Search Results (9)

The exponential growth of multi-modal behavioral data in campus networks poses significant challenges for clustering analysis, including high dimensionality, redundancy, and attribute heterogeneity, which lead to degraded accuracy in existing methods. To address these issues, this study proposes a graph-theoretic subspace deep clustering framework that synergizes a deep sparse auto-encoder (DSAE) with a method of graph partitioning based on normalized cut. First, a four-layer DSAE is designed to extract discriminative features while enforcing sparsity constraints, effectively reducing data dimensionality and mitigating noise. Second, the refined subspace representations are transformed into a similarity graph, where normalized cut optimization partitions users into coherent behavioral clusters by balancing intra-cluster cohesion and inter-cluster separation. Experimental validation on three datasets—USER_DATA, MNIST, and COIL20—demonstrates the superiority of GTSDC. It achieves 91% accuracy on USER_DATA, outperforming traditional algorithms (e.g., CLIQUE, K-means) by 120% and advanced methods (e.g., deep subspace clustering) by 15%. The proposed framework not only enhances network resource allocation through behavior-aware analytics but also lays the groundwork for personalized educational services. This work bridges the gap between graph theory and deep learning, offering a scalable solution for high-dimensional behavioral pattern recognition. In simple terms, this new algorithm can more accurately analyze user behavior in campus networks. It helps universities better allocate network resources, such as ensuring smooth online classes, and can also provide personalized educational services to students according to their behavior patterns. Full article

The oral administration of probiotics is a promising strategy to regulate the host–intestinal flora balance and improve health. Nevertheless, adverse gastrointestinal (GI) conditions affect the activity of free native probiotics. In this study, a novel probiotic encapsulation system based on milk exosomes (mExos) and DSPE-PEG-PBA was developed. mExos acted as a shield to protect probiotics from harsh GI environments, and DSPE-PEG-PBA served as a bridge between mExos and probiotics. The coated probiotics were characterized by transmission electron microscopy (TEM), Fourier transform infrared spectroscopy (FT-IR), and intrinsic fluorescence spectra. The results showed three probiotics (Akkermansia muciniphila (AKK), Bifidobacterium animalis subsp. lactis BB-12 (BB12), and Lactiplantibacillus plantarum Q7 (Q7)) were coated with mExos@DSPE-PEG-PBA, with encapsulation rates of 90.37 ± 0.45%, 84.47 ± 1.22%, and 70.93 ± 2.39%, respectively. This encapsulation not only preserved the growth activity of the probiotics but also provided robust protection against the detrimental effects of acidic pH, bile salts, and digestive enzymes. The encapsulated strains Q7, BB12, and AKK demonstrated survival rates of 80.99 ± 0.41%, 85.28 ± 0.20%, and 94.53 ± 0.26%, respectively, in an in vitro simulated GI environment. The mExos@DSPE-PEG-PBA-encapsulated probiotics exhibited enhanced hydrophobicity and auto-aggregation capacity, accompanied by a significant improvement in mucoadhesive properties, which collectively potentiated their colonization potential within the gastrointestinal tract. These findings substantiate the potential of mExos as an encapsulation platform for probiotics, providing valuable insights into the selection of exosomes as encapsulating agents to enhance probiotic viability and mucoadhesive capacity. Full article

The auto-balancing bridge method is an impedance measurement method with higher accuracy than other traditional methods. The balance control algorithm within the auto-balancing bridge is a crucial component. Its performance in maintaining symmetry between the current flowing through the test element and the current flowing through a known reference resistor determines the impedance measurement accuracy. However, using the imaginary impedance of a practical reference resistor in the bridge diminishes the convergence accuracy of the auto-balancing bridge. In this paper, a feedforward decoupling module is first constructed to compensate for the imaginary part of the reference resistor and decouple the auto-balancing bridge into two independent balance control channels, namely, the real and imaginary channels. Then, two balance controllers based on the variable-domain fuzzy-PID algorithm are used for these two separated balance control channels in order to improve the convergence accuracy and adaptability of bridge balancing. Finally, the particle swarm optimization method is used to automatically tune the controller’s parameters to enhance the development efficiency of the auto-balancing bridge. Experimental results show that this bridge balance control algorithm can quickly stabilize the unbalanced current of the bridge. For the practical auto-balancing bridge circuit, its relative impedance measurement error remains below 0.05%. This method effectively improves measurement accuracy and provides crucial technical support for the application of auto-balancing bridges in the high-precision measurement field. Full article

The booming population and accelerating urbanization in the Huaihe River Basin have sped up the land use transformation and the cultivated land fragmentation (CLF), seriously impeded the advancement of agricultural modernization, and threatened regional stability and national food security as well. The analysis of CLF degree and its spatiotemporal distribution characteristics, along with the influencing factors in the Huaihe River Basin, is of great significance for promoting the intensive and efficient utilization of cultivated land resources and maintaining food security. Previous studies lack the measurement and cause analysis of CLF in Huaihe River Basin. To bridge the gap, this study introduces Fragstats4.2 and ArcGIS10.3 to analyze the spatiotemporal characteristics of CLF in county units in the Huaihe River Basin from 2000 to 2018 through the Lorentz curve, entropy method, and spatial auto-correlation method while the causes of the spatiotemporal differentiation of CLF in the basin were explored with the help of a geographic detector. The results show that the spatial distribution of cultivated land in the Huaihe River Basin is relatively balanced, and the Gini coefficients of cultivated land from 2000 to 2018 were 0.105, 0.108, and 0.113, respectively. More than 56% of the counties in the basin have a location entropy greater than 1. the percentage of landscape, area-weighted mean patch area, patch cohesion index, and aggregation index decrease year by year while the patch density and splitting index show an upward trend. The landscape pattern of cultivated land is highly complex, and the overall fragmentation degree is increasing. The county distribution pattern of the CLF degree with random and agglomeration is generally stable. The spatiotemporal differentiation of CLF in the Huaihe River Basin is affected by multiple factors, among which the influences of the normalized difference vegetation index, per capita cultivated land area, and intensity of human activity obviously stronger than other factors, and the contribution rate of the factors reached more than 0.4. The interaction effect among the factors is stronger than that of single factor, with dual-factor enhancement and nonlinear enhancement dominating. The results of this study have important implications for optimizing the agricultural structure in the Huaihe River Basin and alleviating the CLF in important grain production areas. Full article

