Google Nexus Research Articles

Curious About George: Curious George, Cultural Icons, Colonialism, and US Exceptionalism by Rae Lynn Schwartz-DuPre

Reviewed by: Curious About George: Curious George, Cultural Icons, Colonialism, and US Exceptionalism by Rae Lynn Schwartz-DuPre Tharini Viswanath (bio) Curious About George: Curious George, Cultural Icons, Colonialism, and US Exceptionalism. By Rae Lynn Schwartz-DuPre. University Press of Mississippi, 2021. Rae Lynn Schwartz-DuPre's Curious About George: Curious George, Cultural Icons, Colonialism, and US Exceptionalism examines how the circulation of Curious George materials—such as the book series, films, TV shows, and art exhibits—promotes negative US exceptionalism. The main focus of the monograph is to unpack the rhetorics of colonialism that circulate within US media by viewing the famous monkey, George, as a cultural icon. Accordingly, the chapters in this monograph take up "four of the mediated reincarnations of George—his rise to literacy success, his emergence in film, his placement in STEM education, and his Holocaust remembrance narratives—in order to demonstrate how contemporary postcolonial theory can offer a provocative re-reading of each discourse individually" (6). Schwartz-DuPre's introductory chapter is largely comprised of an extensive literature review. The chapter begins with a detailed overview of the emergence and circulation of Curious George books and media from the monkey's first appearance in Cecily G. and the Nine Monkeys in 1939, to more recent productions including the 2006 Curious George blockbuster film, stuffed toys, collectables, entertainment media, and even giant Curious George parade balloons. Schwartz-DuPre argues [End Page 334] that these various productions make George more than just a character; he is a cultural icon who has the power to direct audiences. The next section provides readers with an overview of cultural icons, metaphors, and ciphers, and George's role as an icon who has immense capacity to uphold certain (American) cultural values. Next, the author provides an overview of postcolonial studies, positing that the US has become one of the greatest colonizing powers in the world. She further argues that "[i]ncluding the US in the rhetoric of postcoloniality is central to understanding that one can be both a victim of violence and a perpetuator of it" (36). In addition to situating the argument and offering definitions and explanations for terms in both literary and media studies, this chapter emphasizes that audiences don't need to have read a Curious George book to be influenced by the monkey's icon status, because the marketing and media surrounding the character is all pervasive. Chapter 2, "Curious George Explores the Diaspora," focuses primarily on postcolonial children's literary criticism to contend that "the Curious George book series, both past and present, fits neatly into the genre of colonial literature and accordingly benefits from a post-colonial re-reading" (46). More than half this chapter is devoted to the following: the intentionality of writers versus the critical rhetorical model, a brief overview of the importance of studying children's literature, and what postcolonial theory has to offer critical readings of children's literature. The literature review is lengthy and can seem a bit dry for those already familiar with the fields of children's literature and postcolonial theory. The literary analysis of the book series, however, redeems this chapter. Building on June Cummins's groundbreaking article "The Resisting Monkey," which demonstrates the parallels between the Curious George narrative and African American enslavement narratives, Schwartz-DuPre analyzes the visual metaphors in the book series to better understand George's diasporic identity and themes of assimilation. This section is most interesting as the author uses media in the form of letters—written by both adults and children—to the Reys to support her argument. The third chapter, "George Teaches Science," is excellent. Schwartz-DuPre analyzes various media depictions of George including Google's Nexus 7 ad (2012), blockbuster films, the popular television series spearheaded by PBS (airing for fifteen seasons from 2006-2022) that offers lessons in STEM education, and digital adventures available on devices such as the iPad or iPhone to demonstrate how, "[i] n George's narrative, a rhetoric of curiosity is upheld as a justification for the colonial quest" (109). Schwartz-DuPre reads the icon of George through the lens of postcolonial Science Technology Studies (STS) to make an important point: while George...

