Research on Design Method of the Full Form Ship with Minimum Thrust Deduction Factor

In the preliminary design stage of the full form ships, in order to obtain a hull form with low resistance and maximum propulsion efficiency, an optimization design program for a full form ship with the minimum thrust deduction factor has been developed, which combined the potential flow theory and boundary layer theory with the optimization technique. In the optimization process, the Sequential Unconstrained Minimization Technique（SUMT） interior point method of Nonlinear Programming（NLP） was proposed with the minimum thrust deduction factor as the objective function. An appropriate displacement is a basic constraint condition, and the boundary layer separation is an additional one. The parameters of the hull form modification function are used as design variables. At last, the numerical optimization example for lines of after-body of 50000 DWT product oil tanker was provided, which indicated that the propulsion efficiency was improved distinctly by this optimal design method.

DEDUCTION OF CONSTRAINT CONDITIONS IN THE CALIBRATION OF STEREO-VISION SYSTEN

In the test-field calibration,multi-azimuth stereo image pairs areproduced of the outdoor large control-field by the stereo-vision system under cali-bration.While in the analytical processing,the relationship between image pairsis adopted as a constraint condition,which ensures the stability and quality of thecalibration results.This paper introduces the deduction process of the constraintconditions.

A genetic algorithm for dynamic parameters reverse deduction of integrated anchorage system

In the analysis of the system of anchoring bar and wall rock in small strain and longitudinal vibration dynamic response, the influence of the cement grouting as well as the rock layer on the anchor bar can be evaluated as the two kinds of parameters: the dynamic stiffness and the damp, which are the vital reference of the anchorage quality. Based on the analytic solution to the dynamic equation of the integrated anchor bar, the new approach which combines genetic algorithm and the toolbox of Matlab is applied to solve the problem of multi-parameters reverse deduction for integrated anchorage system in dynamic testing. Using the traits of the self-organizing, self-adapting and the fast convergence speed of the genetic algorithm, the optimum of all possible solutions to dynamic parameters is obtained by calculating the project instances. Examples show that the method presented in this paper is effective and reliable.

Deduction Theorem and Hypothetical Syllogism Rule on Fuzzy Logic System

Cancelled the first axiom L1) or the third axiom L3) of the classical formal logic system we established two kinds of quasi-formal deductive system, LG-R^* and LG^* respectively. In LG-R^* we proved that neither the deduction theorem nor the hypothetical syllogism (HS) rule held but a deduction theorem and an HS rule are obtained in a weak sense. We also proved that both the deduction theorem and the hypothetical syllogism(HS) rule hold in LG^*.

Implementing Semantic Deduction of Propositional Knowledge in an Extension Multi-layer Perceptron

The paper presents an extension multi-laye r p erceptron model that is capable of representing and reasoning propositional know ledge base. An extended version of propositional calculus is developed, and its some properties is discussed. Formulas of the extended calculus can be expressed in the extension multi-layer perceptron. Naturally, semantic deduction of prop ositional knowledge base can be implement by the extension multi-layer perceptr on, and by learning, an unknown formula set can be found.

Tool Wear Optimization for General CNC Turning Using Fuzzy Deduction

Tool wear is frequently considered in the modern CNC (computer numerical control) turning industry. Most existing optimization researches for CNC finish turning were either accomplished within certain manufacturing circumstances, or achieved through numerous equipment operations. Therefore, a general deduction optimization scheme proposed is deemed to be necessary for the industry. In this paper, four parameters (cutting depth, feed rate, speed, tool nose runoff) with three levels (low, medium, high) are considered to optimize the tool wear for finish turning based on orthogonal array. Additionally, nine fuzzy control rules using triangle membership function with respective to five linguistic grades for tool wear are constructed. Considering four input and twenty output intervals, the defuzzification using center of gravity is then completed and introduced as the S/N (signal-to-noise) ratio. Thus, the optimum general deduction parameters can then be received. The confirmation experiment for optimum general deduction parameters is furthermore performed on an ECOCA-3807 CNC lathe. It is shown that the tool wear ratio from the fuzzy deduction optimization parameters is significantly advanced comparing to those from benchmark. This paper not only proposes a general deduction optimization scheme using orthogonal array, but also contributes the satisfactory fuzzy linguistic approach to tool wear in CNC turning with profound insight.

