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Trading Strategies Within a Low Interest Rates Environment 4th

Trading Strategies Within a Low Interest Rates Environment

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4th International Conference on Digital Technologies and Applications (ICDTA)

作者： Younes, Erraoui Anouar, Malki Hamid, Slimani Aderrahim, Benlakouiri Fac Sci Jurid Econ & Sociales Lab Rech ERMOT Fes Morocco Univ Hassan 2 EST Lab Rech PRISME Casablanca Morocco

ISBN: (纸本)9783031686597;9783031686603

In this work, we propose to construct a trading strategy and simulate its future payoffs in the order to study its behavior within a low-interest rate environment. Indeed, today interest rates are historically low and investors tend to take more risks for yield enhancement. Before constructing the strategy, we explain the basic option strategies of the markets, as they are the main yield enhancement components of almost all strategies. Then we expand the different aspects of structured products and, more precisely, Autocallable (AC: Auto callable) products. In the order to understand the pricing models implemented, the proposed study explains the Black-Scoles Model and the Monte Carlo pricing method. The objective of this study is to investigate the field of the trading strategies within the context of low-interest rates. A genuine AC strategy was constructed from scratch, and the results are quite intriguing. To realize that, we had to implement our AC strategy on python and analyze the results. We conclude that, while the price is attractive, the strategy is highly sensitive to the interest rate when getting low and represents many risks.

关键词： Interest rates Trading strategies Autocallable and structured product

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The Digital Investment Platform as a Means of Forming and Implementing an Investment Project of a Railway Company 9th

The Digital Investment Platform as a Means of Forming and Im...

引用

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

作者： Shevchenko, Iryna Haraev, Mikail Krysovatyy, Ihor Kurtsev, Oleksii West Ukrainian Natl Univ Dept Int Econ Ternopol Ukraine UkrSURT Educ & Sci Ctr Int Cooperat & Educ Kharkiv Ukraine West Ukrainian Natl Univ Dept Entrepreneurship & Trade Ternopol Ukraine Simon Kuznets Kharkiv Natl Univ Econ Kharkiv Ukraine

ISBN: (纸本)9789819735617;9789819735624

A digital investment platform can be a powerful tool for the formation and implementation of a railway company's investment project. It assists in efficient monitoring, management, and optimization of all aspects of the investment project. The digital platform can automatically gather and analyze large volumes of data related to various project aspects, such as financial indicators, technical data, market trends, equipment requirements, and more. The digital investment platform enables railway companies to effectively plan, implement, and control investment projects, reducing risks and ensuring better outcomes. It can be a vital tool for project management improvement and enhancing the competitiveness of railway companies. The main goal of this study is to identify the key elements of improving the formation and implementation of investment projects by utilizing the core features of the digital investment platform. The primary research methods include analysis and synthesis;induction and deduction;morphological analysis method to construct a categorical basis for research and a graphical method to visually represent the main research results. The key findings of the research are as follows: the digital platform enables railway companies to efficiently plan, implement, and manage investment projects;the digital investment platform helps optimize resource utilization and reduce unnecessary expenses, which is crucial for ensuring the efficiency of investment projects;the platform creates favorable conditions for collaboration among different project stakeholders, contributing to achieving better results;thanks to digital tools, railway companies can track project progress in real-time, review financial results, and take timely actions to achieve their goals.

关键词： Investment Digitization Information technology Digital technology Investment activity

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Action Unit Recognition: Leveraging Weak Supervision with Large Loss Rejection

Action Unit Recognition: Leveraging Weak Supervision with La...

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Computing Conference

作者： Enabor, Oseluole Vadapalli, Hima Univ Witwatersrand Sch Comp Sci & Appl Math Johannesburg South Africa Univ Johannesburg Acad Comp Sci & Software Engn Johannesburg South Africa

ISBN: (纸本)9783031622717;9783031622694;9783031622687

Acquiring high-quality annotated datasets is challenging and costly, leading to the advent of Weakly Supervised Learning (WSL) techniques. These methods enable the utilisation of existing noisy labels for model development, making them highly valuable. WSL techniques have demonstrated success across various domains, prompting exploring their applicability to facial Action Unit (AU) recognition. Different from the prevalence of image datasets, facial AU annotated datasets are scarce given that the annotation process is both time- and labour-intensive and requires the expertise of a subject matter expert. This study employs a Weakly Supervised Multi-Label (WSML) classification approach incorporating Large Loss Rejection (LLR) to train an AU recognition model utilising existing limited AU annotated datasets. The AU sample labels from the Extended Denver Intensity of Spontaneous Facial Action Database (DISFA+) were amended to reflect inaccurate labels. The LLR mechanism identified and rejected samples with substantial errors, preventing the model from learning from these erroneous labels. This step was crucial in ensuring the model's accuracy, given the prevalence of introduced inaccurate labelling into the sample data. The performance of the proposed LLR model was compared against a standard AU recognition model using exact AU labels and an AU recognition model using inexact labels (i.e., trained on emotion labels and fine-tuned for AU recognition). The AU recognition model using inaccurate labels and the LLR approach exhibited promising results with a subset accuracy of 69% and a weighted average F1-score of 0.65 for AU recognition. Furthermore, cross-dataset testing on the KDEF dataset resulted in the recognition of relevant AU annotations. These findings underscore the potential of LLR-based weak supervision in addressing the data annotation challenges encountered in facial AU recognition.

