Three Core Controversies of Original Conceptual Metaphor Theory Revisited

This article first introduces the main hypotheses of the original version of Conceptual Metaphor Theory (henceforth, abbreviated as CMT) presented in Metaphors We Live By. On this basis, it then evaluates its three controversial assumptions, referring to the research results of other influential CMT scholars. The three assumptions are: (1) metaphorical languages are possible because there exist metaphorical concepts which we can verify by their corresponding metaphorical expressions (language-concept-language circular reasoning); (2) conventional metaphors underlying literal expressions are the metaphors we live by and the object of CMT study while novel metaphors underlying figurative expressions are not the metaphors we live by since they lack systematic corresponding expressions (definition and scope of conceptual metaphors); (3) we understand the abstract target domain via the concrete source domain (unidirectional cross-domain mappings). In order to settle these tree controversies, future metaphor researchers should endeavor to find supporting evidences from multimodal manifestations, different languages and cultures and psychological experiments.

Online Meaning Construction of Chinese Net Words From Japanese: On the Basis of Conceptual Blending Theory

From the perspective of Conceptual Blending Theory, this paper tries to analyze the online meaning construction of Chinese net words from Japanese by showing the powerful explanation of the three kinds network of blending—single-scope network, double-scope network and multiple network. When understanding Chinese net words from Japanese, Chinese netizens tend to use their existing knowledge, resulting in different interpreting from Japanese net words. Subject to social and cultural factors, deviations of meaning construction come into being in the context of Chinese and Japanese. This paper may facilitate Chinese-Japanese exchange and strengthen Chinese people’s understanding of Chinese language and culture at the same time

Modeling and Analysis of Scheduling Problems Containing Renewable Energy Decisions

With globally increasing energy demands, world citizens are facing one of society\u27s most critical issues: protecting the environment. To reduce the emission of greenhouse gases (GHG), which are by-products of conventional energy resources, people are reducing the consumption of oil, gas, and coal collectively. In the meanwhile, interest in renewable energy resources has grown in recent years. Renewable generators can be installed both on the power grid side and end-use customer side of power systems. Energy management in power systems with multiple microgrids containing renewable energy resources has been a focus of industry and researchers as of late. Further, on-site renewable energy provides great opportunities for manufacturing plants to reduce energy costs when faced with time-varying electricity prices. To efficiently utilize on-site renewable energy generation, production schedules and energy supply decisions need to be coordinated. As renewable energy resources like solar and wind energy typically fluctuate with weather variations, the inherent stochastic nature of renewable energy resources makes the decision making of utilizing renewable generation complex. In this dissertation, we study a power system with one main grid (arbiter) and multiple microgrids (agents). The microgrids (MGs) are equipped to control their local generation and demand in the presence of uncertain renewable generation and heterogeneous energy management settings. We propose an extension to the classical two-stage stochastic programming model to capture these interactions by modeling the arbiter\u27s problem as the first-stage master problem and the agent decision problems as second-stage subproblems. To tackle this problem formulation, we propose a sequential sampling-based optimization algorithm that does not require a priori knowledge of probability distribution functions or selection of samples for renewable generation. The subproblems capture the details of different energy management settings employed at the agent MGs to control heating, ventilation and air conditioning systems; home appliances; industrial production; plug-in electrical vehicles; and storage devices. Computational experiments conducted on the US western interconnect (WECC-240) data set illustrate that the proposed algorithm is scalable and our solutions are statistically verifiable. Our results also show that the proposed framework can be used as a systematic tool to gauge (a) the impact of energy management settings in efficiently utilizing renewable generation and (b) the role of flexible demands in reducing system costs. Next, we present a two-stage, multi-objective stochastic program for flow shops with sequence-dependent setups in order to meet production schedules while managing energy costs. The first stage provides optimal schedules to minimize the total completion time, while the second stage makes energy supply decisions to minimize energy costs under a time-of-use electricity pricing scheme. Power demand for production is met by on-site renewable generation, supply from the main grid, and an energy storage system. An ε-constraint algorithm integrated with an L-shaped method is proposed to analyze the problem. Sets of Pareto optimal solutions are provided for decision-makers and our results show that the energy cost of setup operations is relatively high such that it cannot be ignored. Further, using solar or wind energy can save significant energy costs with solar energy being the more viable option of the two for reducing costs. Finally, we extend the flow shop scheduling problem to a job shop environment under hour-ahead real-time electricity pricing schemes. The objectives of interest are to minimize total weighted completion time and energy costs simultaneously. Besides renewable generation, hour-ahead real-time electricity pricing is another source of uncertainty in this study as electricity prices are released to customers only hours in advance of consumption. A mathematical model is presented and an ε-constraint algorithm is used to tackle the bi-objective problem. Further, to improve computational efficiency and generate solutions in a practically acceptable amount of time, a hybrid multi-objective evolutionary algorithm based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is developed. Five methods are developed to calculate chromosome fitness values. Computational tests show that both mathematical modeling and our proposed algorithm are comparable, while our algorithm produces solutions much quicker. Using a single method (rather than five) to generate schedules can further reduce computational time without significantly degrading solution quality

Integrated Batching and Lot Streaming with Variable Sublots and Sequence-Dependent Setups in a Two-Stage Hybrid Flow Shop

Consider a paint manufacturing firm whose customers typically place orders for two or more products simultaneously: liquid primer, top coat paint, and/or undercoat paint. Each product belongs to an associated product family that can be batched together during the manufacturing process. Meanwhile, each product can be split into several sublots so that overlapping production is possible in a two-stage hybrid flow shop. Various numbers of identical capacitated machines operate in parallel at each stage. We present a mixed-integer programming (MIP) to analyze this novel integrated batching and lot streaming problem with variable sublots, incompatible job families, and sequence-dependent setup times. The model determines the number of sublots for each product, the size of each sublot, and the production sequencing for each sublot such that the sum of weighted completion time is minimized. Several numerical example problems are presented to validate the proposed formulation and to compare results with similar problems in the literature. Furthermore, an experimental design based on real industrial data is used to evaluate the performance of proposed model. Results indicate that the computational cost of solving the model is high

Research on Features of Chatroom Netspeak From a Stylistic View

With the development and popularization of Internet, the appearance of computer mediated communication (CMC) has generated a new variety of language—netspeak, which received a wide publicity in modern linguistics. This paper focuses on the features of netspeak. Firstly, it gives an introduction of its background. Secondly, it discusses its features by employing a lot of examples from English and Chinese. In this part, this paper makes the analysis from the view of stylistics, focusing on phonological, lexical, syntactical and discoursal aspects. Special mention is given here to some differences and similarities found in English netspeak and Chinese netspeak. Thirdly, the great influence of netspeak on written language is involved, which reflects in morphology, meaning, grammar and the degree of politeness. Finally, a conclusion of the features of netspeak is given as well as a reasonable anticipation of its tendency. Lacking in the knowledge of the stylistic features of netspeak, chitchat on line will result in failure in communication. Therefore, this paper, through the systematic analysis on netspeak, aims at revealing its distinctive features and getting netizens to communicate better. As the cyber culture is evolving, netspeak is also changing, which will generate more new features. The study on netspeak needs further analysis and it is never ended