On Achieving Diversity in the Presence of Outliers in Participatory Camera Sensor Networks

This paper addresses the problem of collection and delivery of a representative subset of pictures, in participatory camera networks, to maximize coverage when a significant portion of the pictures may be redundant or irrelevant. Consider, for example, a rescue mission where volunteers and survivors of a large-scale disaster scout a wide area to capture pictures of damage in distressed neighborhoods, using handheld cameras, and report them to a rescue station. In this participatory camera network, a significant amount of pictures may be redundant (i.e., similar pictures may be reported by many) or irrelevant (i.e., may not document an event of interest). Given this pool of pictures, we aim to build a protocol to store and deliver a smaller subset of pictures, among all those taken, that minimizes redundancy and eliminates irrelevant objects and outliers. While previous work addressed removal of redundancy alone, doing so in the presence of outliers is tricky, because outliers, by their very nature, are different from other objects, causing redundancy minimizing algorithms to favor their inclusion, which is at odds with the goal of finding a representative subset. To eliminate both outliers and redundancy at the same time, two seemingly opposite objectives must be met together. The contribution of this paper lies in a new prioritization technique (and its in-network implementation) that minimizes redundancy among delivered pictures, while also reducing outliers.unpublishedis peer reviewe

Seipin oligomers can interact directly with AGPAT2 and lipin 1, physically scaffolding critical regulators of adipogenesis

This work was supported by a Merit Scholarship from the Islamic Development Bank (to M.M.U.T.), The Agency for Science, Technology and Research, Singapore (A*STAR) (M.F.M.S), the Medical Research Council (MRC) [NIRG GO800203 and Research Grant MR/L002620/1 (to J.J.R.), Program GrantG09000554 (to S.O.R)], The Wellcome Trust [078986/Z/06/Z (to S.O.R.)], the MRC Centre for Obesity and Related Metabolic Disorders (MRC-CORD) [GO600717] and the NIHR Comprehensive Biomedical Research Centre [CG50826].Peer reviewedPublisher PD

Design of LMS algorithm for noise canceller based on FPGA

This paper presents the design of an adapting filtering method to remove the noise in the biomedical signal records. The major concern about analyze the presence of various artifacts in ECG records and modular artifacts in EEG records caused due to various noise factors. Here, we have proposed a design based on LMS (Least Mean Square) algorithm to remove the artifacts from biomedical signal using Verilog HDL based on been mapped on  commercially available FPGAs (Field Programmable Gate Arrays). In this design the LMS algorithm used as a noise canceller and the reference signal was adaptively filtered and subtracted from primary signal to obtain the estimated biomedical signal. The original biomedical signal can be reconstructed by passing the digital bit stream through a low pass filter. This design is suitable for its low power biomedical instrument design and it reduces the whole system cost. Keywords: LMS algorithm, noise canceller, Verilog HDL, artifacts, biomedical signal, Low power application

In vivo anxiolytic and in vitro anti-inflammatory activities of water-soluble extract (WSE) of Nigella sativa (L.) seeds

The WSE is a highly polar, gummy and mucilaginous bioactive content of the Nigella sativa (L.) seeds. This study reports the anxiolytic and anti-inflammatory effects of WSE investigated using Elevated Plus Maze (EPM) and Hole-Board Test (HBT) in adult mice and human RBCs haemolysis inhibition and protein denaturation respectively. The oral WSE treatment (100 & 200 mg/kg b.w/day) for 72 hours has exhibited slightly better anxiolytic effect (p < 0.05) through the time span (92.33 & 93.33 s) spent in the opened arms of EPM vs. diazepam (1 mg/kg b.w i.p/day; 69.33 s). In HBT, only WSE (200 mg/kg b.w/day) has shown a promising number of mean head pokes (13.27 times/min) vs. diazepam (12.87 times/min). The WSE (62.5-500 mg/mL) exposure has exhibited 40.14-72.18% protection against lysis of RBCs vs. aspirin (57.04-71.48%) whilst 62.67-67.66% inhibition of protein denaturation vs. diclofenac sodium (43.11-80.64%). The current findings suggested WSE has promising anxiolytic and anti-inflammatory activities

Fuzzy Logic Controller Design for Intelligent Drilling System

An intelligent drilling system can be commercially very profitable in terms of reduction in crude material and labor involvement. The use of fuzzy logic based controller in the intelligent cutting and drilling operations has become a popular practice in the ever growing manufacturing industry. In this paper, a fuzzy logic controller has been designed to select the cutting parameter more precisely for the drilling operation. Specifically, different input criterion of machining parameters are considered such as the tool and material hardness, the diameter of drilling hole and the flow rate of cutting fluid. Unlikethe existing fuzzy logic based methods, which use only two input parameters, the proposed system utilizes more input parameters to provide spindle speed and feed rate information more precisely for the intelligent drilling operation

A New Approach to Solve Transporta-tion Problems

Abstract Finding an initial basic feasible solution is the prime requirement to obtain an optimal solution for the transportation problems. In this article, a new approach is proposed to find an initial basic feasible solution for the transportation problems. The method is also illustrated with numerical examples

IoT-Enabled Big Data Analytics Architecture for Multimedia Data Communications

The present spreading out of the Internet of Things (IoT) originated the realization of millions of IoT devices connected to the Internet. With the increase of allied devices, the gigantic multimedia big data (MMBD) vision is also gaining eminence and has been broadly acknowledged. MMBD management offers computation, exploration, storage, and control to resolve the QoS issues for multimedia data communications. However, it becomes challenging for multimedia systems to tackle the diverse multimedia-enabled IoT settings including healthcare, traffic videos, automation, society parking images, and surveillance that produce a massive amount of big multimedia data to be processed and analyzed efficiently. There are several challenges in the existing structural design of the IoT-enabled data management systems to handle MMBD including high-volume storage and processing of data, data heterogeneity due to various multimedia sources, and intelligent decision-making. In this article, an architecture is proposed to process and store MMBD efficiently in an IoT-enabled environment. The proposed architecture is a layered architecture integrated with a parallel and distributed module to accomplish big data analytics for multimedia data. A preprocessing module is also integrated with the proposed architecture to prepare the MMBD and speed up the processing mechanism. The proposed system is realized and experimentally tested using real-time multimedia big data sets from athentic sources that discloses the effectiveness of the proposed architecture