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The dispute resolution process in the construction industry is known for delays in settlement, with some cases even escalating to complex arbitration and litigation. To avoid conflicts turning into disputes, the parties need to be proactive in identifying and resolving conflicts in their nascent stages. It is here that innovative lean construction practices can potentially act as a game-changer to avoid disputes, and this study aims to attempt to understand this phenomenon empirically.

A questionnaire-based empirical study, followed by semi-structured interviews, is conducted to understand the relevance of key tenets of lean principles in dispute avoidance.

Although stakeholders agree on the usefulness and practicality of lean principles in dispute avoidance, the extent of agreement is lesser when it comes to its implementation practicality. Moreover, there is a demographic influence observed on lean tenets such as “open communication”, “stakeholder collaboration” and “constraint identification”.

The results point towards an approach that combines contractual mandate, training and awareness creation to iron out the differences in the usefulness and practicality of lean approaches to avoid disputes.

Lean implementation is widely discussed in many construction contexts, such as sustainability, productivity improvement and planning. However, a discussion on lean philosophy’s role in dispute avoidance is muted. Therefore, this study assumes significance.

The objective of this research is to investigate the capabilities of the ChatGPT GPT-4 model, a form of artificial intelligence (AI), in comparison to human experts in the context of construction project risk management.

Employing a mixed-methods approach, the study draws a qualitative and quantitative comparison between 16 human risk management experts from Finnish construction companies and the ChatGPT AI model utilizing anonymous peer reviews. It focuses primarily on the areas of risk identification, analysis, and control.

ChatGPT has demonstrated a superior ability to generate comprehensive risk management plans, with its quantitative scores significantly surpassing the human average. Nonetheless, the AI model's strategies are found to lack practicality and specificity, areas where human expertise excels.

This study marks a significant advancement in construction project risk management research by conducting a pioneering blind-review study that assesses the capabilities of the advanced AI model, GPT-4, against those of human experts. Emphasizing the evolution from earlier GPT models, this research not only underscores the innovative application of ChatGPT-4 but also the critical role of anonymized peer evaluations in enhancing the objectivity of findings. It illuminates the synergistic potential of AI and human expertise, advocating for a collaborative model where AI serves as an augmentative tool, thereby optimizing human performance in identifying and managing risks.

I examine Bogdanov’s notion of Tektology within the context of modern communication systems and political agendas.

The practicality of Tektology from the perspective of 21st century sensibilities.

I argue that, like the implications of creating a suitable environment in Red Star, the practicality of enabling tektology in the 21st century is unlikely.

Tektology was an idea created in the early 20th century and the social conditions of that era-especially in Russia. The work associated with it is Stafford Beers VSM – an idea of combining the two was suggested by Jackson in 2023. Clearly, the early ideas rely on the source material of that era which are taken within the context of now. A mixture of early 20th and 21st century references are referred to. To limit such a topic as this to the word limits of the journal necessitates reducing discussion, for example the link between Tektology and Happiness.

It is not possible to test these ideas in a practical sense. The discussion relies upon what Tektology proposes and the way in which ICT is used in the 21 century. The only practical attempt of using technology as a major control system is that of Beer’s Chilean project but Tektolgy was more ambitious; it was aimed at creating a new society. The paper can only relate to observations about the way ICTs are used and controlled presently

The paper highlights the way that communication platforms are used and controlled in western society and elsewhere.

While attempts have been made to link Tektology to modern communication technologies few consider it within the context of 21st century cultural, political and media experience.

An increasing aging population and an increasing number of people suffering from musculoskeletal disorders have increased the demand for wearable robots. Comfortable, wearable robots that can be worn like clothing are currently being investigated. However, the embedded components may be displaced owing to the flexibility of the fabrics, which can lower the sensing accuracy and limit natural body movements. This study aims to develop clothing-type wearable platforms to minimize the displacement of embedded components such as sensors and actuators while maintaining comfort.

