Different Kinds Of Models Research Articles

Non-genetic in vivo experimental models of epilepsy and vagus nerve stimulation

Complexity of epilepsy and a seizure as clinical and pathophysiological entities is reflected in a large number of experimental models of epilepsy. They could be stratified into acute and chronic, chemical and electric. The present review describes some most typical non-genetic models of different kinds used on laboratory rats. Also, the results of application of these models for research of vagus nerve stimulation as a novel treatment of drug resistant epilepsy are summarized.

Knowledge graph embedding via reasoning over entities, relations, and text

Knowledge graph embedding has attracted significant research interest in the field of intelligent web, which aims to embed both entities and relations into a low-dimensional space. In particular, there are two fundamentally different kinds of models, latent feature models and graph feature models, to infer new predictions in the graph. Latent feature models are expert at using latent features of entities to explain triples and infer these features automatically from the data, while graph feature models are do well in extracting features from the observable graph patterns. Combining the strengths of these two fundamental models is a promising approach to increase the predictive performance of graph models. Thus, we propose a new combined model, named as Text-enhanced Knowledge Graph Embedding (TKGE), to perform inference over entities, relations, and text. The model is not only well-suited for modeling interactions of their latent features, but also well-suited for modeling paths between entities in the graph. Experimental results show that TKGE has significant improvements compared to baselines on two tasks: knowledge graph completion and triple classification.

Modelling water with simple Mercedes-Benz models

ABSTRACTThe structures and properties of biomolecules, such as proteins, nucleic acids and membranes, depend on water. Water is also very important in industry. Overall, water is unusual substance with more than 70 anomalous properties. The understanding of water is advancing significantly due to theoretical and computational modelling. There are different kinds of models, models with fine-scale properties and increasing structural detail with increasing computational expense and simple models which focus on global properties of water like thermodynamics, phase diagram and are less computational expensive. Simplified models give a better understanding of water in ways that complement more complex models. Here, we review a simple model, the two-dimensional Mercedes-Benz model of water. We present results by Monte Carlo simulations for anomalies and phase diagram and application of various theoretical methods.

Propuesta de un modelo para analizar y medir la percepción de la calidad de servicio en los programas de cuarto nivel.

El presente artículo tiene como objetivo proponer un modelo para analizar la percepción y eficacia de la calidad de servicio de los estudiantes en programas de cuarto nivel en el Ecuador, actualmente las instituciones gubernamentales han aumentado sus reglamentos para evaluar los establecimientos que ofrecen una educación superior. La metodología que se tomó para realizar este trabajo fue la de observación, se revisaron varios artículos de autores que se centraron en elaborar diferentes tipos de modelos enfocados a la evaluación de la calidad de servicio de las instituciones educativas existentes como: Serqual, servperf y DIHEQS. El modelo que se propone es “Calidad percibida en posgrado” (CPEP). Este modelo está compuesto por las siguientes dimensiones: a) Profesores y enseñanza; b) Malla curricular; c) Tecnología y comunicación; d) Actividades adicionales; y d) Administración y organización, que se dirige a la lealtad y convirtiéndose en una ventaja competitiva hacia la institución educativa

A novel rule based machine translation scheme from Greek to Greek Sign Language: Production of different types of large corpora and Language Models evaluation

One of the aims of assistive technologies is to help people with disabilities to communicate with others and to provide means of access to information. As an aid to Deaf people, in this work we present a novel prototype Rule Based Machine Translation (RBMT) system for the creation of large and quality written Greek Sign Language (GSL) glossed corpora from Greek text. In particular, the proposed RBMT system assists the professional GSL translator in speeding up the production of different kinds of GSL glossed corpora. Then each glossed corpus is used for the production/creation of Language Model (LM) n-grams. With the GSL glossed corpus from Greek text, we can build, test and evaluate different kinds of Language Models for different kinds of glossed GSL corpora. Here, it should be noted that it does not require grammar knowledge of GSL but only very basic GSL phenomena covered by manual RBMT rules as it assists the professional human translator. Furthermore, it should also be stressed that Language Models for written GSL gloss are missing from the scientific literature, thus this work is pioneer in this field. Evaluation of the proposed scheme is carried out for the weather reports domain, where 20,284 tokens and 1000 sentences have been produced. By using the BiLingual Evaluation Understudy (BLEU) metric score, our prototype RBMT system achieves a relative score of 0.84 (84%) for 4-grams and 0.9 (90%) for 1-grams.

