Study of photopolymers. XXXIII. Chemical modification of poly(epichlorohydrin) and its application as photosensitive polymers

High Tg. polymers containing both vinyloxy moiety and pendant phthalyl, 2-thiobenzoxazole or 2-thiobenzothiazole groups were synthesized by elimination reaction of poly(epichlorohydrin) with potassium hydroxide followed by substitution reaction of the obtained polymer with potassium phthalimide, potassium 2-thiobenzoxazole or potassium 2-thiobenzothiazole using tetrabutylammonium bromide as a phase transfer catalyst. The polymers containing vinyloxy moiety and pendant phthalyl or 2-thiobenzothiazole groups showed high photochemical reactivity and excellent practical photosensitivity as a positive type resist with photo-generated cationic catalyst such as 2,5-dibutoxy-4-morpholinobenzene diazonium hexafluoroanthimonate. On the other hand, the polymers had high practical photosensitivity and good resolution as a negative type resist with 2,6-di-(4′-azobenzal)-4-methylcyclohexanone as a photosensitizer.     

One-pot conversion of allyl alcohols into selenochroman derivatives

A one-pot conversion of allyl alcohols into selenochroman derivatives was achieved by treatment with a phenyl trimethylsilyl selenide (TMSSePh)-AIBr3 reagent system.     

Introduction of large sample volumes in capillary supercritical fluid chromatography

A splitless injection method using make-up flow was developed for SFC. Dilution of sample solvent with carbon dioxide mobile phase was very effective for focusing the solutes onto the column. Injection of a 4.5-μl sample volume on a 100-μm i.d. capillary column became possible.     

Reduced lateral leakage losses of TM-like modes in silicon-on-insulator ridge waveguides

We numerically investigate the lateral leakage loss behavior for TM-like modes in silicon-on-insulator ridge waveguides. In order to improve the leakage loss properties, we propose a novel ridge waveguide structure where a dimple is introduced at the ridge center. It is shown that the ridge waveguide with a dimple is both low loss and fabrication tolerant. This behavior is predicted by not only an accurate finite-element-based analysis but also a simple, phenomenological effective-index-based analysis.     

Classification of Indoor Human Fall Events Using Deep Learning

Human fall identification can play a significant role in generating sensor based alarm systems, assisting physical therapists not only to reduce after fall effects but also to save human lives. Usually, elderly people suffer from various kinds of diseases and fall action is a very frequently occurring circumstance at this time for them. In this regard, this paper represents an architecture to classify fall events from others indoor natural activities of human beings. Video frame generator is applied to extract frame from video clips. Initially, a two dimensional convolutional neural network (2DCNN) model is proposed to extract features from video frames. Afterward, gated recurrent unit (GRU) network finds the temporal dependency of human movement. Binary cross-entropy loss function is calculated to update the attributes of the network like weights, learning rate to minimize the losses. Finally, sigmoid classifier is used for binary classification to detect human fall events. Experimental result shows that the proposed model obtains an accuracy of 99%, which outperforms other state-of-the-art models.