General Modeling System Research Articles

A study to assess the outcome of information education communication on knowledge regarding child abuse among pre adolescent girls age group of 10–12 years in selected schools

Population means the whole number of people, or inhabitant, in a country, or portion of country population explosion mean very rapid and unprecedented growth of population which create lots of problems in the country. The research design adopted was pre experimental one group pre-test post design. The conceptual framework based on modified Ludwing Von Bertanalyffys General system model. The study has been conducted in selected school, wankaner Non Probability convenient sampling technique has been adopted to select the desired sample. The sample size was 60. As an intervention of 20 minute of sterilisation was administered to group. The data was collected through structured knowledge questionnaire level of knowledge assess among pre-adolescent girl. The collected data were analysed by using both descriptive and inferential statistical method. ”t” test was used for assessing the effectiveness of structured teaching programme on level of knowledge among pre-adolescent girl. The obtained “t” value was 10.72 which was significant at 0.05. level. The finding of the study was revealed that structured teaching programme helps in increasing the level of knowledge Among all the demographic variable only education of mother and father, occupation of mother and father and sources of information was significant at 0.05level.

Cu-CHA - a model system for applied selective redox catalysis.

We review the structural chemistry and reactivity of copper-exchanged molecular sieves with chabazite (CHA) topology, as an industrially applied catalyst in ammonia mediated reduction of harmful nitrogen oxides (NH3-SCR) and as a general model system for red-ox active materials (also the recent results in the direct conversion of methane to methanol are considered). Notwithstanding the apparent structural simplicity of the material, a crystalline zeolite with only one crystallographically independent T site, the Cu-SSZ-13 catalyst reveals a high degree of complexity that has been decrypted by state of the art characterization tools. From the reviewed data, the following important aspects in the understanding of the Cu-SSZ-13 catalyst clearly emerged: (i) the structural dynamics of the Cu-species require precise control of the environmental conditions during activation and characterization; (ii) the availability of a large library of well-defined catalysts with different Si/Al and Cu/Al compositional ratios is key in unravelling the red-ox properties of the active Cu sites; (iii) a multi-technique approach is required, combining complementary techniques able to provide independent structural, electronic and vibrational information; (iv) synchrotron radiation based techniques (EXAFS, XANES, XES and time-resolved powder XRD) played a relevant role; (v) operando methodology (possibly supported by advanced chemometric approaches) is essential in obtaining structure-reactivity relations; (vi) the support of theoretical studies has been indispensable for the interpretation of the experimental output from characterization and for a critical assessment of mechanistic models. The old literature that classified Cu-exchanged zeolites in the category of single-site catalysts has been partially disproved by the recent advanced studies where it has been shown that the active site in the low temperature NH3-SCR catalyst is a mobile Cu-molecular entity that "lives in symbiosis" with an inorganic solid framework. Only in the high temperature NH3-SCR regime do the mobile Cu-species lose their ligands and find docking sites at the internal walls of the zeolite framework, thus reflecting the idea of a single-site catalyst. After a brief introduction, the review is divided into three main parts devoted to characterization (Section 2), reactivity (Section 3), and industrial applications (Section 4), followed by some concluding remarks and providing a perspective of the field.

Development of a monthly to seasonal forecast framework tailored to inland waterway transport in central Europe

