Intrusion Detection Model Using Chaotic MAP for Network Coding Enabled Mobile Small Cells

Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions,vulnerabilities,and assaults.Complex security systems,such as Intrusion Detection Systems(IDS),are essential due to the limitations of simpler security measures,such as cryptography and firewalls.Due to their compact nature and low energy reserves,wireless networks present a significant challenge for security procedures.The features of small cells can cause threats to the network.Network Coding(NC)enabled small cells are vulnerable to various types of attacks.Avoiding attacks and performing secure“peer”to“peer”data transmission is a challenging task in small cells.Due to the low power and memory requirements of the proposed model,it is well suited to use with constrained small cells.An attacker cannot change the contents of data and generate a new Hashed Homomorphic Message Authentication Code(HHMAC)hash between transmissions since the HMAC function is generated using the shared secret.In this research,a chaotic sequence mapping based low overhead 1D Improved Logistic Map is used to secure“peer”to“peer”data transmission model using lightweight H-MAC(1D-LM-P2P-LHHMAC)is proposed with accurate intrusion detection.The proposed model is evaluated with the traditional models by considering various evaluation metrics like Vector Set Generation Accuracy Levels,Key Pair Generation Time Levels,Chaotic Map Accuracy Levels,Intrusion Detection Accuracy Levels,and the results represent that the proposed model performance in chaotic map accuracy level is 98%and intrusion detection is 98.2%.The proposed model is compared with the traditional models and the results represent that the proposed model secure data transmission levels are high.

A Model of Cloud-Based Enterprise Resource Planning (ERP) for Small and Medium Enterprise

Cloud Computing is an uprising technology in the rapid growing IT world. The adaptation of cloud computing is increasing in very large scale business organizations to small institutions rapidly due to many advanced features of cloud computing, such as SaaS, PaaS and IaaS service models. So, nowadays, many organizations are trying to implement Cloud Computing based ERP system to enjoy the benefits of cloud computing. To implement any ERP system, an organization usually faces many challenges. As a result, this research has introduced how easily this cloud system can be implemented in an organization. By using this ERP system, an organization can be benefited in many ways;especially Small and Medium Enterprises (SMEs) can enjoy the highest possible benefits from this system.

Investigating the elliptic anisotropy of identified particles in p-Pb collisions with a multi-phase transport model

The elliptic azimuthal anisotropy coefficient(v_(2))of the identified particles at midrapidity(|η|<0.8)was investigated in p-Pb collisions at√s_(NN)=5.02 TeV using a multi-phase transport model(AMPT).The calculations of differential v_(2)based on the advanced flow extraction method of light flavor hadrons(pions,kaons,protons,andΛ)in small collision systems were extended to a wider transverse momentum(p_(T))range of up to 8 GeV/c for the first time.The string-melting version of the AMPT model provides a good description of the measured p_(T)-differential v_(2)of the mesons but exhibits a slight deviation from the baryon v_(2).In addition,we observed the features of mass ordering at low p_(T)and the approximate number-of-constituentquark(NCQ)scaling at intermediate p_(T).Moreover,we demonstrate that hadronic rescattering does not have a significant impact on v_(2)in p-Pb collisions for different centrality selections,whereas partonic scattering dominates in generating the elliptic anisotropy of the final particles.This study provides further insight into the origin of collective-like behavior in small collision systems and has referential value for future measurements of azimuthal anisotropy.

