• Journal of Intelligence and Information Systems
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• v.13 no.4
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• pp.45-63
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• 2007

Recently as ubiquitous environment comes to the fore, information density is raised and enterprise is being able to capture and utilize customer-related information at the same time when the customer purchases a product. In this environment, a need for the recommender systems which can deliver proper information to the customer at the right time and right situation is highly increased. Therefore, the research on recommender systems continued actively in a variety of fields. Until now, most of recommender systems deal with item recommendation. However, in the market in ubiquitous environment where the same item can be purchased at several stores, it is highly desirable to recommend store to the customer based on his/her contextual situation and preference such as store location, store atmosphere, product quality and price, etc. In this line of research, we proposed the store recommender system using customer's contextual situation and preference in the market in ubiquitous environment. This system is based on collaborative filtering and Apriori algorithms. It will be able to provide customer-centric service to the customer, enhance shopping experiences and contribute in revitalizing market in the long term.

• Journal of the Korean Chemical Society
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• v.59 no.5
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• pp.429-433
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• 2015

The binding ability and hydrogen storage capacity of nitrogen doped carbon nanotube with divacancy (4NDCN_xNT) that is decorated with transition metals was investigated based on density functional theory calculations. Results indicate that scandium shows an ideal reversible hydrogen binding capability with promising system-weight efficiency compared with other transition metals when functionalized with 4ND-CN_xNT. The (Sc/4ND)₁₀-CN_xNT can store up to 50H₂ molecules, corresponding to a maximum gravimetric density of 5.8 wt%. Detailed structural stability and electronic properties were reported as hydrogen molecules were absorbed. It takes about 0.16 eV/H₂ to add one H₂ molecule, which assures reversible storage of H₂ molecules under ambient conditions.

• Applied Chemistry for Engineering
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• v.20 no.2
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• pp.117-125
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• 2009

In order to utilize natural gas (NG), one of the clean energy sources in next-generation, as a fuel for vehicles, it is important to store natural gas with high density. To store NG by adsorption (ANG) at room temperature and at relatively low pressure(35~40 atm) is safe and economical compared with compressed NG and liquefied NG. However, so far no adsorbent is reported to have adsorption capacity suitable for commercial applications. Nanoporous materials including metal-organic frameworks can be potential adsorbents for ANG. In this review, physicochemical properties of adsorbents necessary for high adsorption capacity are summarized. Wide surface area, large micropore volume, suitable pore size and high density are necessary for high energy density. Moreover, low adsorption-desorption energy, rapid adsorption-desorption kinetics and high delivery are needed. Recently, various efforts have been reported to utilize nanoporous materials in ANG, and it is expected to develop a nanoporous material suitable for ANG.

• Asia pacific journal of information systems
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• v.18 no.3
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• pp.123-145
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• 2008

