Search Results (51)

To explore effects of sleep restriction (SR) on next-morning cognitive recovery of young males under thermoneutral environments, three SR conditions, namely the mild (ending at 01:20), moderate (ending at 02:30) and severe sleep restriction (ending at 03:40), were carried out on participants in a thermoneutral environment. During experiments, the subjective sleepiness, perceived workload, and thermal sensation were surveyed. Electrocardiogram (ECG) data were recoded continuously to conduct the heart rate variability (HRV) analysis. In addition, the Deary–Liewald task (including the Simple Response Time task and the Choice Response Time task), Stroop task and Corsi Block task were completed. Results revealed significant increases in sleepiness and perceived workloads during SR. In addition, mean heart rate reduced significantly during moderate (ΔHR = −9.48, p < 0.05) and severe SRs (ΔHR = −9.69, p < 0.01), although it returned to the baseline level in the next morning. The root mean square of successive differences (RMSSD) was elevated during all SRs (Mild SR ΔRMSSD = 27.34, p < 0.05; Moderate SR ΔRMSSD = 33.06, p < 0.01; Severe SR ΔRMSSD = 24.61, p < 0.05) but reduced to baseline the next morning. Furthermore, the sustained attention (SRT) and selective attention performances (CRT) were impaired significantly under moderate (SRT ΔPI = −0.59, p < 0.05; CRT ΔPI = −0.24, p < 0.05) and severe SR (SRT ΔPI = −0.39, p < 0.05; CRT ΔPI = −0.42, p < 0.01). However, the sustained attention performance was restored the next morning even after severe SR, whereas the selective attention performance remained impaired (ΔPI = −0.36, p < 0.01). Significant reductions were observed in the Stroop task performance only after the severe SR (ΔPI = −0.17, p < 0.05), while short-term memory was slightly affected either during or after all SRs (p > 0.05). The overall cognitive performance reduced significantly after the moderate and severe SRs (Moderate SR ΔOPI = −0.30, p < 0.05; Severe SR ΔOPI = −0.40, p < 0.05), even in the next morning. Findings suggest that cognitive impairments caused by mild and moderate SRs could be partially recovered the next morning, while severe SR produced significant impairments in complex cognitive functions, potentially linked to parasympathetic dysregulation and failure of prefrontal compensatory mechanisms. Preliminary findings from this study offer initial implications for cognitive preservation strategies in office environments after night-time overwork. Full article

The Internet of Things produces vast amounts of data that require specialized algorithms in order to secure them. Lightweight cryptography requires ciphers designed to work on resource-constrained devices like sensors and smart things. A new encryption scheme is introduced based on a blend of the best-performing algorithms, SIMECK and TEA. A selection of software-oriented Addition–Rotation–XOR (ARX) block ciphers are augmented with a dynamic substitution security layer. The performance is compared against other lightweight approaches. The US National Institute of Standards and Technology (NIST) SP800-22 Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications and the German AIS.31 of the Federal Office for Information Security (BSI) are used to validate the output of the proposed encryption scheme. The law of iterated logarithm (LIL) for randomness is verified in all three forms. The total variance (TV), the Hellinger Distance (HD), and the root-mean-square deviation (RMSD) show values smaller than the required limit for 10.000 sequences of ciphertext. The performance evaluation is analyzed on a Raspberry PICO 2040. Several security metrics are compared against other ciphers, like ${\chi }^2$ and encryption quality (EQ). The results show that SIMECK-T is a powerful and fast, software-oriented, lightweight cryptography solution. Full article