Prediction models for recurrence in patients with small bowel bleeding

Obscure gastrointestinal bleeding(OGIB)has traditionally been defined as gastrointestinal bleeding whose source remains unidentified after bidirectional endoscopy.OGIB can present as overt bleeding or occult bleeding,and small bowel lesions are the most common causes.The small bowel can be evaluated using capsule endoscopy,device-assisted enteroscopy,computed tomography enterography,or magnetic resonance enterography.Once the cause of smallbowel bleeding is identified and targeted therapeutic intervention is completed,the patient can be managed with routine visits.However,diagnostic tests may produce negative results,and some patients with small bowel bleeding,regardless of diagnostic findings,may experience rebleeding.Predicting those at risk of rebleeding can help clinicians form individualized surveillance plans.Several studies have identified different factors associated with rebleeding,and a limited number of studies have attempted to create prediction models for recurrence.This article describes prediction models developed so far for identifying patients with OGIB who are at greater risk of rebleeding.These models may aid clinicians in forming tailored patient management and surveillance.

Assessment of corrected time-step method for nominal ionospheric gradient calculation: A comparative analysis with spatial approaches

The effect of ionospheric delay on the ground-based augmentation system under normal conditions can be mitigated by determining the value of the nominal ionospheric gradient(σvig).The nominal ionospheric gradient is generally obtained from Continuously Operating Reference Stations data by using the spatial single-difference method(mixed-pair,station-pair,or satellite-pair)or the temporal single-difference method(time-step).The time-step method uses only a single receiver,but it still contains ionospheric temporal variations.We introduce a corrected time-step method using a fixed-ionospheric pierce point from the geostationary equatorial orbit satellite and test it through simulations based on the global ionospheric model.We also investigate the effect of satellite paths on the corrected time-step method in the region of the equator,which tends to be in a more north–south direction and to have less coverage for the east–west ionospheric gradient.This study also addresses the limitations of temporal variation correction coverage and recommends using only the correction from self-observations.All processes are developed under simulations because observational data are still difficult to obtain.Our findings demonstrate that the corrected time-step method yieldsσvig values consistent with other approaches.

Small-signal modeling and parameter extraction method for a multigate GaAs pHEMT switch

This paper presents an accurate small-signal model for multi-gate GaAs pHEMTs in switching-mode.The extraction method for the proposed model is developed.A 2-gate switch structure is fabricated on a commercial 0.5μm AlGaAs/GaAs pHEMT technology to verify the proposed model.Excellent agreement has been obtained between the measured and simulated results over a wide frequency range.

A Vertex Network Model of Arabidopsis Leaf Growth

Biology provides many examples of complex systems whose properties allow organisms to develop in a highly reproducible,or robust,manner.One such system is the growth and development of flat leaves in Arabidopsis thaliana.This mechanistically challenging process results from multiple inputs including gene interactions,cellular geometry,growth rates,and coordinated cell divisions.To better understand how this complex genetic and cellular information controls leaf growth,we developed a mathematical model of flat leaf production.This two-dimensional model describes the gene interactions in a vertex network of cells which grow and divide according to physical forces and genetic information.Interestingly,the model predicts the presence of an unknown additional factor required for the formation of biologically realistic gene expression domains and iterative cell division.This two-dimensional model will form the basis for future studies into robustness of adaxial-abaxial patterning.

A New Efficient Finite Volume Modeling of Small Amplitude Free Surface Flows with Unstructured Grid

A staggered finite-volume technique for non-hydrostatic, small amplitude free surface flow governed by the incompressible Navier-Stokes equations is presented there is a proper balance between accuracy and computing time. The advection and horizontal diffusion terms in the momentum equation are discretized by an integral interpolation method on the orthogonal unstructured staggered mesh and, while it has the attractive property of being conservative. The pressure-correction algorithm is employed for the non-hydrostatic pressure in order to achieve second-order temporal accuracy. A conservative scalar transport algorithm is also applied to discretize k - c equations in this model. The eddy viscosity is calculated from the k-c turbulent model. The resulting model is mass and momentum conservative. The model is verified by two examples to simulate unsteady small amplitude free surface flows where non-hydrostatic pressures have a considerable effect on the velocity field, and then applied to simulate the tidal flow in the Bohai Sea.

