Using Computational Intelligence Algorithms to Solve the Coalition Structure Generation Problem in Coalitional Skill Games

Coalitional skill games (CSGs) are a simple model of cooperation in an uncertain environment where each agent has a set of skills that are required to accomplish a variety of tasks and each task requires a set of skills to be completed, but each skill is very hard to be quantified and can only be qualitatively expressed. Thus far, many computational questions surrounding CSGs have been studied. However, to the best of our knowledge, the coalition structure generation problem (CSGP), as a central issue of CSGs, is extremely challenging and has not been well solved. To this end, two different computational intelligence algorithms are herein evaluated: binary particle swarm optimization (BPSO) and binary differential evolution (BDE). In particular, we develop the two stochastic search algorithms with two-dimensional binary encoding and corresponding heuristic for individual repairs. After that, we discuss some fundamental properties of the proposed heuristic. Finally, we compare the improved BPSO and BDE with the state-of-the-art algorithms for solving CSGP in CSGs. The experimental results show that our algorithms can find the same near optimal solutions with the existing approaches but take extremely short time, especially under the large problem size.     

Performance of LiNi1/3Co1/3Mn1/3O2 prepared from spent lithium-ion batteries by a carbonate co-precipitation method

Spherical LiNi_1/3Co_1/3Mn_1/3O₂ cathode particles were resynthesized by a carbonate co-precipitation method using spent lithium-ion batteries (LIBs) as a raw material. The physical characteristics of the Ni_1/3Co_1/3Mn_1/3CO₃ precursor, the (Ni_1/3Co_1/3Mn_1/3)₃O₄ intermediate, and the regenerated LiNi_1/3Co_1/3Mn_1/3O₂ cathode material were investigated by laser particle-size analysis, scanning electron microscopy–energy-dispersive spectroscopy (SEM-EDS), thermogravimetry–differential scanning calorimetry (TG-DSC), X-ray diffraction (XRD), inductively coupled plasma–atomic emission spectroscopy (ICP-AES), and X-ray photoelectron spectroscopy (XPS). The electrochemical performance of the regenerated LiNi_1/3Co_1/3Mn_1/3O₂ was studied by continuous charge–discharge cycling and cyclic voltammetry. The results indicate that the regenerated Ni_1/3Co_1/3Mn_1/3CO₃ precursor comprises uniform spherical particles with a narrow particle-size distribution. The regenerated LiNi_1/3Co_1/3Mn_1/3O₂ comprises spherical particles similar to those of the Ni_1/3Co_1/3Mn_1/3CO₃ precursor, but with a narrower particle-size distribution. Moreover, it has a well-ordered layered structure and a low degree of cation mixing. The regenerated LiNi_1/3Co_1/3Mn_1/3O₂ shows an initial discharge capacity of 163.5 mA h g^?1 at 0.1 C, between 2.7 and 4.3 V; the discharge capacity at 1 C is 135.1 mA h g^?1, and the capacity retention ratio is 94.1% after 50 cycles. Even at the high rate of 5 C, LiNi_1/3Co_1/3Mn_1/3O₂ delivers the high capacity of 112.6 mA h g^?1. These results demonstrate that the electrochemical performance of the regenerated LiNi_1/3Co_1/3Mn_1/3O₂ is comparable to that of a cathode synthesized from fresh materials by carbonate co-precipitation.     

高氯酸·四氨·双(5-硝基四唑)合钴(Ⅲ)分子和晶体结构与性能的理论研究

运用密度泛函理论(DFT)分别对高氯酸·四氨·双(5-硝基四唑)合钴(Ⅲ)(BNCP)分子和晶体进行了理论计算.首先选取4种常见密度泛函方法对BNCP气相分子进行优化,结果表明TPSS(Tao,Perdew,Staroverov,Scuseria)方法最适合此体系.随后运用Materials Studio中DMOL3模...     

