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检索条件"丛书名=Lecture Notes in Networks and Systems"

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IntentRec: An Advanced Recommender System Leveraging User-Item Intent

IntentRec: An Advanced Recommender System Leveraging User-It...

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Computing Conference

作者： Vaidya, Abhishrut Chatterjee, Niladri Indian Inst Technol Delhi New Delhi 110023 India

ISBN: (纸本)9783031622793;9783031622779;9783031622762

The present paper proposes a novel recommendation technique called IntentRec that focuses on modeling a movie recommender system based solely on the pattern of user ratings for the items, called intent. Unlike existing recommendation algorithms that rely on item and user descriptions, IntentRec leverages the intent behind ratings to generate more accurate recommendations. The initial intent for each user is computed as a prior-intent probability. It is represented as a distribution of ratings over rating types (i.e., 1, 2, 3, 4, 5) over all the items. Through an optimization process using a convoluted kernel layer followed by a kernelized AutoEncoder, the model calculates post-intent probability, representing the rating distribution of users and items. IntentRec addresses the challenges of variation and sparsity in user ratings by incorporating periodic updates in the user-item intents throughout the learning process. This dynamic adaptation helps the model handle varying and sparse rating data robustly. The objective of predicting missing ratings in IntentRec is to utilize similar users and similar items calibrated with comparable similarity scores. This collaborative filtering approach aids in mitigating the cold start problem, where there is limited information about new users or items. Moreover, IntentRec has fewer parameters, making it computationally efficient. The experimental results demonstrate that IntentRec performs better than the current state-of-the-art results using the RMSE metric on the Movielens and Douban datasets without requiring additional side information.

关键词： Recommender systems Information retrieval Kernel methods

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Speech Emotion Recognition Using Support Vector Machine 9th

Speech Emotion Recognition Using Support Vector Machine

引用

9th International Congress on Information and Communication Technology (ICICT)

作者： Al Zoubi, Rouaa Turky, Ayad Foufou, Sebti Univ Sharjah Coll Comp & Informat Dept Comp Sci Sharjah U Arab Emirates

ISBN: (纸本)9789819733019;9789819733026

Speech Emotion Recognition (SER) is a significant research field focusing on the automatic recognition and classification of emotions from speech signals. With the advancement of machine learning techniques, SER has seen significant development in recent years. This study presents a methodology for SER using a Support Vector Machine method. The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) dataset is used to evaluate the effectiveness of the proposed method, which includes seven emotional states: calmness, neutrality, furiousness, pleasure, fear, sadness, and disgust startlement. The results show that the Support Vector Machine method notably improves over the other machine learning models by providing the highest recognition accuracy of 85% on the RAVDESS dataset.

关键词： Speech emotion recognition Sentiment analysis Support vector machine

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Introduction of Steganography to Improve the Security of Transmitted Data

Introduction of Steganography to Improve the Security of Tra...

引用

Computing Conference

作者： Manankova, Olga Yakubova, Mubarak Yakubov, Bakhodyr Int Informat Technol Univ Alma Ata Kazakhstan Almaty Univ Power Engn & Telecommun Alma Ata Kazakhstan

ISBN: (纸本)9783031622755;9783031622731;9783031622724

The large use of computing technologies and the steady growth in the volume of multimedia streams creates interest in software methods and means of protecting information. The use of information security software does not require significant financial costs when compared with hardware cryptosystems. However, the use of only one method or means of information protection, for example, only encryption, today cannot always cope with data loss. Since, along with the development of methods and means of protecting information, the competence of hackers is also growing, it is possible to ensure reliable protection of information by using additional levels of protection. This article proposes to develop a software implementation of the process of multi-level protection of transmitted data over an insecure channel, which implements data encryption using a symmetric algorithm, then applies the developed Positional LSB steganography algorithm, which is based on a random selection of pixels.

关键词： LSB Steganography Data protection Random

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Human Emergency Detection During Autonomous Hospital Transports 18th

Human Emergency Detection During Autonomous Hospital Transpo...

