Feature selection for unsupervised learning

In this paper, we present a methodology for identifying best features from a large feature space. In high dimensional feature space nearest neighbor search is meaningless. In this feature space we see quality and performance issue with nearest neighbor search. Many data mining algorithms use nearest neighbor search. So instead of doing nearest neighbor search using all the features we need to select relevant features. We propose feature selection using Non-negative Matrix Factorization(NMF) and its application to nearest neighbor search. Recent clustering algorithm based on Locally Consistent Concept Factorization(LCCF) shows better quality of document clustering by using local geometrical and discriminating structure of the data. By using our feature selection method we have shown further improvement of performance in the clustering.

Unsupervised feature selection for outlier detection in categorical data using mutual information

Outlier detection in high dimensional categorical data has been a problem of much interest due to the extensive use of qualitative features for describing the data across various application areas. Though there exist various established methods for dealing with the dimensionality aspect through feature selection on numerical data, the categorical domain is actively being explored. As outlier detection is generally considered as an unsupervised learning problem due to lack of knowledge about the nature of various types of outliers, the related feature selection task also needs to be handled in a similar manner. This motivates the need to develop an unsupervised feature selection algorithm for efficient detection of outliers in categorical data. Addressing this aspect, we propose a novel feature selection algorithm based on the mutual information measure and the entropy computation. The redundancy among the features is characterized using the mutual information measure for identifying a suitable feature subset with less redundancy. The performance of the proposed algorithm in comparison with the information gain based feature selection shows its effectiveness for outlier detection. The efficacy of the proposed algorithm is demonstrated on various high-dimensional benchmark data sets employing two existing outlier detection methods.

Assessing future rainfall projections using multiple GCMs and a multi-site stochastic downscaling model

Impact of global warming on daily rainfall is examined using atmospheric variables from five General Circulation Models (GCMs) and a stochastic downscaling model. Daily rainfall at eleven raingauges over Malaprabha catchment of India and National Center for Environmental Prediction (NCEP) reanalysis data at grid points over the catchment for a continuous time period 1971-2000 (current climate) are used to calibrate the downscaling model. The downscaled rainfall simulations obtained using GCM atmospheric variables corresponding to the IPCC-SRES (Intergovernmental Panel for Climate Change - Special Report on Emission Scenarios) A2 emission scenario for the same period are used to validate the results. Following this, future downscaled rainfall projections are constructed and examined for two 20 year time slices viz. 2055 (i.e. 2046-2065) and 2090 (i.e. 2081-2100). The model results show reasonable skill in simulating the rainfall over the study region for the current climate. The downscaled rainfall projections indicate no significant changes in the rainfall regime in this catchment in the future. More specifically, 2% decrease by 2055 and 5% decrease by 2090 in monsoon (HAS) rainfall compared to the current climate (1971-2000) under global warming conditions are noticed. Also, pre-monsoon (JFMAM) and post-monsoon (OND) rainfall is projected to increase respectively, by 2% in 2055 and 6% in 2090 and, 2% in 2055 and 12% in 2090, over the region. On annual basis slight decreases of 1% and 2% are noted for 2055 and 2090, respectively.

Distinctive contributions of the ribosomal P-site elements m(2)G966, m(5)C967 and the C-terminal tail of the S9 protein in the fidelity of initiation of translation in Escherichia coli

The accuracy of pairing of the anticodon of the initiator tRNA (tRNA(fMet)) and the initiation codon of an mRNA, in the ribosomal P-site, is crucial for determining the translational reading frame. However, a direct role of any ribosomal element(s) in scrutinizing this pairing is unknown. The P-site elements, m(2)G966 (methylated by RsmD), m(5)C967 (methylated by RsmB) and the C-terminal tail of the protein S9 lie in the vicinity of tRNA(fMet). We investigated the role of these elements in initiation from various codons, namely, AUG, GUG, UUG, CUG, AUA, AUU, AUC and ACG with tRNA(CAU)(fmet) (tRNA(fMet) with CAU anticodon); CAC and CAU with tRNA(GUG)(fme); UAG with tRNA(GAU)(fMet) using in vivo and computational methods. Although RsmB deficiency did not impact initiation from most codons, RsmD deficiency increased initiation from AUA, CAC and CAU (2- to 3.6-fold). Deletion of the S9 C-terminal tail resulted in poorer initiation from UUG, GUG and CUG, but in increased initiation from CAC, CAU and UAC codons (up to 4-fold). Also, the S9 tail suppressed initiation with tRNA(CAU)(fMet)lacking the 3GC base pairs in the anticodon stem. These observations suggest distinctive roles of 966/967 methylations and the S9 tail in initiation.

