• Asia pacific journal of information systems
• /
• v.30 no.3
• /
• pp.568-589
• /
• 2020

Recently, Social media has become a concern for businesses, including Small and Medium Enterprises (SMEs). SMEs began to adopt social media to support their performance. To benefit from the application of social media, SMEs must implement the right strategy. This study aims to analyze the factors that influence the use of social media in SMEs. Furthermore, alignment between social media functionalities and strategies and their effect on SME's performance are investigated. A case study is conducted in Gymi, a garment SMEs in East Java, Indonesia. The data collection includes interviews with the owner of SMEs, observations, and document analysis. Data analysis is performed by pattern matching, which matches the patterns from the literature with data from the case study. The results of this study show that cost-effectiveness, interactivity, and compatibility are factors that influence the use of social media in Gymi. The social media used by Gymi are Instagram, Facebook, YouTube, WhatsApp, and LINE. However, the main social media used to support Gymi's functions is Instagram. Gymi has a relatively good social media strategy as it has defined a specific goal, target audience, and channel selection for social media (Instagram). It also has specific resources and policies to handle social media. Gymi monitors and evaluates their social media content activities. These strategies are aligned with the Instagram feature used to support Gymi's function, particularly marketing, sales, customer service, and to some extent, internal operation. The alignment contributes to Gymi's performance measured by the increase in reputation (number of Instagram followers) and sales.

• Korean Journal of Radiology
• /
• v.23 no.9
• /
• pp.921-930
• /
• 2022

Objective: To identify epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma based on ¹⁸F-fluorodeoxyglucose (FDG) PET/CT radiomics and clinical features and to distinguish EGFR exon 19 deletion (19 del) and exon 21 L858R missense (21 L858R) mutations using FDG PET/CT radiomics. Materials and Methods: We retrospectively analyzed 179 patients with lung adenocarcinoma. They were randomly assigned to training (n = 125) and testing (n = 54) cohorts in a 7:3 ratio. A total of 2632 radiomics features were extracted from the tumor region of interest from the PET (1316) and CT (1316) images. Six PET/CT radiomics features that remained after the feature selection step were used to calculate the radiomics model score (rad-score). Subsequently, a combined clinical and radiomics model was constructed based on sex, smoking history, tumor diameter, and rad-score. The performance of the combined model in identifying EGFR mutations was assessed using a receiver operating characteristic (ROC) curve. Furthermore, in a subsample of 99 patients, a PET/CT radiomics model for distinguishing 19 del and 21 L858R EGFR mutational subtypes was established, and its performance was evaluated. Results: The area under the ROC curve (AUROC) and accuracy of the combined clinical and PET/CT radiomics models were 0.882 and 81.6%, respectively, in the training cohort and 0.837 and 74.1%, respectively, in the testing cohort. The AUROC and accuracy of the radiomics model for distinguishing between 19 del and 21 L858R EGFR mutational subtypes were 0.708 and 66.7%, respectively, in the training cohort and 0.652 and 56.7%, respectively, in the testing cohort. Conclusion: The combined clinical and PET/CT radiomics model could identify the EGFR mutational status in lung adenocarcinoma with moderate accuracy. However, distinguishing between EGFR 19 del and 21 L858R mutational subtypes was more challenging using PET/CT radiomics.

• Food Science of Animal Resources
• /
• v.44 no.2
• /
• pp.284-298
• /
• 2024

Restructured meat (RM) products are gaining importance as an essential component of the meat industry due to consumers' interest in health benefits. RM products imply the binding or holding of meat, meat by-products, and vegetable proteins together to form a meat product with meat's sensory and textural properties. RM products provide consumers with diversified preferences like the intake of low salt, low fat, antioxidants, and high dietary fiber in meat products. From the point of environmental sustainability, RM may aid in combining underutilized products and low-valued meat by adequately utilizing them instead of dumping them as waste material. RM processing technique might also help develop diversified and new hybrid meat products. It is crucial to have more knowledge on the quality issues, selection of binding agents, their optimum proportion, and finally, the ideal processing techniques. It is observed in this study that the most crucial feature of RM could be its healthy products with reduced fat content, which aligns with the preferences of health-conscious consumers who seek low-fat, low-salt, high-fiber options with minimal synthetic additives. This review briefly overviews RM and the factors affecting the quality and shelf life. Moreover, it discusses the recent studies on binding agents in processing RM products. Nonetheless, the recent advancements in processing and market scenarios have been summarized to better understand future research needs. The purpose of this review was to bring light to the ways of sustainable and economical food production.

