• Parasites, Hosts and Diseases
• /
• v.60 no.4
• /
• pp.241-246
• /
• 2022

Felids are the unique definitive host of Toxoplasma gondii. The intestine of felid is the only site for initiating Toxoplasma gondii sexual reproduction. T. gondii excretes millions of infectious oocysts from the intestine, which are the primary source of infection. There are many difficulties in developing vaccines and drugs to control oocyst excretion due to the lack of an appropriate experimental model. Here, we established an in vitro feline intestinal epithelial cell (IEC) infection system and an efficient animal model of T. gondii Chinese 1 genotype, Wh6 strain (TgCtwh6). The Kunming mice brain tissues containing TgCtwh6 cysts were harvested 42-day post-infection. The bradyzoites were co-cultured with cat IECs in vitro at a ratio of 1:10. Five 3-month-old domestic cats were orally inoculated with 600 cysts each. The oocysts were detected by daily observation of cat feces by microscopy and polymerase chain reaction. We found that the parasite adhered and invaded cat IECs in vitro, transformed into tachyzoites, and then divided to form rose-like structures. These parasites eventually destroyed host cells, escaped, and finished the asexual reproduction process. Schizonts associated with sexual reproduction have not been observed during development in vitro cultured cells. However, schizonts were detected in all infected cat intestinal epithelial cells, and oocysts were presented in all cat feces. Our study provides a feasible cell model and an efficient infection system for the following studies of T. gondii sexual reproduction, and also lays a foundation to develop drugs and vaccines for blocking excretion and transmission of oocysts.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.2060-2077
• /
• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.10
• /
• pp.794-805
• /
• 2017

This paper proposes a Hardware-In-Loop(HIL) Simulator for a Wind Turbine and an operational control algorithm to evaluate the performance of a wind turbine control system. It provides not only for the validation of the control logics, safety functions and H/W failure, but also for the high reliability of the wind turbines (by reducing/and the reduction of the operating expense(OPEX) through performance evaluation tests with complex scenarios. On the other hand, the proposed simulator uses MATLAB, CODER, and the PLC library to operate in synchronization with the hardware, and a real-time processing-based wind turbine module including a dynamic model and control system, wind module, grid module and host PC to manage the HIL-simulator. Several experiments were carried out under the above concept to verify the effectiveness of the proposed WT HIL-simulator.

• Smart Structures and Systems
• /
• v.10 no.4_5
• /
• pp.411-426
• /
• 2012

The Canton Tower (formerly named Guangzhou New TV Tower) of 610 m high has been instrumented with a long-term structural health monitoring (SHM) system consisting of over 700 sensors of sixteen types. Under the auspices of the Asian-Pacific Network of Centers for Research in Smart Structures Technology (ANCRiSST), an SHM benchmark problem for high-rise structures has been developed by taking the instrumented Canton Tower as a host structure. This benchmark problem aims to provide an international platform for direct comparison of various SHM-related methodologies and algorithms with the use of real-world monitoring data from a large-scale structure, and to narrow the gap that currently exists between the research and the practice of SHM. This paper first briefs the SHM system deployed on the Canton Tower, and the development of an elaborate three-dimensional (3D) full-scale finite element model (FEM) and the validation of the model using the measured modal data of the structure. In succession comes the formulation of an equivalent reduced-order FEM which is developed specifically for the benchmark study. The reduced-order FEM, which comprises 37 beam elements and a total of 185 degrees-of-freedom (DOFs), has been elaborately tuned to coincide well with the full-scale FEM in terms of both modal frequencies and mode shapes. The field measurement data (including those obtained from 20 accelerometers, one anemometer and one temperature sensor) from the Canton Tower, which are available for the benchmark study, are subsequently presented together with a description of the sensor deployment locations and the sensor specifications.

• The KIPS Transactions:PartD
• /
• v.12D no.2 s.98
• /
• pp.289-302
• /
• 2005

The mobile agent has very various performance according to the element of communication number of times between hosts, quantity of transmission data agent's size, network state etc. specially, migration method is caused much effect in whole performance of distributed system. Most existing migration methods have simplicity structure that it moves doing to accumulate continuously result after achieving task by visiting host in the fixed order. Therefore, in case there are situation such as fault, obstacle, and service absence etc. This can be inefficient due to mobile agent increased network required time. In this paper, we design and implementation Multicast Migration Model for minimizing network required time by solving this problems. Multicast Migration Model includes components such as mobile agent including call module and naming agent, which provides object replication information and distributed server's location transparence. And we evaluate and compare with existing migration method applying prototype system to verify implemented migration model.

