Additional kernel observer: privilege escalation attack prevention mechanism focusing on system call privilege changes

International Journal of Information Security - Cyberattacks, especially attacks that exploit operating system vulnerabilities, have been increasing in recent years. In particular, if administrator...     

Study on stiffness visualization and safety control based on will-consensus building for tele-palpation robot system

This paper proposes a method for visualizing the stiffness of a soft object in a palpation-support information system by the teleoperation of a robot hand. It is important that a palpation system display a body’s shape and stiffness. In our method, the stiffness of the contact area between the soft object and the robot finger is estimated by a recursive least-squares method with forgetting factor that uses an impedance dynamics model. With the estimated stiffness and direction of contact force, we calculate the scalar parameter for visualization of stiffness. Moreover, we propose a safety control method for the palpation system, which is part of a tele-control method based on will-consensus building. The system configuration, estimated algorithm, and experimental results are presented.     

A Nom historical document recognition system for digital archiving

A Nom historical document recognition system is being developed for digital archiving that uses image binarization, character segmentation, and character recognition. It incorporates two versions of off-line character recognition: one for automatic recognition of scanned and segmented character patterns (7660 categories) and the other for user handwritten input (32,695 categories). This separation is used since including less frequently appearing categories in automatic recognition increases the misrecognition rate without reliable statistics on the Nom language. Moreover, a user must be able to check the results and identify the correct categories from an extended set of categories, and a user can input characters by hand. Both versions use the same recognition method, but they are trained using different sets of training patterns. Recursive X–Y cut and Voronoi diagrams are used for segmentation; k–d tree and generalized learning vector quantization are used for coarse classification; and the modified quadratic discriminant function is used for fine classification. The system provides an interface through which a user can check the results, change binarization methods, rectify segmentation, and input correct character categories by hand. Evaluation done using a limited number of Nom historical documents after providing ground truths for them showed that the two stages of recognition along with user checking and correction improved the recognition results significantly.     

Bright-field scanning confocal electron microscopy using a double aberration-corrected transmission electron microscope

Scanning confocal electron microscopy (SCEM) offers a mechanism for three-dimensional imaging of materials, which makes use of the reduced depth of field in an aberration-corrected transmission electron microscope. The simplest configuration of SCEM is the bright-field mode. In this paper we present experimental data and simulations showing the form of bright-field SCEM images. We show that the depth dependence of the three-dimensional image can be explained in terms of two-dimensional images formed in the detector plane. For a crystalline sample, this so-called probe image is shown to be similar to a conventional diffraction pattern. Experimental results and simulations show how the diffracted probes in this image are elongated in thicker crystals and the use of this elongation to estimate sample thickness is explored.     

A new optical elasticity resin for mobile LCD modules

Abstract— The display used in current cell phones has an air gap between the cover glass and the liquid‐crystal‐display (LCD) module to prevent the LCD glass from being damaged. Reflections at the boundaries of the air gap cause a reduction in the LCD luminance and contrast. To address this problem, a newly proposed LCD structure has been investigated. The “Super View Resin (SVR),” a transparent elastic resin which improves the shock resistance and visibility of the LCD, has been developed. Filling the air gap between the cover glass and LCD module with a refractive‐index‐matching resin solves the light‐reflection problem inherent in the use of a reinforced cover‐glass lens. Moreover, the elastic filler works as a damper, reducing any external shock, which prevents not only the cover glass and LCD module from being damaged, but also the glass from being shattered when it is broken.     

TMN implementation strategy based on OSI management standards

In order to facilitate the implementations ofTMN interface protocols/services studied inITU-T, it is very important to define profiles for supportingTMN management service. This paper proposes a concrete method for achieving this based on osi management standards as a promisingTMN implementation method. It proposes an idea of structuring theTMN ISP’S based on the structure of the osi managementISP’S. The paper discusses aTMN based on the osi managementISP’S. Finally the implementation as software is discussed and a software architecture for efficient application development is proposed.     

