Characterising the Progress of Gelation in Tofu Making with Ohmic Heating

In tofu making by heat treatment, the addition of coagulant ionizes the proteins as a result of heat dissolution and the ionized proteins aggregate with the coagulant to form protein clusters. The electrical conductivity (EC) of the soya milk emulsion varies in response to the progress of gelation. By ohmic heating, the applied current and voltage directly indicate the electrical conductivity of the soya milk emulsion and then indirectly the progress of tofu gelation. In this paper, ultrasonic measurement is adopted to explore the feasibility of using EC as an indicator of tofu gelation. Experiments showed a strong correlation between EC and ultrasonic measurement in characterisation of tofu gelation.

Guest Editorial:Intelligent Video Surveillance and Related Technologies

Due to the increasing demand for developing a secure and smart living environment, the intelligent video surveillance technology has attracted considerable attention. Building an automatic, reliable, secure, and intelligent video surveillance system has spawned large research projects and triggered many popular research topics in several international conferences and workshops recently. This special issue of Journal of ElecWonic Science and Technology （JEST） aims to present recent advances in video surveillance systems which address the observation of people in an environment, leading to a real-time description of their actions and interactions.

Precise Object Detection Using Iterative Superpixels Grouping Method

The region completeness of object detection is very crucial to video surveillance, such as the pedestrian and vehicle identifications. However, many conventional object detection approaches cannot guarantee the object region completeness because the object detection can be influenced by the illumination variations and clustering backgrounds. In order to overcome this problem, we propose the iterative superpixels grouping （ISPG） method to extract the precise object boundary and generate the object region with high completeness after the object detection. First, by extending the superpixel segmentation method, the proposed ISPG method can improve the inaccurate segmentation problem and guarantee the region completeness on the object regions. Second, the multi- resolution superpixel-based region completeness enhancement method is proposed to extract the object region with high precision and completeness. The simulation results show that the proposed method outperforms the conventional object detection methods in terms of object completeness evaluation.

Slight free falling impact test for assessing guava maturity

A non-destructive method for assessing the maturity of guava was developed based on the mechanical properties of the fruit under the slight falling impact test. The levels of maturity were classified with cluster and discriminant analyses on the primitive impact measurements and their derivatives. The accuracy of classification was improved with linear discriminant analysis and the number of indices being processed was reduced with stepwise regression analysis. The accuracy of classification is 84.21%. The performance shows that slight falling impact together with linear discriminant analysis provides a promising non-destructive approach in assessing the maturity of guavas.

Ohmic Heating for Tofu Making—A Pilot Study

The aim of this study is to explore the relationship between temperature and electrical conductivity of soya milk under ohmic heating in tofu making. The soya milk of 10 Brix was heated to a steady temperature of 90?C. The applied voltage was increased and the temperature rising rate was investigated for adequate heating profiles in tofu making. Experimental results showed that the electrical conductivity of soya milk is proportional to the heating time. The temperature rising rate was increased from 1.46?C to 3.82?C/min as a result of increased voltage. Hence ohmic heating could be an efficient, convenient heating measure in tofu making.

Water Scrubbing for Removal of Hydrogen Sulfide (H₂S) Inbiogas from Hog Farms

Biogas from anaerobic digestion of biological wastes is a renewable energy resource. H2S in biogas may cause corrosion or other damage to engines if it is not removed from the gas before utilization. Because the solubility of H2S in water is higher than methane, water can be used as an adsorbent to remove H2S from biogas. A simple water scrubbing column to reduce the H2S content was designed in this study. The biogas purification process took place in the scrubbing column with water where the gas was continuously fed from the bottom of the column through the diffuser which could produce bubbles. The biogas bubbles and the water can accelerate the reaction inside the column. The water in the column was circulated by means of a pump. H2S content in raw biogas was about 6000 ppm. First, the efficiencies of H2S removal for different biogas flow rate and water level were conducted at 30 and 90 sec. Second, the efficiencies of H2S removal with water recycling system were induced. The results showed that the concentration of H2S in biogas decreased significantly with water level and increased with biogas flow rate through the water scrubbing. It was an effective technique for removing H2S in a short operation time, but absorption capability of water declined rapidly with time. To maintain high absorption rate, water scrubbing after adsorption needed to be replaced or regenerated. The water scrubbing system is a simplest and cheapest method. This work is investigated the feasibility of water scrubbing system and its application to a small hog farm.

Fast Forgery Detection with the Intrinsic Resampling Properties

With the rapid progress of the image processing software, the image forgery can leave no visual clues on the tampered regions and make us unable to authenticate the image. In general, the image forgery technologies often utilizes the scaling, rotation or skewing operations to tamper some regions in the image, in which the resampling and interpolation processes are often demanded. By observing the detectable periodic distribution properties generated from the resampling and interpolation processes, we propose a novel method based on the intrinsic properties of resampling scheme to detect the tampered regions. The proposed method applies the pre-calculated resampling weighting table to detect the periodic properties of prediction error distribution. The experimental results show that the proposed method outperforms the conventional methods in terms of efficiency and accuracy.