A content search system considering the activity and context of a mobile user

People routinely carry mobile devices in their daily lives and obtain a variety of information from the Internet in many different situations. In searching for information (content) with a mobile device, a user’s activity (e.g., moving or stationary) and context (e.g., commuting in the morning or going downtown in the evening) often change, and such changes can affect the user’s degree of concentration on his or her mobile device’s display and information needs. Therefore, a search system should provide the user with an amount of information suitable for the current activity and a type of information suitable for the current context. In this study, we present the design and implementation of a content search system that considers a mobile user’s activity and context, with the goal of reducing the user’s operation load for content search. The proposed system switches between two kinds of content search systems according to the user’s activity: the location-based content search system is activated when the user is stationary (e.g., standing and sitting), while a menu-based content search system is activated when the user is moving (e.g., walking). Both systems present information according to user context. The location-based system presents detailed information via menus and a map according to location-based categories. The menu-based system presents only a few options to enable users to get content easily. Through user experiments, we confirmed that participants could get desired information more easily with this system than with a commercial search system.     

Parsing human skeletons in an operating room

Multiple human pose estimation is an important yet challenging problem. In an operating room (OR) environment, the 3D body poses of surgeons and medical staff can provide important clues for surgical workflow analysis. For that purpose, we propose an algorithm for localizing and recovering body poses of multiple human in an OR environment under a multi-camera setup. Our model builds on 3D Pictorial Structures and 2D body part localization across all camera views, using convolutional neural networks (ConvNets). To evaluate our algorithm, we introduce a dataset captured in a real OR environment. Our dataset is unique, challenging and publicly available with annotated ground truths. Our proposed algorithm yields to promising pose estimation results on this dataset.     

Path-planning and navigation of a mobile robot as discrete optimization problems

There is huge diversity among navigation and path-planning problems in the real world because of the enormous number and great variety of assumptions about the environments, constraints, and tasks imposed on a robot. To deal with this diversity, we propose a new solution to the path-planning and navigation of a mobile robot. In our approach, we formulated the following two problems at each time-step as discrete optimization problems: (1) estimation of a robot's location, and (2) action decision. For the first problem, we minimize an objective function that includes a data term, a constraint term, and a prediction term. This approach is an approximation of Markov localization. For the second problem, we define and minimize another objective function that includes a goal term, a smoothness term, and a collision term. Simulation results show the effectiveness of our approach. This work was presented in part at the Fifth International Symposium on Artificial Life and Robotics, Oita, Japan, January 26–28, 2000     

Minimizing False Positives of a Decision Tree Classifier for Intrusion Detection on the Internet

Machine learning or data mining technologies are often used in network intrusion detection systems. An intrusion detection system based on machine learning utilizes a classifier to infer the current state from the observed traffic attributes. The problem with learning-based intrusion detection is that it leads to false positives and so incurs unnecessary additional operation costs. This paper investigates a method to decrease the false positives generated by an intrusion detection system that employs a decision tree as its classifier. The paper first points out that the information-gain criterion used in previous studies to select the attributes in the tree-constructing algorithm is not effective in achieving low false positive rates. Instead of the information-gain criterion, this paper proposes a new function that evaluates the goodness of an attribute by considering the significance of error types. The proposed function can successfully choose an attribute that suppresses false positives from the given attribute set and the effectiveness of using it is confirmed experimentally. This paper also examines the more trivial leaf rewriting approach to benchmark the proposed method. The comparison shows that the proposed attribute evaluation function yields better solutions than the leaf rewriting approach.

Grain refinement and superplasticity in a magnesium alloy processed by equal-channel angular pressing

The extrusion/equal channel angular pressing (EX-ECAP) processing procedure, in which magnesium-based alloys are subjected to extrusion followed by ECAP, was applied to a Mg-7.5 pct Al-0.2 pct Zr alloy prepared by casting. Microstructural inspection showed the EX-ECAP process was effective in reducing the grain size from ∼21 μm after extrusion to an as-pressed grain size of ∼0.8 μm. It is shown through static annealing that these ultrafine grains are reasonably stable up to 473 K, but grain growth occurs at higher temperatures. Tensile specimens were cut from the billets prepared by EX-ECAP and testing showed these specimens exhibited superplasticity at relatively low temperatures with maximum elongations up to >700 pct. By processing through EX-ECAP to a higher imposed strain and thereby increasing the area fraction of high-angle boundaries, it is demonstrated that there is a potential for achieving high-strain-rate superplasticity. This article is based on a presentation made at the Symposium entitled “Phase Transformations and Deformation in Magnesium Alloys,” which occurred during the Spring TMS meeting, March 14–18, 2004, in Charlotte, NC, under the auspices of the ASM-MSCTS Phase Transformations Committee.     

