Defining the Maturity Levels for Implementing Industrial Logistics Practices in Construction

Logistics practices are processes that require alignment and coordination among project actors to support successful construction operations. While recent research has underlined the effects of single material logistics practices on project performance, practitioners need more knowledge on development paths toward successful overall logistics solutions. Based on a review of current practices obtained from the literature, this research proposes the maturity levels of planning, organizing, operating, use of technology, and information flow regarding the logistics practices in construction. Moreover, the study devises a recommended order for implementing logistics practices and investigates how companies can advance their logistics maturity from one level to the next. The proposed model has been validated via case examples from the industry. The paper contributes to construction logistics research by describing how companies can navigate development efforts to gradually improve their logistics practices. Future research could conduct more case studies within different project contexts.

Persistent Developmental Limits to Devising Policy Innovation for Innovation Policies in Emerging Economies

Promising industrial profiles of Southeast Asian emerging economies have met their developmental limits in the face of the Asian Financial Crisis in the late 1990s. However, following the crisis, they have not been successful in upscaling the technological competitiveness of their industries. By applying the national innovation system approach originally developed in advanced western economies as an institutional mechanism of policy innovation in light of developmentalism, I seek to explain these persistent developmental limits in Malaysia and Indonesia. My qualitative research examines literature discussing policy coordination mechanisms in innovation policies and policy documents containing coordination mechanisms involving firms, universities, and government agencies; then, how these issues implicate innovation policies in the two countries. I employ a comparative institutional analysis between them focusing on institutional characteristics of the national innovation systems, specifically their institutional obstacles occurring within development paths amidst prevailing political environments. I suggest that persistent developmental limits in Malaysia and Indonesia result from systemic failures of achieving developmental aims regardless of their politico-administrative regimes. Existing institutional frameworks of the national innovation systems, entrenched in the socio-economic prevalence of the two countries, have not fit the nations’ developmental aims pursued upon innovation upgrading.

Research on multi-view clustering algorithm on epileptic EEG signal

Epilepsy is caused by the abnormal discharge of the patient's brain. Smart medical uses advanced technologies such as signal recognition and machine learning to identify and analyze the biological signals fed back from the subjects’ brain electrical signals and provide diagnostic results. In the past, doctors used their own experience and theoretical knowledge to judge whether there are characteristic signals by observing the subject’s EEG signal to realize the judgment of the condition. This method of diagnosis through observation often infuses the doctor's own subjective judgment, leading to misdiagnosis of the condition and low diagnosis and treatment efficiency. With the continuous development of advanced technologies such as artificial intelligence and signal recognition, this provides new ideas for the realization of EEG signal recognition and processing technology and opens up new development paths. This article is based on epilepsy EEG signal data, realizes EEG signal processing and uses machine learning methods to realize EEG signal identification and diagnosis.

Research on multi-view clustering algorithm on epileptic EEG signal

Epilepsy is caused by the abnormal discharge of the patient's brain. Smart medical uses advanced technologies such as signal recognition and machine learning to identify and analyze the biological signals fed back from the subjects’ brain electrical signals and provide diagnostic results. In the past, doctors used their own experience and theoretical knowledge to judge whether there are characteristic signals by observing the subject’s EEG signal to realize the judgment of the condition. This method of diagnosis through observation often infuses the doctor's own subjective judgment, leading to misdiagnosis of the condition and low diagnosis and treatment efficiency. With the continuous development of advanced technologies such as artificial intelligence and signal recognition, this provides new ideas for the realization of EEG signal recognition and processing technology and opens up new development paths. This article is based on epilepsy EEG signal data, realizes EEG signal processing and uses machine learning methods to realize EEG signal identification and diagnosis.

