• Journal of Forest and Environmental Science
• /
• v.30 no.1
• /
• pp.1-14
• /
• 2014

Timber harvest in natural forests and its implications on carbon sequestration were investigated in the Southwestern Nigeria. Data on timber harvest from forest estates for a 3-year period were collected from the official record of States' Forestry Department. The data registered the species, volume and number of timbers exploited during the study period. The data were analyzed accordingly for rate of timber harvest and carbon value of the exploited timbers using existing biomass functions. Values were compared for significant differences among states using one way analysis of variance. The results showed that the most exploited logs, in terms of volume and number of trees, have the highest amount of carbon removal. There was a variation in type of timber species being exploited from each state. The total number of harvested trees from Oyo, Ondo, Ogun, Ekiti and Osun were estimated at 100,205; 111,789; 753; 15,884 and 18,153 respectively. Total quantity of carbon removed for the 3-year period stood at 2.3 million metric tons, and this translated to 8.4 million metric tons of $CO_2$. The annual carbon and $CO_2$ removal therefore were estimated at 760,120.73 tons and 2.8 million tons/ year respectively. There were significant differences (p<0.05) in the amount of $CO_2$ removed from the five states. Based on our result, we inferred that there is increasing pressure on economic tree species and it is plausible that they are becoming scarce from the forests in Southwestern Nigeria.. If the present rate of log removal is not controlled, forests could become carbon source rather than carbon sink and the on biological conservation, wood availability and climate change may turn out grave. For the forest to perform its environmental role as carbon sink, urgent conservation measures and logging policies are needed to be put in place.

• Journal of Biomedical Engineering Research
• /
• v.44 no.2
• /
• pp.147-156
• /
• 2023

Efforts to employ smart home sensors to monitor the indoor activities of elderly single residents have been made to assess the feasibility of a safe and healthy lifestyle. However, the bathroom remains an area of blind spot. In this study, we have developed and evaluated a new edge computer device that can automatically detect water usage activities in the bathroom and record the activity log on a cloud server. Three kinds of sound as flushing, showering, and washing using wash basin generated during water usage were recorded and cut into 1-second scenes. These sound clips were then converted into a 2-dimensional image using MEL-spectrogram. Sound data augmentation techniques were adopted to obtain better learning effect from smaller number of data sets. These techniques, some of which are applied in time domain and others in frequency domain, increased the number of training data set by 30 times. A deep learning model, called CRNN, combining Convolutional Neural Network and Recurrent Neural Network was employed. The edge device was implemented using Raspberry Pi 4 and was equipped with a condenser microphone and amplifier to run the pre-trained model in real-time. The detected activities were recorded as text-based activity logs on a Firebase server. Performance was evaluated in two bathrooms for the three water usage activities, resulting in an accuracy of 96.1% and 88.2%, and F1 Score of 96.1% and 87.8%, respectively. Most of the classification errors were observed in the water sound from washing. In conclusion, this system demonstrates the potential for use in recording the activities as a lifelog of elderly single residents to a cloud server over the long-term.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.11a
• /
• pp.1188-1191
• /
• 2021

The function of the black box can be combined with a car to check the video through a cloud server, reduce the hassle of checking the video through a memory card, check the black box image in real time through a PC and smartphone, and check the user's Excel, brake operation status, and handle control record at the time of the accident. In addition, the goal was to accurately identify vehicle accidents and simplify accident handling through artificial intelligence object recognition of black box images using cloud services. Measures can be prepared to preserve images even if the black box itself loses, such as fire, flooding, or damage that occurs in an accident. It has been confirmed that the exact situation before and after the accident can be grasped immediately by providing object recognition and log recording functions under actual driving experimental conditions.