Conventional weather forecasting relies on numerical weather prediction (NWP), which solves atmospheric equations using numerical methods. The Korea Meteorological Administration (KMA) adopted the Met Office Global Seasonal Forecasting System version 6 (GloSea6) NWP model from the UK and runs it on a supercomputer. However, due to high task demands, the limited resources of the supercomputer have caused job queue delays. To address this, the KMA developed a low-resolution version, Low GloSea6, for smaller-scale servers at universities and research institutions. Despite its ability to run on less powerful servers, Low GloSea6 still requires significant computational resources like those of high-performance computing (HPC) clusters. We integrated deep learning with Low GloSea6 to reduce execution time and improve meteorological research efficiency. Through profiling, we confirmed that deep learning models can be integrated without altering the original configuration of Low GloSea6 or complicating physical interpretation. The profiling identified “tri_sor.F90” as the main CPU time hotspot. By combining the biconjugate gradient stabilized (BiCGStab) method, used for solving the Helmholtz problem, with a deep learning model, we reduced unnecessary hotspot calls, shortening execution time. We also propose a convolutional block attention module-based Half-UNet (CH-UNet), a lightweight 3D-based U-Net architecture, for faster deep-learning computations. In experiments, CH-UNet showed 10.24% lower RMSE than Half-UNet, which has fewer FLOPs. Integrating CH-UNet into Low GloSea6 reduced execution time by up to 71 s per timestep, averaging a 2.6% reduction compared to the original Low GloSea6, and 6.8% compared to using Half-UNet. This demonstrates that CH-UNet, with balanced FLOPs and high predictive accuracy, offers more significant execution time reductions than models with fewer FLOPs. Full article

This paper investigated an application of adjustable photovoltaic (PV) slats to improve the thermal performance of an exposed glazing window and sequentially enhance the energy efficiency and thermal comfort of an office room. Solar radiation and longwave heat gains from a window fitted with PV slats were measured through experiments conducted in an outdoor chamber cooled by a radiant ceiling system. The daylight level at the workplane was also measured inside the chamber. A transient thermal model was developed and validated against experimental data. Using the experimental chamber as a demonstration case, the model revealed that adjusting the slats monthly to fully block direct sunlight could reduce the electrical energy use by 67% compared to a typical office with heat reflective glass windows. However, the electricity generated by the PV slats contributed a minor portion of the overall energy savings. To assess the thermal comfort impact of the PV slats in the room with the radiant cooling, this study utilized radiation asymmetry criteria from ASHRAE Standard 55. Simulations showed that the PV slat-shaded glazing window resulted in a lower asymmetric plane radiant temperature than the unshaded window of heat reflective glass. The adjustable slat system reduced the risk of local discomfort for occupants working near the window in the radiantly cooled office room. Full article

Humanoid robots are increasingly being utilized in various activities involving humans, as they can facilitate certain tasks and provide benefits to users. Humanoid service robots possess capabilities akin to human performance, often proving advantageous due to their operational speed and immunity to fatigue. Within the scope of this study, Pepper, a humanoid robot renowned for its fidelity in mimicking human gestures and behavior, serves as the focal point. Tasked with aiding office occupants in object manipulation and relocation, Pepper underwent a targeted reliability assessment. This assessment encompassed the development of a reliability block diagram (RBD), alongside meticulous analyses of individual components and system functionality across diverse operational scenarios. Full article

There has been a wide belief that real estate is a source of good investment portfolios because it has a hedge against inflation. Considering this notion, the present research examined the dynamics of the inflation-hedging capabilities of real estate investment in Nigeria’s three foremost property markets, Abuja (Maitama and Central Business District), Lagos (Lekki and Victoria Island), and Port Harcourt (Rumu Ibekwe and Aba Road). To achieve this aim, this study was carried out by exploring the returns on different types of commercial properties in the chosen location and investigating the effect of inflation on such returns in order to come up with the hedging capabilities of the assets. Out of the four property prime locations in Nigeria’s market, these selected study sites were purposely selected for investigation because they comprise the most desirable and preferred properties regarding location, standards, aesthetics, and value. From the data collected, a mean return, coefficient of variation, and ordinary least square regression analysis were completed. In terms of the coefficient of variation (CV), the findings reveal that the duplex in Port Harcourt exhibits the most performed investment, with a value of 0.33, compared to other locations. However, in terms of the expected return (ER), the duplex outperformed other property types in the different locations, with a return of 39.56%. Results also show that inflation has an adverse effect on the returns of the office space for the three locations considered, with the expected returns below 1%. The block of flats in Abuja has a complete defence against the three components of inflation, with a coefficient beta of 0.5633, 0.6586, and 0.8440, respectively. Thus, investors should consider inflation and other investment attributes when making decisions among arrays of investments. This will help guard against the widespread perception that real estate has a hedge against inflation. This paper adds to the existing literature on inflation hedging by investigating the effect of inflation on the real estate investment returns of commercial properties. Full article

