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Zirkus Empathico 2.0: a multiplayer serious mobile game for children with autism spectrum disorder (ASD), with a focus on enhancing social and emotional development

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Multimedia Tools and Applications 2025年 1-24页

作者： Hassan, Ahmed Pinkwart, Niels Shafi, Muhammad Department of Computer Science and Informatics Berlin School of Business and Innovation Karl Marx Strasse 97 - 99 Berlin12043 Germany Institute for Informatic Humboldt University Berlin Rudower Chaussee 25 Berlin Berlin12489 Germany School of Computing Ulster University Belfast Campus United Kingdom Faculty of Computing & Information Technology Sohar University Sohar Oman

This study explores the effectiveness of the multiplayer serious mobile game "Zirkus Empathico (ZE) 2.0" in enhancing social-emotional behaviors in children diagnosed with autism spectrum disorder (ASD). It aims to assess how such games can foster emotional recognition, empathy, and prosocial behavior, thereby supporting the holistic development of children with ASD. An eight-week randomized controlled trial (RCT) was conducted between January and April 2021 at autism centers in Islamabad, Pakistan, and Berlin, Germany. The study involved 107 children aged 5–11 years, with 60 diagnosed with ASD and 47 typically developing children serving as an Active Control Group (ACG). Participants were engaged in sessions using the bilingual"ZE 2.0"game, incorporating multiplayer and emotional learning modules. The intervention required 120 min of weekly training supplemented by daily sessions. Post-intervention assessments demonstrated significant improvements in the ASD group compared to the control group in areas of empathy and emotional awareness, as evidenced by higher scores on the Griffith Empathy Measure (GEM) and multiplayer module evaluations. Notable was the ability of participants to apply learned social skills in dynamic, real-world contexts, which suggests the game’s effectiveness transcends the controlled settings typically associated with ASD interventions. ZE 2.0 adds to the social and teamwork competencies of children with ASD. Besides encouraging peers to be proactive in communications and cooperation, the multiplayer mode provides an immersion learning atmosphere for facilitating social and emotional development. Such an outcome underlines the perspectives of serious games for use as a framework for the treatment and education of children who have ASD. In this manner, serious games can be utilized as a supplementary or alternative means of treating ASD. Future research may focus on distinguishing the effects of intervention from those of other therapy modalit

关键词： Serious games

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Hybrid Feature Extractions and CNN for Enhanced Periocular Identification During Covid-19

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Computer Systems Science & Engineering 2022年第4期41卷 305-320页

作者： Raniyah Wazirali Rami Ahmed College of Computing and Informatics Saudi Electronic UniversityRiyadh11673Saudi Arabia The School of Information Technology Sebha UniversitySebha71Libya

The global pandemic of novel coronavirus that started in 2019 has ser-iously affected daily lives and placed everyone in a panic *** coronavirus led to the adoption of social distancing and people avoiding unneces-sary physical contact with each *** present situation advocates the require-ment of a contactless biometric system that could be used in future authentication systems which makesﬁngerprint-based person identiﬁcation ***-lar biometric is the solution because it does not require physical contact and is able to identify people wearing face ***,the periocular biometric region is a small area,and extraction of the required feature is the point of *** paper has proposed adopted multiple features and emphasis on the periocular *** the proposed approach,combination of local binary pattern(LBP),color histogram and features in frequency domain have been used with deep learning algorithms for classiﬁ***,we extract three types of fea-tures for the classiﬁcation of periocular regions for *** LBP represents the textual features of the iris while the color histogram represents the frequencies of pixel values in the RGB *** order to extract the frequency domain fea-tures,the wavelet transformation is *** learning from these features,a convolutional neural network(CNN)becomes able to discriminate the features and can provide better recognition *** proposed approach achieved the highest accuracy rates with the lowest false person identiﬁcation.

关键词： Person identiﬁcation convolutional neural network local binary pattern periocular region Covid-19

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A Brief Survey on Data Aggregation and Data Compression Models using Blockchain Model in Wireless Sensor Network

A Brief Survey on Data Aggregation and Data Compression Mode...

