S-curve Method Research Articles

Key saltiness-enhancing substances in Maillard reaction products derived from chicken breast hydrolysate: Identification, saltiness-enhancing ability and mechanism

This work employs a saltiness-guided separation combined with UPLC-QTOF-MS to identify the key saltiness-enhancing substances in Maillard reaction products derived from chicken breast hydrolysate (CBH–MRPs). Thirteen compounds in the U3 fraction exhibited significant saltiness-enhancing abilities, which increased the saltiness intensity of NaCl (3 g/L) from 2.80 to 3.35–3.88. Interactions between the compounds and NaCl were evaluated using the S-curve method. The results showed that five compounds (5′-GMP, 5′-IMP, L-glutamic acid, L-lactic acid, and L-carnosine) and one compound (glutamine) exhibited synergistic and additive effects with NaCl, respectively, at tested concentrations. Notably, 5′-GMP/5′-IMP/glutamine and L-carnosine/L-lactic acid demonstrated better saltiness-enhancing abilities at their suprathreshold and subthreshold levels, respectively. Molecular docking results showed that hydrogen bonding was the key force for docking. Residues Cys475, Glu378, and Trp236 were the primary binding sites of the transmembrane channel-like protein 4 (TMC4). These results contribute to a better understanding of the saltiness modulating mechanisms of CBH–MRPs.

The Technology Innovation of Hybrid Electric Vehicles: A Patent-Based Study

A hybrid electric vehicle (HEV) is a relatively practical technology that has emerged as electric vehicle technology has gradually matured. The analysis of the HEV patent lifecycle is crucial for understanding its impact on the development of this technology. This lifecycle tracks the progress of HEV technologies from their inception and patenting, through their market adoption, and to the expiration of their patent protection. In this study, we aimed to evaluate the technology lifecycle of the HEV industry using the growth S-curve method. The purpose of this study is to describe the technological lifecycle trajectory and current stage of the HEV industry, as well as the technical stages of each sub-technology, to facilitate better decision making. As part of this study, we used patent family data collected from the Derwent Innovation Index database from 1975 to 2022 and established an S-curve model for HEVs and their sub-technologies using logistic regression. In 2022, the technological maturity of HEVs reached 44%. The sub-technologies with the most substantial diffusion capabilities are energy management, propulsion systems, and cooling circuits. According to predictions, the saturation period for the patent family quantity related to HEVs is estimated to be around 53 years.

Simulation of Climate Change Impacts on Crop Yield in the Saskatchewan Grain Belt Using an Improved SWAT Model

Climate change has a potentially significant influence on agricultural production in southern Saskatchewan. Crop yields are susceptible to weather patterns and seasonal fluctuations in this sub-humid region owing to the predominance of rain-fed farming practices. A modified Soil and Water Assessment Tool (SWAT-M) and the output from 10 high-resolution (0.22°) regional climate models (RCMs) were used to develop simulations of spring wheat and rain-fed canola in 296 rural municipalities (RM) for a historical baseline period (1975–2004) and three 30-year future periods: near (2010–2039), middle (2040–2069), and far (2070–2099). We combined SWAT-M with the S-curve method to adjust yield to the original drought stress in the source code and evaluated eight indices of extreme precipitation and temperature. Results of calibration and validation suggest that the simulated crop yields generally agree with observed data. Crop yield showed lesser performance compared with streamflow and soil water content (SWC) along with percent bias, ranging from −9.6% to −14.8%, while streamflow calibration ranges from −5.3% to −7.7%. The multi-model ensemble median showed increasing radiative forcing in the temperature and precipitation indices, such that the RCM-projected weather indices were found to be warmer and wetter than those estimated using regional historical data. The results of simulating canola and spring wheat indicate an increase in crop yield of 17% and 9.7% in the near future, 28.2% and 15.6% in the middle future, and 44.7% and 32% in the far future, respectively. Although, there has been an increase in the median wheat and canola yields, a significant reduction in the annual production is observed. This decline in yield amounts to around 1000 kg/ha and is anticipated to occur in the near and middle future. This trend is quite pronounced in the extreme south and southwest regions. Overall, this innovative research framework, along with the region-specific model outcomes in the form of crop yield projections, will aid in the formulation of future agricultural policies aimed at promoting effective climate adaptation strategies.

