs them on servers across the network. To "hide" latency, Glimpse uses an active cache of video frames on the device and performs tracking on a subset of frames to correct the stale results obtained from the processing pipeline. Our results show that Glimpse achieves a precision of 90% for face recognition, which improves over a scheme performing server-side recognition without using an active cache by 2.8 x. For fast moving objects such as road signs, Glimpse achieves precision up to 80%; without using the active cache, interactive recognition is non-functional (1.9% precision). Panorama enables search on live video streams. It introduces three new mechanisms: (1) an intelligent frame selector that reduces the number of frames on which expensive recognition must be run, (2) a distributed scheduler that uses feedback from the vision algorithms to dynamically determine the order in which streams must be processed, and (3) a search-ranking method that uses visual features to improve search relevance. Our experimental results show that incorporating visual features doubles search relevance from 45% to 90%. To achieve 90% search accuracy, with current pricing from Amazon Web Services, Panorama incurs 24x lower cost than a scheme that recognizes every frame.
by Yu-Han Tiffany Chen.
Ph. D.
Ni-containing heteropolyvanadate, Na6NiV14O40, was synthesized for the first time to be applied in high-energy lithium storage applications as a negative electrode material. Na6NiV14O40 can be ...prepared via a facile solution process that is suitable for low-cost mass production. The as-prepared electrode provided a high capacity of approximately 700 mAh g–1 without degradation for 400 cycles, indicating excellent cycling stability. The mechanism of charge storage was investigated using operando X-ray absorption spectroscopy (XAS), X-ray diffraction (XRD), transition X-ray microscopy (TXM), and density functional theory (DFT) calculations. The results showed that V5+ was reduced to V2+ during lithiation, indicating that Na6NiV14O40 is an insertion-type material. In addition, Na6NiV14O40 maintained its amorphous structure with negligible volume expansion/contraction during cycling. Employed as the negative electrode in a lithium-ion battery (LIB), the Na6NiV14O40//LiFePO4 full cell had a high energy density of 300 W h kg–1. When applied in a lithium-ion capacitor, the Na6NiV14O40//expanded mesocarbon microbead full cell displayed energy densities of 218.5 and 47.9 W h kg–1 at power densities of 175.7 and 7774.2 W kg–1, respectively. These findings reveal that the negative electrode material Na6NiV14O40 is a promising candidate for Li-ion storage applications.
Over the last decade, educators, administrators, and policy makers increasingly focus on corporate social responsibility. However, no studies examine the relationships among corporate social ...responsibility, brand equity, and firm performance. This study uses quantile regression and structural equation modeling to explore the causal linkages among these factors in Taiwanese high-tech companies over the period 2010–2013.
The results of quantile regression analysis show that the economic dimension of corporate social responsibility and the prestige driver of brand equity are positive and significant for all the quantiles. The brand extension driver provides a significant positive effect at the higher quantiles of firm performance. However, the findings indicate a significant negative effect on firm performance for the brand loyalty driver. The findings of structural equation modeling suggest that corporate social responsibility and brand equity positively affect firm performance. This study provides useful insights on brand equity and corporate social responsibility.
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