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2023 IEEE International Conference on Innovative Data Communication Technologies and Application, ICIDCA 2023

作者： Sudheer, Bandlamudi Naga Sujatha, Kamepalli School of Computing and Informatics Vignan's Foundation for Science Technology & Research Guntur Andhra Pradesh Vadlamudi India

ISBN: (纸本)9798350397208

Most of the time, nodes in Wireless Sensor Networks (WSNs) are set up in an unmonitored, potentially dangerous setting. Battery life, storage space, processing power, and network connectivity are all severely lacking in these nodes. Therefore, it is difficult to protect a WSN without negatively impacting the efficiency of the network. The issues listed above can be effectively addressed with a well-designed plan that makes use of Data Aggregation (DA) in conjunction with a robust security system In this work, we provide a thorough analysis of Secure Data Aggregation (SDA) in WSNs, highlighting both the security benefits sought and the challenges currently faced by this approach. Both established and up-and-coming network topologies are covered, with comparisons drawn between them to highlight key differences in application landscapes and security provisions afforded by each. Compressive data gathering (CDG), which employs Compressive Sensing (CS), can significantly enhance energy effieiency with the advantages gained from data compression. The data collection performance and longevity of Internet of Things (IoT) based WSNs are found to be significantly improved by CS based data collecting techniques. However, in hostile and sophisticated network deployments, they encounter significant difficulties with key distribution and adversary attacks. This research explores how wireless sensor networks' security measures affect their ability to collect and analyze data. This research provides a brief survey on data aggregation and data compression using blockchain in WSN for secure data transmission. © 2023 IEEE.

关键词： Compressed sensing

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Hybrid Approaches to Emotion Recognition: A Comprehensive Survey of Audio-Textual Methods and Their Application 4

Hybrid Approaches to Emotion Recognition: A Comprehensive Su...

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4th International Conference on Advanced Research in computing, ICARC 2024

作者： Wewelwala, Sahan Hewage Sumanathilaka, T.G.D.K. School of Computing Informatics Institute of Technology 06 Colombo Sri Lanka Swansea University Department of Computer Science Wales Swansea United Kingdom

ISBN: (纸本)9798350384864

This survey study provides a comprehensive analysis of emotion recognition, documenting its progression from conventional techniques to innovative hybrid algorithms that effectively combine textual and audio information. This work distinguishes itself with its thorough examination of the innovative combination of deep learning-based textual sentiment analysis and sophisticated aural signal processing approaches. This unique combination greatly improves the precision of emotion recognition from intricate sources like social media and consumer feedback. The study addresses the difficulties of processing real-time data and reducing bias in varied datasets. It provides new perspectives on the powers and limitations of neural networks and machine learning in this specific scenario. Our research represents a notable advancement in the utilization of these technologies for human-computer interaction, facilitating the creation of digital interfaces that are more empathic and attuned to human emotions. The final statements underscore the pressing requirement for sophisticated multimodal methodologies and the incorporation of developing technology, underscoring our distinctive contribution to the progress of emotion identification systems. This report offers a thorough analysis of the present condition of the subject and outlines a direction for future advancements, highlighting the crucial significance of emotion identification in improving human-computer interaction. © 2024 IEEE.

关键词： Emotion Recognition

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Swa Bhasha 2.0: Addressing Ambiguities in Romanized Sinhala to Native Sinhala Transliteration Using Neural Machine Translation 4

Swa Bhasha 2.0: Addressing Ambiguities in Romanized Sinhala ...

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4th International Conference on Advanced Research in computing, ICARC 2024

作者： Dharmasiri, Sachithya Sumanathilaka, T.G.D.K. School of Computing Informatics Institute of Technology Colombo06 Sri Lanka Swansea University Department of Computer Science Wales Swansea United Kingdom

