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Project delays are the major problems tackled by the construction sector owing to the associated complexity and uncertainty in the construction activities. Artificial Intelligence (AI) models have evidenced their capacity to solve dynamic, uncertain and complex tasks. The aim of this current study is to develop a hybrid artificial intelligence model called integrative Random Forest classifier with Genetic Algorithm optimization (RF-GA) for delay problem prediction. At first, related sources and factors of delay problems are identified. A questionnaire is adopted to quantify the impact of delay sources on project performance. The developed hybrid model is trained using the collected data of the previous construction projects. The proposed RF-GA is validated against the classical version of an RF model using statistical performance measure indices. The achieved results of the developed hybrid RF-GA model revealed a good resultant performance in terms of accuracy, kappa and classification error. Based on the measured accuracy, kappa and classification error, RF-GA attained 91.67%, 87% and 8.33%, respectively. Overall, the proposed methodology indicated a robust and reliable technique for project delay prediction that is contributing to the construction project management monitoring and sustainability.

Precipitable water vapour (PWV) is an important input for numerical weather prediction model, meteorology and high-precision navigational applications. Conventional methods for the determination of PWV using radiosonde are not sufficient owing to poor temporal resolution, whereas radiometer-derived PWV is reliable only in fair weather conditions. Global positioning system (GPS) is a very useful and cost-effective tool to determine PWV continuously in all weather conditions. The processing of GPS data to extract the PWV information is, however, very complicated due to very small effect of the PWV (∼0.5% of total delay) on GPS frequencies than other sources of delay and errors and requires a network of GPS in differential configuration for such purpose. The authors show how the problem can be handled in a standalone dual-frequency GPS receiver in a relatively less complicated manner with reasonable accuracy. The performances of different dry tropospheric delay models are also investigated. The methodology is tested with GPS measurements at Kolkata (22.57°N, 88.37°E) and Bangalore (13.01°N, 77.5°E). The results indicate that the proposed methodology can be implemented for PWV estimation using single GPS receiver with satisfactory performance.

The characteristic and inherent risks in construction projects present key difficulties to stakeholders and project teams. Risk appraisal is a significant step toward potential variables identification and evaluation. In risk assessment, adequate categorization and prioritization aid planning, budgeting and management of project related risks. In this paper, an analysis of the risks associated with the delay sources in the internal environment of Malaysian construction projects have been presented based on risk priority number (RPN) to determine the degree of severity, occurrence and detection. Through literature review, eighty one risks under four main delay sources were extracted for further analysis. From the results, the main risks include contractor's financial problems, poor coordination by the contractor, change orders, client's financial problems, errors and defective work, poor materials management, poor communication between consultant and contractor, unrealistic contract duration, poor procurement tools and methods, unavailability of materials and labors, ineffective coordination by project managers, poor construction site layout, changes in material types and specification, inaccuracies in estimation and budgeting, delays in approvals, respectively. This study would provide a decision tool for prioritizing and categorizing risks in construction projects to build a realistic and rational resources allocation guide.

Modified group delay based algorithms for estimation of melodic pitch sequences from heterphonic/polyphonic music are discussed in this paper. Two different variants of the modified group delay function are proposed, namely, (a) system based—MODGD (Direct) and (b) source based—MODGD (Source). In (a) the standard modified group delay function (MODGDF) is used to estimate prominent melodic pitch ( f 0 ), which appears like a low frequency formant in the MODGDF spectrum. In (b), the power spectrum of the signal is first flattened to emphasise the source. The flattened power spectrum behaves like a sinusoid in noise, the frequency of the sinusoid being related to the pitch frequency. The modified group delay function of this signal produces peaks at T 0 , 2 T 0 , … , where T 0 = 1 f 0 . Continuity constraints in a dynamic programming framework are imposed across frames to reduce octave errors. Sudden changes in pitch are accommodated by changing the frame size dynamically using a multi-resolution framework. The performance of the proposed systems was evaluated on four datasets: ADC-2004, LabROSA, MIREX-2008 and Carnatic music dataset. The performance of the proposed approaches demonstrate the potential of the group delay based methods for melody extraction.

A wireless sensor network (WSN) consists of a large number of unattended sensors with limited storage, battery power, computation, and communication capabilities, where battery power (or energy) is the most crucial resource for sensor nodes. The information sensed by sensors needs to be transmitted to sink quickly especially for the applications with delay restriction. However, it is difficult to achieve optimal energy efficiency and source-to-sink delay simultaneously. So it is very necessary to find a power control solution based tradeoff between energy and delay. In this paper, a cooperative differential game model is proposed, and a power solution is obtained which determines a fair distribution of the total cooperative cost among sources.

