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With the continual acceleration of urbanization, the amount of urban infrastructure and the quality of public services are increasing in many cities. A pressing concern in this context is the growing problem of incompatible fire protection construction, indicating a need for urban fire stations with well-planned layouts. However, research on optimizing the layout and placement of fire stations by considering the various factors affecting station layouts is lacking. The current study addressed this gap by establishing an optimal fire station layout by using a geographic information system (GIS) and elucidated the trends of GIS application in firefighting and rescue operations. The study’s findings reveal the benefits of avoiding blind spots, enhancing the selection of fire station sites, and optimizing service coverage. Furthermore, this study optimized the layout of CZ city’s downtown fire stations, which could enhance CZ city’s firefighting capabilities.

This aim of this research was to explore the appraisal of the use of smart alert bracelets by older adults diagnosed with dementia. Convenience sampling was adopted to recruit older adults with dementia in Yunlin County, Taiwan. A manual questionnaire survey was conducted, and SPSS 26.0 statistical software was used for analysis. The results of this study showed noticeable positive correlation results in the post-test for the modes “wearing device”, “degree of dementia”, and “field configuration”. Based on the experimental results, the following suggestions are provided: (1) in terms of statistical calculation, the statistical results were affected by changes in some participants; (2) as for the design of equipment, to be more suitable for adult use, the size and color of bracelets need to be optimized; (3) as for the problem of battery charging of the device, because the charging location of the device is not easy to find, it is better to extend device standby time; (4) regarding the selection of equipment, older adults with early-stage dementia could be concerned about the function of the wearable device, so it is recommended to provide a device designed with clear functions, such as a watch, so that older adults are more willing to wear it. Patients diagnosed with moderate and severe dementia should be advised to use concealed non-sensory devices, such as charms and cards, to better facilitate assistance from caregivers in wearing them; and (5) as for the device, in case of a loss event, in addition to mobile phone notifications, other light and sound device notifications can be added, allowing caregivers to pay more attention to information in real time. In summary, the feedback from caregivers and older adults suggests that if the device is to be used without charging, the overall design should be light and small, which is more suitable for service designs.

In recent decades, fractional order calculus has become an important mathematical tool for effectively solving complex problems through better modeling with the introduction of fractional differential/integral operators; fractional order swarming heuristics are also introduced and applied for better performance in different optimization tasks. This study investigates the nonlinear system identification problem of the input nonlinear control autoregressive (IN-CAR) model through the novel implementation of fractional order particle swarm optimization (FO-PSO) heuristics; further, the key term separation technique (KTST) is introduced in the FO-PSO to solve the over-parameterization issue involved in the parameter estimation of the IN-CAR model. The proposed KTST-based FO-PSO, i.e., KTST-FOPSO accurately estimates the parameters of an unknown IN-CAR system with robust performance in cases of different noise scenarios. The performance of the KTST-FOPSO is investigated exhaustively for different fractional orders as well as in comparison with the standard counterpart. The results of statistical indices through Monte Carlo simulations endorse the reliability and stability of the KTST-FOPSO for IN-CAR identification.

The efficient parameter estimation of harmonics is required to effectively design filters to mitigate their adverse effects on the power quality of electrical systems. In this study, a fractional order swarming optimization technique is proposed for the parameter estimation of harmonics normally present in industrial loads. The proposed fractional order particle swarm optimization (FOPSO) effectively estimates the amplitude and phase parameters corresponding to the first, third, fifth, seventh and eleventh harmonics. The performance of the FOPSO was evaluated for ten fractional orders with noiseless and noisy scenarios. The robustness efficiency of the proposed FOPSO was analyzed by considering different levels of additive white Gaussian noise in the harmonic signal. Monte Carlo simulations confirmed the reliability of the FOPSO for a lower fractional order (λ = 0.1) with a faster convergence rate and no divergent run compared to other fractional orders as well as to standard PSO (λ = 1).

