Effects of Annealing Temperature on Microstructure and Tensile Properties in Ferritic Lightweight Steels

An investigation was conducted into the effects of annealing temperature on microstructure and tensile properties of ferritic lightweight steels. Two steels were fabricated by varying the C content, and were annealed at 573 K to 1173 K (300 °C to 900 °C) for 1 hour. According to the microstructural analysis results, κ-carbides were formed at about 973 K (700 °C), which was confirmed by equilibrium phase diagrams calculated from a THERMO-CALC program. In the steel containing low carbon content, needle-shaped κ-carbides were homogeneously dispersed in the ferrite matrix, whereas bulky band-shaped martensites were distributed in the steel containing high carbon content. In the 973 K (700 °C)-annealed specimen of the steel containing high carbon content, deformation bands were formed throughout the specimen, while fine carbides were sufficiently deformed inside the deformation bands, thereby resulting in the greatest level of strength and ductility. These results indicated that the appropriate annealing treatment of steel containing high carbon content was useful for the improvement of both strength and ductility over steel containing low carbon content.     

Generalized mean for feature extraction in one-class classification problems

Biased discriminant analysis (BDA), which extracts discriminative features for one-class classification problems, is sensitive to outliers in negative samples. This study focuses on the drawback of BDA attributed to the objective function based on the arithmetic mean in one-class classification problems, and proposes an objective function based on a generalized mean. A novel method is also presented to effectively maximize the objective function. The experimental results show that the proposed method provides better discriminative features than the BDA and its variants.     

Persistent UAV Service: An Improved Scheduling Formulation and Prototypes of System Components

The flight duration of unmanned aerial vehicles (UAVs) is limited by their battery or fuel capacity. As a consequence, the duration of missions that can be pursued by UAVs without supporting logistics is restricted. However, a system of UAVs that is supported by automated logistics structures, such as fuel service stations and orchestration algorithms, may pursue missions of conceivably indefinite duration. This may be accomplished by handing off the mission tasks to fully fueled replacement UAVs when the current fleet grows weary. The drained UAVs then seek replenishment from nearby logistics support facilities. To support the vision of a persistent fleet of UAVs pursuing missions across a field of operations, we develop an improved mixed integer linear programming (MILP) model that can serve to support the system’s efforts to orchestrate the operations of numerous UAVs, missions and logistics facilities. Further, we look toward the future implementation of such a persistent fleet outdoors and develop prototype components required for such a system. In particular, we develop and demonstrate the concerted operation of a scheduling model, UAV onboard vision-based guidance system and replenishment stations.     

What Are the Causes of Noncompliance Behaviors in Bar Code Medication Administration System Processes?

Healthcare information systems (e.g., Bar Code Medication Administration [BCMA] system) have been adopted to deliver efficient healthcare services recently. However, though it is seemingly simple to use (scanning barcodes before medication), users of the BCMA system (e.g., nurses and pharmacists) often show noncompliance behaviors. Therefore, the goal of this study is to comprehensively understand why such noncompliance behaviors occur with BCMA system. Through comprehensive literature review, 128 instances of causes were identified, which were categorized into five categories: Poor Visual and Audio Interface, Poor Physical Ergonomic Design, Poor Information Integrity, Abnormal Situation for System Use, and User Reluctance and Negligence. The results show that successful use of a BCMA system requires supportive systems and environments, so it is more like an issue of the system rather than that of an individual user or a device. It is believed that the proposed categories could be applicable in investigating noncompliance behaviors in other healthcare information systems as well.     

Torsional stiffness requirements for diaphragm bracing of discretely braced I-girders

I-section girders are laterally interconnected by Torsional bracings that are discretely installed to increase resistance to lateral-torsional buckling. However, there are confusing discrepancies in the current design specifications for the stiffness of diaphragm-type bracings. The mathematical formula for determining the required torsional stiffness is still unclear. In this study, rigorous examinations were carried out to clarify the effects of the web distortional stiffness and the number of diaphragm bracings. To achieve the purpose of this study, the theoretical derivation of the stiffness equations was thoroughly examined. Three-dimensional finite-element analysis was used for the parametric numerical analyses of a series of feasible two-girder system models, and enhanced equations are proposed for achieving sufficient stiffness in the torsional bracings. The practical validity of the proposed equations are verified by statistical correlation analyses, which clearly prove their superiority compared to current design guidelines.     

