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检索条件"机构=Computer Science and Design"

共 8971 条记录，以下是1-10 订阅

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Employability Skills in computer science, Interior design, and Graphic design

Employability Skills in Computer Science, Interior Design, a...

引用

2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems, ICETSIS 2024

作者： Shorman, Samer Al Jubori, Uday Soltan, Mohamed Applied Science University Department of Computer Science Bahrain Applied Science University Department of Interior Design Bahrain Applied Science University Department of Graphic Design Bahrain

ISBN: (纸本)9798350372229

Employability skills are the fundamental competencies that help people succeed in their job and increase their employability. They are often referred to as soft skills or transferable talents. Employers place high importance on a variety of interpersonal, communication, problem-solving, and adaptability abilities that go beyond technical knowledge and credentials. Communication, teamwork, critical thinking, problem-solving, flexibility, time management, digital literacy, leadership, and professionalism are important employability skills. These abilities allow people to manage their time and resources, use technology, efficiently communicate with others, assess complex circumstances, make educated judgments, adjust to new obstacles, and work with professionalism. A combination of formal education, hands-on learning, professional development programs, internships, and ongoing self-improvement can help increase employable skills. The development and integration of these abilities into curriculum, employment settings, and training efforts are greatly aided by the cooperation of businesses, policymakers, and educational institutions. The employability skills for computer science, interior design, and graphic design will be reviewed in this article in order to highlight the most frequently needed abilities for those disciplines. © 2024 IEEE.

关键词： computer science employability skills graphic design interior design

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design and Development of a Knowledge Service Platform in the Field of computer science: Knowledge Service Platform in computer science: design and Development 23

Design and Development of a Knowledge Service Platform in th...

引用

8th International Conference on Distance Education and Learning, ICDEL 2023

作者： Chen, Chunyun Zhu, Shuai Tao, Qianwen Wu, Qidi Shi, Youqun School of Fashion and Art Design Donghua University Shanghai China School of Computer Science and Technology Donghua University Shanghai China

ISBN: (纸本)9798400700422

This paper introduces a crowdsourcing-based method for expanding knowledge graphs, aiming to address the high production cost problem of building high-quality domain knowledge graphs. The method includes stages such as task assignment, task division, and incentive mechanisms, which leverage the power of crowdsourcing workers to obtain high-quality domain knowledge content and expand and refine the structure and content of knowledge graphs. Additionally, to address the problem that traditional computer teaching methods cannot meet students' learning needs, this paper also develops a computer domain knowledge service platform that is easy to read and understand, has multiple types of knowledge expression, and is interactive. The platform presents the structure and content of knowledge graphs in a visual and interactive way, providing a new way of learning computer knowledge for students and relevant personnel. It not only helps students and relevant personnel better understand computer knowledge but also expands the structure and content of knowledge graphs, providing support for the application and promotion of knowledge graphs. The method and platform presented in this paper have practical value and promotion significance and are expected to play an important role in the expansion and teaching of computer domain knowledge graphs. © 2023 ACM.

关键词： Crowdsourcing

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Employability Skills in computer science, Interior design, and Graphic design

Employability Skills in Computer Science, Interior Design, a...

引用

Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS), ASU International Conference in

作者： Samer Shorman Uday Al Jubori Mohamed Soltan Department of Computer Science Applied Science University Kingdom of Bahrain Department of Interior Design Applied Science University Kingdom of Bahrain Department of Graphic Design Applied Science University Kingdom of Bahrain

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Real-Time Gesture Analysis for Evaluating Student Performance and Engagement 4

Real-Time Gesture Analysis for Evaluating Student Performanc...

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Waghmare, Himanshu Sharma, Mansi Suryawanshi, Falguni Department of Computer Science and Design Wardha India

ISBN: (纸本)9798331523923

This paper is an extension of the practical application of computer vision and machine learning in monitoring student performance with the help of nonverbal communication, body language, and facial expressions analysis. The real-time visual input is processed within the system which identifies various postures and gestures by integrating Python packages such as OpenCV, MediaPipe, NumPy, pandas, and scikit-learn. MediaPipe's holistic framework detects 3D landmarks that dynamically capture the body and facial expressions of students. These are then paired with machine learning models to predict behavior in terms of student engagement, attention levels, and participation. The traditional methods of classroom observation rely more on subjective interpretations, which have led to many inconsistencies. The project eliminates the limitations by automatically analyzing nonverbal cues, thus allowing educators to make objective observations about students' behavior. The data gathered is systematically classified into predefined categories by using the Ridge Classifier algorithm for high accuracy and interpretability. The study provides the possibility that such a system can help teachers trace learning issues and improve teaching techniques. It, however, displays possible applications besides education, which include criminal investigation, cooperative assessment of tasks, and remote observation in virtual areas. This advancement in technology increases the interface between AI and education. It shows an ability to affect the traditional methodologies of assessment used in education. © 2025 IEEE.

