Dynamic moduli for short fiber-CR composites

The dynamic moduli, E′ and E″, and tan δ for nylon–CR and PET–CR composites with unidirectional short fibers were studied as a function of temperature by using a Rheovibron. The temperature dependence of tan δ showed two dispersion peaks for nylon–CR composite. The peak at ?28°C corresponded to the main dispersion of CR and the peak at 100°C to the α-dispersion of nylon 6. For a PET-CR composite, in addition to the individual dispersion of CR and PET, a small and broad peak was observed at about 90°C. The angular dependence of E′ indicated that the short fibers assumed good orientation. The storage modulus for the composites was given by the parallel model as E′ = V_f′E_f + V_mE′_m., where E′_c, E′_f and E′_m were the storage modulus for the composite, fiber, and matrix and V_f and V_m were the volume fraction of fiber and matrix, respectively. In the transverse direction of fiber, the peak values of tan δ at ?28°C were given by the following equation; tan δ_c = tan δ_m ? δV_f, where tan δ_c and tan δ_m are the loss tangent for the composite and matrix, respectively, and α is coefficient depending on fiber type. The results indicated that a region with strong interaction was formed between fibers and CR matrix.     

Unmanned Ground Vehicle Navigation in Coordinate-Free and Localization-Free Wireless Sensor and Actuator Networks

We present a set of algorithms for the navigation of Unmanned Ground Vehicles (UGVs) towards a set of pre-identified target nodes in coordinate-free and localization-free wireless sensor and actuator networks. The UGVs are equipped with a set of wireless listeners that provide sensing information about the potential field generated by the network of actuators. Two main navigation scenarios are considered: single-UGV, single-destination navigation and multi-UGV, multi-destination navigation. For the single-UGV, single-destination case, we present both centralized and distributed navigation algorithms. Both algorithms share a similar two-phase concept. In the first phase, the system assigns level numbers to individual nodes based on their hop distance from the target nodes. In the second phase, the UGV uses the potential field created by the network of actuators to move towards the target nodes, requiring cooperation between triplets of actuator nodes and the UGV. The hop distance to the target nodes is used to control the main moving direction while the potential field, which can be measured by listeners on the UGV, is used to determine the UGV’s movement. For the multi-UGV, multi-destination case, we present a decentralized allocation algorithm such that multiple UGVs avoid converging to the same destination. After each UGV determines its destination, the proposed navigation scheme is applied. The presented algorithms do not attempt to localize UGVs or sensor nodes and are therefore suitable for operating in GPS-free/denied environments. We also present a study of the communication complexity of the algorithms as well as simulation examples that verify the proposed algorithms and compare their performances.     

k-NN classification of handwritten characters via accelerated GAT correlation

This paper addresses the problem of reinforcing the ability of the k-NN classification of handwritten characters via distortion-tolerant template matching techniques with a limited quantity of data. We compare three kinds of matching techniques: the conventional simple correlation, the tangent distance, and the global affine transformation (GAT) correlation. Although the k-NN classification method is straightforward and powerful, it consumes a lot of time. Therefore, to reduce the computational cost of matching in k-NN classification, we propose accelerating the GAT correlation method by reformulating its computational model and adopting efficient lookup tables. Recognition experiments performed on the IPTP CDROM1B handwritten numerical database show that the matching techniques of the simple correlation, the tangent distance, and the accelerated GAT correlation achieved recognition rates of 97.07%, 97.50%, and 98.70%, respectively. The computation time ratios of the tangent distance and the accelerated GAT correlation to the simple correlation are 26.3 and 36.5 to 1.0, respectively.     

Anodic Dissolution of Uranium Mononitride in Lithium Chloride-Potassium Chloride Eutectic Melt

Uranium-plutonium nitride is a candidate fuel for fast reactors, but its major drawback is ¹⁴C formation from natural nitrogen. One would probably have to use highly ¹⁵N-enriched nitrogen. A pyrochemical process with molten-salt electroreflning has been proposed as a means to increase the nuclear proliferation resistance of the fuel cycle. Molten-salt electroreflning could also be applied to nitride fuels to make possible the recycling of ¹⁵N. The anodic dissolution behavior of UN in LiCI-KCI melt was studied to provide the basis for a feasibility study of electroreflning of irradiated nitride fuels.     

Thermal and structural properties of KPO3·Ln(PO3)3 glasses (Ln=rare earth ion)

Glass transition temperatures T_g and Raman spectra of KPO₃·Ln(PO₃)₃ (Ln=rare earth ion) glasses were measured for all rare earth members (except Pm). From the series behavior of the T_g and Raman data, it is concluded that the coordination number around rare earth ions changes, probably from nine to eight, in the middle of the rare earth series.     

