Earticle

In this paper, a method of reducing the weight of vehicle wheels through topology optimization by finite element method is proposed. Recently, various environmental pollution caused by the operation of vehicles is gradually increasing, and this has a great correlation with the fuel efficiency of the vehicle. Therefore, it is required to reduce the weight of the vehicle to increase fuel efficiency. Among them, the vehicle's wheels are a key part of vehicle acceleration and braking, and passenger safety. Because the shape of the wheels is different, various effects such as reduced fuel economy and reduced airpower occur as well as aesthetic factors. The stiffness of the wheels plays an important role in transmitting the vehicle's power to the tires and braking. In this study, to reduce weight while satisfying the stiffness value, we propose to use topology optimization to design an arbitrary shape according to the number of spokes on the wheel.

본고는 한국 사설 헤드라인의 기계번역 품질 저하가 번역 엔진의 성능이 아니라 한일 양국 헤드라인의 구조적 비대칭에 기인한다는 인식에서 출발한다. 일본 사설 헤드라인은 ‘키워드＋공백＋클레임’이라는 이분 구조를 신문사에 관계없이 일관되게 유지하는 반면, 한국 사설 헤드라인은 이에 필적할 형식적 규칙성을 보이지 않는다. 본고는 본 연구자가 한일 사설 헤드라인 대조에 관한 일련의 연구를 통해 규명한 키워드–클레임 이분 구조, 기호 사용의 제한, 문말표현 유형 분포, 헤드라인–본문 간 응집성을 통합하여 일본식 헤드라인 구조 모델을 도출하고, 이를 Claude API의 프롬프트로 형식화하였다. 한국 사설 본문을 입력하여 구조 모델에 따른 한국어 헤드라인을 생성한 뒤 DeepL API로 번역하는 파이프라인을 구축하고, 적용 결과에 대해 (a) 구조 모델 적용, (b) 일반 지시, (c) 원제목 직접 번역의 세 조건을 비교 검증하였다. 그 결과, 구조 모델을 적용해 생성한 헤드라인(a)이 이분 구조 준수율 100%, 번역 후 평균 자수 20.6자, 기호 사용률 10%, 문말표현 분포에서 실제 일본 사설에 가장 근접하였으며, 사례 분석에서도 관용 표현의 의미 소실 차단, 과잉 정보의 억제, 담화 기능의 재현이 확인되었다. 종래의 사전 편집이 어휘･통사 수준에 머물렀던 한계를 넘어, 목표 언어의 장르적 관습을 구조 모델로 형식화하여 기계번역 입력을 재구성하는 전략의 유효성을 실증한 점에서 의의가 있다.

In this study, I argue that the deterioration in the quality of machine translated Korean editorial headlines to Japanese stems from the structural asymmetry between the headline conventions of the two countries. Japanese editorial headlines maintain a 100% binary “keyword + space + claim” structure across all newspapers, which is missing in Korean headlines. When I integrated findings from five previous studies on keyword-claim structure, punctuation restrictions, sentence-final expressions, and headline-body cohesion, our study derived a Japanese-style structural model and formalized it as a Claude API prompt. An automated pipeline generated structurally-converted Korean headlines from editorial texts and translated them through DeepL API. I verified 60 editorials across three conditions—(a) structural model application, (b) general instruction only, and (c) direct translation. I showed that condition (a) most closely approximated Japanese norms: 100% binary structure compliance, a post-translation mean of 20.6 characters, 10% punctuation rate, and sentence-final expression distributions that match Japanese patterns. This study extends conventional pre-editing beyond lexical-syntactic modification to demonstrate the effectiveness of formalizing target-language genre conventions as a structural model.

