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An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the inspection robot cross obstacle automatically. This paper aims to propose an improved approach which is called adaptive homomorphic filter and supervised learning (AHSL) for overhead ground wire detection.

First, to decrease the influence of the varying illumination caused by the open work environment of the inspection robot, the adaptive homomorphic filter is introduced to compensation the changing illumination. Second, to represent ground wire more effectively and to extract more powerful and discriminative information for building a binary classifier, the global and local features fusion method followed by supervised learning method support vector machine is proposed.

Experiment results on two self-built testing data sets A and B which contain relative older ground wires and relative newer ground wire and on the field ground wires show that the use of the adaptive homomorphic filter and global and local feature fusion method can improve the detection accuracy of the ground wire effectively. The result of the proposed method lays a solid foundation for inspection robot grasping the ground wire by visual servo.

This method AHSL has achieved 80.8 per cent detection accuracy on data set A which contains relative older ground wires and 85.3 per cent detection accuracy on data set B which contains relative newer ground wires, and the field experiment shows that the robot can detect the ground wire accurately. The performance achieved by proposed method is the state of the art under open environment with varying illumination.

Purpose – The purpose of this study was to determine the efficacy value of national street lighting on energy conservation and carbon dioxide (CO₂) emission reduction.

Design/Methodology/Approach – The methods used are the measurement of electrical parameters (low voltage network), the national road illumination level with SON lamp specification, 400 W, 180 W, and 110 Lumen/W, the simulation of energy conservation calculation, and the CO₂ emission reduction obtained by utilizing panel solar cells as a source of energy and LED lights for illumination.

Finding – The results show the efficacy of a 100-W light bulb at an altitude of 8 m for the following specification of light bulbs: LED, 130 Lumens/W, SON, 110 Lumen/W, and MBF, 53 Lumen/W gives the illumination level respectively 13,913 Lux, 11,773 Lux, and 5,672 Lux. By replacing the 180 W SON lamp with an LED, 100 W, of energy conservation by 3.171 GW h is obtained, which is equivalent to a CO₂ emission reduction of 3.641 kTon CO₂.

Originality/Value – This study is a continuation of a study of energy conservation with the utilization of solar cells as an electrical power source for an LED bulb that replaces low-voltage networks as a power source for the bulb type SON.

Lubricating oil leakage is a common issue in thermal power plant operation sites, requiring prompt equipment maintenance. The real-time detection of leakage occurrences could avoid disruptive consequences caused by the lack of timely maintenance. Currently, inspection operations are mostly carried out manually, resulting in time-consuming processes prone to health and safety hazards. To overcome such issues, this paper proposes a machine vision-based inspection system aimed at automating the oil leakage detection for improving the maintenance procedures.

The approach aims at developing a novel modular-structured automatic inspection system. The image acquisition module collects digital images along a predefined inspection path using a dual-light (i.e. ultraviolet and blue light) illumination system, deploying the fluorescence of the lubricating oil while suppressing unwanted background noise. The image processing module is designed to detect the oil leakage within the digital images minimizing detection errors. A case study is reported to validate the industrial suitability of the proposed inspection system.

On-site experimental results demonstrate the capabilities to complete the automatic inspection procedures of the tested industrial equipment by achieving an oil leakage detection accuracy up to 99.13%.

The proposed inspection system can be adopted in industrial context to detect lubricant leakage ensuring the equipment and the operators safety.

The proposed inspection system adopts a computer vision approach, which deploys the combination of two separate sources of light, to boost the detection capabilities, enabling the application for a variety of particularly hard-to-inspect industrial contexts.

Mouth segmentation is one of the challenging tasks of development in lip reading applications due to illumination, low chromatic contrast and complex mouth appearance. Recently, deep learning methods effectively solved mouth segmentation problems with state-of-the-art performances. This study presents a modified Mobile DeepLabV3 based technique with a comprehensive evaluation based on mouth datasets.

This paper presents a novel approach to mouth segmentation by Mobile DeepLabV3 technique with integrating decode and auxiliary heads. Extensive data augmentation, online hard example mining (OHEM) and transfer learning have been applied. CelebAMask-HQ and the mouth dataset from 15 healthy subjects in the department of rehabilitation medicine, Ramathibodi hospital, are used in validation for mouth segmentation performance.

Extensive data augmentation, OHEM and transfer learning had been performed in this study. This technique achieved better performance on CelebAMask-HQ than existing segmentation techniques with a mean Jaccard similarity coefficient (JSC), mean classification accuracy and mean Dice similarity coefficient (DSC) of 0.8640, 93.34% and 0.9267, respectively. This technique also achieved better performance on the mouth dataset with a mean JSC, mean classification accuracy and mean DSC of 0.8834, 94.87% and 0.9367, respectively. The proposed technique achieved inference time usage per image of 48.12 ms.

