In this paper, we design an efficient P2P based mobile social network to facilitate contents search over mobile ad hoc networks. Social relation is established by considering both the locations and interests of mobile nodes. Mobile nodes with common interests and nearby locations are recommended as friends and are connected directly in a mobile social network. Contents search is handled by using social relationships of the mobile social network rather than those of the whole network. Since each mobile node manages only neighboring nodes that have common interests, network management overhead is reduced. Results of experiments have shown that our proposed method outperforms existing methods.

In this paper, we present an average-case efficient algorithm to resolve the problem of determining whether two Boolean functions in trace representation are identical. Firstly, we introduce a necessary and sufficient condition for null Boolean functions in trace representation, which can be viewed as a generalization of the well-known additive Hilbert-90 theorem. Based on this condition, we propose an algorithmic method with preprocessing to address the original problem. The worst-case complexity of the algorithm is still exponential; its average-case performance, however, can be improved. We prove that the expected complexity of the refined procedure is O(n), if the coefficients of input functions are chosen i.i.d. according to the uniform distribution over F2n; therefore, it performs well in practice.

Heap buffer overflow has been extensively studied for many years, but it remains a severe threat to software security. Previous solutions suffer from limitations in that: 1) Some methods need to modify the target programs; 2) Most methods could impose considerable performance overhead. In this paper, we present iCruiser, an efficient heap buffer overflow monitoring system that uses the multi-core technology. Our system is compatible with existing programs, and it can detect the heap buffer overflows concurrently. Compared with the latest heap protection systems, our approach can achieves stronger security guarantees. Experiments show that iCruiser can detect heap buffer overflow attacks effectively with a little performance overhead.

Cross-view action recognition is a challenging research field for human motion analysis. Appearance-based features are not credible if the viewpoint changes. In this paper, a new framework is proposed for cross-view action recognition by topic based knowledge transfer. First, Spatio-temporal descriptors are extracted from the action videos and each video is modeled by a bag of visual words (BoVW) based on the codebook constructed by the k-means cluster algorithm. Second, Latent Dirichlet Allocation (LDA) is employed to assign topics for the BoVW representation. The topic distribution of visual words (ToVW) is normalized and taken to be the feature vector. Third, in order to bridge different views, we transform ToVW into bilingual ToVW by constructing bilingual dictionaries, which guarantee that the same action has the same representation from different views. We demonstrate the effectiveness of the proposed algorithm on the IXMAS multi-view dataset.

We describe the recent progress on a Nb nine-layer fabrication process for large-scale single flux quantum (SFQ) circuits. A device fabricated in this process is composed of an active layer including Josephson junctions (JJ) at the top, passive transmission line (PTL) layers in the middle, and a DC power layer at the bottom. We describe the process conditions and the fabrication equipment. We use both diagnostic chips and shift register (SR) chips to improve the fabrication process. The diagnostic chip was designed to evaluate the characteristics of basic elements such as junctions, contacts, resisters, and wiring, in addition to their defect evaluations. The SR chip was designed to evaluate defects depending on the size of the SFQ circuits. The results of a long-term evaluation of the diagnostic and SR chips showed that there was fairly good correlation between the defects of the diagnostic chips and yields of the SRs. We could obtain a yield of 100% for SRs including 70,000JJs. These results show that considerable progress has been made in reducing the number of defects and improving reliability.

Superconducting Single-Flux-Quantum (SFQ) devices have been paid much attention as alternative devices for digital circuits, because of their high switching speed and low power consumption. For large-scale circuit design, the role of computer-aided design environment is significant. As the characteristics of the SFQ devices are different from conventional devices, a new design environment is required. In this paper, we propose a new timing-aware circuit description method which can be used for SFQ circuit design. Based on the description and the dedicated algorithms we have been developing for SFQ logic circuit design, we propose an integrated design flow for SFQ logic circuits. We have designed a circuit using our developed design tools along with the design flow and demonstrated the correct operation.

A self-powered urinary-incontinence sensor with a flexible wire-type urine-activated battery has been developed as an application for wireless biosensor networks. It is disposable and can be embedded in a diaper. The battery consists of two long film-type line electrodes printed on a flexible plastic sheet that abuts the absorbent material of the diaper. It conforms to the shape of the diaper when the diaper is worn. The stress produced by the curvature of the diaper presses the electrodes firmly against the diaper material, providing greater contact with any urine present. Thus, the battery generates more power than when it is flat, as in an unworn diaper. To verify the effectiveness of the battery, we fabricated a battery and a prototype sensor, which consists of an intermittent-power-supply circuit and a wireless transmitter, and embedded the battery in a diaper. The anode of the battery also acts as a wide ground plane for the antenna of the wireless transmitter, which radiates a large amount of power. When 80cc of urine is poured onto the diaper, the battery outputs a voltage of around 1V, which allows the sensor to transmit an ID signal over a distance of 5m every 40 seconds or so.