Modeling and Optimization of Interaction between Small Coastal Pelagic Fish, their Biological Predators and Fishermen

Small coastal pelagic fish are one of the fish families most affected by sea fishing. This man-made phenomenon leads to an imbalance in the marine and coastal ecosystem and is one of the main causes of migration north and offshore of the ranges. We used the ordinary differential equations to model the interactions existing between small pelagic resources and fishermen. Modelling follows the same of the Lotka-Volterra equations with a difference in the number of variables. This study confirmed the instability of the marine ecosystem. The objective is first of all to model a system of three interacting individuals composed of two distinct types of predators and two types of prey, and then optimise this interaction with the aim of conserving biodiversity in the ecosystem under study. Determining the Jacobian matrix made it possible to calculate the reproduction rate basic (R0). The study of the strong connectedness has made it possible to reduce the number of variables without losing the objective of the study. A computer program implemented on the language computer python facilitated the visualisation of the results.

Evaluating the accuracy and reproducibility of ChatGPT-4 in answering patient questions related to small intestinal bacterial overgrowth

BACKGROUND Small intestinal bacterial overgrowth(SIBO)poses diagnostic and treatment challenges due to its complex management and evolving guidelines.Patients often seek online information related to their health,prompting interest in large language models,like GPT-4,as potential sources of patient education.AIM To investigate ChatGPT-4's accuracy and reproducibility in responding to patient questions related to SIBO.METHODS A total of 27 patient questions related to SIBO were curated from professional societies,Facebook groups,and Reddit threads.Each question was entered into GPT-4 twice on separate days to examine reproducibility of accuracy on separate occasions.GPT-4 generated responses were independently evaluated for accuracy and reproducibility by two motility fellowship-trained gastroenterologists.A third senior fellowship-trained gastroenterologist resolved disagreements.Accuracy of responses were graded using the scale:(1)Comprehensive;(2)Correct but inadequate;(3)Some correct and some incorrect;or(4)Completely incorrect.Two responses were generated for every question to evaluate reproducibility in accuracy.RESULTS In evaluating GPT-4's effectiveness at answering SIBO-related questions,it provided responses with correct information to 18/27(66.7%)of questions,with 16/27(59.3%)of responses graded as comprehensive and 2/27(7.4%)responses graded as correct but inadequate.The model provided responses with incorrect information to 9/27(33.3%)of questions,with 4/27(14.8%)of responses graded as completely incorrect and 5/27(18.5%)of responses graded as mixed correct and incorrect data.Accuracy varied by question category,with questions related to“basic knowledge”achieving the highest proportion of comprehensive responses(90%)and no incorrect responses.On the other hand,the“treatment”related questions yielded the lowest proportion of comprehensive responses(33.3%)and highest percent of completely incorrect responses(33.3%).A total of 77.8%of questions yielded reproducible responses.CONCLUSION Though GPT-4 shows promise as a supplementary tool for SIBO-related patient education,the model requires further refinement and validation in subsequent iterations prior to its integration into patient care.

Structural modeling of proteins by integrating small-angle x-ray scattering data

Elucidating the structure of large biomolecules such as multi-domain proteins or protein complexes is challenging due to their high flexibility in solution. Recently, an ＂integrative structural biology＂ approach has been proposed, which aims to determine the protein structure and characterize protein flexibility by combining complementary high- and lowresolution experimental data using computer simulations. Small-angle x-ray scattering（SAXS） is an efficient technique that can yield low-resolution structural information, including protein size and shape. Here, we review computational methods that integrate SAXS with other experimental datasets for structural modeling. Finally, we provide a case study of determination of the structure of a protein complex formed between the tandem SH3 domains in c-Cb1-associated protein and the proline-rich loop in human vinculin.

