建构高校心理健康教育模式的探索

高校心理健康教育模式以定位教育目标———适应性目标、创新性目标、协助性目标为出发点 ,通过对心理健康教育的基础途径、关键途径、补充途径、保证途径的探索 ,进一步思考心理健康教育的教学内容、策略、原则的选择 。

技术范式变革环境下组织的战略适应性

技术范式作为组织的外部环境因素之一,是推动组织战略变革的重要因素。在技术变革加速的时代,把握行业技术范式的变革对组织的生存和发展具有重要战略意义。技术范式变革会引起组织外部竞争环境的变化,因此,认识技术范式变革的动力机制以及演化规律,了解技术范式"技术性"和"竞争性"的双重含义,对于组织如何调整其目标市场、组织能力、组织制度和组织边界,制定与外部环境相适应的发展战略,具有重要的现实意义。

集成式健康教育对慢性支气管炎缓解期患者康复锻炼依从性及生活质量的影响

目的探讨适应性行为促进为目标的集成式健康教育对慢性支气管炎缓解期患者康复锻炼依从性及生活质量的影响。方法选取2016年7月至2018年1月商丘市第一人民医院收治的82例慢性支气管炎缓解期患者,按随机数表法分为对照组与观察组,各41例。对照组患者接受随机口头健康教育,观察组患者接受适应性行为促进为目标的集成式健康教育。均干预6个月,比较两组患者康复锻炼依从性及干预前后生活质量。结果观察组患者康复锻炼依从性较对照组高,差异有统计学意义(P <0. 05)。干预6个月后观察组患者生活质量评分较对照组高,差异有统计学意义(P <0. 05)。结论对慢性支气管炎缓解期患者采用适应性行为促进为目标的集成式健康教育,可提高患者康复锻炼依从性,改善生活质量。

Composite multiobjective optimization beamforming based on genetic algorithms

All the parameters of beamforming are usually optimized simultaneously in implementing the optimization of antenna array pattern with multiple objectives and parameters by genetic algorithms （GAs）. Firstly, this paper analyzes the performance of fitness functions of previous algorithms. It shows that original algorithms make the fitness functions too complex leading to large amount of calculation, and also the selection of the weight of parameters very sensitive due to many parameters optimized simultaneously. This paper proposes a kind of algorithm of composite beamforming, which detaches the antenna array into two parts corresponding to optimization of different objective parameters respectively. New algorithm substitutes the previous complex fitness function with two simpler functions. Both theoretical analysis and simulation results show that this method simplifies the selection of weighting parameters and reduces the complexity of calculation. Furthermore, the algorithm has better performance in lowering side lobe and interferences in comparison with conventional algorithms of beamforming in the case of slightly widening the main lobe.

Space luminous environment adaptability of missile-borne star sensor

To solve the problem of stray interference to star point target identification while a star sensor imaging to the sky, a study on space luminous environment adaptability of missile-borne star sensor was carried out. By Plank blackbody radiation law and some astronomic knowledge, irradiancies of the stray at the star sensor working height were estimated. By relative astrophysical and mathematics knowledge, included angles between the star sensor optical axis point and the stray at any moment were calculated. The calculation correctness was verified with the star map software of Stellarium. By combining the upper analysis with the baffle suppression effect, a real-time model for space luminous environment of missile-borne star sensor was proposed. By signal-noise rate （SNR） criterion, the adaptability of missile-borne star sensor to space luminous environment was studied. As an example, a certain type of star sensor was considered when imaging to the starry sky on June 22, 2011 （the Summer Solstice） and September 20, 2011 （August 23 of the lunar year, last quarter moon） in Beijing. The space luminous environment and the adaptability to it were simulated and analyzed at the star sensor working height. In each period of time, the stray suppression of the baffle is analyzed by comparing the calculated included angle between the star sensor optical axis point and the stray with the shielded provided by system index. When the included angle is larger than the shielded angle and less than 90~, the stray is restrained by the baffle. The stray effect on star point target identification is analyzed by comparing the irradiancy of 6 magnitude star with that of the stray on star sensor sensitization surface. When the irradiancy of 6 magnitude star is 5 times more than that of the stray, there is no effect on the star point target identification. The simulation results are identicat with the actual situation. The space luminous environment of the missile-borne star sensor can be estimated real-timely by this model. The adaptability of the star sensor to space luminous environment can be analyzed conveniently. A basis for determining the relative star sensor indexes, the navigation star chosen strategy and the missile launch window can be provided.

Adaptive multi-modal feature fusion for far and hard object detection

In order to solve difficult detection of far and hard objects due to the sparseness and insufficient semantic information of LiDAR point cloud,a 3D object detection network with multi-modal data adaptive fusion is proposed,which makes use of multi-neighborhood information of voxel and image information.Firstly,design an improved ResNet that maintains the structure information of far and hard objects in low-resolution feature maps,which is more suitable for detection task.Meanwhile,semantema of each image feature map is enhanced by semantic information from all subsequent feature maps.Secondly,extract multi-neighborhood context information with different receptive field sizes to make up for the defect of sparseness of point cloud which improves the ability of voxel features to represent the spatial structure and semantic information of objects.Finally,propose a multi-modal feature adaptive fusion strategy which uses learnable weights to express the contribution of different modal features to the detection task,and voxel attention further enhances the fused feature expression of effective target objects.The experimental results on the KITTI benchmark show that this method outperforms VoxelNet with remarkable margins,i.e.increasing the AP by 8.78%and 5.49%on medium and hard difficulty levels.Meanwhile,our method achieves greater detection performance compared with many mainstream multi-modal methods,i.e.outperforming the AP by 1%compared with that of MVX-Net on medium and hard difficulty levels.