• International Journal of Computer Science & Network Security
• /
• v.24 no.5
• /
• pp.111-118
• /
• 2024

In general network-based intrusion detection system is designed to detect malicious behavior directed at a network or its resources. The key goal of this paper is to look at network data and identify whether it is normal traffic data or anomaly traffic data specifically for accounting information systems. In today's world, there are a variety of principles for detecting various forms of network-based intrusion. In this paper, we are using supervised machine learning techniques. Classification models are used to train and validate data. Using these algorithms we are training the system using a training dataset then we use this trained system to detect intrusion from the testing dataset. In our proposed method, we will detect whether the network data is normal or an anomaly. Using this method we can avoid unauthorized activity on the network and systems under that network. The Decision Tree and K-Nearest Neighbor are applied to the proposed model to classify abnormal to normal behaviors of network traffic data. In addition to that, Logistic Regression Classifier and Support Vector Classification algorithms are used in our model to support proposed concepts. Furthermore, a feature selection method is used to collect valuable information from the dataset to enhance the efficiency of the proposed approach. Random Forest machine learning algorithm is used, which assists the system to identify crucial aspects and focus on them rather than all the features them. The experimental findings revealed that the suggested method for network intrusion detection has a neglected false alarm rate, with the accuracy of the result expected to be between 95% and 100%. As a result of the high precision rate, this concept can be used to detect network data intrusion and prevent vulnerabilities on the network.

• Cartoon and Animation Studies
• /
• s.33
• /
• pp.363-382
• /
• 2013

Up until about ten years ago, the use of typography played only an auxiliary role on broadcast television programs, primarily by transmitting information in order to facilitate a basic understanding of content. Recently, however, kinetic typography has become an important component in broadcast production. In fact, kinetic typography has developed into a visual language and a means of artistic expression, one that is increasingly used in the production of entertainment programs on television. This paper analyzes six aspects of kinetic typography: manner of development, location, intent, expressive techniques, color and font selection. Particular attention is placed on their use in three highly rated television entertainment programs: "2 Days & 1 Night", "Running Man", and "Infinite Challenge". The development way consists of the technique : starts off with cut and ends with cut. While, other techniques show conversation and situation representation using Z axis : zoom-in, zoom-out in , X axis : pan in <2 Days & 1 Night>. and Y axis : tilt in . Typographic design elements, expression technique, color, font are shown up according to the feature of each program. The resulting analysis suggests new ways for motion arts designers and the broadcast media to use kinetic typography in the development of television programs.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.47 no.3
• /
• pp.11-22
• /
• 2010

This paper is a study on implementation of intelligent image surveillance system using context information and supplements temporal-spatial constraint, the weak point in which it is hard to process it in real time. In this paper, we propose scene analysis algorithm which can be processed in real time in various environments at low resolution video(320*240) comprised of 30 frames per second. The proposed algorithm gets rid of background and meaningless frame among continuous frames. And, this paper uses wavelet transform and edge histogram to detect shot boundary. Next, representative key-frame in shot boundary is selected by key-frame selection parameter and edge histogram, mathematical morphology are used to detect only motion region. We define each four basic contexts in accordance with angles of feature points by applying vertical and horizontal ratio for the motion region of detected object. These are standing, laying, seating and walking. Finally, we carry out scene analysis by defining simple context model composed with general context and emergency context through estimating each context's connection status and configure a system in order to check real time processing possibility. The proposed system shows the performance of 92.5% in terms of recognition rate for a video of low resolution and processing speed is 0.74 second in average per frame, so that we can check real time processing is possible.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.10 no.2
• /
• pp.27-42
• /
• 2015