关键词： Students

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Cataract Detection and Classification Using YOLOv9 and Machine Learning 4

Cataract Detection and Classification Using YOLOv9 and Machi...

引用

4th International Conference on Sentiment Analysis and Deep Learning, ICSADL 2025

作者： Suryawanshi, Falguni Reddy, Ktv Department of Computer Science and Design Wardha India

ISBN: (纸本)9798331523923

Cataracts, a common age-related eye condition characterized by the clouding of the eye's natural lens, can impair vision if left untreated. Advances in cataract surgery have significantly improved treatment outcomes, but complications like posterior capsule rupture (PCR) still pose risks. Early detection is crucial, and recent developments in machine learning, particularly the YOLOv9 deep learning model, have shown promise in automating cataract detection using medical images such as eye scans. YOLOv9 can be trained to identify cataracts by recognizing distinct features like lens cloudiness and opacities. By leveraging image classification techniques and data augmentation, YOLOv9 achieves high accuracy in real-time cataract detection, assisting healthcare professionals in timely diagnoses and improving clinical workflows. Additionally, this model supports telemedicine applications by enabling remote analysis, expanding access to ophthalmic care. This paper highlights the significance of automated cataract detection using YOLOv9, its impact on early diagnosis, and its potential to enhance patient outcomes in ophthalmology through efficient image classification systems. © 2025 IEEE.

关键词： Ophthalmology

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Recent Gas/Odor Sensor Array Signal Processing Trend for Model Nose: A Mini Review 5

Recent Gas/Odor Sensor Array Signal Processing Trend for Mod...

引用

5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Chaudhri, Shiv Nath Department of Computer Science and Design Wardha India

ISBN: (纸本)9798350379945

The study of merging artificial intelligence and the processing of gas and odor sensors' data is known as artificial olfaction or model nose. Gas/odor sensor data is formed by sensor response modalities that produce signature patterns that represent a particular response of a gas/odor sensor. It can be difficult to analyze the particular objective by using drift-affected gas and odor sensor data and trying to gain hidden insight from the model nose. The classification and quantification of gas and odor sensor signals is significantly challenging in model nose tasks and plays a vital role in careful sensor signal processing. The application of data-driven tactics for utilizing the outcomes of the model nose for higher performance is quite challenging. The gas/odor sensor signal processing aims to provide salient features as per the application area, in addition to achieving high accuracy. The recent sensor signal processing methods for the model nose were reviewed. The dataset, response modalities employed, trade-offs associated with each technique, and classification and quantification techniques were all covered in the article. At the end, it is demonstrated that there is a significant challenge and an open research area regarding the improvement of sensor signal processing techniques, such as raising accuracy and sensitivity values and being practical in using model noses efficiently. © 2024 IEEE.

关键词： Array processing

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Sleep Apnea Prediction using Machine Learning

Sleep Apnea Prediction using Machine Learning

引用

2024 IEEE International Conference on Intelligent Computing and Emerging Communication Technologies, ICEC 2024

作者： Sharma, Mansi Puri, Chetan Department of Computer Science and Design Wardha India

ISBN: (纸本)9798331508432

A promising strategy for improving sleep apnea detection and treatment is machine learning. Through the utilize of cutting-edge algorithms and non-invasive information, scientists can make exact and successful models that help in recognizing those who may be at risk for this unsafe sickness. These models can predict the event of sleep apnea by analyzing a variety of components, such as physiological measures, restorative history, and statistic information. Although machine learning has appeared a part of guarantee in this field, advance investigation is required to affirm how well these models work in an assortment of clinical settings and population categories. Polysomnography, a meddling and time-consuming method that requires a night in a rest lab for patients, is the standard strategy utilized to diagnose sleep apnea. Since of this, there has been a rise in horribleness and passing from deferred early recognizable proof and treatment. Alternately, wearable innovation or smartphone apps may be utilized to manage machine learning-based models at home, increasing accessibility and convenience of diagnosis. Moreover, machine learning can help in recognizing individuals who would advantage from treatment but might not get a determination through routine means. These calculations have the capacity to recognize patterns in information that human masters would miss, which might result in early activity and way better comes about. Huge and different datasets are fundamental for the advancement of machine learning models for sleep apnea expectation, which presents an issue. These datasets got to contain a range of clinical and statistic characteristics, as well as individuals with and without sleep apnea. Also, to ensure consistency and comparability, the information ought to be assembled concurring to built up forms. The complexity of sleep apnea itself presents another trouble. Numerous factors, counting as heredity, lifestyle, and fundamental therapeutic issues, might

关键词： Sleep research

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Comparative Study of Machine Learning and Deep Learning Models for Food Waste Detection Using Image Processing

Comparative Study of Machine Learning and Deep Learning Mode...