Therminator 2: A Fast Thermal Simulator for Portable Devices

Maintaining safe chip and device skin temperatures in small form-factor mobile devices (such as smartphones and tablets) while continuing to add new functionalities and provide higher performance has emerged as a key challenge. This article presents <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Therminator 2</i> , an early stage, fast, full-device thermal analyzer, which generates accurate transient- and steady-state temperature maps of an entire smartphone starting from the application processor and other key device components, extending to the skin of the device itself. Therminator 2 uses advanced numerical optimization techniques to perform steady-state simulations 1.6 times faster than the prior art technique and is capable of performing transient-state simulations in real time and 1.25 times faster than the prior art method. The thermal analysis is sensitive to detailed device specifications (including its material composition and 3-D layout) as well as different use cases (each case specifying the set of active device components and their activity levels.) Therminator 2 considers all major components within the device, builds a corresponding compact thermal model for each component and the whole device, and produces their transient- and steady-state temperature maps. Temperature results obtained by using Therminator 2 have been validated against a commercial computational fluid dynamics (CFDs)-based tool, i.e., Autodesk Simulation CFD, and thermocouple measurements on a Qualcomm Mobile Developer Platform and Google Nexus 5. A case study on a Samsung Galaxy S4 using Therminator 2 is provided to relate the device performance to the skin temperature and investigate the thermal path design.

Peer-to-Peer Localization for Single-Antenna Devices

Some important indoor localization applications, such as localizing a lost kid in a shopping mall, call for a new peer-to-peer localization technique that can localize an individual's smartphone or wearables by directly using another's on-body devices in unknown indoor environments. However, current localization solutions either require pre-deployed infrastructures or multiple antennas in both transceivers, impending their wide-scale application. In this paper, we present P2PLocate, a peer-to-peer localization system that enables a single-antenna device co-located with a batteryless backscatter tag to localize another single-antenna device with decimeter-level accuracy. P2PLocate leverages the multipath variations intentionally created by an on-body backscatter tag, coupled with spatial information offered by user movements, to accomplish this objective without relying on any pre-deployed infrastructures or pre-training. P2PLocate incorporates novel algorithms to address two major challenges: (i) interference with strong direct-path signal while extracting multipath variations, and (ii) lack of direction information while using single-antenna transceivers. We implement P2PLocate on commercial off-the-shelf Google Nexus 6p, Intel 5300 WiFi card, and Raspberry Pi B4. Real-world experiments reveal that P2PLocate can localize both static and mobile targets with a median accuracy of 0.88 m.

MobiGyges: A mobile hidden volume for preventing data loss, improving storage utilization, and avoiding device reboot

Sensitive data protection is essential for mobile users. Plausibly Deniable Encryption (PDE) systems provide an effective manner to protect sensitive data by hiding them on the device. However, existing PDE systems can lose data due to overriding the hidden volume, waste physical storage owing to the “reserved area” for avoiding data loss, and require device reboot when using the hidden volume. This paper presents MobiGyges, a hidden volume-based mobile PDE system, to fill the gap. MobiGyges addresses the problem of data loss by restricting each storage block used only by one volume, and it improves storage utilization by eliminating the “reserved area”. MobiGyges also avoids device reboot by mounting the hidden volume dynamically on-demand with the Dynamic Mounting service. Moreover, we identify two novel PDE oriented attacks, the capacity comparison attack and the fill-to-full attack. MobiGyges can defend against them by jointly leveraging the Shrunk U-disk method and multi-level deniability. We implement the MobiGyges proof-of-concept system on a real mobile phone Google Nexus 6P with LineageOS 13. Experimental results show that MobiGyges prevents data loss, avoids device reboot, improves storage utilization by over 30% with acceptable performance overhead compared with current solutions.