An analytic traffic model is developed for an unreliable wireless sensor network. We model the dynamics of traffic flow from the source node through a set of intermediate nodes to the sink node by using single-server queues. These single-server queues with finite buffers are linked in tandem. To analyze the performance of the sensor network, we decompose the tandem queuing network into individual nodes with modified arrival and service processes and modified queue capacities. In the individual node modeling, we consider the impact of the unreliable transmissions, i.e., node/link failure events, by involving the immediate upstream node and downstream node of the separated node. The steady-state solutions of the individual nodes are determined iteratively. A performance metric source-to-sink delay is derived and selected for studying the quality of service (QoS) control. Adaptive QoS control schemes are developed and their performance is validated by simulation.

We develop an analytic model for traffic flow analysis in a multi-hop wireless sensor network subject to node failure through a queueing theoretic framework. The dynamics of traffic flow in the source-to-sink path is modeled by a number of single-server queues with finite capacity linked in tandem. Both the blocking effect of tandem queues due to limited buffer and the impact of node failure due to limited node power are taken into account during modeling. The tandem-node path is analyzed by decomposing it into individual nodes with modified arrival and service processes as well as queue capacities. An iterative algorithm is developed for evaluating the performance metrics. One metric, i.e., source-to-sink delay, is used for studying QoS (quality of service) control. A simple QoS control scheme is proposed and its effectiveness is validated by simulations. [PUBLICATION ABSTRACT]

Fast radio bursts (FRBs) are a powerful and mysterious new class of transients that are luminous enough to be detected at cosmological distances. By associating FRBs to host galaxies, we can measure intrinsic and environmental properties that test FRB origin models, in addition to using them as precise probes of distant cosmic gas. The Deep Synoptic Array (DSA-110) is a radio interferometer built to maximize the rate at which it can simultaneously detect and localize FRBs. Here, we present the first sample of FRBs and host galaxies discovered by the DSA-110. This sample of 11 FRBs is the largest, most uniform sample of localized FRBs to date, as it is selected based on association with host galaxies identified in optical imaging by Pan-STARRS1. These FRBs have not been observed to repeat, and their radio properties (dispersion, temporal scattering, energy) are similar to that of the known nonrepeating FRB population. Most host galaxies have ongoing star formation, as has been identified before for FRB hosts. Two hosts of the new sample are massive, quiescent galaxies. The distribution of star formation history across this host-galaxy sample shows that the delay time distribution is wide, with a power-law model that spans from ∼100 Myr to ≳2 Gyr. This requires the existence of one or more progenitor formation channels associated with old stellar populations, such as the binary evolution of compact objects.

This paper investigates the data accumulation velocity of 12 Altmetric.com data sources. DOI created date recorded by Crossref and altmetric event posted date tracked by Altmetric.com are combined to reflect the altmetric data accumulation patterns over time and to compare the data accumulation velocity of various data sources through three proposed indicators, including Velocity Index, altmetric half-life, and altmetric time delay. Results show that altmetric data sources exhibit different data accumulation velocity. Some altmetric data sources have data accumulated very fast within the first few days after publication, such as Reddit, Twitter, News, Facebook, Google+, and Blogs. On the opposite spectrum, research outputs are at relatively slow pace in accruing data on some data sources, like Policy documents, Peer review, Q&A, Wikipedia, Video, and F1000Prime. Most altmetric data sources’ velocity degree also changes by document types, subject fields, and research topics. The type Review is slower in receiving altmetric mentions than Article, while Editorial Material and Letter are typically faster. In general, most altmetric data sources show higher velocity values in the fields of Physical Sciences and Engineering and Life and Earth Sciences. Within each field, there also exist some research topics that attract social attention faster than others.

Gravitational-wave detectors are starting to reveal the redshift evolution of the binary black hole (BBH) merger rate, R BBH(z). We make predictions for R BBH(z) as a function of black hole mass for systems originating from isolated binaries. To this end, we investigate correlations between the delay time and black hole mass by means of the suite of binary population synthesis simulations, COMPAS. We distinguish two channels: the common envelope (CE), and the stable Roche-lobe overflow (RLOF) channel, characterized by whether the system has experienced a common envelope or not. We find that the CE channel preferentially produces BHs with masses below about 30 M ⊙ and short delay times (t delay ≲ 1 Gyr), while the stable RLOF channel primarily forms systems with BH masses above 30 M ⊙ and long delay times (t delay ≳ 1 Gyr). We provide a new fit for the metallicity-dependent specific star formation rate density based on the Illustris TNG simulations, and use this to convert the delay time distributions into a prediction of R BBH(z). This leads to a distinct redshift evolution of R BBH(z) for high and low primary BH masses. We furthermore find that, at high redshift, R BBH(z) is dominated by the CE channel, while at low redshift, it contains a large contribution (∼40%) from the stable RLOF channel. Our results predict that, for increasing redshifts, BBHs with component masses above 30 M ⊙ will become increasingly scarce relative to less massive BBH systems. Evidence of this distinct evolution of R BBH(z) for different BH masses can be tested with future detectors.