Exploring Phonetic Differences and Cross-Linguistic Influences: A Comparative Study of English and Mandarin Chinese Pronunciation Patterns

Exploring the differences in phonemes and cross-linguistic influences, particularly by comparing the pronunciation patterns of English and Mandarin, is crucial for language learners. Such comparative studies can help learners better understand and overcome the pronunciation difficulties encountered during second language acquisition. English and Mandarin have significant differences in their vowel and consonant systems, tones, intonation, and syllable structures. A deep understanding of these differences allows learners to engage in targeted pronunciation training, reducing accent interference. This research provides guidance for improving language teaching methods, enabling teachers to design more effective pronunciation strategies and exercises based on the students’ native language backgrounds, thus enhancing learning outcomes. Additionally, cross-linguistic studies aid in improving speech recognition and conversion technologies, achieving higher accuracy and naturalness in multilingual speech processing systems. From a cultural exchange perspective, understanding and respecting the phonetic characteristics of different languages help to enhance the effectiveness and mutual understanding in cross-cultural communication. The comparative study of English and Mandarin pronunciation patterns not only provides a theoretical foundation for language education and technological applications but also promotes effective communication in multilingual environments. This thesis uses a comparative research method to elucidate the study of English and Mandarin pronunciation patterns. It begins with an analysis of the characteristics and similarities of the pronunciation patterns in both languages. The thesis then examines the differences between English and Mandarin pronunciation patterns through four aspects: the number and complexity of vowel phonemes, types and distribution of consonant phonemes, tones and stress, and intonation and phonetic phenomena. Finally, based on the comparative analysis of the differences, the thesis offers targeted policy recommendations for learning English and Mandarin.

Gender Differences in Non-English Major Graduates＇ English Compositions——A Study Based on the Use of Oral/Written Register Features

This article applies the theories of gender differences in language use, makes a survey of non-English major graduates＇ English writing, and analyzes the gender differences in EFL writing proficiency and particularly in the use of oral/written register features, aiming to provide suggestions for gendered teaching in EFL writing.

结合Swin Transformer的多尺度遥感图像变化检测研究

由于地物信息的复杂性及变化检测数据的多元性,遥感图像特征提取的充分性和有效性难以得到保证,导致变化检测方法获取的检测结果可靠性较低。虽然卷积神经网络(CNN)凭借有效提取语义特征的优势,被广泛应用于遥感领域的变化检测之中,但卷积操作固有的局部性导致感受野受限,无法捕获时空上的全局信息以至于特征空间对中远距离依赖关系的建模受限。为捕获远距离的语义依赖,提取深层全局语义特征,设计了一种基于Swin Transformer的多尺度特征融合网络SwinChangeNet。首先,SwinChangeNet采用孪生的多级Swin Transformer特征编码器进行远距离上下文建模;其次,编码器中引入特征差异提取模块,计算不同尺度下变化前后的多级特征差异,再通过自适应融合层将多尺度特征图进行融合;最后,引入残差连接和通道注意力机制对融合后的特征信息进行解码,从而生成完整准确的变化图。在CDD和CD_Data_GZ 2个公开数据集上分别与7种经典和前沿变化检测方法进行比较,CDD数据集中本文模型的性能最优,相比于性能第二的模型,F1分数提高了1.11%,精确率提高了2.38%。CD_Data_GZ数据集中本文模型的性能最优,相比于性能第二的模型,F1分数、精确率和召回率分别提高了4.78%,4.32%,4.09%,提升幅度较大。对比实验结果证明了该模型具有更好的检测效果。在消融实验中也证实了模型中各个改进模块的稳定性和有效性。本文模型针对遥感图像变化检测任务,引入了Swin Transformer结构,使网络可以对遥感图像的局部特征和全局特征进行更有效地编码,让检测结果更加准确,同时保证网络在地物要素种类繁多的数据集上容易收敛。

