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The database-driven CRN has emerged as a promising solution for the spectrum scarcity issue. However, it also raises severe privacy concerns. Although there are some existing works on this topic, they are far from practical due to their restrict on particular database structures or extremely heavy computation and communication overhead. To address these issues, in this paper we develop two practical...
Modern organizations have collected vast amounts of data created by various systems and applications. Scientists and engineers have a strong desire to advance scientific and engineering knowledge from such massive data. QR factorization is one of the most fundamental mathematical tools for data analysis. However, conducting QR factorization of a matrix requires high computational complexity. This...
Cognitive Radio (CR) technology enables secondary users (SUs) to opportunistically access unused licensed spectrum owned by the primary users (PUs). Therefore, it can potentially significantly enhance communication capacity, and hence is very encouraging in aerospace communications and deserve thorough study. One of the key problems in cognitive aerospace communications is to determine spectrum availability...
We introduce a new family of minmax rank aggregation problems under two distance measures, the Kendall τ and the Spearman footrule. As the problems are NP-hard, we proceed to describe a number of constant-approximation algorithms for solving them. We conclude with illustrative applications of the aggregation methods on the Mallows model and genomic data.
Motivated by applications in social network community analysis, we introduce a new clustering paradigm termed motif clustering. Unlike classical clustering, motif clustering aims to minimize the number of clustering errors associated with both edges and certain higher order graph structures (motifs) that represent “atomic units” of social organizations. Our contributions are two-fold: We first introduce...
Cardiac arrhythmia is one of the most popular heart diseases that could lead to serious consequences. However, it is difficult for traditional electrocardiography (ECG) devices to capture arrhythmia symptoms during patients' hospital visits due to their intermittent occurrence nature. A few researchers recently propose continuous monitoring systems to address this problem. However, there are some...
One of the most salient features of smart city is to utilize big data to make our lives more convenient and more intelligent. This is usually achieved through solving a series of large-scale common and fundamental problems such as linear systems of equations, linear programs, etc. However, it is a very challenging task for resource-limited clients and small companies to solve such problems as the...
The database-driven cognitive radio network (CRN) is regarded as a promising way for a better utilization of spectrum resources without introducing the interference to primary users (PUs). However, there are some critical security and privacy issues in database-driven CRNs, which have been rarely discussed before. First of all, in order to retrieve the spectrum available information (SAI) of one's...
Web Phishing (Phishing) uses social engineering technique through short messages, emails and IMs to induce users to visit faked website to get sensitive information. With detecting method for phishing continually proposed and applied, the threat of web phishing has already reduced at a great extent. However, since each type of detection has limitation, phishing attackers can modify their strategies...
Demand response is designed to motivate electricity customers to modify their loads at critical time periods. The accurate estimation of impact of demand response signals to customers' consumption is central to any successful program. In practice, learning these response is nontrivial because operators can only send a limited number of signals. In addition, customer behavior also depends on a large...
Understanding consumer flexibility and behavior patterns is becoming increasingly vital to the design of robust and efficient energy saving programs. Accurate prediction of consumption is a key part to this understanding. Existing prediction methods usually have high relative errors that can be larger than 30%. In this paper, we explore sparsity in users' past data and relationship between different...
Demand response is designed to motivate electricity customers to modify their loads at critical time periods. Accurately estimating customers response to demand response signals is crucial to the success of these programs. In this paper, we consider signals in demand response programs as a treatment to the customers and estimate the average treatment effect. Specifically, we adopt the linear regression...
Crowdsourcing is a crowd-based outsourcing, where a requester (task owner) can outsource tasks to workers (public crowd). Recently, mobile crowdsourcing, which can leverage workers' data from smartphones for data aggregation and analysis, has attracted much attention. However, when the data volume is getting large, it becomes a difficult problem for a requester to aggregate and analyze the incoming...
NAND Flash has been widely used in consumer electronic devices, especially in SSDs (Solid State Disks). However, with the process scaling down, its inherent imperfection will be more severe, such as the limited endurance, asymmetric speed of programming and read. While a traditional cache mechanism can improve the performance partly, it can't reduce the unnecessary writes to NAND Flash resulting from...
With the rapid growth of the smart device market, associated security issues become more threatening and diverse than ever before. Due to the limitations of the traditional explicit authentication mechanisms (e.g., Password-based, biometrics), researchers and the industry have been promoting implicit authentication (IA) that does not require explicit user action and potentially enhances user experience...
The knowledge of the transportation mode, which is used by humans to complete the travels, especially the signal-mode segment directly related to travel behavior research, is critical for application such as travel behavior research, transport planning and traffic management. As application of GPS gradually increased, traffic managers obtain more and more travel data used by residents, which is more...
It has been widely recognized that structure information helps in sparse signal recovery. In this paper, a general form of block structure is considered, which is often referred to hierarchically sparse model. It is assumed that the unknown sparse signal can be divided into blocks, and a block contains either all zero components or a fraction of nonzero components. This model sits between the standard...
Many truthful spectrum auction schemes have been recently proposed to to ensure that the dominant strategy for bidders is to bid truthfully and thus protect the auctioneer's benefits. However, most of them assume the auctioneer is trustful and do not protect bidders' interests. An auctioneer can manipulate the winner's charging price if it knows bidders' bids. Thus, it is critical to protect bids...
Solving large-scale linear systems of equations (LSEs) is one of the most common and fundamental problems in big data. But such problems are often too expensive to solve for resource-limited users. Cloud computing has been proposed as a timely, efficient, and cost-effective way of solving such computing tasks. Nevertheless, one critical concern in cloud computing is data privacy. To be more prominent,...
Widely deployed mHealth systems enable patients to efficiently collect, aggregate, and report their Personal Health Records (PHRs), and then lower the costs and shorten their response time. The increasing needs of PHR monitoring require the involvement of healthcare companies that provide monitoring programs for analyzing PHRs. Unfortunately, healthcare companies are lack of the computation, storage,...
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