Achieving enhanced ductility in a dilute magnesium alloy through severe plastic deformation

Experiments were conducted to evaluate the utility of a new processing procedure developed for Mg-based alloys in which samples are subjected to a two-step processing route of extrusion followed by equal-channel angular pressing (designated as EX-ECAP). The experiments were conducted using a Mg-0.6 wt pct Zr alloy and, for comparison purposes, samples of pure Mg. It is shown that the potential for successfully using ECAP increases in both materials when adopting the EX-ECAP procedure. For the Mg-Zr alloy, the use of EX-ECAP produces a grain size of ∼1.4 μm when the pressing is undertaken at 573 K. By contrast, using EX-ECAP with pure Mg at 573 K produces a grain size of ∼26 μm. Tensile testing of the Mg-Zr alloy at 523 and 573 K after processing by EX-ECAP revealed the occurrence of significantly enhanced ductilities with maximum elongations of ∼300 to 400 pct.     

Processing and photocatalytic properties of Cu-grafted TiO2 powder from acid treated BaTiO3

The respective influences of calcination, drying methods, and washing conditions on the morphologies, surface properties, and photocatalytic activities of TiO₂ powders prepared from acid treatments of BaTiO₃ were investigated. Rutile powder was obtained using the treatment under strong acid conditions. It possesses a bundle-like shape and comprises rutile nanorods. After calcination, characteristic voids were observed in the particles. Anatase powder was obtained by adjusting pH values of a BaTiO₃ suspension to 2.5-3. Drying at 110 °C engendered the formation of spheroidal anatase, although freeze-dried anatase particles assembled into a flake-like shape. The freeze-dried samples show lower crystallinity. With grafting Cu ions, rutile exhibited better photocatalytic performance for the decomposition of gaseous 2-propanol (IPA) under visible light, although it did not work effectively for anatase.     

Improvement of the photostability for YVO4:Bi,Eu nanoparticles synthesized by the citrate route

YVO₄:Bi³⁺,Eu³⁺ nanophosphor synthesized by the citrate route shows the photobleaching behavior, i.e., the decrease in photoluminescence intensity under the continuous irradiation of excitation light. This photobleaching property is remarkably suppressed by the washing post-treatment combined with centrifugation and the hydrothermal post-treatment. A relation between the fraction of photobleach and the amount of citrate ions coordinating to metallic ions at the surface of nanoparticles verifies that the photobleaching behavior of YVO₄:Bi³⁺,Eu³⁺ nanophosphor originates from the redox reaction between the citrate ions and V⁵⁺ in YVO₄ host crystal. The long-term light fastness test reveals that the hydrothermally treated YVO₄:Bi³⁺,Eu³⁺ nanophosphor has sufficient photostability for practical use over 15 years outside.     

Connection‐Strength Estimation of Neuronal Networks by Fitting for Izhikevich Model

Recently, there has been abundant research using multineuron recording, but there are many problems with extracting the features from the obtained spike time series, which are huge in volume and complex. Here we introduce a new method of estimating synaptic connection strengths between neurons by fitting to the Izhikevich model by maximum likelihood estimation. We demonstrate that our method can estimate connection strengths from spike time series given by a simulated neural ensemble and can estimate nonconnectivity between two independent cultured neuronal networks. These results suggest that our method is applicable to network and plasticity analysis of neuronal networks.     

Effects of processing and cooking on the levels of pesticide residues in soybean samples

The effects of processing and cooking on the levels of pesticide residues in soybean samples were investigated for 14 pesticides in pre-harvest samples. On soaking, the transfer ratios (%, total pesticide residue amount in product/that in soybean) of soaked soybean were greater than 60% for most of the pesticides investigated. The transfer ratio of soymilk ranged from 37% to 92%, and that of tofu ranged from 7% to 63%. The processing factor (Pf, the concentration (mg/kg) of pesticide in product/that in soybean) of tofu ranged from 0.026 to 0.28. These values varied among pesticides. There was a high correlation between the log P(ow) and the transfer ratio of tofu. The test described here should be useful to obtain the transfer ratios of pesticide residues in processing and/or cooking steps.