• Korean Journal of Forensic Psychology
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• v.13 no.1
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• pp.75-97
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• 2022

Profiling is recognized as a representative application area of domestic criminal psychology, and the National Police Agency profiler is firmly established as a profession. However, compared to the social awareness, the recognition and utilization within the police is not high. In this study, we tried to identify factors affecting the intention to use profiling by identifying the perception of investigators who request and use profiling from a profiler when a violent incident occurs. To this end, the relationship between the perception of the importance of factors considered by investigators in the criminal investigation process and the attitude toward profiling on the intention to use profiling was verified through the path model. As a result of a survey of 340 police investigators, the investigator's perception of the importance of investigation elements was divided into two factors: the importance of normative investigative elements (evidence collection and legal judgment, etc.) and factual investigative elements (criminal analysis, criminal information system analysis, etc.). Among them, the importance of factual investigative elements were found to have a positive effect on the intention to use it by mediating the attitude toward profiling. On the other hand, in the case of the importance of normative investigative elements, it was found to have a negative effect on the attitude toward profiling. These results suggest that the perception that investigators have about investigation, which is their main work area, plays a role in determining whether to request profiling as well as attitude towards profiling. Based on the research results, strategies necessary to activate the use of profiling were discussed.

• The Journal of the Acoustical Society of Korea
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• v.40 no.3
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• pp.201-212
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• 2021

The present study was conducted as a pilot investigation to suggest the standards of acoustic performance for classrooms suitable for incomplete hearing people such as children under 9 years of age. Subjective evaluations such as questionnaire and speech intelligibility test were conducted to 264 students at two elementary schools in Cheong-ju in order to analyze the characteristics of the listening environment in the classrooms of the lower grades in elementary school. The survey was undertaken with a total of 264 students at two elementary schools in Cheong-ju, and investigated their satisfaction with the classroom listening environment. As a result, students responded that the most helpful information type for understanding class content is the voice of teacher. In addition, the volume of the current teacher's voice is normal, and the level of clarity is highly satisfactory. As for the acoustic performance of the classroom, the opinion that the noise was normal and the reverberation was very short was found to be dominant in overall satisfaction with the listening environment. Meanwhile, as a result of speech intelligibility test using the word list selected for the lower grade students of elementary school, it could be inferred that the longitudinal axis distance from the sound source in the case of 8-year-olds is a factor that affects speech recognition.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.9-16
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• 2023

Robots are expected to expand their scope of application to the military field and take on important missions such as surveillance and enemy detection in the coming future warfare. Swarm robots can perform tasks that are difficult or time-consuming for a single robot to be performed more efficiently due to the advantage of having multiple robots. Swarm robots require mutual recognition and collaboration. So they send and receive vast amounts of data, making it increasingly difficult to verify SW. Hardware-in-the-loop simulation used to increase the reliability of mission verification enables SW verification of complex swarm robots, but the amount of verification data exchanged between the HILS device and the simulator increases exponentially according to the number of systems to be verified. So communication overload may occur. In this paper, we propose a digital twin-based communication optimization technique to solve the communication overload problem that occurs in mission verification of swarm robots. Under the proposed Digital Twin based Multi HILS Framework, Network DT can efficiently allocate network resources to each robot according to the mission scenario through the Network Controller algorithm, and can satisfy all sensor generation rates required by individual robots participating in the group. In addition, as a result of an experiment on packet loss rate, it was possible to reduce the packet loss rate from 15.7% to 0.2%.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.675-681
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• 2021

With the recent growth of the AI speaker market, the demand for speech synthesis technology that enables natural conversation with users is increasing. Therefore, there is a need for a multi-speaker speech synthesis system that can generate voices of various tones. In order to synthesize natural speech, it is required to train with a large-capacity. high-quality speech DB. However, it is very difficult in terms of recording time and cost to collect a high-quality, large-capacity speech database uttered by many speakers. Therefore, it is necessary to train the speech synthesis system using the speech DB of a very large number of speakers with a small amount of training data for each speaker, and a technique for naturally expressing the tone and rhyme of multiple speakers is required. In this paper, we propose a technology for constructing a speaker encoder by applying the deep learning-based x-vector technique used in speaker recognition technology, and synthesizing a new speaker's tone with a small amount of data through the speaker encoder. In the multi-speaker speech synthesis system, the module for synthesizing mel-spectrogram from input text is composed of Tacotron2, and the vocoder generating synthesized speech consists of WaveNet with mixture of logistic distributions applied. The x-vector extracted from the trained speaker embedding neural networks is added to Tacotron2 as an input to express the desired speaker's tone.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.95-118
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• 2021

As the AI speaker business has risen significantly in recent years, the potential for numerous uses of AI speakers has gotten a lot of attention. Consumers have created an environment in which they can express and share their experiences with products through various channels, resulting in a large number of reviews that leave consumers with a variety of candid opinions about their experiences, which can be said to be very useful in analyzing consumers' thoughts. Using this review data, this study aimed to examine the factors driving the continued use of AI speakers. Above all, it was determined whether the seven characteristics associated with the intention to adopt AI identified in prior studies appear in consumer reviews. Based on customer review data on Amazon.com, text mining and social network analysis were utilized to examine Amazon eco-products. CONCOR analysis was used to classify words with similar connectivity locations, and Connection centrality analysis was used to classify the factors influencing the continuous use of AI speakers, focusing on the connectivity between words derived by classifying review data into positive and negative reviews. Consumers regarded personality and closeness as the most essential characteristics impacting the continued usage of AI speakers as a result of the favorable review survey. These two parameters had a strong correlation with other variables, and connectedness, in addition to the components established from prior studies, was a significant factor. Furthermore, additional negative review research revealed that recognition failures and compatibility are important problems that deter consumers from utilizing AI speakers. This study will give specific solutions for consumers to continue to utilize Amazon eco products based on the findings of the research.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.653-659
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• 2022

