The functions and roles of smart homes are continuously developing due to recent developments in Information and Communication Technology (ICT) and Internet of Things (IoT) [1]. According to global market research firm Gartner, the number of smart home devices is projected to grow to 25 billion units by 2020. According to data from Stratecast, the growth rate of the global smart home market is estimated to exceed $7 billion by 2025 [2]. Smart Home refers to a private home that sends and receives data in real-time. It provides automated and intelligent services through various home devices such as TVs, lights, and refrigerators. These machines are part of the home-based communication system between devices and other environments without human intervention

The context-dependent nature of online aggression makes annotating large collections of data extremely difficult. Previously studied datasets in abusive language detection have been insufficient in size to efficiently train deep learning models. Recently, Hate and Abusive Speech on Twitter, a dataset much greater in size and reliability, has been released. However, this dataset has not been comprehensively studied to its potential. In this paper, we conduct the first comparative study of various learning models on Hate and Abusive Speech on Twitter, and discuss the possibility of using additional features and context data for improvements. Experimental results show that bidirectional GRU networks trained on word-level features, with Latent Topic Clustering modules, is the most accurate model scoring 0.805 F1.

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Hydrogel is in the spotlight as a useful biomaterial in the field of drug delivery and tissue engineering due to its similar biological properties to a native extracellular matrix (ECM). Herein, we proposed a ternary hydrogel of gellan gum (GG), silk fibroin (SF), and chondroitin sulfate (CS) as a biomaterial for cartilage tissue engineering. The hydrogels were fabricated with a facile combination of the physical and chemical crosslinking method. The purpose of this study was to find the proper content of SF and GG for the ternary matrix and confirm the applicability of the hydrogel in vitro and in vivo. The chemical and mechanical properties were measured to confirm the suitability of the hydrogel for cartilage tissue engineering. The biocompatibility of the hydrogels was investigated by analyzing the cell morphology, adhesion, proliferation, migration, and growth of articular chondrocytes-laden hydrogels. The results showed that the higher proportion of GG enhanced the mechanical properties of the hydrogel but the groups with over 0.75% of GG exhibited gelling temperatures over 40 °C, which was a harsh condition for cell encapsulation. The 0.3% GG/3.7% SF/CS and 0.5% GG/3.5% SF/CS hydrogels were chosen for the in vitro study. The cells that were encapsulated in the hydrogels did not show any abnormalities and exhibited low cytotoxicity. The biochemical properties and gene expression of the encapsulated cells exhibited positive cell growth and expression of cartilage-specific ECM and genes in the 0.5% GG/3.5% SF/CS hydrogel. Overall, the study of the GG/SF/CS ternary hydrogel with an appropriate content showed that the combination of GG, SF, and CS can synergistically promote articular cartilage defect repair and has considerable potential for application as a biomaterial in cartilage tissue engineering.

Nickel cobalt sulfide nanoparticles embedded in holey defect graphene hydrogel (HGH) that exhibit highly porous structures and uniform nickel cobalt sulfide nanoparticle sizes are successfully prepared by a facile solvothermal-hydrothermal method. As an electrode material for supercapacitors, the as-prepared NiCo S @HGH shows ultra-high specific capacitances of 1000 F g and 800 F g at 0.5 and 6 A g , respectively, owing to the outstanding electrical conductivity of HGH and high specific capacitance of NiCo S . After 2100 charge/discharge cycles at a current density of 6 A g , 96.6 % of the specific capacitance was retained, signifying the superb durability of NiCo S @HGH. Moreover, remarkable specific capacitance (312.6 F g ) and capacity retention (87 % after 5000 cycles) at 6 A g were displayed by the symmetric solid-state supercapacitor fabricated by using NiCo S @HGH electrodes. These auspicious supercapacitor performances demonstrate that the as-developed solvothermal-hydrothermal approach can be widely used to prepare graphene-coupled binary metal sulfides for high-performance supercapacitor applications.