Modified analogue forecasting in the hidden Markov frameworkfor meteorological droughts

An analogue method(AM) is a nonparametric approach that has been applied to predict the future states of a dynamic system by following the evolution of the analogues in the historical archive. In this study, we proposed a hidden Markov model(HMM)framework for a modified analogue forecasting(MAF) approach for meteorological droughts in Korea. The unobservable(hidden) state process in the framework aims to model the underlying drought state, while the observation process was formed from the time series of the standardized precipitation index(SPI) as a drought index. Within the framework, the likelihood estimator was used as the measure of similarity between past SPI analogues and current data. The MAF approach was conducted on the selected analogues to make forecasts at lead times of one and three months. The proposed model was applied to five selected stations in Korea using the SPI data from 1973 to 2016. The forecasting performance of the proposed model was tested during the validation period(2003–2016) using several statistical criteria and it was compared to a persistence-based benchmark model. The results showed significant improvement in the forecasting capacity, and satisfactory performance for numerical SPI forecasting and categorical drought forecasting. The results also suggested that the proposed model was able to provide useful information for determining future drought categories for early drought warning with a lead time of up to three months.     

Physicochemical properties of nanopowdered eggshell

This study was carried out to investigate the physicochemical properties of nanopowdered eggshell (NPES). These characteristics were determined based on the particle size, particle morphology, zeta potential, moisture sorption behaviour, purity and crystallinity. Homogeneous, aggregated and spherical crystals of NPES particles were observed through scanning electron microscope and transmission electron microscope. The average particle sizes of NPES and powdered eggshell (PES) were 202.3 ± 28.9 nm and 113.89 ± 79.37 μm, respectively. Zeta potentials of NPES (?15.41 mV) suggested an incipient instability of the colloidal system. Moisture sorption analysis indicated a higher water adsorption capacity of NPES than that of PES. X‐ray diffractometer (XRD) analysis confirmed the presence of calcite in both NPES and PES. The chemical compositions of the NPES and PES particles were strongly associated with the presence of calcium carbonate, as determined by the Fourier transform infrared (FTIR) spectra. Therefore, eggshell nanopowder has a great potential to be utilised as a component for biomedical applications.     

Multistage PRIM: patient rule induction method for optimisation of a multistage manufacturing process

Industries such as automotive, LCD, PDP, semiconductor and steel produce products through multistage manufacturing processes. In a multistage manufacturing process, performances of stages are not independent. Therefore, the relationship between stages should be considered when optimising the multistage manufacturing process. This study proposes a new procedure of optimising a multistage manufacturing process, called multistage PRIM (patient rule induction method). Multistage PRIM extends the scope of process optimisation from a single stage to the multistage process, and it can use the information encapsulated in the relationship between stages when maximising each stage's performance. A case study in a multistage steel manufacturing process is conducted to illustrate the proposed procedure.     

Situation dependent decision selector for production control in testing and rework cell

This paper presents a production control approach for the testing and rework cell in a dynamic and stochastic computer integrated manufacturing (CIM) system. The proposed situation dependent decision selector (SDDS) observes the status of the system and jobs at every decision point, and makes its three different decisions on dispatching, pre-emption, and dispatching within pre-emption in real time. This paper also develops a new feature selection algorithm for the SDDS. Experimental results show that the SDDS is better than other static control rules and another dynamic control approach with respect to the number of tardy jobs.     

Genetic algorithm-based hysteresis modeling and identification of rotary SMA actuators

This paper describes a new, modified generalized Preisach model for actuators that have severe dead-zone hysteresis, which is mainly observed in rotary SMA actuators. Along with the Preisach model, a new approach of hysteresis modeling and parameter identification using genetic algorithm was proposed. This modeling method achieved significant improvements in both accuracy and computation time. The proposed approach is general; therefore, it can be applied to identify any type of hysteresis. To demonstrate the efficiency of the proposed model, experimental results on hysteresis identification of Rotary SMA Actuator and performance of inverse hysteresis openloop controller are provided and compared.