Small-Angle X-Ray Scattering of Amorphous Germanium: Numerical Modeling

The present work deals with a detailed analysis of the small-angle X-ray scattering of nanoporous atomistic models for amorphous germanium. Structures with spherical nanovoids, others with arbitrarily oriented ellipsoidal ones, with monodisperse and polydisperse size distributions, were first generated. After relaxing the as-generated structure, we compute its radial distribution function, and then we deduce by the Fourier transform technique its X-ray scattering pattern. Using a smoothing procedure, the computed small-angle X-ray scattering patterns are corrected for the termination errors due to the finite size of the model, allowing so, for the first time at our best knowledge, a rigorous quantitative analysis of this scattering. The Guinier’s law is found to be valid irrespective of size and shape of the nanovoids over a scattering vector-range extending beyond the expected limit. A weighted combination of the Guinier’s forms accounts for well the nanovoid size distribution in the amorphous structure. The invariance of the Q-factor and its relationship to the void volume fraction are also confirmed. Our findings support then the quantitative analyses of available small-angle X-ray scattering data for amorphous germanium.

Transfer function modeling and analysis of the open-loop Buck converter using the fractional calculus

Based on the fact that the real inductor and the real capacitor are fractional order in nature and the fractional calculus,the transfer function modeling and analysis of the open-loop Buck converter in a continuous conduction mode（CCM） operation are carried out in this paper.The fractional order small signal model and the corresponding equivalent circuit of the open-loop Buck converter in a CCM operation are presented.The transfer functions from the input voltage to the output voltage,from the input voltage to the inductor current,from the duty cycle to the output voltage,from the duty cycle to the inductor current,and the output impedance of the open-loop Buck converter in CCM operation are derived,and their bode diagrams and step responses are calculated,respectively.It is found that all the derived fractional order transfer functions of the system are influenced by the fractional orders of the inductor and the capacitor.Finally,the realization of the fractional order inductor and the fractional order capacitor is designed,and the corresponding PSIM circuit simulation results of the open-loop Buck converter in CCM operation are given to confirm the correctness of the derivations and the theoretical analysis.

Application of SCS Model in Estimation of Runoff from Small Watershed in Loess Plateau of China

Soil Conservation Service (SCS) model, developed by U. S. Soil Conservation Service in 1972, has been widely applied in the estimation of runoff from an small watershed. In this paper, based on the remote sensing geo-information data of land use and soil classification all obtained from Landsat images in 1996 and 1997 and con-ventional data of hydrology and meteorology, the SCS model was investigated for simulating the surface runoff for single rainstorm in Wangdonggou watershed, a typical small watershed in the Loess Plateau, located in Changwu County of Shaanxi Province of China. Wangdonggou watershed was compartmentalized into 28 sub-units according to natural draining division,and the table of curve number (CN) values fitting for Wangdonggou watershed was also presented. During the flood period from 1996 to 1997, the hydrograph of calculated runoff process using the SCS model and the hydrograph of observed runoff process coincided very well in height as well as shape, and the model was of high precision above 75%. It is indicated that the SCS model is legitimate and can be successfully used to simulate the runoff generation and the runoff process of typical small watershed based on the remote sensing geo-information in the Loess Plateau.

Model test to investigate failure mechanism and loading characteristics of shallow-bias tunnels with small clear distance

