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Earthquakes, forest fires, mudslides and other natural disasters occur frequently in recent years. They usually occur in the mountainous and dense forests, where local communication facilities do not exist or have been destroyed by the disasters. Adverse geographical environment poses a huge challenge to emergency communications and rescue. This paper presents comparative studies on multi-carrier transmission schemes in the mountainous and dense forest environment. The comprehensive communication performance for various multi-carrier waveform schemes, has been extensively analyzed by using the Stanford University Interim channel model. Simulation results show that the pruned discrete Fourier transform spread filter bank multi-carrier scheme exhibits generally the best performance in terms of transmission rate and distance for most operation modes. [ABSTRACT FROM AUTHOR]

This paper addresses the unrelated parallel machine scheduling problem with sequence and machine dependent setup times and machine eligibility constraints. The objective is to minimize the maximum completion time (makespan). Instances of more than 500 jobs and 50 machines are not uncommon in industry. Such large instances become increasingly challenging to provide high-quality solutions within limited amount of computational time, but so far, have not been adequately addressed in recent literature. A hybrid genetic algorithm is developed, which is lean in the sense that is equipped with a minimal number of parameters and operators, and which is enhanced with an effective local search operator, specifically targeted to solve large instances. For evaluation purposes a new set of larger problems is generated, consisting of up to 800 jobs and 60 machines. An extensive comparative study shows that the proposed method performs significantly better compared to other state-of-the-art algorithms, especially for the new larger instances. Also, it is demonstrated that calibration is crucial and in practice it should be targeted at a narrower set of representative instances. [ABSTRACT FROM AUTHOR]

An image caption generator produces syntactically and semantically correct sentences to narrate the scene of a natural image. A neural image caption (NIC) generator is a popular deep learning model for automatically generating image captions in plain English. The NIC generator combines a convolutional neural network (CNN) encoder and a long short-term memory (LSTM) decoder. This paper investigates the performance of different CNN encoders and recurrent neural network decoders for finding the best NIC generator model for image captioning. Besides, we test the image caption generators with four image inject models and with decoding strategies such as greedy search and beam search. We conducted experiments on the Flickr8k dataset and analyzed the results qualitatively and quantitatively. Our results validate the automated image caption generator with ResNet-101 encoder, and the LSTM/gated recurrent units decoder outperforms the popular neural image caption NIC generator in the presence of par-inject concatenate conditioning and beam search. For quantitative assessment, we used R O U G E L , C I D E r D , and B L E U n scores to compare the different models. [ABSTRACT FROM AUTHOR]

Named entity recognition (NER) is a fundamental but crucial task in the field of natural language processing and has been widely studied. Nevertheless, little attention has been given to the segment representation (SR) schemes used to map multi-token entities into categories in Chinese NER. To address this issue, in this paper, we explore and compare the impact of using different SR schemes on Chinese NER. Our experiments are conducted on four benchmark Chinese NER datasets extended with labels to include seven well-known SR schemes: IO, IOB2, IOE2, IOBES, BI, IE, and BIES. Moreover, all seven SR schemes are investigated via two sets of classifiers: machine learning-based and neural network-based classifiers. The experimental results demonstrate that the proper selection of the best SR scheme is a complicated problem that depends on various factors, such as corpus size, corpus distribution, and the chosen classifier. We also provide a comparative analysis of the time consumption of each classifier in different SR schemes and discuss the impacts of using different SR schemes on NER in Chinese and other languages. [ABSTRACT FROM AUTHOR]

The purpose of the paper is to understand if the online consumer reviews differ across the review platforms over the internet. We aim to find the features of the reviews from various platforms and ultimately create a typology of the reviews for those platforms. We apply mixed methods including both quantitative and qualitative techniques to arrive at the conclusion. We find consumers share their views on the highest number of topics in the ecommerce website. Consumers share in-depth views, but on a limited number of topics in other dedicated review platforms. Social media falls somewhere in the middle among these two platforms. While looking into the contents, we could generate themes and meta-themes from these reviews. Based on these facts, we create a typology/ontology for reviews from these platforms and map the motives of reviewers from each platform into the meta-themes identified. Managers can use our findings to boost their online review strategy according to the platform of their interest. [ABSTRACT FROM AUTHOR]