An Efficient Directory Entry Lookup Cache With Prefix-Awareness for Mobile Devices

Modern mobile devices, such as smartphones, maintain a directory cache (DCache) to accelerate directory and file accesses. However, the original DCache recursively walks through all the components of a path name for each directory entry (dentry) lookup operation, leading to low lookup efficiency. In this article, we first investigate intrinsic characteristics of dentry lookup operations in smartphones and make several interesting findings: 1) file path lookup operations are called frequently (up to 104 times per second) by mobile applications; 2) file path lookup operations present high temporal and spatial locality; and 3) the latency of a file path lookup is linear to the depth of the path name. Based on our findings, we further propose an efficient directory entry lookup cache architecture, named dynamic skipping cache (DS-Cache), which adopts an ASCII-based hash table to simplify the path lookup complexity. In DS-Cache, a dynamic skip lookup algorithm is proposed to skip the common prefixes of different accessing paths. A rename algorithm and a delete algorithm are designed to promise the consistence of DS-Cache and the backend file system. We also design a prefix-aware cache replacement scheme to optimize the DS-Cache hit ratio. We have implemented and deployed DS-Cache on a Google Nexus 6P smartphone. The experimental results show that we can significantly reduce the latency of invoking system calls by up to 81%, and further reduce the completion time of real-world mobile applications by up to 67%.

An Efficient LSM-Tree-Based SQLite-Like Database Engine for Mobile Devices

SQLite has been deployed in millions of mobile devices from Web to smartphone applications on various mobile operating systems. However, due to the uncoordinated IO interactions with the underlying file system (e.g., ext4), SQLite is not efficient with low transactions per second. In this paper, we for the first time propose a new SQLite-like database engine, called SQLiteKV, which adopts the LSM-tree-based data structure but retains the SQLite operation interfaces. With its SQLite interface, SQLiteKV can be utilized by existing applications without any modification, while providing high performance with its LSM-tree-based data structure. We separate SQLiteKV into the front-end and back-end. In the front-end, we develop a light-weight SQLite-to-KV compiler to solve the semantic mismatch, so SQL statements can be efficiently translated into KV operations. We also design a novel coordination caching mechanism with memory defragmentation so query results can be effectively cached inside SQLiteKV by alleviating the discrepancy of data management between front-end SQLite statements and back-end data organization. In the back-end, we adopt an LSM-tree-based key-value database engine, and propose a lightweight metadata management scheme to mitigate the memory requirement. We have implemented and deployed SQLiteKV on a Google Nexus 6P smartphone. Experimental results with various workloads show that SQLiteKV outperforms SQLite up to six times.

Smartphone-Based Indoor Fingerprinting Localization Using Channel State Information

Indoor localization technology plays an important role in many indoor application scenarios. Existing WiFi-based indoor localization methods mainly obtain channel state information (CSI) through the personal computer, or obtain coarse-grained received signal strength (RSS) through the smartphone to finish the localization. Little work has been done on using smartphones to obtain fine-grained channel state information for localization. In this paper, we use the smartphone to collect fine-grained CSI that is more convenient and applicable, and propose a indoor fingerprinting localization. Compared with the CSI collected by the computer, the CSI signal collected by the smartphone fluctuates greatly. Hence, we corrects the CSI data through the signal processing technique and selects optimal subcarriers to obtain more stable and effective signals. In order to cope with the noisy WiFi environment, the Density-Based Spatial Clustering of Applications with Noise (DBSCAN) method is used to remove abnormal sample points to reduce environmental interference. Moreover, the support vector machine multi-classification method is used for training and classification to achieve localization. Finally, we use the Google Nexus 5 smartphone to conduct experiments in two typical indoor environments. The localization accuracy is 91% and 86%, respectively, and both average localization errors are less than 0.5m. Experimental results show that the proposed algorithm has higher localization accuracy compared with the typical algorithms.

A real-time logo detection system using data offloading on mobile devices

ABSTRACTIn the past few years, mobile augmented reality (AR) has attracted a great deal of attention. It presents us a live, direct or indirect view of a real-world environment whose elements are augmented (or supplemented) by computer-generated sensory inputs such as sound, video, graphics or GPS data. Also, deep learning has the potential to improve the performance of current AR systems. In this paper, we propose a distributed mobile logo detection framework. Our system consists of mobile AR devices and a back-end server. Mobile AR devices can capture real-time videos and locally decide which frame should be sent to the back-end server for logo detection. The server schedules all detection jobs to minimise the maximum latency. We implement our system on the Google Nexus 5 and a desktop with a wireless network interface. Evaluation results show that our system can detect the view change activity with an accuracy of and successfully process 40 image processing jobs before deadline.

