• Fashion & Textile Research Journal
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• v.24 no.2
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• pp.183-194
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• 2022

This study aims to understand the consumers' negative responses to communication failure of chatbots caused by their imperfections. Specifically, this study examines 1) the relationship among chatbot's communication failure, dissatisfaction, negative behavior (complaint, negative word-of-mouth (nWOM), and inertia); 2) the moderating effect of technostress on the relationship between chatbot's communication failure and dissatisfaction; 3) the differences in the negative responses between the generation MZ and the previous generations. Data were collected via an online survey. First, the participants interacted with the chatbot developed for this survey, to experience the chatbot's communication failure. Thereafter, they responded to a questionnaire. PLS-SEM was conducted using the R software environment to test the hypotheses. This study empirically identified that chatbot's communication failure positively affected dissatisfaction. In addition, the customers who were more dissatisfied with the chatbot's communication failures were more likely to complain than engage in nWOM. Compared to the generation MZ, chatbot's communication failure caused a higher level of dissatisfaction in previous generations. The results suggest that online shopping malls should carefully introduce an improved chatbot service after minimizing its communication failure rate. The chatbot developers of online shopping malls targeting middle-aged and elderly consumers should strive to develop and implement strategies to further alleviate consumers' dissatisfaction in the situation of chatbot's communication failure.

• Iberoamérica
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• v.22 no.2
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• pp.1-23
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• 2020

Jose Donoso's Casa de campo is an uncertain and ambiguous novel because it has a political allegory on one hand and metafiction on the other. The novel may well be considered a political allegory about the 1973 military coup in Chile. This understanding, however, oversimplifies the fictional world of Casa de campo. In the deep level of the narrative, the novel is a literary portrait of challenges and failures that occurred in Latin American history. As metafiction, Casa de campo features discourses on the literary portrait and calls attention to reality outside the novel. Therefore, Donoso seeks to reveal the unusual, temporary and fictional character of the grim reality.

• Smart Structures and Systems
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• v.29 no.1
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• pp.105-116
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• 2022

Stay cables play an essential role in cable-stayed bridges. Severe vibrations and/or harsh environment may result in cable failures. Therefore, an efficient structural health monitoring (SHM) solution for cable damage detection is necessary. This study proposes a data-driven method for immediately detecting cable damage from measured cable forces by recognizing pattern transition from the intact condition when damage occurs. In the proposed method, pattern recognition for cable damage detection is realized by time series classification (TSC) using a deep learning (DL) model, namely, the long short term memory fully convolutional network (LSTM-FCN). First, a TSC classifier is trained and validated using the cable forces (or cable force ratios) collected from intact stay cables, setting the segmented data series as input and the cable (or cable pair) ID as class labels. Subsequently, the classifier is tested using the data collected under possible damaged conditions. Finally, the cable or cable pair corresponding to the least classification accuracy is recommended as the most probable damaged cable or cable pair. A case study using measured cable forces from an in-service cable-stayed bridge shows that the cable with damage can be correctly identified using the proposed DL-TSC method. Compared with existing cable damage detection methods in the literature, the DL-TSC method requires minor data preprocessing and feature engineering and thus enables fast and convenient early detection in real applications.

• Journal of the Korea Safety Management & Science
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• v.25 no.1
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• pp.15-21
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• 2023

In modern society, the delivery service market has grown explosively due to rapid changes in social structure and the recent COVID-19 pandemic. Therefore, various problems such as injury to workers and an increase in human accidents are occurring due to the loading and unloading of parcels. In order to solve this problem, domestic company n is developing a "robot-based cargo loading and unloading system". In developing a new technology system, quantitative reliability targets should be set for efficient operation and development. In this paper, reliability analysis was conducted through field data for the pneumatic gripper of the "robot-based cargo loading system". The reliability of the failure data was analyzed to estimate the distribution parameters and MTTF. Random data was derived for the probability of occurrence of a failure with the estimated value. By repeating the simulation to predict the number and year of failures according to the estimated parameters of the probability distribution, it was proposed as a method that reflects realistic probabilities rather than calculating with simple arithmetic using the average MTTF previously used in the field.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3639-3662
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• 2020

The network capability to accomplish its functions in a timely fashion under failures and attacks is known as survivability. Ad hoc routing protocols have been studied and extended to various domains, such as Intelligent Transport Systems (ITSs), Unmanned Aerial Vehicles (UAVs), underwater acoustic networks, and Internet of Things (IoT) focusing on different aspects, such as security, QoS, energy. The existing solutions proposed in this domain incur substantial overhead and eventually become burden on the network, especially when there are fewer attacks or no attack at all. There is a need that the effectiveness of these routing protocols be analyzed in the presence of Denial of Service (DoS) attacks without any intrusion detection or prevention system. This will enable us to establish and identify the inherently stable routing protocols that are capable to survive longer in the presence of these attacks. This work presents a DoS attack case study to perform theoretical analysis of survivability on node and network level in the presence of DoS attacks. We evaluate the performance of reactive and proactive routing protocols and analyse their survivability. For experimentation, we use NS-2 simulator without detection or prevention capabilities. Results show that proactive protocols perform better in terms of throughput, overhead and packet drop.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4287-4306
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• 2016