An analysis of the development of port operation in Da Nang Port, Vietnam

This paper presents the current operating status in Da Nang Port, Vietnam in the period 2012-2016. The port operation had positive changes that were reflected by a significant increase in total throughputs, especially containerized cargo volumes. Classical decomposition techniques are used to find trend-cycle and seasonal components of monthly throughput flows. Appropriate predictive models of different kinds of throughputs are proposed. Finally, a development strategy towards containerization and investment policies in facilities, equipment, and infrastructure are suggested based on the predictive results.

System‐level energy model for data transmission in wireless biomedical implantable systems

This paper develops simple system-level energy models for different kinds of transmitter implementations. Different communication protocols such as ASK, OOK, FSK, PSK are considered to evaluate the energy cost of both the architecture of the system as well as the electronic circuitry. These models are developed for the systems operating in the Medical Implant Communications Service frequency band. These models are useful for the optimisation of system and circuit parameters and provided some guidelines to choose the right modulation and circuit implementation for energy limited wireless transmitters.

Analysis of fluoroquinolones antibiotic residue in feed matrices using terahertz spectroscopy.

As antibiotic residue becomes more and more serious all over the world, a rapid and effective detection method is needed to evaluate the antibiotic residue in feed matrices to ensure food safety for consumers. In this study, three different kinds of fluoroquinolones (norfloxacin, enrofloxacin, and ofloxacin) in feed matrices were analyzed using terahertz (THz) spectroscopy, respectively. Meanwhile, pure fluoroquinolones and pure feed matrices were also measured in the same way. Then, the absorption spectra of all of the samples were extracted in the transmission mode. Pure norfloxacin has two absorption peaks at 0.825 and 1.187THz, and they could still be observed when mixing norfloxacin with feed matrices. Also, there was an obvious and strong absorption peak for ofloxacin at 1.044THz. However, no obvious absorption peak for enrofloxacin was observed, and only a weak absorption peak was located at 0.8THz. Then, the different models were established with different chemometrics to identify the fluoroquinolones in feed matrices and determined the fluoroquinolones content in the feed matrices. The least squares support vector machines, Naive Bayes, Mahalanobis distance, and back propagation neural network (BPNN) were used to build the identification model with a Savitzky-Golay filter and standardized normal variate pretreatments. The results show that the excellent classification model was acquired with the BPNN combined with no pretreatment. The optimal classification accuracy was 80.56% in the testing set. After that, multiple linear regression and stepwise regression were used to establish the quantitative detection model for different kinds of fluoroquinolones in feed matrices. The optimal correlation coefficients for norfloxacin, enrofloxacin, and ofloxacin in the prediction set were obtained with multiple linear regression that combined absorption peaks with wavelengths selected by stepwise regression, which were 0.867, 0.828, and 0.964, respectively. Overall, this research explored the potential of identifying the fluoroquinolones in feed matrices using THz spectroscopy without a complex pretreatment process and then quantitatively detecting the fluoroquinolones content in feed matrices. The results demonstrate that THz spectra could be used to identify fluoroquinolones in feed matrices and also detect their content quantitatively, which has great significance for the food safety industry.

Themes, Theories, and Models.

Although theory building is often described as the ultimate goal of qualitative research, an examination of articles in Qualitative Health Research ( QHR) shows that themes are actually the typical format for reporting results. In addition, articles that rely on themes often present low-level theories in the form of models that connect these themes. Because models have received less attention than either themes or theories, this article concentrates on summarizing four different kinds of models: hierarchies, timelines, processes, and cycles. In each of these cases, it presents both a general illustration of such a model and a realistic example from a published article in QHR. It concludes with a call for greater recognition of the role that models play in capturing the results of qualitative research.

