Database Systems Journal

ISSN 2069 - 3230

Published with the support of:
The Bucharest University of Economic Studies


Database Systems Journal, Vol. X, 2019


Open PDF Journal


CONTENTS


1. A Reinforcement Learning Approach for Smart Farming (p. 3-12)
Gabriela ENE, The Bucharest University of Economic Studies, Romania
At a basic level, the aim of machine learning is to develop solutions for real-life engineering problems and to enhance the performance of different computers tasks in order to obtain an algorithm that is highly independent of human intervention. The main lying ingredient for all of these, is, of course, data. Data is only valuable if it is transformed into knowledge, or, experience and the machine learning algorithm is only useful if it can make a prediction with high accuracy outside the examples in the training set. The field of machine learning intersects multiple domains such as data science, artificial intelligence, statistics, and computer science, but has appliances in any possible field that relies on decision making based on evidence, including healthcare, finance, manufacturing, education, marketing and recently, more and more in agriculture and farm-related management systems. As the Internet of Things and Cloud-Based solutions are introducing artificial intelligence in farming, the phenomenon of Big Data is going to impact the whole food-supply network. Machines that are connected with each other through a network or that are equipped with deep learning software or just with measurement systems are making the farming processes extremely data-driven. Fast decision-making capabilities might become a game-changing business model in this field.
Keywords: machine learning, reinforcement learning, artificial intelligence, smart farming, Thompson Sampling, Q-Learning.
2. Monitoring and Controlling Electricity Consumption Application for Smart Buildings (p. 13-24)
Maria Irene CALINOIU, The Bucharest University of Economic Studies, Romania
Simona-Vasilica OPREA, The Bucharest University of Economic Studies, Romania
In the context of global concern about climate change and energy security, saving and optimizing electricity usage has become a priority of the European Union's energy policy. In the member states, households consume about 27% of the total electricity used [1]. Thus, controlling electricity consumption remains an important objective for this sector as well. Developing a reliable application for electricity monitoring and optimization is a way to reduce individual consumer consumption, as well as a solution to avoid overloading the distribution network.
Keywords: electric energy consumption feedback, energy literacy, consumer profile, shifting optimization algorithm, mobile application design.
3. Trading Fragmentation Methodology to Reduce the Capital Exposure with Algorithmic Trading (p. 25-32)
Cristian PAUNA, The Bucharest University of Economic Studies, Romania
This paper presents a practical methodology to reduce the capital exposure by early exits from the financial markets using algorithmic trading. The method called trading fragmentation uses several automated trading software applied on more unrelated markets and a particular risk management strategy to obtain a higher profit level with a lower risk. An advanced capital management procedure is used to integrate all into an unitary risk management system applied into a single trading account. It was found that the method presented here is the proper way to avoid large loss trades and to reduce the time when the capital is blocked into negative positions for the recovery process. In this way the efficiency of the capital usage is improved and the profit is made faster with lower risk level. The method was tested with real capital for more than five years and positive results were obtained. Comparative trading numbers will be also included in this paper in order to reveal the efficiency and the advantages obtained with the trading fragmentation methodology.
Keywords: algorithmic trading, capital exposure, risk management, trading fragmentation.
4. Factors that contribute programming skill and CGPA as a CS graduate: Mining Educational Data (p. 33-42)
Md Aref BILLAH, International Islamic University Chittagong (IIUC), Chittagong, Bangladesh
Sheikh Arif AHMED, International Islamic University Chittagong (IIUC), Chittagong, Bangladesh
Shahidul Islam KHAN, International Islamic University Chittagong (IIUC), Chittagong, Bangladesh
Computer Science (CS) has become one of the most popular under graduate program in last few years. According to UGC roughly 116 universities out of 136 are offering computer science program which indicates a massive number of students are choosing this program as their undergraduate program. But statistically significant number of students are failing to become skilled and effective CS graduate because many students are taking CS without accessing their chance in this program. Success in academic and professional life require to choose right under graduate program. Considering CGPA and Programming Skill as two of the most significant factors to determine student's success in CS, we have predicted these two by taking students personal interest, academic results, analytical skill and problem solving skill into account. We also extracted most significant features of a prospective CS student by using gain ratio.
Keywords: Computer Science Student, Predicting Performance, Machine Learning Techniques, Data Mining, Programming skill, CGPA.
5. Big Data: Technologies and Software Products (p. 43-53)
Adriana BANUTA, The Bucharest University of Economic Studies, Romania
Catalina DRAGOMIR, The Bucharest University of Economic Studies, Romania
Madalina GHETU, The Bucharest University of Economic Studies, Romania
The main tendency in technology leans towards huge amounts of data to be stored, analyzed and processed, in order to obtain valuable information on various topics. Regardless the domain of interest, storing data is always a must and it must be done in an efficient, secure and accessible way. Then, it can be used for statistics, studies or as training sets in the field of machine learning. The aim of this paper is to give a brief overview of the concept known as big data, as well as to present and compare the main technologies and software products used to store and manipulate this type of data.