Recently, as the information communication technology develops, the discussion regarding the ubiquitous environment is occurring in diverse perspectives. Ubiquitous environment is an environment that could transfer data through networks regardless of the physical space, virtual space, time or location. In order to realize the ubiquitous environment, the Pervasive Sensing technology that enables the recognition of users' data without the border between physical and virtual space is required. In addition, the latest and diversified technologies such as Context-Awareness technology are necessary to construct the context around the user by sharing the data accessed through the Pervasive Sensing technology and linkage technology that is to prevent information loss through the wired, wireless networking and database. Especially, Pervasive Sensing technology is taken as an essential technology that enables user oriented services by recognizing the needs of the users even before the users inquire. There are lots of characteristics of ubiquitous environment through the technologies mentioned above such as ubiquity, abundance of data, mutuality, high information density, individualization and customization. Among them, information density directs the accessible amount and quality of the information and it is stored in bulk with ensured quality through Pervasive Sensing technology. Using this, in the companies, the personalized contents(or information) providing became possible for a target customer. Most of all, there are an increasing number of researches with respect to recommender systems that provide what customers need even when the customers do not explicitly ask something for their needs. Recommender systems are well renowned for its affirmative effect that enlarges the selling opportunities and reduces the searching cost of customers since it finds and provides information according to the customers' traits and preference in advance, in a commerce environment. Recommender systems have proved its usability through several methodologies and experiments conducted upon many different fields from the mid-1990s. Most of the researches related with the recommender systems until now take the products or information of internet or mobile context as its object, but there is not enough research concerned with recommending adequate store to customers in a ubiquitous environment. It is possible to track customers' behaviors in a ubiquitous environment, the same way it is implemented in an online market space even when customers are purchasing in an offline marketplace. Unlike existing internet space, in ubiquitous environment, the interest toward the stores is increasing that provides information according to the traffic line of the customers. In other words, the same product can be purchased in several different stores and the preferred store can be different from the customers by personal preference such as traffic line between stores, location, atmosphere, quality, and price. Krulwich(1997) has developed Lifestyle Finder which recommends a product and a store by using the demographical information and purchasing information generated in the internet commerce. Also, Fano(1998) has created a Shopper's Eye which is an information proving system. The information regarding the closest store from the customers' present location is shown when the customer has sent a to-buy list, Sadeh(2003) developed MyCampus that recommends appropriate information and a store in accordance with the schedule saved in a customers' mobile. Moreover, Keegan and O'Hare(2004) came up with EasiShop that provides the suitable tore information including price, after service, and accessibility after analyzing the to-buy list and the current location of customers. However, Krulwich(1997) does not indicate the characteristics of physical space based on the online commerce context and Keegan and O'Hare(2004) only provides information about store related to a product, while Fano(1998) does not fully consider the relationship between the preference toward the stores and the store itself. The most recent research by Sedah(2003), experimented on campus by suggesting recommender systems that reflect situation and preference information besides the characteristics of the physical space. Yet, there is a potential problem since the researches are based on location and preference information of customers which is connected to the invasion of privacy. The primary beginning point of controversy is an invasion of privacy and individual information in a ubiquitous environment according to researches conducted by Al-Muhtadi(2002), Beresford and Stajano(2003), and Ren(2006). Additionally, individuals want to be left anonymous to protect their own personal information, mentioned in Srivastava(2000). Therefore, in this paper, we suggest a methodology to recommend stores in U-market on the basis of ubiquitous environment not using personal information in order to protect individual information and privacy. The main idea behind our suggested methodology is based on Feature Matrices model (FM model, Shahabi and Banaei-Kashani, 2003) that uses clusters of customers' similar transaction data, which is similar to the Collaborative Filtering. However unlike Collaborative Filtering, this methodology overcomes the problems of personal information and privacy since it is not aware of the customer, exactly who they are, The methodology is compared with single trait model(vector model) such as visitor logs, while looking at the actual improvements of the recommendation when the context information is used. It is not easy to find real U-market data, so we experimented with factual data from a real department store with context information. The recommendation procedure of U-market proposed in this paper is divided into four major phases. First phase is collecting and preprocessing data for analysis of shopping patterns of customers. The traits of shopping patterns are expressed as feature matrices of N dimension. On second phase, the similar shopping patterns are grouped into clusters and the representative pattern of each cluster is derived. The distance between shopping patterns is calculated by Projected Pure Euclidean Distance (Shahabi and Banaei-Kashani, 2003). Third phase finds a representative pattern that is similar to a target customer, and at the same time, the shopping information of the customer is traced and saved dynamically. Fourth, the next store is recommended based on the physical distance between stores of representative patterns and the present location of target customer. In this research, we have evaluated the accuracy of recommendation method based on a factual data derived from a department store. There are technological difficulties of tracking on a real-time basis so we extracted purchasing related information and we added on context information on each transaction. As a result, recommendation based on FM model that applies purchasing and context information is more stable and accurate compared to that of vector model. Additionally, we could find more precise recommendation result as more shopping information is accumulated. Realistically, because of the limitation of ubiquitous environment realization, we were not able to reflect on all different kinds of context but more explicit analysis is expected to be attainable in the future after practical system is embodied.

• Journal of the Korean Institute of Educational Facilities
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• v.17 no.6
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• pp.23-30
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• 2010

Because the effort to solve space shortage in academic libraries has never been successful, the rapid development of digital technology is being considered as a panacea to revolutionize analog libraries and to open a new era for digital libraries. However, this technology is yet to be perfected. Even with the use of digital technology, we are currently still looking for more space to accommodate newly printed materials and at the same time store valuable resources that are seldomly used. In 1985, Harvard adopted the industrial high-density shelving system into their library. No other retrieving system has proven to be more successful as the Harvard model. Presently, more than 50 colleges have built over 70 high-density library storage facilities. Rice University Library Service Center (RLSC) can be examined as an example of the Harvard-model. This paper will focus on assessing the operating system and architectural requirements of the RLSC which may allow for a more efficient, economical, and fundamental resolution to the library space shortage problem.

• Journal of Hydrogen and New Energy
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• v.32 no.6
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• pp.565-572
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• 2021

Hydrogen is currently produced from natural gas reforming or industrial process of by-product over than 90%. Additionally, there are green hydrogens based on renewable energy generation, but the import of green hydrogen from other countries is being considered due to the output variability depending on the weather and climate. Due to low density of hydrogen, it is difficult to storage and import hydrogen of large capacity. For improving low density issue of hydrogen, the gaseous hydrogen is liquefied and stored in cryogenic tank. Density of hydrogen increase from 0.081 kg/m³ to 71 kg/m3 when gaseous hydrogen transfer to liquid hydrogen. Density of liquid hydrogen is higher about 800 times than gaseous. However, since density and boiling point of liquid hydrogen is too lower than liquefied natural gas approximately 1/6 and 90 K, to store liquid hydrogen for long-term is very difficult too. To overcome this weakness, this paper introduces storage method of hydrogen based on liquid/solid (slush) and facilities for producing slush hydrogen to improve low density issue of hydrogen. Slush hydrogen is higher density and heat capacity than liquid hydrogen, can be expected to improve these issues.

