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Proceedings of the 23rd Koli Calling International Conference on computing Education Research

作者： Mark Guzdial August Evrard Computer Science & Engineering University of Michigan USA Program in Computing for the Arts and Sciences University of Michigan USA

ISBN: (纸本)9798400716539

As a field, computing’s deepest roots lie in liberal arts domains such as philosophy and linguistics. As new technologies rapidly expanded the field, the computer science curricula emerged. The current undergraduate areas of study, including computer science and software engineering, focus on preparing students for careers in the computing industry or academia. The “born digital” students of a modern liberal arts institution need a different, less technology-heavy, form of computing education to support their careers as future scientists, artists, or humanists. At our large, research-focused, US university, the College of Literature, Science, and the Arts (LSA) charged a task force with defining the computing education needs for their students, chaired by the authors. We describe our process, findings and outcomes here with the aim of offering a reference template to faculty at universities that have experienced a similar growth to prominence of computer science in the undergraduate curriculum. The task force identified emergent themes of discovery, expression, and justice that we using to establish a new program, the program for computing in the Arts and Sciences (PCAS). Our themes and process may help other liberal arts and sciences programs organize the computing education needs in support of all their undergraduate students.

关键词： CS for All computational literacy computational science computational thinking critical computing liberal arts and sciences

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Families of Multidimensional Periodic Arrays with Optimal Low Cross-Correlation 1st

Families of Multidimensional Periodic Arrays with Optimal Lo...

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1st International Symposium on Intelligent computing and Networking, ISICN 2024

作者： Bolaños, César Bollman, Dorothy Doctoral Program in Computing and Information Sciences and Engineering University of Puerto Rico at Mayagüez Mayagüez00680 Puerto Rico Department of Mathematical Sciences University of Puerto Rico at Mayagüez Mayagüez00680 Puerto Rico

ISBN: (纸本)9783031674464

We construct new families of multidimensional periodic arrays that can be used for digital watermarking videos and images. Each member of each family is composed of columns of cyclic shifts of a Sidelnikov sequence in which the shifts are given by a multidimensional m1×m2×…×mn "grid" that is determined by applying a logarithmic quadratic map to the elements of a direct product Zm1×Zm2×…×Zmn. These arrays have peak auto-correlation on the order of p2l and non-peak auto- and cross-correlation on the order of pl, where l≥2 and m1m2…mn=pl-1, thereby improving the peak auto-correlation to nonpeak auto- and cross-correlations of other known constructions. Additionally, we show that the low cross-correlation values are optimal with respect to the Welch bound. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Watermarking

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Scaffolding Process-Aware Information Systems with the AKIP Platform 1

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18th International Conference on Web Information Systems and Technologies, WEBIST 2022

作者： Telemaco Neto, Ulisses Oliveira, Toacy Pillat, Raquel Alencar, Paulo Cowan, Don Melo, Glaucia David R. Cheriton School of Computer Science University of Waterloo Waterloo Canada System Engineering and Computing Program Federal University of Rio de Janeiro Rio de Janeiro Brazil

ISBN: (数字)9783031430886

ISBN: (纸本)9783031430879

Business Process Automation (BPA) refers to the automation of business processes through technology, with the goal of improving efficiency, reducing errors, and increasing productivity by eliminating manual and repetitive tasks. Over the past few years, the number of BPA platforms has increased, including both open-source and proprietary solutions. However, some challenges and limitations still exist related to the adoption of these solutions, such as vendor lock-in, limited UI/UX, limited integration, outdated technology stack, and lack of support for non-process features. To address these issues, this paper presents the AKIP platform, an open-source framework for developing process-aware information systems (PAISs) using code generation techniques. AKIP generates functional process-aware web applications from BPMN business process models, making it the only known software tool capable of generating fully functional process-aware web applications. To evaluate the effectiveness of the AKIP platform, a case study was conducted in the industry and six business processes automated into a process-oriented web application were analyzed in this paper. The study showed that the AKIP platform was able to generate a functional web application while supporting the automation of business processes with different model sizes and complexities. Furthermore, this study showed that even a team of professionals with little experience was able to produce such results by using the AKIP platform. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Automation

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A Novel Approach for Commercial Opportunities Qualification Using the BANT Methodology under the Fuzzy Set Theory Framework. 28th

A Novel Approach for Commercial Opportunities Qualification ...

