• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.131-145
• /
• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of the Microelectronics and Packaging Society
• /
• v.30 no.4
• /
• pp.79-85
• /
• 2023

A novel low-temperature co-fired ceramic (LTCC) dielectric, composed of (1-4x)Bi_1.5Zn_1.0Nb_1.5O₇-3xBi₂Zn_2/3Nb_4/3O₇-2xLiZnNbO₄ (x=0.03-0.21), was synthesized through reactive liquid phase sintering of Bi_1.5Zn_1.0Nb_1.5O₇-xLi₂CO₃ ceramic at temperatures ranging from 850℃ to 920℃ for 4 hours. During sintering, Li₂CO₃ reacted with Bi_1.5Zn_1.0Nb_1.5O₇, resulting in the formation of Bi₂Zn_2/3Nb_4/3O₇, and LiZnNbO₄. The resulting sintered body exhibited a relative sintering density exceeding 96% of the theoretical density. By altering the initial Li₂CO₃ content (x) and consequently modulating the volume fraction of Bi_1.5Zn_1.0Nb_1.5O₇, Bi₂Zn_2/3Nb_4/3O₇, and LiZnNbO₄ in the final sintered body, a sample with high dielectric constant (ε_r), low dielectric loss (tan δ), and the temperature coefficient of dielectric constant (TCε) characterized by NP0 specification (TCε ≤ ±30 ppm/℃) was achieved. As the Li₂CO₃ content increased from x=0.03 mol to x=0.15 mol, the volume fraction of Bi₂Zn_2/3Nb_4/3O₇ and LiZnNbO₄ in the composite increased, while the volume fraction of Bi_1.5Zn_1.0Nb_1.5O₇ decreased. Consequently, the dielectric constant (εr) of the composite materials varied from 148.38 to 126.99, the dielectric loss (tan δ) shifted from 5.29×10^-4 to 3.31×10^-4, and the temperature coefficient of dielectric constant (TCε) transitioned from -340.35 ppm/℃ to 299.67 ppm/℃. A dielectric exhibiting NP0 characteristics was achieved at x=0.09 for Li₂CO₃, with a dielectric constant (ε_r) of 143.06, a dielectric loss (tan δ) value of 4.31×10^-4, and a temperature coefficient of dielectric constant (TCε) value of -9.98 ppm/℃. Chemical compatibility experiment with Ag electrode revealed that the developed composite material exhibited no reactivity with the Ag electrode during the co-firing process.

• Korean Journal of Agricultural Science
• /
• v.9 no.2
• /
• pp.546-555
• /
• 1982

To evaluate the digestibility and absorbability of proteins, and the rates of energy and nitrogen(N) metabolism of the Korean native goats, studies were carried out with open type respiration apparatus based on the nitrogen-carbon method. The results on the nitrogen retention and the metabolic rate of energy, which was obtained with one male (10-month-old) and one female (24-month-old) goats, both weighing ${\simeq}20kg$, are summarized as follows. 1. When the goats were fed ad libitum the medium quality orchard grass hay, they consumed hay about 0.66 to 0.92% of body weight per day. The hay intake was remained the same even when high quality hay was provided. This amount of hay intake was relatively lower than that of dairy goat and sheep. It was believed to be partly due to the change in feeding enviroment. When fed with hay and soybean meal together, the goats ate hay about 1.06% and soybean meal about 0.60% of body weight, corresponding to 1.66% of body weight as fed basis. 2. The $CO_2$ gas produced from the goat in the open type respiration chamber and absorbed with KOH solution was estimated to be 99~117g/day. The difference in feed intake did not influence the $CO_2$ production; however, these seems to be a linea relationship between body weight and $CO_2$ production. 3. When fed orchard grass hay only, the goats showed protein digestibility of 24~41%. The protein digestibility incresed to 58.2% when fed hay and soybean meal together. A negative nitrogen balance(-0.16g N/day) was observed with goats fed 11.53g N originated from 212g hay and 150g soybean meal. Converting that nitrogen ingested to a crude protein, the amount of crude protein intake by the goats per day was 77.9g compared to 40~45g N known to be required in a day by goat weighing 20kg, indicating that the extra protein ingested was metabolized to provide energy. 4. When the male and female goats comsumed 624 kcal gross energy and 824 kcal gross energy by consuming 158g and 213g of hay, respectively, the digestible energy intake was calculated to be 260kcal for the male and 199kcal for the female goat. The daily heat production of male and female goats were 338kcal and 334kcal, respectively, when fed hay only. However, the female goat fed 212g hay and 150g soybean meal produced about 591kcal per day. Consequently, the energy requirment of the Korean native goats weighing ${\simeq}20kg$ was concluded to be $${\geq_-}$$600kcal net energy per day. 5. The fasting heat product ion of a male goat weighing 27.7kg was 412kcal per day when fasted for 2~3 days. When fasted for 3~4 days, the value decresed to 240kcal. The enviromental temperatures during the expreimental period were ranged from 19 to $34.5^{\circ}C$. The goats seemed to be panting when the chamber temperature rose to $32^{\circ}C$ or above. 6. When fed low levels of dietary protein, serum protein levels of the goats were decresed slightly ($${\leq_-}$$10%); however, urea content in the serum was observed to decrese to a great extent (3X).