• Title/Summary/Keyword: Contextual Research

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Attention-based CNN-BiGRU for Bengali Music Emotion Classification

  • Subhasish Ghosh;Omar Faruk Riad
    • International Journal of Computer Science & Network Security
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    • v.23 no.9
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    • pp.47-54
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    • 2023
  • For Bengali music emotion classification, deep learning models, particularly CNN and RNN are frequently used. But previous researches had the flaws of low accuracy and overfitting problem. In this research, attention-based Conv1D and BiGRU model is designed for music emotion classification and comparative experimentation shows that the proposed model is classifying emotions more accurate. We have proposed a Conv1D and Bi-GRU with the attention-based model for emotion classification of our Bengali music dataset. The model integrates attention-based. Wav preprocessing makes use of MFCCs. To reduce the dimensionality of the feature space, contextual features were extracted from two Conv1D layers. In order to solve the overfitting problems, dropouts are utilized. Two bidirectional GRUs networks are used to update previous and future emotion representation of the output from the Conv1D layers. Two BiGRU layers are conntected to an attention mechanism to give various MFCC feature vectors more attention. Moreover, the attention mechanism has increased the accuracy of the proposed classification model. The vector is finally classified into four emotion classes: Angry, Happy, Relax, Sad; using a dense, fully connected layer with softmax activation. The proposed Conv1D+BiGRU+Attention model is efficient at classifying emotions in the Bengali music dataset than baseline methods. For our Bengali music dataset, the performance of our proposed model is 95%.

Protecting Privacy of User Data in Intelligent Transportation Systems

  • Yazed Alsaawy;Ahmad Alkhodre;Adnan Abi Sen
    • International Journal of Computer Science & Network Security
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    • v.23 no.5
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    • pp.163-171
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    • 2023
  • The intelligent transportation system has made a huge leap in the level of human services, which has had a positive impact on the quality of life of users. On the other hand, these services are becoming a new source of risk due to the use of data collected from vehicles, on which intelligent systems rely to create automatic contextual adaptation. Most of the popular privacy protection methods, such as Dummy and obfuscation, cannot be used with many services because of their impact on the accuracy of the service provided itself, they depend on changing the number of vehicles or their physical locations. This research presents a new approach based on the shuffling Nicknames of vehicles. It fully maintains the quality of the service and prevents tracking users permanently, penetrating their privacy, revealing their whereabouts, or discovering additional details about the nature of their behavior and movements. Our approach is based on creating a central Nicknames Pool in the cloud as well as distributed subpools in fog nodes to avoid intelligent delays and overloading of the central architecture. Finally, we will prove by simulation and discussion by examples the superiority of the proposed approach and its ability to adapt to new services and provide an effective level of protection. In the comparison, we will rely on the wellknown privacy criteria: Entropy, Ubiquity, and Performance.

Cross-cultural Studies Revisited in International Business (국제비즈니스에서 비교문화 연구의 재검토)

  • Cho, Ho-Hyeon
    • Iberoamérica
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    • v.12 no.1
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    • pp.407-439
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    • 2010
  • Growth of researches addressing cross-culture in international business is exponential. This article reviews the extant researches around the national culture and describes the various conceptualization of culture through discussion of some of popular models of national culture. This article presented some of the most important issues in international business surrounding globalization, especially convergence and divergence of cultures and cultural changes. Global rapid changes in international business environment request the reconsideration of the assumption of cultural stability and the simple view of culture, which tends to examine the static influence of a few cultural factors in isolation form other cultural factors and contextual elements. This paper identifies a valid cultural grouping and proposes the following typology of the possible methodologies in international business; Ethnological description, Use of proxies, Direct values inference, and Indirect values inference. Rather than selecting a single methodology, it appears to be more appropriate to use multi-method in the cross-cultural international business research. It has been shown that cultural change is intertwined with socioeconomic-institutional variables, and that these variables may also add to determine culture contemporarily. This paper also explained the dynamics of culture as multi-level, multi-layer constructs. According to this model, we may understand how the dynamic nature of culture conveys the top-down-bottom-up processes where one cultural level affects changes in other level of culture.

