Browsing by Type "journal articles post-print"
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Item AuNPs‐HRP microneedle biosensor for ultrasensitive detection of hydrogen peroxide for organ preservation(Wiley Periodicals, 2018-10-16) Narayanan, Jeyaraman S.; Slaughter, GymamaThe preservation of tissues and organs for transplantation has garnered considerable attention due to the oxidative stress that arises from the excess of reactive oxygen species produced upon the removal of an organ from its native environment. Herein, gold nanoparticles (AuNPs)‐horseradish peroxidase (HRP) ultrasensitive microneedle biosensor is developed using a simple electrochemical method for the determination of H₂O₂. Tungsten microwire was homogenously modified with AuNPs via electrodeposition and 3‐mercaptopropionic acid (MPA) to form self‐assembled monolayers (SAMs) for the immobilization of HRP. The prepared AuNPs‐MPA electrode exhibited high electrocatalytic activity towards the reduction of H2O2. At an applied potential of −300 mV, the AuNPs‐HRP electrode yielded a linear ranges of 5 nM to 5 µM H₂O₂ (R = 0.999) and 1–5 mM H₂O₂ (R = 0.985) with a low detection limit of 800 pM and a sensitivity of 490.59 Ma/mM/cm² on average as the result of the strong synergistic effect between HRP and AuNPs. Common interfering species such as ascorbic acid, acetaminophen, glucose and uric acid were effectively eliminated. In addition, the fabricated biosensor exhibited high electrocatalytic activity for the determination of H₂O₂ in real time from rat abdominal wall perfused with histidine–tryptophan–ketoglutarate solution.Item Data Integrity Attack in Smart Grid: Optimized Attack to Gain Monetary Economic Profit(IET, 2016-12-08) Khanna, Kush; Panigrahi, Bijaya Ketan; Joshi, AnupamThe cyber-physical security of power grid has gained more attention in the research community due to integration of information and communication technologies. Smart meters are vulnerable to cyber-threats and if the security of these meters are compromised then the consequence can be devastating. It is necessary to study all the possible impacts that cyber-attacks may have on the power grid in order to make the grid immune to such intrusions. With more and more renewable energy and information technology integration, electricity companies must make sure that they are not paying for spoofed electricity. In this paper, we are proposing a new attack through which a private actor injects false data into multiple meters to deceive the system operator with new modified system state to gain momentary profit by projecting higher energy export than actual. Assuming real power injection measurement to be secured at all the generator buses, the attack is simulated for IEEE 14 bus and IEEE 30 bus system. From the system operator’s perspective, the most vulnerable buses are obtained and ranked based on the severity and minimum set of meters required to launch an attackItem Improving cloud optical property retrievals for partly cloudy pixels using coincident higher‐resolution single band measurements: A feasibility study using ASTER observations(American Geophysical Union, 2018-10-09) Werner, F.; Zhang, Z.; Wind, G.; Miller, D.J.; Platnick, S.; Girolamo, L. DiClear‐sky contamination is a challenging and long‐lasting problem for cloud optical thickness (τ) and effective droplet radius (rₑ𝒻𝒻) retrievals using passive satellite sensors. This study explores the feasibility of improving both _ and rₑ𝒻𝒻retrievals for partly cloudy (PCL) pixels by using available subpixel samples in a visible to near‐infrared (VNIR) band, which many satellite sensors offer. Data is provided by high‐resolution reflectance (R) observations and cloud property retrievals by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at horizontal resolutions between 30‐960m. For partly cloudy 960‐m observations, the clear‐sky component of the pixels induces significant underestimations of up to 58% for τ, while overestimations in rₑ𝒻𝒻 can exceed 41%. This yields underestimations in the derived liquid water path and cloud droplet number concentration of up to 68% and 72%, respectively. By means of three different assumptions it is shown that subpixel R observations in the VNIR can be used to estimate higher‐resolution R for the second band in the retrieval scheme, as well as the subpixel cloud cover. The estimated values compare well to actually observed ASTER results and are used to retrieve cloud properties, which are unbiased by the clear‐sky component of PCL pixels. While the presented retrieval approach is only evaluated for marine boundary layer clouds, it is computationally efficient and can be easily applied to observations from different imagers. As an example, the PCL retrieval scheme is applied to data by the Moderate Resolution Imaging Spectroradiometer (MODIS), where similar biases for PCL pixels are observed.Item The Law, Policy, and Portrayal of Zero Tolerance School Discipline(SAGE journals, 2017-02-13) Curran, F. ChrisReform of school zero tolerance discipline policies is complicated by a lack of systematic evidence on the prevalence and characteristics of such policies. Through document analysis, this study compares explicit zero tolerance laws/policies and mandatory expulsion laws/policies across the domains of federal law, state law, district policy, and media portrayal. Results suggest that explicit zero tolerance laws and policies are rare, appearing in less than one in seven states or districts, whereas mandatory expulsion laws/policies are more common. Districts serving high proportions of minority students as well as districts consisting only of charter schools are more likely to have mandatory expulsion policies for certain offenses. Additionally, district zero tolerance policies apply to a broader set of offenses than state laws. Finally, state and district laws/policies tend to not apply to minor offenses to the degree suggested by media coverage. Implications for policy and practice are discussed.Item Mapping pine plantations in the southeastern U.S. using structural, spectral, and temporal remote sensing data(Elsevier Inc., 2018-10) Fagan, M. E.; Morton, D.C.; Cook, B.D.; Masek, J.; Zhao, F.; Nelson, R.F.; Huang, C.The southeastern U.S. produces the most industrial roundwood in the U.S. each year, largely from commercial pine plantations. The extent of plantation forests and management dynamics can be difficult to ascertain from periodic forest inventories, yet short-rotation tree plantations also present challenges for remote sensing. Here, we integrated spectral, temporal, and structural information