• The Journal of Society for e-Business Studies
• /
• v.23 no.3
• /
• pp.1-12
• /
• 2018

Mixed-criticality systems consist of components with different criticality. Recently, components are categorized depending on criticality by ISO 26262 standard and DO-178B standard in automotive and avionic domain. Existing mixed-criticality system research achieved efficient and safe scheduling through system-level criticality mode. The drawback of these approaches is performance degradation of low-criticality tasks on high-criticality mode. Task-level criticality mode is one method to address the problem and improve the performance of low-critical tasks. In this paper, we propose probabilistic performance metric for the approach. In simulation results with probabilistic performance metric, we showed that our approach has better performance than the existing approaches.

• International Journal of Internet, Broadcasting and Communication
• /
• v.13 no.3
• /
• pp.63-72
• /
• 2021

Mobile crowd-sensing (MCS) is a promising sensing paradigm that leverages mobile users with smart devices to perform large-scale sensing tasks in order to provide services to specific applications in various domains. However, MCS sensing tasks may not always be successfully completed or timely completed for various reasons, such as accidentally leaving the tasks incomplete by the users, asynchronous transmission, or connection errors. This results in missing sensing data at specific locations and times, which can degrade the performance of the applications and lead to serious casualties. Therefore, in this paper, we propose a missing data inference approach, called missing data approximation with probabilistic tensor factorization (MDI-PTF), to approximate the missing values as closely as possible to the actual values while taking asynchronous data transmission time and different sensing locations of the mobile users into account. The proposed method first normalizes the data to limit the range of the possible values. Next, a probabilistic model of tensor factorization is formulated, and finally, the data are approximated using the gradient descent method. The performance of the proposed algorithm is verified by conducting simulations under various situations using different datasets.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.13 no.1
• /
• pp.511-525
• /
• 2021

Aluminium outfitting is widely used in offshore platforms owing to its anti-corrosion ability and its light weight. However, various standards exist (ISO, NORSOK and EN) for the design of handrails used in offshore platforms, and different suppliers have different criteria. This causes great confusion for designers. Moreover, the design load required by the standards is not clearly defined or is uncertain. Thus, many offshore projects reference previous project details or are conservatively designed without additional clarification. In this study, all of the codes and standards were reviewed and analysed through prior studies, and data on variable factors that directly and indirectly affect the handrails applied to offshore platforms were analysed. A total of 50 handrail design load scenarios were proposed through deterministic and probabilistic approaches. To verify the proposed new handrail design load selection scenario, structural analysis was performed using SACS (offshore structural analysis software). This new proposal through deterministic and probabilistic approaches is expected to improve safety by clarifying the purpose of the handrails. Furthermore, the acceptance criteria for probabilistic scenarios for handrails suggest considering the frequency of handrail use and the design life of offshore platforms to prevent excessive design. This study is expected to prevent trial and error in handrail design while maintaining overall worker safety by applying a loading scenario suitable for the project environment to enable optimal handrail design.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.4
• /
• pp.367-371
• /
• 2015

In this paper, a novel localization method for a monocular camera is proposed by using a feature-based probabilistic map. The localization of a camera is generally estimated from 3D-to-2D correspondences between a 3D map and an image plane through the PnP algorithm. In the computer vision communities, an accurate 3D map is generated by optimization using a large number of image dataset for camera pose estimation. In robotics communities, a camera pose is estimated by probabilistic approaches with lack of feature. Thus, it needs an extra system because the camera system cannot estimate a full state of the robot pose. Therefore, we propose an accurate localization method for a monocular camera using a probabilistic approach in the case of an insufficient image dataset without any extra system. In our system, features from a probabilistic map are projected into an image plane using linear approximation. By minimizing Mahalanobis distance between the projected features from the probabilistic map and extracted features from a query image, the accurate pose of the monocular camera is estimated from an initial pose obtained by the PnP algorithm. The proposed algorithm is demonstrated through simulations in a 3D space.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.4
• /
• pp.457-466
• /
• 2013

Wind energy is rapidly becoming significant generating technologies in electricity markets. As probabilistic nature of wind energy creates many uncertainties in the short-term scheduling, additional actions for reliable market operation should be taken. This paper presents a novel approach to evaluate ramping capability requirement for changes in imbalance energy between day-ahead market and real-time market due to uncertainty of wind generation as well as system load. Dynamic ramp rate model has been applied for realistic solution in unit commitment problem, which is implemented in day-ahead market. Probabilistic optimal power flow has been used to verify ramping capability determined by the proposed method is reasonable in economic and reliable aspects. This approach was tested on six-bus system and IEEE 118-bus system with a wind farm. The results show that the proposed approach provides ramping capability information to meet both forecasted variability and desired confidence level of anticipated uncertainty.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.2005-2010
• /
• 2004