Headache is a leading cause of disability and suffering. One major challenge in developing device treatments is demonstrating their efficacy given devices’ often-high placebo rate. This paper reviews the importance of validating sham devices as part of finalizing the design for larger-scale prospective randomized controlled trials in patients with chronic headache as well as the results of a prospective, single-blind trial to validate two potential sham noninvasive thermal nerve block devices. Study participants were trained to self-administer thermal nerve block treatment using sham devices in an office visit. Two different sham systems with different temperature profiles were assessed. Devices were offered for patients to use daily at-home for one week to assess the durability of sham placebo effects before participants were given active treatment in a second office visit followed by another optional week of self-administered active treatment at-home use. Sham treatments reduced pain scores by an average of 31% from 6.0 ± 2.3 to 4.3 ± 3.3, including two participants who fell asleep during the in-office treatment and woke up with no pain, but whose pain recurred after returning home during at-home use of the sham system. In-office active treatments reduced pain scores by 52% from 6.7 ± 2.1 to 3.3 ± 2.9 with sustained pain relief during optional at-home use. Successful blinding for the study was confirmed with an ideal Bang’s Blinding Index of 0 and an ideal James’ Blinding Index of 1. Both the sham and active treatments were viewed by participants as highly credible, and credibility increased from the beginning to end of sham treatments on average. Full article

Block morphology refers to critical parameters influencing building energy performance on the block scale. However, analysis of the combined effect of block morphological parameters on building energy consumption with real blocks is lacking. In this paper, the aim is to evaluate the combined effect of office block morphology on building energy consumption in the context of the Hot-summer and Cold-winter zone in China. First, a workflow for the energy assessment of office buildings with the coupled block morphology on the block scale was proposed with evaluation tools. Seventy office blocks in Wuhan were taken as examples and then classified based on building layout typology and building height. Afterwards, the morphological parameters and building energy use intensity (EUI) for different blocks were calculated. Then, the combined effect of block morphology on the buildings’ energy consumption was evaluated and the model on predicting the building energy consumption of office blocks was proposed. Finally, based on the results, low-energy design strategies were projected for office blocks. The results illustrated that the effect of block morphology on building cooling, heating, and lighting is EUI 28.83%, 28.56%, and 23.23%, respectively. Building shape factor (BSF), floor area ratio (FAR), average building height of block (BH), and average building depth of block (BD) are effective block morphological parameters. The key morphological parameters which combined affect the building energy consumption of office blocks are BSF and FAR; BSF has 1.24 times the effect on building energy consumption than FAR. The workflow built in this paper can be applied to other cities around the world for promoting sustainable cities. Full article

With the outbreak of COVID-19, epidemic prevention has become a way to prevent the spread of epidemics. Many public places, such as hospitals, schools, and office places, require disinfection and temperature measurement. To implement epidemic prevention systems and reduce the risk of infection, it is a recent trend to measure body temperature through non-contact sensing systems with thermal imaging cameras. Compared to fingerprints and irises, face recognition is accurate and does not require close contact, which significantly reduces the risk of infection. However, masks block most facial features, resulting in the low accuracy of face recognition systems. This work combines masked face recognition with a thermal imaging camera for use as an automated attendance system. It can record body temperature and recognize the person at the same time. Through the designed UI system, we can search the attendance information of each person. We not only provide the design method based on convolutional neural networks (CNNs), but also provide the complete embedded system as a real demonstration and achieve a 94.1% accuracy rate of masked face recognition in the real world. With the face recognition system combined with a thermal imaging camera, the purpose of screening body temperature when checking in at work can be achieved. Full article