关键词： Action unit recognition Weak supervision Large loss rejection Inaccurate and inexact labelling

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Baseline Proposal of User Experience Practices in the Software Engineering Process: Global MVM Case 12th

Baseline Proposal of User Experience Practices in the Softwa...

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

作者： Gomez Munoz, Patricia Elena Gomez Alvarez, Maria Clara Gallego Burgos, Ricardo Alonso Global MVM Digital Experience Unit Medellin Colombia Univ Nacl Colombia Engn Fac Medellin Colombia

ISBN: (纸本)9783031602269;9783031602276

Software development companies must consider the satisfaction of interested parties, especially users, and within quality attributes including user experience (UX). This factor is relevant since the success or failure of the software will depend on the ease with which users can handle it and interact with it in a way that generates a positive perception, achieves acceptance and allows more significant use. Additionally, the joint participation scenarios that software companies must face due to opening processes through co-creation with clients, users, companies and other agents, increase the complexity of their environment. Thus, under this scenario, research is carried out to incorporate UX practices into the software development life cycle of the Global MVM company in a way that allows it to face current challenges, optimize and improve its portfolio of products and services and a better approach to the needs of its clients and users is achieved.

关键词： User Experience Software Development Open innovation Competitiveness

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Transforming Patient Experience in Underserved Areas with Innovative Voice-Based Healthcare Solutions 9th

Transforming Patient Experience in Underserved Areas with In...

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

作者： Xia, Minliang Huang, Bo Yan, Yan Zhang, Wenjun Lin, Wenjun Univ Saskatchewan Mech Engn Saskatoon SK Canada Univ Guelph Sch Comp Sci Geulph ON Canada Univ Saskatchewan Biomed Engn Saskatoon SK Canada Algoma Univ Sch Comp Sci & Technol Digital Healthcare Innovat Lab Brampton ON Canada

ISBN: (纸本)9789819732883;9789819732890

This study presents a novel voice-driven online appointment system aimed at improving healthcare access in rural and indigenous communities. Utilizing existing telephone infrastructure, the system transcends the limitations of traditional chatbots by leveraging Large Language Models (LLMs) and advanced voice recognition technologies like Whisper. This approach enables the transformation of conventional phone calls into a streamlined digital booking process. The system's integration with current booking processes in rural healthcare facilities and facilitates a smooth transition from voice-based to digital scheduling, providing an intuitive and efficient user experience. This innovation addresses critical healthcare accessibility challenges, notably reducing appointment booking barriers and enhancing the overall patient experience. The implementation of this technology in underserved areas demonstrates a significant advancement in patient-centered care, highlighting the role of LLMs in harmonizing traditional and digital healthcare practices. The paper provides a comprehensive overview of the system's development, explores the challenges that may encounter, and discusses the significant potential of this approach in shaping future healthcare technologies and influencing policy decisions in healthcare accessibility.

关键词： Healthcare accessibility Rural and indigenous communities Voice-driven technology Large language models Digital healthcare innovation Online appointment system Patient-centered care Telecommunications in healthcare Digital booking systems

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Pix2Pix Hyperparameter Optimisation Towards Ideal Universal Image Quality Index Score

Pix2Pix Hyperparameter Optimisation Towards Ideal Universal ...

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Intelligent systems Conference (IntelliSys)

作者： Hoelscher, Dirk Reich, Christoph Knahl, Martin Gut, Frank Clarke, Nathan Furtwangen Univ Inst Data Sci Cloud Comp & IT Secur D-78120 Furtwangen Germany Plymouth Univ Ctr Cyber Secur Communicat & Network Res Plymouth Devon England

ISBN: (纸本)9783031477201;9783031477218

Generative models and their possible applications are almost limitless. But there are still problems that such models have. On one hand, the models are difficult to train. Stability in training, mode collapse or non convergence, together with the huge parameter space make it extremely costly and difficult to train and optimize generative models. The following paper proposes an optimization method limited to a few hyperparameters with grid-search and early stopping which selects the best hyperparameter combination based on the results obtained with the Universal Image Quality Index (UIQ) by creating a copy of the source image and comparing it with the generated target. The proposed method allows to directly measure the impact of hyperparameter tuning by comparing the achieved UIQ score against a baseline.

