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In the recent years, metal-organic frameworks (MOFs) and their derived mixed metal hydroxides/oxides structures have emerged as an engrossing category of functional materials with some unique properties such as high porosity and high specific surface area for energy storage applications. Here, a cathodic electrodeposition strategy was utilized to prepare a bimetallic NiCo metal-organic framework (NiCo-MOF) with flower-like morphology consisting of nanopetals onto Ni foam (NF) as free-standing electrode. Structural characterization revealed that Ni2+ and Co2+ metal ions are uniformly distributed on the deposited films on the nickel foam. Post-chemical treatment of NiCo-MOF/Ni foam electrode under basic condition (i.e. 4 M KOH) was concluded carbon coated hierarchical mixed hydroxide (i.e. C@Ni1-xCox(OH)2) structures onto Ni-foam with similar morphology as its pristine binary MOF. Both ready-to-use fabricated electrodes were characterized with various techniques of X-ray diffraction (XRD), Fourier-transform infrared (FT-IR), Field-emission scanning electron microscope (FE-SEM), Energy dispersive X-ray analysis (EDAX), Energy dispersive spectroscopy (EDS) mapping and Thermogravimetric-differential scanning calorimetry (TG-DSC). Supercapacitive behaviors of pristine NiCo-MOF/NF and its derived C@NiCo-hydroxide/NF electrodes were also measured using cyclic voltammetry (CV), galvanostatic charge/discharge, and electrochemical impedance spectroscopy (EIS) measurements in 2 M KOH as electrolyte. The C@NiCo-hydroxide/NF electrode exhibited better performance as compared to pristine sacrificial binary metallic MOF electrode, which was 1825 F g–1 at a discharge current density of 1 A g–1 which still preserved 66.5% of its initial capacitance even at a high-rate load of 15 A g–1. Additionally, the C@NiCo-hydroxide/NF showed 87.6% of its capacitance at the end of 8000th cycle.

According to the classification of user requirements in Kano model, theory of technology evolution was adopted to determine the future evolution route of product and predict possible structure state for the future technolo- gy, in order to mine the user's potential requirements. In view of the fuzzy and uncertainty of users' potential requir- ements, the fuzzy semantic model was adopted to describe the qualitative user requirements in order to standardly form the user requirements concept sets with functional attributes in different requirement categories, so as to guide the designers to create the innovative solutions along the right direction and then achieve the product rapid innovatio- n design. Taking the Pulse-Jet bag filter as an example, the case analysis shows that this method can effectively be applied to obtain new product innovation concept solution, and provide theoretical support for the mapping between subsequent innovation concept solutions and innovation function solutions and innovation structure solutions, and also provide the model architecture for innovation droved new product digital prototype design.

Multi-label learning has received significant attention in the research community over the past few years. Traditional supervised learning techniques do not fit it well, as real-world objects might be complicated and have multiple semantic meanings simultaneously. In our work, we set our goals to mine the involved product attributes in comment data from JD.com. This task is fundamental and significant to businesses for studying the online market feedbacks from consumers. In this paper, we formally define the three types of text categorization problems and analyze the relations among them. Then, we assign some single-label multiclass classifiers to the new training datasets which are created by our constructing algorithms. Thus, multilabel learning is transformed into a series of single-label multi-class binary classification problems: whether an unseen instance belongs to a certain class or not. Finally, we assemble the outputs of all single-label multi-class classifiers to obtain the multiple labels. In the end of this paper, we conducted comprehensive experiments to evaluate the performance of our proposed algorithms.

In order to design the feed system of high speed Computer Numerical Control (CNC) lathe, the static and dynamic characteristics of feed system driven by linear motor in high speed CNC lathe were analyzed. The slide board was taking as the main moving part of the feed system, and the guide rail was the main support component of the linear motor feed system. The mechanical structure static stiffness of feed system is researched through the slide board statics analysis. The simulation results show that the maximum deformation of the slide board occurs in the middle of the slide board where the linear motor is placed. The linear motor feed system control model was established based on analysis of high-speed linear feed system control principle, and the linear motor feed system transfer function was established, and servo dynamic stiffness factors were analyzed. The control parameters of the servo system and actuating mechanism parameters of feed system on the effect of the linear motor servo dynamic stiffness were analyzed using MATLAB software. The simulation results show that the position loop proportional gain, speed loop proportional gain and speed loop integral response time are the biggest influence factors on servo dynamic stiffness. The displacement response is reduced under the cutting interference force step inputting, the servo dynamic stiffness is increased, the number of system oscillation is also reduced, and the system tends to be stable. DOI: http://dx.doi.org/10.11591/telkomnika.v11i7.2813 Full Text: PDF