Abstract. Traditionally, navigation-related forecasts in central Europe cover short- to medium-range lead times linked to the travel times of vessels to pass the main waterway bottlenecks leaving the loading ports. Without doubt, this aspect is still essential for navigational users, but in light of the growing political intention to use the free capacity of the inland waterway transport in Europe, additional lead time supporting strategic decisions is more and more in demand. However, no such predictions offering extended lead times of several weeks up to several months currently exist for considerable parts of the European waterway network. This paper describes the set-up of a monthly to seasonal forecasting system for the German stretches of the international waterways of the Rhine, Danube and Elbe rivers. Two competitive forecast approaches have been implemented: the dynamical set-up forces a hydrological model with post-processed outputs from ECMWF general circulation model System 4, whereas the statistical approach is based on the empirical relationship (teleconnection) of global oceanic, climate and regional hydro-meteorological data with river flows. The performance of both forecast methods is evaluated in relation to the climatological forecast (ensemble of historical streamflow) and the well-known ensemble streamflow prediction approach (ESP, ensemble based on historical meteorology) using common performance indicators (correlation coefficient; mean absolute error, skill score; mean squared error, skill score; and continuous ranked probability, skill score) and an impact-based evaluation quantifying the potential economic gain. The following four key findings result from this study: (1) as former studies for other regions of central Europe indicate, the accuracy and/or skill of the meteorological forcing used has a larger effect than the quality of initial hydrological conditions for relevant stations along the German waterways. (2) Despite the predictive limitations on longer lead times in central Europe, this study reveals the existence of a valuable predictability of streamflow on monthly up to seasonal timescales along the Rhine, upper Danube and Elbe waterways, and the Elbe achieves the highest skill and economic value. (3) The more physically based and the statistical approach are able to improve the predictive skills and economic value compared to climatology and the ESP approach. The specific forecast skill highly depends on the forecast location, the lead time and the season. (4) Currently, the statistical approach seems to be most skilful for the three waterways investigated. The lagged relationship between the monthly and/or seasonal streamflow and the climatic and/or oceanic variables vary between 1 month (e.g. local precipitation, temperature and soil moisture) up to 6 months (e.g. sea surface temperature). Besides focusing on improving the forecast methodology, especially by combining the individual approaches, the focus is on developing useful forecast products on monthly to seasonal timescales for waterway transport and to operationalize the related forecasting service.

Production optimization in sausage industry based on the demand of the products

AbstractThe sausage production industry has recently had an increase in consumption. This led to the search for the most efficient use of available resources in order to achieve increased productivity, reduced costs, reliability in service, and reduce delivery times. In the sausage industry a wide variety of products is obtained, most of these products do not has an exclusive line, and therefore there is a competition for equipment and intermediate states. The manufactured products are usually perishable and it is recommended that production should not exceed the demand under the disadvantage of stocks generating and exceed the shelf life of the product. The objective of this work was the adaptation and use of a mathematical model of production scheduling to optimize the production of a sausage industry, from demand values for each product. The proposed approach treats the problem as mixed integer linear programming to represent the decisions involved and was solved with the GAMS software (Generic Algebraic Modeling System). The developed model was applied to the problem of production scheduling with actual operational data from a regional industry. The results of the application of the model with data collected in the industry were an increase of the total production of the plant in the range of 20%. and has shown its capacity to generate better results than the production results presented by industry. Therefore, the result of the model presented here can assist in making the production scheduling decisions in the sausage industry.Practical applicationsThe objective of the work was to maximize the production of the products taking into account the demand of each of them avoiding the formation of stocks due to the useful life of the products. For this, we use a mathematic model adapted to the sausage industry that operates in batch. The production scheduling was done in a single campaign mode for weekly production in the industry and short‐term production planning was done to produce the stocks of intermediate products needed at the beginning of the campaign. The results presented in the Gantt tables can be used on the factory floor. The results of the application of the model with data collected in the industry were an increase of the total production of the plant in the range of 20%.

On the performance of a virtual user pairing scheme to efficiently utilize the spectrum of unpaired users in NOMA

