Optimal Portfolio Selection with Delay under the Framework of Uncertainty Theory

This study focuses on investigating the optimal investment strategy for an optimization problem with delay using the uncertainty theory. The financial market is composed of a risk-free asset and a risk asset with an uncertain price process described by an uncertain differential equation. An optimization problem is assumed that its objective is a nonlinear function of decision variable. By deriving the equation of optimality, an analytical solution is obtained for the optimal delay investment strategy, and the optimal delay value function. Finally, an economic analysis and numerical sensitivity analysis are conducted to evaluate the research results.

An Improved Approach to Test Diagnosability of Bounded Petri Nets

For bounded Petri nets, Cabasino et al. propose a diagnosability test method that is based on the analysis of a modified basis reachability graph and a basis reachability diagnoser. However, its complexity is exponential in the number of nodes of the basis reachability diagnoser. In order to reduce the complexity of their method, this paper presents a new diagnosability test approach for bounded Petri nets. We present the concept of an extended basis reachability graph and prove that our approach is of polynomial complexity in the number of nodes of extended basis reachability graphs. An example is given to illustrate the application of the presented approach.

Design of 60GHz RF Transceiver in CMOS:Challenges and Recent Advances

With more than 40 years Moore scaling, the speed of CMOS transistors is around 100 GHz. Such fact makes it possible to realize mm-wave circuits in CMOS. However, with the target of achieving broadband and power-efficient operation, 60 GHz CMOS RF transceiver faces severe challenges. After reviewing the technology issues, regarding the 60 GHz applications, this paper discusses design challenges both from the system and the building block levels, and also presents some simulated or measured circuits results.

Determination of rock depth using artificial intelligence techniques

This article adopts three artificial intelligence techniques, Gaussian Process Regression（GPR）, Least Square Support Vector Machine（LSSVM） and Extreme Learning Machine（ELM）, for prediction of rock depth（d） at any point in Chennai. GPR, ELM and LSSVM have been used as regression techniques.Latitude and longitude are also adopted as inputs of the GPR, ELM and LSSVM models. The performance of the ELM, GPR and LSSVM models has been compared. The developed ELM, GPR and LSSVM models produce spatial variability of rock depth and offer robust models for the prediction of rock depth.

STUDY ON THE SIGNATURE OF GROUND MOVING TARGET FOR AIRBORNE SQUINT SAR IMAGING

Compared with the side-looking Synthetic Aperture Radar (SAR), the flexible beampointing of squint SAR makes great application value. This paper derives the image signature of the ground moving target after the processing of Range-Doppler (RD) algorithm, the SAR signatures of ground moving targets are analyzed, including the geometry correction, the offsets and defocusing in both range and azimuth direction. Finally, computer simulation results validate its effectiveness. The research results are especially significant for moving targets detection and parameters estimation in squint mode SAR.

A new understanding of inert gas narcosis

Anesthetics are extremely important in modem surgery to greatly reduce the patient,s pain. The understanding of anesthesia at molecular level is the preliminary step for the application of anesthetics in clinic safely and effectively. Inert gases, with low chemical activity, have been found to cause anesthesia for centuries, but the mechanism is unclear yet. In this review, we first summarize the progress of theories about general anesthesia, especially for inert gas narcosis, and then propose a new hypothesis that the aggregated rather than the dispersed inert gas molecules are the key to trigger the narcosis to explain the steep dose-response relationship of anesthesia.

Application of Organ-on-Chip in Drug Discovery

Nowadays the pharmaceutical industry is facing long and expensive drug discovery processes. Current preclinical drug evaluation strategies that utilize oversimplified cell cultures and animal models cannot satisfy the growing demand for new and effective drugs. The microengineered biomimetic system, namely organ-on-chip (OOC), simulating both the biology and physiology of human organs, has shown greater advantages than traditional models in drug efficacy and safety evaluation. The microengineered co-culture models recapitulate the complex interactions between different types of cells in vivo. Organ-on-chip system has also avoided the substantial interspecies differences in key disease pathways and disease-induced changes in gene expression profiles between human and other animal models. Biomimetic microsystems representing different organs have been integrated into a single microdevice and linked by a microfluidic circulatory system in a physiologically relevant manner. In this review, I outline the current development of organ-on-chip, and their applications in drug discovery. This human-on-chip system can model the complex, dynamic process of drug absorption, distribution, metabolism and excretion, and more reliably evaluate drug efficacy and toxicity. I also discuss, for the next generation of organ-on-chip, more research is required to identify suitable materials that can be used to mass produce organs-on-chips at low cost, and to scale up the system to be suitable for high-throughput analysis and commercial applications. There are more aspects that need to be further studied, thereby bring a much better tool to patients, drug developers, and clinicians.