Cost-Efficient Traffic Aggregation Employing Cross-Layer Shared Protection

Shared protection/restoration is a promising solution for reducing protection resources and is supported at each layer of the current multi-layer networks. Software-defined networking is expected to reduce equipment cost as well as operational cost by orchestrating these shared protection functionalities. However, although protection resource sharing improves link utilization, it sometimes increases the required equipment. Meanwhile, traffic re-aggregation at each layer is an important technique for low volume traffic to utilize the underlying link capacity more efficiently, but re-aggregation also makes it difficult to share protection resources with traffic at lower layers. In this paper, we present multi-layer network design strategy and method that reduce equipment cost by means of both traffic re-aggregation at each layer and protection resource sharing among multiple service traffic at different layers. The strategy first prioritizes traffic re-aggregation at each layer, and then maximally delegates shared protection to lower layers as long as it does not increase the required capacity at the lower layer. Evaluation results from the example three-layer networks confirm that the proposed method can effectively reduce equipment cost compared to the conventional design method. Cost reduction is achieved by leveraging shared protection functions at multiple layers.     

Relaxation approach to topology optimization of frame structure under frequency constraint

This paper deals with the frame topology optimization under the frequency constraint and proposes an algorithm that solves a sequence of relaxation problems to obtain a local optimal solution with high quality. It is known that an optimal solution of this problem often has multiple eigenvalues and the feasible set is disconnected. Due to these two difficulties, conventional nonlinear programming approaches often converge to a local optimal solution that is unacceptable from a practical point of view. In this paper, we formulate the frequency constraint as a positive semidefinite constraint of a certain symmetric matrix, and then relax this constraint to make the feasible set connected. The proposed algorithm solves a sequence of the relaxation problems with gradually decreasing the relaxation parameter. The positive semidefinite constraint is treated with the logarithmic barrier function and, hence, the algorithm finds no difficulty in multiple eigenvalues of a solution. Numerical experiments show that global optimal solutions, or at least local optimal solutions with high qualities, can be obtained with the proposed algorithm.     

Ergonomics solution for crossing collisions based on field assessment of visual environment at urban intersections in Japan

This paper aims to assess quantitatively the actual visual environment of uncontrolled urban downtown intersections in Japan in relation to frequently occurring crossing collisions and to discuss the safety countermeasures for them. In Field Study 1 dealing with direct visibility, our ultra-wide-angle photograph analysis revealed that most of the right/left-ward visible range at 11 intersections were insufficient to check safety, and the quality of direct visibility was closely associated with causing crossing collisions. The countermeasures to reduce a blind area were determined to be a top priority. In Field Study 2 dealing with indirect visibility, more than half of the 25 traffic convex mirrors had marked shortcomings for preventive safety, and ergonomics guidelines ensuring indirect visibility were proposed for installing traffic convex mirrors. Low-cost/low-technology-oriented countermeasures are highly recommended to obtain clear/sufficient images of crucial information satisfying drivers' requirements on traffic convex mirrors in accordance with those ergonomics guidelines was highly recommended. Crossing collisions could be prevented by improvement of poor direct and indirect visibility.     

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.

     

Ultra-fast microwave aided synthesis of gold nanocages and structural maneuver studies

Gold nanocages (AuNcgs) are well-studied,hollow,metallic nanostructures that have fascinated researchers in the fields of nanotechnology,materials science,photoelectronics,biotechnology,and medical science for the last decade.However,the time-consuming synthesis of AuNcgs has limited their widespread use in materials science and nano-biotechnology.A novel,ultra-fast,simple,and highly convenient method for the production of AuNcgs using microwave heating is demonstrated herein.This quick method of AuNcg synthesis requires mild laboratory conditions for large-scale production of AuNcgs.The microwave heating technique offers the advantage of precise mechanical control over the temperature and heating power,even for the shortest reaction period (i.e.,seconds).Microwave-synthesized AuNcgs were compared with conventionally synthesized AuNcgs.Structural maneuver studies employing the conventionally produced AuNcgs revealed the formation of screw dislocations and a shift in the lattice plane.Detailed characterization of the microwave-generated AuNcgs was performed using high resolution transmission electron microscopy (HRTEM),scanning electron microscopy (SEM),X-ray powder diffraction (XRD),and spectroscopic techniques.