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18th International Conference on Intelligent Autonomous systems (IAS)

作者： Zachariae, Andreas Widera, Julia Plahl, Frederik Hein, Bjoern Wurll, Christian Karlsruhe Univ Appl Sci Karlsruhe Germany

ISBN: (纸本)9783031449802;9783031449819

Human transports in hospitals are labor-intensive and primarily performed in beds to save time. This transfer method does not promote the mobility or autonomy of the patient. To relieve the caregivers from this time-consuming task, a mobile robot is developed to autonomously transport humans around the hospital. It provides different transfer modes including walking and sitting in a wheelchair. The problem that this paper focuses on is to detect emergencies and ensure the well-being of the patient during the transport. For this purpose, the patient is tracked and monitored with a camera system. OpenPose is used for Human Pose Estimation and a trained classifier for emergency detection. We collected and published a dataset of 18,000 images in lab and hospital environments. It differs from related work because we have a moving robot with different transfer modes in a highly dynamic environment with multiple people in the scene using only RGB-D data. To improve the critical recall metric, we apply threshold moving and a time delay. We compare different models with an AutoML approach. This paper shows that emergencies while walking are best detected by a SVM with a recall of 95.8 % on single frames. In the case of sitting transport, the best model achieves a recall of 62.2 %. The contribution is to establish a baseline on this new dataset and to provide a proof of concept for the human emergency detection in this use case.

关键词： Autonomous hospital transport Fall detection Human pose estimation Dataset

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On the Quick and Dirty Learning Factory Within the Industry: A Dual Case Study 14th

On the Quick and Dirty Learning Factory Within the Industry:...

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14th International Conference on Learning Factories (CLF)

作者： Christiansen, Lasse Frendrup, Jonas Petrusch, Natalie Univ Coll Northern Denmark DK-9200 Aalborg SV Denmark Aalborg Univ DK-9220 Aalborg E Denmark Frauenhofer XX D-10587 Berlin Germany

ISBN: (纸本)9783031653995;9783031654008

Industrial upskilling and further education through learning factory activities is a promising path toward the transfer of knowledge from institutions to industry. However, large, complex, and stationary learning factory setups situated at institutions can be far from the contexts of the industrial workers who need upskilling. To meet this need, industrial learners could benefit from more adaptable, mobile, simple, and quick learning factories. Through a dual case study, this article investigates a) how such learning factories can operate, and b) how they can be developed. This article presents five recommendations for educators on how to apply learning factory principles within further education and upskilling to industrial employees. Furthermore, the two cases demonstrate how a simple, contextual learning factory activity can enhance the outcome of such activities. These results can pave the way for learning factories within the industry to provide further benefits.

关键词： Upskilling further education lifelong learning didactics

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How to Help Teaching in a Virtual Environment 1

引用

11st World Conference on Information systems and Technologies (WorldCIST)

作者： Marques, Bertil P. Cardoso, Marilio Reis, Rosa M. GILT ISEP IPP Porto Portugal SIIS ISEP IPP Porto Portugal

ISBN: (数字)9783031456459

ISBN: (纸本)9783031456442;9783031456459

COVID-19 required rapid change in teaching, using virtual environments, as well as at the entire educational level. At the time, teachers were unfamiliar with virtual teaching environments and needed to learn quickly and effectively how these environments worked and how they could be used in courses successfully, regardless of scope. The tips that are presented, provide an insight into the practice of teaching in virtual environments, from the design of courses, through the involvement of students, to evaluation practices, also considering the maximization of the potential that technology can provide both the teacher and students. In addition, these tips present virtual pedagogical practices for all levels of experience.

关键词： Education virtual learning online reviews faculty development cognitive load theory COVID-19

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Real-Time Torque Estimation Using Human and Sensor Data Fusion for Exoskeleton Assistance 6th

Real-Time Torque Estimation Using Human and Sensor Data Fusi...

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6th Iberian Robotics Conference (Robot)

作者： Moreira, Luis Barbosa, Roberto M. Figueiredo, Joana Fonseca, Pedro Vilas-Boas, Joao P. Santos, Cristina P. Univ Minho Ctr MicroElectroMechan Syst CMEMS Braga Portugal Univ Minho LABBELS Associat Lab Braga Portugal Univ Porto Porto Biomechan Lab LABIOMEP Porto Portugal Univ Porto Fac Sport CIFI2D Porto Portugal

