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1

The digital future of information. Determinants of the use of open source intelligence

Lipińska Agnieszka

Cybersecurity and Law

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2024

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Vol. 11 (1)

271--280

EN

Cyberspace as a place of information acquisition is in constant flux. Recognizing the threats and challenges associated with it is one of the key elements influencing national security. Knowledge of the current conditions affecting information security and the possibility of obtaining information is an essential element of the work of the institutions forming the state security system. This article will outline the factors affecting the future of information operation and distribution in the digital world25confirming the increased need for OSINT in state institutions, especially in the face of new challenges. These include: hacktivism, the dissemination of specialized tools and technologies for data acquisition and analysis among the network user community, hybrid and diplomatic-propaganda activities carried out in the info-sphere by nation states. The article will also provide a forecast of the development of cyberspace in the context of future OSINT activities.

PL

Cyberprzestrzeń jako miejsce pozyskiwania informacji podlega ciągłym przemianom. Rozpoznawanie związanych z nią zagrożeń i wyzwań stanowi jeden z elementów wpły-wających na bezpieczeństwo narodowe. Znajomość aktualnych uwarunkowań wpły-wających na bezpieczeństwa informacji i możliwości ich uzyskania stanowi niezbędny element pracy instytucji tworzących system bezpieczeństwa państwa. W niniejszym artykule przedstawiono czynniki wpływające na przyszłość funkcjonowania i dystry¬bucji informacji w świecie cyfrowym potwierdzające wzrost konieczności stosowania OSINT w instytucjach państwowych, szczególnie w obliczu nowych wyzwań. Należą do nich: haktywizm, upowszechnienie wśród użytkowników sieci specjalistycznych narzędzi i technologii do pozyskiwania i analizy danych, działania hybrydowe i dyplomatyczno-pro-pagandowe prowadzone w infosferze przez państwa narodowe. Ponadto przedstawiono prognozę rozwoju cyberprzestrzeni w kontekście przyszłych działań OSINT.

2

Data analytics and global logistics performance: an exploratory study of informatization in the logistics sector

Anwar Muhammad Fahad, Wong Wai Peng, Saad Nor Hasliza, Mushtaq Naveed

LogForum

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2022

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Vol. 18, no. 2

137--160

EN

Background: Informatization has enabled global logistics and supply chains (LSC) to capitalize on data-driven analytics to improve logistics performance. At the country level, logistics performance is gauged through the logistics performance index (LPI), where globally 61.25% or 98 countries perform below the mean LPI score. Previous studies focused on logistics informatization in high and moderate LPI rank economies. The paper aims to conduct an exploratory case study in a low LPI performing country to assess the informatization practices of logistics entities and develop a logistics informatization continuum to unlock data analytics for other countries. Methods: The study implements qualitative methods to develop strategic recommendations to reduce global logistics imbalance. We employ a two-layer methodology consisting of thematic analysis and a novel strategic choice approach (SCA) to involve stakeholders for recommendations on obstruction. For thematic analysis, 16 semi-structured interviews were conducted from logistics companies, also onboard 10 trade associations and government representatives for the SCA analysis. Results: We observed many obstructions in informatization; low willingness on informatization, fear of information leakage by humans, low-reciprocity for collaboration, the myth of information and communication technologies (ICT) as an expensive tool, self-interest, and opportunistic behavior. Conclusion: Information-centric and integrated LSC enables data-driven technologies for real-time decision making, vigilance, and data analytics to distinguished the success of a country’s logistics performance. Originality: This study explores the informatization conformity in the logistics sector to connect data analytics. We introduced a novel strategic choice approach in the technology domain for problem structuring. The paper further contributes by suggesting a logistics informatization continuum for low LPI countries to straighten digitalization in the logistics sector.

3

Monitorology – the Art of Observing the World

Malek Miroslaw

TASK Quarterly : scientific bulletin of Academic Computer Centre in Gdansk

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2021

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Vol. 25, No 2

131--139

EN

We focus on the art of observing the world by electronic devices such as sensors and meters that, in general, we call monitors. We also define main monitoring objectives and pose five challenges for effective and efficient monitoring that still need a lot of research. In the era where compute power like electricity is easily available and easy to use across the globe, and big data is generated in enormous amounts at ever-increasing rates, the question, what to monitor and how, will become ever more relevant to save the world from flood of meaningless, dumb data, leading frequently to false conclusions and wrong decisions whose impact may range from a minor inconvenience to loss of lives and major disasters.

4

Towards the 5th industrial revolution: a literature review and a framework for process optimization based on big data analytics and semantics

Mourtzis Dimitris

Journal of Machine Engineering

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2021

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Vol. 21, No. 3

5--39

EN

The digitalization of modern manufacturing systems has resulted to increasing data generation, also known as Big Data. Although there are several technologies and techniques under the term Data Analytics for gathering such data, their interpretation to information, and ultimately to knowledge remains in its infancy. Consequently, albeit engineers currently can monitor the factory level, optimization is cut off of the data acquisition, and is based on data related methodologies. The focus should be pivoted on designing and developing suitable frameworks for integrating Big Data to process optimization based on the context of information gathered from the shopfloor. This paper aims to investigate the opportunities and the gaps as well as the challenges arising in the current industrial landscape, towards the efficient utilization of Big Data, for process optimization based on the integration of semantics. To that end, a literature review is performed, and a data-based framework is presented.