ISBN: (纸本)9798350384864

With the growing popularity of social media and instantaneous messaging, it is more important than ever to interact online in your native language. In Sinhala, both Romanized and native Sinhala are widely used. Due to the informal textual abbreviation known as 'Singlish' however, attempts to translate Romanized Sinhala into native Sinhala via machine transliteration may result in errors. Rule-based transliteration systems may not be compatible with the ad hoc transliterations used in Singlish. To translate Romanized Sinhala back precisely and consistently into Native Sinhala, a novel NMT approach has been proposed. To address the complexities of casual Romanized Sinhala, a hybrid strategy combining rule-based and neural machine translation has been proposed. This strategy aims to eliminate word selection ambiguity by selecting the best word suggestions from a pool of predicted words using a suggestion algorithm. Combining the advantages of Suggestion algorithms and neural machine translation, the proposed transliterator has the potential to considerably enhance reverse transliteration and improve communication in native Sinhala by combining the strengths of both approaches. After completing the GRU model, the performance of the machine translation models on the BLEU test improved to 0.8, indicating high word-level translation accuracy. Significant potential exists for the proposed transliterator to enhance reverse transliteration and improve communication in Sinhala. While preliminary test results are promising, additional testing and refinement are required to improve the overall efficacy of machine translation models. © 2024 IEEE.

关键词： Neural machine translation

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Blockchain-Based Key State Management for IoT Devices in Post-Quantum Era

Blockchain-Based Key State Management for IoT Devices in Pos...

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2024 IEEE International Conference on Consumer Electronics-Asia, ICCE-Asia 2024

作者： Kok Seng, Vincent Lew Wan, Au Thien Shah Newaz, S.H. Tsuchiya, Tatsuhiro School of Computing and Informatics Universiti Teknologi Brunei GadongBE1410 Brunei Graduate School of Information Science and Technology Osaka University Osaka565-0871 Japan

ISBN: (纸本)9798331530839

Blockchain has been paving the way for new business opportunities as we have witnessed over the last few years. It will continue to proliferate further and be adopted in increasingly diverse sectors. One area of research in Blockchain is how it can be used in Internet of Things (IoT) based applications like Unmanned Aerial Vehicles (UAV), Smart cities and Healthcare. However, with the advent of quantum technology, some widely used security algorithms in blockchain are vulnerable (i.e., quantum algorithms can exponentially solve cryptographic algorithms used to digitally sign or encrypt data), thereby diminishing communication security. Thus, post-quantum algorithms are at the forefront of research to secure data before quantum technologies can fully mature. Early standardized post-quantum algorithms such as hash-based one-time signatures, relies on the proven one-way-ness of hashing algorithm. Hash-based one-time signatures require robust secret key management systems to prevent security degradation. To safeguard IoT applications from quantum threats, this paper proposes a solution which utilizes both hash-based one-time signatures and blockchain to cover each technology's weaknesses. © 2024 IEEE.

关键词： Quantum cryptography

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Exploring Computational Linguistics Techniques for Enhanced Outing Planning: A Comprehensive Review 4

Exploring Computational Linguistics Techniques for Enhanced ...

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4th International Conference on Advanced Research in computing, ICARC 2024

作者： Muthaliff, Faizan Sumanathilaka, T.G.D.K. School of Computing Informatics Institute of Technology Colombo06 Sri Lanka Swansea University Department of Computer Science Wales Swansea United Kingdom

ISBN: (纸本)9798350384864

In this day and age where convenience is king a new competitor in the form of chat-bots has appeared which requires users to only have prior knowledge on the language the chat-bot converses in. When it comes to planning outings there are a multitude of criteria to be wary of to determine the ideal solution. This review paper will address the common issues with extracting meaningful information from the user utilizing modern NLP techniques, the required criteria in addition to the user input such as, real time weather information and communicable diseases pertaining to the outing location, to determine an ideal suggestion and finally the method in which said ideal suggestion is determined after prioritizing criteria. The conclusion underscores that while NLP applications might not entirely replace existing menu-based systems for outing planning, they excel in certain scenarios. Notably, NLP's innate capacity to comprehend user preferences and context allows it to offer tailored outing suggestions. Furthermore, the application's unique feature of dynamically adapting to user requests without necessitating a return to the home page adds a distinctive advantage to its usability. © 2024 IEEE.

