In this paper, a novel channel estimation technique is proposed for Universal Filtered Multi-Carrier (UFMC) systems. The proposed technique employs Deep Learning (DL) models which utilize the, commonly discarded, odd-indexed samples of the received signal in order to enhance the channel estimation. Three DL models with different sets of input features are proposed. The three proposed DL models were trained and then deployed into a UFMC system to evaluate their performance. The performance metric for the training stage is the Normalized Mean Squared Error (NMSE) between the estimated channel and actual channel coefficients. For deployment stage, both NMSE and Bit Error Rate (BER) are chosen as performance metrics. The proposed models are compared versus conventional Least Square (LS) channel estimator. The results show that the proposed DL-models outperform the LS channel estimator for various Signal to Noise Ratio (SNR) even for channel models which are different from the one used for training. The SNR gains of utilizing the proposed models are 5-6dBs and 2-3dBs on average for NMSE and BER, respectively.

AbstractThe construction industry has experienced rapid growth in the last decade, which was not paralleled by a corresponding growth in productivity. A major reason of this stagnant productivity i...

Out-of-sequence (OOS) construction takes place when an activity or series of activities is not performed according to baseline planned logical productive sequencing. A previous expert-based study by the authors-which has already been published-was the first to provide an industry-wide assessment of OOS work that identified 88 causes of OOS work and quantified them in terms of likelihood of occurrence, relative impact, and risk rating. This paper moves forward to create OOS risk tiers and OOS rating score to measure a project's susceptibility to the risks of OOS in comparison with the industry averages. Series of statistical tests were used to determine the number of risk tiers, allocate the OOS causes to these risk tiers, and define cutoff scores for the different risk tiers. Ultimately, the developed OOS decision support tool was evaluated through expert reviews and direct application on 11 different construction projects. For best results, the associated stakeholders should use the proposed tool at the planning stage of their projects to identify the relevant risks and take the proper actions for prevention and mitigation. The research will help in minimizing OOS work in construction projects, which will yield enhanced productivity, reduced cost and incidence of schedule overruns, and a better overall contracting environment. (c) 2020 American Society of Civil Engineers.

Although out-of-sequence work (OOS) is often cited as a recurring challenge that impacts project performance, it has not been fully addressed in the existing literature as a standalone topic. This paper addresses this gap, defining OOS work as an activity or series of activities that was not performed according to baseline planned logical productive sequencing. By developing a project-based survey and contacting 300 professionals, extensive data were gathered from 42 projects. Using these data, the impacts of OOS were examined. It was found that, on average, approximately 15% of project activities are performed as OOS, resulting in 33% growth in construction schedule and 25% additional construction cost. Applying statistical analysis verified that, at 95% confidence level, OOS has a statistically significant inverse correlation with the productivity index, and a significant direct correlation with cost growth, schedule growth, and value of punchlist items. On average, a 5% increase in OOS was shown to be associated with an 8.5% drop in productivity, 10% increase in construction cost, and 11% increase in construction schedule. Regarding safety, no conclusive statistically significant relationships were found between OOS and the examined safety metrics, possibly because safety measures were followed regardless of sequencing. Investigating 19 project factors, the study highlighted statistically significant relationships between OOS and 15 leading indicators, at 95% confidence level. For example, implementing unplanned overtime, trade stacking, rework, as well as request for information (RFI) enumeration and processing time have significant direct correlation with OOS, while overall collaboration among project team members is inversely correlated with OOS. Project complexity, construction pa (c) 2020 American Society of Civil Engineers.ce (traditional versus phased), percent design completion prior to construction, and the use of second shifts were not found to be statistically correlated with OOS. On investigating the level to which projects used five commonly recommended practices (alignment, front-end planning, constructability, planning for startup, and 3D modeling), the study found that the five practices are inversely correlated with OOS, especially when collaboratively implemented early and often throughout the project. Industry practitioners should use the presented findings to address and mitigate OOS and its negative impacts, ultimately enhancing overall project performance. (c) 2020 American Society of Civil Engineers.