Construction project management monitoring system using s-curve

Every construction project generally has a specific implementation plan and implementation schedule: when to start the implementation of the project, when to complete the project, how to do the project, and how to provide resources. Making a plan for a construction project always refers to the estimates that exist when the scheduled development plan is made. Therefore, problems can arise if there is a mismatch between the plan that has been made and its implementation. With the limited resources in the company, thorough and good planning is needed as a guide in carrying out the project to use resources efficiently and organize work to be completed according to the time specified in the contract. To achieve this goal, the manager controls the project with an s-curve by comparing the actual curve graph with the plan curve graph. The method to be used in monitoring the progress of construction projects is the s-curve. The use of the s-curve method is very supportive because it is suitable for monitoring project progress in terms of performance, cost, and timeliness of project work. The results of this study show that the construction project management monitoring website using the s-curve can create a cost budget plan that follows the contract document, a schedule plan, a weekly project report, and a project report recapitulation. The output results are displayed in the form of a Gantt Chart, and S-curves are completed with plan curve lines and realization curve lines. This project management monitoring website has a multi-user feature so that more than one user can use it.

Performance-maximum optimization of the intelligent lifting activities for a polar ship crane through trajectory planning

Knuckle boom crane (KBC) mounted on a polar ship (PS) is a maritime engineering equipment widely used in offshore activities. The working performance of a PS-mounted KBC (PSKBC) may degrade quickly if manipulated manually under extreme working conditions in polar region. To address the challenges, a performance-maximum optimization method through trajectory planning is developed to further promote the intelligently unmanned lifting processes of the PSKBC. Firstly, the dynamic model of lifting activities of the PSKBC is established using Lagrangian equation, based on which the point-to-point trajectory planning (PTP) method is developed for lifting processes. Subsequently, the PTP‐based optimization model is established to realize the minimum energy consumption and time cost of the lifting activities of the PSKBC, and the obtained optimal lifting performance is compared with the traditional S-curve method. To verify the superiority of the proposed performance-maximum optimization method, numerical simulations of the lifting activities of the PSKBC with respect to different crane loads and final lifting positions are performed. Results indicate that the PTP‐based performance-maximum optimization method for the PSKBC can perfectly achieve better performances with applicable lifting trajectories regarding various working conditions and demands.

ANALISIS DAN PENERAPAN METODE LINE OF BALANCE PADA PROYEK REPETITIF

Line of Balance is an effective scheduling method used on projects with repetitive work. The Line of Balance method is able to present productivity levels and duration information in the form of a line graph format that is easier to understand so that it can identify errors that occur in the progress of activities. The purpose of this study was to reschedule the construction project of the Ministry of Finance building in Bandar Lampung using the LoB method to determine the level of time effectiveness and cost efficiency, where initially the project was planned using the Bar Chart method of the s curve. Line of Balance (LoB) is one of the linear scheduling methods that allows balance of application so that each activity can continue. In this final project, the procedure carried out by this research is calculated by using the Line of Balance (LoB) method to simplify the activities so that it is easier to analyze conflicts that occur after drawing them into line diagrams. The calculation results obtained in this planning using the Line of Balance method after merging activities, conflict analysis and drawing diagrams obtained the final duration of work 270 days. while the scheduling using the barchat s-curve method takes 273 days, which means the difference in scheduling using the Line of Balance method to complete the construction project of the Ministry of Finance building in Bandar Lampung is three days faster (0.98%).

Investigation of volatile thiol contributions to rapeseed oil by odor active value measurement and perceptual interactions

Volatile thiols are important aroma components of rapeseed oil. This study established an identification and quantification method of volatile thiols via headspace solid-phase microextraction and gas chromatography-sulfur chemiluminescence detection. Four thiols (phenylmethanthiol, 3-sulfanyl-1-hexanol, 2-methyl-3-furanthiol, and 2-furylmethanthiol) were newly identified in microwaved rapeseed oil, and cause sesame, roasted meat, and garlic odors. The total concentration of the four thiols in rapeseed oil obtained from 13 rapeseed varieties ranged from 11.47 to 153.72 μg/kg. Determination of the threshold revealed that 3-sulfanyl-1-hexanol possessed the highest odor active value (7565), followed by phenylmethanthiol (3589), 2-furylmethanthiol (626), and 2-methyl-3-furanthiol (28). Further, perceptual interactions between volatile thiols and characteristic odor (3-butenyl isothiocyanate) of rapeseed oil were evaluated by Feller’s addition model and S-curve method, which revealed that 2-methyl-3-furanthiol, 2-furylmethanthiol, phenylmethanthiol, and 3-sulfanyl-1-hexanol present a positive effect with 3-butenyl isothiocyanate. This study provides deep insights into the impact of sulfur-containing compounds on the aroma of rapeseed oil.