A Deep Learning Framework for Mass-Forming Chronic Pancreatitis and Pancreatic Ductal Adenocarcinoma Classification Based on Magnetic Resonance Imaging

Pancreatic diseases, including mass-forming chronic pancreatitis (MFCP) and pancreatic ductal adenocarcinoma(PDAC), present with similar imaging features, leading to diagnostic complexities. Deep Learning (DL) methodshave been shown to perform well on diagnostic tasks. Existing DL pancreatic lesion diagnosis studies basedon Magnetic Resonance Imaging (MRI) utilize the prior information to guide models to focus on the lesionregion. However, over-reliance on prior information may ignore the background information that is helpful fordiagnosis. This study verifies the diagnostic significance of the background information using a clinical dataset.Consequently, the Prior Difference Guidance Network (PDGNet) is proposed, merging decoupled lesion andbackground information via the Prior Normalization Fusion (PNF) strategy and the Feature Difference Guidance(FDG) module, to direct the model to concentrate on beneficial regions for diagnosis. Extensive experiments inthe clinical dataset demonstrate that the proposed method achieves promising diagnosis performance: PDGNetsbased on conventional networks record an ACC (Accuracy) and AUC (Area Under the Curve) of 87.50% and89.98%, marking improvements of 8.19% and 7.64% over the prior-free benchmark. Compared to lesion-focusedbenchmarks, the uplift is 6.14% and 6.02%. PDGNets based on advanced networks reach an ACC and AUC of89.77% and 92.80%. The study underscores the potential of harnessing background information in medical imagediagnosis, suggesting a more holistic view for future research.

多模态遥感图像模板匹配Log-Gabor滤波方法

针对多模态遥感图像匹配难的问题,本文提出了一种基于Log-Gabor滤波的高精度匹配方法。该方法采用由粗到细的多层级密集匹配框架,无须进行特征点检测,避开了多模态图像特征点检测重复率低的问题,能够提取大量高精度匹配点对。本文方法主要分为两步:首先,利用多尺度多角度Log-Gabor滤波器构建对图像间非线性辐射差异稳健的特征金字塔;然后,利用粗尺度的底层特征图进行密集模板匹配,提取大量粗粒度的特征匹配点对,在此基础上再利用特征金字塔,实现粗匹配点自下而上的逐层优化,完成高精度特征匹配点对的提取。同时,针对模板匹配滑窗运算效率不高的问题,提出了一种密集模板匹配的快速实现方式,有效减少了密集模板匹配的运算时间。本文使用多组不同模态的遥感图像进行试验,结果表明,本文方法能够克服图像间非线性辐射差异的影响,在正确匹配数目、匹配准确率与匹配精度上均优于现有多模态图像特征匹配方法。

Differences between English and Chinese Syllables and Its Inspiration on English Pronunciation Teaching

English and Chinese belong to different linguistic systems, so English and Chinese syllables, as the basic linguistic structure, own great differences in syllable structure, syllabification, syllable function as well as liaison. Chinese English learners are apt to have the negative transfer in English pronunciation acquisition under the influence of their mother tongue-Chinese. Therefore, only the repeated imitation and practice on the ground of theoretical contrasts and analyses can help learners speak perfect English.

The tectonic differences between the east and the west in the deep-water area of the northern South China Sea

The deep-water area of the northern South China Sea, which has active and complicated tectonics, is rich in natural gas and gas hydrate. While the tectonic characteristics is different obviously between the east and the west because of the special tectonic position and tectonic evolution process. In terms of submarine geomorphology, the eastern shelf-slope structure in Pearl River Mouth Basin is characterized by having wide sub-basins and narrow intervening highs, whereas the western （Qiongdongnan Basin） structure is characterized by narrow sub- basins and wide uplift. As to the structural features, the deep-water sags in the east are all structurally half- grabens, controlled by a series of south-dipping normal faults. While the west sags are mainly characterised by graben structures with faulting in both the south and north. With regards to the tectonic evolution, the east began neotectonic activity when the post-rifting stage had completed at the end of the Middle Miocene. In the Baiyun Sag, tectonic activity became strong and was characterised by rapid subsidence and obvious faulting. Whereas in the west, neotectonic activity began at the end of the Late Miocene with rapid deposition and weak fault activity.