This study, high-rise structure design of lateral loads, topics are slenderness ratio and stiffness. CTBUH said that high-rise structure is defined by slenderness ratio and later load resistance system. Selected analysis model is optimized by weight optimization method by taking the principle of virtual work. It's slenderness ratio is 5. Lateral load is proportional to structure's height. Stiffness method gives some analytical advantages to analysis the high-rise building rather than strength method. In generally analysis, lateral deflection controls structural limit state in the high-rise building design. And the lateral deflection can be easily find by stiffness method rather than strength method. We study for the weight optimization of the high-rise concrete structural model. We set up object function of weight and constraint function to obtain optimization member sizes. Because the lateral deformation constraint function can not be simply defined between correlation with object function. So, use principal of virtual work for lateral deformation constraint function to clear correlation with object function. This thesis suppose the slenderness ratio and many assumption. As a results from this study, we easily find member sizes, and lateral deformation at the limit state and strength with minimum weight. By structural analysis of deduction member sizes, demonstrate validity and usefulness of high-rise concrete structure optimization. Results of this thesis are as follows. First, Stiffness design is more effective than strength method. Cause, Strength method finds hard later deformation and takes more time than stiffness method. Enfin, Stiffness method is advantageous at High-rise structure design. Second, Existing constraint function isn't reflect geometrical shape for members. So, interaction between constraint and object function are indefinite. To solve this problem, We define between member shapes and lateral deformation to use principle of virtual work. In result, We find that it is relation of effect of lateral deformation and member shapes.

The prototype of Hanhwa AUV (Autonomous Underwater Vehicle) was developed to prepare future system developments in Hanwha Corporation. This paper presents the procedure and results of the structural design and analysis for the End Cap of Hanwha AUV. Several methodologies used for structural optimization were presented and applied to the design of the End Cap structure. Both shape optimization and thickness optimization were performed simultaneously. And because the FEM analysis model was used for structural optimization, design and analysis procedures were simultaneously conducted. Several analysis methods such as static analysis, buckling analysis, and normal mode analysis were used with procedure that was similar to the MDO (Multidisciplinary Design Optimization). The objective is to design the structural weight. The constraints are maximum displacement and maximum von Mises stress in static analysis, the buckling coefficient in buckling analysis, and lowest natural frequency in normal mode analysis. The design variable concerning thickness optimization is the thickness of the End Cap shell, as well as the depth of the End Cap concerning shape optimization. In thickness optimization, the optimization for variable thicknesses at the final shape iteration was performed, and we can see that the weight was significantly reduced.

In this paper, we combine the literature review and technique reports to conduct research on the novel non-contact power supply system tuning methodology based on fuzzy neural network theory under the random load condition. Power supply by non-contact way could increase the flexibility of electrical equipment, eliminates the traditional power supply methods of safe hidden trouble and makes up for the traditional power supply methods because of the existence of electrical connections of the lack of divination. The background harmonic separation of qualitative method is detecting system side and user side common connection point for the size of the harmonic distortion effect. The genetic algorithm with adaptive system, cellular automata, chaos theory and artificial intelligence is considered for the next decade computing technology has a significant impact on the key technology which is adopted by our research to optimize the proposed system. Mathematical analysis and dynamic load change can lead to circuit reactance, so system will deviate from the resonance state. The experimental simulation proves the feasibility and robustness of our proposed methodology. In the near future, more related research will be conducted to optimize and modify the current method.

In this paper, we theoretically and numerically analyze the time delay and corresponding issues for the novel category of Internet of things control system. At present, the Internet of things technology progress and mature, people also gradually combine control system and Internet connection and make them to give full play to their strengths. Internet of things has great innovation in goods intelligent network, and the general Internet of things in the motion control system has a great development space, the future of control system is applied to the large number of the wireless fieldbus and sensor networks. To overcome the severe issues of the IOT system denoted as the time delay, we conduct research from following perspectives. (1) The control system modelling and analysis. Compared in the actual control system in an event-driven clock driver has many advantages such as when the controller equipment or setting of event-driven actuators equipment. (2) The time delay analysis with mathematical modelling. Due to the signal delay, controller cannot receive timely feedback information of the object which will seriously affect the dynamic performance of the remote control system. Complex math model is proposed to deal with the issues. In the final part, we numerically simulation the proposed model and theory compared with other famous methods, the result indicates that the proposed method obtain better performance and feasibility.

This paper suggests the optimization method of RDF Repository. When state data that occurred thing composing context information, this method processes in real-time using ontology technique in IoT environment. It needs to adapt meaning system about state to delivery correct state among different things. In other words, it is important to adapt technique to guarantee Semantic Interoperability. For this, People suggest a method such as SSNO based on ontology. However, techniques were center of modeling to express most things. They have a lack of paper about real-time reasoning engine that processes thing’s state and context. Also, ontology reasoning engine based on RDF repository currently optimized static data processing. Due to this reason, it can not be satisfy real-time processing that request from IoT service. Therefore, this paper research a method about optimizing RDF repository composition to solve this problem.