from airborne and satellite platforms to distinguish pine plantations from natural forests and evaluate the contribution from planted forests to regional forest cover in the southeastern U.S. Within flight lines from NASA Goddard's Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager, lidar metrics of forest structure had the highest overall accuracy for pine plantations among single-source classifications (90%), but the combination of spectral and temporal metrics from Landsat generated comparable accuracy (91%). Combined structural, temporal, and spectral information from G-LiHT and Landsat had the highest accuracy for plantations (92%) and natural forests (88%). At a regional scale, classifications using Landsat spectral and temporal metrics had between 74 and 82% mean class accuracy for plantations. Regionally, plantations accounted for 28% of forest cover in the southeastern U.S., a result similar to plot-based estimates, albeit with greater spatial detail. Regional maps of plantation forests differed from existing map products, including the National Land Cover Database. Combining plantation extent in 2011 with Landsat-based forest change data identified strong regional gradients in plantation dynamics since 1985, with distinct spatial patterns of rotation age (east-west) and plantation expansion (interior). Our analysis demonstrates the potential to improve the characterization of dynamic land cover classes, including economically important timber plantations, by integrating diverse remote sensing datasets. Critically, multi-source remote sensing provides an approach to leverage periodic forest inventory data for annual monitoring of managed forest landscapes.Item MCTS: Multi-Channel Transmission Simultaneously using Non-Feedback Fountain Code(IEEE, 2018-10-08) Liu, Jianhang; Wang, Shuqing; Li, Shibao; Cui, Xuerong; Pan, Yan; Zhu, TingData dissemination is an essential application in IoT network. It is generally relayed hop by hop due to the limitation of the communication distance of IoT devices. However, multi-hop transmission increases dissemination time, especially in a low duty-cycle network. Channel contention is another factor result in long delay, because most of IoT devices and WiFi equipment work within the same bandwidth (2.4G Hz). To reduce transmission delay of data dissemination, our group proposes a method of Multi-Channel Transmission Simultaneously using no-feedback fountain code (MCTS). Instead of terminating sending data by feedback as traditional fountain code protocol, in the MCTS, the sink node pours a certain amount of packets into the network according to the distance of object nodes to guarantee reliable transmission. By making use of channel encoding, the data to ZigBee nodes can be carried by some subcarriers of WiFi in multi ZigBee channels simultaneously when WiFi sends itself data. This method technically avoids the delay from channel contention. Compared with flooding method, the delay of the MCTS sending data from the sink node to all ZigBee nodes is decreased to 1/4.Item Platys: From Position to Place- Oriented Mobile Computing(AAAI Press, 2015-06-01) Zavala, Laura; Murukannaiah, Pradeep K.; Poosamani, Nithyananthan; Finin, Tim; Joshi, Anupam; Rhee, Injong; Singh, MunindarThe Platys project focuses on developing a high-level, semantic notion of location called place. A place, unlike a geospatial position, derives its meaning from a user's actions and interactions in addition to the physical location where it occurs. Our aim is to enable the construction of a large variety of applications that take advantage of place to render relevant content and functionality and, thus, improve user experience. We consider elements of context that are particularly related to mobile computing. The main problems we have addressed to realize our place-oriented mobile computing vision are representing places, recognizing places, and engineering place-aware applications. We describe the approaches we have developed for addressing these problems and related subproblems. A key element of our work is the use of collaborative information sharing where users' devices share and integrate knowledge about places. Our place ontology facilitates such collaboration. Declarative privacy policies allow users to specify contextual features under which they prefer to share or not share their information.Item Robust Semantic Text Similarity Using LSA, Machine Learning and Linguistic Resources(Springer, 2016-03-01) Kashyap, Abhay L.; Han, Lushan; Yus, Roberto; Sleeman, Jennifer; Satyapanich, Taneeya W.; Gandhi, Sunil R; Finin, TimSemantic textual similarity is a measure of the degree of semantic equivalence between two pieces of text. We describe the SemSim system and its performance in the *SEM 2013 and SemEval-2014 tasks on semantic textual similarity. At the core of our system lies a robust distributional word similarity component that combines latent semantic analysis and machine learning augmented with data from several linguistic resources. We used a simple term alignment algorithm to handle longer pieces of text. Additional wrappers and resources were used to handle task specific challenges that include processing Spanish text, comparing text sequences of different lengths, handling informal words and phrases, and matching words with sense definitions. In the *SEM 2013 task on Semantic Textual Similarity, our best performing system ranked first among the 89 submitted runs. In the SemEval-2014 task on Multilingual Semantic Textual Similarity, we ranked a close second in both the English and Spanish subtasks. In the SemEval-2014 task on Cross-Level Semantic Similarity, we ranked first in Sentence–Phrase, Phrase–Word, and Word–Sense subtasks and second in the Paragraph–Sentence subtask.Item Target-Based, Privacy Preserving, and Incremental Association Rule Mining(IEEE, 2015-09-30) Ahluwalia, Madhu V.; Gangopadhyay, Aryya; Chen, Zhiyuan; Yesha, YelenaWe consider a special case in association rule mining where mining is conducted by a third party over data located at a central location that is updated from several source locations. The data at the central location is at rest while that flowing in through source locations is in motion. We impose some limitations on the source locations, so that the central target location tracks and privatizes changes and a third party mines the data incrementally. Our results show high efficiency, privacy and accuracy of rules for small to moderate updates in large volumes of data. We believe that the framework we develop is therefore applicable and valuable for securely mining big data.