• 제목/요약/키워드: Internet.

Search Result 29,982, Processing Time 0.054 seconds

Racism in the movie ≪Green Book≫ and solutions through discussion (영화 ≪그린북≫에 나타난 인종주의와 토의를 통한 해결 방안)

  • Park, Joo Eun
    • The Journal of the Convergence on Culture Technology
    • /
    • v.8 no.3
    • /
    • pp.159-165
    • /
    • 2022
  • The purpose of this study is to examine racism in the movie ≪Green Book≫ and to find solutions to racism through discussion with students. Set in 1962 in the United States, this film depicts the process of forming a good bond with the black pianist Dr. Shirley and the driver Tony in a racist society. This study utilized the subject of race, one of the subjects covered in the humanities class in the global era of S University in the second semester of 2021. This is because, since the outbreak of racism, the problem of racism has continued to arise in the current COVID-19 pandemic situation. Therefore, the researcher looked at racism and intercultural education as a theoretical background, and looked at cases of racism in movies and cases of racism that have occurred today. The history of racism and discrimination dates back to medieval Europe and was caused by religious conflicts and was attributed to white supremacy. As a solution to this racial discrimination, international organizations suggested intercultural education. And the reason why film was used in this study is because it aims to provoke students' interest and motivation for learning by targeting first-year university students called the digital native generation who were born and grew up with the Internet. In this study, students' solutions to racism were presented using discussion, and then the researcher's solutions were presented.

Improvement Mechanism for Automatic Web Vulnerability Diagnosis (웹취약점 자동진단 개선방안)

  • Kim, Tae-Seop;Jo, In-June
    • The Journal of the Korea Contents Association
    • /
    • v.22 no.2
    • /
    • pp.125-134
    • /
    • 2022
  • Due to the development of smartphone technology, as of 2020, 91.9% of people use the Internet[1] to frequently acquire information through websites and mobile apps. As the number of homepages in charge of providing information is increasing every year, the number of applications for web vulnerability diagnosis, which diagnoses the safety of homepages, is also increasing. In the existing web vulnerability check, the number of diagnostic personnel should increase in proportion to the number of homepages that need diagnosis because the diagnosticians manually test the homepages for vulnerabilities. In reality, however, there is a limit to securing a web vulnerability diagnosis manpower, and if the number of diagnosis manpower is increased, a lot of costs are incurred. To solve these problems, an automatic diagnosis tool is used to replace a part of the manual diagnosis. This paper explores a new method to expand the current automatic diagnosis range. In other words, automatic diagnosis possible items were derived by analyzing the impact of web vulnerability diagnosis items. Furthermore, automatic diagnosis identified possible items through comparative analysis of diagnosis results by performing manual and automatic diagnosis on the website in operation. In addition, it is possible to replace manual diagnosis for possible items, but not all vulnerability items, through the improvement of automatic diagnosis tools. This paper will explore some suggestions that can help improve plans to support and implement automatic diagnosis. Through this, it will be possible to contribute to the creation of a safe website operating environment by focusing on the parts that require precise diagnosis.

An Exploratory Study on the Learning Community: Focusing on the Covid19 Untact Era (배움공동체에 대한 탐색적 연구 : covid19 언택트시대를 중심으로)

  • Jeong, Su-Jeong;Im, Hong-Nam;Park, Hong-Jae
    • Journal of Convergence for Information Technology
    • /
    • v.12 no.5
    • /
    • pp.237-245
    • /
    • 2022
  • This study examines the social discourse on the characteristics of the learning community in the untact era, and discusses the directions that learning communities for children could explore and consider in the pandemic situation and beyond. For this purpose, big data for one year, from January 20, 2020 to January 20, 2021, were collected through internet portal sites (includingincluding Google News, Daum, Naver and other News surfaces), using two keywords "untact" and "learning community", and analyzed by employing a word frequency and network analysis method. The analysis results show that several important terms, such as 'village education community', 'operation', 'activity', 'corona 19', 'support', and 'online' are closely related to the learning community in the untact era. The findings from this study also have implications for developing the learning community as an alternative model to fill the existing gaps in public care and education for children during the prolonged pandemic and afterwards. In conclusion, the study findings highlight that it is meaningful to identify key terms and concepts through word frequency analysis in order to examine social trends and issues related to the learning community.