Keywords: Big Data, Hadoop, NoSQL, Traditional Database.
6. Open Standards for public software used by a National Health Insurance House. A study of EU vs USA standardization approaches (p. 54-64)
Antonio CLIM, The Bucharest University of Economic Studies, Romania
Razvan Daniel ZOTA, The Bucharest University of Economic Studies, Romania
Information technology improves reliability, innovation, and efficiency in the medical care sector by assisting in coming up with electronic health records. Looking into the interoperability of software and databases is relevant from the perspective of electronic health records. The standardization of processes in the European Union and the United States is diverse, which makes it all the more important to discuss open standards. Software systems create patient-centric medical care services and a platform for management. Thus, they facilitate the formation of functional health information networks and the exchange of information. Therefore, this improves the value proposition for all stakeholders involved. Open-source standards have been found to be developed independently of any single party. They do not have any legal or technical closest that prevent any party to use them. Similarly, they do not have extensions or components with a dependency or being based on preparation standards. Additionally, they are available for full public assessment without any form of constraints. This paper discusses these open standards and how best they have been deployed in the United States and the European Union - understanding that advantages and disadvantages of open standards are also imperative.
Keywords: User as Developer (UaD), Free and Open-Source Software (FOSS), cost-effectively software, EHR, interoperability, software, open standards, databases, security.
7. Improving the Customers' In-Store Experience using Apriori Algorithm (p. 65-74)
Ioana DAVID, The Bucharest University of Economic Studies, Romania
The 21st century is the era of technology and digital development. That's the reason why mobile applications nowadays became an important support for businesses and a significant part of our daily activities. The usage of smart devices and the ease of access to technology lead to obvious changes in consumer behavior. Therefore, as it has been remarked a decrease of in-store shopping, improving the shopping experience in traditional stores has become of high interest for many retailers. In this paper, we propose a mobile application which helps people to optimize the time they spend inside of hypermarkets and which suggests an optimal placement for aisles in a store.
Keywords: in-store experience, aisles placement, mobile application development.
8. Waterative Model: an Integration of the Waterfall and Iterative Software Development Paradigms (p. 75-81)
Mohammad Samadi GHARAJEH, Islamic Azad University, Tabriz, Iran
Software development paradigms help a software developer to select appropriate strategies to develop software projects. They include various methods, procedures, and tools to describe and define the software development life cycle (SDLC). The waterfall and iterative models are two useful development paradigms, which have been used by various software developers in the last decades. This paper proposes a new software development methodology, called waterative model, which applies an integration of the waterfall and iterative development paradigms. In this model, the iterative model is embedded into the waterfall model to use the advantages of both models as an integrated one. It, in the most cases, is appropriate for large software products that need a long-term period of time for the development process. Experimental results demonstrate that the customer satisfaction score could be high by using the proposed model in various software projects.
Keywords: Software Engineering, Software Development, Waterfall Model, Iterative Model, Waterative Model.
9. Organizational development through Business Intelligence and Data Mining (p. 82-99)
Denis-Catalin ARGHIR, The Bucharest University of Economic Studies, Romania
Ioana-Gilia DUSA, The Bucharest University of Economic Studies, Romania
Miruna ONUTA, The Bucharest University of Economic Studies, Romania
The article presents the concept of Business Intelligence and their influence on decision making. Examining Business Intelligence systems was accomplished by theoretically comparing of four systems: Microsoft Power Bi, IBM Cognos, Oracle BI, and SAS, focusing on "functionality", "performance", "usage" and "cost" criteria. Functionality testing was done through the Power BI system using a HORECA industry dataset, namely a café retailer. On this dataset has been applied data mining concepts as cluster analysis, KNN classification analysis, and association study, to determine the frequently encountered templates, to categorize buyers into various key categories, and to help the business thrive.
Keywords: Business Intelligence, Power BI, Data Mining, Apriori Algorithm, Cluster Analysis, KNN Analysis.
10. Internet of Things (IoT) (p. 100-110)
Diana - Iuliana BOBOC, The Bucharest University of Economic Studies, Romania
Stefania - Corina CEBUC, The Bucharest University of Economic Studies, Romania
After the World Wide Web (the 1990's) and the mobile Internet (the 2000's), we are now heading to the third phase of the Internet evolution - the Internet of Things. A new era where the real, digital and virtual converge to create smart environments that make energy, transport, cities and many other areas more intelligent. Smart is the new green and the green products and services are being replaced by smart products and services. The Internet of things means billions of smart objects that are incorporated into our everyday life, improving the social, technical and economic benefits. The Internet of Things enables anytime, anyplace connectivity for anything and anyone. However, there are many issues that need to be solved in order to reach the full potential of the Internet of things.
Keywords: technology, Internet of things, networks, sensors, augmented behaviour, augmented intelligence, standards, interconnectivity, Web, security, privacy, IP, Internet, transfer rate, network protocols, smartphone, interoperability, smart applications.