BacHbpred: support vector machine methods for the prediction of bacterial hemoglobin-like proteins

The recent upsurge in microbial genome data has revealed that hemoglobin-like (HbL) proteins may be widely distributed among bacteria and that some organisms may carry more than one HbL encoding gene. However, the discovery of HbL proteins has been limited to a small number of bacteria only. This study describes the prediction of HbL proteins and their domain classification using a machine learning approach. Support vector machine (SVM) models were developed for predicting HbL proteins based upon amino acid composition (AC), dipeptide composition (DC), hybrid method (AC + DC), and position specific scoring matrix (PSSM). In addition, we introduce for the first time a new prediction method based on max to min amino acid residue (MM) profiles. The average accuracy, standard deviation (SD), false positive rate (FPR), confusion matrix, and receiver operating characteristic (ROC) were analyzed. We also compared the performance of our proposed models in homology detection databases. The performance of the different approaches was estimated using fivefold cross-validation techniques. Prediction accuracy was further investigated through confusion matrix and ROC curve analysis. All experimental results indicate that the proposed BacHbpred can be a perspective predictor for determination of HbL related proteins. BacHbpred, a web tool, has been developed for HbL prediction.

Power demand and energy usage of container crane - comparison between AC and DC drives

The electrical data of two quay cranes, one has a DC drive system and the other has an AC drive system, in actual working conditions at a container terminal are measured and presented in this paper. Peak demand, energy usage, power factor and power quality are examined and compared.

Robust adaptive backstepping controller design for DC-DC buck converters with external disturbances

In modern power electronic systems, DC-DC converter is one of the main controlled power sources for driving DC systems. But the inherent nonlinear and time-varying characteristics often result in some difficulties mostly related to the control issue. This paper presents a robust nonlinear adaptive controller design with a recursive methodology based on the pulse width modulation (PWM) to drive a DC-DC buck converter. The proposed controller is designed based on the dynamical model of the buck converter where all parameters within the model are assumed as unknown. These unknown parameters are estimated through the adaptation laws and the stability of these laws are ensured by formulating suitable control Lyapunov functions (CLFs) at different stages. The proposed control scheme also provides robustness against external disturbances as these disturbances are considered within the model. One of the main features of the proposed scheme is that it overcomes the over-parameterization problems of unknown parameters which usually appear in some conventional adaptive methods. Finally, the effectiveness of the proposed control scheme is verified through the simulation results and compared to that of an existing adaptive backstepping controller. Simulation results clearly indicate the performance improvement in terms of a faster output voltage tracking response.

Rationale for the use of DC microgrids: feasibility, efficiency and protection analysis

Electrical power systems are undergoing highly significant changes in their structures. The emergence of renewable energy units in the power generation sector, the use of high-voltage DC in the power transmission sector, and the prevalence of islanded or integrated microgrids in the distribution sector are the strongest evidence supporting this claim. These changes are mostly the consequences of the increasing energy demand rate, climate change, and environmental challenges, as well as the high investment and maintenance cost of the previous structures. Considering these new conditions and according to the recent development in DC/DC conversion topologies and control techniques, different studies have been conducted on how and why DC microgrids outperform AC microgrids. This study discusses the feasibility of the DC microgrid system according to recent developments in power systems. The efficiency and power loss reduction in DC distribution systems are then analyzed, some of the common strategies and devices for protection systems in such networks are reviewed, and the possible and existing challenges in developing the DC microgrids are highlighted. The mathematical calculations and theories for this evaluation are presented to determine the reliable justification for selecting the appropriate microgrid systems.

Modelling and simulation of regeneration in AC traction propulsion system of electrified railway

This paper presents a robust model and its simulation to investigate the performance of an AC propulsion system in a rail vehicle for directly returning the regenerative braking power to the feeder substation of an AC traction network. This direct returning method can be an efficient approach for energy recovery if the regenerative braking is reliably applied. However, it is shown that this method can cause undesired voltage fluctuations if the regenerative braking regime or braking location of the rail vehicle change. The load torque on the traction motor (TM) is precisely modelled when pure electrical braking is applied. Different states of the direct torque controlled inverter are modelled when the TM regenerates. A circuit model for the utility grid, load impedances and the traction network is developed to evaluate the network receptivity against the regenerated power. The dynamics of the electromagnetic torque and the fluctuations of the DC-link voltage are investigated for two operational conditions: changes on the regenerative braking regime and changes on the rail vehicle braking location. The results justify how the DC-link voltage dramatically fluctuates with variations of the rail vehicle's operation conditions, whereas the electromagnetic torque is maintained on optimum rates.