This thesis focuses on the problems of high-temperature furnace motor in term of rotary shaft over length as well as deformation tendency under high-temperature condition, and therefore the thesis conducts design optimization upon rotary shaft of a motor that is applied in high-temperature furnace regarding its mechanical property and thermal-stress distribution. First, it establishes a full-scale 3D model of the shaft-fan system, then it analyzes its mechanical properties such as rigidity and stiffness under the high-temperature environment, which bases on reasonable assumed conditions and the boundary conditions, where hence the thesis puts forwards an optimized dimension design solution for the motor rotary shaft. And then the thesis analyzes and calculates the shaft-fan system to improve the motor shaft size from the angle of thermal stress and thermal deformation consideration and the special characteristics of such motor working under high-temperature environment. And the improved motor shaft size is verified as reasonable. The thesis analysis can be the designing references for cooling system applied in the high-temperature furnace motor.

Based on an analysis of the advantages and disadvantages of single-layer and multi-layer BOM structure, and combine with specific examples of products, a more practical—cross-type BOM structure method is presented. Aiming to solve the system efficiency problems brought by the BOM operation in manufacturing. Regarding the queue as a temporary table, we put forward an improved multi-layer BOM traversal algorithm, makes full use of the basic operation characteristics and setting marks in related fields queue and simplifies the complexity of the algorithm. Compared with the traditional recursive algorithm and hierarchical algorithm, the improved algorithm has the advantages of fast speed, low resource consumption, and high practicability. And the improved algorithm is verified through an example.

In this paper, we research on the modern Internet of things system structure optimization methodology based on the information theory and the communication signal transmission model. We analyze the current IOT system from the following aspects. (1) Reliable delivery, that is, through some of the Internet and telecommunication network integration, it will send some information about the object accurately in real time; For the Internet of things, it is an integrated which is by a variety of network and the access and application technology of an integrated, at the same time it is also a can make the objects and people, nature and people as well as a platform for communication between objects and the objects. (2) The comprehensive perception which is to use some of the perception, capture and real-time measurement technology to information acquisition and access to an object with the sensing device can achieve data readout and data sent and no contact some automated to realize long-distance induction. (3) Intelligent processing, is one of the core content of the Internet of things, is to use some intelligent computing some analysis was carried out on large amount of information and data disposal, the Internet of things is able to intelligently control object by the computer network technology, micro processing technology, wireless communication technology and sensor technology product of development of fusion, therefore the Internet of things can be representative even instead of rational analysis. Through combining the information theory and the efficient signal transmission models, we optimize the current IOT architecture and the final experiment result indicates the feasibility of the proposed methodology.

With the rapid and bursting development of computer science and related technology, the design and optimization of network topology has been a most important issue for thee researchers to solve. However, the increasing needs of the current control schemes have already been shown. In this paper, we theoretically analysis the features of neural network structure and convex optimization related method. There are a lot of shortcomings but the cable network should be restricted the wiring in some situations, for example, wiring, reroute workload big, easy to damage, in the network, each node cannot move and so on. With the mathematical optimization, game theory, mathematical economics and optimal control theory to the development of disciplines, convex analysis are increasingly brought to the attention of the people. Our proposed methodology combines the neural network and optimization theory to obtain better performance, the experimental result shows the performance of our approach compared with other state-of-the-art algorithms.

Welding sequence is the important influence factor of the temperature field and residual stress and deformation in welding structure, At present, determining the welding sequence is usually based on experience and test method. For complex structure it is very difficult to get the optimum welding sequence. This study is aiming to settle the problem of solving the optimum welding sequence of complex box welding structure. In our study, we take the welding deformation as objective function, and then, associate glowworm swarm optimization algorithm with thermal-mechanical coupling and nonlinear thermal elastoplastic finite element model to optimize numerical simulation, eventually the optimum welding sequence is determined. Optimization results demonstrate that the optimum welding sequence obtained by our method has small welding deformation and little change rate. At the same time, our method is faster, more accurate, more effective than the traditional experience or test method.

