• Title/Summary/Keyword: human attributes

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Objective Measurements of Textural and Rheological Properties of Cheese (치즈 물성의 객관적 측정을 위한 고찰)

  • Lee, Mee-Ryung
    • Journal of Dairy Science and Biotechnology
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    • v.36 no.2
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    • pp.73-80
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    • 2018
  • The textural and rheological properties of cheese are major attributes for the characterization of cheese types, ripening, and consumer preferences. The use of small amplitude oscillatory rheological testing has made it possible for cheese researchers to assess the major properties of cheese, such as melting behavior and storage modulus, without irreversible deformation. In addition, large deformation testing such as textural profile analysis can assess properties such as hardness of cheese. While the sensory properties of cheese are valued by consumers, objective and reliable measurements are paramount for researchers. Ongoing development and refinement of scientific measurement methods of cheese are vital.

Bio-inspired self powered nervous system for civil structures

  • Shoureshi, Rahmat A.;Lim, Sun W.
    • Smart Structures and Systems
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    • v.5 no.2
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    • pp.139-152
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    • 2009
  • Globally, civil infrastructures are deteriorating at an alarming rate caused by overuse, overloading, aging, damage or failure due to natural or man-made hazards. With such a vast network of deteriorating infrastructure, there is a growing interest in continuous monitoring technologies. In order to provide a true distributed sensor and control system for civil structures, we are developing a Structural Nervous System that mimics key attributes of a human nervous system. This nervous system is made up of building blocks that are designed based on mechanoreceptors as a fundamentally new approach for the development of a structural health monitoring and diagnostic system that utilizes the recently developed piezo-fibers capable of sensing and actuation. In particular, our research has been focused on producing a sensory nervous system for civil structures by using piezo-fibers as sensory receptors, nerve fibers, neuronal pools, and spinocervical tract to the nodal and central processing units. This paper presents up to date results of our research, including the design and analysis of the structural nervous system.

A Human-Scaled Future for Dense Development

  • Harbour, Ivan
    • International Journal of High-Rise Buildings
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    • v.7 no.2
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    • pp.141-143
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    • 2018
  • Critics of height argue that it de-humanizes our cities. Yet a critical mass is a necessity for vibrant city life, and height is a key contributor. If we can overcome the environmental impacts and technicalities of building tall and dense, our cities' streets can thrive and prosper. To make this happen, we must move towards working together to share resources, so we can ensure the continuity of the public realm. We already have the tools to do this; the challenge lies in the coordination of the public and private institutions that govern urban space. District heating and cooling systems; shared logistics spaces; care, responsibility and ownership of the public realm between buildings; seamless connectivity between modes of transport; creative combinations of shelter and seating, and the placement of buildings so that they are not overbearing to the streets around them - these attributes can be found in many places, though rarely all at once. This paper looks at the development of the city and offers Barangaroo South, Sydney, which addresses all these aspects, as a potential template for future city planning.

A Qualitative Approach to eIT Project Management (e-비즈니스 IT 프로젝트 관리의 정성적 접근 모형의 개발)

  • Jeong, Gi-Ho
    • Journal of Information Technology Services
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    • v.1 no.1
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    • pp.45-55
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    • 2002
  • This paper suggests a new approach to IT project management based on a regular project meeting results to consider the recent project environment. The greater part of recent IT projects are related to e-business transformation. Transforming to e-business is a new problem very different from those they have been worked, in several point of views. Under e-business era, therefore any IT project is being implemented in more complex, dynamic and uncertain environment than traditional. That is, project leaders must consider more factors to control projects including resources, quality, risks, and technologies, and human resources. The project organizations and software corporations thus need to develop and establish new concepts or methodologies to manage e-business projects. In this point of view, an entropy model in this study is introduced for estimating and managing the uncertainty in project control using multi-attributes of project meeting. This paper proposes a new frame work based on entropy model using project meeting results to consider eIT project environment with a small pilot study.

Analysis of Traffic Accident using Association Rule Model

  • Ihm, Sun-Young;Park, Young-Ho
    • Journal of Multimedia Information System
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    • v.5 no.2
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    • pp.111-114
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    • 2018
  • Traffic accident analysis is important to reduce the occurrence of the accidents. In this paper, we analyze the traffic accident with Apriori algorithm to find out an association rule of traffic accident in Korea. We first design the traffic accident analysis model, and then collect the traffic accidents data. We preprocessed the collected data and derived some new variables and attributes for analyzing. Next, we analyze based on statistical method and Apriori algorithm. The result shows that many large-scale accident has occurred by vans in daytime. Medium-scale accident has occurred more in day than nighttime, and by cars more than vans. Small-scale accident has occurred more in night time than day time, however, the numbers were similar. Also, car-human accident is more occurred than car-car accident in small-scale accident.