DIFFERENCE FEATURE NEURAL NETWORK IN RECOGNITION OF HUMAN FACES

This article discusses vision recognition process and finds out that human recognizes objects not by their isolated features, but by their main difference features which people get by contrasting them. According to the resolving character of difference features for vision recognition, the difference feature neural network(DFNN) which is the improved auto-associative neural network is proposed.Using ORL database, the comparative experiment for face recognition with face images and the ones added Gaussian noise is performed, and the result shows that DFNN is better than the auto-associative neural network and it proves DFNN is more efficient.

Robust Radiometric Normalization of the near Equatorial Satellite Images Using Feature Extraction and Remote Sensing Analysis

Relative radiometric normalization (RRN) minimizes radiometric differences among images caused by inconsistencies of acquisition conditions rather than changes in surface. Scale invariant feature transform (SIFT) has the ability to automatically extract control points (CPs) and is commonly used for remote sensing images. However, its results are mostly inaccurate and sometimes contain incorrect matching caused by generating a small number of false CP pairs. These CP pairs have high false alarm matching. This paper presents a modified method to improve the performance of SIFT CPs matching by applying sum of absolute difference (SAD) in a different manner for the new optical satellite generation called near-equatorial orbit satellite and multi-sensor images. The proposed method, which has a significantly high rate of correct matches, improves CP matching. The data in this study were obtained from the RazakSAT satellite a new near equatorial satellite system. The proposed method involves six steps: 1) data reduction, 2) applying the SIFT to automatically extract CPs, 3) refining CPs matching by using SAD algorithm with empirical threshold, and 4) calculation of true CPs intensity values over all image’ bands, 5) preforming a linear regression model between the intensity values of CPs locate in reverence and sensed image’ bands, 6) Relative radiometric normalization conducting using regression transformation functions. Different thresholds have experimentally tested and used in conducting this study (50 and 70), by followed the proposed method, and it removed the false extracted SIFT CPs to be from 775, 1125, 883, 804, 883 and 681 false pairs to 342, 424, 547, 706, 547, and 469 corrected and matched pairs, respectively.

Research on Difference of Tourism Consumption Behavior of the Youth

The tourism consumption behavior of the young people has significant effect on the present social tourism consumption behavior. Intensifying the research on tourism consumption behavior of the youth group helps to explore the hot spot of tourism consumption, and designing specific marketing programs and taping into consumption potential is the key to market development. The research takes the university students in the youth group as an example to analyze the features and difference of tourism consumption behavior and observe tourism consumption marketing of the university students, for providing reference for the expansion of tourism market.

单幅图像局部特征分层模糊挖掘算法仿真

为了能够深入获得图像纹理特征信息,提高后续数据识别精准度。因此,提出了单幅图像局部特征分层模糊挖掘算法。通过直方图均衡化方法,将图像中灰度值集中到对应灰度等级区域。由不均匀分布向均匀分布状态转换,拓展像素的灰度动态范围。分析图像局部特征复杂度与差异度,求出相邻模板灰度等级,得到局部复杂性和差异度矩阵,采用Laplace算法对图像局部特征推荐分类,根据推荐级别分层模糊挖掘所选特征,以此实现对单幅图像的局部特征分层模糊挖掘。通过实验证明,所提算法可准确挖掘出图像特征,不同层级纹理信息都完整,且挖掘时间保持在0.25s内。