In this paper, we focus on various compression and classification algorithms for three different paralinguistic signal classification tasks. These tasks are quite difficult for humans because the sound information from such signals is difficult to distinguish. Therefore, when machine learning techniques are applied to analyze paralinguistic signals, several different aspects of speech-related information, such as prosody, energy, and cepstral information, are usually considered for feature extraction. However, when the size of the training corpus is not sufficiently large, it is extremely difficult to directly apply machine learning to classify such signals due to their high feature dimensions; this problem is also known as the curse of dimensionality. This paper proposes to address this limitation by means of feature compression. First, we present experimental results obtained by using various compression algorithms to compress signals to eliminate redundancy of the signal features. We observe that compared with the original features, the compressed signal features still provide a comparable ability to distinguish the signals, especially when using a fully connected neural network classifier. Second, we calculate the output distribution of the F1-score for each emotion in the speech emotion recognition problem and show that the fully connected neural network classifier performs more stably than other classical methods. [ABSTRACT FROM AUTHOR]

The aim of this paper is to propose a comparative study between three advanced signal processing methods for the vibratory diagnosis of rotating machines working in industrial conditions. Cyclostationary analysis, empirical mode decomposition (EMD), and complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) are then applied for the detection of mechanical defects of a turbofan machine in the biggest fertilizer company in Algeria. These methods proved their efficiency for the diagnosis of specific defects, like rolling bearing and gear defects in laboratory test rigs, but their application in industrial field remains limited. The application of these methods on vibratory signals measured in low, medium, and high-frequency range allowed determining the efficiency of each method to diagnose the occurrence of different defects manifested in the three considered frequency ranges. The great advantage of the modulation intensity distribution (MID), and its integration (IMID), obtained from the cyclostationary analysis, is proven compared to the envelope spectra performed from the EMD or the CEEMDAN approaches, especially for defects inducing modulation phenomena. Finally, the main result of this paper is that the advanced signal processing tools can be easily applied on signals measured in industrial environment, and can be extended to detect mechanical defects in real running conditions, more real than those simulated on laboratory test rigs. [ABSTRACT FROM AUTHOR]

In recent years, the rapid development of the automotive industry has brought about several environmental and energy issues worldwide. Many countries have established fuel consumption regulations. Among them, fuel consumption regulations based on the curb weight or footprint have been put forward in China and the US. This paper mainly compares the effect of the application of footprint-based and curb weight-based regulations in China. To compare the effect of these two different benchmarks, a Chinese footprint-based fuel consumption regulation is designed based on the principles of the American footprint regulations and the actual conditions of the Chinese passenger car market, and fuel consumption data from 14 enterprises are also used. It is found that regulations help maintain market neutrality if the target value is separated into two curves according to the type of vehicle. Additionally, footprint regulations are more conducive to vehicle lightweighting than curb weight regulations. Finally, policy recommendations are drawn: to maintain market neutrality, there should be two target value curves in the fifth stage of the weight regulation: one for sedans and one for SUVs. Meanwhile, footprint regulation adaptation should be considered in the future to promote vehicle lightweighting in the Chinese market. [ABSTRACT FROM AUTHOR]