• The Journal of Fisheries Business Administration
• /
• v.4 no.1_2
• /
• pp.19-57
• /
• 1973

Laver io one of the most necessary and seasonal items in Korean food from oldtimes. Laver is lagely eaten in dried form, and its supply depends entirely upon culture weeds. The history of laver culture in Korea about sixty or seventy years is older than in Japan. Significance of laver culture is divided into two aspects, one is food supply in the nation, and the other is export to other countries. Houses engaged in laver culture are about foully thousands, and laver production in 1972 is estimated as 1, 3 bitten sheets. (1 sheet is a dried laver of 20 cm sq, in the shape of paper) Especcially meaning of layer production is the concentration of labour input, and systematic management of labour. From around 1920, the method of laver culture was introduced by Japanese Imperialism for mono culture in shallow seas, and mass products of laver is provided to Japan market, DOMESTIC MARKET Fundamental consume function calculates at below, $D_{(68_71)}$=16354 $Y^{0.471}$ $P^{-1.0662}$ where D is total layer demand, Y income variable, P price variable. It means income elasticity is 476. in the whole country, and price elasticity is 1, 07. But generally income elasticity is higher in urban area than in rural area, as shown at 1, 3 in Seoul city. Expence of laver in house expenditure is mutually correlated with another expence, See Table 12 about the relative function. See Table 14 and 16 about the relation between the gathering and the changes of price in auction, wholesale and retail price support system is for two effects, one of which is constraint of the upper price, the other is rise of the lower price. Before the system control, the equation in three year average calculated as below, $Y_{b}$ ＝18, 907.7455＋15435.9364 t (r=0.89) where the origin t＝0 is the November and the units are month. Post the system control, $Y_{p}$ =30, 047.9636+1, 631.1721t (r＝0.97) therefore, this system has an effect only on the rise of lower price, Average annual margins of laver products at four market levels according to the consumer spent is below. EXPORTING MARKET Japanese demand function of laver products is, Log D=5, 289+1, 108 Log Y-1, 395 Log P (r=0.987) where D is Japanese laver demand, Y income variable, P price variable. according to which income elasticity is 1. 1 and price elasticity is 1.4. Laver production in 1970 tile highest record till then, is estimated as six billion sheets. But the recent improvement of laver culture techniques, the production of seeds and freezing storage of seeds has been stabilized. Futher new culture farms have been developed by means of break- water fences or by floating culture method. These improvements have been backed up with increased demand of laver products. Import quantity and price of Korean laver products are restrained by three organizations, that is producer, distributor and consumer. This relationship calculated by regression equation shows that import is influenced only producer organization, at the sacrifice of consumer profit. For increase to export of laver products, we urgently require to open foreign trade of laver products for Japanese consumer, .and Japan has political responsibility to solve Korean laver structure. But with long run timeseries, as regards Japanese production and import quantity, importing function shows increasing trend as below, 250 million sheets ＜3, 947.1674+0.005 $L_{g}$ ＞) 600 million sheets where $L_{q}$ is relative production quantity of laver in Japan. (unit; 100 thousand sheets) Our Export effort should be put on the highly processed products whithin the restraind quote.ote.

• KIISE Transactions on Computing Practices
• /
• v.21 no.2
• /
• pp.154-159
• /
• 2015

Over the past few years, user needs in the smartphone application market have been shifted from diversity toward intelligence. Here, we propose a novel cognitive agent that plans the daily routines of users using the lifelog data collected by the smart phones of individuals. The proposed method first employs DPGMM (Dirichlet Process Gaussian Mixture Model) to automatically extract the users' POI (Point of Interest) from the lifelog data. After extraction, the POI and other meaningful features such as GPS, the user's activity label extracted from the log data is then used to learn the patterns of the user's daily routine by POMDP (Partially Observable Markov Decision Process). To determine the significant patterns within the user's time dependent patterns, collaboration was made with the SNS application Foursquare to record the locations visited by the user and the activities that the user had performed. The method was evaluated by predicting the daily routine of seven users with 3300 feedback data. Experimental results showed that daily routine scheduling can be established after seven days of lifelogged data and feedback data have been collected, demonstrating the potential of the new method of place-time-activity coupled daily routine planning systems in the intelligence application market.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.11 no.6
• /
• pp.764-771
• /
• 2018

