A constrained portfolio selection model at considering risk-adjusted measure by using hybrid meta-heuristic algorithms

Portfolio selection is a key issue in the business world and financial fields. This article presents a new decision making method of portfolio optimization (PO) issues in different risk measures by using new evolutionary computing method and cardinality constrains which is mentioned as hybrid meta-heuristic algorithms. Based on mean–variance (MV) Method by Markowitz we collected three risk levels; mean absolute deviation (MAD), semi variance (SV) and variance with skewness (VWS). The developed algorithms are Electromagnetism-like algorithm (EM), particle swarm optimization (PSO), genetic algorithm (GA), genetic network programming (GNP) and simulated annealing (SA). Also a diversification mechanism strategy is implemented and hybridized with the developed algorithms to increase the diversity and overcome local optimality. The sustainability of this proposed model is verified by 50 factories on the Iranian stock exchange. Finally, experimental results of proposed algorithms with cardinality constraint are compared with each other by four effective metrics in which the algorithms performance for achieving the optimal solution discussed. In addition, we have done the analysis of variance technique to confirm the validity and accurately analyze of the results which the success of this method was proved.     

An unsupervised learning method with a clustering approach for tumor identification and tissue segmentation in magnetic resonance brain images

Malignant and benign types of tumor infiltrated in human brain are diagnosed with the help of an MRI scanner. With the slice images obtained using an MRI scanner, certain image processing techniques are utilized to have a clear anatomy of brain tissues. One such image processing technique is hybrid self-organizing map (SOM) with fuzzy K means (FKM) algorithm, which offers successful identification of tumor and good segmentation of tissue regions present inside the tissues of brain. The proposed algorithm is efficient in terms of Jaccard Index, Dice Overlap Index (DOI), sensitivity, specificity, peak signal to noise ratio (PSNR), mean square error (MSE), computational time and memory requirement. The algorithm proposed through this paper has better data handling capacities and it also performs efficient processing upon the input magnetic resonance (MR) brain images. Automatic detection of tumor region in MR (magnetic resonance) brain images has a high impact in helping the radio surgeons assess the size of the tumor present inside the tissues of brain and it also supports in identifying the exact topographical location of tumor region. The proposed hybrid SOM-FKM algorithm assists the radio surgeon by providing an automated tissue segmentation and tumor identification, thus enhancing radio therapeutic procedures. The efficiency of the proposed technique is verified using the clinical images obtained from four patients, along with the images taken from Harvard Brain Repository.     

Stabilization in probability and mean square of controlled stochastic dynamical system with state delay

Although stochastic dynamical systems have received a great deal of attention in terms of stabilization studies, so far there are few works on controlled stochastic dynamical systems with state delay. In this paper, a controlled stochastic dynamical system represented by a stochastic differential equation with state delay is considered. Condition under which the system is exponentially stable in mean square and in probability is examined.     

The impact of temperature on mean local air age and thermal comfort in a stratum ventilated office

The influence of the supply air temperature on the mean local air age and thermal comfort of a typical individual office under stratum ventilation is investigated by a numerical method, which is validated by an experiment carried out by the authors. The results show that for an office, when the supply air temperature is increased from 19 °C to 21 °C, the corresponding mean occupied zone temperature rises from 24.5 °C to 26.5 °C. The inhaled air quality for the occupant is improved when supply air temperature rises from 19 °C to 21 °C. Also, the thermal comfort indices (predicted mean vote or PMV, predicted percentage of dissatisfied or PPD and predicted dissatisfied or PD) fulfill the requirements of ISO 7730 and CR 175 1998. For summer cooling operation, stratum ventilation may offer a feasible solution to elevated indoor temperatures, which are recommended by several governments in East Asia.     

基于CMN和PMC算法的语音增强失真补偿方法研究

语音增强技术在低信噪比情况下,由于语音增强带来的失真使得系统的识别性能严重下降.因此提出一种结合特征空间的倒谱均值归一化算法(CMN)和模型空间的并行模型合并算法(PMC)的语音增强失真补偿技术.实验结果表明,该方法有效提高了低信噪比情况下的语音信号识别率.     

一种基于局部ML的DFT-S-OFDM检测算法

离散傅里叶变换扩频正交频分复用(DFT-S-OFDM)作为一种单载波调制方案,与传统正交频分复用相比具有较小的峰均功率比(PAPR),并且已被3GPP采用作为其长期演进项目(LTE)的上行调制方案。针对该方案,提出了一种改进的基于局部最大似然(ML)的DFT-S-OFDM检测算法,首先挑选一阶最小均方误差-最大似然(MMSE-ML)检测后最有可能的2个星座符号位置,进而在这2个位置上做最大似然检测。仿真结果表明,提出的算法相比二阶MMSE-ML,在大幅度降低计算复杂度的基础上,性能损失很小;相比一阶MMSE-ML,能获得0.5 dB~0.7 dB的增益,而所需的额外计算量较少。     

Influence of mechanical surface treatments on the high cycle fatigue performance of TIMETAL 54M

TIMETAL 54M (in the following Ti-54M) is a newly developed (α + β) titanium alloy with nominal composition Ti-5Al-4V-0.6Mo-0.4Fe. The alloy can provide a cost benefit over Ti-6Al-4V due to improved machinability and formability. These attractive properties might be a driving force for replacing Ti-6Al-4V in many aircraft as well as biomedical applications. Since HCF performance is one of the most important requirements for these applications, it is essential to improve this property by microstructural optimization and by mechanical surface treatments such as shot peening or ball burnishing. The latter improvement is mainly the result of induced near-surface severe plastic deformation which results in work-hardening and the generation of compressive residual stresses that retard fatigue crack propagation. The main aim of the present study was to investigate the potential fatigue life improvements in Ti-54M due to shot peening and ball-burnishing. The process-induced residual stresses and stress-depth profiles were determined by energy-dispersive X-ray diffraction (ED) of synchrotron radiation with the beam energy of 10-80 keV. Results on Ti-54M and Ti-6Al-4V will be compared and correlated with the mean stress and environmental sensitivities of the fatigue strengths in the microstructures.     

数字媒体时代工业产品设计中的“中庸”设计探讨

根据孔子、孟子、荀子为代表的儒家思想对中华民族文化、审美观、价值观的影响。分析了工业产品设计师对儒家"中庸"思想的继承与发扬,论述了中国工业设计师注重产品设计的文化内涵和民族特点的必然性。在此基础上,提出了数字媒体时代儒家"中庸"思想对工业产品外型设计的影响,论述了设计各要素的组合关系、儒家的环境保护理念与绿色设计的契合以及进行本土设计的策略。     

联合Kalman和自适应Meanshift的稳健相关视频跟踪方法

相关视频跟踪器存在计算量大、模板漂移、对机动目标,杂波影响大以及遮挡情况无法跟踪的问题,而Kalman滤波能通过利用相关跟踪器的输出结果来预测目标在下一帧里在图像中的坐标,可以在高概率的小范围内对目标进行搜索,以大幅减小计算量和杂波的影响.然后,当跟踪器由于受到杂波或遮挡的影响而提供了错误的测量信息时,跟踪的性能将大幅下降.大量研究表明,Mean-Shift跟踪器具有运算速度快和跟踪性能好的特点,而当目标柱状图和待选图像区域相近时,其跟踪性能也将大幅下降,甚至无法进行跟踪.为了解决该问题,结合上述3种思想提出了一种改进的、稳健的视频目标跟踪方法,并通过理论分析和仿真结果表明了算法的有效性和优越性.