• Journal of Intelligence and Information Systems
• /
• v.23 no.4
• /
• pp.1-31
• /
• 2017

Modern businesses are adopting new technologies to serve their markets better as well as to improve efficiency and productivity. The advertising industry has continuously experienced disruptions from the traditional channels (radio, television and print media) to new complex ones including internet, social media and mobile-based advertising. This case study focuses on proposing intelligent advertising business model in Seoul's metro network. Seoul has one of the world's busiest metro network and transports a huge number of travelers on a daily basis. The high number of travelers coupled with a well-planned metro network creates a platform where marketers can initiate engagement and interact with both customers and potential customers. In the current advertising model, advertising is on illuminated and framed posters in the stations and in-car, non-illuminated posters, and digital screens that show scheduled arrivals and departures of metros. Some stations have digital screens that show adverts but they do not have location capability. Most of the current advertising media have one key limitation: space. For posters whether illuminated or not, one space can host only one advert at a time. Empirical literatures show that there is room for improving this advertising model and eliminate the space limitation by replacing the poster adverts with digital advertising platform. This new model will not only be digital, but will also provide intelligent advertising platform that is driven by data. The digital platform will incorporate location sensing, e-commerce, and mobile platform to create new value to all stakeholders. Travel cards used in the metro will be registered and the card scanners will have a capability to capture traveler's data when travelers tap their cards. This data once analyzed will make it possible to identify different customer groups. Advertisers and marketers will then be able to target specific customer groups, customize adverts based on the targeted consumer group, and offer a wide variety of advertising formats. Format includes video, cinemagraphs, moving pictures, and animation. Different advert formats create different emotions in the customer's mind and the goal should be to use format or combination of formats that arouse the expected emotion and lead to an engagement. Combination of different formats will be more effective and this can only work in a digital platform. Adverts will be location based, ensuring that adverts will show more frequently when the metro is near the premises of an advertiser. The advertising platform will automatically detect the next station and screens inside the metro will prioritize adverts in the station where the metro will be stopping. In the mobile platform, customers who opt to receive notifications will receive them when they approach the business premises of advertiser. The mobile platform will have indoor navigation for the underground shopping malls that will allow customers to search for facilities within the mall, products they may want to buy as well as deals going on in the underground mall. To create an end-to-end solution, the mobile solution will have a capability to allow customers purchase products through their phones, get coupons for deals, and review products and shops where they have bought a product. The indoor navigation will host intelligent mobile-based advertisement and a recommendation system. The indoor navigation will have adverts such that when a customer is searching for information, the recommendation system shows adverts that are near the place traveler is searching or in the direction that the traveler is moving. These adverts will be linked to the e-commerce platform such that if a customer clicks on an advert, it leads them to the product description page. The whole system will have multi-language as well as text-to-speech capability such that both locals and tourists have no language barrier. The implications of implementing this model are varied including support for small and medium businesses operating in the underground malls, improved customer experience, new job opportunities, additional revenue to business model operator, and flexibility in advertising. The new value created will benefit all the stakeholders.

• Convergence Security Journal
• /
• v.10 no.2
• /
• pp.1-9
• /
• 2010

Snort is an open source network intrusion prevention and detection system (IDS/IPS) developed by Sourcefire. Combining the benefits of signature, protocol and anomaly-based inspection, Snort is the most widely deployed IDS/IPS technology worldwide. With millions of downloads and approximately 300,000 registered users. Snort identifies network indicators by inspecting network packets in transmission. A process on a host's machine usually generates these network indicators. This means whatever the snort signature matches the packet, that same signature must be in memory for some period (possibly micro seconds) of time. Finally, investigate some security issues that you should consider when running a Snort system. Paper coverage includes: How an IDS Works, Where Snort fits, Snort system requirements, Exploring Snort's features, Using Snort on your network, Snort and your network architecture, security considerations with snort under digital forensic windows environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2001.05a
• /
• pp.676-679
• /
• 2001

As network security is coning up with significant problem after the major Internet sites were hacked nowadays, IDS(Intrusion Detection System) is considered as a next generation security solution for more reliable network and system security rather than firewall. In this paper, we propose the new IDS model which tan detect intrusion in different systems as well as which ran make real-time detection of intrusion in the expanded distributed environment in host level of drawback of existing IDS. We implement its prototype and verify its validity. We use pattern extraction agent so that we can extract automatically audit file needed in distributed intrusion detection even in other platforms.

• Proceedings of the KIEE Conference
• /
• 1993.07a
• /
• pp.284-286
• /
• 1993

Software and hardware for cochlear implant system have been developed to create a speech signal processing system which, in real-time, extracts model parameter including formants, pitch, amplitude information. The system is based on the Texas Instruments TMS320 family. In hardware, computer interface has been desisted and implemented that allows presentation of biphasic pulse stimuli to patients with the hearing handicapped. The host computer sends a stream of bytes to the parallel port. Upon receipt of the data the interface generates the appropriate burst sequence that is delivered to the patient's external transmitter coil. The coded information is interpreted by the Nucleus-22 internal receiver that delivers the pulse to the specified electrodes at the specified amplitude and pulse width.

• Journal of the Korean Data and Information Science Society
• /
• v.20 no.6
• /
• pp.1177-1190
• /
• 2009

In this paper, we propose a fuzzy proxy cache scheme for caching web documents in mobile base stations. In this scheme, a mobile cache model is used to facilitate data caching and data replication. Using the proposed cache scheme, the individual proxy in the base station makes cache decisions based solely on its local knowledge of the global cache state so that the entire wireless proxy cache system can be effectively managed without centralized control. To improve the performance of proxy caching, the proposed cache scheme predicts the direction of movement of mobile hosts, and uses various cache methods for neighboring proxy servers according to the fuzzy-logic-based control rules based on the membership degree of the mobile host. The performance of our cache scheme is evaluated analytically in terms of average response delay and average energy cost, and is compared with that of other mobile cache schemes.