Analisis Kinerja Waktu dan Penerapan Building Information Modeling pada Proyek Pembangunan Jasmine Park Apartment Bogor

Increasing of certainly development requires jobs with high productivity, effectiveness and efficiency. The application of BIM up to four-dimensional modeling (4D) using Tekla Structure software is a solution because it can analyze time performance, determine the causative factors in the event of delays and actions to overcome them. 3D modeling included modeling of foundations, columns, beams, slabs, stairs, and roofs. 4D modeling is conducted by adding work schedule to the 3D modeling that had been made. Time performance analysis was performed using the S-curve method for all buildings in Tower Green Jasmine Park Apartment Bogor construction project. Time performance analysis using the S curve found that this project experienced delays with the highest negative deviation value happened in June 2020 by -13.67%. The main delays in the project occured in procurement of MEP logistics and weather conditions. Work acceleration is carried out by increasing working hours and increasing the number of workers.

Data-Driven Regularization Parameter Selection in Dynamic MRI.

In dynamic MRI, sufficient temporal resolution can often only be obtained using imaging protocols which produce undersampled data for each image in the time series. This has led to the popularity of compressed sensing (CS) based reconstructions. One problem in CS approaches is determining the regularization parameters, which control the balance between data fidelity and regularization. We propose a data-driven approach for the total variation regularization parameter selection, where reconstructions yield expected sparsity levels in the regularization domains. The expected sparsity levels are obtained from the measurement data for temporal regularization and from a reference image for spatial regularization. Two formulations are proposed. Simultaneous search for a parameter pair yielding expected sparsity in both domains (S-surface), and a sequential parameter selection using the S-curve method (Sequential S-curve). The approaches are evaluated using simulated and experimental DCE-MRI. In the simulated test case, both methods produce a parameter pair and reconstruction that is close to the root mean square error (RMSE) optimal pair and reconstruction. In the experimental test case, the methods produce almost equal parameter selection, and the reconstructions are of high perceived quality. Both methods lead to a highly feasible selection of the regularization parameters in both test cases while the sequential method is computationally more efficient.

Design of PI Speed Controller for 3-Ph Converter fed DC motor drive using Symmetrical Optimization

ABSTRACT This research paper focuses on the mathematical model of DC motor drive fed from the 3-Ph converter and the design of the PI speed controller for its speed control. To evaluate the gain coefficients of the PI speed controller, Symmetrical Optimum criteria are proposed. The proposed criterion is easier to understand than other advanced control methods. Using this criterion the gains of the PI controller are obtained by developing the mathematical model of the DC motor drive. This controller can be easily implemented for real-time applications of keeping motor speed at any desired set-point speed under varying operating conditions. The speed performance using the proposed method was compared with the S-curve method in MATLAB. The simulation results, with constant operating speed, indicate that the proposed criterion provides superior speed performance than the S-curve method. A similar speed response can be obtained with the selected PI gains for variable speeds. Finally, a comparative study has been done to highlight the proposed method benefits.

Characterization of the key aroma compounds in Laoshan green teas by application of odour activity value (OAV), gas chromatography-mass spectrometry-olfactometry (GC-MS-O) and comprehensive two-dimensional gas chromatography mass spectrometry (GC × GC-qMS)

To investigate the key aroma compounds in Laoshan green teas (Huangshan (S1), Changling (S2), and Fangling (S3)), gas chromatography-mass spectrometry-olfactometry (GC-MS-O), a flame photometric detector (FPD), odor activity value (OAV), and comprehensive two-dimensional gas chromatography mass spectrometry (GC × GC-qMS) were employed. A total of 50 aroma compounds were perceived and 24 compounds were identified as important compounds related to OAV, such as dimethyl sulfide (OAV: 126–146), skatole (OAV: 27–50), furaneol (OAV: 8–27), (Z)-jasmone (OAV: 16–23), 2-methylbutanal (OAV: 15–22), and 3-methylbutanal (OAV: 68–87). Furthermore, the S-curve method was used to research the effect of aroma compounds on the threshold of aroma recombination (AR). The AR thresholds decreased from 3.8 mL to 0.45, 0.66, 0.93, 0.95, 0.75, 1.09, 3.01, and 2.57 mL after addition of eight compounds (skatole, furaneol, (Z)-jasmone, α-damascenone, sclareololide, dihydroactinidiolide, vanillin, and δ-valerolactone), indicating that those compounds (OAV >1) were contributors to the overall aroma of Laoshan teas.