基于多特征融合时差网络的带式输送机区域违规行为识别

现有的煤矿井下带式输送机区域违规行为(如攀爬、跨越、倚靠带式输送机等)识别方法对特征提取不充分、难以考虑到行为时间差异,导致违规行为识别准确率不高。针对该问题,基于ResNet50模型,提出了一种基于多特征融合时差网络(MFFTDN)的带式输送机区域违规行为识别方法,将多特征融合和时间差分进行结合,对不同时间段的行为进行多特征融合。首先在原始模型ResNet50的第2和第3阶段引入短期多特征融合(STMFF)模块,将来自多个连续帧的时间和特征拼接在一起,再对融合后的特征进行时间差分计算,即相邻帧的特征差值,以在短期内捕捉局部动作变化。然后在原始模型ResNet50的第4阶段引入长期多特征融合(LTMFF)模块,将来自连续帧的短期多特征拼接在一起,再对相邻时间点的特征进行时间差分计算,以获取行为的长期多特征。最后将融合后的特征进行分类,输出识别结果。实验结果表明:①该方法的平均精度和准确率较原始模型ResNet50分别提高了8.18%和8.47%,说明同时引入STMFF和LTMFF模块能够有效提取到不同时间段的多特征信息。②该方法在自建煤矿井下带式输送机区域违规行为数据集上的准确率为89.62%,平均精度为89.30%,模型的参数量为197.2×10^(6)。③Grad−CAM热力图显示,该方法能够更有效地关注到违规行为的关键区域,精确捕捉到井下带式输送机区域的违规行为。

融合时序Sentinel数据多特征优选的南方丘陵区油茶种植区提取

油茶作为江西省经济林树种之一,也是江西省特色优势产业,准确获取其空间分布在产量估算、生产管理和政策制定等方面具有重要意义。本研究针对南方多云多雨气候导致光学影像不足,以及丘陵山区地形破碎问题,以江西省宜春市袁州区为研究区,采用时序Sentinel系列影像数据和SRTM DEM数据为数据源,构建和优选了光谱特征、植被-水体指数、红边指数、雷达特征、地形特征和纹理特征共125个特征变量,其中,纹理特征采用累计差法(Δf)对比15种不同尺度窗口,计算Sentinel-1和Sentinel-2影像最佳纹理特征。基于ReliefF特征优选算法和随机森林分类算法,设计了8种特征组合方案开展实验,探讨不同特征类型对油茶提取精度的影响。结果表明:利用累计差法计算出的Sentinel-1和Sentinel-2的最佳纹理特征窗口尺寸均为35×35,最佳纹理特征组合为均值(Mean)、方差(Variance)和对比度(Contrast);在光谱特征、植被-水体指数的基础上加入不同特征对油茶进行分类,不同类型特征对油茶提取的有利程度由大到小依次为S2纹理特征、S1纹理特征、地形特征、雷达特征、红边指数,相比于单一光谱和指数特征,纹理特征的加入可大幅度提高分类精度。多特征协同分类结果优于单特征分类结果,基于特征优选的油茶提取精度最高;基于ReliefF算法特征优选后的方案精度最高,总体精度为88.29%,Kappa系数为0.81。本研究利用时序Sentinel系列遥感影像和DEM地形数据,构建了针对多云雨南方丘陵山区的大范围油茶遥感提取方法,可为中国南方丘陵区域油茶资源调查与监测提供参考。

基于可靠度差值特征的自适应判决多元LDPC译码算法

利用变量节点符号可靠度在迭代过程中的分布特征,提出了一种基于可靠度差值特征的自适应判决多元低密度奇偶校验(Low Density Parity Check, LDPC)译码算法。整个迭代过程划分为两个阶段,针对不同阶段节点可靠度的差值特征分别采用不同的判决策略:前期阶段,采用传统的基于最大可靠度的判决策略;后期阶段,根据最大、次大可靠度之间的差值特征,设计自适应的码元符号判决策略。仿真结果表明,所提算法在相当的译码复杂度前提下,能获得0.15~0.4 dB的性能增益。同时,对于列重较小的LDPC码,具有更低的译码错误平层。