Four designs were developed using materials with different seam lines, that can serve as anchoring details, and flatlock stitches considering body movements and musculoskeletal structures. The wear evaluation experiment was filmed using a speed camera and analyzed using the TimeViewer software and SPSS 26.0. Based on these results, four clothing-type wearable platform designs were developed.

The variation in the location of a point in the armhole among the designs was marginal. Participants were satisfied with the functionality, practicality, wearability, efficiency and ease of use of the developed designs. A final clothing-type wearable platform was developed by applying a design with the least change in location, a suitable design for each area and wear comfort.

The results of this study contribute to the development of wearable robots by establishing clothing design data to minimize changes in sensor and actuator movements.

This study aims to examine Braille usage among consumers with visual impairments, investigating motivations and addressing inherent challenges.

Drawing insights from 16 semistructured interviews with individuals experiencing blindness, this study reveals nuanced aspects of Braille utilization.

Three key motivations for Braille usage are identified: as a coping mechanism for functional needs and to combat stigma; as an embodied experience contributing to pleasure; and as a heritage embodying a culture of visual impairment. Obstacles include cultural and financial barriers to learning, incomplete retail transcriptions limiting practicality and spatial congestion issues.

This study underscores Braille’s dual function as both coping mechanism and cultural heritage. By highlighting obstacles, it sheds light on challenges faced by consumers with visual impairments, facilitating advocacy and promoting inclusive retail practices. Originality lies in recognizing diverse motivations and experiences among Braille users, offering insights for enhancing tactile engagement in the marketplace.

This research paper aimed to investigate the affordances of using virtual reality (VR) in teaching culture among in-service teachers of teaching Persian to speakers of other languages (TPSOL) in Iran.

This qualitative case study, conducted at two Iranian universities, used purposeful sampling to select 34 eligible in-service Persian teachers from a pool of 73. Data collection used an open-ended questionnaire and interviews.

Before the TPSOL in-service training workshop, teachers expressed their reservations regarding the use of VR to teach culture in TPSOL courses. The emerged themes were “skepticism toward effectiveness,” “practicality concerns,” “limited awareness of VR applications,” “technological apprehension” and “prevalence of traditional teaching paradigms.” During the post-workshop interview, it was discovered that the teachers’ perceptions of VR in teaching culture had undergone a positive shift. The workshop generated emergent themes that reflected positive perceptions and affordances for using VR to teach culture in TPSOL, including “enhanced cultural immersion,” “increased student engagement,” “simulation of authentic cultural experiences,” and “facilitation of interactive learning environments.”

One primary limitation is the lack of prior experience with VR for teaching practices in real-world classrooms among the participants. While the study aimed to explore the potential of VR in enhancing pedagogical approaches, the absence of participants with prior exposure to VR in educational contexts may impact the generalizability of the findings to a broader population. Additionally, the study faced practical constraints, such as the unavailability of sufficient facilities in the workshop. As a result, the instructor had to project the VR cont7ent on a monitor, potentially diverging from the immersive nature of true VR experiences. These limitations offer opportunities for future research to refine methodologies and gain a more comprehensive understanding of the implications of integrating VR into teaching practices.

Extensive research has been conducted on the effectiveness of VR in language education. However, there is a significant gap in research on TPSOL, which is considered a less commonly taught language. This study aims to address this gap by exploring the use of VR in the TPSOL through the lenses of in-service teachers. As part of a larger investigation, this qualitative inquiry focuses on the perceptions of in-service teachers about VR, with a particular emphasis on the cultural understanding of the Persian language.

This paper aims to Solar photovoltaic (PV) power can significantly impact the power system because of its intermittent nature. Hence, an accurate solar PV power forecasting model is required for appropriate power system planning.

In this paper, a long short-term memory (LSTM)-based double deep Q-learning (DDQL) neural network (NN) is proposed for forecasting solar PV power indirectly over the long-term horizon. The past solar irradiance, temperature and wind speed are used for forecasting the solar PV power for a place using the proposed forecasting model.

