Level Prediction Method Research Articles

Structures, stabilities and electronic properties of boron-doped silicon clusters B3Sin (n=1–17) and their anions

The structures, stabilities and electronic properties of neutral and anionic B3Sin (n = 1–17) clusters have been systemically investigated on the basis of density functional theory at the B3LYP/6-311 + G(d) level and CALYPSO structure prediction method. The structural searches show that three boron atoms tend to form B3 triangle encapsulated into Sin cages with the increasing number of silicon atoms. Most of the lowest energy structures can be derived by using the squashed pentagonal bipyramid structure of B3Si4 and B3Si4− as the major building unit. The relative stabilities are studied based on the calculated binding energies, second-order difference of energies and HOMO–LUMO gaps of the lowest energy structures. In addition, Hirshfeld, natural population analysis, Bader approaches and natural electronic configuration are performed to explore the charge transfer. At last, molecular orbital, magnetic properties, IR, Raman and UV–vis spectra are also, respectively, analysed for providing strong support for essential theoretical and experimental research.

Proteome-wide prediction and annotation of mitochondrial and sub-mitochondrial proteins by incorporating domain information

Mitochondrion is one of the most important subcellular organelle of eukaryotic cells. It carries out several biochemical functions that are extremely vital for cells. Defects in mitochondria also play an important role in the development and progression of different types of cancer. Therefore knowledge of complete mitochondrial protein repertoire is essential to understand overall mitochondrial functionality, maintenance, dynamics and metabolism. It would be of a great practical significance to develop an automated and reliable approach that can identify the mitochondrial proteins and their sub-mitochondrial location. In the present study, we report a two level prediction method, named as SubMitoPred, which predicts mitochondrial proteins (at first level) and their sub-mitochondrial localization (at second level). Our approach is based on combined usage of Pfam domain information and support vector machine model. During training we achieved an overall prediction accuracy of 94.37% at first level while at the second level a prediction accuracy of 74.91% for inner membrane, 82.98% for outer membrane, 71.23% for inter-membrane space and 81.58% accuracy was achieved for matrix. Evaluation on independent data shows better performance of SubMitoPred. Benchmarking showed that SubMitoPred performed better than other existing methods. We also annotated human proteome using SubMitoPred. We also developed a freely accessible web-server as well as standalone software for the use of scientific community, which is available at http://proteininformatics.org/mkumar/submitopred/.

Development of Prediction Method for Engine Compartment Water Level by Using Coupled Multibody and Fluid Dynamics

Development of Prediction Method for Engine Compartment Water Level by Using Coupled Multibody and Fluid Dynamics

Development of a Water Surface Level Prediction Method Affected by River Mouth Sandbar Collapse

The purpose of this study is to apply a non-linear filtering methods (Particle Filter) to a flood prediction system to improve the accuracy of flood water level. The uniqueness of the flood prediction system is to estimates the water level considering temporal change of the sandbar collapse at the backwater reach in the Kumano River. A one dimensional hydrodynamic model of unsteady flow was applied to predict the longitudinal profile of the water level at the reach affected by the sandbar collapse of the river mouth. It was shown that the bed deformation height as one of the state quantities could explain the timing of the sandbar collapse. Other state quantities are discharge at the upstream and the lateral discharge from the branches. These were given from the results of a distributed rainfall-runoff model. Error coefficients are included to update the state quantities by using filtering method with the observed water level. The water level at the objective river of the study was predicted by using the updated initial condition after the filtering, which showed a good agreement with observed water level. It is concluded that the precision of the flood prediction system combined the water surface level prediction model are improved more than before.

Fault level prediction for distribution network using fuzzy logic identifier

With the increasing penetration of the renewable power energy sources, the potential fault current of the distribution power systems changes more frequently as the connection structure of the distribution power system varies from time to time. Traditionally, the fault level can be estimated through short circuit analysis which is time consuming and sometimes difficult as it needs to know the parameters of the transmission line and transformers as well as the structure of the power system. In this paper, an online-used fault level prediction method is proposed via monitoring the phasor value of the local positive-sequence voltage and current. The ratio of the voltage change and current change are used to distinguish the natural deviation of the load from the switching operations or disturbances on the grid side. Several continuous changes of the voltage and current caused by load fluctuations are recorded and used to parameterize the equivalent circuit of the power system and to estimate the fault current level. A fuzzy logic identifier is used for adaptively selecting and recording the satisfactory changes by defining an index of confidence level. The implementation of the proposed scheme is demonstrated in a relay after introducing a low-voltage blocking function. A typical distribution power system with renewable generators is established in PSCAD/EMTDC and is used to verify the effectiveness and accuracy of the proposed method under various load changing conditions.