The modified Mobile DeepLabV3 technique was developed with extensive data augmentation, OHEM and transfer learning. This technique gained better mouth segmentation performance than existing techniques. This makes it suitable for implementation in further lip-reading applications.

The paper aims to solve the problem of personnel intrusion identification within the limits of high-speed railways. It adopts the fusion method of millimeter wave radar and camera to improve the accuracy of object recognition in dark and harsh weather conditions.

This paper adopts the fusion strategy of radar and camera linkage to achieve focus amplification of long-distance targets and solves the problem of low illumination by laser light filling of the focus point. In order to improve the recognition effect, this paper adopts the YOLOv8 algorithm for multi-scale target recognition. In addition, for the image distortion caused by bad weather, this paper proposes a linkage and tracking fusion strategy to output the correct alarm results.

Simulated intrusion tests show that the proposed method can effectively detect human intrusion within 0–200 m during the day and night in sunny weather and can achieve more than 80% recognition accuracy for extreme severe weather conditions.

(1) The authors propose a personnel intrusion monitoring scheme based on the fusion of millimeter wave radar and camera, achieving all-weather intrusion monitoring; (2) The authors propose a new multi-level fusion algorithm based on linkage and tracking to achieve intrusion target monitoring under adverse weather conditions; (3) The authors have conducted a large number of innovative simulation experiments to verify the effectiveness of the method proposed in this article.

The present shift and change in the human lifestyle across the world are undeniable. Currently, individuals spend a substantial amount of time indoors due to the global COVID-19 pandemic that strikes the entire world. This change in human lifestyle has devastating effects on human health and productivity. As a result, the influence of indoor environmental quality (IEQ) on the health and productivity of building users becomes a critical field of research that requires immediate attention. As a result, the purpose of this study is to review the state-of-the-art literature by establishing a connection between the factors that influence health and productivity in any given indoor environment.

The methodology involves a thorough review of selected published journals from 1983 to 2021, and the result was analysed through content analysis. The search included journal articles, books and conference proceedings on the critical factors influencing IEQ and their impact on building occupants, which was sourced from different databases such as ScienceDirect, Taylor, GoogleScholar and Web of Science.

The findings from the 90 selected articles revealed four critical factors influencing the quality of the indoor environment and are categorised into; indoor air quality, indoor thermal comfort, visual comfort and acoustic comfort. The findings suggested that when developing a system for controlling the quality of the indoor environment, the indoor air quality, indoor thermal comfort, visual comfort and acoustic comfort should be taken into account.

The indoor environment deeply impacts the health of individuals in their living and work environments. Industry must have a moral responsibility to provide health facilities in which people and workers feel satisfies and give conditions for prosperity. Addressing these essential aspects will not only help the decision-making process of construction professionals but also encourages innovative construction techniques that will enhance the satisfaction, wellness and performance of building occupants.

The health and environmental hazards associated with synthetic dyes have led to a revival of natural dyes that are non-toxic, environmentally benign and coupled with various functions. The study aims to investigate and develop the potentiality of a popular herb called Chromolaena odorata (C. odorata) as a sustainable and stable dyestuff in textiles.

Natural colorant extracted from C. odorata leaves is used to dye the worsted fabric, which is one of the premier end-use of wool in fashion, via the padding method associated with pre-, simultaneous and post-mordanting with chitosan, tannic acid and copper sulfate pentahydrate. The effects of extraction, dyeing and mordanting processes on fabric’s color strength K/S and color difference ΔE_CMC are investigated via International Commission on Illumination’s L*a*b* color space, Fourier transform infrared spectroscopy, scanning electron microscope, color fastness to washing, rubbing, perspiration and light.

The results obtained indicate extraction with ethanol 90% with a solid/liquid ratio of 1:5 within 1 h, and coloration with a liquor ratio of 1:5 (pH 5) within 2 h under padding pressure of 0.3 MPa are the most effective for coloring worsted fabric.

The C. odorata’s application as a highly effective dyestuff possessing good colorimetric effectiveness has expanded this herb's economic potential, contributing partly to economic growth and adding value to wool in global supply chain.

C. odorata dyestuff has prevailed over other natural colorants because of its impressive color fastness against washing, rubbing, perspiration and especially color stability for pH change.

The authors argue that the mainstream scholarly discourse on hybridity and accounting is thus far primarily interested in the use and effects of accounting “in” hybrid organizations. Consequently, the literature has to a lesser extent explored how accounting mediates hybrid settings (while also being mediated), and the role of disentanglements in such processes. In hybrid settings, objects are difficult to define, and measures and tools difficult to agree upon. However, the literature on hybrid accounting is inconclusive and indicates that accounting can potentially both stabilize and de-stabilize relations in a hybrid setting. The authors address the research question of how accounting emerges and manifests itself in a process of entangling and disentangling in a heterogeneous emerging hybrid setting.

