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This paper aims to examine the present‐day use of, and future prospects for, robots for detecting mines and improvised explosive devices (IEDs), with an emphasis on the key operational requirements.

Following an introduction to the impact of mines and IEDs, this paper considers the problems with their detection and considers the techniques used. It then highlights their limitations and identifies key detection requirements. The remainder of the paper discusses the present‐day and future role of robots, notably for IED detection and humanitarian demining. This is followed by a brief conclusion.

This shows that mines and IEDs pose a major military and humanitarian threat but existing detection methods, including robots, suffer from many shortcomings. Robotic technologies that offer prospects are discussed but many specific requirements must be met if robotic solutions are to exert any real, future impact.

This paper highlights the need for improved mine and IED detection methods and identifies the factors that need to be taken into account if robots are to contribute meaningfully to these tasks in the future.

Reducing energy consumption in walking robots is an issue of great importance in field applications such as humanitarian demining so as to increase mission time for a given power supply. The purpose of this paper is to address the problem of improving energy efficiency in statically stable walking machines by comparing two leg, insect and mammal, configurations on the hexapod robotic platform SILO6.

Dynamic simulation of this hexapod is used to develop a set of rules that optimize energy expenditure in both configurations. Later, through a theoretical analysis of energy consumption and experimental measurements in the real platform SILO6, a configuration is chosen.

It is widely accepted that the mammal configuration in statically stable walking machines is better for supporting high loads, while the insect configuration is considered to be better for improving mobility. However, taking into account the leg dynamics and not only the body weight, different results are obtained. In a mammal configuration, supporting body weight accounts for 5 per cent of power consumption while leg dynamics accounts for 31 per cent.

As this paper demonstrates, the energy expended when the robot walks along a straight and horizontal line is the same for both insect and mammal configurations, while power consumption during crab walking in an insect configuration exceeds power consumption in the mammal configuration.

The purpose of this paper is to introduce the design of a training tool intended to improve deminers' technique during close‐in detection tasks.

Following an introduction that highlights the impact of mines and improvised explosive devices (IEDs), and the importance of training for enhancing the safety and the efficiency of the deminers, this paper considers the utilization of a sensory tracking system to study the skill of the hand‐held detector expert operators. With the compiled information, some critical performance variables can be extracted, assessed, and quantified, so that they can be used afterwards as reference values for the training task. In a second stage, the sensory tracking system is used for analysing the trainee skills. The experimentation phase aims to test the effectiveness of the elements that compose the sensory system to track the hand‐held detector during the training sessions.

The proposed training tool will be able to evaluate the deminers' efficiency during the scanning tasks and will provide important information for improving their competences.

This paper highlights the need of introducing emerging technologies for enhancing the current training techniques for deminers and proposes a sensory tracking system that can be successfully utilised for evaluating trainees' performance with hand‐held detectors.

The goal of this work is to evaluate how digital transformation disclosure in corporate news and press releases affects stock prices. We examine American and Chinese companies from the energy and industry sectors for two periods: pre-COVID-19 and during the COVID-19 pandemic.

To estimate the effects of disclosure of information related to digital transformation, we applied the bag-of-words (BOW) method. As the benchmark dictionary, we used Kindermann et al. (2021), with the addition of original dictionaries created via Latent Dirichlet allocation (LDA) analysis. We also employed panel regression analysis and random forest.

For USA energy sector, all aspects of digital transformation were insignificant in pre-COVID-19 period, while sustainability topics became significant during the pandemic. As for the Chinese energy sector, digital strategy implementation was significant in pre-pandemic period, while digital technologies adoption and business model innovation became relevant in COVID-19 period. The results show the greater significance of digital transformation aspects for industrials sectors compared to the energy sector. The result of random forest analysis proves the efficiency of the authors’ dictionary which could be applied in practice. The developed methodology can be considered relevant.

The research contributes to the existing literature in theoretical, empirical and methodological ways. It applies signaling and information asymmetry theories to the financial markets, digital transformation being used as an instrument. The methodological contribution of this article can be described in several ways. Firstly, our data collection process differs from that in previous papers, as the data are gathered “from investor’s point of view”, i.e. we use all public information published by the company. Secondly, in addition to the use of existing dictionaries based on Kindermann et al. (2021), with our own modifications, we apply the original methodology based on LDA analysis. The empirical contribution of this research is the following. Unlike past works, we do not focus on particular technologies (Hong et al., 2023) connected with digital transformation, but try to cover all multi-dimensional aspects of the transformational process and aim to discover the most significant one.

The paper aims to estimate how corporate philanthropy expenditures and corporate philanthropy disclosure (in general and in different spheres) affect investment attractiveness of Russian companies.

To assess the degree of corporate philanthropy disclosure the authors compiled lexicons based on a set of techniques: text and frequency analysis, correlations, principal component analysis. To adjust the existing classifications of corporate philanthropic activities to the Russian market the authors employed expert analysis. The empirical research base includes 83 Russian publicly traded companies for the period 2013–2019. To estimate the impact of indicators of corporate philanthropy disclosure on company's investment attractiveness the authors utilized panel data regression and random forest algorithm.

We compiled 2 Russian lexicons: one on general issues of corporate philanthropy and another one on philanthropic activities in various spheres (sports and healthcare; support for certain groups of people; social infrastructure; children protection and youth policy; culture, education and science). 2. The paper observes that the disclosure of non-financial data including that related to general issues of corporate philanthropy as well as to different spheres affects the market capitalization of the largest Russian companies. The results of regression analysis suggest that disclosure of altruism-driven philanthropic activities (such as corporate philanthropy in the sphere of culture, education and science) has a lesser impact on company's investment attractiveness than that of activities driven by business-related motives (sports and healthcare, children protection and youth policy).