Non-Volatile Memory Based Page Swapping for Building High-Performance Mobile Devices

Smartphones are getting increasingly high-performance with advances in mobile processors and larger main memories to support feature-rich applications. However, the storage subsystem has always been a prohibitive factor that slows down the pace of reaching even higher performance while maintaining good user experience. Despite today's smartphones are equipped with larger-than-ever main memories, they consume more energy and still run out of memory. But the slow NAND flash based storage vetoes the possibility of swapping-an important technique to extend main memory-and leaves a system that constantly terminates user applications under memory pressure. In this paper, we propose NVM-Swap by revisiting swapping for smartphones with fast, byte-addressable, non-volatile memory (NVM) technologies. Instead of using flash, we build the swap area with NVM, to allow high performance without sacrificing user experience. NVM-Swap supports Lazy Swap-in, which can reduce memory copy operations by giving the swapped out pages a second chance to stay in byte-addressable NVM backed swap area. To avoid fast worn-out of certain NVM, we also propose Heap-Wear, a wear leveling algorithm that distributes writes in NVM more evenly. Evaluation results based on the Google Nexus 5 smartphone show that our solution can effectively enhance smartphone performance and achieve better wear-leveling of NVM.

Building NVRAM-Aware Swapping Through Code Migration in Mobile Devices

Mobile applications are becoming increasingly feature-rich and powerful, but also dependent on large main memories, which consume a large portion of system energy, especially for devices equipped with 4/6 GB DRAM. Swapping inactive DRAM pages to byte-addressable, non-volatile memory (NVRAM) is a promising solution to this problem. However, most NVRAMs have limited write endurance and the current victim pages selecting algorithm does not aware it. Therefore, to make it practical, the design of an NVRAM based swapping system must also consider endurance. In this paper, we target at prolonging the lifetime of NVRAM based swap area in mobile devices by reducing the write activities to NVRAM based swap area. Different from traditional wisdom, such as wear leveling and hot/cold data identification, we propose to build a system called n Code, which exploits the fact that code pages are easy to identify, read-only, and therefore a perfect candidate for swapping. Utilizing NVRAM’s byte-addressability, we support execute-in-place (XIP) of the code pages in the swap area, without copying them back to DRAM based main memory. Experimental results based on the Google Nexus 5 smartphone show that n Code can effectively prolong the lifetime of NVRAM under various workloads.

Locking it down: The privacy and security of mobile medication apps.

To explore the privacy and security of free medication applications (apps) available to Canadian consumers. The authors searched the Canadian iTunes store for iOS apps and the Canadian Google Play store for Android apps related to medication use and management. Using an Apple iPad Air 2 and a Google Nexus 7 tablet, 2 reviewers generated a list of apps that met the following inclusion criteria: free, available in English, intended for consumer use and related to medication management. Using a standard data collection form, 2 reviewers independently coded each app for the presence/absence of passwords, the storage of personal health information, a privacy statement, encryption, remote wipe and third-party sharing. A Cohen's Kappa statistic was used to measure interrater agreement. Of the 184 apps evaluated, 70.1% had no password protection or sign-in system. Personal information, including name, date of birth and gender, was requested by 41.8% (77/184) of apps. Contact information, such as address, phone number and email, was requested by 25% (46/184) of apps. Finally, personal health information, other than medication name, was requested by 89.1% (164/184) of apps. Only 34.2% (63/184) of apps had a privacy policy in place. Most free medication apps offer very limited authentication and privacy protocols. As a result, the onus currently falls on patients to input information in these apps selectively and to be aware of the potential privacy issues. Until more secure systems are built, health care practitioners cannot fully support patients wanting to use such apps.