This paper evaluates the performance of a virtual user pairing scheme that efficiently utilizes the spectrum of unpaired users in non-orthogonal multiple access (NOMA), termed as VP-NOMA. The scheme aims at utilizing the frequency bands of those users which remain unpaired due to the non-uniform distribution of users in a cellular area. We consider a case where the cell edge users are more than the cell center users, so that complete one-to-one correspondence does not exist between all cell center and cell edge users to be accommodated/paired using conventional NOMA (C-NOMA) user pairing. Thus, some cell edge users remain unpaired, and are served using conventional multiple access (OMA) schemes. In such scenario, VP-NOMA pairs a single cell center user with two or more clustered (closely located) cell edge users over non-overlapping frequency bands, thus enabling the cell center user to efficiently use the frequency bands of these previously unpaired cell edge users. Performance of VP-NOMA in terms of ergodic sum capacity (ESC), outage probability (OP), and outage sum capacity (OSC), is analyzed through comprehensive mathematical derivations and simulations for a generalized system model. Moreover, the mathematical analysis is validated through close concordance between analytical and simulation results of ESC, OP, and OSC.

Systems enabling low-carbon operations: The salience of accuracy

This article focuses on systems that enable low-carbon operations within organizations. The thesis that system accuracy matters to achieving low-carbon operations is explored using two approaches. First, a generic system model is developed and three alternative technical architectures are described, thereby illustrating that accuracy varies across architectures but can also be attended to outside system boundaries. Second, empirical analysis of 220 global organizations assesses the association between accuracy, managerial incentives, emission targets, and low-carbon impacts. Overall, empirical findings demonstrate that firms attending to accuracy tend to have managerial incentives to reduce emissions and emission reductions targets in place. They also tend to exhibit reduced carbon emissions for the same level of economic output.

Precision Motion Control for Electro-Hydraulic Servo Systems With Noise Alleviation: A Desired Compensation Adaptive Approach

A desired compensation adaptive controller is proposed in this paper for precision motion control of electro-hydraulic servo systems, with consideration of the nonlinearity, modeling uncertainty, and especially the severe measurement noise arising from actual state feedbacks and deteriorating the control performance significantly. To alleviate the noise, actual states in the model-based compensation design are replaced with corresponding desired values. Considering that the general hydraulic system model contains unmatched modeling uncertainties (e.g., unmodeled nonlinear friction), an innovative approach to construct the desired values of the intermediate state variables is proposed in backstepping design procedure. It is then applied especially to the load pressure state, which appears in the system in a nonlinear way, and the discontinuous sign function is approximated by a continuous function to facilitate the controller design. As a result, the adaptive compensation and the regressor in the proposed controller depend on the desired trajectory and online parameter estimates only. Hence, the effect of measurement noise can be reduced and then high control performance is expected. Theoretical analysis reveals that the proposed controller can guarantee a prescribed transient performance and final tracking accuracy in the presence of both parametric uncertainties and uncertain nonlinearities. Moreover, it can guarantee the asymptotic tracking performance when subjected to parametric uncertainties only. Extensively comparative experimental results are obtained to verify the effectiveness of the proposed control strategy.

Noise properties of Fourier deconvolution for time-domain electromagnetic soundings

The transient electromagnetic method (TEM) is widely used for mapping the earth’s subsurface resistivity structures, e.g., for groundwater or mineral exploration, using airborne and ground-based systems. Data from TEM surveys can be modified using Fourier deconvolution to correct for instrument drift, increase apparent bandwidth, or alter the apparent excitation waveform, e.g., to fuse or compare measurements from different systems, for visual presentation purposes, or to make the data compatible with a specific processing or inversion code. Although this method has been applied in several studies, little attention has been devoted to its properties with regard to noise. Using a generic analytical system model and examples featuring synthetic and field data, we perform a detailed analysis of the noise properties of Fourier deconvolution in the context of TEM. We find that although the effects from stationary noise are trivial, effects from nonstationary noise are less intuitive and more severe, e.g., causing on-time noise phenomena to degrade off-time data. In general, we observe that the method decreases the signal-to-noise ratio, and our recommendation is therefore that Fourier deconvolution should only be applied when it is desirable for presentation purposes or when strictly necessary for processing or inversion.