Our findings are important to management, investors, financial analysts, regulators and various agencies providing guidance on corporate governance and sustainability reporting. However, the authors acknowledge that the research results may lack generalizability due to the sample covering a single national context. Researchers are encouraged to test the proposed approach further on other countries' data by using the authors’ compiled lexicons.

The study aims to expand the domains of signaling and agency theories. First, this subject has not been widely examined in terms of emerging markets, the authors’ study is the first to focus on the Russian market. Secondly, the majority of scholars use text analysis to examine not only the impact of charitable donations but also the effect of corporate philanthropy disclosure. Thirdly, the authors provided the authors’ own lexicon of corporate philanthropy disclosure based on machine learning technique and expert analysis. Fourthly, to estimate the impact of corporate philanthropy on company's investment attractiveness the authors used the original approach based on combination of linear (regression), and non-linear methods (permutation importance. The authors’ findings extend the theoretical concept of Peterson et al. (2021): corporate philanthropy is viewed as the company strategy to reinforce its reputation, it helps to establish more efficient relationships with stakeholders which, in its turn, results in the increased business value.

This study analyzes the blade channel vortices inside Francis runner with a particular focus on the identification of different types of vortices and their causes.

A single-flow passage of the Francis runner with refined mesh and periodic boundary conditions was used for the numerical simulation to reduce the computational resource. The steady-state Reynolds-averaged Navier–Stokes equations closed with the k-ω shear–stress transport (SST) turbulence model were solved by ANSYS CFX to determine the flow field. The vortices were identified by the second largest eigenvalue of velocity.

Four types of vortices were identified inside the runner. Three types were related to the inlet flow. The last one (Type 4) was caused by the reversed flow near the runner crown and had the lowest pressure inside the core near the runner outlet. Thus, in the blade channel vortex inception line, Type 4 vortex would appear earlier than the other three ones. Besides, the Type 4 vortex emerged from the crown and shed toward the blade-trailing edge. And its location moved from near the crown down to near the band when the unit speed increased or unit discharge decreased.

Although the refined mesh was used and the main vortices in the Francis runner were well predicted, the current mesh is not enough to accurately predict the lowest pressure in the channel vortex core.

This knowledge is instructive in the runner blade design and troubleshooting related to the channel vortex.

This study gives an overview of the main observed blade channel vortices and their causes, and points out the important role the reversed flow plays in the formation of blade channel vortices. This knowledge is instructive in the runner blade design and troubleshooting related to blade channel vortices.

The purpose of this paper is to design and implement a landmine detection robot (Venus) equipped with three electromagnetic sensors and controlled by ordered weighted averaging (OWA) sensor fusion approach. Higher numbers of detected mines in a fixed time interval and lower total power consumption are the achieved goals of this research.

OWA sensor fusion is exploited for data combination in this paper. Unlike most other landmine detection robots, Venus has three electromagnetic sensors, the positions of which can be adjusted according to the environmental conditions. Also, a novel approach for OWA weight dedication using Gaussian distribution function is applied and the whole idea is evaluated practically in several randomly mined fields. Finally, for better evaluation, performance of Venus is compared with the other two landmine detection robots.

The simulation and experimental results proved that in a predetermined interval of time, not only total energy consumption is reduced, but also by expanding the surface and the depth of influence of electromagnetic waves, the number of detected mines is considerably raised.

In contrast to the regular demining process, which is relatively expensive and complicated, the landmine detection method proposed in this research is surprisingly simple, cost effective, and efficient. Therefore, it may be attractive for every company or organization in this field of research.

The paper describes research which implements and evaluates a novel control approach based on OWA sensor fusion method, a new way of using Gaussian distribution function for determining OWA weights, and also an adaptive physical configuration for sensors based on environmental conditions.

In recent years, the application of artificial intelligence and digital technology has increasingly become a priority for online retailers. It is crucial to choose a way to make use of human–computer interaction (HCI) design to exert the positive influence of intelligent technology on consumer welfare. Despite the increasing use of HCI design in online retail context, there remain limitations in their effect of consumer well-being improvement. Although there is extensive literature in the field of consumer well-being improvement, few studies have empirically examined how HCI design drives the improvement of consumer well-being in the online retail context. Therefor, this study aims to deeply and systematically analyze the psychological mechanism between HCI and consumer well-being in the online retail environment.

The empirical analysis is based on data collection of 476 samples of online shoppers through the online survey method. From the perspective of autonomy, this study deeply analyzes the influence mechanism of different dimensions of HCI perception on consumer well-being.

The results indicated that autonomy plays a positive intermediary role in the impact of perceived connectivity, perceived personalization, perceived control and perceived responsiveness on the eudaimonia and hedonic enjoyment. Also, it revealed that psychological resistance negatively regulates the impact of perceived connectivity, perceived personalization and perceived control on autonomy, while experience purchase positively regulates the impact of autonomy on hedonic enjoyment.

This paper expands the research situation of consumer well-being by making integration of the dual structure of subjective well-being and psychological well-being to define the psychological mechanism and boundary conditions of the impact of HCI perception on consumer well-being. The main contribution of this study is to provide enlightenment for online retail enterprises to improve HCI design and help consumers enhance long-term well-being.