关键词： Natural language processing systems

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A Cross-Domain Ontology Semantic Representation Based on NCBI-BlueBERT Embedding

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Chinese Journal of Electronics 2022年第5期31卷 860-869页

作者： ZHAO Lingling WANG Junjie WANG Chunyu GUO Maozu Faculty of Computing Harbin Institute of Technology Department of Medical Informatics School of Biomedical Engineering and InformaticsNanjing Medical University Beijing Key Laboratory of Intelligent Processing for Building Big Data School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture

A common but critical task in biological ontologies data analysis is to compare the difference between ontologies. There have been numerous ontologybased semantic-similarity measures proposed in specific ontology domain, but it still remains a challenge for crossdomain ontologies comparison. An ontology contains the scientific natural language description for the corresponding biological aspect. Therefore, we develop a new method based on natural language processing(NLP) representation model bidirectional encoder representations from transformers(BERT) for cross-domain semantic representation of biological ontologies. This article uses the BERT model to represent the word-level of the ontologies as a set of vectors, facilitating the semantic analysis or comparing the biomedical entities named in an ontology or associated with ontology terms. We evaluated the ability of our method in two experiments: calculating similarities of pair-wise disease ontology and human phenotype ontology terms and predicting the pair-wise of proteins interaction. The experimental results demonstrated the comparative performance. This gives promise to the development of NLP methods in biological data analysis.

关键词： human phenotype ontology cross-domain semantic representation natural language description pair-wise disease ontology data analysis bidirectional encoder representations NLP protein interaction diseases proteins natural language processing ontologies (artificial intelligence) natural language processing representation neural nets bioinformatics semantic-similarity measures cross-domain ontology semantic representation semantic analysis NCBI-BlueBERT embedding biological ontology data analysis

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A Survey on Image Captioning Using Object Detection and NLP 4

A Survey on Image Captioning Using Object Detection and NLP

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4th International Conference on Advanced Research in computing, ICARC 2024

作者： De Silva, Vathila Sumanathilaka, T.G.D.K. School of Computing Informatics Institute of Technology 06 Colombo Sri Lanka Swansea University Department of Computer Science Wales Swansea United Kingdom

ISBN: (纸本)9798350384864

Recent years have seen the emergence of image captioning as a revolutionary technical development that seamlessly blends computer vision and natural language processing. The integration of various domains facilitates the production of captivating captions for pictures, promoting a more profound comprehension of visual material. This study offers a thorough analysis of the rapidly developing field of image captioning, examining its uses in various settings such as social media, online platforms, assistive technology, and content indexing. It emphasizes the critical importance of advanced techniques like You Only Look Once (YOLO) for accurate item detection and Natural Language Processing (NLP) for creating subtle captions. While NLP gives the resulting text a layer of contextual depth, YOLO guarantees precise object detection, which helps with caption accuracy. Using these cutting-edge methods boosts the overall efficacy of image captioning systems and represents a noteworthy trend in the literature. Examining the evolution of image captioning, the review paper highlights how important it is for multimodal comprehension. Image captioning is a transformative tool that enhances the readability of visual content and influences contemporary digital experiences in various contexts. The development of image captioning is summarized in this abstract, which also highlights the tendency to use cutting-edge techniques for more accurate and nuanced caption production. © 2024 IEEE.

关键词： Object detection

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Enhanced Employee Performance Management System with AI Driven Analytics

Enhanced Employee Performance Management System with AI Driv...

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Data Science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： W. Rividi Helanka De Silva Banuka Athuraliya School of Computing Informatics Institute of Technology Sri Lanka

ISBN: (数字)9798331537555

ISBN: (纸本)9798331537562

The Enhanced Employee Performance Management System (EPMS) that is proposed in this paper is a concept-based framework that aims to enhance the efficiency of the workforce through the application of artificial intelligence in predictive modeling. To overcome longstanding issues with employee performance, the EPMS includes new elements, for example, feedback loops and Explainable Artificial Intelligence (XAI). Using ARIMA based predictive algorithms, the system provides performance forecasts that product-oriented industries can benefit from. This unique approach delivers adaptability for improving organizational efficiency and the corporate well-being of personnel.

关键词： Industries Feedback loop Adaptation models Explainable AI Predictive models Prediction algorithms Personnel Long short term memory

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