Background: Patient-reported outcomes (PROs) refer to any report of the status of a patient's health condition, health behavior, or experience with healthcare directly from the patient, without interpretation of the patient's response by a clinician or any other external party. While many PROs, such as the Pediatric Quality of Life Inventory (PedsQL), were originally administered in paper-and-pencil format, these are now available as electronic versions (ePROs). Although ePROs might well have used the same structure as their paper versions, we developed an alternate ePedsQL incorporating three software functions: 1) a non-forcing non-response alert, 2) a conditional question branch of the School Functioning Scale that only displays for (pre) school children, and 3) a vertical item-by-item display for small-screen devices. This report evaluated the effect of these functions on item non-response rate, survey completion time, and user experience. Methods: All surveys were conducted via the online/computer mode. We compared the dynamic format containing the three functions with the basic format in a randomized comparative study in 2803 children and 6289 caregivers in Japan. Results: We found that the non-response alert lowered the item non-response rate (0.338% to 0.046%, t = − 4.411, p < 0.001 by generalized linear mixed model analysis). The conditional question branch had mixed effects on survey completion time depending on the respondents' age. Surprisingly, respondents rated the vertical question display for handheld devices less legible than the matrix format. Further, multigroup structural equation modelling revealed that the same configuration for both formats showed an acceptable fit (CFI 0.933, RMSEA 0.060, SRMR 0.038) but the errors of observed variables were larger for the dynamic format than the basic format. Conclusions: We confirmed the robustness of the ePedsQL in different formats. The non-response rate of ePedsQL was very low even in the absence of an alert. The branch and item-by-item display were effective but unnecessary for all populations. Our findings further understanding of how humans respond to special software functions and different digital survey formats and provide new insight on how the three tested functions might be most successfully implemented. [ABSTRACT FROM AUTHOR]

Mudstone reservoirs demand accurate information about subsurface lithofacies for field development and production. Normally, quantitative lithofacies modeling is performed using well logs data to identify subsurface lithofacies. Well logs data, recorded from these unconventional mudstone formations, are complex in nature. Therefore, identification of lithofacies, using conventional interpretation techniques, is a challenging task. Several data-driven machine learning models have been proposed in the literature to recognize mudstone lithofacies. Recently, heterogeneous ensemble methods (HEMs) have emerged as robust, more reliable and accurate intelligent techniques for solving pattern recognition problems. In this paper, two HEMs, namely voting and stacking, ensembles have been applied for the quantitative modeling of mudstone lithofacies using Kansas oil-field data. The prediction performance of HEMs is also compared with four state-of-the-art classifiers, namely support vector machine, multilayer perceptron, gradient boosting, and random forest. Moreover, the contribution of each well logs on the prediction performance of classifiers has been analyzed using the Relief algorithm. Further, validation curve and grid search techniques have also been applied to obtain valid search ranges and optimum values for HEM parameters. The comparison of the test results confirms the superiority of stacking ensemble over all the above-mentioned paradigms applied in the paper for lithofacies modeling. This research work is specially designed to evaluate worst- to best-case scenarios in lithofacies modeling. Prediction accuracy of individual facies has also been determined, and maximum overall prediction accuracy is obtained using stacking ensemble. [ABSTRACT FROM AUTHOR]

Background: In order to close the gap between discoveries that could improve health, and widespread impact on routine health care practice, there is a need for greater attention to the factors that influence dissemination and implementation of evidence-based practices. Evidence synthesis projects (e.g., systematic reviews) could contribute to this effort by collecting and synthesizing data relevant to dissemination and implementation. Such an advance would facilitate the spread of high-value, effective, and sustainable interventions.Objective: The objective of this paper is to evaluate the feasibility of extracting factors related to implementation during evidence synthesis in order to enhance the replicability of successes of studies of interventions in health care settings.Design: Drawing on the implementation science literature, we suggest 10 established implementation measures that should be considered when conducting evidence synthesis projects. We describe opportunities to assess these constructs in current literature and illustrate these methods through an example of a systematic review.Subjects: Twenty-nine studies of interventions aimed at improving clinician-patient communication in clinical settings.Key Results: We identified acceptability, adoption, appropriateness, feasibility, fidelity, implementation cost, intervention complexity, penetration, reach, and sustainability as factors that are feasible and appropriate to extract during an evidence synthesis project.Conclusions: To fully understand the potential value of a health care innovation, it is important to consider not only its effectiveness, but also the process, demands, and resource requirements involved in downstream implementation. While there is variation in the degree to which intervention studies currently report implementation factors, there is a growing demand for this information. Abstracting information about these factors may enhance the value of systematic reviews and other evidence synthesis efforts, improving the dissemination and adoption of interventions that are effective, feasible, and sustainable across different contexts. [ABSTRACT FROM AUTHOR]