Out-of-sequence work (OOS) is an activity or series of activities that were not performed according to baseline planned logical productive sequencing. Since OOS significantly weakens project performance, this paper pinpoints the factors that should be addressed to help mitigate it. Using an extensive project-based survey, 42 projects were statistically investigated. Projects with inadequate coordination among different parties were shown to suffer from significant OOS. Lack of owner participation and engineering support during construction were main causes of OOS, whereas implementing constructability and alignment processes helped mitigate it. Additionally, more collaborative project delivery systems better mitigated OOS compared to less collaborative ones. Change orders were highly associated with OOS. However, project complexity was not correlated with OOS, highlighting that all projects are prone to OOS regardless of complexity. Front-end planning, planning for start-up, three-dimensional modeling, and frequently updating project schedules helped mitigate OOS. In contrast, the excessive use of request-for-information forms and their prolonged processing time, unplanned overtime, trade stacking, and absenteeism were all directly associated with OOS. Professionals are advised to use the findings presented in this paper to help mitigate OOS, thus significantly improving project performance.

In this paper, the task of performing finite-length minimum mean square error (MMSE) equalization is considered for single carrier communication systems. A detailed mathematical derivation of the finite-length MMSE equalizer is presented where the MMSE equalizer coefficients are described using linear convolution instead of the matrix form representation, which is commonly found in literature. The linear convolution is then transformed into circular convolution by performing frequency-domain sampling while avoiding time-domain aliasing. The computation of the circular convolution naturally lends itself to employing FFT and IFFT operations, which leads to a significant complexity reduction compared to the traditional approaches of computing the MMSE equalizer coefficients using matrix inversion.

A project delivery system (PDS) defines the relationship and timing of involvement between different contracting parties in construction. Using data from 109 projects, this paper statistically investigates the project performance of the four main PDSs: design-bid-build (DBB), construction management (CM), design-build (DB), and integrated project delivery (IPD). First, descriptive statistical methodologies were applied to the dataset to determine performance benchmarks for each examined PDS. Next, by applying statistical tests, such as the analysis of variance (ANOVA) F-test and the Kruskal-Wallis H-test, statistically significant performance differences among the examined PDSs were identified in five performance areas: cost, schedule, quality, communication, and change management. Finally, pairwise comparisons were performed by applying posthoc statistical tests to each pair of PDSs, demonstrating that IPD outperformed DBB in 11 metrics, while it outperformed CM and DB in two metrics each. Also, DB outperformed DBB in seven metrics, and CM outperformed DBB in five metrics. This paper addresses a consistently missing piece in the existing body of literature related to project delivery. The findings presented in this paper should prompt industry leaders and professionals to move away from the DBB model and toward IPD and other synergic PDSs. (c) 2020 American Society of Civil Engineers.

The universal filtered multicarrier (UFMC) system is one of the novel candidate waveforms for 5G systems. UFMC is expected to achieve low latency, robustness against frequency offset, and reduce out-of-band (OoB) radiation that leads to a higher spectral efficiency. Although, the UFMC system offers many advantages as mentioned before, but being a multicarrier transmission technology, it suffers from high peak-to-average power ratio (PAPR). In this paper, a modified selected mapping (SLM) approach with low-complexity is proposed for reducing PAPR in UFMC systems. The main idea of the proposed modified SLM (P-SLM) approach is to utilize the linearity property of the UFMC modulator. The P-SLM approach generates Uw alternative UFMC waveforms using Um UFMC modulators, where Um is the square-root of Uw. Therefore, the computational complexity of the P-SLM approach is reduced compared to the existing SLM based PAPR reduction approaches for UFMC systems. The P-SLM approach is compared to the other approaches found in the literature in terms of PAPR reduction ability, bit error rate (BER) performance, and the computational complexity.

Universal filtered multicarrier (UFMC) is a promising candidate waveform for 5G systems. UFMC is an alternative candidate waveform to orthogonal frequency division multiplexing (OFDM), in which the filtering operation is performed for subband of subcarriers instead of the whole band. The subband filtering process reduces-of-band (OOB) emission and therefore minimizes the intercarrier interference (ICI) between adjacent users. However, UFMC system is limited by its high peak-to-average power ratio (PAPR). So in this paper, we first analyze the differences in PAPR between the UFMC and OFDM waveforms. Second, we propose an efficient selected mapping (SLM) technique for PAPR reduction in UFMC systems. The proposed technique achieves significant PAPR reduction as compared with the conventional SLM-OFDM system and single carrier frequency division multiple access (SC-FDMA) system. Also, the proposed technique performs very well in terms of bit error rate (BER) for the UFMC system.

