Computer-aided detection (CADe) and diagnosis (CAD) has been a rapidly growing, active area of research in medical imaging. Machine leaning (ML) plays an essential role in CAD, because objects such as lesions and organs may not be represented accurately by a simple equation; thus, medical pattern recognition essentially require “learning from examples.” One of the most popular uses of ML is the classification of objects such as lesion candidates into certain classes (e.g., abnormal or normal, and lesions or non-lesions) based on input features (e.g., contrast and area) obtained from segmented lesion candidates. The task of ML is to determine “optimal” boundaries for separating classes in the multi-dimensional feature space which is formed by the input features. ML algorithms for classification include linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), multilayer perceptrons, and support vector machines (SVM). Recently, pixel/voxel-based ML (PML) emerged in medical image processing/analysis, which uses pixel/voxel values in images directly, instead of features calculated from segmented lesions, as input information; thus, feature calculation or segmentation is not required. In this paper, ML techniques used in CAD schemes for detection and diagnosis of lung nodules in thoracic CT and for detection of polyps in CT colonography (CTC) are surveyed and reviewed.

This paper presents an adaptive cache architecture for wide-range reliable low-voltage operations. The proposed associativity-reconfigurable cache consists of pairs of cache ways so that it can exploit the recovery feature of the novel 7T/14T SRAM cell. Each pair has two operating modes that can be selected based upon the required voltage level of current operating conditions: normal mode for high performance and dependable mode for reliable low-voltage operations. We can obtain reliable low-voltage operations by application of the dependable mode to weaker pairs that cannot operate reliably at low voltages. Meanwhile leaving stronger pairs in the normal mode, we can minimize performance losses. Our chip measurement results show that the proposed cache can trade off its associativity with the minimum operating voltage. Moreover, it can decrease the minimum operating voltage by 140 mV achieving 67.48% and 26.70% reduction of the power dissipation and energy per instruction. Processor simulation results show that designing the on-chip caches using the proposed scheme results in 2.95% maximum IPC losses, but it can be chosen various performance levels. Area estimation results show that the proposed cache adds area overhead of 1.61% and 5.49% in 32-KB and 256-KB caches, respectively.

This paper presents a new technique to smooth speech feature vectors for text-independent speaker verification using an adaptive band-pass IIR filer. The filter is designed by considering the probability density of modulation-frequency components of an M-dimensional feature vector. Each dimension of the feature vector is processed and filtered separately. Initial filter parameters, low-cut-off and high-cut-off frequencies, are first determined by the global mean of the probability densities computed from all feature vectors of a given speech utterance. Then, the cut-off frequencies are adapted over time, i.e. every frame vector, in both low-frequency and high-frequency bands based also on the global mean and the standard deviation of feature vectors. The filtered feature vectors are used in a SVM-GMM Supervector speaker verification system. The NIST Speaker Recognition Evaluation 2006 (SRE06) core-test is used in evaluation. Experimental results show that the proposed technique clearly outperforms a baseline system using a conventional RelAtive SpecTrA (RASTA) filter.

To support mobility, multihoming, routing scalability, and security, there are a lot of proposals based on ID/Locator split approach not only for the current Internet but also for the future Internet. However, none of them meet the requirements for practical operation such as (1) support heterogeneous network layer protocols, (2) scalability of ID/Locator mapping system, (3) independence of mapping information management, and (4) avoidance of locator leakage beyond the administrative boundary. This paper proposes a network layer protocol called Z Network Protocol (ZNP) for the future Internet based on the clean slate approach. ZNP supports heterogeneity of network layer protocols by “Internetworking with a Common ID Space”. Its mapping systems meet the requirements (1)–(4) described above. For manipulating the mapping systems, Z Control Message Protocol (ZCMP) is designed. For resolving the link layer (L2) address from the ZNP Locator, Z Neighbor Discovery Protocol (ZNDP) is designed. We implement ZNP and ZNDP in the Linux kernel, ZCMP in the user space and measure the times needed for transmission, reception, forwarding, and locator conversion. The results show the practicability of ZNP as a network layer protocol for the future Internet.

We propose a method of the precise frequency tuning in millimeter wave (MMW) generation using a Mach-Zehnder-modulator-based flat comb generator (MZ-FCG). The MZ-FCG generates a flat comb signal where the comb spacing is exactly the same as the frequency of a radio-frequency signal driving the MZ-FCG. Two modes are extracted from the comb signal by using optical filters. One of them was modulated by a phase modulator, creating precisely frequency-controllable sidebands. In the experiment, typical phase modulation was used. By photomixing of the extracted two modes using a high-speed photodiode, MMW signals with precisely frequency-controllable sidebands are generated. By changing the modulation frequency, the frequency of MMW signals can be continuously tuned. In this scheme, there are two methods for the frequency tuning of MMW signals; one is a coarse adjustment which corresponds to the comb spacing, and the other is fine tuning by the phase-modulation. It was demonstrated that the intensity fluctuation of the upper sideband of the modulated MMW signal was less than 1 dB, and the frequency fluctuation was less than the measurement resolution (300 Hz).

