
Rong PhoophuangpairojRangsit University | RSU
Rong Phoophuangpairoj
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27
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Publications (27)
This paper proposes a method to recognize fruits whose quality, including their ripeness, grades, brix values, and flesh characteristics, cannot be determined visually from their skin but from striking and flicking sounds. Four fruit types consisting of durians, watermelons, guavas, and pineapples were studied in this research. In recognition of fr...
p style="text-align: justify;">During the pandemic of Coronavirus disease 2019 (COVID-19), English as a foreign language (EFL) students have to study and submit their assignments and quizzes through online systems using electronic files instead of hardcopies. This has created an opportunity for teachers to use computer tools to conduct preliminary...
This research studies the use of a single accelerometer inside a smartphone as a sensor to detect those postures that may be risks for patients with hip surgery to dislocate their joints. Various postures were analyzed using Euclidean distances to determine the feasibility to detect eight postures that were harmful. With the mobile phone attached t...
Property buyers and homeowners throughout the world have discovered badly tiled floors in their buildings. Consequently, they spend time on expensive repairs because their tiling has a shorter than expected lifetime. If it were possible to ascertain the quality of floor tiling before making a payment, this problem could be solved. Usually, it is di...
It is challenging for buyers around the globe to identify good quality fruit. For several kinds of fruit, it may be difficult for buyers to determine the fruit quality by appearance. The ability to select only good quality fruit without cutting or cleaving is useful because buyers will not waste money ordering undesirable fruit. To decrease the cha...
Fruit is one of the essential sources of human nutrition. Consumers around the world need to be able to purchase fruit of reliable flavor and nutritional quality. Physical appearance and physicochemical properties play a key role in determining desirable quality and flavor. However, for some fruits such as watermelon, durian, pineapple, it is very...
Buying expensive agricultural produce and fruit such as durians that are unripe can result in a bad experience for a consumer and a loss in profit for a retailer. Therefore, the study of durian striking sounds to create an automatic method of recognizing the ripeness of durians without cutting or damaging them is interesting because it could benefi...
Durians are green spiky fruits, which are considered as a delicacy throughout Southeast Asia. They are valued for their unique flavor and powerful taste. It is desirable to be able to determine the quality of durians without cutting them because it is difficult to quantify the ripeness from the external appearance and they are expensive to purchase...
This paper proposes a speech recognition method using multiple speech recognizers with a combination of techniques to enhance robot control. The procedure consisted of 2 parts: 1) recognizing robot commands using multiple Hidden Markov model (HMM) recognizers, and 2) sending recognized commands to control the robot. In the first part, which is the...
This paper proposes a method for identifying a gender by using a Thai spoken syllable with the Average Magnitude Difference
Function (AMDF) and a neural network (NN). The AMDF is applied to extracting pitch contour from a syllable. Then the NN uses
the pitch contour to identify a gender. Experiments are carried out to evaluate the effects of Thai t...
In this paper, a highly effective system for Thai speech recognition is proposed. The speech recognizer for so-called speaker-independent is created by using Continuous Density Hidden Markov Model (CDHMM). In the acoustic level, the models trained for both speaker genders, and for each separate gender are investigated and tested in terms of accurac...
This paper presents a Thai syllable speech recognition system with the capability to achieve high accuracy of Thai syllable
speech and Thai tone recognition. The recognition accuracy of 97.84% is achieved for Thai syllable speech recognition using
the Continuous Density Hidden Markov Model (CDHMM). To provide a faster response, a beam pruning techn...