5

Methodology for Diagnosing the Causes of Die-Casting Defects, Based on Advanced Big Data Modelling

Okuniewska A., Perzyk M. A., Kozłowski J.

Archives of Foundry Engineering

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2021

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Vol. 21, iss. 4

103--109

EN

The purpose of this paper was to develop a methodology for diagnosing the causes of die-casting defects based on advanced modelling, to correctly diagnose and identify process parameters that have a significant impact on product defect generation, optimize the process parameters and rise the products’ quality, thereby improving the manufacturing process efficiency. The industrial data used for modelling came from foundry being a leading manufacturer of the high-pressure die-casting production process of aluminum cylinder blocks for the world's leading automotive brands. The paper presents some aspects related to data analytics in the era of Industry 4.0. and Smart Factory concepts. The methodology includes computation tools for advanced data analysis and modelling, such as ANOVA (analysis of variance), ANN (artificial neural networks) both applied on the Statistica platform, then gradient and evolutionary optimization methods applied in MS Excel program’s Solver add-in. The main features of the presented methodology are explained and presented in tables and illustrated with appropriate graphs. All opportunities and risks of implementing data-driven modelling systems in high-pressure die-casting processes have been considered.

6

Suggesting teaching methods by analyzing the behavior of children with special needs

Shrawankar Urmila, Shireen Azra

Bio-Algorithms and Med-Systems

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2020

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Vol. 16, no. 1

art. no. 20190038

EN

The behavioral pattern of children with special needs depends on their emotional and developmental disability. Any abnormal and incorrect pattern of behavior which is below the level of development as the expected norm can be considered as “the challenging behavior.” For supporting children with behavioral problems, many interventions and strategies alone, or in combination, are used. Behavioral and developmental problems, if not treated well, in childhood, may cause a problem and have negative long-term and short-term effects on a child’s personal life, education, family, and professional life. Detailed knowledge about the child’s behavior is important to define the problem. Hence, the software contains the questionnaire pattern, which is divided into categories like parents, teachers, doctors, and friends. Child behavior checklist is used to define the questionnaire. Images and video analysis are used to detect the current emotion in the child. By analyzing the behavioral pattern and current emotion, the teaching method will be suggested.

7

Introducing Advanced Data Analytics in Perspective of Industry 4.0 in a Die Casting Foundry

Perzyk M., Dybowski B., Kozłowski J.

Archives of Foundry Engineering

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2019

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iss. 1

53--57

EN

The paper presents some aspects of a development project related to Industry 4.0 that was executed at Nemak, a leading manufacturer of the aluminium castings for the automotive industry, in its high pressure die casting foundry in Poland. The developed data analytics system aims at predicting the casting quality basing on the production data. The objective is to use these data for optimizing process parameters to raise the products’ quality as well as to improve the productivity. Characterization of the production data including the recorded process parameters and the role of mechanical properties of the castings as the process outputs is presented. The system incorporates advanced data analytics and computation tools based on the analysis of variance (ANOVA) and applying an MS Excel platform. It enables the foundry engineers and operators finding the most efficient process variables to ensure high mechanical properties of the aluminium engine block castings. The main features of the system are explained and illustrated by appropriate graphs. Chances and threats connected with applications of the data-driven modelling in die casting are discussed.

8

Combining Data Analytics with Team Feedback to Improve the Estimation Process in Agile Software Development

Vetrò A., Dürre R., Conoscenti M., Fernández D. M., Jørgensen M.

Foundations of Computing and Decision Sciences

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2018

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Vol. 43, No. 4

305--334

EN

We apply a mixed research method to improve the user stories estimation process in a German company following agile software development. We combine software project data analytics with elicitation of teams’ feedback, identify root causes for wrong estimates and propose an improved version of the estimation process. Three major changes are adopted in the new process: a shorter non numerical scale for story points, an analogy-based estimation process, and retrospectives analyses on the accuracy of previous sprints estimates. The new estimation process is applied on a new project, and an improvement of estimates accuracy from 10% to 45% is observed.

9

My City Dashboard: Real-time Data Processing Platform for Smart Cities

Usurelu C.-C., Pop C.

Journal of Telecommunications and Information Technology

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2017

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nr 1

89--100

EN

In recent years, with the increasing popularity of IoT, the rapid growth of smartphone usage enabled by the increase adoption of Internet services and the continuously decreasing costs of these devices and services has led to a huge increase in the volume of data that governments can use in the context of smart city initiatives. The need for analytics is becoming a requirement for smart city projects such as city dashboards to provide citizens with an easy to understand overview of the city. As such, data should be analyzed, reduced and presented in such a way that citizens can easily understand various aspects of the city and use this information to increase quality of life. In this paper, we firstly present the context and the start of the design and implementation of proposed solution for real-time data processing in smart cities, mainly an analytics processing pipeline and a dashboard prototype for this solution, named My City Dashboard. We focus on high scalability and modularity of this platform.