Arabic Online Handwriting Recognition (AOHR)

This article comprehensively surveys Arabic Online Handwriting Recognition (AOHR). We address the challenges posed by online handwriting recognition, including ligatures, dots and diacritic problems, online/offline touching of text, and geometric variations. Then we present a general model of an AOHR system that incorporates the different phases of an AOHR system. We summarize the main AOHR databases and identify their uses and limitations. Preprocessing techniques that are used in AOHR, viz. normalization, smoothing, de-hooking, baseline identification, and delayed stroke processing, are presented with illustrative examples. We discuss different techniques for Arabic online handwriting segmentation at the character and morpheme levels and identify their limitations. Feature extraction techniques that are used in AOHR are discussed and their challenges identified. We address the classification techniques of non-cursive (characters and digits) and cursive Arabic online handwriting and analyze their applications. We discuss different classification techniques, viz. structural approaches, Support Vector Machine (SVM), Fuzzy SVM, Neural Networks, Hidden Markov Model, Genetic algorithms, decision trees, and rule-based systems, and analyze their performance. Post-processing techniques are also discussed. Several tables that summarize the surveyed publications are provided for ease of reference and comparison. We summarize the current limitations and difficulties of AOHR and future directions of research.

Descriptive analysis of analogies between information security management and queuing systems

It is established that none of the existing international standards contains specific methods for the development of project requirements for the information security management system applied to a particular organization for now. To overcome this limitation it is considered a possible analogy of queuing systems and information security management systems. A descriptive analysis of possible analogies is carried out by comparing the composition and the general functional model of the queuing system. On the basis of this comparison, it is established that the mathematical apparatus of the theory of queuing systems can be used to formulate project requirements for the information security management system. This will allow the development of the model of such system. It will be possible to determine sensitivity of different aspects of information security applied to a particular organization with its help.

Integrated model of port oil piping transportation system safety including operating environment threats

Abstract The paper presents an integrated general model of complex technical system, linking its multistate safety model and the model of its operation process including operating environment threats and considering variable at different operation states its safety structures and its components safety parameters. Under the assumption that the system has exponential safety function, the safety characteristics of the port oil piping transportation system are determined.

Experimental Validation of Energy Harvesting-System Availability Improvement Through Battery Heating

Operation of wireless sensor nodes or battery powered embedded systems in cold and harsh environments requires careful battery selection and management. In this paper, we first provide a general model of an energy harvesting sensor system and the respective energy flows. We then present a maximum power point tracking solar harvesting system according to that model. The system is coupled with rechargeable Li-ion batteries and equipped with a battery heating mechanism. The significant signals of that system are monitored to have a deeper insight into the energy distribution. Real-world experiments demonstrate benefits of battery heating during high irradiation periods at temperatures below safe charging conditions. The presented case study for a cold winter day shows that the additional energy, which can be stored thanks to battery heating would more than double the autonomy of the sensor system.

Comparative Geological and Mineral-Petrological Analysis of Ore-Bearing Rock in Lithium and Beryllium Deposits for Modeling the Behavior of Ore Minerals During Processing

A comparative analysis of ore-bearing rock in the Zavitinskoe and Ermakovskoe deposits is made. Such an analysis is needed because of the requirements of working with ore-mining concentrates, which model the basic physical and chemical parameters of beryllium-containing concentrates that influence their preparation efficiency and subsequent opening with reagents. It was found that it is possible to develop a general model system for the chemical and physical behavior of lithium and beryllium ore minerals and the bearing rock in the Ermakovskoe and Zavitinskoe deposits. Ore materials in the Zavitinskoe deposit (lithium association) model the physicochemical behavior of beryllium-containing ore minerals in the Ermakovskoe deposit (beryllium association).

Analytical analysis on damping characteristics of rotor system

A general vibration model of a flexible rotor system is established to investigate the influences of the damping characteristics on vibration behaviors. Based on the multi-scale method, the analytical solutions of steady-state and transient-state are derived under the positive and negative conditions of nonlinear damping. The physical significance of the coefficients and their influences on rotor behaviors are analyzed through theoretical analysis and numerical calculation. The experimental results elaborate the damping effect and verify the rationality of the model.

