The Magnetic Properties of the Spin-1 Ising System with?the?Effect of the Transverse Crystal Field

Within the framework of the effective-field theory with a probability distribution technique which accounts for the self-spin correlations, we study the magnetic properties of the spin-1 Ising system with the transverse crystal field and the applied external magnetic field. The influence of the transverse crystal field on the phase diagrams, hysteresis loops and susceptibility is discussed in detail.     

Optical properties and energy transfer among Nd in Nd:Ca2Al2SiO7 crystals for diode pumped lasers

The energy levels of neodymium in the Nd³⁺:Ca₂Al₂SiO₇ (CAS) laser material with gehlenite structure are reported. As the Nd³⁺:Ca₂Al₂SiO₇ compound presents a broad absorption around 806 nm, it is a good candidate for diode pumped laser. The ⁴F_3/2→⁴I_9/2 and ⁴F_3/2→⁴I11/2 emission have been recorded and the fluorescence branching ratios calculated from the Judd-Ofelt analysis are 0.41 and 0.47 respectively. The emission cross section at 1.06 μm (⁴F_3/2→⁴I11/2 transition) is 5 × 10^-20 cm². The decay profiles of the Nd³⁺ emission have been analyzed for several Nd³⁺ concentrations using the kinetic microparameters related to the cross relaxation ( and R₀≈6 Å) and the energy migration probabilities ( ). In the Nd:CAS laser material, the optimal concentration corresponding to the maximum of the fluorescence intensity is determined to be around 2.7 × 10²⁰ Nd³⁺ ions cm^-3. The Nd³⁺-Nd³⁺ interactions are not very strong in this material as the optical concentration value is two times higher than in the Nd:YAG laser material.     

Multi-operator based evolutionary algorithms for solving constrained optimization problems

Over the last two decades, many sophisticated evolutionary algorithms have been introduced for solving constrained optimization problems. Due to the variability of characteristics in different COPs, no single algorithm performs consistently over a range of problems. In this paper, for a better coverage of the problem characteristics, we introduce an algorithm framework that uses multiple search operators in each generation. The appropriate mix of the search operators, for any given problem, is determined adaptively. The framework is tested by implementing two different algorithms. The performance of the algorithms is judged by solving 60 test instances taken from two constrained optimization benchmark sets from specialized literature. The first algorithm, which is a multi-operator based genetic algorithm (GA), shows a significant improvement over different versions of GA (each with a single one of these operators). The second algorithm, using differential evolution (DE), also confirms the benefit of the multi-operator algorithm by providing better and consistent solutions. The overall results demonstrated that both GA and DE based algorithms show competitive, if not better, performance as compared to the state of the art algorithms.     

用LELA轻松管理家庭网络

现在组建无线局域网、享受无线上网的家庭越来越多,但不论新用户还是老玩家都对无线局域网的管理颇为头疼。例如想了解当前无线局域网中连接了哪些设备。有没有别人偷偷“蹭”网？在不同品牌的无线路由器上,查询连接状态的方式各不相同,有的甚至不提供这项功能。查询网络连接状态都这么麻烦,其它网络管理功能就更不用说了,难道大家就只能对网络放任不管了吗？     

Fuzzy unit commitment solution—A novel twofold simulated annealing approach

The authors propose a twofold simulated annealing (twofold-SA) method for the optimization of fuzzy unit commitment formulation in this paper. In the proposed method, simulated annealing (SA) and fuzzy logic are combined to obtain SA acceptance probabilities from fuzzy membership degrees. Fuzzy load is calculated from error statistics and an initial solution is generated by a priority list method. The initial solution is decomposed into hourly-schedules and each hourly-schedule is modified by decomposed-SA using a bit flipping operator. Fuzzy membership degrees are the selection attributes of the decomposed-SA. A new solution consists of these hourly-schedules of entire scheduling period after repair, as unit-wise constraints may not be fulfilled at the time of an individual hourly-schedule modification. This helps to detect and modify promising schedules of appropriate hours. In coupling-SA, this new solution is accepted for the next iteration if its cost is less than that of current solution. However, a higher cost new solution is accepted with the temperature dependent total cost membership function. Computation time of the proposed method is also improved by the imprecise tolerance of the fuzzy model. Besides, excess units with the system dependent probability distribution help to handle constraints efficiently and imprecise economic load dispatch (ELD) calculations are modified to save the execution time. The proposed method is tested using standard reported data sets. Numerical results show an improvement in solution cost and time compared to the results obtained from other existing methods.     