Big Data Management in Structured Storage Based on Fintech Models for IoMT using Machine Learning Techniques (기계학습법을 이용한 IoMT 핀테크 모델을 기반으로 한 구조화 스토리지에서의 빅데이터 관리 연구)

  • Kim, Kyung-Sil
    • Advanced Industrial SCIence
    • /
    • v.1 no.1
    • /
    • pp.7-15
    • /
    • 2022
  • To adopt the development in the medical scenario IoT developed towards the advancement with the processing of a large amount of medical data defined as an Internet of Medical Things (IoMT). The vast range of collected medical data is stored in the cloud in the structured manner to process the collected healthcare data. However, it is difficult to handle the huge volume of the healthcare data so it is necessary to develop an appropriate scheme for the healthcare structured data. In this paper, a machine learning mode for processing the structured heath care data collected from the IoMT is suggested. To process the vast range of healthcare data, this paper proposed an MTGPLSTM model for the processing of the medical data. The proposed model integrates the linear regression model for the processing of healthcare information. With the developed model outlier model is implemented based on the FinTech model for the evaluation and prediction of the COVID-19 healthcare dataset collected from the IoMT. The proposed MTGPLSTM model comprises of the regression model to predict and evaluate the planning scheme for the prevention of the infection spreading. The developed model performance is evaluated based on the consideration of the different classifiers such as LR, SVR, RFR, LSTM and the proposed MTGPLSTM model and the different size of data as 1GB, 2GB and 3GB is mainly concerned. The comparative analysis expressed that the proposed MTGPLSTM model achieves ~4% reduced MAPE and RMSE value for the worldwide data; in case of china minimal MAPE value of 0.97 is achieved which is ~ 6% minimal than the existing classifier leads.

A Study on the Influence of Augmented Reality Experience in Mobile Applications on Product Purchase (모바일 어플리케이션의 증강현실 이용경험이 제품구매에 미치는 영향 연구)

  • Kim, Minjung
    • The Journal of the Convergence on Culture Technology
    • /
    • v.8 no.6
    • /
    • pp.971-978
    • /
    • 2022
  • As a marketing method in a non-face-to-face society, the purpose of this study is to test how AR experience affects purchase intention in the process of consumers recognizing product information to purchase products and to secure the basis for the effectiveness of developing and introducing augmented reality functions in future product brand applications. Literary research methods and empirical research methods were used to verify the research purpose, and to measure this, an application of domestic tableware brand 'Odense', which implements augmented reality functions, was produced and used as an experimental tool. Also, a direct causal relationship was attempted by constituting a questionnaire by deriving a measurement scale for perceived usefulness, perceived ease, perceived pleasure, and purchase, which are factors of technology acceptance theory (TAM), and empirical analysis was conducted using the SPSS 25.0 statistical package to achieve the purpose of the study. As a result of the study, significant results were derived from all factors in the effect of perceived usefulness, ease, and pleasure on purchase intention, and several significant differences were found among factors according to gender, age, and internet shopping usage time in general characteristics. In conclusion, the user experience of the medium in which the augmented reality function is introduced in the information recognition stage of the product has a positive effect on purchase compared to the user experience of existing applications.

Active VM Consolidation for Cloud Data Centers under Energy Saving Approach

  • Saxena, Shailesh;Khan, Mohammad Zubair;Singh, Ravendra;Noorwali, Abdulfattah
    • International Journal of Computer Science & Network Security
    • /
    • v.21 no.11
    • /
    • pp.345-353
    • /
    • 2021
  • Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO2. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

A study on deep neural speech enhancement in drone noise environment (드론 소음 환경에서 심층 신경망 기반 음성 향상 기법 적용에 관한 연구)

  • Kim, Jimin;Jung, Jaehee;Yeo, Chaneun;Kim, Wooil
    • The Journal of the Acoustical Society of Korea
    • /
    • v.41 no.3
    • /
    • pp.342-350
    • /
    • 2022
  • In this paper, actual drone noise samples are collected for speech processing in disaster environments to build noise-corrupted speech database, and speech enhancement performance is evaluated by applying spectrum subtraction and mask-based speech enhancement techniques. To improve the performance of VoiceFilter (VF), an existing deep neural network-based speech enhancement model, we apply the Self-Attention operation and use the estimated noise information as input to the Attention model. Compared to existing VF model techniques, the experimental results show 3.77%, 1.66% and 0.32% improvements for Source to Distortion Ratio (SDR), Perceptual Evaluation of Speech Quality (PESQ), and Short-Time Objective Intelligence (STOI), respectively. When trained with a 75% mix of speech data with drone sounds collected from the Internet, the relative performance drop rates for SDR, PESQ, and STOI are 3.18%, 2.79% and 0.96%, respectively, compared to using only actual drone noise. This confirms that data similar to real data can be collected and effectively used for model training for speech enhancement in environments where real data is difficult to obtain.