• Transactions of the Society of Information Storage Systems
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• v.6 no.2
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• pp.63-67
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• 2010

Holographic data storage system is one of next generation high density optical memories. Thereby storing multiple data pages using multiplexing method in one spot, we can achieve high store density and fast access time. However, for uniform writing, we must control exposure time properly by the change of writing material characteristics. Many studies have been investigated about exposure time scheduling. However, once it is decided, we cannot change the scheduled time. Therefore, it is hard to obtain uniform data intensity. In this study, we propose exposure time control method using additional red beam as the monitoring signal. Through reconstructed red beam intensity in real time, we can adjust exposure time by the writing condition change. We construct compensation method mathematically and verify the feasibility of proposed method through the experiments.

• BMB Reports
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• v.50 no.6
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• pp.323-328
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• 2017

Lysophosphatidylcholine (LPC) is a major phospholipid component of oxidized low-density lipoprotein (ox-LDL) and is implicated in its atherogenic activity. This study investigated the effects of LPC on cell viability, intracellular calcium homeostasis, and the protective mechanisms of chlorogenic acid (CGA) in human umbilical vein endothelial cells (HUVECs). LPC increased intracellular calcium ($[Ca^{2+}]_i$) by releasing $Ca^{2+}$ from intracellular stores and via $Ca^{2+}$ influx through store-operated channels (SOCs). LPC also increased the generation of reactive oxygen species (ROS) and decreased cell viability. The mRNA expression of Transient receptor potential canonical (TRPC) channel 1 was increased significantly by LPC treatment and suppressed by CGA. CGA inhibited LPC-induced $Ca^{2+}$ influx and ROS generation, and restored cell viability. These results suggested that CGA inhibits SOC-mediated $Ca^{2+}$ influx and ROS generation by attenuating TRPC1 expression in LPC-treated HUVECs. Therefore, CGA might protect endothelial cells against LPC injury, thereby inhibiting atherosclerosis.

• Journal of the Semiconductor & Display Technology
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• v.19 no.3
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• pp.118-123
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• 2020

In this paper, the design method of asynchronous nonvolatile memory module that can efficiently process and store large amounts of data without loss when the power turned off is proposed and implemented. PSRAM, which takes advantage of DRAM and SRAM, was used for data processing, and NAND flash memory was used for data storage and backup. The problem of a lot of signal interference due to the characteristics of memory devices was solved through PCB design using high-density integration technology. In addition, a boost circuit using the super capacitor of 0.47F was designed to supply sufficient power to the system during the time to back up data when the power is off. As a result, an asynchronous nonvolatile memory module was designed and implemented that guarantees reliability and stability and can semi-permanently store data for about 10 years. The proposed method solved the problem of frequent data loss in industrial sites and presented the possibility of commercialization by providing convenience to users and managers.

• The Korean Journal of Physiology and Pharmacology
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• v.13 no.1
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• pp.27-32
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• 2009

The effects of oxidized low-density lipoprotein(OxLDL) and its major lipid constituent lysophosphatidylcholine(LPC) on $Ca^{2+}$ entry were investigated in cultured human umbilical endothelial cells(HUVECs) using fura-2 fluorescence and patch-clamp methods. OxLDL or LPC increased intracellular $Ca^{2+}$ concentration($[Ca^{2+}]_i$), and the increase of $[Ca^{2+}]_i$ by OxLDL or by LPC was inhibited by $La^{3+}$ or heparin. LPC failed to increase $[Ca^{2+}]_i$ in the presence of an antioxidant tempol. In addition, store-operated $Ca^{2+}$ entry(SOC), which was evoked by intracellular $Ca^{2+}$ store depletion in $Ca^{2+}$-free solution using the sarcoplasmic reticulum $Ca^{2+}$ pump blocker, 2, 5-di-t-butyl-l,4-benzohydroquinone(BHQ), was further enhanced by OxLDL or by LPC. Increased SOC by OxLDL or by LPC was inhibited by U73122. In voltage-clamped cells, OxLDL or LPC increased $[Ca^{2+}]_i$ and simultaneously activated non-selective cation(NSC) currents. LPC-induced NSC currents were inhibited by 2-APB, $La^{3+}$ or U73122, and NSC currents were not activated by LPC in the presence of tempol. Furthermore, in voltage-clamped HUVECs, OxLDL enhanced SOC and evoked outward currents simultaneously. Clamping intracellular $Ca^{2+}$ to 1 ${\mu}M$ activated large-conductance $Ca^{2+}$-activated $K^+(BK_{ca})$ current spontaneously, and this activated $BK_{ca}$ current was further enhanced by OxLDL or by LPC. From these results, we concluded that OxLDL or its main component LPC activates $Ca^{2+}$-permeable $Ca^{2+}$-activated NSC current and $BK_{ca}$ current simultaneously, thereby increasing SOC.