Multiphase composites of tetragonal zirconia agglomerate dispersed into alumina and alumina-zirconia matrices

Multiphase composites of yttria- and ceria-doped tetragonal zirconia agglomerates (10–50 m) dispersed into an alumina or alumina-zirconia matrix were sintered at 1500–1600 °C in air, followed by post-Hot Isostatic Pressing (HIP) at 1450°C and 150 MPa in an Ar gas atmosphere. The relative density of the recovered composites was above 98% of the theoretical density. By chemically etching on the surface of zirconia agglomerates, the sinterability of composites was apparently improved; and no microcracks nor pores were observed at the interface of agglomerate and matrix. According to scanning electron microscopy (SEM) observation, tetragonal and tetragonal-monoclinic zirconia agglomerates were highly dispersed into the alumina or alumina-zirconia matrix. The multiphase composites containing 10 vol% spherical agglomerates demonstrate the relatively low value of bending strength, < 400 MPa, and a high value of fracture toughness, > 11 MPa m^1/2. The crack propagation introduced by Vickers indentation was efficiently suppressed and deflected by the agglomerates.     

Reduction of higher harmonic sequences in terminal voltage of an AC exciting synchronous generator using magnetically anisotropic slot wedges

This paper describes relationships between characteristics of a magnetically anisotropic slot wedge and voltage higher harmonics in an ac exciting synchronous generator terminal due to permeance ripple caused by an open-slot-type rotor. From the relationships obtained, practical guidelines were formulated for machine designs applying the magnetically anisotropic slot wedge. The results are as follows.

• 1 (1) Equivalent permeability of the magnetically anisotropic slot wedge became isotropic wedge permeability for air-gap flux ripple.
• 2 (2) Two ways were identified to reduce voltage-higher harmonics by using the slot wedges.
• 3 (3) The level of leakage flux passing through the anisotropic slot wedge was determined only by its permeability in the width direction.
• 4 (4) Effectiveness of the magnetic anisotropic slot wedges inserted into the stator slots was verified from experimental results using a model machine of the open- slot-type rotor.

     

SPIDER: An availability-aware framework for the service function chain placement in distributed scenarios

The network function virtualization (NFV) paradigm replaces hardware-dependent network functions by virtual network functions (VNFs) that can be deployed in commodity hardware, including legacy servers. Consequently, the use of NFV is expected to reduce operating and capital expenses, as well as improve service deployment operation and management flexibility. For many use cases, the VNFs must be visited and invoked following a specific order of execution in order to compose a complete network service, named service function chain (SFC). Nonetheless, despite the benefits from NFV and SFC virtualization technologies, their introduction must not harm network performance and service availability. On the one hand, redundancy is seen by network service planners as a mechanism well established to combat availability issues. At same time, there is a goal to optimize resource utilization in order to reduce operational expenditure. In this article, we share our experience in the design use of a framework, named SPIDER, focused on SFC placement that considers the network infrastructure condition and the required SFC availability to define the placement strategy. The SPIDER monitors the status of infrastructure nodes and links and defines which servers the VNFs should be placed on and the number of redundant replicas needed. We present a proof-of-concept of SPIDER using Kubernetes to launch the VNFs as containers. We also use Kubernetes to forward the traffic between the VNFs, composing the service chain. We perform experiments to evaluate the runtime of SPIDER and the SFC delay under different network conditions.     

Development of an epileptic seizure prediction algorithm using R–R intervals with self-attentive autoencoder

Epilepsy is a neurological disorder that may affect the autonomic nervous system (ANS) from 15 to 20 min before seizure onset, and disturbances of ANS affect R–R intervals (RRI) on an electrocardiogram (ECG). This study aims to develop a machine learning algorithm for predicting focal epileptic seizures by monitoring R–R interval (RRI) data in real time. The developed algorithm adopts a self-attentive autoencoder (SA-AE), which is a neural network for time-series data. The results of applying the developed seizure prediction algorithm to clinical data demonstrated that it functioned well in most patients; however, false positives (FPs) occurred in specific participants. In a future work, we will investigate the causes of FPs and optimize the developing seizure prediction algorithm to further improve performance using newly added clinical data.