Implementation study of relay selection schemes for energy harvesting WSNs

We propose energy harvesting technologies and cooperative relaying techniques to power the devices and improve reliability. We propose schemes to (a) maximize the packet reception ratio (PRR) by cooperation and (b) minimize the average packet delay (APD) by cooperation amongst nodes. Our key result and insight from the testbed implementation is about total data transmitted by each relay. A greedy policy that relays more data under a good harvesting condition turns out to be a sub optimal policy. This is because, energy replenishment is a slow process. The optimal scheme offers a low APD and also improves PRR.

Estimation of design basis earthquake using region-specific M-max, for the NPP site at Kalpakkam, Tamil Nadu, India

The objective of the paper is to estimate Safe Shutdown Earthquake (SSE) and Operating/Design Basis Earthquake (OBE/DBE) for the Nuclear Power Plant (NPP) site located at Kalpakkam, Tamil Nadu, India. The NPP is located at 12.558 degrees N, 80.175 degrees E and a 500 km circular area around NPP site is considered as `seismic study area' based on past regional earthquake damage distribution. The geology, seismicity and seismotectonics of the study area are studied and the seismotectonic map is prepared showing the seismic sources and the past earthquakes. Earthquake data gathered from many literatures are homogenized and declustered to form a complete earthquake catalogue for the seismic study area. The conventional maximum magnitude of each source is estimated considering the maximum observed magnitude (M-max(obs)) and/or the addition of 0.3 to 0.5 to M-max(obs). In this study maximum earthquake magnitude has been estimated by establishing a region's rupture character based on source length and associated M-max(obs). A final source-specific M-max is selected from the three M-max values by following the logical criteria. To estimate hazard at the NPP site, ten Ground-Motion Prediction Equations (GMPEs) valid for the study area are considered. These GMPEs are ranked based on Log-Likelihood (LLH) values. Top five GMPEs are considered to estimate the peak ground acceleration (PGA) for the site. Maximum PGA is obtained from three faults and named as vulnerable sources to decide the magnitudes of OBE and SSE. The average and normalized site specific response spectrum is prepared considering three vulnerable sources and further used to establish site-specific design spectrum at NPP site.

Optimal design of timer-based, distributed selection with unknown number of nodes

The timer-based selection scheme is a popular, simple, and distributed scheme that is used to select the best node from a set of available nodes. In it, each node sets a timer as a function of a local preference number called a metric, and transmits a packet when its timer expires. The scheme ensures that the timer of the best node, which has the highest metric, expires first. However, it fails to select the best node if another node transmits a packet within Delta s of the transmission by the best node. We derive the optimal timer mapping that maximizes the average success probability for the practical scenario in which the number of nodes in the system is unknown but only its probability distribution is known. We show that it has a special discrete structure, and present a recursive characterization to determine it. We benchmark its performance with ad hoc approaches proposed in the literature, and show that it delivers significant gains. New insights about the optimality of some ad hoc approaches are also developed.

CXI-benzo-84 reversibly binds to tubulin at colchicine site and induces apoptosis in cancer cells

Here, we have discovered CXI-benzo-84 as a potential anticancer agent from a library of benzimidazole derivatives using cell based screening strategy. CXI-benzo-84 inhibited cell cycle progression in metaphase stage of mitosis and accumulated spindle assembly checkpoint proteins Mad2 and BubR1 on kinetochores, which subsequently activated apoptotic cell death in cancer cells. CXI-benzo-84 depolymerized both interphase and mitotic microtubules, perturbed EB1 binding to microtubules and inhibited the assembly and GTPase activity of tubulin in vitro. CXI-benzo-84 bound to tubulin at a single binding site with a dissociation constant of 1.2 +/- 0.2 mu M. Competition experiments and molecular docking suggested that CXI-benzo-84 binds to tubulin at the colchicine-site. Further, computational analysis provided a significant insight on the binding site of CXI-benzo-84 on tubulin. In addition to its potential use in cancer chemotherapy, CXI-benzo-84 may also be useful to screen colchicine-site agents and to understand the colchicine binding site on tubulin. (C) 2013 Elsevier Inc. All rights reserved.