In the arsenal of resources for improving computer memory system performance, predictors have gained an increasing role in the past few years. They can suppress the latencies when accessing cache or main memory. In our previous work we proposed predictors that not only close the opened DRAM row but also predict the next row to be opened, hence the name ‘Complete Predictor’. It requires less than 10kB of SRAM for a 2GB SDRAM system. In this paper we evaluate how much additional hardware is needed and whether the activations of the predictors will slow down the DRAM controller.

The estimation of the power spectral density (PSD) of noise is crucial for retrieving speech in noisy environments. In this study, we propose a novel method for estimating the non-white noise PSD from noisy speech on the basis of a generalized gamma distribution and the minimum mean square error (MMSE) approach. Because of the highly non-stationary nature of speech, deriving its actual spectral probability density function (PDF) using conventional modeling techniques is difficult. On the other hand, spectral components of noise are more stationary than those of speech and can be represented more accurately by a generalized gamma PDF. The generalized gamma PDF can be adapted to optimally match the actual distribution of the noise spectral amplitudes observed at each frequency bin utilizing two real-time updated parameters, which are calculated in each frame based on the moment matching method. The MMSE noise PSD estimator is derived on the basis of the generalized gamma PDF and Gaussian PDF models for noise and speech spectral amplitudes, respectively. Combined with an improved Weiner filter, the proposed noise PSD estimate method exhibits the best performance compared with the minimum statistics, weighted noise estimation, and MMSE-based noise PSD estimation methods in terms of both subjective and objective measures.

Detection of human respiration and heartbeat is an essential demand in medical monitoring, healthcare vigilance, as well as in rescue activities after earthquakes. Radar is an important tool to detect human respiration and heartbeat. Compared to body-attached sensors, radar has the advantage of conducting detection without contacting the subject, which is favorable in practical usage. In this paper, we conduct fundamental studies on ultra-wideband (UWB) radar for detection of the respiration and heartbeat by computer simulations. The main achievement of our work is the development of a UWB radar simulation system. Using the developed simulation system, three UWB frequency bands, i.e., 3.4-4.8GHz, 7.25-10.25GHz, as well as 3.1-10.6GHz, are compared in terms of their respiration and heartbeat detection performance. Our results show that the first two bands present identical performance, while the third one presents much better performance. The effects of using multiple antennas are also evaluated. Our results show that increasing the number of antennas can steadily increase the detection ability.

Broadband wireless channels are frequency selective in nature. In this paper, a novel precoder with finite impulse response (FIR) structure is proposed to maximize the throughput of the multiple-input multiple-output (MIMO) frequency-selective multicast channel. An iteration mechanism is investigated to obtain the desired FIR precoding matrix. In the iterative process, two associated parameters, namely the innovation orientation and the iteration step size, are jointly derived by the convex optimization program and the traditional Gauss-Newton algorithm. Convergence and complexity analyses are presented, and the numerical simulations indicate that the proposed method outperforms the existing schemes in the moderate to high signal to noise ratio (SNR) regime.

The problem of resource allocation to minimize the outage probability for the secondary user (SU) groups in a cognitive radio (CR) multicast network is investigated. We propose a joint power and rate allocation scheme that provides significant improvement over the conventional scheme in terms of outage probability.

In this paper, we propose a new trusted modeling approach based on state graphs. We introduce a novel method of deriving state-layer from a system call sequence in terms of probability and statistics theory, and we identify the state sequence with the help of Hidden Markov Model (HMM). We generate state transition graph according to software executing process and pruning rules. Then, we separate local function graphs according to software specific functions by semantic analysis. The state-layer is a bridge between the basic behaviors and the upper layer functions of software to compensate semantic faults. In addition, a pruning strategy of formulating state graphs is designed to precisely describe each piece of software functions. Finally, a detecting system based on our model is proposed, and a case study of RSS software reveals how our system works. The results demonstrate that our trusted model describes software behaviors successfully and can well detect un-trust behaviors, anomaly behaviors, and illegal input behaviors.

