Robust kernelized approach to clustering by incorporating new distance measure

A new data clustering algorithm Density oriented Kernelized version of Fuzzy c-means with new distance metric (DKFCM-new) is proposed. It creates noiseless clusters by identifying and assigning noise points into separate cluster. In an earlier work, Density Based Fuzzy C-Means (DOFCM) algorithm with Euclidean distance metric was proposed which only considered the distance between cluster centroid and data points. In this paper, we tried to improve the performance of DOFCM by incorporating a new distance measure that has also considered the distance variation within a cluster to regularize the distance between a data point and the cluster centroid. This paper presents the kernel version of the method. Experiments are done using two-dimensional synthetic data-sets, standard data-sets referred from previous papers like DUNN data-set, Bensaid data-set and real life high dimensional data-sets like Wisconsin Breast cancer data, Iris data. Proposed method is compared with other kernel methods, various noise resistant methods like PCM, PFCM, CFCM, NC and credal partition based clustering methods like ECM, RECM, CECM. Results shown that proposed algorithm significantly outperforms its earlier version and other competitive algorithms.     

Optimal monolithic configuration for heat integrated ethanol steam reformer

A design concept for optimal design of monolith catalyst is presented through modeling of transport–kinetic interactions in a monolith catalyst. We argue that reactors employing monolithic catalysts should be based on its optimal choice of geometry. In line with that argument, we present a thorough analysis of the geometrical parameters influencing the performance of non-isothermal reactor operation. In this study, an optimal monolith configuration is estimated to be a combination (d_h, t_w) of (0.9 mm, 0.2 mm) for a compact ethanol reformer to produce hydrogen for portable applications where maximum volumetric reactor activity exists. A three-dimensional modeling framework is developed for the resulting optimal monolithic catalyst design that couples the reforming section with a suitable heat source in a recuperative way. As a result, greater ethanol conversion is obtained from the monolith channels near the periphery of the block. The coupling with combustion could predict the formation of cold and hot spots inside the reactor, their nature being dependent on the flow configuration. Further, the effect of altering the feed inlet operating conditions over the variation of ethanol conversion and temperature inside the reactor is also analyzed. The increase in reforming inlet velocity decreases the outlet conversion and shifts the cold spot, forward and deeper in co-flow configuration. The decreasing inlet feed temperature enhances the transfer of heat, eliminating the cold spot.     

Particle size reduction of RDX by sequential application of solvent–antisolvent recrystallization and mechanical methods

ABSTRACT

Solvent–antisolvent recrystallization produced ~8 µm average size RDX particles (UF-RDX) that were subsequently subjected to mechanical methods of ultrasonication and ball-milling to find further achievable reduction in particle size. Long duration ultrasonication for 20 h and 300 rpm ball milling for 4 h of UF-RDX decreased its average particle size to ~2 µm. RDX produced by all the three processes (solvent–antisolvent recrystallization, ultrasonication and ball-milling) was similar to coarser RDX in structure and thermal decomposition behavior. However, UF-RDX produced by solvent–antisolvent recrystallization was significantly less impact sensitive than that produced by ball-milling and ultrasonication. The issues of residual solvent and the metal contamination during RDX processing were addressed by process parameter optimization. Solvent–antisolvent recrystallization and mechanical methods even when used sequentially could not bring average particle size of RDX to nano-scale.     

Cuckoo Search Based Optimization of Multiuser Cognitive Radio System Under the Effect of Shadowing

Shadow fading is one of the least investigated factors of received signal power in a typical wireless communication system. Variations in the received power caused by shadowing events can impose some serious changes in the communication. This paper, proposes a new multiuser cognitive radio system in shadowing environment and its design optimization using cuckoo search algorithm. The transmission parameters of multiple secondary users in the purposed CR model are considered on the basis of IEEE 802.22 WRAN standard. An attempt to optimize these parameters in shadowing environment to achieve multiple objectives for desired quality of service have been made using a relatively newer and simpler cuckoo search algorithm. The optimization results have been compared with another efficient biogeography based optimization technique and the traditional simulated annealing.     

A Conditionally Fluorescent Peptide Reporter of Secondary Structure Modulation

Proteins containing intrinsic disorder often form secondary structure upon interaction with a binding partner. Modulating such structures presents an approach for manipulating the resultant functional outcomes. Translational repressor protein 4E-BP1 is an example of an intrinsically disordered protein that forms an α-helix upon binding to its protein ligand, eIF4E. Current biophysical methods for analyzing binding-induced structural changes are low-throughput, require large amounts of sample, or are extremely sensitive to signal interference by the ligand itself. Herein, we describe the discovery and development of a conditionally fluorescent 4E-BP1 peptide that reports structural changes of its helix in high-throughput format. This reporter peptide is based on conditional quenching of fluorescein by thioamides. In this case, fluorescence signal increases as the peptide becomes more ordered. Conversely, destabilization of the α-helix results in decreased fluorescence signal. The low concentration and low volume of peptide required make this approach amenable for high-throughput screening to discover ligands that alter peptide secondary structure.     

On Effects of Frequency Offset on Simulink Model of OFDM

Wireless Personal Communications - OFDM is a multicarrier transmission technique, widely preferred due to advantages like high data rate, less bandwidth consumption and channel robustness. IEEE...     

Deep Convolutional Neural Network for Graphics Forgery Detection in Video

Wireless Personal Communications - Doctored video generation with easily accessible editing software has proved to be a major problem in maintaining its authenticity. Nowadays, deep neural networks...     

MIMO Channel Capacity and Configuration Selection for Switched Parasitic Antennas

Multiple-input multiple-output (MIMO) systems offer significant enhancements in terms of their data rate and channel capacity compared to traditional systems. However, correlation degrades the system performance and imposes practical limits on the number of antennas that can be incorporated into portable wireless devices. The use of switched parasitic antennas (SPAs) is a possible solution, especially where it is difficult to obtain sufficient signal decorrelation by conventional means. The covariance matrix represents the correlation present in the propagation channel, and has significant impact on the MIMO channel capacity. The results of this work demonstrate a significant improvement in the MIMO channel capacity by using SPA with the knowledge of the covariance matrix for all pattern configurations. By employing the “water-pouring algorithm” to modify the covariance matrix, the channel capacity is significantly improved compared to traditional systems, which spread transmit power uniformly across all the antennas. A condition number is also proposed as a selection metric to select the optimal pattern configuration for MIMO-SPAs.     

Relationship between physicochemical and functional properties of amaranth (Amaranthus hypochondriacus) protein isolates

Protein isolates from six amaranth lines/cultivars (APIs) were evaluated to study their physicochemical (hunter colour, protein content and zeta potential), structural (thermal and conformational) and functional (emulsification, foaming, water and fat absorption) properties. APIs had protein content, whiteness index and gel temperature in range of 79.4–85.4%, 41.17–54.26 and 87.8–91.8 °C, respectively. The Fourier‐transform infrared spectra of APIs revealed α‐helix, β‐sheets and random coil conformations in the secondary structure. APIs with higher relative proportion of β‐sheets had higher Differential Scanning Calorimeter denaturation temperature and gel temperature. Minimum protein solubility (PS) was observed at pH 5.0, indicating isoelectric point (pI) of amaranth proteins. The PS, emulsifying activity index (EAI), emulsifying stability index (ESI), foaming capacity (FC) and foam stability (FS) of APIs at neutral pH were related to their zeta potential (ζ). The emulsifying and foaming properties were also determined at different pHs (between 2.0 and 9.0). The EAI‐pH profile of APIs confirmed close relationship between the emulsifying ability and PS.