We present novel grid coverage strategies for effective surveillance and target location in distributed sensor networks. We represent the sensor field as a grid (two or three-dimensional) of points ...(coordinates) and use the term target location to refer to the problem of locating a target at a grid point at any instant in time. We first present an integer linear programming (ILP) solution for minimizing the cost of sensors for complete coverage of the sensor field. We solve the ILP model using a representative public-domain solver and present a divide-and-conquer approach for solving large problem instances. We then use the framework of identifying codes to determine sensor placement for unique target location, We provide coding-theoretic bounds on the number of sensors and present methods for determining their placement in the sensor field. We also show that grid-based sensor placement for single targets provides asymptotically complete (unambiguous) location of multiple targets in the grid.
Natural-gas-fueled solid oxide fuel cell (SOFC) systems have the potential for high-efficiency conversion of carbon to power due to the underlying electrochemical conversion process while readily ...facilitating carbon capture through the separation of the fuel and oxidant sources. Compressed air energy storage (CAES) technology can potentially store significant quantities of energy for later use with a high round-trip efficiency and lower cost when compared with state-of-the-art battery technology. The base load generation capability of SOFC can be coupled with CAES technology to provide a potentially flexible, low-carbon solution to meet the fluctuating electricity demands imposed by the increasing share of intermittent variable renewable energy (VRE) production. SOFC and CAES can be hybridized through thermal integration to maximize power output during periods of high electrical demand and then store power when either demand is low or renewable generation reduces power prices. The techno-economics of a low-carbon hybrid SOFC and CAES system was developed and investigated in the present study. The proposed hybrid system was found to be cost-competitive with other power-generating base-load facilities when power availability was considered. The hybrid system shows increased resilience to changes in a high VRE grid market scenario.
What is the effect of option categorization on choosers’ satisfaction? A combination of field and laboratory experiments reveals that the mere presence of categories, irrespective of their content, ...positively influences the satisfaction of choosers who are unfamiliar with the choice domain. This “mere categorization effect” is driven by a greater number of categories signaling greater variety among the available options, which allows for a sense of self‐determination from choosing. This effect, however, is attenuated for choosers who are familiar with the choice domain, who do not rely on the presence of categories to perceive the variety available.
•We present a theoretical framework that can be used for analyzing, and quantifying the performance of parallel algorithms designed for MS based omics data.•We prove the lower communication bounds ...for the existing parallel algorithms.•We also prove lower communication bounds that can be theoretically achieved by parallel algorithms for MS based omics analysis.•Extensive experimentation for state of the art tools confirms our theoretical results.•This is first proof of any communication bounds for parallel algorithms for MS based omics.
Mass spectrometry (MS) based omics data analysis require significant time and resources. To date, few parallel algorithms have been proposed for deducing peptides from mass spectrometry-based data. However, these parallel algorithms were designed, and developed when the amount of data that needed to be processed was smaller in scale. In this paper, we prove that the communication bound that is reached by the existing parallel algorithms is Ω(mn+2rqp), where m and n are the dimensions of the theoretical database matrix, q and r are dimensions of spectra, and p is the number of processors. We further prove that communication-optimal strategy with fast-memory M=mn+2qrp can achieve Ω(2mnqp) but is not achieved by any existing parallel proteomics algorithms till date. To validate our claim, we performed a meta-analysis of published parallel algorithms, and their performance results. We show that sub-optimal speedups with increasing number of processors is a direct consequence of not achieving the communication lower-bounds. We further validate our claim by performing experiments which demonstrate the communication bounds that are proved in this paper. Consequently, we assert that next-generation of provable, and demonstrated superior parallel algorithms are urgently needed for MS based large systems-biology studies especially for meta-proteomics, proteogenomic, microbiome, and proteomics for non-model organisms. Our hope is that this paper will excite the parallel computing community to further investigate parallel algorithms for highly influential MS based omics problems.
Differentiated product models are predicated on the belief that a product’s utility can be derived from the summation of utilities for its individual attributes. In one framed field experiment and ...two natural field experiments, we test this assumption by experimentally manipulating the order of attribute presentation in the product customization process of custom‐made suits and automobiles. We find that order affects the design of a suit that people configure and the design and price of a car that people purchase by influencing the likelihood that they will accept the default option suggested by the firm.
