• Advances in nano research
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• v.2 no.2
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• pp.111-119
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• 2014

The chemical synthesis of anisotropic defective polyaniline/Ag composite (PANI/Ag) is explored using silver nitrate ($AgNO_3$) as the precursor material. This study provides a simple method for the formation of PANI/Ag nanocomposites at two different aniline concentrations $5{\mu}l$ (PANC5) and $10{\mu}l$ (PANC10). The composite PANC5 exhibits UV-Visible absorption peaks at 436 nm and 670 nm whereas, PANC10 exhibits absorption peaks at 446 nm and 697 nm. This shift is caused by the strong interaction between polyaniline and silver. The characterized FTIR peaks observed at around $3410cm^{-1}$ (PANC5) and $3420cm^{-1}$ (PANC10) was due to the N-H stretching vibrations. The appearance of a broad band instead of a sharp peak can be attributed due to the presence of a high concentration of N-H groups in the nanocomposite. The TEM images show that the sample contains defective spherical, truncated triangular and rod shaped particles. The results showed that the PANI/Ag nanocomposites are composed of nano-sized particles of 43-53 nm that contain Ag domains of 33-37 nm with polymer thickness 5.7-11.2 nm at two different aniline concentrations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1317-1341
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• 2021

Nowadays, the Internet of Things (IoT) is adopted to enable effective and smooth communication among different networks. In some specific application, the Wireless Sensor Networks (WSN) are used in IoT to gather peculiar data without the interaction of human. The WSNs are self-organizing in nature, so it mostly prefer multi-hop data forwarding. Thus to achieve better communication, a cross-layer routing strategy is preferred. In the cross-layer routing strategy, the routing processed through three layers such as transport, data link, and physical layer. Even though effective communication achieved via a cross-layer routing strategy, energy is another constraint in WSN assisted IoT. Cluster-based communication is one of the most used strategies for effectively preserving energy in WSN routing. This paper proposes a Bio-inspired cross-layer routing (BiHCLR) protocol to achieve effective and energy preserving routing in WSN assisted IoT. Initially, the deployed sensor nodes are arranged in the form of a grid as per the grid-based routing strategy. Then to enable energy preservation in BiHCLR, the fuzzy logic approach is executed to select the Cluster Head (CH) for every cell of the grid. Then a hybrid bio-inspired algorithm is used to select the routing path. The hybrid algorithm combines moth search and Salp Swarm optimization techniques. The performance of the proposed BiHCLR is evaluated based on the Quality of Service (QoS) analysis in terms of Packet loss, error bit rate, transmission delay, lifetime of network, buffer occupancy and throughput. Then these performances are validated based on comparison with conventional routing strategies like Fuzzy-rule-based Energy Efficient Clustering and Immune-Inspired Routing (FEEC-IIR), Neuro-Fuzzy- Emperor Penguin Optimization (NF-EPO), Fuzzy Reinforcement Learning-based Data Gathering (FRLDG) and Hierarchical Energy Efficient Data gathering (HEED). Ultimately the performance of the proposed BiHCLR outperforms all other conventional techniques.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.110-119
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• 2021

The Coronavirus or COVID-19 is contagiousness virus that infected almost every single part of the world. This pandemic forced a major country did lockdown and stay at a home policy to reduce virus spread and the number of victims. Interactions between humans and robots form a popular subject of research worldwide. In medical robotics, the primary challenge is to implement natural interactions between robots and human users. Human communication consists of dynamic processes that involve joint attention and attracting each other. Coordinated care involves sharing among agents of behaviours, events, interests, and contexts in the world from time to time. The robotics arm is an expensive and complicated system because robot simulators are widely used instead of for rehabilitation purposes in medicine. Interaction in natural ways is necessary for disabled persons to work with the robot simulator. This article proposes a low-cost rehabilitation system by building an arm gesture tracking system based on a depth camera that can capture and interpret human gestures and use them as interactive commands for a robot simulator to perform specific tasks on the 3D block. The results show that the proposed system can help patients control the rotation and movement of the 3D arm using their hands. The pilot testing with healthy subjects yielded encouraging results. They could synchronize their actions with a 3D robotic arm to perform several repetitive tasks and exerting 19920 J of energy (kg.m².S^-2). The average of consumed energy mentioned before is in medium scale. Therefore, we relate this energy with rehabilitation performance as an initial stage and can be improved further with extra repetitive exercise to speed up the recovery process.

• Smart Structures and Systems
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• v.8 no.1
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• pp.1-15
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• 2011

Cerebral aneurysm is common lesion among adult population. Current methods for treating the disease have several limitations. Inspired by fern leaves, we have developed a new stent, called leaf stent, which can provide a tailored coverage at the neck of an aneurysm and thus prevent the blood from entering the aneurysm. It alone can be used to treat the cerebral aneurysm and therefore overcomes problems existing in current treating methods. The paper focuses on the numerical simulation of the leaf stents. The mechanical behaviour of the stent in various designs has been investigated using the finite element method. It has been found that certain designs provide adequate radial force and have excellent longitudinal flexibility. The performance of certain leaf stents is comparable and even superior to those of the commercially available cerebral stents such as the Neuroform stent and the Enterprise stent, commonly used for stent assisted coiling, while at the same time, providing sufficient coverage to isolate the aneurysm without using coils.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.9-20
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• 2014

Making good predictions about the outcome of one's actions would seem to be essential in the context of social interaction and decision-making. This paper proposes a computational model for learning articulated motion patterns for action recognition, which mimics biological-inspired visual perception processing of human brain. Developed model of cortical architecture for the unsupervised learning of motion sequence, builds upon neurophysiological knowledge about the cortical sites such as IT, MT, STS and specific neuronal representation which contribute to articulated motion perception. Experiments show how the model automatically selects significant motion patterns as well as meaningful static snapshot categories from continuous video input. Such key poses correspond to articulated postures which are utilized in probing the trained network to impose implied motion perception from static views. We also present how sequence selective representations are learned in STS by fusing snapshot and motion input and how learned feedback connections enable making predictions about future input sequence. Network simulations demonstrate the computational capacity of the proposed model for motion recognition.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.481-485
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• 2014

In service robots, a number of human movements are analyzed using a variety of sensors. Vibration signals from walking movements of a human provide useful information about the distance and the movement direction of the human. In this paper, we measure the intensity of vibrations and detect both human walking pace and direction. In our experiments, vibration signals detected by microphone sensors provide good estimation of the distance and direction of a human movement. This can be applied to HRI (Human-Robot Interaction) technology.

• Bulletin of the Korean Chemical Society
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• v.32 no.7
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• pp.2217-2221
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• 2011

We investigated the selective deoxyribonucleic acid (DNA) adsorption on layered double hydroxide (LDH) nanoparticles via studying the interaction between positively charged LDH nanoparticle as adsorbent and negatively charged adsorbates such as methyl orange (MO), fluorescein (FL), and DNA strands. The size controlled LDH $(Mg_{0.78}Al_{0.22}(OH)_2(CO_3)_{0.11}{\cdot}mH_2O)$ was prepared by conventional coprecipitation method, followed by the hydrothermal treatment. According to the adsorption isotherms, the adsorbed amounts of MO and FL were similar, however, that of DNA were much larger. The adsorption behaviors were well fitted to Freundlich adsorption model. The concentration dependent adsorption behavior on LDH surface was described in order to verify the selective DNA separation ability. The result showed that the LDH has advantages in selective adsorption of DNA competing with single molecular anions.