Role of the Ribosomal P-Site Elements of m(2)G966, m(5)C967, and the S9 C-Terminal Tail in Maintenance of the Reading Frame during Translational Elongation in Escherichia coli

The ribosomal P-site hosts the peptidyl-tRNAs during translation elongation. Which P-site elements support these tRNA species to maintain codon-anticodon interactions has remained unclear. We investigated the effects of P-site features of methylations of G966, C967, and the conserved C-terminal tail sequence of Ser, Lys, and Arg (SKR) of the S9 ribosomal protein in maintenance of the translational reading frame of an mRNA. We generated Escherichia coli strains deleted for the SKR sequence in S9 ribosomal protein, RsmB (which methylates C967), and RsmD (which methylates G966) and used them to translate LacZ from its +1 and -1 out-of-frame constructs. We show that the S9 SKR tail prevents both the +1 and -1 frameshifts and plays a general role in holding the P-site tRNA/peptidyl-tRNA in place. In contrast, the G966 and C967 methylations did not make a direct contribution to the maintenance of the translational frame of an mRNA. However, deletion of rsmB in the S9 Delta 3 background caused significantly increased -1 frameshifting at 37 degrees C. Interestingly, the effects of the deficiency of C967 methylation were annulled when the E. coli strain was grown at 30 degrees C, supporting its context-dependent role.

Training for Antenna Selection in Time-Varying Channels: Optimal Selection, Energy Allocation, and Energy Efficiency Evaluation

Single receive antenna selection (AS) is a popular method for obtaining diversity benefits without the additional costs of multiple radio receiver chains. Since only one antenna receives at any time, the transmitter sends a pilot multiple times to enable the receiver to estimate the channel gains of its N antennas to the transmitter and select an antenna. In time-varying channels, the channel estimates of different antennas are outdated to different extents. We analyze the symbol error probability (SEP) in time-varying channels of the N-pilot and (N+1)-pilot AS training schemes. In the former, the transmitter sends one pilot for each receive antenna. In the latter, the transmitter sends one additional pilot that helps sample the channel fading process of the selected antenna twice. We present several new results about the SEP, optimal energy allocation across pilots and data, and optimal selection rule in time-varying channels for the two schemes. We show that due to the unique nature of AS, the (N+1)-pilot scheme, despite its longer training duration, is much more energy-efficient than the conventional N-pilot scheme. An extension to a practical scenario where all data symbols of a packet are received by the same antenna is also investigated.

Interplay Between Optimal Selection Scheme, Selection Criterion, and Discrete Rate Adaptation in Opportunistic Wireless Systems

An opportunistic, rate-adaptive system exploits multi-user diversity by selecting the best node, which has the highest channel power gain, and adapting the data rate to selected node's channel gain. Since channel knowledge is local to a node, we propose using a distributed, low-feedback timer backoff scheme to select the best node. It uses a mapping that maps the channel gain, or, in general, a real-valued metric, to a timer value. The mapping is such that timers of nodes with higher metrics expire earlier. Our goal is to maximize the system throughput when rate adaptation is discrete, as is the case in practice. To improve throughput, we use a pragmatic selection policy, in which even a node other than the best node can be selected. We derive several novel, insightful results about the optimal mapping and develop an algorithm to compute it. These results bring out the inter-relationship between the discrete rate adaptation rule, optimal mapping, and selection policy. We also extensively benchmark the performance of the optimal mapping with several timer and opportunistic multiple access schemes considered in the literature, and demonstrate that the developed scheme is effective in many regimes of interest.