Internet of Things (IoT) paradigm links physical objects in the real world to cyber world and enables the creation of smart environments and applications. A physical object is the fundamental ...building block of the IoT, known as a Smart Device , that can monitor the environment. These devices can communicate with each other and have data processing abilities. When deployed, smart devices collect real-time data and publish the gathered data on the Web. The functionality of smart devices can be abstracted as a service and an IoT application can be built by combining the smart devices with these services that help to address challenges of day-to-day activities. The IoT comprises billions of these intelligent communicating devices that generate enormous amount of data, and hence performing analysis on this data is a significant task. Using search techniques, the size and extent of data can be reduced and limited, so that an application can choose just the most important and valuable data items as per its necessities. It is, however, a tedious task to effectively seek and select a proper device and/or its data among a large number of available devices for a specific application. Search techniques are fundamental to IoT and poses various challenges like a large number of devices, dynamic availability, restrictions on resource utilization, real time data in various types and formats, past and historical monitoring. In the recent past, various methods and techniques have been developed by the research community to address these issues. In this paper, we present a review of the state-of-the-art search methods for the IoT, classifying them according to their design principle and search approaches as: IoT data and IoT object-based techniques. Under each classification, we describe the method adopted, their advantages and disadvantages. Finally, we identify and discuss key challenges and future research directions that will allow the next generation search techniques to recognize and respond to user queries and satisfy the information needs of users.
Summary Background The need for multiple clinical visits remains a barrier to women accessing safe legal medical abortion services. Alternatives to routine clinic follow-up visits have not been ...assessed in rural low-resource settings. We compared the effectiveness of standard clinic follow-up versus home assessment of outcome of medical abortion in a low-resource setting. Methods This randomised, controlled, non-inferiority trial was done in six health centres (three rural, three urban) in Rajasthan, India. Women seeking early medical abortion up to 9 weeks of gestation were randomly assigned (1:1) to either routine clinic follow-up or self-assessment at home. Randomisation was done with a computer-generated randomisation sequence, with a block size of six. The study was not blinded. Women in the home-assessment group were advised to use a pictorial instruction sheet and take a low-sensitivity urine pregnancy test at home, 10–14 days after intake of mifepristone, and were contacted by a home visit or telephone call to record the outcome of the abortion. The primary (non-inferiority) outcome was complete abortion without continuing pregnancy or need for surgical evacuation or additional mifepristone and misoprostol. The non-inferiority margin for the risk difference was 5%. All participants with a reported primary outcome and who followed the clinical protocol were included in the analysis. This study is registered with ClinicalTrials.gov , number NCT01827995. Findings Between April 23, 2013, and May 15, 2014, 731 women were recruited and assigned to clinic follow-up (n=366) or home assessment (n=365), of whom 700 were analysed for the main outcomes (n=336 and n=364, respectively). Complete abortion without continuing pregnancy, surgical intervention, or additional mifepristone and misoprostol was reported in 313 (93%) of 336 women in the clinic follow-up group and 347 (95%) of 364 women in the home-assessment group (difference −2·2%, 95% CI −5·9 to 1·6). One case of haemorrhage occurred in each group (rate of adverse events 0·3% in each group); no other adverse events were noted. Interpretation Home assessment of medical abortion outcome with a low-sensitivity urine pregnancy test is non-inferior to clinic follow-up, and could be introduced instead of a clinic follow-up visit in a low-resource setting. Funding Swedish Research Council and Swedish International Development Agency.
We propose a distributed solution for a canonical task in wireless sensor networks - the binary detection of interesting environmental events. We explicitly take into account the possibility of ...sensor measurement faults and develop a distributed Bayesian algorithm for detecting and correcting such faults. Theoretical analysis and simulation results show that 85-95 percent of faults can be corrected using this algorithm, even when as many as 10 percent of the nodes are faulty.
Internet of Things (IoT) paradigm connects physical world and cyberspace via physical objects and facilitate the development of smart applications and infrastructures. A physical object is the basic ...constituent of IoT, often called as smart object, that interact with other objects and possess the information processing abilities. The smart objects when deployed in the real world, collect information from the surrounding environment and this is abstracted as a service. IoT has established a universe where humans are provided smart data services by the fusion of physical objects and information networks. This approach has been extended to include social networking aspects in the IoT that autonomously build social relationships to discover objects and their services viz; Social Internet of Things (SIoT). SIoT enhances information sharing, supports new applications and provide a reliable and trustworthy networking solutions utilizing the social network of friend objects. In this paper, we present the fundamentals of SIoT, identify thrust areas of it (as service discovery and composition, network navigability, relationship management, and trustworthiness management) and present several prerequisites, challenges and use case scenarios based on them. State-of-the-art research publications are reviewed on service discovery, relationship management, service composition and trust management constituents of the SIoT environment. Finally, we identify and discuss the future research directions that serves as a reference for the next generation discovery techniques to improve service provisioning, find the optimal solution for the link selection in the SIoT structure, develop large scale platforms and provide a smart mechanism for trust evaluation.
Belief in one's ability to exert control over the environment and to produce desired results is essential for an individual's wellbeing. It has repeatedly been argued that perception of control is ...not only desirable, but is also probably a psychological and biological necessity. In this article, we review the literature supporting this claim and present evidence of a biological basis for the need for control and for choice-that is, the means by which we exercise control over the environment. Converging evidence from animal research, clinical studies and neuroimaging suggests that the need for control is a biological imperative for survival, and a corticostriatal network is implicated as the neural substrate of this adaptive behavior.
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