This paper reports on two studies that used qualitative thematic and quantitative linguistic analysis, respectively, to assess the content and language of the largest ever sample of graded research impact case studies, from the UK Research Excellence Framework 2014 (REF). The paper provides the first empirical evidence across disciplinary main panels of statistically significant linguistic differences between high- versus low-scoring case studies, suggesting that implicit rules linked to written style may have contributed to scores alongside the published criteria on the significance, reach and attribution of impact. High-scoring case studies were more likely to provide specific and high-magnitude articulations of significance and reach than low-scoring cases. High-scoring case studies contained attributional phrases which were more likely to attribute research and/or pathways to impact, and they were written more coherently (containing more explicit causal connections between ideas and more logical connectives) than low-scoring cases. High-scoring case studies appear to have conformed to a distinctive new genre of writing, which was clear and direct, and often simplified in its representation of causality between research and impact, and less likely to contain expressions of uncertainty than typically associated with academic writing. High-scoring case studies in two Main Panels were significantly easier to read than low-scoring cases on the Flesch Reading Ease measure, although both high-scoring and low-scoring cases tended to be of "graduate" reading difficulty. The findings of our work enable impact case study authors to better understand the genre and make content and language choices that communicate their impact as effectively as possible. While directly relevant to the assessment of impact in the UK's Research Excellence Framework, the work also provides insights of relevance to institutions internationally who are designing evaluation frameworks for research impact. [ABSTRACT FROM AUTHOR]

Due to its excellent specific mechanical properties, carbon fibre-reinforced polymer (CFRP) composite is a widely used structural material in the aerospace industry. However, this material is difficult to cut, mainly due to its inhomogeneity and anisotropic features and because of the strong wear effects of its carbon fibres. In the scope of aerospace industrial uses of this material, thousands of holes have to be machined for purposes of assembly. Nevertheless, conventional drilling technology – even if special drilling tools are used – is only moderately able to manufacture good quality holes. Wobble milling is a novel advanced hole-making technology, which has been developed to minimize machining-induced geometrical defects like delamination or uncut fibres. The main objective of the present paper is to compare wobble milling, helical milling and conventional drilling technologies concerning unidirectional CFRPs. In addition, the kinematics of wobble milling technology is discussed in detail. In the scope of this paper, numerous machining experiments were conducted in unidirectional CFRPs: herein the impact of the type of cutting tool and of process parameters on the quality of machined holes are analysed and discussed (diameter of holes, circularity error and characteristics of uncut fibres). During these investigations, experimental data were evaluated with the help of digital image processing (DIP) and with the help of analysis of variance (ANOVA) techniques. Experimental results show that the amount of uncut fibres can significantly be minimized through the application of wobble milling technology. [ABSTRACT FROM AUTHOR]

Environmental impact assessment (EIA) has evolved as an environmental management and sustainability tool. Despite common principles shared by EIA globally, there are considerable variations in EIA processes across countries. In this paper, we reviewed and compared EIA processes of China, Queensland State of Australia and Nepal considering five key steps (selection of consultants, report preparation, public participation, report review and approval, and monitoring and evaluations) of EIA. Our review indicated that the EIA is well recognised in legal instruments in all state and countries under consideration and there are both similarities and differences in key steps of EIA. Monitoring of EIA recommendations and the integration of feedbacks from the past and current practices are important in improving EIA processes. This study also found that there are elements for possible improvement in existing EIA processes by each state and country introducing the best practices from others' EIA system. Some of the practices that Nepal can follow from the EIA processes of Queensland and China are licensing and accreditation of individuals and firms to conduct EIA, establishment of separate monitoring unit within regulating department, development of clear guidelines for approvals and monitoring, and the use of independent third-party auditing in EIA monitoring. The findings of this paper are useful in revising and improving EIA policies, practices and processes in the selected state, countries and elsewhere. [ABSTRACT FROM AUTHOR]