引用

2025 IEEE International Students' Conference on Electrical, Electronics and computer science, SCEECS 2025

作者： Rajagopal, R. Chaithanya, K. Sonth, Ankita Kallappagoudar, Prasanna Basanagouda Mohammadishaq Nadaf, Mohammadzaid Ananda Theertha, H. Dept of Computer Science Alliance College of Engineering and Design Alliance University Bangalore India Bangalore India Alliance College of Engineering and Design Dept of Computer Science Bangalore India Alliance College of Engineering and Design Dept of Computer Science and Engineering Bangalore India

ISBN: (纸本)9798331529833

For the purpose of reducing financial losses and environmental impacts, food waste detection is essential. Inorder to detect food waste using image processing, this study investigates the efficiency of several machine learning algorithms, including Convolutional Neural Network (CNN), K-Nearest Neighbors (KNN), Random Forest, and Inception Model (IV3). A set of images of food are then processed. Before each algorithm is used for classification, pre-processing methods like segmentation and feature extraction are used. © 2025 IEEE.

关键词： k-nearest neighbors

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A Review: Transformative Impact of Data Visualization Across Various Industries 8

A Review: Transformative Impact of Data Visualization Across...

引用

8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Sharma, Mansi Puri, Chetan Kumar, Praveen Department of Computer Science and Design Wardha India Department of Computer Science and Medical Engineering Wardha India

ISBN: (纸本)9798350376425

In today's data-driven world, data visualization has emerged as a powerful tool for transforming raw data into actionable insights. This paper explores the profound impact of data visualization across various industries, including banking, healthcare, and education. By utilizing advanced visualization tools, professionals can gain unparalleled clarity in identifying patterns, trends, and hidden opportunities within complex datasets. The introduction of dynamic dashboards and immersive 3D representations are revolutionizing the process of data interpretation, enabling real-time monitoring and enhanced spatial understanding. This research study analyzes the transformative effects of data visualization on decision-making, particularly in the realm of finance and budgeting. Visual representations can uncover hidden patterns, mitigate risks, and inform strategic decisions. Beyond these industries, data visualization is also revolutionizing marketing, manufacturing, and education. By enhancing creativity, streamlining workflows, and improving communication, visual experiences are driving innovation and progress. Overall, data visualization is a critical tool for unlocking the value of data in today's information-intensive world. By providing actionable insights and driving effective decision-making, data visualization is transforming industries and empowering organizations to achieve their goals. © 2024 IEEE.

关键词： Budget control

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A Comprehensive Study of Water Quality Trends and Seasonal Variations in Coastal Bays 2

A Comprehensive Study of Water Quality Trends and Seasonal V...

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2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Sharma, Mansi Kumar, Praveen Department of Computer Science and Design Wardha India Department of Computer Science and Medical Engineering Wardha India

ISBN: (纸本)9798331528713

Monitoring and analysing water quality parameters is fundamental for the early detection of natural changes in coastal bays. This paper examines regular varieties and relationships among key water quality parameters - salinity, broken up oxygen, pH, Secchi profundity, water profundity, and water temperature - collected from a coastal bay over a period in 1994. Information preprocessing included changing over dates to a standardized arrange and guaranteeing numerical consistency over parameters. Exploratory data analysis (EDA) given experiences into the temporal patterns of individual parameters. Consequent relationship examination revealed significant interdependencies among the parameters, highlighting potential impacts of seasonal and environmental components. The paper moreover reviewed monthly midpoints to recognize regular designs. Line plots laid out the varieties in saltiness, broken up oxygen, pH, and water temperature over differing months, emphasizing the cyclic nature of these parameters. Comes about appear unmistakable regular designs, such as higher broken down oxygen levels amid colder months and assortments in saltiness comparing to potential freshwater convergences. These revelations emphasize the centrality of nonstop water quality watching to induce it the energetic natural forms impacting coastal ecosystems. This investigate contributes to natural administration methods by giving a comprehensive examination of water quality variances, helping inside the definition of approaches for the conservation and economical administration of coastal bay regions. © 2024 IEEE.

关键词： Abiotic

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