A theoretical deduction for the location of neutral axis in intestine at unloaded configuration

The function of Gastrointestinal tract including intestine is to a large degree mechanical.The mechanical properties of the intestinal wall,and the tonic (sustained) and/or phasic(short-

Emotion Deduction from Social Media Text Data Using Machine Learning Algorithm

Emotion represents the feeling of an individual in a given situation. There are various ways to express the emotions of an individual. It can be categorized into verbal expressions, written expressions, facial expressions and gestures. Among these various ways of expressing the emotion, the written method is a challenging task to extract the emotions, as the data is in the form of textual dat. Finding the different kinds of emotions is also a tedious task as it requires a lot of pre preparations of the textual data taken for the research. This research work is carried out to analyse and extract the emotions hidden in text data. The text data taken for the analysis is from the social media dataset. Using the raw text data directly from the social media will not serve the purpose. Therefore, the text data has to be pre-processed and then utilised for further processing. Pre-processing makes the text data more efficient and would infer valuable insights of the emotions hidden in it. The preprocessing steps also help to manage the text data for identifying the emotions conveyed in the text. This work proposes to deduct the emotions taken from the social media text data by applying the machine learning algorithm. Finally, the usefulness of the emotions is suggested for various stake holders, to find the attitude of individuals at that moment, the data is produced. .

Artificial intelligence driving perception,cognition,decision‐making and deduction in energy systems:State‐of‐the‐art and potential directions

In the context of energy systems,managing the complex interplay between diverse power sources and dynamic demands is crucial.With a focus on smart grid technology,continuously innovating artificial intelligence(AI)algorithms,such as deep learning,reinforcement learning,and large language model technologies,have been or have the potential to be leveraged to predict energy consumption patterns,enhance grid operation,and manage distributed energy resources efficiently.These capabilities are essential to meet the requirements of perception,cognition,decision‐making,and deduction in en-ergy systems.Nevertheless,there are some critical challenges in efficiency,interpretability,transferability,stability,economy,and robustness.To overcome these challenges,we propose critical potential directions in future research,including reasonable sample generation,training models with small datasets,enhancing transfer ability,combining with physics models,collective generative pre‐trained transformer‐agents,multiple foundation models,and improving system robustness,to make advancing AI technologies more suitable for practical engineering.

What Characterizes Chinese Students’ Exposition Besides Deduction and Induction?: A Comparative Rhetoric Perspective

Rhetorical features of Chinese writers’essays have been studied for decades but inconsistent interpretations of deduction and induction lead to controversial results.Taking a comparative rhetoric perspective,this paper clarifies the notions of deduction and induction and investigates what rhetorical features characterize Chinese expository paragraphs besides deduction and induction and whether Chinese EFL learners’English paragraphs have similar features.Two kinds of data sources were used—29 full-score Chinese expositions in College Entrance Examinations and 29 English expositions written by Chinese EFL learners.The results show that deduction is preferred in both Chinese and EFL writing,and that rhetorical paragraphs and coordinate paragraphs are particular to Chinese writing while the EFL learners’paragraphs display hybrid rhetoric such as semi-coordination.It is concluded that neither Chinese paragraphs nor EFL ones are similar to the modern English rhetorical paradigm,and English rhetoric instruction will facilitate the introspection of the two kinds of rhetoric.

Polynomial algorithm of limited propositional deduction

For the problem of propositional satisfiability a polynomial algorithm of limited propositional deduction is proposed which can be viewed as a sort of boolean constraint propagation mechanism. It can be embodied in a backtracking search program for propositional satisfiability problems to make search efficient. The efficiency is gained in two ways:One is to use the algorithm to derive literals so as to overcome the ambiguities in search. The other is to exploit the consequence sets of unbound atoms generated during limited deduction as a heuristic measure for possible choices. The experiments have shown remarkable improvement in reducing search space.

N SYSTEM:A NATURAL TEMPORAL DEDUCTION SYSTEM

In the last decade temporal logic has been developed into an effective means of specifying and proving properties of programs and behaviour of dynamic information systems.This note presents a natural deduction system (N system) of propositional temporal logic, which can be easily and immediately extended to other temporal logics.

Monotonic and nonmonotonic gentzen deduction systems for L_(3)-valued propositional logic

A sequent is a pair(Г,△),which is true under an as-signment if either some formula inГis false,or some formula in △ is true.In L3-valued propositional logic,a mulisequent is a triple △|Θ|Г,which is true under an assignment if either some formula in △ has truth-value t,or some formula in Θ has truth-value m,or some formula in Г has truth-value￡.Corre-spondingly there is a sound and complete Gentzen deduction system G for multisequents which is monotonic.Dually,a CO-multisequent is a triple △:Θ:Г,which is valid if there is an assignment v in which each formula in△has truth-value≠t,each formula in Θ has truth-value≠m,and each formula in Г has truth-value≠￡.Correspondingly there is a sound and com-plete Gentzen deduction system G-for co-multisequents which is nonmonotonic.