Mapping organizational complexity: a network-based approach to behavior through machine learning tools

The current uncertain, dynamic scenario calls for a systemic perspective when referring to organizational complexity and behavior. Our research contributes to the analysis of organizational complexity through multidimensional behavioral mapping. Our method uses machine learning tools to detect the interconnections between the different behaviors of a person in his/her operating context. First, the research project dealt with prototyping a model to read the organizational behavior, the related detection tool, and a data analysis methodology. It used machine learning tools and ended with a data visualization phase. We set our model to read the organizational behavior by comparing the literature benchmark theories with our field experience. The model was organized around 4 areas and 16 behaviors. These were the basis for singling out the indicators and the questionnaire items. The data analysis methodology aimed at detecting the interconnections between behaviors. We designed it by joining univariate analysis with a multivariate technique based on the application of machine learning tools. This led to a high-resolution network map through three specific steps: (a) creating a multidimensional topology based on a Kohonen Map (a type of unsupervised learning artificial neural network) to geometrically represent behavioral relationships; (b) implementing k-means clustering for identifying which areas of the map have behavior similarity or affinity factors; and (c) locating people and the various identified clusters within the map. The research highlighted the validity of machine learning tools to detect the multidimensionality of organizational behavior. Therefore, we could delineate the networking of the observed elements and visualize an otherwise unattainable complexity through multimedia and interactive reporting. Application in the field of research consisted of the design and development of a prototype integrated with our LMS platform via a plugin. Field experimentation confirmed the effectiveness of the method for creating professional growth and development paths. Furthermore, this experimentation allowed us to obtain significant data by applying our model to several sectors, namely pharmaceutical, TLC, banking, automotive, machinery, and services.

Development of Roadmap for Photovoltaic Solar Technologies and Market in Poland

Poland is dynamically changing its energy mix. As a result of this process, solar energy is increasing its share in energy production. The development of the solar energy market is determined by numerous factors. This paper aims to develop a roadmap for further development of the photovoltaic (PV) energy market in Poland. The scope of the research covers five areas of PV technology and market development in Poland: (i) technology; (ii) power grids; (iii) law; (iv) economic conditions; and (v) social conditions. With the use of a Technology Roadmapping Methodology (TRM), for each of the determined areas, several factors were analyzed, and their development paths were described. In addition, the article focuses on technological challenges (regarding PV cells, modules, components, power conversion and monitoring and management system, optimizers, batteries, and other energy storage systems), grid efficiency, recycling, production costs, subsidies, public awareness and education, and the energy exclusion problem. The main result of the research is the roadmap of the photovoltaic solar energy technology and market development in Poland. Further development of the PV market and technology requires parallel progress in all the identified areas. This study offers implications for policymakers, investors, managers, and technology and infrastructure developers regarding their involvement in photovoltaic market.

Profitability of Prosumers According to Various Business Models—An Analysis in the Light of the COVID-19 Effect

The European Union has set itself ambitious emission-reduction targets—becoming carbon neutral by 2050. The member states’ energy systems are increasingly switching to renewable and decentralized configurations, in line with the EU guidelines. This is accompanied by the support for “prosumers”—entities that both consume and generate renewable energy. In parallel, a number of prosumer support schemes are emerging as a result of the search for optimal development paths. At the same time, the COVID-19 pandemic has significantly affected the power market, causing huge anomalies mainly in demand and billing. The objective of the study was to assess the impact of the proposed changes in the prosumer schemes on the level of benefits prosumers obtained, including the performance of sensitivity analyses reflected in different levels and stability of electricity consumption resulting from extreme situations caused by the COVID-19 pandemic. Numerical computer simulations for five predefined prosumer support schemes were carried out in the R-project environment. The basic conclusion is that the prosumer benefits most from participating in the applicable discount mechanism, in which the unused energy is fed into a network storage, from which the prosumer can take 70% or 80% of the stored volume. The research also allows us to conclude that in Poland the COVID-19 pandemic has had a very significant impact on the level and profile of energy demand due to the introduction of restrictions on selected areas and economic sectors. The reduced demand is particularly visible in services (−58%), tourism and sport (−39%), and education (−19%). The analysis is an important contribution to the search for an optimal model of prosumer market development in Europe.