In order to solve such problems as large delay and large energy consumption in current wireless sensor network (WSN) during data collection, a network structure for WSN data collection based on delay perception is designed in this article. Firstly, the tree structure thought is introduced therein to divide WSN sensor nodes into multiple single-layer clusters with different sizes so as to construct a new network structure, thus to improve the topological structure and enable the cluster heads to complete the data communication in an interlaced mode as well as significantly reduce the delay during data collection; secondly, the model for calculating the delay and the energy consumption during WSN data collection is established in this article; thirdly, Top-Down technology is introduced therein to design the network structure formation algorithm, thus to optimize the energy consumption of the data collection mechanism through the communication distance minimization. The experiment shows: compared with existing network structure for WSN data collection, the proposed network structure can not only effectively reduce the delay during WSN data collection, but also maintain the whole communication energy consumption at a relatively low level.

This paper analysis the prediction structure based on layered B frame used by multi view video coding, introduces the common predictive structure and their evaluation index, proposes a kind of improved prediction structure, and makes comparative analysis on the performance of encoding time, PSNR and code rate by experiment which uses the typical test sequences Ball-room and Exit provided by MERL on the multi view video coding test platform. The experimental results show that: the improved prediction structure showed better coding efficiency; coding complexity reduction is up to 15%, the better to improve the real-time performance of code.

Bayesian network is a directed acyclic graph. Existing Bayesian network learning approaches based on search & scoring usually work with a heuristic search for finding the highest scoring structure. This paper describes a new data mining algorithm to learn Bayesian networks structures based on an immune binary particle swarm optimization (IB-PSO) method and the Minimum Description Length (MDL) principle. IBPSO is proposed by combining the immune theory in biology with particle swarm optimization (PSO). It constructs an immune operator accomplished by two steps, vaccination and immune selection. The purpose of adding immune operator is to prevent and overcome premature convergence. Experiments show that IBPSO not only improves the quality of the solutions, but also reduces the time cost.

With the rapid growth of the economy and the increasing improvement of life, the large electricity consumption gradually intensifies power grid transmission pressure. In order to solve this problem, the paper analyses the trend of tremendous development in computer, electronic and electric power technology and makes a deep related research. Based on the further analysis of key technologies, the author sets constraint conditions, analyzes the supporting effect, and establishes an optimal configuration model with multiple purposes for distribution network topological structure. On the basis of the minimal module ideal point algorithm, the over all planning is conducted through deep consideration to assure the further optimal configuration of the model. Then the value will be calculated by using the POS algorithm. At last, four optimization plans are obtained and the fourth one whose weight value can be adjusted is chosen to achieve automation and the more rationalized and optimal development of the distribution network topological structure. In addition, this optimal plan provides a stronger basis of theory to the practical application of related work and industries.

In this work, we show that the excessive lattice heating problem due to parasitic pnp transistor action in the diode electrostatic discharge (ESD) protection device in the diode input protection circuit, which is favorably used in CMOS RF ICs, can be solved by adopting a symmetrical cathode structure. To explain how the recipe works, we construct an equivalent circuit for input human-body model (HBM) test environment of a CMOS chip equipped with the diode protection circuit, and execute mixed-mode transient simulations utilizing a 2-dimensional device simulator. We attempt an in-depth comparison study by varying device structures to suggest valuable design guidelines in designing the protection diodes connected to the $V_{DD}$ and $V_{SS}$ buses. Even though this work is based on mixed-mode simulations utilizing device and circuit simulators, the analysis given in this work clearly explain the mechanism involved, which cannot be done by measurements.

The inherent drawback of iron-core type permanent magnet linear synchronous motor (PMLSM) is detent force that is dependent on several major factors such as PM length, slot clearance, and skewing. To minimize the detent force, this paper proposes a structure optimization using the combination computation of two dimensional (2-D) finite element analysis (FEA) and response surface methodology (RSM). The RSM, that is a collection of the statistical and mathematical techniques, is utilized to predict the global optimal solution based on the FEA calculated results of the detect forces for different combinations of factors. With the help of the combination computation the high capacity iron-core type PMLSM with more than 12000 N propulsion forces only contains less than 3 N detent forces.