Activities of daily living and lesion position among multiple sclerosis patients by Bayes network

Magnetic resonance imaging is a highly sensitive approach for diagnosis of multiple sclerosis, and T2-weighted images can reveal lesions in the cerebral white matter, gray matter, and spinal cord. However, the lesions have a poor correlation with measurable clinical disability. In this study, we performed a large-scale epidemiological survey of 238 patients with multiple sclerosis in eleven districts by network member hospitals in Shanghai, China within 1 year. The involved patients were scanned for position and size of lesions by MRI. Results showed that lesions in the cerebrum, spina cord, or supratentorial position had an impact on the activities of daily living in multiple sclerosis patients, as assessed by the Bayes network. On the other hand, brainstem lesions were very unlikely to influence the activities of daily living, and were not associated with the position of lesion, patient＇s gender, and patient＇s living place.

Electronic Structure and Optical Properties of LiBiO3 Doped with V,Nb,and Ta

The crystal structure, band structure, density of states, Mulliken charge, bond population and optical properties for LiBi_（1-x）M_xO_3（M=V, Nb, and Ta） were investigated using hybrid density functional theory. It was found that LiBiO_3 doped with V, Nb, and Ta presented distinctly stronger covalent interactions in M-O（M=V, Nb, and Ta） than Bi-O, thus resulting in mild distortion of the structure and facilitating the separation of photogenerated carriers. Furthermore, the hybridizations of Bi-6s, M-d（M=V, Nb, and Ta） and O-2p widened the valence and conduction bands, which promoted transmission of photogenerated carriers in the band edge and thus caused better photocatalytic performance.

Research of relationship between uncertainty and investment

This study focuses on revealing the relationship between uncertainty and investment probability through real option model involving investment critical trigger and project earning. Use of Matlab software on the experimental results showing that project earning volatility influences investment probability, led the authors to conclude that this notion is not always correct, as increasing uncertainty should have an inhibiting effect on investment, and that in certain situation, increasing uncertainty actually increases the investment probability and so, should have positive impact on investment.

Biphasic behavior of energy in a stepped chain

The impact energy decay in a step-up chain containing two sections is numerically studied.There is a marked biphasic behavior of energy decay in the first section.Two sections close to the interface are in compression state.The degree of compression of the first section first decreases and becomes weakest at ＂crossing＂ time of biphasic behavior of energy,then increases.The further calculations provide the dependence of the character time on mass ratio（m1/m2）,where m1 and m2are the particle mass in the first and second section respectively.The bigger the α（α = [（？ m1-m2）/（？ m1＋ m2）]2 with？ = 1.345）,the bigger the energy ratio is.The multipulse structure restricts the transport of energy.

A KIND OF PAPR REDUCTION METHOD BASED ON PRUNING WPM AND PTS TECHNOLOGY

Wavelet packet multicarrier system gains widespread concern because of its better resistance performance to Inter-Symbol Interference (ISI) and Inter-Carrier Interference (ICI), as well as the higher spectrum efficiency. However, multicarrier system has a high Peak to Average Power Ratio (PAPR), which will lead to many problems such as lower system performance. In order to solve the problem, a kind of PAPR reduction method based on pruning Wavelet Packet Modulation (WPM) and Partial Transmit Sequences (PTS) technology is proposed in this paper, through proper pruning of the full-tree structure of wavelet packet modulation in the PTS technology to reduce the number of nodes in the system, and finally improve the reduction effect of PAPR. Simulation results show that when Complementary Cumulative Distribution Function (CCDF) is 10 -3 , PTS based on pruning WPM compared with PTS technique and pruning technique has improved about 1 dB and 1.5 dB, which will not affect the system's Bit Error Rate (BER) performance in the wavelet packet multicarrier system.

Out-of-plane shear flow effects on fast magnetic reconnection in a two-dimensional hybrid simulation model

The effects of out-of-plane shear flows on fast magnetic reconnection are numerically investigated by a two- dimensional （2D） hybrid model in an initial Harris sheet equilibrium with flows. The equilibrium and driven shear flows out of the 2D reconnection plane with symmetric and antisymmetric profiles respectively are used in the simulation. It is found that the out-of-plane flows with shears in-plane can change the quadrupolar structure of the out-of-plane magnetic field and, therefore, modify the growth rate of magnetic reconnection. Furthermore, the driven flow varying along the anti-parallel magnetic field can either enhance or reduce the reconnection rate as the direction of flow changes. Secondary islands are also generated in the process with converting the initial X-point into an O-point.

Intelligent Integrated Control of Underactuated Mechanical Systems with Second-order Nonholonomic Constraints

This paper describes an intelligent integrated control of an acrobot, which is an underactuated mechanical system with second-order nonholonomic constraints. The control combines a model-free fuzzy control, a fuzzy sliding-mode control and a model-based fuzzy control. The model-free fuzzy controller designed for the upswing ensures that the energy of the acrobot increases with each swing. Then the fuzzy sliding-mode controller is employed to control the movement that the acrobot enters the balance area from the swing-up area. The model-based fuzzy controller, which is based on a Takagi-Sugeno fuzzy model, is used to balance the acrobot. The stability of the fuzzy control system for balance control is guaranteed by a common symmetric positive matrix, which satisfies linear matrix inequalities.

