A study on the effective hydraulic conductivity of an anisotropie porous medium

Effective hydraulic conductivity of a statistically anisotropic heterogeneous medium is obtained for steady two-dimensional flows employing stochastic analysis. Flow equations are solved up to second order and the effective conductivity is obtained in a semi-analytic form depending only on the spatial correlation function and the anisotropy ratio of the hydraulic conductivity field, hence becoming a true intrinsic property independent of the flow field. Results are obtained using a statistically anisotropic Gaussian correlation function where the anisotropy is defined as the ratio of integral scales normal and parallel to the mean flow direction. Second order results indicate that the effective conductivity of an anisotropic medium is greater than that of an isotropic one when the anisotropy ratio is less than one and vice versa. It is also found that the effective conductivity has upper and lower bounds of the arithmetic and the harmonic mean conductivities.     

Variable forgetting factor linear least squares algorithm forfrequency selective fading channel estimation

In this article, the variable forgetting factor linear least squares algorithm is presented to improve the tracking capability of channel estimation. A linear channel model with respect to time change describes a time-varying channel more accurately than a conventional stationary channel model. To reduce the estimation error due to model mismatch, we incorporate the modified variable forgetting factor into the proposed algorithm. Compared to the existing algorithms-exponentially windowed recursive least squares algorithm with the optimal forgetting factor and linear least squares algorithm-the proposed method makes a remarkable improvement in a fast fading environment. The effects of channel parameters such as signal-to-noise ratio and fading rate are investigated by computer simulations     

Possible superoxide radical-induced alteration of vascular reactivity in aortas from streptozotocin-treated rats

We investigated the possible involvement of the superoxide (.O2-) radical in alterations of vascular reactivity and phosphoinositide (PI) turnover in aortas from streptozotocin (STZ)-induced diabetic (4 week) rats. STZ treatment increased the maximal contractile response of the aorta to norepinephrine (NE), phenylephrine (PE) and high K+, whereas the sensitivity remained unaltered. Ca(++)-induced contractions in the presence of maximally effective concentrations of PE and K+ were also augmented after STZ treatment. The increased maximal response was associated with both decreased endothelium-dependent relaxation and increased NE-induced PI turnover. Pyrogallol (PYR), a potent .O2- generating agent, did not affect basal tone or PI turnover but, depending on concentrations, it significantly increased or decreased both the contractile response to PE and NE-induced PI turnover in control aorta. In contrast, PYR decreased NE-induced PI turnover in diabetic aorta. The malondialdehyde content of liver, serum and aorta, and of .O2- from aorta of diabetic rats, were increased significantly. Copper catalyzed oxidation of ascorbic acid resulted in contraction followed by relaxation, depending upon the ascorbic acid concentration in both control and diabetic aorta. Pretreatment with superoxide dismutase (300 U/ml) prevented the PYR-induced potentiation of the PE contraction, but not of NE+PYR-induced PI turnover in control aorta and decreased further NE+PYR-induced PI turnover in diabetic aorta. The present findings indicate that .O2- may be responsible, at least in part, for the impaired endothelial integrity, enhanced alpha adrenergic receptor-mediated PI turnover and augmented contractility, possibly through modification of calcium channels in STZ-induced short-term (4 week) diabetic rat aorta.     

Efficient image downconversion for mixed field/frame-mode macroblocks

An efficient image downconversion algorithm in the compressed domain for mixed field/frame-mode macroblocks is proposed. A 16 /spl times/ 16 field/frame-mode macroblock is converted into an 8 /spl times/ 8 reduced block in the discrete cosine transform (DCT) domain using a modified inverse DCT (IDCT) kernel. Experimental results show that the proposed algorithm provides the downconverted image quality similar to an existing method with significantly lower computational cost.     

Packet Error Rate Analysis of ZigBee Under WLAN and Bluetooth Interferences

In this paper, the performance of IEEE 802.15.4 ZigBee under the interference of IEEE 802.11b wireless local area network (WLAN) and/or Bluetooth is evaluated using an analytic model for the coexistence among ZigBee, WLAN, and Bluetooth. The packet error rate (PER) is evaluated, where the PER is obtained from the bit error rate (BER) and the collision time. The BER is obtained from the signal-to-interference-plus-noise ratio (SINR). Finally, the analytic results are validated by simulations.     