ISBN: (纸本)9783031591662;9783031591679

Robotic assistive devices have emerged as a potential complement for repetitive and user-centered gait rehabilitation. In this field, the development of electromyography (EMG)-based torque controls has played a crucial role in improving the user experience with robotic assistive devices. However, most existing approaches for EMG-based joint torque estimation (i) are designed for upper limbs;(ii) often do not consider the complexity of the walking motion, focusing only on the stance phase;and (iii) rely on complex mathematical models that result in time-consuming estimations. This study aims to address these shortcomings by evaluating the generalization ability of a Deep Learning regressor (Convolutional Neural Network (CNN)) for estimating ankle torque trajectories, in real-time. Several inputs were incorporated, namely, EMG signals from Tibialis Anterior and Gastrocnemius Lateralis, hip kinematic data in the sagittal plane (angle, angular velocity, angular acceleration), walking speed (from 1.5 to 2.0 km/h), user's demographic (gender and age) and anthropometric information (height and mass, ranging from 1.50 to 1.90 m and 50.0 to 90.0 kg, respectively, and shank and foot lengths). Results showed that a CNN model with two convolutional layers showed the highest generalization ability (Root Mean Square Error: 23.4 +/- 8.36, Normalized Mean Square Error: 0.494 +/- 0.299, and Spearman Correlation 0.754 +/- 0.105). CNN model's time-effectiveness was tested in an active ankle orthosis, being able to estimate ankle joint torques in less than 2 ms. This study contributes to a more time-effective model for real-time EMG-based torque estimation, enabling a promising advancement in EMG-based torque control for lower limb robotic assistive devices.

关键词： Deep Learning Electromyography Human-Robot Interaction

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Solving the Relational Data Access Problem with Data Access Services 12th

Solving the Relational Data Access Problem with Data Access ...

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12th World Conference on Information systems and Technologies (WorldCIST)

作者： Wang, Ken BackLogic LLC Chino Hills CA 91709 USA

ISBN: (纸本)9783031602269;9783031602276

The object-relational impedance mismatch problem consists of two sub-issues: language impedance and data structure mismatch. Solution to the first issue is to abstract away the programming language from SQL;to the second issue is to abstract away the object-relational transformation from developer. This paper presents three standardized data access services, query, command and repository, collectively as a preferable solution to relational data access. These services are specified declaratively with SQL and JSON. The hard object-relational transformation is delegated to service engine. This paper also presents a reference implementation of the service engine for service execution. The complexity test proves that this reference service engine is capable of handling highly complex objects up to the 5x5 level on the complexity scale developed in this research.

关键词： object relational database data access persistence

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A Collaborative Coding Platform for Both College Students and Teachers 8th

A Collaborative Coding Platform for Both College Students an...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Hingve, Himani Tembhare, Aakash Gawande, Kartiki Mandal, Aadarsh Pawar, Ritu Dorlikar GH Raisoni Coll Engn Dept Informat Technol Nagpur 440016 India

ISBN: (纸本)9789819713288;9789819713295

In the rapidly evolving field of computer science education, there is an increasing demand for a comprehensive coding platform that caters to the needs of both college students and educators Although the educational setting is vital in exposing students to computer programming, current coding practices are frequently unsatisfactory because evaluating proposed solutions takes a lot of time. The aim of this research paper is to develop an integrated web-based coding platform called "CodeConnect". This platform offers a flexible ecosystem for coding practice, assessment, and collaborative learning, with the goal of empowering educators and learners alike. It acts as a database of programming problems, providing opportunities for training, practice, and tracking of progress. Our web application aims to create a supportive community that promotes collaboration, skill development, and a passion for coding by bridging the gap between students and educators.

关键词： Code editor Web application Coding practice Collaborative platform Computer programming

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An Intrinsic Framework of Information Retrieval Evaluation Measures

An Intrinsic Framework of Information Retrieval Evaluation M...

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Intelligent systems Conference (IntelliSys)

作者： Giner, Fernando ETSI Informat UNED Juan del Rosal 16 Madrid 28040 Spain

ISBN: (纸本)9783031477201;9783031477218

Information retrieval (IR) evaluation measures are cornerstones for determining the suitability and task performance efficiency of retrieval systems. Their metric and scale properties enable to compare one system against another to establish differences or similarities. Based on the representational theory of measurement, this paper determines these properties by exploiting the information contained in a retrieval measure itself. It establishes the intrinsic framework of a retrieval measure, which is the common scenario when the domain set is not explicitly specified. A method to determine the metric and scale properties of any retrieval measure is provided, requiring knowledge of only some of its attained values. The method establishes three main categories of retrieval measures according to their intrinsic properties. Some common user-oriented and system-oriented evaluation measures are classified according to the presented taxonomy.

关键词： Information retrieval Evaluation Metric Scale

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