Synthesis,characterisation and potential biomedical applications of magnetic core–shell structures: carbon‐, dextran‐, SiO2 ‐ and ZnO‐coated Fe3 O4 nanoparticles

Due to the strong effect of nanoparticles'' size and surface properties on cellular uptake and bio‐distribution, the selection of coating material for magnetic core–shell nanoparticles (CSNPs) is very important. In this study, the effects of four different biocompatible coating materials on the physical properties of Fe₃ O₄ (magnetite) nanoparticles (NPs) for different biomedical applications are investigated and compared. In this regard, magnetite NPs are prepared by a simple co‐precipitation method. Then, CSNPs including Fe₃ O₄ as a core and carbon, dextran, ZnO (zincite) and SiO₂ (silica) as different shells are synthesised using simple one‐ or two‐step methods. A comprehensive study is carried out on the prepared samples using X‐ray diffraction, vibrating sample magnetometry, transmission electron microscopy and Fourier transform infrared spectroscopy analyses. According to the authors'' findings, it is suggested that carbon‐ and dextran‐coated magnetite NPs with high M _s have great potential in the application of magnetic resonance imaging contrast agents. Moreover, silica‐coated magnetite NPs with high coercivity are potentially suitable candidates for hyperthermia and ZnO‐coated Fe₃ O₄ is potentially suitable for photothermal therapy.Inspec keywords: iron compounds, carbon, silicon compounds, zinc compounds, nanomedicine, biomedical materials, nanofabrication, nanoparticles, magnetic particles, coatings, X‐ray diffraction, magnetometry, transmission electron microscopy, Fourier transform spectra, infrared spectra, biomedical MRI, hyperthermia, radiation therapyOther keywords: biomedical applications, magnetic core‐shell nanoparticles, CSNP, cellular uptake, biodistribution, coating material, biocompatible coating materials, co‐precipitation, dextran, zincite, silica, X‐ray diffraction, vibrating sample magnetometry, transmission electron microscopy, Fourier transform infrared spectroscopy, magnetic resonance imaging contrast agents, hyperthermia, photothermal therapy, SiO₂ ‐Fe₃ O₄ , ZnO‐Fe₃ O₄      

Multi-layer neural network algorithm for vehicle-to-everything communication in 5G networks

Internet of Vehicles (IoVs), the emerging trend of Internet of Things (IoTs), has undoubtedly become a promising trend to improve communication among vehicles on the roads. Vehicle-to-everything (V2X) communication that is based on 5G technology enables vehicle users to communicate and collaborate with each other to enhance road traffic efficiency and safety. Owing to the increased traffic load and restricted resources of existing network substructure, a channel that responds to the latency and reliability needs of V2X communication must be designed. Thereby, several intelligent spectrum allocation techniques have been proposed to improve the system's overall effectiveness. In this paper, we discuss the spectrum sharing issue of V2X communication in Device-to-Device (D2D)-based cellular networks. We propose a new multi-layer neural network (MLNN)-based Resource Allocation and sharing approach (MNNRA) for D2D-based V2X communications. According to the main advantages of MLNN, the proposed algorithm takes several profits by improving system performance while reducing computational complexity. Numerical analysis is presented to approve the effectiveness of our proposed solution in terms of network sum rate, packet reception ratio, resource utilization ratio, and time complexity.     

An ideal-seeking fuzzy data envelopment analysis framework

Data envelopment analysis (DEA) is a widely used mathematical programming approach for evaluating the relative efficiency of decision making units (DMUs) in organizations. Crisp input and output data are fundamentally indispensable in traditional DEA evaluation process. However, the input and output data in real-world problems are often imprecise or ambiguous. In this study, we present a four-phase fuzzy DEA framework based on the theory of displaced ideal. Two hypothetical DMUs called the ideal and nadir DMUs are constructed and used as reference points to evaluate a set of information technology (IT) investment strategies based on their Euclidean distance from these reference points. The best relative efficiency of the fuzzy ideal DMU and the worst relative efficiency of the fuzzy nadir DMU are determined and combined to rank the DMUs. A numerical example is presented to demonstrate the applicability of the proposed framework and exhibit the efficacy of the procedures and algorithms.     

Handling disruptions in manufacturing systems: An immune perspective

One of the major issues in the monitoring and control of manufacturing systems is to determine how to effectively deal with unexpected disruptions (e.g. material unavailability, resource failures, unavailability of operators, rush orders, etc.). Existing approaches and tools offer few concepts that are specific enough and sufficiently generic to help in handling a broad variety of such unexpected events. The biological immune system potentially offers interesting features to face the threats (bacteria, viruses, cancers, etc.) that may harm an organism. This research aims to investigate this potential for the monitoring and control of manufacturing systems at the occurrence of disruptions. Based on analogies that we point out, we suggest a framework to help with the design of software tools that are more able to assist decision makers in dealing with various types of disruptions occurring in a manufacturing system. A first prototype implementation, developed using a multi agent approach, contributes to show the feasibility and the interest of this immune based framework.