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Detection of the water content in ethanol has become very important in many fields; however, well-established methods usually require complex strategies and devices. Herein, a simple and non-instrument methodology was developed for the determination of the water content in ethanol. In this work, a CsPbBr3@PVA imaging array sensor was constructed based on the fluorescence on/off mechanism and applied to the detection of water content for the first time. When preparing CsPbBr3@PVA, the photoluminescence of CsPbBr3 was quenched by water in PVA due to the decomposition of CsPbBr3. By employing ethanol with fast volatilization to remove water, the decomposed composition recrystallized and formed luminescent CsPb2Br5. When the water content in ethanol was increased, the degree of the recovered fluorescence drastically reduced. To develop a portable and easily-operated methodology, the pictures of the sensor array were captured using a smartphone and quickly analyzed with ImageJ to read the gray-level values for each sample. The latter displayed a good linear relationship (R2 = 0.995) with the water content increasing from 0% to 7% in ethanol, and a low limit of detection of 0.006% was achieved. Moreover, the sensor array showed advantages like a fast response speed (5 s), strong selectivity and application potential in real samples. This method does not require expensive spectrometers and professional personnel to operate, having the virtues of low cost, fast detection and high sensitivity. [ABSTRACT FROM AUTHOR]

Objective This study aims to overcome the challenges of traditional image inpainting algorithms, wherein texture extension may occur and some incorrect samples may be selected as candidate patches when sample-based algorithms are employed to inpaint the damaged region with complex geometric structure and rich texture. Method An image inpainting method based on weight variation of neighborhood window is proposed. In the method, so-called weight variation is introduced by combining total variation and intrinsic variation in a neighborhood window to modify the priority measure in Criminisi's algorithm. With the proposed method, the ability of identifying geometric and texture information has been improved and geometric information can be urgently inpainted. Meanwhile, matching accuracy has been improved by introducing structure difference operator in combination with pixel color comparison. Result Compared with other recent algorithm, the proposed algorithm can settle the problem of texture expansion and block mismatching and can maintain visual connectivity. Moreover, the peak signal-to-noise ratio (PSNR) of its inpainting result is improved by 2 dB to 3 dB. Conclusion Compared with the original Criminisi's algorithm and its improved algorithms, the proposed algorithm can achieve better result in inpainting the damaged region with both geometric structure and rich texture, as well as in inpainting some ordinary damaged region. Thus, the proposed algorithm has generality. [ABSTRACT FROM AUTHOR]

Objective The original image inpainting algorithm based on partition block of damaged region (IIPBDR) algorithm is not suitable to inpaint a damaged image with large damaged area that contains broken boundaries with large curvature because this algorithm uses a straight path to inpaint the matching broken boundaries in inpainting process. We aim to obtain a smooth curve path between any two matching broken boundaries. This smooth curve path is then used to improve 'IIPBDR algorithm, instead of a straight path. Method The following steps are performed in this study: 1) A smooth-fitting model that satisfies human visual connecting is proposed. 2 ) Least square is employed to search all coefficients of this model by using the prior information of the matching broken boundaries. Then, a smooth curve path between two matching broken boundaries is obtained. 3 ) The smooth curve path, instead of the straight path, is used in IIPBDR algorithm to inpaint two matching broken boundaries. Result "Improved IIPBDR algorithm based on smooth-fitting model" is proposed based on preceding studies. Experimental results indicate that compared with Bertalmio-Sapiro-Caselles-Ballester, Criminisi, IIPB-DR algorithms, the improved method can increase peak signal-to-noise ratio value by approximately 2. 4 dB, and the in-painted images have better visual effects. Thus, the improved method is more competent than the aforementioned algorithms in inpainting a damaged image that contains broken boundaries with large curvature. Conclusion The proposed algorithm can solve the problem, in which IIPBDR algorithm is not suitable to inpaint a damaged image with large damaged area that contains broken boundaries with large curvature. [ABSTRACT FROM AUTHOR]

In order to quickly and accurately extract the emotional feature words, this paper presents the algorithm. Firstly, seed words are selected from emotional words set by artificial selection and assigned their emotional intensity, and emotional intensity of the rest of emotional words set can be calculated by referencing these seed words. Thus, tendentious contribution degree of each feature words can be gotten in word granularity. Secondly, tendentious contribution degree of each feature words is calculated in sentence granularity. Finally, tendentious contribution degree of feature words, which are calculated in word granularity and sentence granularity, are integrated and constructed Chinese emotional feature extraction. Due to the tendency of emotion feature word in the word level and sentence level, the proposed approach improves the accuracy of the final extract emotional words. As long as there is an emotional dictionary and seed word, the experimental results show the proposed approach can achieved desirable precision and recall rate [ABSTRACT FROM AUTHOR]

Detection of the water content in ethanol has become very important in many fields; however, well-established methods usually require complex strategies and devices. Herein, a simple and non-instrument methodology was developed for the determination of the water content in ethanol. In this work, a CsPbBr 3 @PVA imaging array sensor was constructed based on the fluorescence on/off mechanism and applied to the detection of water content for the first time. When preparing CsPbBr 3 @PVA, the photoluminescence of CsPbBr 3 was quenched by water in PVA due to the decomposition of CsPbBr 3 . By employing ethanol with fast volatilization to remove water, the decomposed composition recrystallized and formed luminescent CsPb 2 Br 5 . When the water content in ethanol was increased, the degree of the recovered fluorescence drastically reduced. To develop a portable and easily-operated methodology, the pictures of the sensor array were captured using a smartphone and quickly analyzed with ImageJ to read the gray-level values for each sample. The latter displayed a good linear relationship ( R 2 = 0.995) with the water content increasing from 0% to 7% in ethanol, and a low limit of detection of 0.006% was achieved. Moreover, the sensor array showed advantages like a fast response speed (5 s), strong selectivity and application potential in real samples. This method does not require expensive spectrometers and professional personnel to operate, having the virtues of low cost, fast detection and high sensitivity.