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Crowd-ML: A Privacy-Preserving Learning Framework for a Crowd of Smart Devices  [PDF]
Jihun Hamm,Adam Champion,Guoxing Chen,Mikhail Belkin,Dong Xuan
Computer Science , 2015,
Abstract: Smart devices with built-in sensors, computational capabilities, and network connectivity have become increasingly pervasive. The crowds of smart devices offer opportunities to collectively sense and perform computing tasks in an unprecedented scale. This paper presents Crowd-ML, a privacy-preserving machine learning framework for a crowd of smart devices, which can solve a wide range of learning problems for crowdsensing data with differential privacy guarantees. Crowd-ML endows a crowdsensing system with an ability to learn classifiers or predictors online from crowdsensing data privately with minimal computational overheads on devices and servers, suitable for a practical and large-scale employment of the framework. We analyze the performance and the scalability of Crowd-ML, and implement the system with off-the-shelf smartphones as a proof of concept. We demonstrate the advantages of Crowd-ML with real and simulated experiments under various conditions.
Line Spectral Frequency-based Noise Suppression for Speech-Centric Interface of Smart Devices
JANG, G. J.,PARK, J. S.,KIM, J. H.,SEO, Y. H.
Advances in Electrical and Computer Engineering , 2011, DOI: 10.4316/aece.2011.04001
Abstract: This paper proposes a noise suppression technique for speech-centric interface of various smart devices. The proposed method estimates noise spectral magnitudes from line spectral frequencies (LSFs), using the observation that adjacent LSFs correspond to peak frequencies of spectrum, whereas isolated LSFs are close to flattened valley frequencies retaining noise components. Over a course of segmented time frames, the logarithms of spectral magnitudes at respective LSFs are computed, and their distribution is then modeled by the Rayleigh probability density function. The standard deviation from the Rayleigh function approximates the noise spectral magnitude. The model is updated at every frame in an online manner so that it can deal with real-time inputs. Once the noise spectral magnitude is estimated, a time-domain Wiener filter is derived for the suppression of the estimated noise spectral magnitude, and this is then applied to the input noisy speech signals. Our proposed approach operates well on most smart devices owing to its low computational complexity and real-time implementation. Speech recognition experiments, conducted to evaluate the proposed technique, show that our method exhibits superior performance, with less distortion of original speech, when compared to conventional noise suppression techniques.
Fingerprinting Smart Devices Through Embedded Acoustic Components  [PDF]
Anupam Das,Nikita Borisov,Matthew Caesar
Computer Science , 2014,
Abstract: The widespread use of smart devices gives rise to both security and privacy concerns. Fingerprinting smart devices can assist in authenticating physical devices, but it can also jeopardize privacy by allowing remote identification without user awareness. We propose a novel fingerprinting approach that uses the microphones and speakers of smart phones to uniquely identify an individual device. During fabrication, subtle imperfections arise in device microphones and speakers which induce anomalies in produced and received sounds. We exploit this observation to fingerprint smart devices through playback and recording of audio samples. We use audio-metric tools to analyze and explore different acoustic features and analyze their ability to successfully fingerprint smart devices. Our experiments show that it is even possible to fingerprint devices that have the same vendor and model; we were able to accurately distinguish over 93% of all recorded audio clips from 15 different units of the same model. Our study identifies the prominent acoustic features capable of fingerprinting devices with high success rate and examines the effect of background noise and other variables on fingerprinting accuracy.
From MEMS Devices to Smart Integrated Systems  [PDF]
O. Soeraasen,J. E. Ramstad
Computer Science , 2008,
Abstract: The smart integrated systems of tomorrow would demand a combination of micromechanical components and traditional electronics. On-chip solutions will be the ultimate goal. One way of making such systems is to implement the mechanical parts in an ordinary CMOS process. This procedure has been used to design an oscillator consisting of a resonating cantilever beam and a CMOS Pierce feedback amplifier. The resonating frequency is changed if the beam is bent by external forces. The paper describes central features of this procedure and highlights the design considerations for the CMOS-MEMS oscillator. The circuit is used as an example of a "VLSI designer" way of making future integrated micromechanical and microelectronic systems on-chip. The possibility for expansion to larger systems is reviewed.