This research presents a comparative study of different bio-sourced and recycled insulation materials and their impact on energy consumption of office buildings located in Ouagadougou, a city with a dry hot climate. A thorough assessment of the country’s meteorological and urban development data from 2004 to 2018 was conducted for climatic data. EnergyPlus was used for thermal comfort based on the American Society of Heating, Refrigerating, and Air-conditioning Engineers Standard (ASHRAE) 55 adaptive comfort model and energy analysis by calculating and comparing the yearly energy consumption, heat transfer through the building envelope, and discomfort degree hours. A four-story “H”-shaped office building made of cement blocks with a fixed north–south orientation and a 30% window-to-wall ratio served as the base case for this study to perform two rounds of multiple simulations and evaluate the most effective insulation material. First, exterior walls were insulated, and then the roof and inner floors were insulated using the best material from the first round. The findings confirmed hemp wool as the best performing bio-sourced insulation material, which reduces by 25.8% and 17.7% the annual cooling energy demand at 114,495 kWh and the annual energy consumption at 203,598 kWh, respectively, contributing to saving up to 43,852 kWh in annual energy consumption. Hemp wool impacted wall, roof, and internal floor heat transfer by reducing them by 90.86% at 12,583 kWh, 85.1% at 6666 kWh, and 88.1% at −2664 kWh, respectively, while the discomfort degree hours were reduced by 17.6% at 9720.12. The outcomes provide patterns, explanations, and inferences that may be generalized to other projects in Burkina Faso, especially, and sub-Saharan African countries, in general, where most buildings are not well insulated. The availability of these bio-based and recycled insulation materials may also serve as proof to foster a circular economy in the Burkina Faso construction industry. Full article

Under the umbrella of assistive technologies research, a lot of different platforms have appeared since the 1980s, trying to improve the independence of people with severe mobility problems. Those works followed the same path coming from the field of robotics trying to reach users’ needs. Nevertheless, those approaches rarely arrived on the market, due to their specificity and price. This paper presents a new prototype of an intelligent wheelchair (IW) that tries to fill the gap between research labs and market. In order to achieve such a goal, the proposed solution balances the criteria of performance and cost by using low-cost hardware and open software standards in mobile robots combined together within a modular architecture, which can be easily adapted to different profiles of a wide range of potential users. The basic building block consists of a mechanical chassis with two electric motors and a low-level electronic control system; driven by a joystick, this platform behaves similar to a standard electrical wheelchair. However, the underlying structure of the system includes several independent but connected nodes that form a distributed and scalable architecture that allows its adaptability, by adding new modules, to tackle autonomous navigation. The communication among the system nodes is based on the controller area network (CAN) specification, an extended standard in industrial fields that have a wide range of low-cost devices and tools. The system was tested and evaluated in indoor environments and by final users in order to ensure its usability, robustness, and reliability; it also demonstrated its functionality when navigating through buildings, corridors, and offices. The portability of the solution proposed is also shown by presenting the results on two different platforms: one for kids and another one for adults, based on different commercial mechanical platforms. Full article

The growth in the number of automobiles in metropolitan areas has drawn attention to the need for more efficient carpark control in public spaces such as healthcare, retail stores, and office blocks. In this research, dynamic pricing is integrated with real-time parking data to optimise parking utilisation and reduce traffic jams. Dynamic pricing is the practice of changing the price of a product or service in response to market trends. This approach has the potential to manage car traffic in the parking space during peak and off-peak hours. The dynamic pricing method can set the parking fee at a greater price during peak hours and a lower rate during off-peak times. A method called deep reinforcement learning-based dynamic pricing (DRL-DP) is proposed in this paper. Dynamic pricing is separated into episodes and shifted back and forth on an hourly basis. Parking utilisation rates and profits are viewed as incentives for pricing control. The simulation output illustrates that the proposed solution is credible and effective under circumstances where the parking market around the parking area is competitive among each parking provider. Full article