Energy-Efficient In-Memory Paging for Smartphones

Smartphones are becoming increasingly energy-hungry to support feature-rich applications, posing a lot of pressure on battery lifetime and making energy consumption a non-negligible issue. In particular, dynamic random access memory (DRAM)-based main memory subsystem is a major contributor to the energy consumption of mobile devices. In this paper, we propose direct read (DR). Swap, an energy-efficient in-memory paging design to reduce energy consumption in smartphones. In DR. Swap, we adopt emerging energy-efficient nonvolatile memory (NVM) and use it as the swap area. Utilizing NVMs byte-addressability, we propose DR which guarantees zero memory copy for read-only requests when accessing a page in swap area. To better understand the energy consumption of swapping, we build an energy model to analyze the energy consumption of different paging architectures. We evaluate DR. Swap based on the Google Nexus 5 smartphone, experimental results show that our technique can reduce more than 50% energy consumption compared to DRAM backed swapping.

Participatory Sensing Meets Opportunistic Sharing: Automatic Phone-to-Phone Communication in Vehicles

This paper explores direct phone-to-phone communication (via WiFi interface) among vehicles to support participatory sensing applications. Sensing data usually contains location, speed, and fuel consumption of the car, and has a long time delay between collected and transferred to the server. Direct communication among phones aboard is important in reducing data transfer delay time and sharing participatory sensing information in an inexpensive manner. We design a practical and optimized communication mechanism for direct phone-to-phone data transfer among phones aboard that strategically enables phone-to-phone and/or phone-to-WiFiAP communications by optimally toggling the phones between the normal client and the hotspot modes. We take advantage of the WiFi hotspot functionality on smartphones, and hence require neither involvement of participants nor changes to existing wireless infrastructure and protocols. An analytical model is established to optimize toggling between client and hotspot modes for optimal system efficiency. We fully implement this system on off-the-shelf Google Galaxy Nexus and Nexus S phones. Through a 35-vehicle two-month deployment study, as well as simulation experiments using the real-world T-drive 9,211-taxicab dataset, we show that our solution significantly reduces data transfer delay time and maintains over 80 percent system efficiency under varying system parameters.

Kernelized correlation tracker on smartphones

This paper shows the implementation of a KC tracker (high-speed kernelized correlation tracker) on an Android smartphone. The image processing part is implemented with the Android-NDK in C/C++. Some parts of the tracking algorithm, which can be parallelized very well, are partitioned and calculated on the GPU with OpenGL ES and OpenCL. Other parts, such as the Discrete Fourier Transform (DFT), are calculated on the CPU (partly with the ARM-NEON features). With these hardware acceleration steps we could reach real-time performance (at least 20–30 FPS) on up-to-date smartphones, such as Samsung Galaxy S4, S5 or Google Nexus 5.Beyond that, we present some new color features and compare their tracking quality to the HOG features using the KC tracker and show that their tracking quality is mostly superior compared to the HOG features.If an object gets lost by the tracker which is the case e.g. if the object is totally hidden or outside the viewing range, there should be a possibility to perform a re-detection. In this paper, we show a basic approach to determine the tracking quality and search for the tracking object in the entire images of the subsequent video-frames.

MARS: Mobile Application Relaunching Speed-Up through Flash-Aware Page Swapping

The approach for fast application relaunching on the current Android system is to cache background applications in memory. This mechanism is limited by the available memory size. In addition, the application state may not be easily recovered. We propose a prototype system, MARS, to enable page swapping and cache more applications. MARS can speed up the application relaunching and restore the application state. As a new page swapping design for optimizing application relaunching, MARS isolates Android runtime Garbage Collection (GC) from page swapping for compatibility and employs several flash-aware techniques for swap-in speedup. Two main components of MARS are page slot allocation and read/write control. Page slot allocation reorganizes page slots in swap area to produce sequential reads and improve the performance of swap-in. Read/Write control addresses the read/write interference issue by reducing concurrent and extra internal writes. Compared to the conventional Linux page swapping, these two components can scale up the read bandwidth up to about 3.8 times. Application tests on a Google Nexus 4 phone show that MARS reduces the launching time of applications by 50 - 80 percent. The modified page swapping mechanism can outperform the conventional Linux page swapping up to four times.