Based on the Patent Index Method and S Curve Method Prediction Analysis of Pure Electric Vehicle Life Cycle

In order to grasp the direction of pure electric vehicle technology innovation in strategic macro, this paper retrieves the domestic patents in the field related to pure electric vehicles, using the patent index method and S-curve method to analyze the life cycle of pure electric vehicle technology. It is clear that the pure electric vehicle technology in China is in the mature stage of the technology life cycle, In view of the development stage and development trend of pure electric vehicle technology in China, this paper provides patent strategies for related enterprises from the perspective of patent strategy. The combination of patent indicator method and s-curve method can predict the technology life cycle more accurately, providing a feasible analytical method for the identification and prediction of the patent technology life cycle.

A Robust Algorithm for 2-D NMR Diffusion–Relaxation Spectra Inversion

A two-step iterative shrinkage/thresholding (TIST) algorithm was proposed to solve the objective function of the L1 regularization for the 2-D nuclear magnetic resonance diffusion–relaxation ( $D - T_{2}$ ) spectra inversion. Moreover, a simple and effective method combining the S-curve method and the Chi-square method was proposed to select the optimal L1 regularization parameter. We compared the inverted $D - T_{2}$ spectra derived from the TIST algorithm with those from the truncated singular value decomposition (TSVD), Butler–Reeds–Dawson (BRD), original IST (OIST), and IST algorithms using numerical experiments. The experimental results indicated that the inverted $D - T_{2}$ spectra derived from the OIST, IST, and TIST algorithms were affected by noise to a smaller degree, and the robustness was higher for the OIST, IST, and TIST algorithms than for the TSVD and BRD algorithms. In addition, we compared the accuracy and operating time of the TIST, OIST, and IST algorithms for $D - T_{2}$ spectra inversion and concluded that the three algorithms had an equivalent accuracy but the TIST algorithm had a faster convergence rate.

Unit Hydrograph Modeling using Geomorphological Instantaneous Unit Hydrograph (GIUH) Method

Flood forecasting at Wonogiri Reservoir is restricted on the availability of hydrologic data due to limited monitoring gauges. This issue triggers study of unit hydrograph modeling using Geomorphological Instantaneous Unit Hydrograph (GIUH) which is based on Geographic Information System (GIS). Analysis of physical watershed parameters was conducted on Digital Elevation Model (DEM) data using software Watershed Modeling System (WMS) 10.1 and ArcGIS. Nash model and S-curve method were used to process triangular GIUH into hourly Instantaneous Unit Hydrograph (IUH) and Unit Hydrograph (UH) and then was compared with the observed UH of Collins method. A sensitivity analysis was conducted on parameter of RL and Nash-model k. Evaluation of accuracy of the simulated GIUH runoff hydrograph was also conducted. The GIUH model generated UH with smaller peak discharge Qp, also slower and longer of tp and tb values than the observed UH. Accuracy test of the simulated GIUH runoff hydrograph using Nash-Sutcliffe Efficiency (NSE) shows that Keduang watershed gives a satisfying result, while Wiroko watershed gives less satisfactory result. The inaccuracies occur due to limited flood events used to derive the observed UH and stream tributaries that were not properly modeled based on Strahler method.

Multiresolution Parameter Choice Method for Total Variation Regularized Tomography

A computational method is introduced for choosing the regularization parameter for total variation (TV) regularization. A partial understanding of the properties of the method is provided by rigorously proving that the TV norms of the reconstructions converge with any choice of regularization parameter. The computational approach is based on computing reconstructions at a few different resolutions and various values of regularization parameter. The chosen parameter is the smallest one resulting in approximately discretization-invariant TV norms of the reconstructions. The method is tested with simulated and experimental X-ray tomography data and compared to the S-curve method. The results are comparable to those of the S-curve method. However, the S-curve method needs quantitative a priori information about the expected sparsity (TV norm) of the unknown, while the proposed method does not require such input parameters.