Evaluating Regulation within an Artificial Financial System A Framework and Its Application to the Liquidity Coverage Ratio Regulation

We develop a general model of the financial system that allows for the evaluation of bank regulation. Our framework comprises the agents and institutions that have proved crucial in the propagation of the subprime mortgage shock in the U.S. into a global financial crisis: Commercial banks and investment banks, which can also be interpreted as shadow banks, interact on wholesale debt markets. Beside a market for short term interbank loans and long term bank bonds, other funding sources include insured customer deposits, uninsured investor deposits and repos. While credit to the real sector is the principal asset of commercial banks, investment banks specialize in trading securities, which may differ according to risk, maturity and liquidity. As a first application of the model we implement the liquidity coverage ratio (LCR) regulation and analyze its impact on bank balance sheets, interest rates, the transmission of monetary policy and the stability of bank lending in the face of shocks. We find that the LCR regulation reduces the supply of loans to the real sector, increases the maturity and interest rate of long term wholesale debt, and strongly diminishes the role of the overnight interbank market as a funding source. Our simulations suggest that the transmission of changes to short term monetary policy rates is severely impaired when the LCR regulation is binding. Furthermore, we find that a strong confidence shock can lead to a protracted credit crunch under the liquidity regulation.

Evaluation of growth, milk and manure production in Norwegian dairy goats in one highland of Tanzania 30 years after introduction

Dairy goats have been imported into Tanzania since the 1960s to improve the milk production of Small East African (SEA) goats through crossbreeding. The SEA goats have poor genetic potential for milk. Although crossbreeding programmes started in the early 1980s, most were abandoned or failed for a number of reasons, including lack of performance records, which were important for the design and management of breeding programmes for dairy goats. This study was designed to evaluate growth, lactation, and manure yield in Norwegian Landrace (NL) goats in one rural community of Tanzania. Growth was evaluated in 211 goats by birth weight (BW), weaning weight (WW), weight at six (W6M) and nine months (W9M), and average daily gain (ADG). Lactation performance involved lactation milk yield (LMY), lactation length (LL), and dry off days in 251 does. Twenty four additional goats were confined to determine manure production and chemical composition in a different on-station study. The general linear model (GLM) of Statistical Analysis System (SAS) was used in data analysis. Averages for BW, WW, and adult weight (W9M) were 3.27 ± 0.04, 12.79 ± 0.09, and 28.33 ± 0.19 kg, respectively. Average LMY of 322 litres, LL 214.5 days and dry off days of 84 were obtained. Animals with ≥75% NL genetic make-up produced more milk and showed longer LL and higher ADG than those with 50%. For example, BW was 3.38 ± 0.12 kg in 75% NL animals compared with 2.56 ± 0.12 kg in 50%, whereas LMY was 324.09 ± 16.22 and 248.67 ± 16.20, respectively. The amount of manure was 311.8 g and 218 g per day for mature and grower goats, respectively. Nitrogen was the major content, comprising 1.98% of all nutrients in manure. Compared with the early years of introducing NL goats, growth and productivity of milk have increased several fold, indicating that the development of NL goats in Mgeta is positive at the moment. Keywords: Exotic goats, goat kids, Mgeta, productivity, smallholder

An EcoCity model for regulating urban land cover structure and thermal environment: Taking Beijing as an example

