Innovations in Individual Feature History Management—The Significance of Feature-based Temporal Model

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO’s temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO’s temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure.

Optimization of 3.5-in. HDD spindle motors for OP-vibration performance: theoretical prediction and experimental verification

The purpose of this paper is to optimize OP-vibration performance of 3.5-in. hard disk drive (HDD) spindle motors through theoretical prediction and experimental verification. OP-vibration performance of HDD is closely related to the first rocking vibration of spindle motors because excited frequencies of 3.5-in. HDD from the environment are mostly below 500 Hz and the first rocking vibration is the only resonance in the corresponding frequencies. Therefore, minimizing first rocking vibration leads to improve OP-vibration performance of the spindle motors. In order to minimize the first rocking vibration key parameters of FDB spindle motors were selected from a previous work done by Heo and Shen (Microsyst Technol 11:1204–1213, 2005). Then, the selected parameters have been optimized to minimize the first rocking vibration through a theoretical model developed at University of Washington. Then, experiments with ten prototype FDB spindle motors have been conducted to verify the theoretical results. Each prototype motor has different spindle parameter configurations including bearing coefficients, bearing locations, and center of gravity location, etc. Also, this paper demonstrated that radial measurements of spindle rocking vibration have better correlation with OP-vibration performance than axial measurements through PES measurements. Finally, the optimized design has been manufactured by a motor maker and has also successfully verified the theoretical prediction experimentally.     

A method of predicting the number of clusters using Rand's statistic

Distributional and asymptotic results on the moment of Rand's C_k statistic were derived by DuBien and Warde [1981. Some distributional results concerning a comparative statistic used in cluster analysis. ASA Proceedings of the Social Statistics Section, 309–313.]. Based on those results, a method to predict the number of clusters is suggested by applying various agglomerative clustering algorithms. In the procedure, the methods using different indexes are examined and compared based on the concept of agreement (or, disagreement) between clusterings generated by different clustering algorithms on the set of data. Our method having practical generality works better than the other methods and assigns statistical meaning to C_k values in determining the number of clusters from the comparison.     

Monthly Joint Operations for the Nakdong Multi-reservoir System in Korea

Abstract

This study applies a state-of-art optimization technique, SSDP/ESP (Sampling Stochastic Dynamic Programming with Ensemble Streamflow Prediction), to derive a monthly joint operating policy for the Nakdong multi-reservoir system in Korea. A rainfall-runoff model, SSARR (Streamflow Synthesis And Reservoir Regulation), is linked to the SSDP/ESP model to provide ESP scenarios for runoff during the next month in the Nakdong River basin. The primary advantage of the SSDP/ESP is that it updates the derived operating policy as new ESP forecasts become available. Another SSDP model that employs historical runoff scenarios (SSDP/Hist) is also developed. The main difference between the two SSDP models is that SSDP/Hist is an off-line model whereas the SSDP/ESP is on-line. The developed operating policies are tested with a simulation model using an object-oriented simulation software, STELLA. The simulation results show that SSDP/ESP is superior to SSDP/Hist with respect to the water supply criterion, although both models perform similarly with respect to the hydroelectric energy production criterion.     

Multidimensional local spatial autocorrelation measure for integrating spatial and spectral information in hyperspectral image band selection

Hyperspectral band selection aims at the determination of an optimal subset of spectral bands for dimensionality reduction without loss of discriminability. Many conventional band selection approaches depend on the concept of “statistical distance” measure between the probability distributions characterizing sample classes. However, the maximization of separability does not necessarily guarantee that a classification process results in the best classification accuracies. This paper presents a multidimensional local spatial autocorrelation (MLSA) measure that quantifies the spatial autocorrelation of the hyperspectral image data. Based on the proposed spatial measure, a collaborative band selection strategy is developed that combines both spectral separability measure and spatial homogeneity measure for hyperspectral band selection without losing the spectral details useful in classification processes. The selected band subset by the proposed method shows both larger separability between classes and stronger spatial similarity within class. Case studies in biomedical and remote sensing applications demonstrate that the MLSA-based band selection approach improves object classification accuracies in hyperspectral imaging compared with conventional approaches.     

Multiple target tracking using cognitive data association of spatiotemporal prediction and visual similarity

Object tracking is crucial to surveillance systems, which provide target information including position, size, and velocity. This paper presents a data association process combining two primary components of visual features and spatiotemporal prediction. In addition, the change perception and the visual distinguishability are utilized to adaptively combine the two primary components. The proposed spatiotemporal prediction is performed on several consecutive frames in order to cover the irregular motion of targets. The prediction is then filtered with a change perception mask to determine whether the candidate observations have motion or not. In addition, the level of contribution of a visual feature is adjusted by the proposed distinguishability to maintain a reward-penalty balance. The proposed method is applied to various video sequences having small targets and abrupt motions, and the experimental results show consistent tracking performance.     

Optimal Checkpoint Placement on Real-Time Tasks with Harmonic Periods

This paper presents an optimal checkpoint strategy for fault-tolerance in real-time systems where transient faults occur in Poisson distribution. In our environment, multiple real-time tasks with different deadlines and harmonic periods are scheduled in the system by rate-monotonic algorithm, and checkpoints are inserted at a constant interval in each task. When a fault is detected, the system carries out rollback to the latest checkpoint and re-executes tasks. The maximum number of re-executable checkpoints and an equation to check schedulability are derived, and the optimal number of checkpoints is selected to maximize the probability of completing all the tasks within their deadlines.     

New thermogelling poly(organophosphazenes) with methoxypoly(ethylene glycol) and oligopeptide as side groups

A new class of thermogelling poly(organophosphazenes) bearing a hydrophilic methoxypoly(ethylene glycol) (MPEG) and a hydrophobic tri or tetrapeptide such as GlyPheLeuEt, GlyPheIleEt, GlyLeuPheEt, and GlyPheLeuGlyEt have been synthesized and characterized by means of multinuclear (¹H, ³¹P) NMR spectroscopy, gel permeation chromatography, viscometry, and elemental analysis. The gelation of the present polymers is presumed to be attributed to the intermolecular interaction between the hydrophobic oligopeptide side groups, which can form strong physical junction zones in the polymer aqueous solution. The gelation properties of the polymer were affected by the subtle change in the nature of the hydrophobic oligopeptide, composition of the hydrophilic to hydrophobic side groups, and the concentration of the polymer solutions. Among the present thermogels, the copolymer with equimolar MPEG and GlyPheIleEt as side groups showed the excellent gel phase persisting over 35-43 °C, which indicates that it is a new promising material for drug delivery and tissue engineering.     

Ni implantation-induced enhancement of the crystallisation of amorphous Si

We report on the effect of Ni implantation on the crystallisation process of amorphous Si formed by ion implantation during excimer laser annealing. Scanning transmission electron microscopy and X-ray photoemission spectroscopy results show that NiSi₂ precipitates are formed in the Si–Ni-implanted samples. It is shown that the Ni implantation results in the enhanced crystallisation of amorphous Si during laser annealing. The Si–Ni-implanted samples become epitaxial to the Si substrate at 600 mJ/cm², while the Si-implanted samples produce epitaxial relationship at 800 mJ/cm². Possible mechanisms by which implanted Ni atoms play a role are given to describe the enhanced crystallisation process of amorphous Si.