Search Results (2,267)

Polyurethane materials, widely used in indoor environments, occasionally exhibit unpleasant odors. An important source of polyurethane odorants is polyether polyols. Previous studies identified odorous 2-ethyldimethyl-1,3,6-trioxocanes in polyurethane materials and polyols but did not investigate the odor activity of the individual isomers. In the present work, an isomer mixture of the precursor dipropylene glycol was fractionated through preparative high-performance liquid chromatography. After the conversion to the corresponding trioxocanes, gas chromatography-olfactometry analyses revealed that just one positional isomer, namely 2-ethyl-4,7-dimethyl-1,3,6-trioxocane, was odor active. Moreover, we observed clear differences in the odor threshold concentrations among its stereoisomers. Only two out of eight isomers displayed an odor, both with an earthy smell and one being approximately 60 times more potent than the other. These insights contribute to a better understanding of polyurethane odor on a molecular level and provide a basis for effective odor control. Full article

Nowadays, indoor positioning using ultra-wideband (UWB) signals is actively being developed with the aim of implementing existing ideas and solutions, improving their performance, and searching for new measurement schemes. This paper proposes an approach to estimating the distance between wireless nodes by measuring radio signal propagation time using UWB chaotic radio pulses and UWB transceivers. This type of signal is a simple and practically interesting alternative to radio carriers of other types of UWB signals, which are based on packets of pulses (usually ultra-short pulses). The practical interest is caused by the noise-like nature of chaotic radio pulses, as well as their immunity to multipath fading and ease of generation. The aim of this work is to analyze such a system and identify the fundamental limitations inherent in the proposed approach. This paper describes a wireless system for measuring the signal propagation time based on the envelope of chaotic radio pulses using the SS-TWR (Single-Sided Two-Way Ranging) method. A difference scheme is used to determine the range. The characteristics of the proposed system are studied experimentally. The factors related to the threshold scheme for determining the time of arrival of a radio signal that introduce a systematic error into the measurement results are revealed, and approaches to correcting their influence are proposed. Full article

Visible light positioning (VLP) can provide indoor positioning functions under LED lighting, and it is becoming a cost-effective indoor positioning solution. However, the actual application of VLP is limited by the fact that most positioning requires at least two or more LEDs. Therefore, this paper introduces a positioning system based on a single LED lamp, using an image sensor as the receiver. Additionally, due to the high computational cost of image processing affecting system real-time performance, this paper proposes a virtual grid segmentation scheme combined with the Sobel operator to quickly search for the region of interest (ROI) in a lightweight image processing method. The LED position in the image is quickly determined. Finally, the position is achieved by utilizing the geometric features of the LED image. An experimental setup was established in a space of 80 cm × 80 cm × 180 cm to test the system performance and analyze the positioning accuracy of the receiver in horizontal and tilted conditions. The results show that the positioning accuracy of the method can reach the centimeter level. Furthermore, the proposed lightweight image processing algorithm reduces the average positioning time to 53.54 ms. Full article

Shear failure of non-persistent joints represents a significant contributing factor to rock mass instability. Since non-persistent joints have various parameter characteristics, it is of great practical importance to explore shear behavior with different parameters for preventing geological disasters and engineering construction. In this study, the effects of joint aperture, joint persistency, and normal stress on the shear behavior of non-persistent persistent joints were investigated by combining indoor tests with numerical simulations. Firstly, an indoor direct shear test was carried out to examine the shear stress, normal displacement, and failure patterns from a macroscopic perspective. Then, a numerical model was constructed using the FEM-CZM method to analyze the stress evolution process of non-persistent joint shear failure from a microscopic perspective. The results show that within the scope of the research, the peak shear strength of non-persistent joints is negatively correlated with joint aperture and joint persistency and positively correlated with normal stress. The residual shear strength is negatively correlated with joint persistency and positively correlated with normal stress. Peak normal displacement is negatively correlated with joint aperture and normal stress, and final normal displacement is negatively correlated with joint persistency and normal stress. The failure pattern of non-persistent joints is affected by internal stress. As joint aperture, joint persistency, and normal stress increase, stress concentration at the rock bridge intensifies, the width of the shear failure zone diminishes, and the specimen changes from tensile failure or mixed failure to shear failure. The research results may enrich the understanding of the shear behavior of non-persistent joints and provide some reference value for safe construction and geological hazard protection. Full article