The LSTM-based DDQL NN reduces over- and underestimation and avoids gradient vanishing. Thus, the proposed model improves the forecasting accuracy of solar PV power using deep learning techniques (DLTs). In addition, the proposed model requires less training time and forecasts solar PV power with improved stability.

The proposed model is trained and validated for several places with different climatic patterns and seasons. The proposed model is also tested for a place with a temperate climatic pattern by constructing an experimental solar PV system. The training, validation and testing results have confirmed the practicality of the proposed solar PV power forecasting model using LSTM-based DDQL NN.

This study aims to discuss the numerical solutions of weakly singular Volterra and Fredholm integral equations, which are used to model the problems like heat conduction in engineering and the electrostatic potential theory, using the modified Lagrange polynomial interpolation technique combined with the biconjugate gradient stabilized method (BiCGSTAB). The framework for the existence of the unique solutions of the integral equations is provided in the context of the Banach contraction principle and Bielecki norm.

The authors have applied the modified Lagrange polynomial method to approximate the numerical solutions of the second kind of weakly singular Volterra and Fredholm integral equations.

Approaching the interpolation of the unknown function using the aforementioned method generates an algebraic system of equations that is solved by an appropriate classical technique. Furthermore, some theorems concerning the convergence of the method and error estimation are proved. Some numerical examples are provided which attest to the application, effectiveness and reliability of the method. Compared to the Fredholm integral equations of weakly singular type, the current technique works better for the Volterra integral equations of weakly singular type. Furthermore, illustrative examples and comparisons are provided to show the approach’s validity and practicality, which demonstrates that the present method works well in contrast to the referenced method. The computations were performed by MATLAB software.

The convergence of these methods is dependent on the smoothness of the solution, it is challenging to find the solution and approximate it computationally in various applications modelled by integral equations of non-smooth kernels. Traditional analytical techniques, such as projection methods, do not work well in these cases since the produced linear system is unconditioned and hard to address. Also, proving the convergence and estimating error might be difficult. They are frequently also expensive to implement.

There is a great need for fast, user-friendly numerical techniques for these types of equations. In addition, polynomials are the most frequently used mathematical tools because of their ease of expression, quick computation on modern computers and simple to define. As a result, they made substantial contributions for many years to the theories and analysis like approximation and numerical, respectively.

This work presents a useful method for handling weakly singular integral equations without involving any process of change of variables to eliminate the singularity of the solution.

To the best of the authors’ knowledge, the authors claim the originality and effectiveness of their work, highlighting its successful application in addressing weakly singular Volterra and Fredholm integral equations for the first time. Importantly, the approach acknowledges and preserves the possible singularity of the solution, a novel aspect yet to be explored by researchers in the field.

The purpose of this paper is to explore the importance of personalisation in the relationship between the architectural design of homes and inhabitants’ psychological well-being.

This interdisciplinary mixed-method study first investigates the existence of a link between personalisation and users’ association with home through a quantitative study (n = 101) and then explores the nature of this relationship through qualitative interviews (n = 13) in a sequential explanatory approach.

The main findings of the study highlight the significance of personalisation in relation to the way people perceive home. A direct link was established between participants’ involvement in the transformation of the home and their satisfaction with the residence, as well as satisfaction with life in general. Further thematic analysis of the qualitative study revealed further conceptualisations of personalisation, which together form an umbrella concept called transformability.

The findings underscore the need for embedding flexibility as an architectural concept in the design of residential buildings for improving the well-being of occupants.

The design of homes has a great impact on inhabitants’ psychological well-being. This is becoming of greater importance in light of the global COVID-19 pandemic that has led to an increase in the amount of time spent in homes. This research contributes to this debate by proposing concepts for a deeper understanding of architectural influences on the psychology of the home.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.