Many people have faced mortal risks due to sudden disasters such as earthquakes, fires, and terrorisms, etc. In disasters where most people become panic, it is important to grasp disaster positions immediately and to find out some appropriate evacuation routes. We previously proposed the specific evacuation support system named as Emergency Rescue Evacuation Support System (ERESS). ERESS is based on Mobile Ad-hoc network (MANET) and aims to reduce the number of victims in panic-type disasters. This system consists of mobile terminals with advanced disaster recognition algorithm and various sensors such as acceleration, angular velocity and earth magnetism. However, the former ERESS did not have the clear criteria to detect the disaster outbreak. In this paper, we propose a new disaster recognition algorithm by Support Vector Machine (SVM) which is a kind of machine learning. In this method, an ERESS mobile terminal learns the behaviors of its holder by SVM. The SVM acquires the decision boundary based on the sensing data of the terminal holder, and it is judged whether to be the emergency. We show the validity of the proposed method by panic-type experiments.

BitTorrent is one of the most popular P2P file sharing applications worldwide. Each BitTorrent network is called a swarm, and millions of peers may join multiple swarms. However, there are many unreachable peers (NATed (network address translated), firewalled, or inactive at the time of measurement) in each swarm; hence, existing techniques can only measure a part of all the peers in a swarm. In this paper, we propose an improved measurement method for BitTorrent swarms that include many unreachable peers. In essence, NATed peers and those behind firewalls are found by allowing them to connect to our crawlers by actively advertising our crawlers' addresses. Evaluation results show that the proposed method increases the number of unique contacted peers by 112% compared to the conventional method. Moreover, the proposed method increases the total volume of downloaded pieces by 66%. We investigate the sampling bias among the proposed and conventional methods, and we find that different measurement methods yield significantly different results.

Chip Multiprocessors (CMPs) allow different applications to share LLC (Last Level Cache). Since each application has different cache capacity demand, LLC capacity should be partitioned in accordance with the demands. Existing partitioning algorithms estimate the capacity demand of each core by stack processing considering the LRU (Least Recently Used) replacement policy only. However, anti-thrashing replacement algorithms like BIP (Binary Insertion Policy) and BIP-Bypass emerged to overcome the thrashing problem of LRU replacement policy in a working set greater than the available cache size. Since existing stack processing cannot estimate the capacity demand with anti-thrashing replacement policy, partitioning algorithms also cannot partition cache space with anti-thrashing replacement policy. In this letter, we prove that BIP replacement policy is not feasible to stack processing but BIP-bypass is. We modify stack processing to accommodate BIP-Bypass. In addition, we propose the pipelined hardware of modified stack processing. With this hardware, we can get the success function of the various capacities with anti-thrashing replacement policy and assess the cache capacity of shared cache adequate to each core in real time.

We evaluated the single side-band phase noise of a 40 GHz beat signal generated by two free-running lasers. This allowed us to verify the utility of the two free-running lasers is verified as a light source for a next-generation radio-over-fiber system using frequency such as those in the millimeter-wave and terahertz bands. We also measured the phase noise of a frequency quadrupler using a Mach-Zehnder modulator for comparison. The phase noise of the two free-running lasers and the frequency quadrupler are -63.85 and -95.22 dBc/Hz at a 10 kHz offset frequency, respectively.

We propose a practical local and global path-planning algorithm for an autonomous vehicle or a car-like robot in an unknown semi-structured (or unstructured) environment, where obstacles are detected online by the vehicle's sensors. The algorithm utilizes a probabilistic method based on particle filters to estimate the dynamic obstacles' locations, a support vector machine to provide the critical points and Bezier curves to smooth the generated path. The generated path safely travels through various static and moving obstacles and satisfies the vehicle's movement constraints. The algorithm is implemented and verified on simulation software. Simulation results demonstrate the effectiveness of the proposed method in complicated scenarios that posit the existence of multi moving objects.

This paper deals with reflection and transmission of a TE plane wave from a one-dimensional random slab with slanted fluctuation by means of the stochastic functional approach. By starting with a generalized representation of the random wavefield from a two-dimensional random slab, and by using a manner for slanted anisotropic fluctuation, the corresponding random wavefield representation and its statistical quantities for one-dimensional cases are newly derived. The first-order incoherent scattering cross section is numerically calculated and illustrated in figures.

To improve Last-Level Cache (LLC) management, numerous approaches have been proposed requiring additional hardware budget and increased overhead. A number of these approaches even change the organization of the existing cache design. In this letter, we propose Adaptive Insertion and Promotion (AIP) policies based on Least Recently Used (LRU) replacement. AIP dynamically inserts a missed line in the middle of the cache list and promotes a reused line several steps left, realizing the combination of LRU and LFU policies deliberately under a single unified scheme. As a result, it benefits workloads with high locality as well as with many frequently reused lines. Most importantly, AIP requires no additional hardware other than a typical LRU list, thus it can be easily integrated into the existing hardware with minimal changes. Other issues around LLC such as scans, thrashing and dead lines are all explored in our study. Experimental results on the gem5 simulator with SPEC CUP2006 benchmarks indicate that AIP outperforms LRU replacement policy by an average of 5.8% on the misses per thousand instructions metric.