Domestic and foreign agricultural environments nowadays are undergoing various changes such as aging of agricultural population, increase of earned population, rapid climate change, diversification of agricultural product distribution structure, depletion of water resources and limited cultivation area. In order to respond to various environmental changes in recent agriculture, practical use of Smart Greenhouse to easily record, store and manage crop production information such as crop growing information, growth environment and agriculture work log, Interest is growing. In this paper, we propose a system that collects the situation information necessary for growth such as temperature, humidity, solar radiation, CO2 concentration, and monitor the collected data, which can be measured in the rhizosphere of the crop. We have developed a system that collects data such as temperature, humidity, radiation, and growth environment data, which are measured by data obtained from the rhizosphere measuring section of a growing crop and measured by a sensor, and transmitted to a wireless communication gateway of 400 MHz. We developed the integrated SW that can monitor the rhythm environment data and visualize the data by using cloud based data. We can monitor by graph format and data format for visualization of data. The existing smart farm managed crops and facilities using only the data within the farm, and this study suggested the most efficient growth environment by collecting and analyzing the weather and growth environment of the farms nationwide.

• Journal of radiological science and technology
• /
• v.28 no.4
• /
• pp.317-325
• /
• 2005

The recent medical treatment guidelines and the development of information technology make hospitals reduce the expense in surrounding environment and it requires improving the quality of medical treatment of the hospital. That is, with the new guidelines and technology, hospital business escapes simple fee calculation and insurance claim center. Moreover, MIS(Medical Information System), PACS(Picture Archiving and Communications System), OCS(Order Communicating System), EMR(Electronic Medical Record), DSS(Decision Support System) are also developing. Medical Information System is evolved toward integration of medical IT and situation si changing with increasing high speed in the ICT convergence. These changes and development of ubiquitous environment require fundamental change of medical information system. Mobile medical information system refers to construct wireless system of hospital which has constructed in existing environment. Through RFID development in existing system, anyone can log on easily to Internet whenever and wherever. RFID is one of the technologies for Automatic Identification and Data Capture(AIDC). It is the core technology to implement Automatic processing system. This paper provides a comprehensive basic review of RFID model in Korea and suggests the evolution direction for further advanced RFID application services. In addition, designed and implemented DB server's agent program and Client program of Mobile application that recognized RFID tag and patient data in the ubiquitous environments. This system implemented medical information system that performed patient data based EMR, HIS, PACS DB environments, and so reduced delay time of requisition, medical treatment, lab.

• Journal of Mushroom
• /
• v.11 no.4
• /
• pp.230-239
• /
• 2013

The major species of fungus gnats which caused the severe damage in shiitake farm were identified as a Bradysia difformis, B. alpicola, and Camtomyia cortocalis on oak log beds cultivation. The B. difformis occurred early in the middle of March while B. alpicola and C. cortocalis appeared since the beginning of May. The occurrence rate for adults of B. difformis showed highly at the end of July (11.9~1,774.2 in dong-myeon and 0.4~2,583.3 in pungse-myeon) in 2012 and mid-June (10.7~4,650 in dong-myeon and 36.8~4740 in pungse-myeon) in 2013. The counting numbers on the traps for B. alpicola reached highest peak in the middle of June (2.1~63.2 in dong-myeon and 1.0~21.7 in pungse-myeon) and the end of May (0.8~163.7 in dong-myeon and 0.5~280.5 in pungse-myeon) in 2012 and 2013, respectively. The number of C. cortocalis showed high record in the middle of May in 2012 (0.6~4.7) and in the middle of June (2.1~17.3) in 2013 in dong-myeon whereas showed the peaks in the middle of May (0.6~4.7) in 2012 and in the late of May (1.3~17.6) in 2013 in pungse-myeon. The fruiting bodies of shiitake mushroom by fungus gnats were severely damaged from mid-June to late-July and the damage rate were 0.625.5% (2012) and 0.7~30.5% (2013) in dong-myeon and 1.5%~21.6% (2012) and 1.9~36.8%(2012) in pungse-myeon. To investigate the control effect for fungus gnats by Hypoaspis aculeifer, H. aculeifer (30 mixutre of nymph and adult per $m^2$) were treated to oak log beds shiitake cultivation for six times (May 2 and 28, June 25, July 10 and 25 and August 28). The occurrence rate of adults and damage rate of fruiting bodies of 3 major species reduced 79.3% (adult numbers) and 74.8% (fruiting bodies) in dong-myeon and 64.1% (adult numbers) and 65.5% (fruiting bodies) in pungse-myeon, respectively, compared to non-treatment. Accordingly, H. aculeifer effectively controlled the fungus gnats on shiitake mushroom and can be used as good control agent.

