K-nearest neighbor finding using MaxNearestDist

Similarity searching often reduces to finding the k nearest neighbors to a query object. Finding the k nearest neighbors is achieved by applying either a depth- first or a best-first algorithm to the search hierarchy containing the data. These algorithms are generally applicable to any index based on hierarchical clustering. The idea is that the data is partitioned into clusters which are aggregated to form other clusters, with the total aggregation being represented as a tree. These algorithms have traditionally used a lower bound corresponding to the minimum distance at which a nearest neighbor can be found (termed MinDist) to prune the search process by avoiding the processing of some of the clusters as well as individual objects when they can be shown to be farther from the query object q than all of the current k nearest neighbors of q. An alternative pruning technique that uses an upper bound corresponding to the maximum possible distance at which a nearest neighbor is guaranteed to be found (termed MaxNearestDist) is described. The MaxNearestDist upper bound is adapted to enable its use for finding the k nearest neighbors instead of just the nearest neighbor (i.e., k=1) as in its previous uses. Both the depth-first and best-first k-nearest neighbor algorithms are modified to use MaxNearestDist, which is shown to enhance both algorithms by overcoming their shortcomings. In particular, for the depth-first algorithm, the number of clusters in the search hierarchy that must be examined is not increased thereby potentially lowering its execution time, while for the best-first algorithm, the number of clusters in the search hierarchy that must be retained in the priority queue used to control the ordering of processing of the clusters is also not increased, thereby potentially lowering its storage requirements.     

Driers based on tall oil—A review

The metal soaps of tall oil were introduced as paint driers during World War II. Paint industry experience reveals that these oxidation-polymerization catalysts are generally equivalent in performance to naphthenate driers. Physical properties, manufacturing procedures and application of tallate driers in typical paint systems are reviewed. Presented at the AOCS Meeting, New Orleans, 1964.     

Automatic Eyewitness Identification During Disasters by Forming a Feature-Word Dictionary

Social media provide digitally interactional technologies to facilitate information sharing and exchanging individuals. Precisely, in case of disasters, a massive corpus is placed on platforms such as Twitter. Eyewitness accounts can benefit humanitarian organizations and agencies, but identifying the eyewitness Tweets related to the disaster from millions of Tweets is difficult. Different approaches have been developed to address this kind of problem. The recent state-of-the-art system was based on a manually created dictionary and this approach was further refined by introducing linguistic rules. However, these approaches suffer from limitations as they are dataset-dependent and not scalable. In this paper, we proposed a method to identify eyewitnesses from Twitter. To experiment, we utilized 13 features discovered by the pioneer of this domain and can classify the tweets to determine the eyewitness. Considering each feature, a dictionary of words was created with the Word Dictionary Maker algorithm, which is the crucial contribution of this research. This algorithm inputs some terms relevant to a specific feature for its initialization and then creates the words dictionary. Further, keyword matching for each feature in tweets is performed. If a feature exists in a tweet, it is termed as 1; otherwise, 0. Similarly, for 13 features, we created a file that reflects features in each tweet. To classify the tweets based on features, Naïve Bayes, Random Forest, and Neural Network were utilized. The approach was implemented on different disasters like earthquakes, floods, hurricanes, and Forest fires. The results were compared with the state-of-the-art linguistic rule-based system with 0.81 F-measure values. At the same time, the proposed approach gained a 0.88 value of F-measure. The results were comparable as the proposed approach is not dataset-dependent. Therefore, it can be used for the identification of eyewitness accounts.     

Novel type-2 fuzzy logic technique for handover problems in a heterogeneous network

Small cells are deployed in the long-term evolution—advanced (LTE-A) data standard to satisfy rapidly increasing data rates at hotspots and enhance coverage in buildings. Small cells are low-cost, low-power nodes with limited coverage. With small cells, the more sophisticated network architecture increases the difficulty of dealing with mobility management. The conflict between traffic demands and network resources is also very important, and the signalling overhead (ping-pong) in the handover procedure should be considered in mobility management. With the aim of solving these issues, efficient handover algorithms are being used to enhance mobility management in small-cell networks. This article presents a new handover optimization algorithm for LTE-A networks based on fuzzy logic. It consists of selecting the optimum handover margins for both macro and small cells which are required for the handover process to optimize the performance metrics. The proposed handover optimization technique is evaluated and compared with two well-known handover algorithms. The results show that it achieves a minimum call drop rate and has a minimum number of handovers.     

