Improving the security of multiparty quantum secret splitting and quantum state sharing

A protocol for multiparty quantum secret splitting (MQSS) with an ordered $N$ Einstein-Podolsky-Rosen (EPR) pairs and Bell state measurements is recently proposed by Deng {\rm et al.} [Phys. Lett. A 354(2006)190]. We analyzed the security of the protocol and found that this protocol is secure for any other eavesdropper except for the agent Bob who adopts intercept-and-resend attack. Bob can obtain all the information of Alice's alone without being found. We also propose an improved version of the MQSS protocol.Comment: To appear in Phys. Lett.

Attack Detection in Sensor Network Target Localization Systems with Quantized Data

We consider a sensor network focused on target localization, where sensors measure the signal strength emitted from the target. Each measurement is quantized to one bit and sent to the fusion center. A general attack is considered at some sensors that attempts to cause the fusion center to produce an inaccurate estimation of the target location with a large mean-square-error. The attack is a combination of man-in-the-middle, hacking, and spoofing attacks that can effectively change both signals going into and coming out of the sensor nodes in a realistic manner. We show that the essential effect of attacks is to alter the estimated distance between the target and each attacked sensor to a different extent, giving rise to a geometric inconsistency among the attacked and unattacked sensors. Hence, with the help of two secure sensors, a class of detectors are proposed to detect the attacked sensors by scrutinizing the existence of the geometric inconsistency. We show that the false alarm and miss probabilities of the proposed detectors decrease exponentially as the number of measurement samples increases, which implies that for sufficiently large number of samples, the proposed detectors can identify the attacked and unattacked sensors with any required accuracy

More Robust Spatial Sampling Strategies for Non-motorized Traffic

With the widespread promotion of New Urbanism and Smart Growth there is an assumption that levels of non-motorized traffic will increase. However, planners and analysts for non-motorized transportation modes still rely on very limited data resources and therefore are limited in identifying demand patterns and moving forward with more productive management and planning schemes. In this study, we utilized continuous non-motorized traffic counts collected along four share use paths in Chittenden County, Vermont and analyzed the association between hourly (volume percentages of daily total) distribution patterns at each count station and land uses in the adjacent areas. The findings herein show the linkage is not as evident as expected between surrounding land use and the hourly patterns of the counts gathered, which is likely due to the insufficient diversity of the land use patterns around the count stations. Therefore, a dire need for the development of more robust sampling strategies are essential to obtain counts efficiently that can extrapolate short period counts into region-wide travel estimates. This study proposes a spatial-based clustering analysis to identify five land use categories to assist planning practitioners in selecting sampling locations that are representative for generating consistent nonmotorized traffic counts for entire network

Scheme for implementing quantum information sharing via tripartite entangled state in cavity QED

We investigate economic protocol to securely distribute and reconstruct a single-qubit quantum state between two users via a tripartite entangled state in cavity QED. Our scheme is insensitive to both the cavity decay and the thermal field.Comment: Final version to appear in Physica

Multiparty quantum secret sharing of secure direct communication

Based on the two-step protocol [Phys. Rev. A68(03)042317], we propose a $(n,n)$-threshold multiparty quantum secret sharing protocol of secure direct communication. In our protocol only all the sharers collaborate can the sender's secure direct communication message be extracted. We show a variant version of this protocol based on the variant two-step protocol. This variant version can considerably reduce the realization difficulty in experiment. In contrast to the use of multi-particle GHZ states in the case that the sharer number is larger than 3, the use and identification of Bell states are enough in our two protocols disregarding completely the sharer number, hence, our protocols are more feasible in technique

Lance-Adams Syndrome

Lance-Adams syndrome (LAS) is a rare complication of successful cardiopulmonary resuscitation and is often accompanied by action myoclonus. LAS is seen in patients who have undergone a cardiorespiratory arrest, later regained consciousness, and then developed myoclonus days or weeks after the event. Less than 150 cases of LAS have been reported in the worldwide medical literature. Here, we present a 32-year-old man who suffered from myoclonus after hypoxic brain damage due to hanging himself. This case was diagnosed as Lance-Adams syndrome according to a history of hypoxic brain damage, the clinical features, and the neuroimages such as brain SPECT. Making an early diagnosis and properly managing LAS is positively related to improving the patient's functional outcome. If patients have posthypoxic myoclonus after successful cardiopulmonary resuscitation, we should consider the diagnosis of LAS and initiate a proper rehabilitation program

An adaptive genetic algorithm for selection of blood-based biomarkers for prediction of Alzheimer's disease progression

Background: Alzheimer's disease is a multifactorial disorder that may be diagnosed earlier using a combination of tests rather than any single test. Search algorithms and optimization techniques in combination with model evaluation techniques have been used previously to perform the selection of suitable feature sets. Previously we successfully applied GA with LR to neuropsychological data contained within the The Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging, to select cognitive tests for prediction of progression of AD. This research addresses an Adaptive Genetic Algorithm (AGA) in combination with LR for identifying the best biomarker combination for prediction of the progression to AD. Results: The model has been explored in terms of parameter optimization to predict conversion from healthy stage to AD with high accuracy. Several feature sets were selected - the resulting prediction moddels showed higher area under the ROC values (0.83-0.89). The results has shown consistency with some of the medical research reported in literature. Conclusion: The AGA has proven useful in selecting the best combination of biomarkers for prediction of AD progression. The algorithm presented here is generic and can be extended to other data sets generated in projects that seek to identify combination of biomarkers or other features that are predictive of disease onset or progression