Joint Antenna Selection and Frequency-Domain Scheduling in OFDMA Systems with Imperfect Estimates from Dual Pilot Training Scheme

Transmit antenna selection (AS) has been adopted in contemporary wideband wireless standards such as Long Term Evolution (LTE). We analyze a comprehensive new model for AS that captures several key features about its operation in wideband orthogonal frequency division multiple access (OFDMA) systems. These include the use of channel-aware frequency-domain scheduling (FDS) in conjunction with AS, the hardware constraint that a user must transmit using the same antenna over all its assigned subcarriers, and the scheduling constraint that the subcarriers assigned to a user must be contiguous. The model also captures the novel dual pilot training scheme that is used in LTE, in which a coarse system bandwidth-wide sounding reference signal is used to acquire relatively noisy channel state information (CSI) for AS and FDS, and a dense narrow-band demodulation reference signal is used to acquire accurate CSI for data demodulation. We analyze the symbol error probability when AS is done in conjunction with the channel-unaware, but fair, round-robin scheduling and with channel-aware greedy FDS. Our results quantify how effective joint AS-FDS is in dispersive environments, the interactions between the above features, and the ability of the user to lower SRS power with minimal performance degradation.

A Markov Decision Theoretic Approach to Pilot Allocation and Receive Antenna Selection

This paper considers antenna selection (AS) at a receiver equipped with multiple antenna elements but only a single radio frequency chain for packet reception. As information about the channel state is acquired using training symbols (pilots), the receiver makes its AS decisions based on noisy channel estimates. Additional information that can be exploited for AS includes the time-correlation of the wireless channel and the results of the link-layer error checks upon receiving the data packets. In this scenario, the task of the receiver is to sequentially select (a) the pilot symbol allocation, i.e., how to distribute the available pilot symbols among the antenna elements, for channel estimation on each of the receive antennas; and (b) the antenna to be used for data packet reception. The goal is to maximize the expected throughput, based on the past history of allocation and selection decisions, and the corresponding noisy channel estimates and error check results. Since the channel state is only partially observed through the noisy pilots and the error checks, the joint problem of pilot allocation and AS is modeled as a partially observed Markov decision process (POMDP). The solution to the POMDP yields the policy that maximizes the long-term expected throughput. Using the Finite State Markov Chain (FSMC) model for the wireless channel, the performance of the POMDP solution is compared with that of other existing schemes, and it is illustrated through numerical evaluation that the POMDP solution significantly outperforms them.

En Masse relay selection algorithms for multi-source, multi-relay, decode-and-forward cooperative systems

Opportunistic relay selection in a multiple source-destination (MSD) cooperative system requires quickly allocating to each source-destination (SD) pair a suitable relay based on channel gains. Since the channel knowledge is available only locally at a relay and not globally, efficient relay selection algorithms are needed. For an MSD system, in which the SD pairs communicate in a time-orthogonal manner with the help of decode-and-forward relays, we propose three novel relay selection algorithms, namely, contention-free en masse assignment (CFEA), contention-based en masse assignment (CBEA), and a hybrid algorithm that combines the best features of CFEA and CBEA. En masse assignment exploits the fact that a relay can often aid not one but multiple SD pairs, and, therefore, can be assigned to multiple SD pairs. This drastically reduces the average time required to allocate an SD pair when compared to allocating the SD pairs one by one. We show that the algorithms are much faster than other selection schemes proposed in the literature and yield significantly higher net system throughputs. Interestingly, CFEA is as effective as CBEA over a wider range of system parameters than in single SD pair systems.

Generation of Ligand Specificity and Modes of Oligomerization in beta-Prism I Fold Lectins

beta-Prism I fold lectins constitute one of the five widely occurring structural classes of plant lectins. Each single domain subunit is made up of three Greek key motifs arranged in a threefold symmetric fashion. The threefold symmetry is not reflected in the sequence except in the case of the lectin from banana, a monocot, which carries two sugar-binding sites instead of the one in other lectins of known three-dimensional structure, all from dicots. This is believed to be a consequence of the different evolutionary paths followed by the lectin in monocots and dicots. The galactose-specific lectins among them have two chains produced by posttranslational proteolysis and contain three aromatic residues at the binding site. The extended binding sites of galactose- and mannose-specific lectins have been thoroughly characterized. Ligand binding at the sites involves both conformational selection and induced fit. Molecular plasticity of some of the lectins in the family has been characterized. The plasticity appears to be such as to promote variability in quaternary association which could be dimeric, tetrameric, or octameric. Structural and evolutionary reasons for the variability have been explored, and the relation of oligomerization to ligand binding and conformational selection investigated.