基于峰值比拟合匹配的时差式气体超声波流量计

时差式气体超声波流量计的回波信号在气体中传播时能量衰减严重,且存在着不同程度的幅值晃动问题。因此如何在幅值晃动的气体回波信号中确定特征点,以准确测量回波信号渡越时间及其顺、逆流渡越时间差,是当前时差式气体超声波流量计信号处理方法的主要研究热点。该文基于超声回波信号的数学模型,研究构建了一种基于峰值比拟合匹配的信号处理方法,利用拟合指标来筛选符合匹配条件的波形。并且通过实际数据验证了该方法的有效性和优越性。

ERP全景视频VVC帧内编码CU快速划分算法

针对等矩柱状投影(equirectangular projection,ERP)全景视频多功能视频编码(versatile video coding,VVC)帧内编码复杂度过高的问题,提出一种编码单元(coding unit,CU)快速划分算法。根据ERP采样特性,将编码帧分为不同纬度区域。基于不同纬度区域CU四叉树深度的分布特性和相邻CU的相关性,对当前CU的划分模式进行提前终止决策;利用梯度差异评估当前CU纹理特性,跳过冗余的水平或垂直划分模式。针对纹理模糊CU,通过纬度采样权重加权的二次比较,判断是否跳过垂直划分模式;利用二维哈尔小波变换系数评估当前CU子块间的差异,判断是否跳过三叉树划分模式。实验结果表明,在全帧内模式下,与VVC官方测试平台相比,所提算法能节省43.85%的编码时间,码率仅增加0.85%,视频质量没有明显下降。

基于7~10岁儿童防护口罩设计的面部特征

为设计研发更贴合儿童面部的防护口罩,运用三维扫描技术采集130名7~10岁儿童的面部数据,获取了包括面宽、形态面长、耳屏颌下弧长等10项面部指标,探索儿童面部发展规律及脸型分类。运用Pearson相关性分析挖掘各面部指标的发育相关程度,通过独立样本t检验分析面部指标在性别上的差异,使用主成分因子分析提取能反映面部数据的3个主要因子;基于主成分分析结果,结合K-means聚类将儿童脸型分为狭面型(44.9%)、中面型(32.2%)和阔面型(22.9%),提出按脸型分类进行儿童防护口罩设计的理念。

基于注意力机制与特征重建的水下图像增强

针对现有水下图像增强方法缺少对图像中关键目标物体的关注,对图像边缘细节信息的增强效果不佳等问题,提出一种基于注意力机制与特征重建的水下图像增强方法。首先,残差模块联合CBAM(Convolutional Block Attention Module)模块构建超像素图像增强模型,提升水下图像整体质量的同时改善图像中目标物体的清晰度和可视性;然后,设计一种边缘差分模块,使模型关注图像的高频信息,增强图像中目标物体的边缘细节;最后,构建多粒度特征重建模块,重构超像素图像增强模块的隐藏层特征,还原输入图像,进一步优化模型参数。实验结果表明,相比于对比方法,本文模型在SSIM(Structural Similarity)、PSNR(Peak Signal to Noise Ratio)和UIQM(Underwater Image Quality Measures)三个评价指标上均有提升,具备更好的增强性能。尤其在增强水下图像关键目标物体上具有显著的效果。

地名用字异读现象及其规范化

地名作为专有名词的一种,其读音往往能够反映出某一地区的历史语音情况。我国一部分地名用字在读音上存在着异读现象,具体表现为地名的用字具有不同于普通话常用读音的特殊读音。该文结合《现代汉语词典》(第7版)中所收录的地名用字及读音,就我国目前地名用字异读现象进行考察,发现其与文白异读、古音遗存、约定俗成等之间存在着密切的联系。地名用字的异读现象呼吁的是地名定音、定字的规范化,而地名的读音问题受到历史、方言等多方面的影响,其审定工作需要结合历史读音,并尊重当地读音,同时遵循汉语语音的发展趋势,以制定合适的标准并进行专门的研究。