Project managers (PMs) play a key role in the successful completion of construction projects. Therefore, PM competencies have been heavily investigated over the past few decades, often focusing on two types of skills: hard skills, including technical knowledge; and soft skills, including personal traits. This extensive body of knowledge was lacking the focus on PMs of transportation projects who work in a state highway agency (SHA). This research addresses this gap by developing a comprehensive competency assessment model tailored for SHA PMs. This research identified 55 PM essential competencies spanning five categories: project management knowledge and experience; leadership; SHA operational knowledge and experience; industry knowledge and experience; and cognitive/personal effectiveness. Also, by collecting extensive data from 90 PMs, this research developed a mathematical model to compute competency weights for differentiating exceptional and average PMs. The weights were then used to create a comprehensive score that can assess PM competencies as an overall percentage. This score was benchmarked using the collected data to distinguish between exceptional and average PMs. To effectively communicate the research findings to industry practitioners, a computer-based tool was created. This tool assists SHAs and their PMs in assessing competencies, and identifies training needs to improve overall PM performance and skill sets. The tool was tested and validated by five Wisconsin Department of Transportation PM supervisors, all of whom acclaimed its accuracy and potential value.

Out-of-sequence (OOS) construction is regarded as one of the most significant factors contributing to construction inefficiencies and loss of labor productivity. Nevertheless, no prior research efforts have attempted to study the impacts of OOS work on productivity, cost, or even schedule. The goal of this paper is to identify and study the causes and early warning signs of OOS work. Using an expert-based analytic approach, the authors formed an industry panel of 13 construction professionals to gather the basic information related to OOS work and consequently surveyed 88 other industry respondents. The panel as well as the survey enabled the authors to (1) recognize the extent of OOS work, (2) identify 88 causes of OOS work and quantify their characteristics, (3) identify 54 early warning signs of OOS work and investigate their relationship with the occurrence of OOS events, (4) classify the causes and early warning signs of OOS into 11 different categories, and (5) investigate the impacts of OOS work on project performance in terms of productivity, schedule, cost, quality, and safety. Among many important and interesting results, it was clear that late design deliverables represented the most important factor causing OOS work, and late start of precommissioning activities was the most highly ranked early warning sign for OOS work. This research adds to the body of knowledge by providing unprecedented knowledge on why OOS work occurs and by providing a suite of practices that contribute most to OOS work in construction projects. This paper fills a significant gap in the literature and contributes in assisting project participants in better understanding the overall industry perception on the different causes, early warning signs, and impacts of OOS work.

Project Delivery System (PDS) defines the relationship and timing of involvement between different contracting parties.The main PDSs referred to in cited literature are: Design-Bid-Build (DBB), Construction Management at Risk (CMR), Design-Build (DB), and Integrated Project Delivery (IPD).By applying statistical tests such as Analysis of Variance (ANOVA) F-test and Kruskal-Wallis H-test to a dataset of 109 projects, this paper compares the performance of the four PDSs.As a result, statistically significant performance differences among the examined PDSs were identified in five performance areas: cost, schedule, quality, communication, and change management.Furthermore, performing pairwise comparisons using post-hoc statistical tests to each pair of PDSs shows that DBB performs markedly worse than the other examined PDSs, especially IPD.The findings presented in this paper should encourage industry professionals to move away from the DBB model, and towards IPD and other synergic PDSs.

Competent project managers (PMs) are the backbone of any construction project. It is extremely important to constantly develop and enhance their competencies. However, to establish effective training and development plans for PMs, the relative importance of the key competencies that define a PM's performance should be first understood. Instead of subjectively weighting the relative importance of differing competencies, this paper aims at developing an automated model that uses real-life data to compute the PM competency weights. The rationale behind the model is to maximize the distance in a higher dimensional space between average and exceptional PM performances. The model solves an eigenvalue problem, and identifies a single data-based weight for each competency. The model is generic and can be applied to various research settings to alleviate the problems associated with opinion-based assessment and reduce individuals' subjectivity. Findings within this paper reveal the most critical competencies that enable PMs to perform their roles in construction projects exceptionally.