Videolaryngoscopy using an Android smartphone: A direct digital technique.

Sir, Direct laryngoscopy has been the standard of care in securing the airway, in both routine and emergent cases. Videolaryngoscopy, introduced about a decade earlier aims to overcome the limitations of direct laryngoscopy. Some of the disadvantages of direct laryngoscopy include the need for an optimal line of sight for glottic visualisation, greater cervical spine movement during laryngoscopy, a lack of visual feedback for other healthcare providers during resuscitation and for novices undergoing training in laryngoscopy, and lack of image archiving capability.[1,2] Despite the advantages, the high initial cost of investment remains a deterrent for the widespread adoption of videolaryngoscopy over direct laryngoscopy.[3] Videolaryngoscopy may be done inexpensively. The use of complementary metal oxide semiconductor sensors attached to the blade of a conventional Macintosh laryngoscope should suffice. The authors, in an earlier study, demonstrated the use of a low cost universal serial bus (USB) endoscope camera assembled on a Macintosh laryngoscope, to perform videolaryngoscopy.[4] The device used the video processing capabilities of a personal computer to display real time video. The evolution of this technique could then be to utilise the high quality display and graphical processing present in the ubiquitous smartphone, keeping the initial and recurring costs of the technique low. For technical reasons, the use of smartphones for displaying the video stream from an USB endoscope camera is not simple. We chose the Android smartphone operating system (OS) V3.1 or higher (checked using “about device” menu of the OS), that supports the USB on-the-go (OTG) host function. This feature allows direct interfacing of the USB camera with the mobile device using an USB OTG cable. Apple OS devices do not support a similar capability due to restrictions in its use of its host-capable USB port. Initial attempts at obtaining a video stream were unsuccessful, due to lack of inbuilt USB video class drivers in the Android OS kernel of several mobile devices. We attempted to recreate this functionality with open source custom software that processes the USB video stream directly in Google Nexus 2012 Android mobile device.[5] However, a high quality video recording was obtained in most of the mobile devices that we tested, by using “CameraFi” (Vault Micro Inc., Seoul, Korea) app freely downloaded from the online Google Play Store at https://play.google.com/store/apps/details?id=com.vaultmicro. CameraFi. The USB endoscope camera was disinfected prior to use, assembled and upright orientation done as described in our earlier study.[4] The USB camera was fixed about 40 mm from the tip of a Macintosh blade (size 3 or 4) using clean adhesive tape (Durapore, 3M Inc., USA). The application supported capture of high quality images as well as real time video capture Figure 1. The camera required minimal electrical power supplied through the USB port of the mobile device. The electrical safety of the camera was ensured due its completely insulated, waterproof casing. We had successfully tested this assembly for videolaryngoscopy in an adult mannequin. The mouth opening required by the USB camera-blade assembly was the same as that for a conventional Macintosh blade. Figure 1 Real time video capture from universal serial bus endoscope camera using CameraFi app in Android operating system This technique used readily available components with minor modification of a conventional laryngoscope. The technique involves direct digital transmission of the image to a smartphone through its USB port, without the use of cumbersome, optical-based smartphone adapters such as the Airtraq Universal Phone adapter (Prodol Meditec S.A, Vizcaya, Spain) that may affect image quality. Newer USB endoscope cameras of 5.5 mm diameter, 2 m cable length are available from online retailers, which are inexpensive, costing <10$, for example, at http://www.tomtop.com/product?q=endoscope+borescope. Future efforts would involve developing medical grade, 3D-printed laryngoscope conduits that encase the USB camera, conforming to all regulatory standards. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

A Lightweight Virtualization Solution for Android Devices

Mobile virtualization has emerged fairly recently and is considered a valuable way to mitigate security risks on Android devices. However, major challenges in mobile virtualization include runtime, hardware, resource overhead, and compatibility. In this paper, we propose a lightweight Android virtualization solution named Condroid , which is based on container technology. Condroid utilizes resource isolation based on namespaces feature and resource control based on cgroups feature. By leveraging them, Condroid can host multiple independent Android virtual machines on a single kernel to support mutilple Android containers. Furthermore, our implementation presents both a system service sharing mechanism to reduce memory utilization and a filesystem sharing mechanism to reduce storage usage. The evaluation results on Google Nexus 5 demonstrate that Condroid is feasible in terms of runtime, hardware resource overhead, and compatibility. Therefore, we find that Condroid has a higher performance than other virtualization solutions.