Based on the similarity theory,a tunnel excavation simulation testing system under typical unsymmetrical loading conditions was established.Using this system,the failure mechanism of surrounding rock of shallow-bias tunnels with small clear distance was analyzed along with the load characteristics.The results show that:1) The failure process of surrounding rock of shallow-bias tunnels with small clear distance consists of structural and stratum deformation induced by tunnel excavation; Microfracture surfaces are formed in the tunnel surrounding rock and extend deep into the rock mass in a larger density; Tensile cracking occurs in shallow position on the deep-buried side,with shear slip in deep rock mass.In the meantime,rapid deformation and slip take place on the shallow-buried side until the surrounding rocks totally collapse.The production and development of micro-fracture surfaces in the tunnel surrounding rock and tensile cracking in the shallow position on the deep-buried side represent the key stages of failure.2) The final failure mode is featured by an inverted conical fracture with tunnel arch as its top and the slope at tunnel entrance slope as its bottom.The range of failure on the deep-buried side is significantly larger than that on the shallow-buried side.Such difference becomes more prominent with the increasing bias angle.What distinguishes it from the "linear fracture surface" model is that the model proposed has a larger fracture angle on the two sides.Moreover,the bottom of the fracture is located at the springing line of tunnel arch.3) The total vertical load increases with bias angle.Compared with the existing methods,the unsymmetrical loading effect in measurement is more prominent.At last,countermeasures are proposed according to the analysis results: during engineering process,1) The surrounding rock mass on the deep-buried side should be reinforced apart from the tunnel surrounding rock for shallow-buried tunnels with small clear distance; moreover,the scope of consolidation should go beyond the midline of tunnel(along the direction of the top of slope) by 4 excavation spans of single tunnel.2) It is necessary to modify the load value of shallow-bias tunnels with small clear distance.

Hierarchical hybrid testability modeling and evaluation method based on information fusion

In order to meet the demand of testability analysis and evaluation for complex equipment under a small sample test in the equipment life cycle, the hierarchical hybrid testability model- ing and evaluation method （HHTME）, which combines the testabi- lity structure model （TSM） with the testability Bayesian networks model （TBNM）, is presented. Firstly, the testability network topo- logy of complex equipment is built by using the hierarchical hybrid testability modeling method. Secondly, the prior conditional prob- ability distribution between network nodes is determined through expert experience. Then the Bayesian method is used to update the conditional probability distribution, according to history test information, virtual simulation information and similar product in- formation. Finally, the learned hierarchical hybrid testability model （HHTM） is used to estimate the testability of equipment. Compared with the results of other modeling methods, the relative deviation of the HHTM is only 0.52%, and the evaluation result is the most accu rate.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

AN ANALYTICAL SOLUTION FOR THE MODEL OF DRUG DISTRIBUTION AND ABSORPTION IN SMALL INTESTINE

According to the physiological and anatomical characteristics of small intestine,neglecting the effect of its motility on the distribution and absorption of drug and nutrient,Y.Miyamoto et al.proposed a model of two-dimensional laminar flow in a circular porous tube with permeable wall and calculated the concentration profile of drugby numerical analysis.In this paper,we give a steady-state analytical solution of the above model including deactivationterm.The obtained results are in agreement with the results of their numerical analysis. Moreover the analytical solution presented in this paper reveals the relation among the physiological parameters of the model and describes the basic absorption rule of drug and nutrient through the intestinal wall and hence pro- vides a theoretical basis for determining the permeability and reflection coefficient through in situ experiments.

Allometric models for aboveground biomass of six common subtropical shrubs and small trees

The aboveground biomass(AGB)of shrubs and small trees is the main component for the productivity and carbon storage of understory vegetation in subtropical secondary forests.However,few allometric models exist to accurately evaluate understory biomass.To estimate the AGB of five common shrub(diameter at base<5 cm,<5 m high)and one small tree species(<8 m high,trees’s seedling),206 individuals were harvested and species-specific and multi-species allometric models developed based on four predictors,height(H),stem diameter(D),crown area(Ca),and wood density(ρ).As expected,the six species possessed greater biomass in their stems compared with branches,with the lowest biomass in the leaves.Species-specific allometric models that employed stem diameter and the combined variables of D~2H andρDH as predictors accurately estimated the components and total AGB,with R^(2) values from 0.602 and 0.971.A multi-species shrub allometric model revealed that wood density×diameter×height(ρDH)was the best predictor,with R^(2) values ranging from between 0.81 and 0.89 for the components and total AGB,respectively.These results indicated that height(H)and diameter(D)were effective predictors for the models to estimate the AGB of the six species,and the introduction of wood density(ρ)improved their accuracy.The optimal models selected in this study could be applied to estimate the biomass of shrubs and small trees in subtropical regions.