This paper describes the design and the performance of simultaneous, multifrequency impedance measurement system for four inductive-loop (IL) sensors which have been developed for vehicle parameters measurement based on vehicle magnetic profile (VMP) analysis. Simultaneous impedance measurement on several excitation frequencies increases the VMP measurement reliability because typical electromagnetic interferences (EMI) are narrowband, and should not simultaneously affect, in the same way, all measurement bands that are spread in the frequency, i.e., it is expected that at least one measurement band is disturbance-free. The system consists of two standard and two slim IL sensors, specially designed and installed, the analogue front-end, and an industrial computer with digital-to-analogue and analogue-to-digital converters accessed via field-programmable gate array (FPGA). The impedance of the IL sensors is obtained by vector measurement of voltages from auto-balancing bridge (ABB) front-end. Complex voltages are demodulated from excitation frequencies with FIR filters designed with the flat-top windows. The system is capable of delivering VMPs in real-time mode, and also storing voltages for off-line postprocessing and analysis. Field distributions and sensitivities of slim and standard IL sensors are also discussed. Field test confirmed assumed increased reliability of VMP measurement for proposed simultaneous multifrequency operational mode. Full article

Numerical models are employed widely to evaluate the hydrological components of a watershed but, traditionally, watershed models simplify either surface or subsurface flow module. In this setup, as a bridge between groundwater and surface water regimes, aquifer recharge is the most affected segment of the water balance. Since the watershed processes are increasingly changed, the need for a comprehensive model with detailed conceptualizing capacity of both groundwater and surface water flow systems is growing. This work focuses on the spatiotemporal groundwater recharge assessment in gauged and ungauged agro-urban watersheds in South Korea using the updated SWAT-MODFLOW model, which integrates the Soil and Water Assessment Tool (SWAT2012) and Newton–Raphson formulation for Modular Finite Difference Groundwater Flow (MODFLOW-NWT) in a single executable code. Before coupling, the setup, calibration, and verification of each model were performed separately. After integration, irrigation pumps and drain cells mapping to SWAT auto-irrigation and subbasins were initiated. Automatic calibration techniques were used for SWAT and MODFLOW-NWT models, but a manual calibration was used for the integrated model. A physical similarity approach was applied to transfer parameters to the ungauged watershed. Statistical model performance indicators revealed that the low streamflow estimation was improved in SWAT-MODFLOW. The spatiotemporal aquifer recharge distribution from both the stream seepage and precipitation showed a substantial change, and most of the aquifer recharge occurs in July–September. The areal annual average recharge reaches about 18% of the precipitation. Low-lying areas receive higher recharge consistently throughout a year. Overall, SWAT-MODFLOW exhibited reasonable versatility in evaluating watershed processes and produced valuable results with reasonable accuracy. The results can be an important input for policymakers in the development of sustainable groundwater protection and abstraction strategies for the region. Full article

In this article we respond to the comments made by Chavanne et al., who have questioned: (i) the name of the technique used; (ii) the ability of the system to determine both soil water content and salinity due to potential instrument biases and choice of sensor frequencies; and (iii) the procedure used to determine temperature effect on readings presented in the article “A Novel Low-Cost Instrumentation System for Measuring the Water Content and Apparent Electrical Conductivity of Soils” (Sensors 2015, 15, 25546–25563). We have carefully analyzed the arguments in the comment, and have concluded that they only partially affect the previous conclusions, as will be discussed in this reply. We show here that the findings and conclusions previously drawn are valid and supported by the many experiments previously conducted. Full article

In this work, the authors introduce a new full-analog front-end for differential capacitance sensors which provides a DC output voltage, directly proportional to the measurand variations. The readout circuit architecture is based on a De Sauty bridge as core of the capacitive sensing whereas the feedback circuitry performs the bridge autobalancing operation by means of changes in a multiplier output. The circuit is designed in a standard CMOS technology (AMS 0.35 µm) so is suitable for portable systems. Simulated results have shown a good agreement with the theoretical model being the percentage relative error less than 2.5%. Interface sensitivity is constant and values around 0.055 V/mm for the considered application. Full article

The scarcity of drinking water affects various regions of the planet. Although climate change is responsible for the water availability, humanity plays an important role in preserving this precious natural resource. In case of negligence, the likely trend is to increase the demand and the depletion of water resources due to the increasing world population. This paper addresses the development, design and construction of a low cost system for measuring soil volumetric water content (θ), electrical conductivity (σ) and temperature (T), in order to optimize the use of water, energy and fertilizer in food production. Different from the existing measurement instruments commonly deployed in these applications, the proposed system uses an auto-balancing bridge circuit as measurement method. The proposed models to estimate θ and σ and correct them in function of T are compared to the ones reported in literature. The final prototype corresponds to a simple circuit connected to a pair of electrode probes, and presents high accuracy, high signal to noise ratio, fast response, and immunity to stray capacitance. The instrument calibration is based on salt solutions with known dielectric constant and electrical conductivity as reference. Experiments measuring clay and sandy soils demonstrate the satisfactory performance of the instrument. Full article