Performance Analysis of Optical Wireless Communication System Employing Neuro-Fuzzy Based Spot-Diffusing Techniques

The spot-diffusing technique provides better performance compared to conventional diffuse system for indoor optical-wireless communication (OWC) system. In this paper, the performance of an OW spot-diffusing communication system using Neuro-Fuzzy (NF) adaptive multi-beam transmitter configuration has been proposed. The multi-beam transmitter generates multiple spots pointed in different directions, hence, forming a matrix of diffusing spots based on position of the receiver and receiver mobility. Regardless of the position of the transmitter and receiver, NF controller target the spots adaptively at the best locations and allocates optimal power to the spots and beam angle are adapted in order to achieve better signal-to-noise plus interference ratio (SNIR). Maximum ratio combining (MRC) is used in the imaging receiver. The proposed OW spot-diffusing communication system is compared with other spot-beam diffusion methods proposed in literature. Performance evaluation revels that the proposed NF based OW spot-diffusing communication system outperforms other spot-beam diffusion methods.

Study on the Elman Neural Network Operation Control Strategy of the Central Air Conditioning Chilled Water System

The stable operation of the central air conditioning water system always is a major difficulty for the control profession. Paper focus on the water system with multi variable, strong coupling, nonlinear, large time delay characteristics, presented use feed forward coupling compensation method, to eliminate the coupling effect between temperature and pressure. In this paper, the Elman neural network controller is designed for the first time, and the simulation results show that the response time of Elman neural network controller is shorter, the system is more stable and the overshoot is small.

Role based access control design using Triadic concept analysis

Role based access control is one of the widely used access control models.There are investigations in the literature that use knowledge representation mechanisms such as formal concept analysis(FCA),description logics,and Ontology for representing access control mechanism.However,while using FCA,investigations reported in the literature so far work on the logic that transforms the three dimensional access control matrix into dyadic formal contexts.This transformation is mainly to derive the formal concepts,lattice structure and implications to represent role hierarchy and constraints of RBAC.In this work,we propose a methodology that models RBAC using triadic FCA without transforming the triadic access control matrix into dyadic formal contexts.Our discussion is on two lines of inquiry.We present how triadic FCA can provide a suitable representation of RBAC policy and we demonstrate how this representation follows role hierarchy and constraints of RBAC on sample healthcare network available in the literature.

Three-axis magnetic flux leakage in-line inspection simulation based on finite-element analysis

With the increase of pipelines, corrosion leakage accidents happen frequently. Therefore, nondestructive testing technology is important for ensuring the safe operation of the pipelines and energy mining. In this paper, the structure and principle of magnetic flux leakage （MFL） in-line inspection system is introduced first. Besides, a mathematic model of the system according to the ampere circuit rule, flux continuity theorem, and column coordinate transform is built, and the magnetic flux density in every point of space is calculated based on the theory of finite element analysis. Then we analyze and design the disposition of measurement section probes and sensors combining both three-axis MFL in-line inspection and multi-sensor fusion technology. Its advantage is that the three-axis changes of magnetic flux leakage field are measured by the multi-probes at the same time, so we can determine various defects accurately. Finally, the theory of finite element analysis is used to build a finite element simulation model, and the relationship between defects and MFL inspection signals is studied. Simulation and experiment results verify that the method not only enhances the detection ability to different types of defects but also improves the precision and reliability of the inspection system.

Quantum Secret Sharing Based on Chinese Remainder Theorem

分享的一个新奇的量秘密(QSS ) 计划根据中国剩余物定理(CRT ) 被建议。在计划，古典消息根据 CRT 方程被印射到秘密序列，并且分别地由不同维的编码 superdense 散布了到不同接收装置。CRT 的秘密分享功能和高度维的编码 superdense，为秘密分发提供便利，安全，和大能力量隧道并且恢复。分析显示出计划的安全。

基于对偶原理的炼钢-连铸生产双层规划问题的遗传算法研究(英文)

Steel-making and continuous/ingot casting are the key processes of modern iron and steel enterprises. Bilevel programming problems(BLPPs) are the optimization problems with hierarchical structure. In steel-making production, the plan is not only decided by the steel-making scheduling, but also by the transportation equipment.This paper proposes a genetic algorithm to solve continuous and ingot casting scheduling problems. Based on the characteristics of the problems involved, a genetic algorithm is proposed for solving the bilevel programming problem in steel-making production. Furthermore, based on the simplex method, a new crossover operator is designed to improve the efficiency of the genetic algorithm. Finally, the convergence is analyzed. Using actual data the validity of the proposed algorithm is proved and the application results in the steel plant are analyzed.