The knacks of evolutionary and swarm computing paradigms have been exploited to solve complex engineering and applied science problems, including parameter estimation for nonlinear systems. The population-based computational heuristics applied for parameter identification of nonlinear systems estimate the redundant parameters due to an overparameterization problem. The aim of this study was to exploit the key term separation (KTS) principle-based identification model with adaptive evolutionary computing to overcome the overparameterization issue. The parameter estimation of Hammerstein control autoregressive (HC-AR) systems was conducted through integration of the KTS idea with the global optimization efficacy of genetic algorithms (GAs). The proposed approach effectively estimated the actual parameters of the HC-AR system for noiseless as well as noisy scenarios. The simulation results verified the accuracy, convergence, and robustness of the proposed scheme. While consistent accuracy and reliability of the designed approach was validated through statistical assessments on multiple independent trials.

To prevent and mitigate chemical risks in the petrochemical industry, such as fires and spillage, process safety management (PSM), is essential, especially where flammable, corrosive, explosive, toxic, or otherwise dangerous chemicals are used. We investigated process safety (PS) between man⁻machine (material equipment) and environmental interfaces by using process hazard analysis (PHA) and fault tree analysis (FTA). By analyzing the data obtained through machinery and mechanical integrity (MI), pre-startup safety review (PSSR), current operating modes, and areal locations of hazardous atmospheres (ALOHA) simulations of the disaster’s aftermath, the cause of the styrene plant accident was found to be the fuel furnace (F101) switching process. Although the furnace had been extinguished, fuel continued to enter the furnace, and it was exposed to a high-temperature surface, resulting in the flashing ignition of the C4 fuel. The plan-do-check-act (PDCA) management model can be used to forestall the system from accident, and it is used to improve the proposal and develop countermeasures that would increase PSM performance and substantially lessen the impact of the thermal hazard. Disasters are often attributable to the unsafe state of machinery, equipment, or the environment, dangerous behaviors of the operator, and the lack of a thorough management system. It is anticipated that the investigation and analysis of the accident would not only find the real cause of the disaster but also lead to the establishment of better effective solutions for common safety problems.

Many thermal runaway incidents have been caused by organic peroxides due to the peroxy group, –O–O–, which is essentially unstable and active. Lauroyl peroxide (LPO) is also sensitive to thermal sources and is incompatible with many materials, such as acids, bases, metals, and ions. From the thermal decomposition reaction of various concentrations of nitric acid (HNO3) (from lower to higher concentrations) with LPO, experimental data were obtained as to its exothermic onset temperature (T0), heat of decomposition (ΔHd), isothermal time to maximum rate (TMRiso), and other safety parameters exclusively for loss prevention of runaway reactions and thermal explosions. As a novel finding, LPO mixed with HNO3 can produce the detonation product of 1-nitrododecane. We used differential scanning calorimetry (DSC), thermal activity monitor III (TAM III), and gas chromatography/mass spectrometer (GC/MS) analyses of the reactivity for LPO and itself mixed with HNO3 to corroborate the decomposition reactions and reaction mechanisms in these investigations.

To understand the propagation characteristics of methane-air deflagration flames and in an obstacle-filled tube, a high-speed color video camera, photoelectric sensors, and pressure transducers were used to test the deflagration flame propagating parameters. The tests were run in a 1500 mm long plexiglass tube with a 100 × 100 mm square cross-section. The obstacles included four types of repeated baffles and five forms of solid structure obstacles. The results showed that: (1) the flame front was constantly distorted, stretched, and deformed by different types of obstacles and, consequently, the flame propagating parameters increased; (2) plates and triple prisms increased the speed of the flame and overpressure to the highest extent, whereas cuboids and quadrangulars exerted an intermediate effect. However, the effect of cylindrical obstacles was comparatively limited. It was suggested that the obstacle’s surface edge mutation or curvature changes were the main factors stimulating the flame acceleration; (3) the peak pressure of deflagration was relatively low near the ignition end, increased gradually until it reached the maximum at the middle of the tube, and decreased rapidly near the open end; and (4) the fixed obstacles in front of the flame exhibited a blocking effect on flame propagation during the initial stages; the flame speed and overpressure increased when the flame came into contact with the obstacles. This study is of significance because it explains the methane-air propagation mechanism induced by different types of obstacles. The findings have value for preventing or controlling gas explosion disasters.