The Research of Supersonic Aircraft Low Sonic Boom Configuration Design and Optimizations

High noise level of sonic boom is one of the most important reasons that the supersonic transport can’t be applied to civil aviation broadly. Sonic boom is a complicated problem relating to aircraft configuration design, aerodynamics, acoustics and so on. The traditional sonic boom minimization theory is an inverse design method with single object, which makes it difficult to be applied in multi-objective optimization, effectively. For the low sonic boom configuration optimization, the sonic boom noise level prediction method based on supersonic linear theory was developed. The sonic boom level of a basic configuration of supersonic business jet was computed and the cause of formation of sonic boom was analyzed, based on which the fuse and wing plane wais optimized to decrease the noise level of sonic boom. Compared with the basic configuration, the sonic boom level of optimized configuration decreased distinctively, with the overpressure decreasing 41% and the A-weighted noise level decreasing 7.55 decibel. The aerodynamic characteristics of optimized configuration were computed. Compared with the basic configuration, the drag decreased obviously at the cruise condition without moment change.

In silico platform for predicting and initiating β-turns in a protein at desired locations.

Numerous studies have been performed for analysis and prediction of β-turns in a protein. This study focuses on analyzing, predicting, and designing of β-turns to understand the preference of amino acids in β-turn formation. We analyzed around 20,000 PDB chains to understand the preference of residues or pair of residues at different positions in β-turns. Based on the results, a propensity-based method has been developed for predicting β-turns with an accuracy of 82%. We introduced a new approach entitled "Turn level prediction method," which predicts the complete β-turn rather than focusing on the residues in a β-turn. Finally, we developed BetaTPred3, a Random forest based method for predicting β-turns by utilizing various features of four residues present in β-turns. The BetaTPred3 achieved an accuracy of 79% with 0.51 MCC that is comparable or better than existing methods on BT426 dataset. Additionally, models were developed to predict β-turn types with better performance than other methods available in the literature. In order to improve the quality of prediction of turns, we developed prediction models on a large and latest dataset of 6376 nonredundant protein chains. Based on this study, a web server has been developed for prediction of β-turns and their types in proteins. This web server also predicts minimum number of mutations required to initiate or break a β-turn in a protein at specified location of a protein.

A Noise Level Prediction Method Based on Electro-Mechanical Frequency Response Function for Capacitors

The capacitors in high-voltage direct-current (HVDC) converter stations radiate a lot of audible noise which can reach higher than 100 dB. The existing noise level prediction methods are not satisfying enough. In this paper, a new noise level prediction method is proposed based on a frequency response function considering both electrical and mechanical characteristics of capacitors. The electro-mechanical frequency response function (EMFRF) is defined as the frequency domain quotient of the vibration response and the squared capacitor voltage, and it is obtained from impulse current experiment. Under given excitations, the vibration response of the capacitor tank is the product of EMFRF and the square of the given capacitor voltage in frequency domain, and the radiated audible noise is calculated by structure acoustic coupling formulas. The noise level under the same excitations is also measured in laboratory, and the results are compared with the prediction. The comparison proves that the noise prediction method is effective.

Prediction of Interstitial Glucose Level

Glucose is an important source of energy for cells. In clinical practice, we measure glucose level in blood and interstitial fluid. Each method has its pros and cons, and both levels correlate with each other. As the body tries to maintain the glucose level within a particular range to avoid adverse effects, it is desirable to predict future glucose levels in order to aid provided health care. We can see this desire in research, e.g., research on glucose transporters of cells. As yet another example, we can see it with diabetic patients, patients in a metabolic intensive care unit, particularly. In this paper, a glucose level prediction method is proposed.

Prediction method for the operation level of agricultural mechanization in Heilongjiang Province.

Prediction method for the operation level of agricultural mechanization in Heilongjiang Province.