The paper is based on a longitudinal qualitative case study of the implementation of social investments, a public sector calculative framework based on the logic of measuring long term and social and economic impact of prevention. Methodologically, the study was guided by actor-network theory. In total, 18 observations and 48 interviews were conducted.

The observation the authors make in their case study is that much effort was spent on both keeping things apart and tying elements together. What the authors add to the literature is an illumination of how the interplay between entanglements and disentanglements facilitated the design idea of social investments to be enacted as multiple semi-integrated and purified hybridizations. The authors describe different translation points, each representing a specific hybridization where elements were added, recombined and disentangled. Still, the translation points were not completely compartmentalized, but rather semi-integrated where associations were facilitated through active mediation, likeness and productiveness for each other.

One limitation is the single case approach. A second limitation arises from the ANT approach to hybridity.

A practical implication of this paper is that in hybrid settings, the semi-integrated character may be interpreted as a strength because it allows the mobilization of heterogenous actors. However, this may also come at the cost of governability and raises further questions of managerial practices in hybrid settings.

The paper suggests the potentially productive role of disentanglements in allowing multiple hybridizations to evolve in hybrid accounting settings.

The paper suggests the potentially productive role of disentanglements in allowing multiple stabilized hybridizations to evolve in hybrid accounting settings.

The emergence of COVID-19 has exacerbated and spurred the growth of mental health issues in ways that have challenged mental health workers tremendously. The complex nature of COVID-19 has made the need of mental health professionals extremely important. Hospital ward overcrowding, social distancing requirements, sequestrations, limits to face-to-face consultations have created barriers to mental health access, especially those in need of Certified Peer Recovery Specialists. Certified Peer Recovery Specialists play a critical role in the treatment of mental illness through their support and engagement of those recovering from substance abuse. Many in this role are hired because they have a strong skillset for help-oriented clinical work but are often challenged, especially in times like this to development and demonstrate leadership skills. This paper explores the nature and need to develop leadership skills and leadership challenges for people in this field through interpretative phenomenological analysis (IPA) and a content analysis of the current and seminal literature.

This paper explores the nature and need to develop leadership skills and leadership challenges for people in mental health through IPA and a content analysis of the current and seminal literature.

The essential necessity to invest in the cultivation of peer recovery specialists and mental health professionals as organizational leaders.

Hospital ward overcrowding, social distancing requirements, sequestrations, limits to face- to- face consultations have created barriers to mental health access, especially those in need of Certified Peer Recovery Specialists. Certified Peer Recovery Specialists play a critical role in the treatment of mental illness through their support and engagement of those recovering from substance abuse.

In the cylinders of a marine diesel engine, self-ignition occurs in a very short time after the fuel injection into the combustion chamber. Therefore, this paper aims to develop a model of diesel fuel spray for the early stage of fuel spray in the marine diesel engine. The main technical aspects such as nozzle diameter of the marine engine injector and backpressure in the combustion chamber were taken into consideration.

In this paper, laboratory experimental studies were carried out to determine parameters of fuel spray in an early stage of injection in the marine diesel engine. The optical measuring Mie scattering technique was used to record the fuel injection process. The working space was a constant volume chamber. The backpressure parameters in the constant volume chamber were the same as during the operation of the marine diesel engine. Based on the experimental studies and important Hiroyasu and Arai models of fuel spray presented in literature was proposed new model of fuel spray parameters for marine diesel injectors.

In this paper, the proposed new model of the two main parameters described fuel spray evolution”: new model of spray tip penetration (STP) and spray cone angle (SCA). New model propagation of fuel STP in time was included the influence of nozzle diameter and backpressure. The proposed model has a lower error, about 15%–34%, than the model of Hiroyasu and Arai. Moreover, a new model of the evolution over time of the SCA is developed.

In the future research of fuel spray process must be taken influence of the fuel temperature. Diesel fuel has a different density and viscosity in dependence of fuel temperature. Therefore are predicted of the expansion about influence of fuel temperature, new model of fuel spray for a marine diesel engine. The main limitations occurring in the research are not possible to carry out the research while real operation marine diesel engine.

An experimental test was carried out for a real fuel injector of a marine diesel engine. Design parameters and fuel injection parameters were selected on the basis of the actual one. In the literature, SCA is defined as a constant parameter for the specific preliminary data. A new model for the early stage of fuel spray of SCA propagation in time has been proposed. The early stage of fuel spray is especially important, because in this time comes in there to fuel self-ignition.