Clausal Presentation of Theories in Deduction Modulo

Resolution modulo is an extension of first-order resolution in which rewrite rules are used to rewrite clauses during the search. In the first version of this method, clauses are rewritten to arbitrary propositions. These propositions are needed to be dynamically transformed into clauses. This unpleasant feature can be eliminated when the rewrite system is clausal, i.e., when it rewrites clauses to clauses. We show in this paper how to transform any rewrite system into a clausal one, preserving the existence of cut free proofs of any sequent.

Computational Experiments for Complex Social Systems:Experiment Design and Generative Explanation

Powered by advanced information technology,more and more complex systems are exhibiting characteristics of the cyber-physical-social systems(CPSS).In this context,computational experiments method has emerged as a novel approach for the design,analysis,management,control,and integration of CPSS,which can realize the causal analysis of complex systems by means of“algorithmization”of“counterfactuals”.However,because CPSS involve human and social factors(e.g.,autonomy,initiative,and sociality),it is difficult for traditional design of experiment(DOE)methods to achieve the generative explanation of system emergence.To address this challenge,this paper proposes an integrated approach to the design of computational experiments,incorporating three key modules:1)Descriptive module:Determining the influencing factors and response variables of the system by means of the modeling of an artificial society;2)Interpretative module:Selecting factorial experimental design solution to identify the relationship between influencing factors and macro phenomena;3)Predictive module:Building a meta-model that is equivalent to artificial society to explore its operating laws.Finally,a case study of crowd-sourcing platforms is presented to illustrate the application process and effectiveness of the proposed approach,which can reveal the social impact of algorithmic behavior on“rider race”.

F-fuzzy Calculus System

A formalized calculus system called F_fuzzy calculus system, which is a symbol deduction system to formalize fuzzy inference, is constructed in this paper. The fuzzy modus ponens was completely formalized in this calculus system.

Tree of Fermat-Pramanik Series and Solution of AM +B2 =C2 with Integers Produces a New Series of (C12- B12)=(C22- B22)=(C32- B32)=Others

The Fermat–Pramanik series are like below: .The mathematical principle has been established by factorization principle. The Fermat-Pramanik tree can be grown. It produces branched Fermat-Pramanik series using same principle making Fermat-Pramanik chain. Branched chain can be propagated at any point of the main chain with indefinite length using factorization principle as follows: Same principle is applicable for integer solutions of AM+B2=C2which produces series of the type . It has been shown that this equation is solvable with N{A, B, C, M}. where , , M=M1+M2 and M1>M2. Subsequently, it has been shown that using M= M1+M2+M3+... The combinations of Ms should be taken so that the values of both the parts (Cn+Bn) and (Cn-Bn) should be even or odd for obtaining Z{B,C}. Hence, it has been shown that the Fermat triple can generate a) Fermat-Pramanik multiplate, b) Fermat-Pramanik Branched multiplate and c) Fermat-Pramanik deductive series. All these formalisms are useful for development of new principle of cryptography. .

教师谈“双语教学”的授课体会

我在硕士研究生一年级的《电子商务概论》课程中采用“双语教学”已有4年时间了。该课程为每周3课时，共16周，计48学时，目前使用的教材是高等教育出版社出版的、教育部高等教育司推荐的“国外优秀信息科学与技术系列教材”中的影印版教材“Electronic Commerce A Managerial Pcrspective(电子商务管理视角)”。讲课用比较详细的PowerPoint英语演示文稿。

Application of CPD in Analyzing EM Field in Stratified Media with an Uniform Plane Wave Slanted Through

The Counter-Propagation Deduction (CPD) method suggested by the authors is a new one for analyzing electromagnetic (EM) field in stratified media. The mechanism or the method is briefly introduced, and the rield in a layered medium in the presence or slant incidence of a perpendicularly or parallelly polarized electric wave is investigated. Some illustrative examples show that the method is capable of providing the direct mathematic expressions of the fields in an arbitrary layer, and is convenient for numerical evaluation through an unified program, irrespective of the number of medium layers.

A Worsted Yarn Virtual Production System Based on BP Neural Network

Back-Propagation (BP) neural network and its modified algorithm are introduced. Two series of BP neural network models have been established to predict yarn properties and to deduce wool fiber qualities. The results from these two series of models have been compared with the measured values respectively, proving that the accuracy in both the prediction model and the deduction model is high. The experimental results and the corresponding analysis show that the BP neural network is an efficient technique for the quality prediction and has wide prospect in the application of worsted yarn production system.