The evolution of functional left peripheries in Hungarian syntax ed. by Katalin É. Kiss

Reviewed by: The evolution of functional left peripheries in Hungarian syntax ed. by Katalin É. Kiss István Kenesei and Anikó Lipták The evolution of functional left peripheries in Hungarian syntax. Ed. by Katalin É. Kiss. (Oxford studies in diachronic & historical linguistics.) Oxford: Oxford University Press, 2014. Pp. 263. ISBN 9780198709855. $110 (Hb). This is the first English language book on Hungarian diachronic syntax in the generative framework. It summarizes the outstanding achievements of a four-year OTKA (Hungarian Scientific Research Fund) project on diachronic syntax of Hungarian, carried out at the Research Institute for Linguistics under the leadership of Katalin É. Kiss. The book is a somewhat more concise version of the Hungarian publication É. Kiss 2014, adapted to an international readership. The book provides an empirical overview of the syntactic changes in Hungarian, covering the following five major areas: basic sentence structure, DP structure, quantification, PP structure, and subordination. The book’s title is slightly misleading since the volume is not explicitly about the functional left periphery in all of the above areas, but rather about the development of functional material (in the left periphery or elsewhere) that is closely linked to historical change and grammaticalization. The diachronic data studied are texts originating between the end of the twelfth century and the end of the sixteenth century, from the second half of the Old Hungarian period (which roughly corresponds to six centuries between c. 900 and 1500) and the beginning of the Middle Hungarian era that followed it. In this period, the most important documents comprise forty-seven hand-written codices (Old Hungarian) and printed books in various genres (Middle Hungarian). These texts were annotated and entered into a corpus built for the project (currently available for the Hungarian-speaking audience at http://oldhungariancorpus.nytud.hu). The building of the corpus itself was a massive undertaking, the details of which (the process of digitalization, problems of character recognition, text encoding, annotation, etc.) are documented by Eszter Simon in the appendix to the volume. The five chapters detailing historical change in Hungarian share a methodology. The reconstruction of the Proto-Hungarian language (with no surviving documents) is based on the S-curve method (Croft 2000): new constructions first spread slowly, then fast, then slowly again, while old constructions are ousted following the reverse pattern. Using the backward extension of these curves, as well as comparisons with the Ob-Ugric sister languages Khanti and Mansi, the research established several features of Proto-Hungarian and Old/Middle Hungarian. The following gives a brief summary of the chapter contents. Ch. 1 by Katalin É. Kiss argues that Hungarian has changed from an SOV to an SVO language, a change that went hand in hand with the disappearance of unmarked objects and the appearance of the modern Hungarian left periphery. Possibly, rightward-dislocated phrases came to be reanalyzed as base-generated arguments, bringing about the reanalysis of preverbal elements as A-bar constituents, resulting in a Topic–Focus–V–X order (rather than, strictly speaking, SVO). The change must have taken place before the start of the Old Hungarian period since the fifty clauses of the first Old Hungarian document already utilize every clausal functional projection that is attested in Modern Hungarian. Although the head-final nature of Proto-Hungarian is argued for on the basis of evidence that VP, TP, and CP were all head-final in that period, the role of Tense is neglected throughout in the change from SOV to the Old Hungarian structure. Note that there is precious little on this topic even in the highly relevant chapter on finite and nonfinite subordination apart from an important, though rather brief, observation, claiming that ‘Old Hungarian was not an OV language any more, yet auxiliaries strictly followed the main verb, which means that VP was not head final, but TP/AspP still was’ (n. 17, p. 182). The paper also provides a detailed account of the development of object agreement, which is descended from topic-verb agreement in Proto-Hungarian, where the subject was a primary topic, and the object a focus or a secondary topic, which triggered agreement only in the latter case (an instance of differential object agreement...

