• Journal of Information Processing Systems
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• v.20 no.1
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• pp.13-23
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• 2024

Music brings pleasure and relaxation to people. Therefore, it is necessary to classify musical genres based on scenes. Identifying favorite musical genres from massive music data is a time-consuming and laborious task. Recent studies have suggested that machine learning algorithms are effective in distinguishing between various musical genres. However, meeting the actual requirements in terms of accuracy or timeliness is challenging. In this study, a hybrid machine learning model that combines a deep residual auto-encoder (DRAE) and support vector machine (SVM) for musical genre recognition was proposed. Eight manually extracted features from the Mel-frequency cepstral coefficients (MFCC) were employed in the preprocessing stage as the hybrid music data source. During the training stage, DRAE was employed to extract feature maps, which were then used as input for the SVM classifier. The experimental results indicated that this method achieved a 91.54% F1-score and 91.58% top-1 accuracy, outperforming existing approaches. This novel approach leverages deep architecture and conventional machine learning algorithms and provides a new horizon for musical genre classification tasks.

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.2
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• pp.115-122
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• 2020

In Korea, the agricultural machinery market has been generally on the rise, and particularly the demand for the diverse agricultural machine is increasing due to the radical changes in agriculture, such as a high supply of the advanced and automated agricultural machine and an increase in aged or female farmer population. Therefore, this study analyzes the technical trends in the precision agricultural machine domestically and globally to guide the direction of development of the ICT-based machine. The investigation of the precision agricultural machine in this study focuses on the production technology through analyzing the trends in sensor-related technology, the decision-making research, variable treatment technology, and academic publication. The result shows that information processing technology including the sensor and the decision-making requires various measurement factors and the established technologies are continually being developed.

• Korean Journal of Agricultural Science
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• v.43 no.3
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• pp.432-440
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• 2016

The consumption of pre-treated vegetables (including fresh-cut vegetables) that are washed, peeled, and trimmed has been significantly increased because of their easy use for cooking. Vegetable cutting machines have been widely utilized for producing fresh-cut vegetables or agricultural products of different sizes; however, the design standard is not established for specific types of agricultural products. Therefore, this study was conducted to determine mechanical properties (compressive and shear forces) of targeted agricultural products (radish, carrot, squash, cucumber, shiitake mushroom, and sweet potato) for developing a multipurpose vegetable cutting machine. According to ASAE standard (s368.3), compressive and shear forces of targeted agricultural products were measured by using a custom built UTM (universal testing machine). Shape type of samples and speed ranges (5 - 15 mm/min) of loading rate on bioyield and shear points varied depending on the targeted agricultural product. The range of averaged bioyield points of targeted agricultural products were between 7.89 and 146.98 N. On the other hand, their averaged shear points ranged from 22.50 to 53.47 N. Results clearly showed that the bioyield and shear points of targeted agricultural products were thoroughly affected by their components. As measuring compressive and shear forces of a variety of agricultural products, it will be feasible to calculate blade cutting force for designing multipurpose vegetable cutting machine.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.119-128
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• 1993

Effective machine capacity is affected by the physical and geometrical conditions of the fields. In the small and scattered farmland structure field efficiency is greatly influenced by plot geometry. In this paper, a method for estimating field efficiency and effective machine capacity was developed . The developed method was applied to Korean paddy cultivation. Various time elements related to farm operations for small and scattered plots are discussed in this paper . Available working time is divided into two parts, viz. the preparation time for machine operation and actual working time. Two kinds of machine efficiencies, namely , Machine Efficiency 1, applicable on a single large plot or set of well consolidated plots ; and Machine Efficiency 2, applicable on small and scattered multiple plots, are considered. Based assumptions made and steps followed to construct the model are discussed. Effective capacity of each machine based on different plot geometries are calculated y the model. Machine efficiency on a single plot increases with increase in the dimension of longer side of the plot . Low speed, low theoretical capacity machines have higher machine efficiency which is only slightly influenced by plot geometry. As plot geometry is improved , the machine efficiency of high speed, high capacity machines increases rapidly. The effects of short side length and plot size on machine efficiency on a single plot depend on the type of farm operation. For a particular plot shape, as plot size increases, machine efficiency on multiple plots increases rapidly. The effects of consolidation on machine efficiency is highly significant if the plot size is small and/or machine size is large.