Methods for in-network joins of sensing data with tuples, in partitioned condition tables stored in sensor nodes, have been studied for efficient event detection. A recently proposed method performs the join operation after distributing the tuples of a condition table evenly among homogeneous sensor nodes with the same storage capacity. In the method, the condition table is horizontally partitioned, and each partition is allocated to the corresponding node, along the path from the highest level to the leaf level. If the path length is larger than the number of partitions, the second round distribution of the partitions resumes from the node at the next level, and so on. Thus, the last node at each round can be assigned the partition that is smaller than the others, which would otherwise cause wasted internal fragmentation. Further, little research has been conducted on methods for the cases of heterogeneous sensor nodes with different available spaces, as well as the vertical partitioning of condition table. In this study, we propose a method of partitioning a condition table that utilizes the internal fragmentation, by treating the tuples of a condition table as a circular list. The proposed method is applicable to the case in which nodes have different available spaces. Furthermore, a new method for vertically partitioning a condition table is suggested. Experiments verify the reduction in the data transmission amount offered by the proposed methods, as compared to existing methods.

This paper proposes a new flash time-to-digital converter (TDC) circuit which exploits unbalanced arbiters to integrate intrinsic delay offsets into the decision elements. The unbalanced arbiters are implemented with cross-coupled standard NAND cells and the combination of the NAND cells decides the timing offset between two input signals. Simulations and measurements are conducted to validate the new circuit, which provides variable time difference ranges by controlling the slope of input signals. Since the proposed flash TDC uses only NAND cells in a standard cell library for the arbiters which easily enables the TDC to be used as a soft macro in a typical digital circuit design flow.

This paper proposes and investigates a multiplexing and error control scheme for Body Area Network (BAN). In February 2012, an international standard of WBAN, IEEE802.15.6, was published and it supports error control schemes. This standard also defines seven different QoS modes however, how to utilize them is not clearly specified. In this paper, an optimization method of the QoS is proposed. In order to utilize the QoS parameters, a multiplexing scheme is introduced. Then, the Hybrid ARQ in IEEE 802.15.6 is modified to employ decomposable codes and Weldon's ARQ protocol for more associations with channel conditions and required QoS. The proposed scheme has higher flexibility for optimizing the QoS parameters according to the required QoS.

For battery based real-time embedded systems, high performance to meet their real-time constraints and energy efficiency to extend battery life are both essential. Real-Time Dynamic Voltage Scaling (RT-DVS) has been a key technique to satisfy both requirements. This paper presents EccEDF (Enhanced ccEDF), an efficient algorithm based on ccEDF. ccEDF is one of the most simple but efficient RT-DVS algorithms. Its simple structure enables it to be easily and intuitively coupled with a real-time operating system without incurring any significant cost. ccEDF, however, overlooks an important factor in calculating the available slacks for reducing the operating frequency. It calculates the saved utilization simply by dividing the slack by the period without considering the time needed to run the task. If the elapsed time is considered, the maximum utilization saved by the slack on completion of the task can be found. The proposed EccEDF can precisely calculate the maximum unused utilization with consideration of the elapsed time while keeping the structural simplicity of ccEDF. Further, we analytically establish the feasibility of EccEDF using the fluid scheduling model. Our simulation results show that the proposed algorithm outperforms ccEDF in all simulations. A simulation shows that EccEDF consumes 27% less energy than ccEDF.

Suppose that each arc in a digraph D = (V,A) has two costs of non-negative integers, called a spine cost and a leaf cost. A caterpillar is a directed tree consisting of a single directed path (of spine arcs) and leaf vertices each of which is incident to the directed path by exactly one incoming arc (leaf arc). For a given terminal set K ⊆ V, we study the problem of finding a caterpillar in D such that it contains all terminals in K and its total cost is minimized, where the cost of each arc in the caterpillar depends on whether it is used as a spine arc or a leaf arc. In this paper, we first show that the problem is NP-hard for any fixed constant number of terminals with |K| ≥ 3, while it is solvable in polynomial time for at most two terminals. We also give an inapproximability result for any fixed constant number of terminals with |K| ≥ 3. Finally, we give a linear-time algorithm to solve the problem for digraphs with bounded treewidth, where the treewidth for a digraph D is defined as the one for the underlying graph of D. Our algorithm runs in linear time even if |K| = O(|V|), and the hidden constant factor of the running time is just a single exponential of the treewidth.

Presented is a new measuring and reconstruction framework of Compressed Sensing (CS), aiming at reducing the measurements required to ensure faithful reconstruction. A sparse vector is segmented into sparser vectors. These new ones are then randomly sensed. For recovery, we reconstruct these vectors individually and assemble them to obtain the original signal. We show that the proposed scheme, referred to as SegOMP, yields higher probability of exact recovery in theory. It is finished with much smaller number of measurements to achieve a same reconstruction quality when compared to the canonical greedy algorithms. Extensive experiments verify the validity of the SegOMP and demonstrate its potentials.