Exposure assessment of engineered nanomaterials in the workplace

Nanotechnology is a rapidly growing field and numerous products containing engineered nanomaterials are already in the market. With the increasing use of engineered nanomaterials, it is expected to increase the exposures to nanomaterials in the workplace. However, the researches on the exposure assessment of nanomaterials to humans and the environment are just a beginning step, as the nanotechnology industries are expanding. Questionnaire surveys conducted by various organizations reveal that many nanotechnology companies are searching for information on exposure measurement for the protection of workers who handle nanomaterials. We analyze the trends of researches on the occupational exposure measurement of engineered nanomaterials and investigate the methodologies of exposure assessment recommended by the related working groups. This work is expected to fill the gaps in knowledge on the exposure assessment of nanomaterials.     

Laser diffraction particle sizing by wet dispersion method for spray-dried infant formula

A laser diffraction particle sizing method involving wet analysis could be adapted effectively to measure the accurate particle size distribution of a spray-dried infant formula. Polar, polar aprotic and non-polar solvents, such as ethanol, methanol, acetone, pentane, heptane and hexane, were tested as dispersants for wet analysis. Non-polar solvents such as pentane, heptane and hexane found to be suitable dispersant because the shape of the infant formula particles in non-polar solvents was similar before and after the measurement while the particles had dissolved in the other solvents. The particle size distributions (PSD) of the infant formula determined by laser diffraction (Malvern Master Sizer, UK) using the dry analysis method with air was unsuitable because some parts of the primary and aggregated infant formula particles had been destroyed. The PSD graph of the air dispersion was shifted toward a smaller particle size from that of hexane dispersion. Overall, it is believed that laser diffraction particle sizing involving wet analysis with non-polar solvents may provide a suitable particle sizing method for infant formula products that is better than an air dispersion method.     

Improved Emotion Recognition With a Novel Speaker-Independent Feature

Emotion recognition is one of the latest challenges in human-robot interaction. This paper describes the realization of emotional interaction for a Thinking Robot, focusing on speech emotion recognition. In general, speaker-independent systems show a lower accuracy rate compared with speaker-dependent systems, as emotional feature values depend on the speaker and their gender. However, speaker-independent systems are required for commercial applications. In this paper, a novel speaker-independent feature, the ratio of a spectral flatness measure to a spectral center (RSS), with a small variation in speakers when constructing a speaker-independent system is proposed. Gender and emotion are hierarchically classified by using the proposed feature (RSS), pitch, energy, and the mel frequency cepstral coefficients. An average recognition rate of 57.2% (plusmn 5.7%) at a 90% confidence interval is achieved with the proposed system in the speaker-independent mode.     

Measurement of the heat transfer coefficient in the dimpled channel: effects of dimple arrangement and channel height

Heat transfer coefficients were measured in a channel with one side dimpled surface. The sphere type dimples were fabricated, and the diameter (D) and the depth of dimple was 16 mm and 4 mm, respectively. Two channel heights of about 0.6D and 1.2D, two dimple configurations were tested. The Reynolds number based on the channel hydraulic diameter was varied from 30000 to 50000. The improved hue detection based transient liquid crystal technique was used in the heat transfer measurement. Heat transfer measurement results showed that high heat transfer was induced downstream of the dimples due to flow reattachment. Due to the flow recirculation on the upstream side in the dimple, the heat transfer coefficient was very low. As the Reynolds increased, the overall heat transfer coefficients also increased. With the same dimple arrangement, the heat transfer coefficients and the thermal performance factors were higher for the lower channel height. As the distance between the dimples became smaller, the overall heat transfer coefficient and the thermal performance factors increased. This paper was recommended for publication in revised form by Associate Editor Yong Tae Kang Jae Su Kwak received his B.S. and M.S. degrees in Mechanical Engineering from Korea University in 1996 and 1998, respectively. He then received his Ph.D. from Texas A&M University in 2002. Dr. Kwak is currently an Assistant Professor at the School of Aerospace and Mechanical Engineering at Korea Aerospace University in Goyang-City, Korea. His main research interests include gas turbine heat transfer, compact heat exchanger, and enhancement of heat transfer.     

Face recognition using a fuzzy fisherface classifier

In this study, we are concerned with face recognition using fuzzy fisherface approach and its fuzzy set based augmentation. The well-known fisherface method is relatively insensitive to substantial variations in light direction, face pose, and facial expression. This is accomplished by using both principal component analysis and Fisher's linear discriminant analysis. What makes most of the methods of face recognition (including the fisherface approach) similar is an assumption about the same level of typicality (relevance) of each face to the corresponding class (category). We propose to incorporate a gradual level of assignment to class being regarded as a membership grade with anticipation that such discrimination helps improve classification results. More specifically, when operating on feature vectors resulting from the PCA transformation we complete a Fuzzy K-nearest neighbor class assignment that produces the corresponding degrees of class membership. The comprehensive experiments completed on ORL, Yale, and CNU (Chungbuk National University) face databases show improved classification rates and reduced sensitivity to variations between face images caused by changes in illumination and viewing directions. The performance is compared vis-à-vis other commonly used methods, such as eigenface and fisherface.     

A Simulated transportation problem for improved operational planning: An application in the trucking industry

This paper demonstrates the use of a simulated transportation method as an approach to developing an instructional guide that is operationally flexible and feasible for planning truck rental needs in a way to minimize costs. The informational impact of this approach aids not only the internal operations, but also external relations with truck renting companies by providing a more accurate measure of the anticipated demand on rental equipment, thus allowing the rental companies an opportunity to meet this demand.The results of the research conducted indicate the simulated transportation method is a reliable and valid planning instrument for minimizing transportation cost and generating useful information for management decision making.     

Hierarchical community classification and assessment of aquatic ecosystems using artificial neural networks

Benthic macroinvertebrate communities in stream ecosystems were assessed hierarchically through two-level classification methods of unsupervised learning. Two artificial neural networks were implemented in combination. Firstly, the self-organizing map (SOM) was used to reduce the dimension of community data, and secondly, the adaptive resonance theory (ART) was subsequently applied to the SOM to further classify the groups in different scales. Hierarchical grouping in community data efficiently reflected the impact of the environmental factors such as topographic conditions, levels of pollution, and sampling location and time across different scales. New community data not included in the training process were used to test the trained network model. The input data were appropriately grouped at different hierarchical levels by the trained networks, and correspondingly revealed the impact of environmental disturbances and temporal dynamics of communities. The hierarchical clusters based on a two-level classification method could be useful for assessing ecosystem quality and community variations caused by environmental disturbances.