Network resilience provides an effective way to overcome the problem of network failure and is crucial to Internet protocol (IP) network management. As one of the main challenges in network resilience, recovering from link failure is important to maintain the constancy of packets being transmitted. However, existing failure recovery approaches do not handle the traffic engineering problem (e.g., tuning the routing-protocol parameters to optimize the rerouting traffic flow), which may cause serious congestions. Moreover, as the lack of QoS (quality of service) restrictions may lead to invalid rerouting traffic, the QoS requirements (e.g., bandwidth and delay) should also be taken into account when recovering the failed links. In this paper, we first develop a probabilistically correlated failure model that can accurately reflect the correlation between link failures, with which we can choose reliable backup paths (BPs). Then we construct a mathematical model for the failure recovery problem, which takes maximum rerouting traffic as the optimizing objective and the QoS requirements as the constraints. Moreover, we propose a heuristic algorithm for link failure recovery, which adopts the improved k shortest path algorithm to splice the single BP and supplies more protection resources for the links with higher priority. We also prove the correctness of the proposed algorithm. Moreover, the time and space complexity are also analyzed. Simulation results under NS2 show that the proposed algorithm improves the link failure recovery rate and increases the QoS satisfaction rate significantly.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.2
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• pp.27-32
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• 2018

One of the crucial issues in mobile edge cloud computing environments is to monitor mobile devices. Due to the inherit properties of mobile devices, they are prone to unstable behavior that leads to failures. In order to satisfy the service level agreement (SLA), the mobile edge cloud administrators should take appropriate measures through a monitoring scheme. In this paper, we propose a monitoring scheme of mobile devices based on artificial intelligence in mobile edge cloud computing environments. The proposed monitoring scheme is able to measure faults of mobile devices based on previous and current monitoring information. To this end, we adapt the hidden markov chain model, one of the artificial intelligence technologies, to monitor mobile devices. We validate our monitoring scheme based on the hidden markov chain model. The proposed monitoring scheme can also be used in general cloud computing environments to monitor virtual machines.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.795-804
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• 2009

An HSS(Home Subscriber Server) system requires a main-memory database on main-memory unit for the real-tine management of the subscriber information in the mobile communication service, in that the system controls not only basic data for handling calls of users, but also additional service data related to user authentication and operational data. Nonetheless, HSS-DBS system, requiring the reliability and stability, need more secure data store method and a back-up technique because the system have a long startup time and the big problem on the failures of main-memory. This paper proposes an efficient back-up replication technique, on the basis of enhancing the stability and performance of HSS system. The proposed shadowing back-up technique adopting the delayed recovery process, can help minimize the real-time back-up overloads by location registration, while the proposed backup replication method enables more stable system operations with replicating the data to remote server in real time.

• Korean Journal of Veterinary Research
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• v.43 no.1
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• pp.129-137
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• 2003

Porcine reproductive and respiratory syndrome (PRRS) is characterized by reproductive failures in sows and respiratory problems in piglets. The nucleocapsid(N) protein, encoded by the open reading frame 7 (ORF7) gene, is known to be the most abundant and antigenic protein in PRRS virus. Therefore, it was suggested that the N protein could be a suitable candidate for the detection of PRRS virus-specific antibodies and diagnosis of PRRS. In the present study, the ORF7 gene encoding the N protein was cloned and expressed as a fusion protein with the glutathione S-transferase (GST) in Escherichia coli. The resulting GST-N recombinant protein was used as an antigen for an indirect sandwich enzyme-linked immunosorbent assay (i-ELISA). Expressed GST-N recombinant protein was migrated at 41 kDa and reacted with ORF7-specific monoclonal antibody by Western blotting. In order to increase the specificity of the ELISA for the detection of PRRS virus-specific antibodes, an i-ELISA was developed using an anti-GST antibody as a capture antibody. The sensitivity and specificity of developed i-ELISA were 92% and 96%, respectively. Based on these results, it was suggested that the i-ELISA is a simple and rapid test for screening a large number of swine sera for the anti-PRRS virus antibodies.

• Corrosion Science and Technology
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• v.14 no.6
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• pp.261-266
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• 2015

The capacity of passive metal to repassivate after film damage determines the development of local corrosion and the resistance to corrosion failures. In this work, the repassivation kinetics of 316L stainless steel (316L SS) was investigated in borate buffer solution (pH 9.1) using a novel abrading electrode technique. The repassivation kinetics was analyzed in terms of the current density flowing from freshly bare 316L SS surface as measured by a potentiostatic method. During the early phase of decay (t < 2 s), according to the Avrami kinetics-based film growth model, the transient current was separated into anodic dissolution ($i_{diss}$) and film formation ($i_{film}$) components and analyzed individually. The film reformation rate and thickness were compared according to applied potential. Anodic dissolution initially dominated the repassivation for a short time, and the amount of dissolution increased with increasing applied potential in the passive region. Film growth at higher potentials occurred more rapidly compared to at lower potentials. Increasing the applied potential from 0 $V_{SCE}$ to 0.8 $V_{SCE}$ resulted in a thicker passive film (0.12 to 0.52 nm). If the oxide monolayer covered the entire bare surface (${\theta}=1$), the electric field strength through the thin passive film reached $1.6{\times}10^7V/cm$.