Positioning using ultra-wideband (UWB) signals can be used to achieve centimeter-level indoor positioning. UWB has been widely used in indoor localization, vehicle networking, industrial IoT, etc. However, due to non-line-of-sight (NLOS) and multipath interference problems, UWB cannot provide adequate position information, which affects the final positioning accuracy. This paper proposes an adaptive UWB/PDR localization algorithm based on the maximum point-by-point distance to solve the problems of poor UWB performance and the error accumulation of the pedestrian dead reckoning (PDR) algorithm in NLOS scenarios that is used to enhance the robustness and accuracy of indoor positioning. Specifically, firstly, the cumulative distribution function (CDF) map of localization under normal conditions is obtained through offline pretraining and then compared with the CDF obtained when pedestrians are moving on the line. Then, the maximum point-by-point distance algorithm is used to identify the abnormal base stations. Then, the standard base stations are filtered out for localization. To further improve the localization accuracy, this paper proposes a UWB/PDR algorithm based on an improved adaptive extended Kalman filtering (EKF), which dynamically adjusts the position information through the adaptive factor, eliminates the influence of significant errors on the current position information and realizes multi-sensor fusion positioning. The realization results show that the algorithm in this paper has a solid ability to identify abnormal base stations and that the adaptive extended Kalman filtering (AEKF) algorithm is improved by 81.27%, 58.50%, 29.76%, and 18.06% compared to the PDR, UWB, EKF, and AEKF algorithms, respectively. Full article

Micro- and nanobubbles are tiny gas bubbles that are smaller than 100 μm and 1 μm, respectively. This study investigated the impact of electric field ozone nanobubbles (EF-ONBs) on the purification of both deionised and aquaculture water bodies, finding that heightened reactive oxygen species (ROS) production and oxygen reduction potential (ORP) are correlated to a higher production of EF-ONBs. In particular, it was found that there were substantially reduced ultraviolet light requirements for aquaculture when using EF-ONBs to maintain aquaculture purification standards. It is clear that the approximately exponential decay is slowed down by almost ten times by EF-ONBs even without UV applied, and that it is still roughly six times longer than the ‘control’ case of standard O₃ sparging in water (i.e., meso- and macro-bubbles with no meaningful level of dispersed-phase, bubble-mediated dissolution beyond the standard Henry’s law state—owing mostly to rapid Stokes’ law rising speeds). This has very positive implications for, inter alia, recirculation aeration systems featuring an ozonation cycle, as well as indoor agriculture under controlled-light environments and malting, where ozonation cycles are also often used or contemplated in process redesign strategies. Such promising results for EF-ONBs offer, inter alia, more sustainable aquaculture, water sterilisation, indoor farming, and malting. Full article

This study investigated the effects of film hole diameter and soil bulk density on the unidirectional intersection infiltration laws of muddy water fertilization film hole irrigation. Indoor soil box infiltration experiments were conducted. The thickness of the sediment layer, cumulative infiltration amount per unit area, vertical wetting front transport distance, moisture distribution in the wetting body, and nitrate and ammonium nitrogen transport laws were observed and analyzed. The results indicated that both the thickness of the sediment layer and the cumulative infiltration per unit area are inversely correlated with film hole diameter and soil bulk density. Conversely, the vertical wetting front transport distance and nitrogen content are positively correlated with film hole diameter, while exhibiting a negative correlation with soil bulk density. Notably, the initial point of intersection for the moist body was located below the soil surface, with the peak vertical soil moisture content at the intersection approximately 1.5 cm beneath the surface. The distribution pattern of soil nitrate nitrogen at the conclusion of infiltration mirrored that of water content, characterized by a sharp decline near the wetting front. In contrast, soil ammonium nitrogen content decreased significantly in the shallow soil layer as soil depth increased, without a corresponding abrupt decrease near the wetting front. These findings may provide a theoretical foundation for future research on the intersection infiltration laws of muddy water fertilization through film hole irrigation. Full article