1000 au exterior arcs connected to the protoplanetary disk around HL Tauri

The protoplanetary disk around HL Tau is so far the youngest candidate of planet formation, and it is still embedded in a protostellar envelope with a size of thousands of au. In this work, we study the gas kinematics in the envelope and its possible influence on the embedded disk. We present our new ALMA cycle 3 observational results of HL Tau in the 13CO (2-1) and C18O (2-1) emission at resolutions of 0.8" (110 au), and we compare the observed velocity pattern with models of different kinds of gas motions. Both the 13CO and C18O emission lines show a central compact component with a size of 2" (280 au), which traces the protoplanetary disk. The disk is clearly resolved and shows a Keplerian motion, from which the protostellar mass of HL Tau is estimated to be 1.8+/-0.3 M$_\odot$, assuming the inclination angle of the disk to be 47 deg from the plane of the sky. The 13CO emission shows two arc structures with sizes of 1000-2000 au and masses of 3E-3 M$_\odot$ connected to the central disk. One is blueshifted and stretches from the northeast to the northwest, and the other is redshifted and stretches from the southwest to the southeast. We find that simple kinematical models of infalling and (counter-)rotating flattened envelopes cannot fully explain the observed velocity patterns in the arc structures. The gas kinematics of the arc structures can be better explained with three-dimensional infalling or outflowing motions. Nevertheless, the observed velocity in the northwestern part of the blueshifted arc structure is ~60-70% higher than the expected free-fall velocity. We discuss two possible origins of the arc structures: (1) infalling flows externally compressed by an expanding shell driven by XZ Tau and (2) outflowing gas clumps caused by gravitational instabilities in the protoplanetary disk around HL Tau.

Point-particle explanations: the case of gravitational waves

This paper explores the role of physically impossible idealizations in model-based explanation. We do this by examining the explanation of gravitational waves from distant stellar objects using models that contain point-particle idealizations. Like infinite idealizations in thermodynamics, biology and economics, the point-particle idealization in general relativity is physically impossible. What makes this case interesting is that there are two very different kinds of models used for predicting the same gravitational wave phenomena, post-Newtonian models and effective field theory models. The paper contends that post-Newtonian models are explanatory while effective field theory models are not, because only in the former can we eliminate the physically impossible point-particle idealization. This suggests that, in some areas of science at least, models invoking ineliminable infinite idealizations cannot have explanatory power.

The Impact of Corporate Board Size on Firm Performance: Evidence from Ghana and Nigeria

This paper examines the impact of corporate board size on firm performance for a sample of 137 listed firms in Ghana and Nigeria. Our findings suggest a statistically significant and positive relationship between board size and firm performance, implying that in Ghana and Nigeria allowing corporate board size to be dependent of firm size tends to improve firm performance. Our findings are consistent across different kinds of models that deal with different types of endogeneities and corporate performance proxies. Our results provide empirical support for agency theory, which suggests that optimal corporate board size effectively advise, monitor and discipline management thereby improving firm performance.

Load Flow Analysis for AC/DC Distribution Systems with Distributed Generations

Hybrid AC/DC distribution systems are rapidly growing due to the recent developments in power electronic technologies and increasing deployment of DC output type distributed generations (DGs) in distribution voltage levels. The presence of DGs in DC distribution systems imposes new challenges in load flow calculations. In response, this paper is dealing with the load flow calculation problem in AC/DC distribution systems in the presence of different kinds of DGs. For this purpose, mathematical models of different kinds of DGs are presented, and then, the models are incorporated into the sensitivity matrix method for using in load flow calculations. Since the large number of load buses and the high R/X ratios in the AC part of the system can lead to the divergence of Jacobian matrix based methods, the suggested method is based on backward forward sweep (BFS) method. The proposed method is simulated on a test system equipped with different kinds of DGs and converters and the results are presented.

Study of Flexible Load Dispatch to Improve the Capacity of Wind Power Absorption

The dispatch method which track the trend of load demand by arranging the generation scheme of controllable hydro or thermal units faces great difficulties and challenges. With the increase of renewable energy sources such as wind power and photovoltaic power introduced to grid, system has to arrange much more spinning reserve units to compensate the unbalanced power. How to exploit the peak-shaving potential of flexible load which can be shifted with time or storage energy has become many scholars’ research direction. However, the modelling of different kinds of load and control strategy is considerably difficult, this paper choose the Air Conditioner with compressor which can storage energy in fact to study. The equivalent thermal parameters of Air Conditioner has been established. And with the use of “loop control” strategies, we can predict the regulated power of Air Conditioner. Then we established the Gen-Load optimal scheduling model including flexible load based on traditional optimal scheduling model. At last, an improved IEEE-30 case is used to verify. The result of simulation shows that flexible load can fast-track renewable power changes. More than that, with flexible load and reasonable incentive method to consumers, the operating cost of the system can be greatly cut down.