Project delivery system (PDS) defines the relationship and timing of involvement between different contracting parties. Traditional PDSs referred to in cited literature are: design-bid-build (DBB), construction management at risk (CM), and design build (DB). More recent studies, including this paper, add a fourth PDS: integrated project delivery (IPD). Existing PDS literature has claimed that increased PDS collaboration results in performance improvement. However, these studies have either studied the performance differences among the three traditional PDSs, or compared the performance of IPD to the three traditional ones collectively. Very limited research has examined the statistical performance differences between the four PDSs. By collecting quantitative data from 109 real-world projects, and applying statistical methodologies such as analysis of variance (ANOVA), Kruskal-Wallis H test and related post-hoc tests, this paper illustrates that PDSs significantly differ in 10 performance metrics spanning five performance areas: cost, schedule, quality, communication, and change management. Furthermore, the findings of this paper demonstrate the poor performance of DBB as compared to the superior performance of more collaborative PDSs, specifically IPD.

This paper proposes a new channel estimation algorithm based on data nulling superimposed pilots for the spatial multiplexing multiple-input-multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems. In the proposed method each OFDM data symbol of each transmit antenna is spread over all subcarriers by using a spreading matrix then nulls are introduced at certain subcarriers to cancel the mutual interference between data symbols and superimposed pilots. At receiver accurate channel estimation can be easily acquired based on the superimposed pilots. Then the superimposed pilots are removed from the received signal and simple iterative data detection scheme is used to compensate the distortion which occurred in the data symbols. The simulation results of the proposed algorithm show improvement in the estimation accuracy, bit error rate (BER) and computational complexity compared to that of the conventional superimposed pilot technique. The simulation results also show that the performance of the proposed technique approaches that of the frequency division multiplexed pilots technique while having higher data rate and some excess in the receiver complexity.

In this paper, a localisation system based on Wi-Fi fingerprinting and fuzzy data analysis is presented. Three localisation techniques were used, Euclidean distance, K-nearest neighbours (KNN), and weighted K-nearest neighbours (WKNN), to get three independent estimations of a user's location. Then fuzzy analysis is used to combine the three estimates to achieve highly-accurate localisation. Two experiments were conducted in order to test the proposed new technique and compare it to the traditional fingerprinting techniques present in the literature. The results of the experiments proved that the proposed technique outperforms the traditional techniques.

One of the orthogonal frequency division multiplexing (OFDM) schemes is the Time Domain Synchronous OFDM (TDS-OFDM) scheme, in which, the guard intervals between consecutive OFDM symbols contain Pseudo Noise (PN) sequences which are known to the receiver and are used for channel estimation and synchronization. In this paper, a joint channel estimation algorithm is proposed for TDS-OFDM scheme, the proposed algorithm is based on using a Data-Dependent Superimposed Training (ST) sequence to improve the channel estimation accuracy in TDS-OFDM by utilizing two sources for channel estimation, the PN sequence at the guard interval and the ST sequence added to the data-dependent sequence. Furthermore, a simple linear combination algorithm is used to combine the two channel estimation results. The simulation results of the proposed algorithm show improvement in the estimation accuracy and bit error rate (BER) with little excess in the receiver complexity while, conserving same spectral efficiency as conventional TDS-OFDM scheme.

The anticipated services of the 5th Generation mobile networks (5G) requires new technologies to be introduced and to be thoroughly investigated in order to assess their ability to satisfy the new 5G system requirements. The main focus of this paper is the relaxed system synchronization procedures used to meet the new 5G requirements which cannot be satisfied by strictly synchronized OFDM systems and their costly synchronization procedures The most promising technology to replace OFDM in 5G is Universal Filtered Multi-Carrier (UFMC) whose performance has already been assessed in literature where the main focus was proving the enhanced performance of UFMC in presence of Carrier Frequency Offsets (CFO) and Timing Offsets (TO) arising from the reduced synchronization limitations. In this paper we address a new aspect of UFMC performance by investigating its capability to overcome the multipath fading channels' effects and to provide good and reliable performance levels without using the cyclic prefix concept introduced in OFDM to overcome these channel effects.