Harvesting grapes requires a large amount of manual labor. To reduce the labor force for the harvesting job, in this study, we developed a robot harvester for the vine grapes. In this paper, we proposed an algorithm that using multi-cameras, as well as artificial intelligence (AI) object detection methods, to detect the thin stem and decide the cut point. The camera system was constructed by two cameras that include multi-lenses. One camera is mounted at the base of the robot and named the “base camera”; the other camera is mounted at the robot hand and named the “hand camera” to recognize grapes and estimate the stem position. At the first step, the grapes are detected by using a You Only Look Once (YOLO) method, while the stems of the grapes are detected at the second step using a pixel-level semantic segmentation method. Field experiments were conducted at an outdoor grapes field. The experiment results show that the proposed algorithm and the camera system can successfully detect out the cut point, and the correct detection rate is around 98% and 93% in the indoor and outdoor conditions, respectively. The detection system was integrated to a grape-harvesting robot in the experiment, and the experiment results show the system can successfully harvest the grapes in the outdoor conditions. Full article

The application of heat pump systems in agriculture, especially within livestock farms, has attracted considerable attention due to their potential for energy efficiency and improved environmental sustainability. Many studies have explored using heat pumps to optimize the indoor environments of barns. This review offers a comprehensive overview and analysis of the current applications of heat pump systems in livestock barn environmental control. Initially, it outlines the fundamental principle of heat pumps and the various types of heat pumps. Then, the technical advantages of the heat pump systems in regulating indoor temperature and humidity of livestock facilities, improving energy efficiency, and reducing environmental impacts are evaluated. Heat pump systems outperform conventional heating and cooling methods in terms of energy utilization and cost-effectiveness, and they positively contribute to reducing environmental pollution. However, some barriers obstruct the widespread adoption of heat pump systems, including policy and regulatory, economic and financial, and technological and infrastructure, as well as public perception and awareness. Future research is recommended to address these barriers. Thus, more heat pump systems in livestock farms could be extensively applied. Full article

A data-efficient training method, namely Q-AL-GPR, is proposed for visible light positioning (VLP) systems with Gaussian process regression (GPR). The proposed method employs the methodology of active learning (AL) to progressively update the effective training dataset with data of low similarity to the existing one. A detailed explanation of the principle of the proposed methods is given. The experimental study is carried out in a three-dimensional GPR-VLP system. The results show the superiority of the proposed method over both the conventional training method based on random draw and a previously proposed line-based AL training method. The impacts of the parameter of active learning on the performance of the GPR-VLP are also presented via experimental investigation, which shows that (1) the proposed training method outperforms the conventional one regardless of the number of final effective training data ($\mathbb{E}$), especially for a small/moderate effective training dataset, (2) a moderate step size (k) should be chosen for updating the effective training dataset to balance the positioning accuracy and computational complexity, and (3) due to the interplay of the reliability of the initialized GPR model and the flexibility in reshaping such a model via active learning, the number of initial effective training data (m) should be optimized. In terms of data efficiency in training, the required number of training data can be reduced by ~27.8% by Q-AL-GPR for a mean positioning accuracy of 3 cm when compared with GPR. The CDF analysis shows that with the proposed training method, the 97th percentile positioning error of GPR-VLP with 300 training data is reduced from 11.8 cm to 7.5 cm, which corresponds to a ~36.4% improvement in positioning accuracy. Full article

Indoor positioning systems have become increasingly important due to the rapid expansion of Internet of Things (IoT) technologies, especially for providing precise location-based services in complex environments such as multi-floor campus buildings. This paper presents a WiFi fingerprint indoor localization system based on AdaBoost, combined with a new access point (AP) filtering technique. The system comprises offline and online phases. During the offline phase, a fingerprint database is created using received signal strength (RSS) values for two four-floor campus buildings. In the online phase, the AdaBoost classifier is used to accurately estimate locations. To improve localization accuracy, APs that always appear in the measurement data are selected for applying the AdaBoost algorithm, aiming to eliminate noise from the fingerprint database. The performance of the proposed method is compared with other well-known machine learning-based positioning algorithms in terms of positioning accuracy and error distances. The results indicate that the average positioning accuracy of the proposed scheme reaches 95.55%, which represents an improvement of 5.55% to 16.21% over the other methods. Additionally, the two-dimensional positioning error can be reduced to 0.25 m. Full article