Microfiber SMPU film affords quicker shape recovery than the bulk one

Comparing to the bulk SMPU (shape memory polyurethane) film, microfiber SMPU film afforded much quicker and sharper shape recovery when heated in water bath. The shape recovery of the microfiber film only took ~ 1/4 time of that needed for the bulk film from R_r (shape recovery ratio) = 10% to R_r = 90%. The final R_r and R_f (shape fix ratio) of the microfiber film was also enhanced. The microfiber film was fabricated by electrospinning with the fiber diameter of 200 nm to 1 μm. DSC and DMA results indicate that the formation of microfiber has very limited effect on the T_trans (switching temperature) of the SMPU. The quick shape recovery of the microfiber SMPU film is considered due to the higher surface area of microfiber film that is favorable for quicker heating/cooling of the sample and quicker diffusion of water. This study offers a possible way to improve the shape recovery speed without changing the chemical composition, which may meet special needs for sensors or actuators of biomedical devices and others.     

一步水热法制备超长VO_2(B)纳米带及其电化学性能（英文）

采用简易的一步水热法制备了超长的VO2(B)纳米带。对纳米带的结构、形貌、最优合成条件及电化学性能进行了研究。结果发现:制得的VO2(B)纳米带长度约为几十微米,宽度为~200 nm;且最优合成条件为在钒源与还原剂摩尔比为2:1的条件下,200℃水热反应24 h。当该VO2(B)纳米带被作为锂离子电池的阳极材料时,显示出了优异的电化学性能,尤其是循环稳定性,循环500周后的电容量损失率仅为10.41%,极大的解决了钒类纳米材料作为锂离子电池阳极材料时稳定性差的问题,提高了其成为锂离子电池阳极材料的可能性。     

Path Selection in Disaster Response Management Based on Q-learning

Suitable rescue path selection is very important to rescue lives and reduce the loss of disasters,and has been a key issue in the field of disaster response management.In this paper,we present a path selection algorithm based on Q-learning for disaster response applications.We assume that a rescue team is an agent,which is operating in a dynamic and dangerous environment and needs to find a safe and short path in the least time.We first propose a path selection model for disaster response management,and deduce that path selection based on our model is a Markov decision process.Then,we introduce Q-learning and design strategies for action selection and to avoid cyclic path.Finally,experimental results show that our algorithm can find a safe and short path in the dynamic and dangerous environment,which can provide a specific and significant reference for practical management in disaster response applications.     

Pruning least objective contribution in KMSE

Although kernel minimum squared error (KMSE) is computationally simple, i.e., it only needs solving a linear equation set, it suffers from the drawback that in the testing phase the computational efficiency decreases seriously as the training samples increase. The underlying reason is that the solution of Naïve KMSE is represented by all the training samples in the feature space. Hence, in this paper, a method of selecting significant nodes for KMSE is proposed. During each calculation round, the presented algorithm prunes the training sample making least contribution to the objective function, hence called as PLOC-KMSE. To accelerate the training procedure, a batch of so-called nonsignificant nodes is pruned instead of one by one in PLOC-KMSE, and this speedup algorithm is named MPLOC-KMSE for short. To show the efficacy and feasibility of the proposed PLOC-KMSE and MPLOC-KMSE, the experiments on benchmark data sets and real-world instances are reported. The experimental results demonstrate that PLOC-KMSE and MPLOC-KMSE require the fewest significant nodes compared with other algorithms. That is to say, their computational efficiency in the testing phase is best, thus suitable for environments having a strict demand of computational efficiency. In addition, from the performed experiments, it is easily known that the proposed MPLOC-KMSE accelerates the training procedure without sacrificing the computational efficiency of testing phase to reach the almost same generalization performance. Finally, although PLOC and MPLOC are proposed in regression domain, they can be easily extended to classification problem and other algorithms such as kernel ridge regression.     

Boiling characteristics of carbon nanotube suspensions under sub-atmospheric pressures

An experimental study was performed to understand the pool boiling heat transfer of deionized water-based carbon nanotube (CNT) suspensions on a flat copper surface under atmospheric and sub-atmospheric pressures. Experimental results indicate that the addition of CNT in the base liquid can apparently enhance both the heat transfer coefficient (HTC) and the critical heat flux (CHF). The pressure has great impacts on both the HTC and the CHF enhancement of CNT suspensions and the both increase significantly with the decrease of the pressure. The CNT mass concentration of CNT suspensions also has strong influences on both the HTC and the CHF of CNT suspensions and there exists an optimal CNT mass concentration corresponding to the maximum heat transfer enhancement. Besides, the effects of the surface characteristics of the heated surface on both the HTC and the CHF of CNT suspensions were also investigated.