RPW: A hybrid reverse prediction method for level of detail

In this paper, we propose a way of using multiple domain analysis methodology to speed up the image rendering process. We first apply wavelet transform to the original image, and then compress the wavelets in the frequency domain using histogram equalization techniques. When rendering the image, we uncompress the wavelets and reverse predict the upper level images. This process continues until it reaches a certain criteria. We use two terms—total image size (TIS) and total loading time (TLT) to measure the performance of level of detail (LOD) in a network environment. We compare traditional image-based LOD methods with the new method we are proposing. Experiments show that the proposed method can reduce both TIS and TLT. The image rendering speed on a remote client is approximately 2.5 times faster than the common image compression methods. Applications such as remote diagnostic systems and online museums can use this technique to achieve better real-time animation effects.

Economic feasibility analysis of roadway capacity expansion with accounting traffic noise barrier cost

Transportation externalities like air pollution, noise and others are acost or a benefit that arises from an economic transaction and that falls on people who do not participate in the transaction (Perkin, 2000). Among those externalities, noise has become such a pervasive factor in our life recently. Conventional economic feasibility analysis, however, does not account the costs of such externalities. The purpose of this paper is to address the issue of the economic feasibility analysis with accounting such externalities, focusing on traffic noise area. Based on TNM model cost along with conventional construction, right-of-way, and maintenance costs, a revised benefit/cost (B/C) analysis will be conducted for a hypothetical city called U-TOWN. By incorporating the noise cost, represented by the noise barrier cost, the revised B/C indicator can be obtained along with range of cost share by the addition of the noise barrier and the range of B/Cs thereof. This paper, more specifically, proposes the framework of how to incorporate noise element into the existing B/C analysis. It also includes the usage of TNM, noise level prediction method, and how to obtain the optimal design of noise barrier within TNM. If successfully conducted, the analysis framework set forth here in this paper can be further explored and the results may shed light on a new and better framework combining transportation and environmental modeling to better address the environmental aspects of transportation.

A Reactor Water Level and Pressure Prediction Method Under Small Loss-of-Coolant-Accident Conditions in Boiling Water Reactors

An on-line method of predicting reactor water level and pressure under small loss-of-coolant-accident (LOCA) conditions has been proposed. The method features initialization of a simplified reactor model in transient conditions. This is done by using plant data in time series and estimating unknown parameters, such as break area, by a nonlinear optimization method. Off-line simulations were performed for small LOCAs (break area: ∼100 cm2) using the results of a reference LOCA analysis code for plant data. These showed that the difference from the reference calculation during a 10-min period was within 10%, normalized by the value at the initialization time, and the estimation error for break area was below 11%. The overall CPU time required for the prediction was below 10 s in a general purpose computer of 10 million instructions per second.

Research on a noise control device. 3rd report The fundamental design (2) of the device.

The structural design method of the noise control device was described in the 2nd report and it is possible to design the structure of the device by this method. But it is necessary to design how to set the device to the noise source when it is applied. That is, the appropriate set position to the noise source is required in order to obtain more noise reduction effect. Therefore, the design method for setting the device was considered through some model experiments in the anechoic room and the field, and the sound pressure level prediction method for the device with a barrier was obtained. These results are described in this paper.

Noise of a model helicopter rotor due to ingestion of isotropic turbulence

A theoretical and experimental investigation of the noise of a model helicopter rotor due to the ingestion of grid-generated, isotropic turbulence is described. Simulated forward flight and vertical ascent tests were performed with a 0·76 m diameter, articulated model rotor in the United Technologies Research Center Acoustic Research Tunnel. Far field noise spectra and directivity were measured in addition to inflow turbulence intensities, length scales and spectra. Measured inflow turbulence statistics and rotor operating parameters were employed in a theoretical procedure to predict turbulence ingestion noise spectra and directivity. This theoretical formulation represented an absolute level prediction method in that empirical or adjustable constants were not employed. From this study it is concluded that incident turbulence represents a potentially important source of rotor narrowband random (quasi-tonal) and broadband noise. With due regard to the absolute level nature of the prediction method, agreement between theory and experiment is reasonable: quasi-tonal noise at low frequency tends to be overpredicted whereas mid-frequency tonal noise and high frequency broadband noise are well predicted. This theory, therefore, provides a means to predict the contribution of turbulence ingestion noise to overall rotor noise spectra and directivity in cases where reasonable estimates of incident turbulence statistics can be made. Ingestion of main rotor wake turbulence by tail rotors in flight and ingestion of atmospheric turbulence by main and tail rotors in hover would be expected to be the most important sources of turbulence ingestion noise in full scale applications.