Due to the typical production of Cannabis sativa L. for medical use in an artificial environment, it is crucial to optimize environmental and nutritional factors to enhance cannabinoid yield and quality. While the effects of light intensity and nutrient composition on plant growth are well-documented for various crops, there is a relative lack of research specific to Cannabis sativa L., especially in controlled indoor environments where both light and nutrient inputs can be precisely manipulated. This research analyzes the effect of different light intensities and nutrient solutions on growth, flower yield, and cannabinoid concentrations in seeded chemotype III cannabis (high CBD, low THC) in a controlled environment. The experiment was performed in a licensed production facility in the Czech Republic. The plants were exposed to different light regimes during vegetative phase and flowering phase (light 1 (S1), photosynthetic photon flux density (PPFD) 300 µmol/m²/s during vegetative phase, 900 µmol/m²/s in flowering phase and light 2 (S2) PPFD 500 µmol/m²/s during vegetative phase, 1300 µmol/m²/s during flowering phase) and different nutrition regimes R1 (fertilizer 1) and R2 (fertilizer 2). Solution R1 (N-NO₃⁻ 131.25 mg/L; N-NH₄⁺ 6.23 mg/L; P₂O₅ 30.87 mg/L; K₂O 4112.04 mg/L; CaO 147.99 mg/L; MgO 45.68 mg/L; SO₄²⁻ 45.08 mg/L) was used for the whole cultivation cycle (vegetation and flowering). Solution R2 was divided for vegetation phase (N-NO₃⁻ 171.26 mg/L; N-NH₄⁺ 5.26 mg/L; P₂O₅ 65.91 mg/L; K₂O 222.79 mg/L; CaO 125.70 mg/L; MgO 78.88 mf/L; SO₄²⁻ 66.94 mg/L) and for flowering phase (N-NO₃⁻ 97.96 mg/L; N-NH₄⁺ 5.82 mg/L; P₂O₅ 262.66 mg/L; K₂O 244.07 mg/L; CaO 138.26 mg/L; MgO 85.21 mg/L; SO₄²⁻ 281.54 mg/L). The aim of this study was to prove a hypothesis that light will have a significant impact on the yield of flowers and cannabinoids, whereas fertilizers would have no significant effect. The experiment involved a four-week vegetative phase followed by an eight-week flowering phase. During the vegetative and flowering phases, no nutrient deficiencies were observed in plants treated with either nutrient solution R1 (fertilizer 1) or R2 (fertilizer 2). The ANOVA analysis showed that fertilizers had no significant effect on the yield of flowers nor cannabinoids. Also, light intensity differences between groups S1 (light 1) and S2 (light 2) did not result in visible differences in plant growth during the vegetative stage. However, by the fifth week of the flowering phase, plants under higher light intensities (S2—PPFD 1300 µmol/m²/s) developed noticeably larger and denser flowers than plants in the lower light intensity group (S1). The ANOVA analysis also confirmed that the higher light intensities positively influenced cannabidiol (CBD), tetrahydrocannabinol (THC), cannabigerol (CBG), and cannabichromene (CBC) when the increase in the concentration of individual cannabinoids in the harvested product was 17–43%. Nonetheless, the study did not find significant differences during the vegetative stage, highlighting that the impact of light intensities is phase-specific. These results are limited to controlled indoor conditions, and further research is needed to explore their applicability to other environments and genotypes. Full article