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28th International Conference on Knowledge Based and Intelligent information and engineering Systems, KES 2024

作者： Leite, Marcus Vinicius Abe, Jair Minoro Hoffmann Souza, Marcos Leandro Graduate Program in Production Engineering-Paulista University-UNIP Rua Dr. Bacelar 1212 São Paulo-SP04026002 Brazil Graduate Program in Applied Computing-Vale do Rio dos Sinos University-UNISINOS Av. Unisinos 950 - São LeopoldoRS-93022-000 Brazil

Demand generation is crucial for organizations, supplying sales teams with well-qualified commercial opportunities. Despite the wide variety of existing opportunity qualification methodologies, the subjective nature of experts' final evaluation remains an obstacle to efficiency and productivity in the business process. This research investigated how Fuzzy Set Theory and Fuzzy Logic could be applied to the BANT methodology for qualifying commercial opportunities, aiming to replace these deliberative evaluations by experts to increase the sales cycle performance. A fuzzy inference system was developed to emulate the assessments of the experts. The analysis of the ratings obtained after processing a sample of commercial opportunities from 2022 and 2023 confirmed the system's effectiveness in aligning with expert perceptions. While the study indicated room for refinements in the model, the findings underscore the potential to streamline the qualification of opportunities and improve sales cycle performance. © 2024 The Authors.

关键词： Fuzzy set theory

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AI Recommendations: Friend or Foe? Unraveling the Impact on Consumer Benefits and Privacy 11

AI Recommendations: Friend or Foe? Unraveling the Impact on ...

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11th International Conference on ICT for Smart Society, ICISS 2024

作者： Dewanthi, Desyra Sukma Kristopo, Hari Qomariyah, Nunung Nurul Axel, Muhammad Business Management & Marketing Program Binus Business School International Undergraduate Program Bina Nusantara University Management Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Food Technology Department Jakarta11480 Indonesia School of Computing and Creative Arts Bina Nusantara University Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350389654

Artificial Intelligence (AI) and marketing have transformed consumer behavior and shopping experiences, especially through Recommender Systems (RSs) in e-commerce. RSs use algorithms to provide personalized recommendations, enhancing shopping convenience. However, this raises data privacy and ethical concerns, as RSs rely on user data. This research explores the quality determinants of RSs and their impact on consumer behavior, focusing on privacy awareness and its effect on repurchase intentions. Using a qualitative approach with semi-structured interviews, the study targets Indonesian respondents aged 18-40 with e-commerce experience. Findings reveal that recommendation quality, especially self-reference and vividness, significantly influences purchasing decisions. Respondents prefer recommendations that match their preferences and are visually appealing. Positive shopping experiences are linked to efficient and accurate RSs, but there's a need for improvements in transparency, novelty, diversity, and advanced technologies like AR. Respondents are aware of digital data storage but have limited understanding of privacy concerns. They trust e-commerce platforms with basic personal details but are hesitant to share sensitive information. Despite privacy issues, e-commerce remains vital, with respondents emphasizing the need for transparency, robust security, and clear explanations for data use to maintain trust. Addressing these issues not only enhances customer experience but also demonstrates that consumer trust directly impacts the sustainability and success of the business. © 2024 IEEE.

关键词： Differential privacy

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A Hybrid Learning Approach for Automatic Data Labelling and Anomaly Detection in IoT Networks 3

A Hybrid Learning Approach for Automatic Data Labelling and ...

