205 research outputs found
Self-Paced Multi-Task Learning
In this paper, we propose a novel multi-task learning (MTL) framework, called
Self-Paced Multi-Task Learning (SPMTL). Different from previous works treating
all tasks and instances equally when training, SPMTL attempts to jointly learn
the tasks by taking into consideration the complexities of both tasks and
instances. This is inspired by the cognitive process of human brain that often
learns from the easy to the hard. We construct a compact SPMTL formulation by
proposing a new task-oriented regularizer that can jointly prioritize the tasks
and the instances. Thus it can be interpreted as a self-paced learner for MTL.
A simple yet effective algorithm is designed for optimizing the proposed
objective function. An error bound for a simplified formulation is also
analyzed theoretically. Experimental results on toy and real-world datasets
demonstrate the effectiveness of the proposed approach, compared to the
state-of-the-art methods
The relationship among customer demand, competitive strategy and manufacturing system functional objectives
Purpose: To ascertain the relationship between the operation system function goal decision making and customer demand and competition strategy, can better discover and integrate all available resources (including important capital resources) to achieve business opportunities, the establishment of sustainable competitive ability. Because, to achieve business development lead policymakers take great uncertainty, which led to the investment behavior required for the operational activities of resources also bear the enormous risks.
Design/methodology/approach: Through principal component analysis on the data collected by questionnaires, the manuscript obtains dominant factors for customer demand, competitive strategy and manufacturing system functional objectives respectively. By these factors, it tests its three hypotheses with the data from northeast of China and draws some conclusions.
Findings: The results show that customer demand have a significant positive effect on competitive strategy; competitive strategy have positive influence on manufacturing system functional objectives; customer demand affect the functional objectives, by competitive strategy.
Research limitations/implications: In this research, competitive strategy and manufacturing system functional objectives are influenced by customer demand. The conclusion of the research can provide theoretical guidance for Chinese enterprises which carry out manufacturing system functional objectives.
Originality/value: In this research, a new measure questionnaire of competition strategy, customer satisfaction and operating system function goal was used, analyzed the influence factors of time, quality, cost, efficiency, service and environment, on the operation of the system. The study shows that the effect of competition strategy and customer demand has a direct impact on the operating system functions, customer demand through competitive strategy of indirect effects operating system functions.Peer Reviewe
An Evaluation Method of Comprehensive Product Quality for Customer Satisfaction Based on Intuitionistic Fuzzy Number
How to maximize customer satisfaction is an important research topic in the service quality evaluation. This paper proposes an evaluation method of comprehensive product quality for customer satisfaction based on the intuitionistic fuzzy number. In this method, we design a questionnaire and investigate the customer’s language evaluation information of product quality evaluation, including product expectations and product perception at first. And then, the product quality evaluation model is obtained by Delphi method; that is, the first-level evaluation indexes and the second-level evaluation indexes are obtained and the weight vector of each evaluation index is determined. Next, language evaluation information translates into corresponding fuzzy numbers using intuitionistic fuzzy numbers. Therefore, the results of the product quality evaluation of the production system are obtained using the weighted mean method. Finally, an example is used to illustrate the feasibility and effectiveness of the proposed method
Progress of the satellite laser ranging system TROS1000
AbstractThe mobile satellite laser ranging system TROS1000, successfully developed in 2010, achieves a high repetition rate and enables daytime laser ranging. Its measurement range has reached up to 36000Â km with an accuracy as precise as 1Â cm. Using recent observations in Wuhan, Jiufeng, Xianning, and Rongcheng, Shandong, we introduce the progress made using this mobile observation system
Effect of customer demand and competitive strategy on decision-making of manufacturing system functional objectives
Low-Rate Smartphone Videoscopy for Microsecond Luminescence Lifetime Imaging with Machine Learning
Time-resolved techniques have been widely used in time-gated and luminescence
lifetime imaging. However, traditional time-resolved systems require expensive
lab equipment such as high-speed excitation sources and detectors or
complicated mechanical choppers to achieve high repetition rates. Here, we
present a cost-effective and miniaturized smartphone lifetime imaging system
integrated with a pulsed UV LED for 2D luminescence lifetime imaging using a
videoscopy-based virtual chopper (V-chopper) mechanism combined with machine
learning. The V-chopper method generates a series of time-delayed images
between excitation pulses and smartphone gating so that the luminescence
lifetime can be measured at each pixel using a relatively low acquisition frame
rate (e.g., 30 fps) without the need for excitation synchronization. Europium
(Eu) complex dyes with different luminescent lifetimes ranging from
microseconds to seconds were used to demonstrate and evaluate the principle of
V-chopper on a 3D-printed smartphone microscopy platform. A convolutional
neural network (CNN) model was developed to automatically distinguish the gated
images in different decay cycles with an accuracy of >99.5%. The current
smartphone V-chopper system can detect lifetime down to ~75 microseconds
utilizing the default phase shift between the smartphone video rate and
excitation pulses and in principle can detect much shorter lifetimes by
accurately programming the time delay. This V-chopper methodology has
eliminated the need for the expensive and complicated instruments used in
traditional time-resolved detection and can greatly expand the applications of
time-resolved lifetime technologies
A service-oriented energy assessment system based on BPMN and machine learning
Increasing energy cost and environmental problems push forward research on energy saving and emission reduction strategy in the manufacturing industry. Energy assessment of machining, as the basis for energy saving and emission reduction, plays an irreplaceable role in engineering service and maintenance for manufacturing enterprises. Due to the complex energy nature and relationships between machine tools, machining parts, and machining processes, there is still a lack of practical energy evaluation methods and tools for manufacturing enterprises. To fill this gap, a serviced-oriented energy assessment system is designed and developed to assist managers in clarifying the energy consumption of machining in this paper. Firstly, the operational requirements of the serviced-oriented energy assessment system are analyzed from the perspective of enterprises. Then, based on the establishment of system architecture, three key technologies, namely data integration, process integration, and energy evaluation, are studied in this paper. In this section, the energy characteristics of machine tools and the energy relationships are studied through the working states of machine tools, machining features of parts and process activities of processes, and the relational database, BPMN 2.0 specification, and machine learning approach are employed to implement the above function respectively. Finally, a case study of machine tool center stand base machining in a manufacturing enterprise was applied to verify the effectiveness and practicality of the proposed approach and system
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