Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational safety and reliability of the parcel loading system, a predictive maintenance platform was implemented based on the Naive Bayes-LSTM(Long Short Term Memory) model. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on a RabbitMQ, loading data in an InMemory method using a Redis, and managing snapshot DB in real time. Also, in this paper, as a verification of the Naive Bayes-LSTM predictive maintenance platform, the function of measuring the time for data collection/storage/processing and determining outliers/normal values was confirmed. The predictive maintenance platform can contribute to securing reliability and safety by identifying potential failures and defects that may occur in the operation of the parcel loading system in the future.

The aim of this study was to prepare rice straw silage using cabbage by-product and persimmon peel which are agricultural by-products produced during the same season in Korea. The treatments comprised a commercial corn silage as the control and four rice straw silages (P15-1, P15-2, P30-1, and P30-2) with different levels of persimmon peel supplementation (15%, 30%) and ensiled periods (1 or 2 months). The cabbage by-products were used to adjust silage moisture (approximately 65%). The quality of the experimental silages was evaluated based on organic acid content, palatability to three Holstein dairy cows, and manufacturing cost. In the corn silage, all chemical compositions, except total digestible nutrients and levels of lactic and butyric acids, were significantly (p<0.05) higher than those of the rice straw silages. However, considering the quality analysis using Flieg's score, the rice straw silage supplemented with 30% persimmon peel ensiled for 2 months (P30-2) was estimated as second grade to corn silage, and was relatively better in palatability to dairy cows than the other rice straw silages, which were considered third grade. The manufacturing cost of rice straw silages using cabbage by-product and persimmon peel compared to that of corn silage was reduced by 28%. Consequently, to prepare rice straw silage adjusted to 65% moisture using only cabbage by-products without inoculant, 30% of persimmon peel, 10% of ground corn, and 2% of molasses as a sugar source should be ensiled for at least 2 months.

PURPOSES : The purpose of this study is to verify the influences on the compactibility evaluation of WMA (Warm Mix Asphalt) mixture by laboratory experiments. METHODS : Two types of WMA additives (chemical and wax types) and two types of compactors (marshall and gyratory) are used in laboratory experiments. In addition, two types of WMA processes (wet and dry) are tested to verify the impact of manufacturing process. RESULTS : The laboratory results show that the effects of compaction method on compactibility are different depending on the type of additive. The compaction method has a significant impact on WMA mixture with chemical type additive to extent that it determines whether required criterion is satisfied, but only little on WMA mixture with wax type additive. In the case of wet process for WMA mixture manufacturing, it is hard to assess the air void of HMA mixture made of same asphalt binder used in WMA mixture since the additive has already been added in asphalt binder. And the test results show that air voids of HMA mixture vary within properties of asphalt binder. CONCLUSIONS : Through this study, it is found that compactibility of WMA mixture is affected by the compaction methods depending on the additive types and by the WMA mixture manufacturing process. Therefore, those are recommended to be considered when evaluating compactibility of WMA mixtures.

The consumption of enoki mushrooms has been associated with cases of listeriosis produced by Listeria monocytogenes, highlighting the significance of sanitizing food-contact surface, such as the velcro used in welding processing of enoki mushrooms, to ensure microbial safety. We investigated the inhibitory activity of nine chemical disinfectants at regular concentrations against L. monocytogenes isolated from a mushroom farm environment. The bacterial suspension was prepared in phosphate buffered saline and mushroom extract broth and inoculated onto the velcro surface. After inoculation, most disinfectants reduced the initial 8 log CFU/coupon concentration by less than 2 log CFU/coupon during a 5-min treatment. Slightly acidic hypochlorous water showed a reduction of approximately 4 log CFU/coupon when tested for more than 30 min at the maximum allowable concentration of 200 mg/L. Sodium hypochlorite solution showed a reduction of approximately 5 log CFU/coupon when used at 100 mg/L for 60 min. Peracetic acid, at the maximum allowable concentration of 300 mg/L, showed the most effective reduction of 5 log CFU/coupon or more when the surface was treated with 37.5 mg/L for 30 min. These results indicate that peracetic acid can be used as the disinfectant strategy to control cross-contamination of L. monocytogenes on the velcro surface of plastic wrappers used in the welding processing of enoki mushrooms.

GC-MS/MS using liquid-liquid extraction (LLE) and C18 cartridges was used to identify and quantify levels of chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin and permethrin in bulk raw milk. A calibration curve spanning 10 ng/mL to 200 ng/mL was obtained with a satisfactory correlation coefficient of 0.99. The limits of detection (LOD) and limits of quantitation (LOQ) for chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin, and permethrin in the matrix ranged from 0.06 to 1.81 ng/mL and 0.19 to 6.04 ng/mL, respectively. The recoveries of 5 pesticides from spiked samples at 37.5-125 ng/mL ranged from 86.1 to 102.1%. The measurement of uncertainty of the GC-MS/MS method for these five pesticides was developed based on the analytical process and quantification. An analysis method that is easier and faster than the method specified in the Korean food standards codes for analyzing these five pesticides in raw material milk was developed. Moreover, the analytical method for chlorpyrifos, chlorpyrifos-methyl, cypermethrin, deltamethrin, and permethrin in bulk raw milk by GC-MS/MS was established.