At a high level, data centres are large IT facilities hosting physical machines (servers) that often run a large number of virtual machines (VMs)—but at a lower level, data centres are an intricate collection of interconnected and virtualised computers, connected services, complex service-level agreements. While data centre managers know that reassigning VMs to the servers that would best serve them and also minimise some cost for the company can potentially save a lot of money—the search space is large and constrained, and the decision complicated as they involve different dimensions. This paper consists of a comparative study of heuristics and exact algorithms for the multi-objective machine reassignment problem. Given the common intuition that the problem is too complicated for exact resolutions, all previous works have focused on various (meta)heuristics such as First-Fit, GRASP, NSGA-II or PLS. In this paper, we show that the state-of-art solution to the single objective formulation of the problem (CBLNS) and the classical multi-objective solutions fail to bridge the gap between the number, quality and variety of solutions. Hybrid metaheuristics, on the other hand, have proven to be more effective and efficient to address the problem—but as there has never been any study of an exact resolution, it was difficult to qualify their results. In this paper, we present the most relevant techniques used to address the problem, and we compare them to an exact resolution (ϵ -Constraints). We show that the problem is indeed large and constrained (we ran our algorithm for 30 days on a powerful node of a supercomputer and did not get the final solution for most instances of our problem) but that a metaheuristic (GeNePi) obtains acceptable results: more (+ 188%) solutions than the exact resolution and a little more than half (52%) the hypervolume (measure of quality of the solution set). [ABSTRACT FROM AUTHOR]

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The paper considers the determination of the mass flow rate of a fluid in one working cycle of a positive displacement hybrid reciprocating power machine for three types of slot seals: smooth, stepped, and conic. Based on a theoretical study of the mass flows of fluid flowing from the pumping cavity to the compressor and back, with laminar fluid flow, a comparison of the efficiency of piston seals was carried out. It was found that the value of the ratio of fluid flow in the forward and reverse directions for a conic slot seal is significantly higher than that for smooth and stepped slot seals. This makes it possible to recommend a conic slot seal for use in positive displacement hybrid reciprocating power machines having a high discharge pressure in the compressor section and a low discharge pressure in the pumping section. [ABSTRACT FROM AUTHOR]

Islamic indices encompass different fundamental principles to those held by conventional ones, which directs attention onto comparative financial performance. This paper offers a comprehensive performance comparison between Islamic indices and conventional indices, based on four main markets: worldwide, the US, Europe and Asia–Pacific for the period of 2007 and 2017 through financial ratio comparison and also the CAPM-EGARCH model. The main finding shows that Islamic indices yield higher average returns and lower risks during the 2007–2009 and 2013–2017 periods for all four markets, compared with respective conventional markets. During 2009–2013 period, the comparison proves inconclusive, since Islamic indices demonstrate better performance in European and Asia–Pacific markets, while conventional indices operate at an enhanced level within other markets. Overall, Islamic indices outperformed conventional indices during the global financial crisis period (2007–2009) and the latter post-crisis phase (2013–2017), especially in the European and Asia–Pacific markets. [ABSTRACT FROM AUTHOR]

Purpose: Vortioxetine an anti-depressant FDA-drug recently reported showing better in vitro efficacy against SARS-CoV-2. Methods: In this study, we have synthesized ten new derivatives having alkenes, alkynes, benzyl, aryl, and mixed carbamate at the N-terminal of vortioxetine. Then the binding energy and interactions with the crucial amino acid residues in the binding pocket of main protease (Mpro) of SARS-CoV-2, of reported and ten newly synthesized vortioxetine derivatives (total thirty-one) in comparison with remdesivir are analyzed and presented in this paper. Results: Based on the docking scores predicted by ADV and AD, most vortioxetine derivatives showed better binding efficiency towards Mpro of SARS-CoV-2 in comparison with remdesivir (an EUA approved drug against SARS-CoV-2 Mpro) and vortioxetine. Conclusion: This study shows that some vortioxetine derivatives can be developed into promising drugs for COVID-19 treatment. [ABSTRACT FROM AUTHOR]