A Methodology to Model the Execution of Communication Software for Accurate Network Simulation

Network simulation is commonly used to evaluate the performance of distributed systems, but these approaches do not account for the performance impact that protocol execution on nodes has on performance, which can be significant. We provide a methodology to extract from real devices models of communication software execution that can be used to extend network simulators to improve their accuracy. The models are obtained by instrumenting the target devices to obtain the events necessary to describe software execution. We specify which events must be captured, how to capture them, and how to transform the event traces into models that can be used to extend network simulators. The obtained models are based on high-level abstractions that can be used to describe the execution of a wide range of communication software, and the design principles to extend network simulators are not restricted to any specific network simulator. The same model of communication software execution can be used without modification in all discrete event-based network simulators that are extended according to our principles. The models are represented in a human-readable format that is suitable for modification and can therefore be used to predict how software modifications impact performance. We evaluate our models with two proof-of-concept extensions of Ns-3 that execute the models of two modern smartphones: the Google Nexus One (GN1) and the Nokia N900. We measure the accuracy of our models by comparing results from real experiments with those from simulations with our models and analyze the simulation overhead of our approach.

Face Spoof Detection With Image Distortion Analysis

Automatic face recognition is now widely used in applications ranging from deduplication of identity to authentication of mobile payment. This popularity of face recognition has raised concerns about face spoof attacks (also known as biometric sensor presentation attacks), where a photo or video of an authorized person’s face could be used to gain access to facilities or services. While a number of face spoof detection techniques have been proposed, their generalization ability has not been adequately addressed. We propose an efficient and rather robust face spoof detection algorithm based on image distortion analysis (IDA). Four different features (specular reflection, blurriness, chromatic moment, and color diversity) are extracted to form the IDA feature vector. An ensemble classifier, consisting of multiple SVM classifiers trained for different face spoof attacks (e.g., printed photo and replayed video), is used to distinguish between genuine (live) and spoof faces. The proposed approach is extended to multiframe face spoof detection in videos using a voting-based scheme. We also collect a face spoof database, MSU mobile face spoofing database (MSU MFSD), using two mobile devices (Google Nexus 5 and MacBook Air) with three types of spoof attacks (printed photo, replayed video with iPhone 5S, and replayed video with iPad Air). Experimental results on two public-domain face spoof databases (Idiap REPLAY-ATTACK and CASIA FASD), and the MSU MFSD database show that the proposed approach outperforms the state-of-the-art methods in spoof detection. Our results also highlight the difficulty in separating genuine and spoof faces, especially in cross-database and cross-device scenarios.

Validating the Accuracy of Reaction Time Assessment on Computer-Based Tablet Devices.

Computer-based assessment has evolved to tablet-based devices. Despite the availability of tablets and "apps," there is limited research validating their use. We documented timing delays between stimulus presentation and (simulated) touch response on iOS devices (3rd- and 4th-generation Apple iPads) and Android devices (Kindle Fire, Google Nexus, Samsung Galaxy) at response intervals of 100, 250, 500, and 1,000 milliseconds (ms). Results showed significantly greater timing error on Google Nexus and Samsung tablets (81-97 ms), than Kindle Fire and Apple iPads (27-33 ms). Within Apple devices, iOS 7 obtained significantly lower timing error than iOS 6. Simple reaction time (RT) trials (250 ms) on tablet devices represent 12% to 40% error (30-100 ms), depending on the device, which decreases considerably for choice RT trials (3-5% error at 1,000 ms). Results raise implications for using the same device for serial clinical assessment of RT using tablets, as well as the need for calibration of software and hardware.