• Journal of Intelligence and Information Systems
• /
• v.27 no.2
• /
• pp.1-15
• /
• 2021

If it is difficult for us to make decisions, we ask for advice from friends or people around us. When we decide to buy products online, we read anonymous reviews and buy them. With the advent of the Data-driven era, IT technology's development is spilling out many data from individuals to objects. Companies or individuals have accumulated, processed, and analyzed such a large amount of data that they can now make decisions or execute directly using data that used to depend on experts. Nowadays, the recommender system plays a vital role in determining the user's preferences to purchase goods and uses a recommender system to induce clicks on web services (Facebook, Amazon, Netflix, Youtube). For example, Youtube's recommender system, which is used by 1 billion people worldwide every month, includes videos that users like, "like" and videos they watched. Recommended system research is deeply linked to practical business. Therefore, many researchers are interested in building better solutions. Recommender systems use the information obtained from their users to generate recommendations because the development of the provided recommender systems requires information on items that are likely to be preferred by the user. We began to trust patterns and rules derived from data rather than empirical intuition through the recommender systems. The capacity and development of data have led machine learning to develop deep learning. However, such recommender systems are not all solutions. Proceeding with the recommender systems, there should be no scarcity in all data and a sufficient amount. Also, it requires detailed information about the individual. The recommender systems work correctly when these conditions operate. The recommender systems become a complex problem for both consumers and sellers when the interaction log is insufficient. Because the seller's perspective needs to make recommendations at a personal level to the consumer and receive appropriate recommendations with reliable data from the consumer's perspective. In this paper, to improve the accuracy problem for "appropriate recommendation" to consumers, the recommender systems are proposed in combination with context-based deep learning. This research is to combine user-based data to create hybrid Recommender Systems. The hybrid approach developed is not a collaborative type of Recommender Systems, but a collaborative extension that integrates user data with deep learning. Customer review data were used for the data set. Consumers buy products in online shopping malls and then evaluate product reviews. Rating reviews are based on reviews from buyers who have already purchased, giving users confidence before purchasing the product. However, the recommendation system mainly uses scores or ratings rather than reviews to suggest items purchased by many users. In fact, consumer reviews include product opinions and user sentiment that will be spent on evaluation. By incorporating these parts into the study, this paper aims to improve the recommendation system. This study is an algorithm used when individuals have difficulty in selecting an item. Consumer reviews and record patterns made it possible to rely on recommendations appropriately. The algorithm implements a recommendation system through collaborative filtering. This study's predictive accuracy is measured by Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). Netflix is strategically using the referral system in its programs through competitions that reduce RMSE every year, making fair use of predictive accuracy. Research on hybrid recommender systems combining the NLP approach for personalization recommender systems, deep learning base, etc. has been increasing. Among NLP studies, sentiment analysis began to take shape in the mid-2000s as user review data increased. Sentiment analysis is a text classification task based on machine learning. The machine learning-based sentiment analysis has a disadvantage in that it is difficult to identify the review's information expression because it is challenging to consider the text's characteristics. In this study, we propose a deep learning recommender system that utilizes BERT's sentiment analysis by minimizing the disadvantages of machine learning. This study offers a deep learning recommender system that uses BERT's sentiment analysis by reducing the disadvantages of machine learning. The comparison model was performed through a recommender system based on Naive-CF(collaborative filtering), SVD(singular value decomposition)-CF, MF(matrix factorization)-CF, BPR-MF(Bayesian personalized ranking matrix factorization)-CF, LSTM, CNN-LSTM, GRU(Gated Recurrent Units). As a result of the experiment, the recommender system based on BERT was the best.

