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AI-driven Voice Recognition: Model Development and Application

In the course of the work is decided to develop a speech recognition model with the application with the system assistant capabilities. The result of the author's work is a model that is capable of speech recognition on a limited set of words and the application that will be the prototype of the concept. The software is implemented using Visual Studio Code/Jupyter, Python programming language with big framework such as Keras. The developed software fully meets the requirements and is ready for operation.

Author: Aleksejs Ņikiforovs

Supervisor: Dmitry Pavlyuk

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Computer Science

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Improvement of machine leaning algorithms performance by data set dimensionality reduction using cellular automata

A significant challenge in Machine Learning is dealing with high-dimensional data. Complexity knowns as the "curse of dimensionality" results in deterioration оf Machine Learning algorithms performance as the dimensionality and dataset size increases. Cellular automata are a dynamical discrete computational system with mathematical functions knows as rules that result in complex global behaviour. We used one-dimensional elementary cellular automata as a tool for dataset size. Model variables were selected for initial status vector generation and its further transformation to format that is suitable for cellular automata rules application known in cellular automata theory as configuration. Then model iterated through all possible cellular automata rules and various epochs variations were applied. Model performance for reduced dataset was compared with benchmark results of original dataset after standard dimensionality reduction technics used. It was concluded that applied cellular automata rules can be used as alternative methods for dataset size reduction without deteriorating model performance.

Author: Alexey Kuchvalskiy

Supervisor: Dmitry Pavlyuk

Degree: Master

Year: 2024

Work Language: English

Study programme: Computer Sciences

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Best practices for enhancing customer centricity through digital solutions

The first part of the thesis considers the concept of a customer-centric approach and the best practices of digital solutions for achieving this approach through an improved customer experience.In the second part of the thesis, the data-driven decision-making method is discussed, as well as the existing tools for analysing data and matrices for evaluating customer success. Furthermore, it examines the successful implementation of digital solutions to enhance customer experience at companies such as Netflix and Spotify.The third part of the thesis is devoted to an analysis of the Latvian online food delivery market. The analysis includes an examination of the current market situation, the identification and comparison of the main players on the market, and an identification of the needs and expectations of users. In the fourth part of the thesis, the findings of the previous sections are used to identify the best practices for digital solutions to improve the customer experience in online food delivery applications. In addition, the possible aspects to meet user needs are identified and recommendations are made.

Author: Alisa Purviņa

Supervisor: Oksana Skorobogatova

Degree: Bachelor

Year: 2024

Work Language: English

Study programme: Business and Management

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Change management in catering companies in the context of the digital economy

The first chapter describes that based on digital platforms as the main factor of production, labor relations and labor functions are being transformed. In the modern economy, various industries and activities are being transformed, new industries are being formed, based only on the use of new technologies.The second chapter describes that the catering sector is very competitive in the Latvian market. In the context of transformation of the labor market, there are changes in the requirements for employees, which are associated with their personal development and desire for personal growth. Digitalization is transforming existing jobs, requiring workers to have new skills to perform new tasks, requiring continuous training.The third chapter describes that in a market economy, digital business transformation can drive growth, productivity and competitiveness. Digitalization allows us to minimize the risk of human error and free up specialists’ time to solve more important issues.The fourth chapter analyzes the main activities and problem areas of the enterprise, analyzes and proposes promising concepts for personnel management of an existing enterprise in the Latvian public catering market, since in modern changing conditions personnel are the key asset of the enterprise.

Author: Alīna Uļjanovska

Supervisor: Oksana Skorobogatova

Degree: Master

Year: 2024

Work Language: English

Study programme: Business and Management

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Use of Artificial Intelligence in Human Resource Management

The integration of Artificial Intelligence into Human Resource Management processes presents an evolving domain of exploration and practical application. The widespread adoption of AI technologies presents the potential for significant transformations in products, innovation processes and business models. The research aim is to develop a framework for effective use of AI in Human Resource Management. The subject of the research is AI-based solutions in Human Resource Management. The object of the research is Human Resource Management processes in an enterprise.A multifaceted research approach was used to scrutinize the effective utilization of AI in HRM: Literature review, Case Studies, Employee Surveys, Interviews with HR experts.During this research, the author highlighted aspects of contemporary HRM that can be improved using AI technologies; made a list of the recommended practices for integrating AI-based solutions into HRM; developed a framework for AI tools implementation and found out that HR experts’ and employees’ overall perspective on AI within HRM appears optimistic.This research holds both theoretical and practical significance, driving advancements in theoretical knowledge, informing organizational practices, and shaping the future of work in the digital age.

Author: Ana Enache

Supervisor: Yulia Stukalina

Degree: Master

Year: 2024

Work Language: English

Study programme: Business and Management

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