• Journal of Biosystems Engineering
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• v.34 no.3
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• pp.167-174
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• 2009

This study was conducted to develop an agaricus bisporus washing machine which uses compressed air to remove foreign materials attached on the surface of agaricus bisporus. A prototype of the washing machine was constructed, and performance of removing foreign materials was tested. Research results are as follows: 1. Several transferring methods including PE roller rotation, brush roller rotation, PE screw rotation, vibration plate, and belt conveyor were evaluated. Roller, screw, and vibration methods caused damages on the surface of the products, but belt conveyor method caused the least damages. 2. For air jet, a stationary nozzle type and a rotational type were evaluated. The best air jet nozzle was the jet-type nozzle, and the rotational type was more effective than stationary type nozzle. 3. With the conveyer belt, box type moving method and the rotational air jet nozzle, the washing machine showed the best performance when higher than 5.4${\times}$105 Pa of air jet pressure and lower than 0.047 m/s of moving speed was used. Working performance of the system was 650 kg/h, and the damaging rate was 1.2 %.

• Journal of Drive and Control
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• v.17 no.4
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• pp.23-30
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• 2020

Driving on irregular and inclined roads using agricultural machinery such as spraying machines or trucks in orchards causes farmer casualties associated with the overturning of agricultural machinery. In addition, the harm to agricultural workers caused by the excessive inhalation of the scattered pesticide frequently occurs during pest control processes. To address these problems, we introduced precision agricultural technology that could selectively spray pesticides only where the fruit is present by recognizing the presence or shape of the fruit in the orchard. In this paper, a 16-channel LIDAR (VLP-16) made of Velodyne was used to identify the shape of fruit trees. Solenoid valves were attached to the end parts of 12 nozzles of the orchard spraying machine for on/off control. The smart spraying machine implemented in this way was mounted on a vehicle capable of autonomous travel and performed selective control depending upon the shape of the fruit trees while traveling in the orchards. This is expected to significantly reduce the amounts of pesticides used in orchards and production costs.

• Journal of Drive and Control
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• v.16 no.4
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• pp.74-79
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• 2019

In this study, an edible fresh corn harvest testing machine was designed and manufactured. And harvesting performance was analyzed through the field test. The testing machine is of the tractor attached type. It is connected to the tractor PTO shaft to transfer power to the each part of the harvesting machine. And it harvests fresh corn by one row through the processes of cutting, stem crushing, detaching, and collecting. The performance test was performed at PTO speed (540, 750, 1050 rpm, respectively), working speed (0.1, 0.15, 0.2 m/s, respectively), and cropping cultivation (row spacing·hill spacing 70·25 cm, 70·40 cm, 90·30 cm, respectively). The performance test was repeated three times in the 15 m section. The detachment loss ratio, uncollected crop ratio, damage ratio, and harvest ratio were analyzed. As a result of the performance test, it was analyzed that the PTO speed 540 rpm, running speed of 0.1 m/s, and row spacing·hill spacing 70·40 cm were the optimal condition.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.810-819
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• 1993

An autonomous lan vehicle for agriculture(ALVA-II) was developed. A prototype vehicle was made by modifying a commercial tractor. A Navigation sensor system with a geo-magnetic sensor performed the autonomous operations of ALVA-II, such as rotary tilling with headland turnings. A navigation sensor system with a machine vision system was also investigated to control ALVA-II following a work boudnary.

• Journal of Biosystems Engineering
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• v.36 no.5
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• pp.361-368
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• 2011

The amount of export of paprika has been increased rapidly in recent years. Therefore, its cultivation area has greatly increased in Korea according to current consumer's attraction. Moreover, it becomes one of the major exporting products while it recorded 53 million dollars, in 2009 resulting in 40% of the total vegetables export. Most of the products are exported to Japan, but it is necessary to prolong the quality preservation periods to export paprika to nations like U.S.A. or EU. However, to encourage an export to many countries, washing and disinfection became more important to deal with longer transportation and medical inspection. The non-chemical use is very important due to stronger regulation of safety to agricultural production. Accordingly, this study was performed to determine the optimum conditions and develop a prototype washing machine, hot water washing of paprika. The results were as follows : The working performance of the prototype was 938 kg/hr, and which was 1.5 times higher than the conventional air gun type washing machine. The operation cost of prototype was 30 won/kg, and 56% of the cost was reduced when compared with air gun type washing machine.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.435-446
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• 2020

With the ability to learn rules from training data, the machine learning model can classify unknown objects. At the same time, the dimension of hyperspectral data is usually large, which may cause an over-fitting problem. In this research, an identification methodology of tea diseases was proposed based on spectral reflectance and machine learning, including the feature selector based on the decision tree and the tea disease recognizer based on random forest. The proposed identification methodology was evaluated through experiments. The experimental results showed that the recall rate and the F1 score were significantly improved by the proposed methodology in the identification accuracy of tea disease, with average values of 15%, 7%, and 11%, respectively. Therefore, the proposed identification methodology could make relatively better feature selection and learn from high dimensional data so as to achieve the non-destructive and efficient identification of different tea diseases. This research provides a new idea for the feature selection of high dimensional data and the non-destructive identification of crop diseases.