On the Future of Computational Thinking Education: Moving beyond the Digital Agenda, a Discourse Analysis Perspective

This article explores the development directions of the phenomenon of Computational Thinking (CT) from the perspectives of discourse analysis. The motivation is based on the understanding of CT as an advanced educational approach, methodology, and community, aimed at a set of learners’ digital and further competences having a huge impact on modern education and society. The novelty of this study lies in the attempt to look holistically at CT and its perspectives, considering it as an evolving phenomenon per se, leaving aside discussion on its internal characteristics or applications. The study utilizes a comprehensive analysis, applying discourse analysis and social semiotics methods. The results present the most trended storylines associated with CT and its context, providing a thorough introduction to the CT discursive landscape. The findings and discussion present a reflective insight into the discursive landscape directions, focusing on meaning-makers and their identities, the transformative and transductive potential of CT, observing the phenomenon’s development paths from a metaphorical perspective and positioning it towards the development of the socio-technical networks it mediates. In the conclusion, the options for development and possible trends in the reconstitution of the CT phenomenon are outlined.

Impact of the COVID-19 on the Destination Choices of Hungarian Tourists: A Comparative Analysis

The pandemic caused by the SARS-CoV-2 virus (COVID-19) has transformed the tourism sector to an unprecedented extent, creating new challenges and new development paths. Although the recovery of tourism is fraught with uncertainties, the changes in tourists’ travel habits offer a unique opportunity for tourism to recover in a way that respects the principles of sustainable development. Several international studies suggest that the pandemic has significantly transformed tourists’ travel habits and destination choices, making them more environmentally conscious and shifting their preferences towards inland destinations close to nature. To test these claims, we examined tourists’ destination choices and the factors influencing them in a sample of 500 respondents in Hungary before the pandemic and after the restrictions on travel, businesses, gatherings, and mask requirements were lifted in the summer of 2021. Our results show that there was no significant change in the destination choices of the tourists surveyed. The main influences were the aspects of safety and comfort; the consideration of environmental concerns, despite our assumptions, did not play a significant role.

Submersible pumps - application practice, technical requirements, development paths

Проанализировано применение погружных (плавающих) насосов в насосно-рукавных комплексах. Рассмотрены их преимущества перед центробежными насосами, устанавливаемыми в мобильной пожарной технике. На основе практики применения и технических характеристик погружных насосов, производимых ведущими зарубежными фирмами, сформулированы технические требования для разработки отечественного погружного насоса. Кроме того, технические требования могут стать основой разработки национального стандарта для этого типа пожарно-технической продукции. The article analyzes the results of operation of a relatively new type of centrifugal pump - a submersible (floating) centrifugal pump with a hydraulic drive. These pumps have a number of significant advantages over centrifugal pumps installed on mobile fire fighting equipment - they can be used to pump liquid from a mark up to minus 30 m. Since the suction pipe of such a pump is located directly in the pumped liquid (below the liquid mirror level), the phenomenon of cavitation is practically excluded. Submersible pumps are used to supply water in case of fire and for water disposal during the elimination of hazardous hydrological phenomena, both independently and in conjunction with centrifugal pumps installed on mobile fire fighting equipment (supply to pumping). All submersible pumps included in the set of hose-pumping complexes are of foreign production. The demand for such pumping units causes the need to develop domestic samples in order to get away from import dependence in the manufacture of pumping and hose systems and their operation. Based on the practice of using submersible pumps and the technical characteristics of submersible pumps produced by leading foreign companies, the following technical requirements for the development of a domestic submersible pump have been formulated. Pump delivery is 170-180 l ∙ s from the mark to minus 30 m. Water intake is possible both in equipped (adapted) and unequipped (unsuitable) places. In addition, the requirements for the hydraulic drive, weight and size characteristics, and some components have been formulated. In conclusion, some directions for the further development of pumping and hose systems and submersible pumping stations are considered.