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3rd IEEE International Conference on Artificial Intelligence, ICAI 2023

作者： Kanwal, Rimsha Noor, Umara Rashid, Zahid International Islamic University Faculty of Computing and Information Technology Department of Computer Science Islamabad Pakistan College of Engineering Technology Management Economics and Policy Program Seoul National University Seoul Korea Republic of

ISBN: (纸本)9798350322125

Internet of Things (IoT) is an environment in which digital equipment is augmented with sensors to share and receive data through network. When devices share data it can be effected by anomalies or any attack due to corrupted data or by any other uncertainty and ambiguity in data. The data can also be corrupted through a damage in device. These attacks or anomalies damage the working of the IoT networks. The anomalous data can be detected through detection techniques however most anomaly detection techniques depend upon labelled data but for IoT datasets, usually class labels are not available. Labeling is performed by a manual process which is time consuming and also costly. As data in IoT increases day by day so there is a need to label and classify data for future unseen data. In this paper a hybrid algorithm is proposed in which both clustering and classification techniques are applied for automatic labeling and classifying on IoT dataset. The model contains two function. In the first phase k-means clustering is employed for labelling dataset instances as normal or anomalous. In the second phase labelled dataset is used to train Random Forest model to detect anomalies in IoT networks. The results show that the proposed model is detecting anomalies in IoT networks with an accuracy 98%, precision 98 %, recall 98%, and F-meausre 0.98%. © 2023 IEEE.

关键词： Classification (of information)

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Propranolol hydrochloride degradation using La@TiO_(2) functionalized with CMCD

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Journal of Rare Earths 2022年第4期40卷 579-585,I0003页

作者： Gustavo Lopes Colpani Vitor Follmann Santos Rubieli Carla Frezza Zeferino Micheli Zanetti Josiane Maria Muneron de Mello Luciano Luiz Silva Natan Padoin Regina de Fatima Peralta Muniz Moreira Márcio Antônio Fiori Cíntia Soaresc Post-Graduate Program in Technology and Innovation Management Community University of ChapecóRegionChapecó89809-900Brazil Department of Chemical Engineering Community University of ChapecóRegionChapecó89809-900Brazil Laboratory of Materials and Scientific Computing(LabMAC) Department of Chemical and Food EngineeringFederal University of Santa CatarinaFlorianópolis88040-900Brazil

Propranolol hydrochloride can be considered a persistent and bioaccumulative pharmaceutical in the *** drug and its by-products are potentially toxic and have adverse effects,since these compounds have been associated with endocrine-disrupting effects,reproductive deficiencies,embryo abnormalities and pericardial ***_(2)–La 0.05%–carboxymethyl-β-cyclodextrin(CMCD)nanoparticles were successfully prepared by a simple two-step method,which consists of sonification and *** characterization analyses reveal that lanthanum is dispersed on the semiconductor surface,probably forming Ti–O–La bonds,which can induce oxygen vacancies and surface defects that effectively restrain the recombination of photogenerated electron/holes *** efficiency of TiO_(2)–La 0.05%–CMCD samples in degradation of propranolol under UV-light irradiation is higher than that of pristine TiO_(2) within 20 min reaction,probably due to complex formation between theβ-blocker and the oligosaccharide,which allows us to propose a photocatalytic mechanism based on the formation of intermediates and competition of these compounds to the radicals and CMCD cavities.

关键词： TiO_(2) Lanthanum CMCD Propranolol Photocatalysis Functionalization

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Predicting Microsatellite Instability from Histology Images with Dilated Neighborhood Attention Transformer in Colorectal Cancer 24

Predicting Microsatellite Instability from Histology Images ...

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24th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2024

作者： Chen, Yun-Chi Chao, Tung Phandita, Wimaya Nitya Sun, Tzu-Yu Wang, Huai-Zhi Hsieh, Yi-Hsien Hsu, Le-Yin Lin, Che Taipei Taiwan College of Bioresources and Agriculture NTU Taipei Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei Taiwan Graduate Institute of Communication Engineering NTU Taipei Taiwan NTU Data Science Degree Program Taipei Taiwan NTU Department of Electrical Engineering Taipei Taiwan Center for Advanced Computing and Imaging in Biomedicine NTU Taipei Taiwan NTU Smart Medicine and Health Informatics Program Taipei Taiwan