• Journal of Intelligence and Information Systems
• /
• v.19 no.2
• /
• pp.177-189
• /
• 2013

In Smart Education, the roles of digital textbook is very important as face-to-face media to learners. The standardization of digital textbook will promote the industrialization of digital textbook for contents providers and distributers as well as learner and instructors. In this study, the following three objectives-oriented digital textbooks are looking for ways to standardize. (1) digital textbooks should undertake the role of the media for blended learning which supports on-off classes, should be operating on common EPUB viewer without special dedicated viewer, should utilize the existing framework of the e-learning learning contents and learning management. The reason to consider the EPUB as the standard for digital textbooks is that digital textbooks don't need to specify antoher standard for the form of books, and can take advantage od industrial base with EPUB standards-rich content and distribution structure (2) digital textbooks should provide a low-cost open market service that are currently available as the standard open software (3) To provide appropriate learning feedback information to students, digital textbooks should provide a foundation which accumulates and manages all the learning activity information according to standard infrastructure for educational Big Data processing. In this study, the digital textbook in a smart education environment was referred to open digital textbook. The components of open digital textbooks service framework are (1) digital textbook terminals such as smart pad, smart TVs, smart phones, PC, etc., (2) digital textbooks platform to show and perform digital contents on digital textbook terminals, (3) learning contents repository, which exist on the cloud, maintains accredited learning, (4) App Store providing and distributing secondary learning contents and learning tools by learning contents developing companies, and (5) LMS as a learning support/management tool which on-site class teacher use for creating classroom instruction materials. In addition, locating all of the hardware and software implement a smart education service within the cloud must have take advantage of the cloud computing for efficient management and reducing expense. The open digital textbooks of smart education is consdered as providing e-book style interface of LMS to learners. In open digital textbooks, the representation of text, image, audio, video, equations, etc. is basic function. But painting, writing, problem solving, etc are beyond the capabilities of a simple e-book. The Communication of teacher-to-student, learner-to-learnert, tems-to-team is required by using the open digital textbook. To represent student demographics, portfolio information, and class information, the standard used in e-learning is desirable. To process learner tracking information about the activities of the learner for LMS(Learning Management System), open digital textbook must have the recording function and the commnincating function with LMS. DRM is a function for protecting various copyright. Currently DRMs of e-boook are controlled by the corresponding book viewer. If open digital textbook admitt DRM that is used in a variety of different DRM standards of various e-book viewer, the implementation of redundant features can be avoided. Security/privacy functions are required to protect information about the study or instruction from a third party UDL (Universal Design for Learning) is learning support function for those with disabilities have difficulty in learning courses. The open digital textbook, which is based on E-book standard EPUB 3.0, must (1) record the learning activity log information, and (2) communicate with the server to support the learning activity. While the recording function and the communication function, which is not determined on current standards, is implemented as a JavaScript and is utilized in the current EPUB 3.0 viewer, ths strategy of proposing such recording and communication functions as the next generation of e-book standard, or special standard (EPUB 3.0 for education) is needed. Future research in this study will implement open source program with the proposed open digital textbook standard and present a new educational services including Big Data analysis.