Smart Deferral of Messages for Privacy Protection in Online Social Networks  [PDF]
Javier Parra-Arnau,Félix Gómez Mármol,David Rebollo-Monedero,Jordi Forné
Computer Science , 2014,
Abstract: Despite the several advantages commonly attributed to social networks such as easiness and immediacy to communicate with acquaintances and friends, significant privacy threats provoked by unexperienced or even irresponsible users recklessly publishing sensitive material are also noticeable. Yet, a different, but equally hazardous privacy risk might arise from social networks profiling the online activity of their users based on the timestamp of the interactions between the former and the latter. In order to thwart this last type of commonly neglected attacks, this paper presents a novel, smart deferral mechanism for messages in online social networks. Such solution suggests intelligently delaying certain messages posted by end users in social networks in a way that the observed online-activity profile generated by the attacker does not reveal any time-based sensitive information. Conducted experiments as well as a proposed architecture implementing this approach demonstrate the suitability and feasibility of our mechanism.
Smart portable rehabilitation devices
Constantinos Mavroidis, Jason Nikitczuk, Brian Weinberg, Gil Danaher, Katherine Jensen, Philip Pelletier, Jennifer Prugnarola, Ryan Stuart, Roberto Arango, Matt Leahey, Robert Pavone, Andrew Provo, Dan Yasevac
Journal of NeuroEngineering and Rehabilitation , 2005, DOI: 10.1186/1743-0003-2-18
Abstract: In this paper we present several new advancements in the area of smart rehabilitation devices that have been developed by the Northeastern University Robotics and Mechatronics Laboratory. They are all compact, wearable and portable devices and boast re-programmable, real time computer controlled functions as the central theme behind their operation. The sensory information and computer control of the three described devices make for highly efficient and versatile systems that represent a whole new breed in wearable rehabilitation devices. Their applications range from active-assistive rehabilitation to resistance exercise and even have applications in gait training. The three devices described are: a transportable continuous passive motion elbow device, a wearable electro-rheological fluid based knee resistance device, and a wearable electrical stimulation and biofeedback knee device.Laboratory tests of the devices demonstrated that they were able to meet their design objectives. The prototypes of portable rehabilitation devices presented here did demonstrate that these concepts are capable of the performance their commercially available but non-portable counterparts exhibit.Smart, portable devices with the ability for real time monitoring and adjustment open a new era in rehabilitation where the recovery process could be dramatically improved.During the last several decades a great deal of work has been undertaken for developing devices to accelerate recovery from injuries, operations and other complications. Many successful devices and methods have come out of this work. This included a general division of the recovery process into several phases.In the early stages of therapy, passive rehabilitation is often a preferred method for reducing swelling, alleviating pain, and restoring range of motion. This consists of moving the limb with the muscles remaining passive and often involves devices such as Continuous Passive Motion (CPM) machines. The next stage of rehab
Many-core applications to online track reconstruction in HEP experiments  [PDF]
S. Amerio,D. Bastieri,M. Corvo,A. Gianelle,W. Ketchum,T. Liu,A. Lonardo,D. Lucchesi,S. Poprocki,R. Rivera,L. Tosoratto,P. Vicini,P. Wittich
Computer Science , 2013, DOI: 10.1088/1742-6596/513/1/012002
Abstract: Interest in parallel architectures applied to real time selections is growing in High Energy Physics (HEP) experiments. In this paper we describe performance measurements of Graphic Processing Units (GPUs) and Intel Many Integrated Core architecture (MIC) when applied to a typical HEP online task: the selection of events based on the trajectories of charged particles. We use as benchmark a scaled-up version of the algorithm used at CDF experiment at Tevatron for online track reconstruction - the SVT algorithm - as a realistic test-case for low-latency trigger systems using new computing architectures for LHC experiment. We examine the complexity/performance trade-off in porting existing serial algorithms to many-core devices. Measurements of both data processing and data transfer latency are shown, considering different I/O strategies to/from the parallel devices.
