Development of an Electrogenerated Chemiluminescence Biosensor using Carboxylic acid-functionalized MWCNT and Au Nanoparticles

A COOH-F-MWCNT-Nafion-Ru(bpy)32+-Au-ADH electrogenerated chemiluminescence (ECL) electrode using COOH-functionalized MWCNT (COOH-F-MWCNT) and Au nanoparticles synthesized by the radiation method was fabricated for ethanol sensing. A higher sensing efficiency for ethanol for the ECL biosensor prepared by PAAc-g-MWCNT was measured compared to that of the ECL biosensor prepared by PMAc-g-MWCNT, and purified MWCNT. Experimental parameters affecting ethanol detection were also examined in terms of pH and the content of PAAc-g-MWCNT in Nafion. Little interference of other compounds was observed for the assay of ethanol. Results suggest this ECL biosensor could be applied for ethanol detection in real samples

A Distributed Signature Detection Method for Detecting Intrusions in Sensor Systems

Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on theWu–Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors

A Distributed Signature Detection Method for Detecting Intrusions in Sensor Systems

Sensor nodes in wireless sensor networks are easily exposed to open and unprotected regions. A security solution is strongly recommended to prevent networks against malicious attacks. Although many intrusion detection systems have been developed, most systems are difficult to implement for the sensor nodes owing to limited computation resources. To address this problem, we develop a novel distributed network intrusion detection system based on theWu–Manber algorithm. In the proposed system, the algorithm is divided into two steps; the first step is dedicated to a sensor node, and the second step is assigned to a base station. In addition, the first step is modified to achieve efficient performance under limited computation resources. We conduct evaluations with random string sets and actual intrusion signatures to show the performance improvement of the proposed method. The proposed method achieves a speedup factor of 25.96 and reduces 43.94% of packet transmissions to the base station compared with the previously proposed method. The system achieves efficient utilization of the sensor nodes and provides a structural basis of cooperative systems among the sensors

Balanced Column-Wise Block Pruning for Maximizing GPU Parallelism

Pruning has been an effective solution to reduce the number of computations and the memory requirement in deep learning. The pruning unit plays an important role in exploiting the GPU resources efficiently. The filter is proposed as a simple pruning unit of structured pruning. However, since the filter is quite large as pruning unit, the accuracy drop is considerable with a high pruning ratio. GPU rearranges the weight and input tensors into tiles (blocks) for efficient computation. To fully utilize GPU resources, this tile structure should be considered, which is the goal of block pruning. However, previous block pruning prunes both row vectors and column vectors. Pruning of row vectors in a tile corresponds to filter pruning, and it also interferes with column-wise block pruning of the following layer. In contrast, column vectors are much smaller than row vectors and can achieve lower accuracy drop. Additionally, if the pruning ratio for each tile is different, GPU utilization can be limited by imbalanced workloads by irregular-sized blocks. The same pruning ratio for the weight tiles processed in parallel enables the actual inference process to fully utilize the resources without idle time. This paper proposes balanced column-wise block pruning, named BCBP, to satisfy two conditions: the column-wise minimal size of the pruning unit and balanced workloads. We demonstrate that BCBP is superior to previous pruning methods through comprehensive experiments

One-pot hydrothermal preparation of hierarchical manganese oxide nanorods for high-performance symmetric supercapacitors

An eco-friendly, new, and controllable approach for the preparation of manganese oxide (α-MnO2) nanorods has been introduced using hydrothermal reaction for supercapacitor application. The in-depth crystal structure analysis of α-MnO2 is analyzed by X-ray Rietveld refinement by using FullProf program with the help of pseudo-Voigt profile function. The developed α-MnO2 electrode attains a remarkable capacitance of 577.7 F/g recorded at a current density value of 1 A/g with an excellent cycle life when is used for 10,000 repeated cycles due to the porous nanorod-morphology assisting the ease penetration of electrolyte ions into the electroactive sites. The diffusive and capacitive contributions of the electrode have been estimated by considering standard numerical packages in Python. After successfully assembling the aqueous symmetric supercapacitor (SSC) cell by utilizing the as-prepared α-MnO2, an excellent capacitance of 163.5 F/g and energy density of 58.1 Wh/kg at the constant current density of 0.5 A/g are obtained with an expanded potential frame of 1.6 V. Moreover, the cell has exceptionally withstood up to 10,000 cycles with an ultimate capacitance retention of 94.1% including the ability to light an LED for 18 s. Such findings recommend the developed α-MnO2 electrode to be a highly felicitous electrode for the field of energy storage