In this paper we turn our attention to comparing the policy function obtained by Beck and Wieland (J Econ Dyn Control 26:1359-1377, ) to the one obtained with adaptive control methods. It is an integral part of the optimal learning method used by Beck and Wieland to obtain a policy function that provides the optimal control as a feedback function of the state of the system. However, computing this function is not necessary when doing Monte Carlo experiments with adaptive control methods. Therefore, we have modified our software in order to obtain the policy function for comparison to the BW results. [ABSTRACT FROM AUTHOR]

With the development of Web services, the quantity of services in clusters has increased rapidly, and the time complexity of service clustering becomes higher. To solve this problem, a new construction method of service clusters is proposed based on service space in this paper. The main innovation is the construction of service space. Firstly, a mathematical space is defined. Then, services are abstracted and quantized to the space based on ontology trees. The experiment illustrates that the time complexity of constructing service clusters is decreased. Moreover, the construction of service space and the mapping rules are shown in this paper. A service cluster and its dynamic library are constructed based on service space. The structure, updating mechanism and generation flows of service clusters are modeled by logic Petri nets. Finally, the validity and advantages of proposed methods are illustrated by some experiments and comparative analysis. [ABSTRACT FROM AUTHOR]

Lightweight aluminium alloys have been recognized as key actors in the aerospace industry due to their excellent strength-to-weight ratio. Appropriate formability estimators and deeper knowledge on the fracture behaviour would therefore benefit this preliminary production time. This paper aims to unprecedentedly complete comparative study of multiple promising fracture criteria on the 1.2-mm-thick AA2024-T3 sheet aluminium alloy through reliable practical forming processes to achieve the most faithful understanding of its fracture nature. Four fracture criteria–namely, Hill'48-R-MMC, Hill'48-S-MMC, Hill'48-R-Lou-Huh and Hill'48-S-Lou-Huh–in the form of fracture loci (FLs) are developed by means of numerical optimisation against the measured fracture strains at varying states. The strain data are extracted from the conventional fracture forming limit curve (FFLC), experimentally determined with the help of both standard Nakajima stretching and notched tensile tests. Two industrial forming parts like a classic square cup and an x-cross-shaped cup are employed to verify those four criteria. The criteria are put into service via the element-deletion feature in ABAQUS 2017, by which any element whose damage value reaches a certain limit is removed. In terms of final drawing depth, all four criteria produce satisfactory results; the best one from the Hill'48-R-Lou-Huh square cup has a slight error of 0.3%, whereas the two least acceptable ones from both Hill'48-S-based cross-die samples have an equal error of only 11%. In contrast, all Hill'48-S-based simulated cups have more matching crack appearances than Hill'48-R-based ones do. [ABSTRACT FROM AUTHOR]

Multipliers are the most demanding component of any filter. They not only dominate most of the chip area but also contribute to most of the computational delay. An efficient realization of filter thus requires optimization of the multipliers. In this paper, a high performance block reconfigurable finite impulse response filter structure is presented. Block-based realization improves the overall throughput of the structure. A novel partial-product-based structure is proposed for Multiply and Accumulation operation, instead of traditional multipliers-based structure. Pipelining and parallelism in the structure improves the throughput of the design. The reuse of the partial products reduces the number of adders and increases the speed, thereby reducing the area-delay product (ADP) and energy-per output (EPO), in comparison with the earlier reported structures. The comparative analysis is done with the help of ASIC synthesis results and the results show that the proposed architecture for filter order 16 and block input 8requires 28.91% less ADP and 25.72% less EPO than the earlier reported architecture. [ABSTRACT FROM AUTHOR]

The semantic segmentation of omnidirectional urban driving images is a research topic that has increasingly attracted the attention of researchers, because the use of such images in driving scenes is highly relevant. However, the case of motorized two-wheelers has not been treated yet. Since the dynamics of these vehicles are very different from those of cars, we focus our study on images acquired using a motorcycle. This paper provides a thorough comparative study to show how different deep learning approaches handle omnidirectional images with different representations, including perspective, equirectangular, spherical, and fisheye, and presents the best solution to segment road scene omnidirectional images. We use in this study real perspective images, and synthetic perspective, fisheye and equirectangular images, simulated fisheye images, as well as a test set of real fisheye images. By analyzing both qualitative and quantitative results, the conclusions of this study are multiple, as it helps understand how the networks learn to deal with omnidirectional distortions. Our main findings are that models with planar convolutions give better results than the ones with spherical convolutions, and that models trained on omnidirectional representations transfer better to standard perspective images than vice versa. [ABSTRACT FROM AUTHOR]