Personal Information Privacy Settings of Online Social Networks and their Suitability for Mobile Internet Devices  [PDF]
Nahier Aldhafferi,Charles Watson,A. S. M Sajeev
Computer Science , 2013, DOI: 10.5121/ijsptm.2013.2201
Abstract: Protecting personal information privacy has become a controversial issue among online social network providers and users. Most social network providers have developed several techniques to decrease threats and risks to the users privacy. These risks include the misuse of personal information which may lead to illegal acts such as identity theft. This study aims to measure the awareness of users on protecting their personal information privacy, as well as the suitability of the privacy systems which they use to modify privacy settings. Survey results show high percentage of the use of smart phones for web services but the current privacy settings for online social networks need to be improved to support different type of mobile phones screens. Because most users use their mobile phones for Internet services, privacy settings that are compatible with mobile phones need to be developed. The method of selecting privacy settings should also be simplified to provide users with a clear picture of the data that will be shared with others. Results of this study can be used to develop a new privacy system which will help users control their personal information easily from different devices, including mobile Internet devices and computers.
Smart Charging Technologies for Portable Electronic Devices  [PDF]
Stefan Hild,Sean Leavey,Christian Gr?f,Borja Sorazu
Computer Science , 2012,
Abstract: In this article we describe our efforts of extending demand-side control concepts to the application in portable electronic devices, such as laptop computers, mobile phones and tablet computers. As these devices feature built-in energy storage (in the form of batteries) and the ability to run complex control routines, they are ideal for the implementation of smart charging concepts. We developed a prototype of a smart laptop charger that controls the charging process depending on the locally measured frequency of the electricity grid. If this technique is incorporated into millions of devices in UK households, this will contribute significantly to the stability of the electricity grid, help to mitigate the power production fluctuations from renewable energy sources and avoid the high cost of building and maintaining conventional power plants as standby reserve.
poolMC: Smart pooling of mRNA samples in microarray experiments
Raghunandan M Kainkaryam, Angela Bruex, Anna C Gilbert, John Schiefelbein, Peter J Woolf
BMC Bioinformatics , 2010, DOI: 10.1186/1471-2105-11-299
Abstract: A theoretical framework to perform smart pooling of mRNA samples in microarray experiments was established and the software implementation of the pooling and decoding algorithms was developed in MATLAB. A proof-of-concept smart pooled experiment was performed using validated biological samples on commercially available gene chips. Differential-expression analysis of the smart pooled data was performed and compared against the unpooled control experiment.The theoretical developments and experimental demonstration in this paper provide a useful starting point to investigate smart pooling of mRNA samples in microarray experiments. Although the smart pooled experiment did not compare favorably with the control, the experiment highlighted important conditions for the successful implementation of smart pooling - linearity of measurements, sparsity in data, and large experiment size.Presently, pooling in microarray experiments refers to the act of mixing messenger RNA (mRNA) collected from several biological-replicate samples, before hybridization onto a microarray chip [1-6]. This form of pooling may be used to reduce biological variation, to lower costs by reducing the number of microarray chips used, and to overcome the problem of limited sample availability.In this paper, we describe a different pooling strategy; a smart pooling strategy based on compression algorithms from digital communication theory. The smart pooling strategy is applied to a large number of diverse biological samples, not necessarily biological replicates, which are pooled and tested on several microarray chips based on a pre-specified pooling design. The mathematical properties of smart pooling designs ensure that each sample is tested on multiple chips, but always in pools made up of a different set of samples, such that, data from all the chips taken together capture the same information as the standard one-sample-one-chip approach. Because of the convolution step involved in testing pools of sa
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