Wireless Fidelity (Wi-Fi) based positioning has gained popularity for accurate indoor robot positioning in indoor navigation. In daily life, it is a low-cost solution because Wi-Fi infrastructure is already installed in many indoor areas. In addition, unlike the Global Navigation Satellite System (GNSS), Wi-Fi is more suitable for use indoors because signal blocking, attenuation, and reflection restrictions create a unique pattern in places with many Wi-Fi transmitters, and more precise positioning can be performed than GNSS. This paper proposes a machine learning-based method for Wi-Fi-enabled robot positioning in indoor environments. The contributions of this research include comprehensive 3D position estimation, utilization of existing Wi-Fi infrastructure, and a carefully collected dataset for evaluation. The results indicate that the AdaBoost algorithm attains a notable level of accuracy, utilizing the dBm signal strengths from Wi-Fi access points distributed throughout a four-floor building. The mean average error (MAE) values obtained in three axes with the Adaptive Boosting algorithm are 0.044 on the x-axis, 0.063 on the y-axis, and 0.003 m on the z-axis, respectively. In this study, the importance of various Wi-Fi access points was examined with explainable artificial intelligence methods, and the positioning performances obtained by using data from a smaller number of access points were examined. As a result, even when positioning was conducted with only seven selected Wi-Fi access points, the MAE value was found to be 0.811 for the x-axis, 0.492 for the y-axis, and 0.134 for the Z-axis, respectively. Full article

Phlebotomus pedifer is a vector of Leishmania aethiopica, the causative agent of cutaneous leishmaniasis. This study assessed the abundance and distribution of P. pedifer in different habitats and human houses situated at varying distances from hyrax (reservoir host) dwellings, in Wolaita Zone, southern Ethiopia. Sandflies were collected from January 2020 to December 2021 using CDC light traps, sticky paper traps, and locally made emergence traps. Sampling was performed in human houses, peri-domestic areas, farmlands, and hyrax dwellings. Houses 200 m and 400 m from hyrax dwellings were selected to study whether distance affects indoor sandfly abundance. A total of 2485 sandflies were captured, with P. pedifer accounting for 86.1% of the catch and Sergentomyia spp. comprising the remaining 13.9%. The abundance of P. pedifer was highest in human houses (72.3%) and lowest in farmlands (4.0%). Temperature showed a positive correlation with sandfly abundance (r = 0.434, p = 0.000), while rainfall (r = −0.424, p = 0.001) and humidity (r = −0.381, p = 0.001) were negatively correlated with abundance. Houses near hyrax dwellings had significantly higher P. pedifer abundance compared to those further away. Soil-emergence trapping yielded only a few P. pedifer specimens, primarily from hyrax dwellings. The findings highlight the increased presence of P. pedifer indoors, particularly in houses close to hyrax habitats, emphasizing the need for targeted indoor vector control strategies to mitigate the risk of cutaneous leishmaniasis transmission. Full article

Advancements in 3D modelling technology have facilitated more immersive and efficient solutions in spatial planning and user-centred design. In healthcare systems, 3D modelling is beneficial in various applications, such as emergency evacuation, pathfinding, and localization. These models support the fast and efficient planning of evacuation routes, ensuring the safety of patients, staff, and visitors, and guiding them in cases of emergency. To improve urban modelling and planning, 3D representation and analysis are used. Considering the advantages of 3D modelling, this study proposes a framework for 3D indoor navigation and employs a multiphase methodology to enhance spatial planning and user experience. Our approach combines state-of-the art GIS technology with a 3D hybrid model. The proposed framework incorporates federated learning (FL) along with edge computing and Internet of Things (IoT) devices to achieve accurate floor-level localization and navigation. In the first phase of the methodology, Quantum Geographic Information System (QGIS) software was used to create a 3D model of the building’s architectural details, which are required for efficient indoor navigation during emergency evacuations in healthcare systems. In the second phase, the 3D model and an FL-based recurrent neural network (RNN) technique were utilized to achieve real-time indoor positioning. This method resulted in highly precise outcomes, attaining an accuracy rate over 99% at distances of no less than 10 metres. Continuous monitoring and effective pathfinding ensure that users can navigate safely and effectively during emergencies. IoT devices were connected with the building’s navigation software in Phase 3. As per the performed analysis, it was observed that the proposed framework provided 98.7% routing accuracy between different locations during emergency situations. By improving safety, building accessibility, and energy efficiency, this research addresses the health and environmental impacts of modern technologies. Full article