Assessing the predictability of different kinds of models in estimating impacts of climatic factors on food grain availability in India

The study explored the relationship of the climatic predictor variables such as seasonal temperature and rainfall pattern and non-climatic variable such as area under cultivation with the predictand per capita food grain production. We applied a linear method “Generalized Linear Model” and two non-linear methods “Multivariate Adaptive Regression Spline” and “Generalized Additive Model” to Indian data and assessed the data on basis of their performance in predicting food grain production. It was found that an adaptive version of generalized additive model has yielded the lowest predictive error in terms of lower root mean squared error. Better predictability of food grain production based on climatic factors may necessarily help to anticipate the nation’s food grain availability. The forecasts would facilitate scientists, farmers, policy makers, business organizations and the government to formulate appropriate adaptable strategies to cope with the climatic variability influence on food availability.

Analysis of bending and angular vibration of the crankshaft with a torsional vibrations damper

The paper presents the analysis of vibrations of the crankshaft system and proposition of its modelling. At the beginning there are general information about the torsional vibration dampers. Moreover, models of different kinds of dampers are shown with their governing equations. The next section presents proposition of the algorithm of modelling of the crank-piston mechanism with a torsional vibrations damper. Furthermore, there are equations of motion of the analyzed system in this chapter. After that, the results of numerical simulations and experiments are shown. Finally, the paper is summarized by giving conclusions about the analysis of crankshaft systems with a dynamic eliminator of vibrations and their modelling.

A survey of lifted inference approaches for probabilistic logic programming under the distribution semantics

Lifted inference aims at answering queries from statistical relational models by reasoning on populations of individuals as a whole instead of considering each individual singularly. Since the initial proposal by David Poole in 2003, many lifted inference techniques have appeared, by lifting different algorithms or using approximation involving different kinds of models, including parfactor graphs and Markov Logic Networks. Very recently lifted inference was applied to Probabilistic Logic Programming (PLP) under the distribution semantics, with proposals such as LP2 and Weighted First-Order Model Counting (WFOMC). Moreover, techniques for dealing with aggregation parfactors can be directly applied to PLP. In this paper we survey these approaches and present an experimental comparison on five models. The results show that WFOMC outperforms the other approaches, being able to exploit more symmetries.

Verification of Fowler–Nordheim electron tunneling mechanism in Ni/SiO2/n-4H SiC and n+ poly-Si/SiO2/n-4H SiC MOS devices by different models

This article emphasizes verification of Fowler–Nordheim electron tunneling mechanism in the Ni/SiO2/n-4H SiC MOS devices by developing three different kinds of models. The standard semiconductor equations are categorically solved to obtain the change in Fermi energy level of semiconductor with effect of temperature and field that extend support to determine sustainable and accurate tunneling current through the oxide layer. The forward and reverse bias currents with variation of electric field are simulated with help of different models developed by us for MOS devices by applying adequate conditions. The latter is quite different from former in terms of tunneling mechanism in the MOS devices. The variation of barrier height with effect of quantum mechanical, temperature, and fields is considered as effective barrier height for the generation of current–field (J–F) curves under forward and reverse biases but quantum mechanical effect is void in the latter. In addition, the J–F curves are also simulated with variation of carrier concentration in the n-type 4H SiC semiconductor of MOS devices and the relation between them is established.

Categorical approach to modelling and to coupling of models

Solution of any engineering problem starts with a modelling process, which typically involves a choice among different kinds of models. To create a realistic model, one has to think carefully about the modelling process. Particularly in the case of coupled problems when several models are coupled together to represent a given physical phenomenon. This paper presents an approach based on the category theory that allows to describe this modelling process on a more abstract level. Using the advantages of abstract level, one can describe the coupling process in a concise way and introduce certain criteria to check consistency of a coupled model. The main idea of the proposed approach is to introduce a structure in the modelling process, which allows to see how different models interact without a precise look into them. Copyright © 2016 John Wiley & Sons, Ltd.

Modelling the nucleon structure

We review the status of our understanding of nucleon structure based on the modelling of different kinds of parton distributions. We use the concept of generalized transverse momentum dependent parton distributions and Wigner distributions, which combine the features of transverse-momentum dependent parton distributions and generalized parton distributions. We revisit various quark models which account for different aspects of these parton distributions. We then identify applications of these distributions to gain a simple interpretation of key properties of the quark and gluon dynamics in the nucleon.