A semi-analytical method for a planar periodic array formed by a finite number of magnetized ferrite circular cylinders is presented using a model of layered cylindrical structures. The method uses the T-matrix approach and the extraction of the reflection and transmission matrices based on the cylindrical harmonic mode expansion. Based on the proposed method, plane wave scattering by the finite number of magnetized ferrite circular cylinders is numerically studied from the viewpoint of realization the electronic switching and electronic scanning effects by varying the applied magnetic field.

Memory deduplication improves the utilization of physical memory by sharing identical blocks of data. Although memory deduplication is most effective when many virtual machines with same operating systems run on a CPU, cross-user memory deduplication is a covert channel and causes serious memory disclosure attack. It reveals the existence of an application or file on another virtual machine. The covert channel is a difference in write access time on deduplicated memory pages that are re-created by Copy-On-Write, but it has some interferences caused by execution environments. This paper indicates that the attack includes implementation issues caused by memory alignment, self-reflection between page cache and heap, and run-time modification (swap-out, anonymous pages, ASLR, preloading mechanism, and self-modification code). However, these problems are avoidable with some techniques. In our experience on KSM (kernel samepage merging) with the KVM virtual machine, the attack could detect the security level of attacked operating systems, find vulnerable applications, and confirm the status of attacked applications.

Caches are one of the most leakage consuming components in modern processor because of massive amount of transistors. To reduce leakage power of caches, several techniques using power-gating (PG) were proposed. Despite of its high leakage saving, a side effect of PG for caches is the loss of data during a sleep. If useful data is lost in sleep mode, it should be fetched again from a lower level memory. This consumes a considerable amount of energy, which very unfortunately mitigates the leakage saving. This paper proposes a new PG scheme considering data retentiveness of SRAM. After entering the sleep mode, data of an SRAM cell is not lost immediately and is usable by checking the validity of the data. Therefore, we utilize data retentiveness of SRAM to avoid energy overhead for data recovery, which results in further chance of leakage saving. To check availability, we introduce a simple hardware whose overhead is ignorable. Our experimental result shows that utilizing data retentiveness saves up to 32.42% of more leakage than conventional PG.

This paper is concerned with coding theorems in the optimistic sense for separate coding of two correlated general sources X1 and X2. We investigate the achievable rate region Ropt (X1,X2) such that the decoding error probability caused by two encoders and one decoder can be arbitrarily small infinitely often under a certain rate constraint. We give an inner and an outer bounds of Ropt (X1,X2), where the outer bound is described by using new information-theoretic quantities. We also give two simple sufficient conditions under which the inner bound coincides with the outer bound.

Random telegraph noise (RTN) is a phenomenon that is considered to limit the reliability and performance of circuits using advanced devices. The time constants of carrier capture and emission and the associated change in the threshold voltage are important parameters commonly included in various models, but their extraction from time-domain observations has been a difficult task. In this study, we propose a statistical method for simultaneously estimating interrelated parameters: the time constants and magnitude of the threshold voltage shift. Our method is based on a graphical network representation, and the parameters are estimated using the Markov chain Monte Carlo method. Experimental application of the proposed method to synthetic and measured time-domain RTN signals was successful. The proposed method can handle interrelated parameters of multiple traps and thereby contributes to the construction of more accurate RTN models.

One of the significant issues of processor architecture is to overcome memory latency. Prefetching can greatly improve cache performance, but it has the drawback of cache pollution, unless its aggressiveness is properly set. Several techniques that have been proposed for prefetcher throttling use accuracy as a metric, but their robustness were not sufficient because of the variations in programs' working set sizes and cache capacities. In this study, we revisit prefetcher throttling from the viewpoint of data lifetime. Exploiting the characteristics of cache line reuse, we propose Cache-Convection-Control-based Prefetch Optimization Plus (CCCPO+), which enhances the feedback algorithm of our previous CCCPO. Evaluation results showed that this novel approach achieved a 30% improvement over no prefetching in the geometric mean of the SPEC CPU 2006 benchmark suite with 256 KB LLC, 1.8% over the latest prefetcher throttling, and 0.5% over our previous CCCPO. Moreover, it showed superior stability compared to related works, while lowering the hardware cost.

Source coding with a helper is one of the most fundamental fixed-length source coding problem for correlated sources. For this source coding, Wyner and Ahlswede-Korner showed the achievable rate region which is the set of rate pairs of encoders such that the probability of error can be made arbitrarily small for sufficiently large block length. However, their expression of the achievable rate region consists of the sum of indefinitely many sets. Thus, their expression is not useful for computing the achievable rate region. This paper deals with correlated sources whose conditional distribution is related by a binary-input output-symmetric channel, and gives a parametric form of the achievable rate region in order to compute the region easily.

A concurrent FIFO queue is a widely used fundamental data structure for parallelizing software. In this letter, we introduce a novel concurrent FIFO queue algorithm for multicore architecture. We achieve better scalability by reducing contention among concurrent threads, and improve performance by optimizing cache-line usage. Experimental results on a server with eight cores show that our algorithm outperforms state-of-the-art algorithms by a factor of two.