The aim of this research is to investigate the difference in the capturing opportunities for each type of venture companies in the industry undergoing competition of a dominant design and then figure out the reason why they can be successful. Existing studies on venture companies are focused on the way to enhance a firm's competencies by acquiring and combining its resources. However, it is important for startups which have a lack of resources and capabilities to capture the opportunity to survive by understanding a changing environment. This study is focused on opportunity capture and strategic response to a changing environment and attempts to select and observe startup companies which are able to capture the opportunity and enter the market in the industry undergoing dominant design competition. In order to find out its difference in different types of business, we select one case from hardware startups and the other from software startups. According to the result of this study, the hardware startup focuses on market extension by lowering their prices and the software startup strives to induce more users to participate by the universalization of enabling technology so as to extend and standardize their technology in the environment undergoing dominant design competition. This feature of environment leads the difference in the approach for successfully capturing opportunity and thus hardware firms need to recognize the opportunity with profit potential from relationship with a number of cooperative firms while software firms need to identify the opportunity for extension of enabling technology which can be used by many users.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.13 no.3
• /
• pp.661-668
• /
• 2018

Biomedical signals using skin resistance have different characteristics according to stress diseases. Biological diagnostic devices for diagnosing stress diseases have been developed by using these characteristics, and devices have been developed so that the signals measured by the skin storage meter can be easily analyzed. Experts in the field will look directly at the output signal to determine the likelihood of any stress disorder. However, it is very difficult for a person to accurately determine whether a person to be measured has a stress disorder by analyzing a bio-signal measured by each person to be measured, and the result of the judgment is very likely to be wrong. In order to solve these problems, we implemented the function of determining the signal of a stress disorder by using the machine learning technique. SVM was used as a classification method in consideration of low computing ability of measurement equipment. Training data and test data were randomly generated for each disease using error range 5 based on 13 diseases. Simulation results showed more than 90% decision accuracy. In the future, if the measurement equipment is actually applied to the patients, we can retrain the classifier with the newly generated data.

• Convergence Security Journal
• /
• v.13 no.5
• /
• pp.187-196
• /
• 2013

Recently, school violence has come to the fore as a social phenomenon. "Comprehensive countermeasures for eradication of school violence" as a policy safety are created by Safety Administration bureau and Ministry of Education, Science and Technology under the chairmanship of the Office of Prime Minister on Feb,2012. This policy is supposed to be test-operated for a year from March, 2012. but voices of concern about effectiveness have been brought up by some critics greatly. So 172 teachers in high school in Seoul were surveyed in order to examine the effectiveness of "Comprehensive countermeasures for eradication of school violence" with a questionnaire composed of 5 point Likert-type. Among the fundamental measures, there were a total of 12 countermeasures about 'Practices for personality education' (with the exception of unrelated one question). 'Expanding opportunities of various art education and Supporting reading activities' of them ranked highest on average. Then, 'Reflecting results of special feature related to character develops to the Selection of Admission officers and Self-directed learning was the next. And among the three countermeasures about 'Reinforcement of roles of the family and society', 'Pan governmental conducting annual campaign related to broadcast, press, civic group to combat school violence was highest. Finally, among the 7 countermeasures about 'Countermeasure about harmful factors of games and internet addiction', 'Reinforcement of preventive discipline about game and internet addiction' was highest and 'Development and Promotion of various educational contents for preventive discipline about game and internet addiction' was the next.

• Korean Journal of Construction Engineering and Management
• /
• v.17 no.3
• /
• pp.32-42
• /
• 2016

In Korea, the absence of BIM use in existing civil structures and buildings is driving a demand for as-built BIM. As-built BIMs are often created using laser scanners that provide dense 3D point cloud data. Conventional static laser scanning approaches often suffer from limitations in their operability due to the difficulties in moving the equipment, the selection of scanning location, and the requirement of placing targets or extracting tie points for registration of each scanned point cloud. This paper aims at reducing the manual effort using a kinematic 3D laser scanning system based on graph-based simultaneous localization and mapping (SLAM) for continuous indoor mapping. The robotic platform carries three 2D laser scanners: the front scanner is mounted horizontally to compute the robot's trajectory and to build the SLAM graph; the other two scanners are mounted vertically to scan the profiles of surrounding environments. To reduce the accumulated error in the trajectory of the platform through loop closures, the graph-based SLAM system incorporates AdaBoost loop closure approach, which is particularly suitable for the developed multi-scanner system providing more features than the single-scanner system for training. We implemented the proposed method and evaluated it in two indoor test sites. Our experimental results show that the false positive rate was reduced by 13.6% and 7.9% for the two dataset. Finally, the 2D and 3D mapping results of the two test sites confirmed the effectiveness of the proposed graph-based SLAM.