ISBN: (纸本)9798331518622

Microsatellite instability (MSI) is a pivotal genetic marker influencing the efficacy of immunotherapy in colorectal cancer. Traditional MSI examination often requires additional genetic or immunohistochemical tests, whereas histology images, widely available in colorectal cancer diagnosis, offer a valuable alternative for MSI prediction. Although Transformer-based models have demonstrated promising outcomes in predicting MSI from histology images, they are hampered by traditional local attention mechanisms that struggle to capture long-range interdependencies and establish a comprehensive global receptive field. In this study, we introduce DiNAT-MSI, a novel framework for histology-based MSI prediction that incorporates the Dilated Neighborhood Attention Transformer (DiNAT). This model enhances global context recognition and substantially expands receptive fields, all without additional computational burden. Our results demonstrate that DiNAT-MSI achieves a superior patientwise AUROC compared to ResNet18 and Swin Transformer, along with commendable explainability. Our work not only illustrates a more accessible diagnostic tool for leveraging histological data but also underscores the potential of Transformerbased models with sophisticated attention designs in advancing precision medicine for colorectal cancer patients. © 2024 IEEE.

关键词： Diseases

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CIMulator: Evaluating Neuromorphic Accelerators with HZO FefinFET-Based Synaptic Device 7

CIMulator: Evaluating Neuromorphic Accelerators with HZO Fef...

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7th International Conference on Green Technology and Sustainable Development, GTSD 2024

作者： Le, Hoang-Hiep Lu, Hao-Yu Baig, Md. Aftab De, Sourav Lin, Ing-Chao Lu, Darsen D. Minghsin University of Science and Technology Department of Computer Science and Information Engineering Hsinchu Taiwan National ChengKung University Intelligent Computing Industrial Doctorate Program Tainan Taiwan Institute of Microelectronics National ChengKung University Tainan Taiwan National ChengKung University Department of Computer Science and Information Engineering Tainan Taiwan

ISBN: (纸本)9798350386073

In this study, we use the CIMulator platform to evaluate the performance of neuromorphic accelerators with novel Hf0.5Zr0.5O2 (HZO) ferroelectric fin field-effect transistor (FefinFET) as synaptic device. The MNIST handwritten digit dataset is used for training and inference processes in multilayer perceptron (MLP) neural networks. With the highly optimized synaptic device, the results demonstrate high training and inference accuracy, achieving up to 97% for the MLP, approaching the accuracy of software implementations. © 2024 IEEE.

关键词： Multilayer neural networks

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Towards Trustworthy Aircraft Safety: Explainable AI for Accurate Incident and Accident Predictions 20th

Towards Trustworthy Aircraft Safety: Explainable AI for Accu...

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20th International Conference on the Economics of Grids, Clouds, Systems, and Services, GECON 2024

作者： Amin, Maryam Noor, Umara Fatima, Manahil Rashid, Zahid Altmann, Jörn Department of Software Engineering Faculty of Computing and Information Technology International Islamic University Islamabad44000 Pakistan Technology Management Economics and Policy Program College of Engineering Seoul National University Seoul Korea Republic of College of Engineering Seoul National University Seoul Korea Republic of Integrated Major in Smart City Global Convergence Seoul National University Seoul Korea Republic of

ISBN: (纸本)9783031812255

Despite technological advancements, ensuring aircraft safety remains a challenge, however, Machine learning (ML)-based approaches for predicting future incidents play a crucial role in addressing flight safety. As ML models increase in complexity, their decision-making process becomes less transparent, posing significant challenges to trustworthiness. While simpler models demonstrate lower accuracy, more intricate models such as deep neural networks achieve higher accuracy but sacrifice interpretability. In this study, we enhance trustworthiness in aircraft safety prediction by leveraging a dataset of past accidents and incidents to prevent similar accidents from occurring in the future. To achieve this, we apply Random Forest and Extreme Gradient Boosting models to classify different categories of aircraft incidents. Additionally, we apply two powerful explainable artificial intelligence (XAI) techniques: Local Interpretable Model-Agnostic Explanations (LIME) and Shapley Additive exPlanations (SHAP) to provide insights into both local and global predictions made by the models. Notably, our results reveal high accuracy in these predictions while maintaining trustworthiness. This research contributes to the advancement of XAI and offers valuable insights for safety-critical applications and decision support systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Aircraft accidents

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