Design of an Intellectual Smart Mirror Appication helping Face Makeup (얼굴 메이크업을 도와주는 지능형 스마트 거울 앱의설계)

  • Oh, Sun Jin;Lee, Yoon Suk
    • The Journal of the Convergence on Culture Technology
    • /
    • v.8 no.5
    • /
    • pp.497-502
    • /
    • 2022
  • Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.

The Role of Innovative Activities in Training Students Using Computer Technologies

  • Minenok, Antonina;Donets, Ihor;Telychko, Tetiana;Hud, Hanna;Smoliak, Pavlo;Kurchatova, Angelika;Kuchai, Tetiana
    • International Journal of Computer Science & Network Security
    • /
    • v.22 no.8
    • /
    • pp.105-112
    • /
    • 2022
  • Innovation is considered as an implemented innovation in education - in the content, methods, techniques and forms of educational activity and personality education (methods, technologies), in the content and forms of organizing the management of the educational system, as well as in the organizational structure of educational institutions, in the means of training and education and in approaches to social services in education, distance and multimedia learning, which significantly increases the quality, efficiency and effectiveness of the educational process. The classification of currently known pedagogical technologies that are most often used in practice is shown. The basis of the innovative activity of a modern teacher is the formation of an innovative program-methodical complex in the discipline. Along with programmatic and content provision of disciplines, the use of informational tools and their didactic properties comes first. It combines technical capabilities - computer and video technology with live communication between the lecturer and the audience. In pedagogical innovation, the principles reflecting specific laws and regularities of the implementation of innovative processes are singled out. All principles are elements of a complex system of organization and management of innovative activities in the field of education and training. They closely interact with each other, which enhances the effect of each of them due to the synergistic effect. To improve innovative activities in the training of students, today computer technologies are widely used in pedagogy as a science, as well as directly in the practice of the pedagogical process. They have gained the most popularity in such activities as distance learning, online learning, assistance in the education management system, development of programs and virtual textbooks in various subjects, searching for information on the network for the educational process, computer testing of students' knowledge, creation of electronic libraries, formation of a unified scientific electronic environment, publication of virtual magazines and newspapers on pedagogical topics, teleconferences, expansion of international cooperation in the field of Internet education. The article considers computer technologies as the main building material for the entire society. In the modern world, there is a need to prepare a person for life in a multimedia environment. This process should be started as early as possible, because the child's contact with the media is present almost from the moment of his birth.

The Investigation of Pre-Service Elementary Teachers' Awareness on the Sources of Microplastics (미세플라스틱 배출원에 대한 초등예비교사들의 인식 조사)

  • Kyungmoon Jeon
    • Journal of Science Education
    • /
    • v.46 no.3
    • /
    • pp.223-236
    • /
    • 2022
  • The purpose of this study is to investigate pre-service elementary teachers' awareness on the sources of microplastics. The participants were 75 male and 91 female undergraduates. A 15-item survey questionnaire was developed based on prior researches regarding microplastics emission sources and were modified through expert review and preliminary research. The survey results show that over 80% of the respondents had heard of microplastics before through news, internet, TV, etc. However, they tended not to be aware that things such as lab coats, wet tissue, dust protective mask, or paper cup were made of microplastics-causing substances. For the questions on the expected situation of microplastics contamination, the frequency of their choices were relatively low in 'Tires of cars running are worn out' and 'The gum stuck to the floor becomes smaller.' These results show that many of them were not aware that synthetic fiber or synthetic rubber was one of the microplastics emission sources. Gender differences were found in the attitudes toward microplastics problems. Female students are more interested in the issues and are more willing to participate in the solution, and recognize the need for more education on microplastics. The implications and future directions for science education were discussed.