In this study, the awareness of hazardous chemicals and the need for education of dental hygienists were investigated. The subject of this study was an online survey of 103 dental hygienists working in medical institutions from June to August 2021 and analyzed using the SPSS 21.0 program. As a result, work experience was positively correlated with perception (r=.280, p<0.01) and work (r=.303, p<0.01), and work experience with perception (r=.411, p<0.01).Hazardous chemical information showed a positive correlation with practice (r=.371, p<0.01). As a result of the education requirement survey, only 27.2% had experience in hazardous chemical education, and 96.1% of the awareness of the need for education was highly surveyed. As for the desired method of education, 49.5% of them were online education, and the desired time for education was 1 hour. Therefore, in order to create a safe working environment for dental hygienists and to secure the safety of hazardous chemicals, it was necessary to expand educational opportunities at universities, medical institutions, and maintenance education, and to increase accessibility through online education.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.3
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• pp.439-448
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• 2022

Recently, domestic small and medium-sized subcontractors participating in the overseas construction market are suffering from the continuous loss and damage due to the insufficient recognition of the importance of risk Sub-Clauses among conditions of subcontracts. Therefore, the need to derive risk Sub-Clauses for conditions of the subcontract has been raised, but until now, previous studies have been conducted focusing on deriving risk Sub-Clauses for standard conditions of contract for construction between the Employer and the Contractor. In this study, 52 risk Sub-Clauses were derived on the basis of the influence size of the Sub-Clauses through the Delphi technique targeting 94 Sub-Clauses of conditions of standard subcontract for construction edition 2011, issued by the International Federation of Consulting Engineers (FIDIC) and In addition, 33 key risk Sub-Clauses were finally derived through the PI Risk Matrix by Probability and Impact. The results of this study provide will useful information on key risk Sub-Clauses that need to be reviewed in advance to minimize contractual risks at the stage of bidding and signing contracts for overseas subcontract construction projects.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.41-46
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• 2023

Human urine is a process of excreting waste products in the blood, and it is easy to collect and contains various substances. Urinalysis is used to check for diseases, health conditions, and urinary tract infections. There are three methods of urinalysis: physical property test, chemical test, and microscopic test, and chemical test results can be easily confirmed using urine test strips. A variety of items can be tested on the urine test strip, through which various diseases can be identified. Recently, with the spread of smart phones, research on reading urine test strips using smart phones is being conducted. There is a method of detecting and reading the color change of a urine test strip using a smartphone. This method uses the RGB values and the color difference formula to discriminate. However, there is a problem in that accuracy is lowered due to various environmental factors. This paper applies a deep learning model to solve this problem. In particular, color discrimination of a urine test strip is improved in a smartphone using a lightweight CNN (Convolutional Neural Networks) model. CNN is a useful model for image recognition and pattern finding, and a lightweight version is also available. Through this, it is possible to operate a deep learning model on a smartphone and extract accurate urine test results. Urine test strips were taken in various environments to prepare deep learning model training images, and a urine test service application was designed using MobileNet V3.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1235-1249
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• 2022

This study applied the web crawling technique for extracting big data news on water quality accidents in the water supply system and presented the algorithm in a procedural way to obtain accurate water quality accident news. In addition, in the case of a large-scale water quality accident, development patterns such as accident recognition, accident spread, accident response, and accident resolution appear according to the occurrence of an accident. That is, the analysis of the development of water quality accidents through key keywords and sentiment analysis for each stage was carried out in detail based on case studies, and the meanings were analyzed and derived. The proposed methodology was applied to the larval accident period of Incheon Metropolitan City in 2020 and analyzed. As a result, in a situation where the disclosure of information that directly affects consumers, such as water quality accidents, is restricted, the tone of news articles and media reports about water quality accidents with long-term damage in the event of an accident and the degree of consumer pride clearly change over time. could check This suggests the need to prepare consumer-centered policies to increase consumer positivity, although rapid restoration of facilities is very important for the development of water quality accidents from the supplier's point of view.

• Korean Journal of Clinical Pharmacy
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• v.32 no.1
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• pp.20-26
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• 2022

Background and objective: The Seoul National University Bundang Hospital (SNUBH) implemented ward-based clinical pharmacy system with designated pharmacists in 10 general wards. Designated pharmacists conduct inpatient medication review, medication intervention, and medication consultation, and provide drug information for health care providers. This study aimed to evaluate the clinical pharmacy services and to examine the perception and expectations of health care providers on the services provided by the designated pharmacists in general wards. Methods: A survey was constructed to include questions on the health care providers' recognition, satisfaction, and perceived needs of designated pharmacists. We determined the frequency and type of interventions of ward pharmacist and their acceptance rate through a retrospective observational study using electronic medical records. Results: A total of 59 health care providers responded the questionnaire and 79.7% of the respondents reported moderate to high levels of satisfaction. Satisfaction with the services was positively associated with clinical interventions and nutrition support team (81.4%). Of 59 respondents, 88.1% agreed that preventing drug-related problems by designated pharmacists' activities were effective. The most common interventions included inadequate dosage (27.4%), omission and additional prescription (14.6%) and inadequate drug form (9.6%). The acceptance rate of intervention was 91.5%, and 151 potentially serious risks and 523 significant risks were prevented by the intervention. Conclusion: Positive results were confirmed in the awareness, satisfaction, and perceived needs of the health care providers for designated pharmacists. Expansion of the ward-based clinical pharmacy system with designated pharmacists to other wards may be considered.