Error model customization for different work type of complex CNC equipments is significant to identify and compensate the errors of CNC integrated manufacturing, and further to achieve process optimization and product quality control. Traditional error modeling method is complicated, takes long time and is difficult to change itself. A flexible customized error modeling method based on feature and multi-body system (MBS) theory is proposed. Firstly, feature space of machine tool and Denavit-Hartenberg(DH) homogeneous transformation matrix space are build separately. Secondly, feature mapping function is deduced. Thirdly, customization method of error model is described. Finally, flexible customization system for error modeling based on feature is developed. Using this system and method to execute error modeling for several typical machine tools of Shenyang Machine Tool Group. It takes about 1minute to get an accurate error model. It can analyze single error’s percentage of total error. These are basis of error compensation. The practices indicate the method is effective and feasible. The method provides a new thought for error control, optimization of integrated manufacturing process, digital manufacturing and automation technology.

In view of the characteristics of flexible inspection and the specific requirements of flexible inspection path planning, a new adaptive multi-object genetic algorithm (AMOGA) was proposed to provide quick and near-optimal solutions to large flexible inspection path planning problems. The encoding mechanism, crossover operator and mutation operator was designed in this algorithm according to the problem of the shortest path planning, meanwhile, the on-line adaptive adjustment strategy of crossover probability and mutation probability was used to compensate for the traditional algorithmpsilas limitations, which improved the search speed and search quality in genetic algorithm. Finally, we had experimented on the SSCK - U6035 5-axis CNC machine tools in Shenyang Machine Tool Co., LTD., and the inspection of Roller Bits Palm adopted AMOGA can get higher measurement accuracy. Moreover, the on-line inspection system was successfully developed based on OpenGL platform according to user needs, the effective inspection track was generated, the number of inspection points was obviously dropped compared with unplanning inspection. The experimental results demonstrated that this algorithm applied in the flexible inspection path planning was feasibility and reasonable, which can improve the measurement accuracy and inspection efficiency and provide a new thought for the largescale flexible inspection path planning.

In view of the characteristics of flexible inspection and its specific requirements, a new adaptive multi-object genetic algorithm (AMOGA) was proposed and successfully applied to the flexible inspection path planning. The encoding mechanism, crossover operator and mutation operator was designed in this algorithm according to the problem of the shortest path planning, meanwhile, the on-line adaptive adjustment strategy of crossover probability and mutation probability was used to compensate for the traditional algorithmpsilas limitations, which improved the search speed and search quality in genetic algorithm. Finally, we had experimented on the SSCK-U6035 5-axis CNC machine tools in Shenyang Machine Tool Co., LTD., and the inspection of Roller Bits Palm adopted AMOGA can get higher measurement accuracy. Moreover, the on-line inspection system was developed based on OpenGL platform according to user needs, the effective inspection track was generated and the number of inspection points was obviously dropped, which can improve the inspection efficiency.

Intelligent tutoring system (ITS) is a new educational methodology. It includes the integration of education technology and advanced technology in multidisciplinary field. In this paper, we focused on the intelligent knowledge tutor mode which is based on the theory of ontology, an architecture of integrated intelligent tutoring system (IITS) is proposed, its ontology model is established, and its application characteristics is analyzed. Research shows that multi-level isomeric knowledge integration processing can be excluded the factors generated internal interfere and conflicts from the bottom of system, large isomeric information could be better shared and reused, which solved the problem of processing the personify and visualization with IITS knowledge; the redundancy feedback control based on the ontology model can achieve self-learning, self-regulating and self-maintenance of the knowledge for settling the distributed adaptive of the IITS knowledge processing.