Distributed ledger technology in supply chains: a transaction cost perspective

With the emergence of distributed ledger technology (DLT), numerous practitioners and researchers have proclaimed its beneficial impact on supply chain transactions in the future. However, the vast majority of DLT initiatives are discontinued after a short period. With the full potential of DLT laying far down the road, especially managers in supply chain management (SCM) seek for short-term cost-saving effects of DLT in order to achieve long-term benefits of DLT in the future. However, the extant research has bypassed grounding long-term as well as short-term effects of DLT on supply chain transaction with empirical data. We address this shortcoming, following an abductive research approach and combining empirical data from a multiple case study design with the corresponding literature. Our study reveals that the effects of DLT on supply chain transactions are two-sided. We found six effects of DLT solutions that have a cost-reducing or cost avoidance impact on supply chain transactions. In addition, we found two effects that change the power distribution between buyers and suppliers in transactions and a single effect that reduces the dependency of supply chain transactions on third parties. While cost-reducing and avoidance as well as dependency-reducing effects are positive effects, the change in power distribution might come with disadvantages. With these findings, the paper provides the first empirical evidence of the impact of DLT on supply chain transactions, which will enable managers to improve their assessment of DLT usage in supply chains.     

Two‐sided matching framework for optimal user association in 5G multi‐RAT UDNs

Recently, academic and industrial research communities are paying more explicit attention to the 5G multiple radio access technology ultra‐dense networks (5G multi‐RAT UDNs) for boosting network capacity, especially in UD urban zones. To this aim, in this paper, we intend to tackle the user association problem in 5G multi‐RAT UDNs. By considering the decoupled uplink/downlink access (DUDA), we divide our user association problem into two distinct subproblems representing, respectively, the uplink and the downlink channels. Next, we formulated each one as a nonlinear optimization problem with binary variables. Then, to solve them, we were restricted by the hard complexity, as well as the hard feasibility of centralized user association schemes. Thus, to resolve our user association problem in a reasonable time and distributed manner, we formulated each subproblem as a many‐to‐one matching game based on matching theory. Next, we provide two fully distributed association algorithms to compute the uplink and downlink stable matching among user equipments (UEs) and base stations (BSs). Simulation results corroborate our theoretical model and show the effectiveness and improvement of our achieved results in terms of the overall network performance, quality of service (QoS), and energy efficiency (EE) of UEs.     

Hybrid fully convolutional networks-based skin lesion segmentation and melanoma detection using deep feature

Fully convolutional networks (FCNs) take the input of arbitrary size and produce correspondingly sized output with efficient inference and learning. The automatic diagnosis of melanoma is very essential for reducing the mortality rate by identifying the disease in earlier stages. A two-stage framework is used for implementing the melanoma detection, segmentation of skin lesion, and identification of melanoma lesions. Two FCNs based on VGG-16 and GoogLeNet are incorporated for improving the segmentation accuracy. A hybrid framework is used for incorporating these two FCNs. The classification is done by extracting the feature from segmented lesion by using deep residual network and a hand-crafted feature. Classification is done by support vector machine. The performance analysis of our framework gives a promising accuracy, that is, 0.8892 for classification in ISBI 2016 dataset and 0.853 for ISIC 2017 dataset.     

综掘工作面智能化开采技术的实践

针对煤矿开采深度的增加引起的采掘和衔接问题,山西长平煤业公司通过技术引进,设计了基于信息自动化的智能化开采技术,为实现该矿安全高效生产奠定了基础。     

全自动集装箱码头装卸系统质量管理

全自动集装箱码头装卸系统集成了当今世界各项先进技术,在研发、制造、调试过程中,都要坚持质量第一、安全第一的原则,确保各项技术参数可靠,设备运行稳定。在总结国内几个全自动码头装卸系统的质量管理方法与经验的基础上,结合自动化码头自身特点,给出全自动集装箱码头装卸系统主要质量管理方法,进一步丰富发展自动化码头装卸系统建造过程中的“不欠债离岸”质量管理理念。     

综采工作面粉尘防治问题分析与技术改进

针对新桥煤矿2301综采工作面机载喷雾系统喷雾效果差、喷雾耗水量大造成煤质含水量超标、喷嘴雾化程度不高、喷嘴容易发生堵塞等问题,提出了高压喷雾系统设计方案,选择了1.2mm的锥形引射喷嘴和1.5mm的扇形引射喷嘴。采用固定水泵供水方式,结合工作面实际情况,计算出喷雾总用水量247.5L/min,提高了喷雾射程,提升了除尘效果。     

Distributed Kalman filter for linear system with complex multi-channel stochastic uncertain parameter and decoupled local filters

This article considers a distributed Kalman filtering problem for linear system contaminated by complex multi-channel random uncertain parameter in which a number of nodes cooperative without central coordination to estimate a common state based on local measurements and data received from neighbors. We propose an approach to eliminate this error propagation. The proposed local filters are guaranteed to be stable under some mild conditions on certain global structural data, and their fusion yields the centralized Kalman estimate. Then, we extend this method to smoothing and deconvolution algorithm. Finally, simulation experiments demonstrate the validity of the proposed approach.     

煤矿智能化开采关键技术分析

煤矿智能化开采是中国煤炭工业技术发展的必经之路,是煤矿企业进一步发展的主要目标。通过阐述智能化的概念,介绍了煤矿智能化开采的定义和系统构成,分析了煤矿智能化开采的关键技术,包括工作面综采装备位姿监测技术、围岩-装备耦合自适应控制技术、综采装备核心智能控制技术和矿井机器人技术。针对各关键技术问题进行分析,提出相应的解决方案和核心装备智能化控制逻辑。通过解决煤矿智能化开采过程中的关键技术问题,加快煤矿企业智能化改革,确保企业稳定、可持续发展。     

Scheduling distributed flowshops with flexible assembly and set-up time to minimise makespan

The scheduling problems under distributed production or flexible assembly settings have achieved increasing attention in recent years. This paper considers scheduling the integration of these two environments and proposes an original distributed flowshop scheduling problem with flexible assembly and set-up time. Distributed production stage is deployed several homogeneous flowshop factories that process the jobs to be assembled into final products in the flexible assembly stage. The objective is to find a schedule, including a production subschedule for jobs and an assembly subschedule for products, to minimise the makespan. Such a scheduling problem involves four successive decisions: assigning jobs to production factories, sequencing jobs at every factory, designating an assembly machine for each product and sequencing products on each assembly machine. The computational model is first established, and then a constructive heuristic (TPHS) and two hybrid metaheuristics (HVNS and HPSO) are proposed. Numerical experiments have been carried out and results validate the algorithmic feasibility and effectiveness. TPHS can obtain reasonable solutions in a shorter time, while metaheuristics can report better solutions using more yet acceptable time. HPSO is statistically comparable yet less robust compared with HVNS for small-scale instances. For the large-scale case, HPSO outperforms HVNS on both effectiveness and robustness.     

SAM智能综采技术在龙滩煤矿的应用

介绍了四川省首个智能综采设备在龙滩煤矿3124S工作面的应用情况,总结了SAM智能化综采的六大核心技术,包括成套设备一键启停、液压支架自动跟机、采煤机记忆割煤、机巷远程集中控制、工作环境智能监控、工况监测及故障诊断。通过现场应用,一键启停功能成功率超过90%、自动跟机率平均88%、记忆割煤使用率62%,实现了工作面设备集中控制、回采参数实时监控及故障诊断。结果表明,相较于传统综采工作面,智能化综采工作面生产人员减少50%,工效提高63%,单产提高65%。