Electrochemical Performance of Na3V2(PO4)2F3 Electrode Material in a Symmetric Cell

A NASICON-based Na₃V₂(PO₄)₂F₃ (NVPF) cathode material is reported herein as a potential symmetric cell electrode material. The symmetric cell was active from 0 to 3.5 V and showed a capacity of 85 mAh/g at 0.1 C. With cycling, the NVPF symmetric cell showed a very long and stable cycle life, having a capacity retention of 61% after 1000 cycles at 1 C. The diffusion coefficient calculated from cyclic voltammetry (CV) and the galvanostatic intermittent titration technique (GITT) was found to be ~10⁻⁹–10⁻¹¹, suggesting a smooth diffusion of Na⁺ in the NVPF symmetric cell. The electrochemical impedance spectroscopy (EIS) carried out during cycling showed increases in bulk resistance, solid electrolyte interphase (SEI) resistance, and charge transfer resistance with the number of cycles, explaining the origin of capacity fade in the NVPF symmetric cell. Finally, the postmortem analysis of the symmetric cell after 1000 cycles at a 1 C rate indicated that the intercalation/de-intercalation of sodium into/from the host structure occurred without any major structural destabilization in both the cathode and anode. However, there was slight distortion in the cathode structure observed, which resulted in capacity loss of the symmetric cell. The promising electrochemical performance of NVPF in the symmetric cell makes it attractive for developing long-life and cost-effective batteries.     

Sublimation Transfer Printing of Cotton and Wool Fabrics

An attempt has been made to transfer print cotton and wool fabrics with disperse dyes through the use of a thin polymer layer (polyethylene film) placed between the transfer paper and the fabric. This would result in simultaneous transfer of the coloured design to the polyethylene film and bonding of the film to the fabric. Among the factors studied were the conditions of transfer printing as well as the weight and thickness of the polyethylene film. The produced prints were evaluated for colour strength, fastness properties as well as mechanical properties.     

Cluster‐based data dissemination,cluster head formation under sparse,and dense traffic conditions for vehicular ad hoc networks

Information and communication technologies have changed the way of operations in all fields. These technologies also have adopted for wireless communication and provide low cost and convenient solutions. Vehicular ad hoc networks are envisioned with their special and unique intercommunication systems to provide safety in intelligent transportation systems and support large‐size networks. Due to dense and sparse traffic conditions, routing is always a challenging task to establish reliable and effective communication among vehicle nodes in the highly transportable environment. Several types of routing protocols have been proposed to handle high mobility and dynamic topologies including topology‐based routing, position and geocast routing, and cluster‐based routing protocols. Cluster‐based routing is one of the feasible solutions for vehicular networks due to its manageable and more viable nature. In cluster‐based protocols, the network is divided into many clusters and each cluster selects a cluster head for data dissemination. In this study, we investigate the current routing challenges and trend of cluster‐based routing protocols. In addition, we also proposed a Cluster‐based Routing for Sparse and Dense Networks to handle dynamic topologies, the high‐mobility of vehicle nodes. Simulation results show a significant performance improvement of the proposed protocol.     

The virtual museum: Interactive 3D navigation of a multimedia database

The Virtual Museum is an interactive, electronic museum where users can move from room to room, and select any exhibit in a room for more detailed examination. The exhibits in the museum are educational, encompassing topics such as medicine, plant growth, the environment, and space. To facilitate interaction with the museum, a new method for navigating through a prerendered 3D space, and interacting with objects in that space has been developed, called ‘virtual navigation’. Virtual navigation employs real-time video decompression for the display of, and interaction with, high-quality computer animation. In addition, a representation for 3D objects in animated sequences is used which permits pixel-accurate, frame-accurate object picking, so that a viewer can select any 3D object to trigger movement within the 3D space, to examine an exhibit in animated form, or to play a digital movie or soundtrack. The use of precomputed video permits 3D navigation in a realistic-looking space, without requiring special-purpose graphics hardware.     

Graphitic Carbon Nitride Decorated with Iron Oxide Nanoparticles as a Novel High-Performance Biomimetic Electrochemical Sensing Platform for Paracetamol Detection

Design and development of new generation smart sensors for medical applications have gained considerable interest of research community in the recent past. In this work, we propose the fabrication of highly sensitive paracetamol sensors-based iron oxide nanoparticles intercalated with graphitic carbon nitride (g-C₃N₄) (GCN) via insitu chemical synthesis. Structural features of the composites were analyzed through SEM, EDX, XRD, FTIR, and UV-Visible spectroscopic techniques. Presence of iron oxide nanoparticles in GCN, significantly improved the conductivity bare GCN from 16 to 125 S cm^?1 due to extended π–π conjugation and large surface area in the composite system. The GCN-Iron oxide (GCN-FO) nanocomposite has been employed as an electrochemical sensing platform for non-enzymatic detection of paracetamol. The electrochemical studies and cyclic voltammetry (CV) results shows that the GCN-FO composite exhibit superior electrochemical properties due to their lower values of the oxidation and reduction potentials. Electrochemical impedance spectroscopy (EIS) studies indicate decreased charge-transfer resistance for iron oxide doped GCN composite in compare to base GCN. The improved electrochemical sensing performance of modified GCN-FO composite electrode is attributed to the formation heterojunctions between iron oxide nanoparticles and GCN. The modified GCN-FO electrodes were employed for non-enzymatic electrochemical detection of PR. The GCN-FO composite electrode shows excellent sensitivity towards PR with a LOD 0.3 μM. Furthermore, the modified GCN-FO electrodes show excellent reproducibility, selectivity, stability and anti-interference performance. Due to its low-cost fabrication, superior electrochemical sensing performance, these modified GCN-FO electrodes could be a promising material for the detection of paracetamol at low concentrations.