As robots become more prevalent in human daily life, situations requiring interaction between humans and robots will occur more frequently. Therefore, human-robot interaction (HRI) is becoming increasingly important. Although robotics researchers have made many technical developments in their field, intuitive and easy ways for most common users to interact with robots are still lacking. This paper introduces a new approach to enhance human-robot interaction using a semantic symbol language and proposes a method to acquire the intentions of robot users. In the proposed approach, each semantic symbol represents knowledge about either the environment or an action that a robot can perform. Users'intentions are expressed by symbolized multimodal information. To interpret a users'command, a probabilistic approach is used, which is appropriate for interpreting a freestyle user expression or insufficient input information. Therefore, a first-order Markov model is constructed as a probabilistic model, and a questionnaire is conducted to obtain state transition probabilities for this Markov model. Finally, we evaluated our model to show how well it interprets users'commands.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.3
• /
• pp.453-463
• /
• 2013

The probabilistic nature of renewable energy, especially wind energy, increases the needs for new forms of planning and operating with electrical power. This paper presents a novel approach for determining the short-term generation schedule for optimal operations of wind energy-integrated power systems. The proposed probabilistic security-constrained optimal power flow (P-SCOPF) considers dispatch, network, and security constraints in pre- and post-contingency states. The method considers two sources of uncertainty: power demand and wind speed. The power demand is assumed to follow a normal distribution, while the correlated wind speed is modeled by the Weibull distribution. A Monte Carlo simulation is used to choose input variables of power demand and wind speed from their probability distribution functions. Then, P-SCOPF can be applied to the input variables. This approach was tested on a modified IEEE 30-bus system with two wind farms. The results show that the proposed approach provides information on power system economics, security, and environmental parameters to enable better decision-making by system operators.

• Journal of Korean Society on Water Environment
• /
• v.25 no.4
• /
• pp.494-501
• /
• 2009

Probabilistic Ecological risk assessment (PERA) is extensive approach to qualify and quantify risk on the multi species based on species sensitivity distribution (SSD). As a while, deterministic ecological risk assessment (DERA) considers the comparison of predicted no-effect concentration (PNEC) and predicted exposure concentration (PEC). DERA is used to determine if there is potential risk or no risk, and it doesn't consider the nature variability and the species sensitivity. But PERA can be more realistic and reasonable approach to estimate likelihood or risk. In this study, we compared PERA used in developed countries, and proposed PERA applicable for the Korean water environment. Taxonomic groups were classified as "class" level including Actinopterygill, Branchiopoda, Chlorophyceae, Maxillapoda, Insects, Bivalvia, Gastropoda, Secernentea, Polychaeta, Monocotyldoneae, and Chanophyceae in this study. Statistical extrapolation method (SEM), statistical extrapolation method $_{acutechronicratio}$ ($SEM_{ACR}$) and assessment factor method (AFM) were used to calculate the ecological protective concentration based on qualitative and quantitative levels of taxonomic toxicity data. This study would be useful to establish the PERA for the protection of aquatic ecosystem in Korea.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.8
• /
• pp.3657-3682
• /
• 2018

This paper presents a Bluetooth and pedestrian dead reckoning (PDR)-based indoor fusion localization approach (BtPDR) using smartphones. A Bluetooth and PDR-based indoor fusion localization approach can localize the initial position of a smartphone with the received signal strength (RSS) of Bluetooth. While a smartphone is moving, BtPDR can track its position by fusing the localization results of PDR and Bluetooth RSS. In addition, BtPDR can adaptively modify the parameters of PDR. The contributions of BtPDR include: a Bluetooth RSS-based Probabilistic Voting (BRPV) localization mechanism, a probabilistic voting-based Bluetooth RSS and PDR fusion method, and a heuristic search approach for reducing the complexity of BRPV. The experiment results in a real scene show that the average positioning error is < 2m, which is considered adequate for indoor location-based service applications. Moreover, compared to the traditional PDR method, BtPDR improves the location accuracy by 42.6%, on average. Compared to state-of-the-art Wireless Local Area Network (WLAN) fingerprint + PDR-based fusion indoor localization approaches, BtPDR has better positioning accuracy and does not need the same offline workload as a fingerprint algorithm.

• Geomechanics and Engineering
• /
• v.18 no.6
• /
• pp.661-668
• /
• 2019

Seismic vulnerability assessment is a useful tool for rational safety analysis and planning of large and complex structural systems; it can deal with the effects of uncertainties on the performance of significant structural systems. In this study, an efficient dynamic reliability approach, probability density evolution methodology (PDEM), is proposed for seismic vulnerability analysis of earth dams. The PDEM provides the failure probability of different limit states for various levels of ground motion intensity as well as the mean value, standard deviation and probability density function of the performance metric of the earth dam. Combining the seismic reliability with three different performance levels related to the displacement of the earth dam, the seismic fragility curves are constructed without them being limited to a specific functional form. Furthermore, considering the seismic fragility analysis is a significant procedure in the seismic probabilistic risk assessment of structures, the seismic vulnerability results obtained by the dynamic reliability approach are combined with the results of probabilistic seismic hazard and seismic loss analysis to present and address the PDEM-based seismic probabilistic risk assessment framework by a simulated case study of an earth dam.