Thermal diffusivity measurements of foil-shaped materials by vectorial analysis using an AC calorimeter

Measurements of thermal diffusivity of foil-shaped materials have been carried out using a photoirradiation-type AC calorimeter at room temperature. In this method the frequency effect, which is caused by heat loss from the sample to the environment, is readily detected in measurements of both amplitude and phase components of the AC temperature signal, Even though the chopping frequency is appropriate, the two diffusivities calculated from these two components differ from each other, Moreover, the difference between the two values increases when the chopping frequency increases. Simple vectorial calculation with the two components one from the amplitude and the other from the phase- permits the frequency ellect to be determined. The calculated result is the geometric average of the two diffusivities. This analytic method was tested with diamond film and SUS-304 foil. From these we confirmed that the vectorial analytic method gives similar diffusivity values for different frequencies indicating its reliability.Paper presented at the Twelfth Symposium on TherrmophysicaI Properties, June 19–24, 1994, Boulder, Colorado, U.S.A.     

Diagnosis of Middle Ear Diseases Based on Convolutional Neural Network

An otoscope is traditionally used to examine the eardrum and ear canal. A diagnosis of otitis media (OM) relies on the experience of clinicians. If an examiner lacks experience, the examination may be difficult and time-consuming. This paper presents an ear disease classification method using middle ear images based on a convolutional neural network (CNN). Especially the segmentation and classification networks are used to classify an otoscopic image into six classes: normal, acute otitis media (AOM), otitis media with effusion (OME), chronic otitis media (COM), congenital cholesteatoma (CC) and traumatic perforations (TMPs). The Mask R-CNN is utilized for the segmentation network to extract the region of interest (ROI) from otoscopic images. The extracted ROIs are used as guiding features for the classification. The classification is based on transfer learning with an ensemble of two CNN classifiers: EfficientNetB0 and Inception-V3. The proposed model was trained with a 5-fold cross-validation technique. The proposed method was evaluated and achieved a classification accuracy of 97.29%.     

Detection of DDoS attacks using optimized traffic matrix

Distributed Denial of Service (DDoS) attacks have been increasing with the growth of computer and network infrastructures in Ubiquitous computing. DDoS attacks generating mass traffic deplete network bandwidth and/or system resources. It is therefore significant to detect DDoS attacks in their early stage. Our previous approach used a traffic matrix to detect DDoS attacks quickly and accurately. However, it could not find out to tune up parameters of the traffic matrix including (i) size of traffic matrix, (ii) time based window size, and (iii) a threshold value of variance from packets information with respect to various monitored environments and DDoS attacks. Moreover, the time based window size led to computational overheads when DDoS attacks did not occur. To cope with it, we propose an enhanced DDoS attacks detection approach by optimizing the parameters of the traffic matrix using a Genetic Algorithm (GA) to maximize the detection rates. Furthermore, we improve the traffic matrix building operation by (i) reforming the hash function to decrease hash collisions and (ii) replacing the time based window size with a packet based window size to reduce the computational overheads. We perform experiments with DARPA 2000 LLDOS 1.0, LBL-PKT-4 of Lawrence Berkeley Laboratory and generated attack datasets. The experimental results show the feasibility of our approach in terms of detection accuracy and speed.     

Evaluating Information Strategic Planning: An Evaluation System and Its Application

Information technology (IT) plays an obviously important role in gaining opportunities and taking the competitiveness advantages, and information strategy planning (ISP) becomes the major concern for the effective implementation of information system (IS) among researchers and practitioners. Most companies have difficulties in developing ISP due to its complexity and diversity. Thus, numerous studies have been done on ISP and the methodology for its effective devising process. However, traditional methodologies do not reflect the rapid change of IT markets and business environments. We identify the critical factor for ISP methodology, and develop the new methodology, so-called information strategy planning methodology (ISPM). Also, based on ISPM an evaluation system of ISP is proposed to enhance the quality and practicality of ISP. The evaluation system is composed of two domains, evaluation of ISP procedure and evaluation of ISP supporting systems. The evaluation system is applied to seventeen major Korean companies' ISPs to reveal its value.