Inversion of nuclear magnetic resonance echo data based on maximum entropy

Nuclear magnetic resonance (NMR) [Formula: see text] inversion is an ill-posed problem in which regularization techniques are usually adopted to suppress the oscillations caused by noise in the solutions. The maximum entropy concept provides an unbiased way to obtain information from incomplete data, and it implicitly imposes a positive constraint on probability distribution, so we used the maximum entropy method to invert NMR echo data. We have developed a simple and effective method for solving the objective function of the maximum entropy method. First, the solution was replaced by a positive function to achieve the positive constraint of the solution, the objective function was converted to an unconstrained one, and then the Levenberg-Marquardt method was used to solve the newly obtained unconstrained objective function. To suppress the highly tilted tail at the short relaxation time of the [Formula: see text] distribution, a modified or normalized Shannon entropy function was used to replace the standard Shannon entropy function as the penalty term. Furthermore, the S-curve method was used to select the regularization parameter and the formula of the slope of the S-curve was developed. We have determined that the maximum entropy method was better able to separate the peaks of short and long relaxation times in the [Formula: see text] distribution in comparison with the truncated singular value decomposition method. This was true for low signal-to-noise ratio data derived from numerical simulation and the NMR log. In addition, the short relaxation peak caused by the norm smoothing method can also be reduced.

Regularization methods for the extraction of depth profiles from simulated ARXPS data derived from overlayer/substrate models

Starting from posited input depth profiles of silicon oxide on silicon, 100 sets of noisy simulated ARXPS data were created for each oxide layer thickness of 3, 6, 9, 12, 15, 18, 21, 24 and 27 Å. Oxygen depth profiles were then recovered from the noisy simulated data using regularized inversion methods, including maximum entropy and Tikhonov regularization. Three regularization parameters were used: one determined by the S-curve method, one determined by the L-curve method and a third corresponding to the closest correspondence between the input and extracted profiles. The various regularization schemes evaluated were ranked with respect to their ability to reproduce the input profile.

Simplified time-optimal path planning of [formula omitted]- [formula omitted] gantry systems along circular paths

In this paper, we consider time-optimal path planning for X - Y gantry systems along circular paths, in which acceleration and jerk limitations of each actuator are taken into full account. The physical limitations are expressed as highly nonlinear state/input constraints, and are mathematically very difficult to handle effectively. In this context, we formulate the time-optimal problem under reasonably simplified constraints and derive its solution in feedback form. Numerical examples demonstrate that the proposed time-optimal circular path planning method decreases the traverse time significantly compared to the well-known s-curve method.

FLOOD MODELLING WITH GIS-DERIVED DISTRIBUTED UNIT HYDROGRAPHS

The concept of a spatially distributed unit hydrograph is based on the fact that the unit hydrograph can be derived from the time-area curve of a watershed by the S-curve method. The time-area diagram is a graph of cumulative drainage area contributing to discharge at the watershed outlet within a specified time of travel. Accurate determination of the time-area diagram is made possible by using a GIS. The GIS is used to describe the connectivity of the links in the watershed flow network and to calculate distances and travel times to the watershed outlet for various points within the watershed. Overland flow travel times are calculated by the kinematic wave equation for time to equilibrium; channel flow times are based on the Manning and continuity equations. To account for channel storage, travel times for channel reaches are increased by a percentage depending on the channel reach length and geometry. With GIS capability for rainfall mapping, the assumption of a uniform spatial rainfall distribution is no longer necessary; hence the term, spatially distributed unit hydrograph. An example of the application for the Waiparous Creek in the Alberta Foothills is given. IDRISI is used to develop a simple digital elevation model of the 229 km 2 watershed, using 1 km x 1 km grid cells. A grid of flow directions is developed and used to create an equivalent channel network. Excess rainfall for each 1 km x 1 km cell is individually computed by the Soil Conservation Service (SCS) runoff curve method and routed through the equivalent channel network to obtain the time-area curve. The derived unit hydrograph gave excellent results in simulating an observed flood hydrograph. The distributed unit hydrograph is no longer a lumped model, since it accounts for internal distribution of rainfall and runoff. It is derived for a watershed without the need for observed rainfall and discharge data, because it is essentially a geomorphoclimatic approach. As such, it allows the derivation of watershed responses (hydrographs) to inputs of various magnitudes, thus eliminating the assumption of proportionality of input and output if needed. The superposition of outputs is retained in simulating flood hydrographs by convolution, since it has been shown that some non-linear systems satisfy the principle of superposition. The distributed unit hydrograph appears to be a very promising rainfall runoff model based on GIS technology.