Decentralized, smart indoor cultivation systems can produce herbs and vegetables for fresh and healthy daily nutrition of the urban population. This study assesses technical and resource requirements, productivity, and economic viability of the “Smart Office Farm” (SOF), based on a 5-week production cycle of curled lettuce, lolo rosso, pak choi and basil at three photosynthetic photon flux density (PPFD) levels using a randomized block design. The total fresh matter yield of consumable biomass of all crops was 2.5 kg m⁻² with operating expenses (without labor costs) of EUR 53.14 kg⁻¹; more than twice as expensive compared to large-scale vertical farm and open-field cultivation. However, there is no need to add trade margins and transportation costs. The electricity supply to SOF is 73%, by far the largest contributor to operational costs of office-based crop production. Energetic optimizations such as a more homogeneous PPFD distribution at the plant level, as well as adaptation of light quality and quantity to crop needs can increase the economic viability of such small indoor farms. With reduced production costs, urban indoor growing systems such as SOF can become a viable option for supporting fresh and healthy daily nutrition in urban environments. Full article

As a systematic, preventive, and structural adjustment method of improving building energy conservation and carbon emission reduction, urban planning has received extensive attention. However, due to the insufficient interface between energy-saving technology and urban planning systems, urban planning has not properly played a role in building energy conservation. Scientific and innovative technical methods are urgently needed to explore the role of coordinating multiple effective planning elements in overall building energy conservation through urban planning means. Due to climate conditions, there is high demand for conserving building energy in severe cold regions, but research into this has not been thoroughly carried out. Harbin, located in the northeast of China, belongs to the Dwa zone of the Köppen–Geiger Climate Classification, and is also a typical city of severe cold regions where the daily average temperature is lower than 5 °C for more than 145 days in a year. This study takes Harbin as an example and uses agent-based modeling to establish an urban-scale building energy consumption simulation model. The model contains four types of agents (a global agent, building agent, residential agent, and household equipment agent) and two types of influence factor modules (an urban form module and a climate module). Three simulation scenarios were designed, including a baseline scenario, an urban form scenario, and a climate scenario. The baseline scenario provided an overview of the urban-scale building energy consumption distribution characteristics of Harbin and served as a reference group for the simulation results of other scenarios. The urban form scenario results show that when the elements with a highly significant impact change by 1 unit, the retail building block has the most obvious change in energy consumption, up to 44.7 × 10⁶ kWh/10⁵ m²/year, while the office building block has the lowest change, with 34.5 × 10³ kWh/10⁵ m²/year. The fluctuation of electricity is the most obvious, but the total change is lower than the heating energy consumption. The climate scenario shows that the energy consumption of residential land in urban centers will consistently rise in the next 50 years, up to 5.3 × 10⁵ kWh/10⁵ m²/year. Based on these results, this study puts forward future building energy conservation planning strategies for Harbin, focusing on three aspects: the planning and control of urban form, the optimization and adjustment of the climate, and the building energy conservation planning system. These research results are expected to provide scientific support for transforming Harbin into a low-carbon city. Full article

In the context of the COVID-19 global epidemic, it is particularly important to use limited medical resources to improve the systemic control of infectious diseases. There is a situation where a shortage of medical resources and an uneven distribution of resources in China exist. Therefore, it is important to have an accurate understanding of the current status of the healthcare system in China and to improve the efficiency of their infectious disease control methods. In this study, the MP-SBM-Shannon entropy model (modified panel slacks-based measure Shannon entropy model) was proposed and applied to measure the disposal efficiency of the medical institutions responding to public health emergencies (disposal efficiency) in China from 2012 to 2018. First, a P-SBM (panel slacks-based measure) model, with undesirable outputs based on panel data, is given in this paper. This model measures the efficiency of all DMUs based on the same technical frontier and can be used for the dynamic efficiency analysis of panel data. Then, the MP-SBM model is applied to solve the specific efficiency paradox of the P-SBM model caused by the objective data structure. Finally, based on the MP-SBM model, undesirable outputs are considered in the original efficiency matrix alignment combination for the deficiencies of the existing Shannon entropy-DEA model. The comparative analysis shows that the MP-SBM-Shannon model not only solves the problem of the efficiency paradox of the P-SBM model but also improves the MP-SBM model identification ability and provides a complete ranking with certain advantages. The results of the study show that the disposal efficiency of the medical institutions responding to public health emergencies in China shows an upward trend, but the average combined efficiency is less than 0.47. Therefore, there is still much room for improvement in the efficiency of infectious disease prevention and control in China. It is found that the staffing problem within the Center for Disease Control and the health supervision office are two stumbling blocks. Full article