Extracting and Clustering of Story Events from a Story Corpus

  • Yu, Hye-Yeon;Cheong, Yun-Gyung;Bae, Byung-Chull
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.10
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    • pp.3498-3512
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    • 2021
  • This article describes how events that make up text stories can be represented and extracted. We also address the results from our simple experiment on extracting and clustering events in terms of emotions, under the assumption that different emotional events can be associated with the classified clusters. Each emotion cluster is based on Plutchik's eight basic emotion model, and the attributes of the NLTK-VADER are used for the classification criterion. While comparisons of the results with human raters show less accuracy for certain emotion types, emotion types such as joy and sadness show relatively high accuracy. The evaluation results with NRC Word Emotion Association Lexicon (aka EmoLex) show high accuracy values (more than 90% accuracy in anger, disgust, fear, and surprise), though precision and recall values are relatively low.

Classification System of Fashion Emotion for the Standardization of Data (데이터 표준화를 위한 패션 감성 분류 체계)

  • Park, Nanghee;Choi, Yoonmi
    • Journal of the Korean Society of Clothing and Textiles
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    • v.45 no.6
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    • pp.949-964
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    • 2021
  • Accumulation of high-quality data is crucial for AI learning. The goal of using AI in fashion service is to propose of a creative, personalized solution that is close to the know-how of a human operator. These customized solutions require an understanding of fashion products and emotions. Therefore, it is necessary to accumulate data on the attributes of fashion products and fashion emotion. The first step for accumulating fashion data is to standardize the attribute with coherent system. The purpose of this study is to propose a fashion emotional classification system. For this, images of fashion products were collected, and metadata was obtained by allowing consumers to describe their emotions about fashion images freely. An emotional classification system with a hierarchical structure, was then constructed by performing frequency and CONCOR analyses on metadata. A final classification system was proposed by supplementing attribute values with reference to findings from previous studies and SNS data.

Effectiveness of e-health systems in improving hypertension management and awareness: a systematic review

  • Alotaibi, Mohamed;Ammad uddin, Mohammad
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.1
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    • pp.173-187
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    • 2022
  • Recent studies have focused on self-management of hypertension using smart devices (cellular phones, tablets, watches). It has proven to be an effective tool for early detection and control of high Blood Pressure (BP) without affecting patients' daily routines. This systematic review surveys the existing self-monitoring systems, evaluate their effectiveness and compares the different approaches. We investigated the current systems in terms of various attributes, including methods used, sample size, type of investigation, inputs/ outputs, rate of success in controlling BP, group of users with higher response rate and beneficiaries, acceptability, and adherence to the system. We identified some limitations, shortcomings, and gaps in the research conducted recently studying the impact of mobile technology on managing hypertension. These shortcomings can generate future research opportunities and enable it to become more realistic and adaptive. We recommended including more observable factors and human behaviors that affect BP. Furthermore, we suggested that vital monitoring/logging and medication tuning are insufficient to improve hypertension control. There is also a need to observe and alter patient behavior and lifestyles.

A study of creative human judgment through the application of machine learning algorithms and feature selection algorithms

  • Kim, Yong Jun;Park, Jung Min
    • International journal of advanced smart convergence
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    • v.11 no.2
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    • pp.38-43
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    • 2022
  • In this study, there are many difficulties in defining and judging creative people because there is no systematic analysis method using accurate standards or numerical values. Analyze and judge whether In the previous study, A study on the application of rule success cases through machine learning algorithm extraction, a case study was conducted to help verify or confirm the psychological personality test and aptitude test. We proposed a solution to a research problem in psychology using machine learning algorithms, Data Mining's Cross Industry Standard Process for Data Mining, and CRISP-DM, which were used in previous studies. After that, this study proposes a solution that helps to judge creative people by applying the feature selection algorithm. In this study, the accuracy was found by using seven feature selection algorithms, and by selecting the feature group classified by the feature selection algorithms, and the result of deriving the classification result with the highest feature obtained through the support vector machine algorithm was obtained.

Theories, Frameworks, and Models of Using Artificial Intelligence in Organizations

  • Alotaibi, Sara Jeza
    • International Journal of Computer Science & Network Security
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    • v.22 no.11
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    • pp.357-366
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    • 2022
  • Artificial intelligence (AI) is the replication of human intelligence by computer systems and machines using tools like machine learning, deep learning, expert systems, and natural language processing. AI can be applied in administrative settings to automate repetitive processes, analyze and forecast data, foster social communication skills among staff, reduce costs, and boost overall operational effectiveness. In order to understand how AI is being used for administrative duties in various organizations, this paper gives a critical dialogue on the topic and proposed a framework for using artificial intelligence in organizations. Additionally, it offers a list of specifications, attributes, and requirements that organizations planning to use AI should consider.