Updating BIM: Reflecting Thermographic Sensing in BIM-based Building Energy Analysis

  • Ham, Youngjib;Golparvar-Fard, Mani
    • International conference on construction engineering and project management
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    • 2015.10a
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    • pp.532-536
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    • 2015
  • This paper presents an automated computer vision-based system to update BIM data by leveraging multi-modal visual data collected from existing buildings under inspection. Currently, visual inspections are conducted for building envelopes or mechanical systems, and auditors analyze energy-related contextual information to examine if their performance is maintained as expected by the design. By translating 3D surface thermal profiles into energy performance metrics such as actual R-values at point-level and by mapping such properties to the associated BIM elements using XML Document Object Model (DOM), the proposed method shortens the energy performance modeling gap between the architectural information in the as-designed BIM and the as-is building condition, which improve the reliability of building energy analysis. The experimental results on existing buildings show that (1) the point-level thermography-based thermal resistance measurement can be automatically matched with the associated BIM elements; and (2) their corresponding thermal properties are automatically updated in gbXML schema. This paper provides practitioners with insight to uncover the fundamentals of how multi-modal visual data can be used to improve the accuracy of building energy modeling for retrofit analysis. Open research challenges and lessons learned from real-world case studies are discussed in detail.

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Developing and Evaluating Damage Information Classifier of High Impact Weather by Using News Big Data (재해기상 언론기사 빅데이터를 활용한 피해정보 자동 분류기 개발)

  • Su-Ji, Cho;Ki-Kwang Lee
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.46 no.3
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    • pp.7-14
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    • 2023
  • Recently, the importance of impact-based forecasting has increased along with the socio-economic impact of severe weather have emerged. As news articles contain unconstructed information closely related to the people's life, this study developed and evaluated a binary classification algorithm about snowfall damage information by using media articles text mining. We collected news articles during 2009 to 2021 which containing 'heavy snow' in its body context and labelled whether each article correspond to specific damage fields such as car accident. To develop a classifier, we proposed a probability-based classifier based on the ratio of the two conditional probabilities, which is defined as I/O Ratio in this study. During the construction process, we also adopted the n-gram approach to consider contextual meaning of each keyword. The accuracy of the classifier was 75%, supporting the possibility of application of news big data to the impact-based forecasting. We expect the performance of the classifier will be improve in the further research as the various training data is accumulated. The result of this study can be readily expanded by applying the same methodology to other disasters in the future. Furthermore, the result of this study can reduce social and economic damage of high impact weather by supporting the establishment of an integrated meteorological decision support system.

Design and Implementation of Contextual Information Analysis System in USN Environment (USN 환경에서의 상황정보 분석 시스템의 설계 및 구현)

  • Cheng Hao Jin;Yongmi Lee;Kwang Woo Nam;Jun Wook Lee;Keun Ho Ryu
    • Proceedings of the Korea Information Processing Society Conference
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    • 2008.11a
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    • pp.422-425
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    • 2008
  • 최근 IT 기술의 발전과 더불어 다양한 종류의 컴퓨터가 사람, 사물, 환경 속으로 스며들어 네트워크 망을 이루는 USN(Ubiquitous Sensor Network) 환경이 급속히 보급되고 있다. USN 환경에서 수집되는 센서 스트림 데이터는 연속적이며 동적으로 끊임없이 전달이 되기 때문에 그 양이 방대하며 또한 제한된 메모리를 사용하기 때문에 모든 데이터를 저장하여 처리할 수는 없게 된다. 스트림 데이터의 이러한 특성 때문에 본 논문에서는 입력되는 스트림 상황정보에 대해서 신속한 상황 분석 서비스를 진행하기 위하여 슬라이딩 윈도우 기법을 지원하는 상황정보 분석 시스템을 제안한다. 이 시스템은 온도, 습도, 조도 등 스트림 데이터에 대해서 WHEN-DO 상황질의모델을 적용하여 상황질의모델의 조건 만족 여부를 판단하고 특정 행동을 취한다. 따라서 본 논문에서 제안한 시스템은 실시간 건물의 상황정보를 수집하여 상태를 모니터링 하는 등 많은 USN 응용분야에 적용이 가능하다.

Research on Chinese Microblog Sentiment Classification Based on TextCNN-BiLSTM Model

  • Haiqin Tang;Ruirui Zhang
    • Journal of Information Processing Systems
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    • v.19 no.6
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    • pp.842-857
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    • 2023
  • Currently, most sentiment classification models on microblogging platforms analyze sentence parts of speech and emoticons without comprehending users' emotional inclinations and grasping moral nuances. This study proposes a hybrid sentiment analysis model. Given the distinct nature of microblog comments, the model employs a combined stop-word list and word2vec for word vectorization. To mitigate local information loss, the TextCNN model, devoid of pooling layers, is employed for local feature extraction, while BiLSTM is utilized for contextual feature extraction in deep learning. Subsequently, microblog comment sentiments are categorized using a classification layer. Given the binary classification task at the output layer and the numerous hidden layers within BiLSTM, the Tanh activation function is adopted in this model. Experimental findings demonstrate that the enhanced TextCNN-BiLSTM model attains a precision of 94.75%. This represents a 1.21%, 1.25%, and 1.25% enhancement in precision, recall, and F1 values, respectively, in comparison to the individual deep learning models TextCNN. Furthermore, it outperforms BiLSTM by 0.78%, 0.9%, and 0.9% in precision, recall, and F1 values.