Urban land-use/cover changes and their effects on the eco-environment have long been an active research topic in the urbanization field. However, the characteristics of urban inner spatial heterogeneity and its quantitative relationship with thermal environment are still poorly understood, resulting in ineffective application in urban ecological planning and management. Through the integration of “spatial structure theory” in urban geography and “surface energy balance” in urban climatology, we proposed a new concept of urban surface structure and thermal environment regulation to reveal the mechanism between urban spatial structure and surface thermal environment. We developed the EcoCity model for regulating urban land cover structure and thermal environment, and established the eco-regulation thresholds of urban surface thermal environments. Based on the comprehensive analysis of experimental observation, remotely sensed and meteorological data, we examined the spatial patterns of urban habitation, industrial, infrastructure service, and ecological spaces. We examined the impacts of internal land-cover components (e.g., urban impervious surfaces, greenness, and water) on surface radiation and heat flux. This research indicated that difference of thermal environments among urban functional areas is closely related to the proportions of the land-cover components. The highly dense impervious surface areas in commercial and residential zones significantly increased land surface temperature through increasing sensible heat flux, while greenness and water decrease land surface temperature through increasing latent heat flux. We also found that different functional zones due to various proportions of green spaces have various heat dissipation roles and ecological thresholds. Urban greening projects in highly dense impervious surfaces areas such as commercial, transportation, and residential zones are especially effective in promoting latent heat dissipation efficiency of vegetation, leading to strongly cooling effect of unit vegetation coverage. This research indicates that the EcoCity model provides the fundamentals to understand the coupled mechanism between urban land use structure and surface flux and the analysis of their spatiotemporal characteristics. This model provides a general computational model system for defining urban heat island mitigation, the greening ratio indexes, and their regulating thresholds for different functional zones.

Nonequilibrium Thermodynamics and Steady State Density Matrix for Quantum Open Systems

We consider the generic model of a finite-size quantum electron system connected to two (temperature and particle) reservoirs. The quantum open system is driven out of equilibrium by the presence of both potential temperature and chemical differences between the two reservoirs. The nonequilibrium (NE) thermodynamical properties of such a quantum open system are studied for the steady state regime. In such a regime, the corresponding NE density matrix is built on the so-called generalised Gibbs ensembles. From different expressions of the NE density matrix, we can identify the terms related to the entropy production in the system. We show, for a simple model, that the entropy production rate is always a positive quantity. Alternative expressions for the entropy production are also obtained from the Gibbs–von Neumann conventional formula and discussed in detail. Our results corroborate and expand earlier works found in the literature.

Synthesizing power management strategies for wireless sensor networks with UPPAAL-STRATEGO

Effective power management has become a key concern in the design of wireless sensor networks. Dynamic power management refers to strategies which selectively switch between several power states of a device during the runtime in order to achieve a tradeoff between power consumption and performance. In this article, we present a novel methodology that exploits current model-checking technology for automatic synthesis for dynamic power management. The generic system model for dynamic power management is modeled as a network of timed games. And the synthesis objectives are expressed as synthesis queries. Subsequently, automatic synthesis of power management strategies is performed by UPPAAL-STRATEGO with respect to the synthesis queries. Once a strategy has been constructed, its performance can be analyzed through statistical model-checking using the same tool. The modeling and synthesizing procedures are illustrated with a running example. Finally, the applicability of the methodology is assessed by synthesizing and evaluating a range of power management strategies for a concrete sensor node. Our methodology can be employed to help designers in constructing dynamic power management strategies for wireless sensor networks in practical applications.

Design and analysis of compressive antenna arrays for direction of arrival estimation

In this paper we investigate the design of compressive antenna arrays for narrow-band direction of arrival (DOA) estimation that aim to provide a larger aperture with a reduced hardware complexity and allowing reconfigurability, by a linear combination of the antenna outputs to a lower number of receiver channels. We present a basic receiver architecture of such a compressive array and introduce a generic system model that includes different options for the hardware implementation. We then discuss the design of the analog combining network that performs the receiver channel reduction, and propose two design approaches. The first approach is based on the spatial correlation function which is a low-complexity scheme that in certain cases admits a closed-form solution. The second approach is based on minimizing the Cramér-Rao Bound (CRB) with the constraint to limit the probability of false detection of paths to a pre-specified level. Our numerical simulations demonstrate the superiority of the proposed optimized compressive arrays compared to the sparse arrays of the same complexity and to compressive arrays with randomly chosen combining kernels.