关键词： Hyperparameter tuning Generative models Pix2Pix Universal image quality index Quality assessment

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Ga-starfish: A Gamified Retrospective 12th

Ga-starfish: A Gamified Retrospective

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

作者： Restrepo-Tamayo, Luz Marcela Gasca-Hurtado, Gloria Piedad Univ Medellin Medellin Colombia

ISBN: (纸本)9783031602207;9783031602214

Technical and non-technical factors influence productivity in software development teams, with technical aspects being more commonly considered. However, non-technical ones hold significant sway in software development, especially within agile contexts. Achieving productivity within a software development team involves enhancing how tasks are executed. In agile work environments, improvement actions are carried out through retrospectives. However, effectively addressing retrospectives as a key event for software process improvement poses a challenge for teams, mainly when aiming to enhance productivity. This study provides a useful tool for conducting retrospectives, primarily focusing on analyzing non-technical factors that influence the productivity of software development teams. To achieve that goal, the proposal is to employ gamification elements by designing the tool based on an instrument design method and a list of non-technical factors. The most relevant outcome of this work is a technique called Ga-starfish, intended for conducting a retrospective based on gamification elements for agile software development environments. The proposed technique is a valuable alternative to improve the software development team's productivity, which is highly demanded given the challenges of the Fourth Industrial Revolution.

关键词： Agile Gamification Retrospective Social and human factors Software development teams Starfish

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A Proposed Intelligent Map Fusion for Pavement Crack Detection Using Structure from Motion

A Proposed Intelligent Map Fusion for Pavement Crack Detecti...

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International Conference on Intelligent and Fuzzy systems (INFUS)

作者： Benmhahe, Brahim Basmassi, Mohamed Amine Chentoufi, Jihane Alami Ibn Tofail Univ Fac Sci Lab Comp Sci Res Kenitra Morocco

ISBN: (纸本)9783031671913;9783031671920

Due to its small dimension and low-intensity variation to the background, crack is considered the most challenging distress on the pavement surface. Despite multiple methods deployed to detect and classify cracks, Smart City still intends for an intelligent and cost-effective solutions. This paper proposes a novel approach based on an intelligent Map Fusion of extracted features from 2D images and 3D models. The proposed method transforms pavement images taken by a commercial camera into a 3D model using the Structure from Motion as a computer vision technique. Then, the grayscale level and roughness are computed for each 3D point and filtered to produce the crack 3D Point candidates at the decision-making level. Finally, the Graham Scan algorithm was used to define the contour of the crack. The presented method has been assessed and validated for a case study. The findings indicate that the model can detect and accurately contour the crack.

关键词： Map Fusion Intelligent system Cracks classification Features Extraction Decision Making Computer Vision Graham Scan Algorithm

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Effect of Social Media on Workplace Procrastination Among Employees in Bosnia and Herzegovina 12th

Effect of Social Media on Workplace Procrastination Among Em...

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

作者： Pestek, Suada Pestek, Almir Kozo, Amra Univ Sarajevo Sch Econ & Business Trg Oslobodjenja-A Izetbegov 1 Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031603273;9783031603280

The paper deals with workplace procrastination, which results from using the Internet and social media during working hours. Practice shows that the appearance of procrastination causes numerous negative consequences, both for employees and organizations. Although procrastination is exceptionally well represented in literature and researched from different angles, this phenomenon has not been given sufficient attention in Bosnia and Herzegovina (B&H), and therefore the number of papers on this topic is negligible. In order to study the effects of workplace procrastination caused by the use of social media, a field survey was conducted on a sample of 701 employees in B&H. Our results align with the findings of other studies worldwide and offer new insights into the topic.

关键词： procrastination social media Bosnia and Herzegovina

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Unsupervised Feature Selection Approach for Smartwatches 4th

Unsupervised Feature Selection Approach for Smartwatches

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4th Congress on Intelligent systems (CIS)

作者： Kapse, Manohar Sharma, Vinod Elangovan, N. Gupta, Suchita Symbiosis Int Symbiosis Ctr Management & Human Resource Dev Pune Maharashtra India Christ Univ Sch Business Management Bangalore Karnataka India Prestige Inst Management & Res Indore Madhya Pradesh India

ISBN: (纸本)9789819990399;9789819990405

Traditional feature selection methods can be time-consuming and labor-intensive, especially with large datasets. This study's unsupervised feature selection approach can automate the process and help identify important features preferred by a particular segment of users. The unsupervised feature selection method is applied for smartwatches. Smartwatches continue to gain popularity. It is important to understand which features are most important to users to design and develop smartwatches that are more engaging, user-friendly, and meet the needs and preferences of their target audience. The rapid pace of technological innovation in the smartwatch industry means that new features and functionalities are constantly being developed. Multicluster feature selection, Laplacian score, and unsupervised spectral feature are used. Conjoint analysis is done on the most common features in all three selection methods. The unsupervised feature selection technique is used for identifying the relevant and important features of new smartwatch users. The practical implication of the research is in the application of the technique in the new product design of smartwatches. The result of the study also informs smartwatch manufacturers and developers on the features they need to prioritize and invest in. This can ultimately result in better and more user-friendly smartwatches and a good overall experience for the user.

关键词： Unsupervised Feature Selection Conjoint analysis Multi-cluster Laplacian score Spectral Smartwatch

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