Effects of Digital Shadow Work on Foreign Users' Emotions and Behaviors during the Use of Korean Online Shopping Sites

  • Pooja Khandagale;Joon Koh
    • Asia pacific journal of information systems
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    • v.33 no.2
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    • pp.389-417
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    • 2023
  • Social distancing required the use of doorstep delivery for nearly all purchases during the COVID-19 pandemic. Foreign users in Korea are forced to participate in superfluous tasks, leading to an increase in their anxiety and fatigue while online shopping. This study examines how digital shadow work stemming from the language barrier can affect the emotions and behaviors of foreign shoppers that use Korean shopping sites. By interviewing 37 foreign users in Korea, this draft examined their experiences, behaviors, and emotional output, classifying them into 14 codes and seven categories. Using grounded theory, we found that online shoppers' emotions, feelings, experiences, and decision making may be changed in the stages of the pre-use, use, and post-use activities. User responses regarding shadow work and related obstacles can be seen with the continue, discontinue, and optional (occasional use) of Korean online shopping sites. Pleasure and satisfaction come from high efficiency and privileges, whereas anger and disappointment come from poor self-confidence and pessimism. Furthermore, buyer behavior and product orientation are identified as intervening conditions, while the online vs. offline shopping experiences are identified as contextual conditions. In conclusion, language barriers and other factors make online shopping difficult for foreign shoppers, which negatively affects their psychological mechanisms and buying behaviors. The implications from the study findings and future research are also discussed.

Collaboration Development Factors and Consideration for Community Health Promotion Practice (지역사회 건강증진을 위한 협력개발 요인과 논점)

  • Yoo, Seung-Hyun
    • Korean Journal of Health Education and Promotion
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    • v.27 no.5
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    • pp.73-78
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    • 2010
  • Background: Although collaboration for community health is emphasized, the concept and process of collaboration are rather unclear. International research has classified the types of collaboration and focused on the factors influencing successful collaboration. Greater attention is needed for collaboration practice and research domestically. Findings: By the level of intensity, the types of collaboration range from simpler networking to more formal and sophisticated collaboration. A 4-stage collaboration development consists of formation, implementation, maintenance, and institutionalization stages. Influential factors for collaboration development include: shared goals; operational structure and process; sufficient resources; member and leadership characteristics; environment and climate for collaboration; and information exchange and communication. Discussion: Most of collaboration research so far has dealt with partnerships and coalition building with community-based organizations, and much attention is given to private-public partnership for health. Contextual understanding and collaborative environment are the foremost tasks for us to enhance collaboration for community health in our centralized public health system.

Accessibility Factors to Health Check-Ups for People with Disability: A Qualitative Study (장애인 건강검진 접근성 저해요인과 개선방안 도출에 대한 질적 연구)

  • Hong, Hye-Su;Lim, Myung Joon;Kim, Oi-Sook;Choi, Eun-Sook;Kim, Jung Hwan
    • Health Policy and Management
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    • v.30 no.3
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    • pp.335-344
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    • 2020
  • Background: The purpose of this study was to identify factors inhibiting access of people with disability to health check-ups as well as identify pertinent solutions for improvement. Methods: Twenty-three people with disability older than the age of 19 who took respective health check-ups within the last 3 years were selected as participants. For the data collection, the 1:1 intensive interview was used. The data were analyzed by the grounded theory by Corbin and Strauss. Results: The results comprised nine categories, 23 subcategories, and 179 concepts. The central phenomenon was 'failure to obtain check-ups.' Causal conditions were observed as a 'lack of communication method,' 'physical difficulties,' and 'staff unfamiliar with people with disability,' Interventional conditions comprised 'physical accessibility,' 'staffs' competency,' and 'assistant manpower.' The active strategy was included 'to investigate the professional medical institution,' 'to find the medical institution of convenient traffic accessibility,' 'to overcome communication difficulties through equipment,' and 'to overcome linguistic barriers through sufficient communication.' Whereas, 'utilization of ancillary equipment,' 'the education of staffs on people with disability,' 'universal design manual,' and 'customized check-ups' were included in the passive strategy. Such processes arose in the contextual conditions of 'lack of expectations for daily lives' and 'lack of government support.' As a consequence, the subjects participated experienced the 'disadvantages,' 'discrimination,' and 'reduced reliability of the health check-ups.' Conclusion: The subjects who participated in this study emphasized 'staffs familiar with people with disability' and 'systems customized for people with disability' are mandatory to secure complete health check-ups for people with disability.