Al-Si wrought piston alloys can lack properties due to inefficient grain refining. A novel Al-Nb-B grain refiner was introduced some time ago, but has still not been assessed in industry for wrought alloys. This paper describes the first trial of Al-Ni-B addition and its impact on the full-scale manufacturing, structure, and properties of the AA4032 products extruded with and without billet homogenization. It is shown that Nb-B inoculation gives opportunities not only to have a refined as-cast structure but also a more homogenous distribution of the solute. In contrast, homogenization drives nucleation and coarsening of the Mg2Si phase that is retained during further extrusion and heat treatment also affecting the precipitation and properties. It was observed that non-homogenized specimens perform better during machining and tensile testing compared to homogenized specimens. The results are supported by electron microscopy investigations of microstructure formation during different steps in downstream processing. [ABSTRACT FROM AUTHOR]

When a decision-maker prefers to compare different alternatives in pairs to handle real situations, there are many different expression styles that can be used. Two representative expression styles are the probabilistic linguistic preference relation (PLPR), which originates from the fuzzy linguistic approach and the distributed preference relation (DPR), which originates from the evidential reasoning approach. Although these two expression styles look quite similar, their meanings, operations, and relevant decision making processes are significantly different. This presents the decision-maker with the challenge of selecting either PLPRs or DPRs in different real cases. To address this issue, this paper provides a detailed analysis of the similarities and differences between PLPRs and DPRs. The analysis is conducted from five perspectives, including modeling of decision making problems, handling of uncertainty, consistency between preference relations, information aggregation, and elicitation process. An engineer selection problem for an automobile manufacturing enterprise is investigated to demonstrate how to appropriately select PLPRs or DPRs to model and analyze decision making problems in real situations with consideration for the preferences of decision-makers. [ABSTRACT FROM AUTHOR]

In this paper, a multiproduct multiperiod capacitated production system that has been organized as a flow shop is considered. The main novelty of the paper is proposing a more efficient mathematical model for the problem of integrating lot sizing and scheduling with sequence-dependent setups. In comparison to the former model, because of fewer continuous and binary decision variables and constraints in the proposed model, this model is very easier to solve. Comparison between two models proves the superiority of the proposed model. Two mixed integer programming-based approaches with rolling horizon framework have been used to solve this model. To evaluate the performance of the proposed model and solution method, problems of different scales have been studied. The used algorithms search the solution space for both lot-sizing and scheduling problems and find a combination of production planning and scheduling that is feasible and close to optimum. [ABSTRACT FROM AUTHOR]

The paper deals with a simulation study of influence of conductive material of the rotor squirrel cage on output characteristics of single-phase self-excited induction generators. For calculation of performance characteristics, two-dimensional field-circuit model of the single-phase induction generator was applied. A comparison of self-excitation waveforms of terminal voltage and load characteristics of the generators for rotor bars of the same shape, made of aluminium and copper, was presented. The obtained simulation results by the field-circuit model and analysis may be utilized for designing new constructions of single-phase self-excited induction generators as well for modifying construction of the generators designing on the base of general-purpose single-phase induction motors. [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive analysis of the effect of speaking rate on frame classification accuracy. Different speaking rates may affect the performance of the automatic speech recognition system yielding poor recognition accuracy. A model trained on a normal speaking rate is better able to recognize speech at a normal pace but fails to achieve similar performance when tested on slow or fast speaking rates. Our recent study has shown that a drop of almost ten percentage points in the classification accuracy is observed when a deep feed-forward network is trained on the normal speaking rate and evaluated on slow and fast speaking rates. In this paper, we extend our work to convolutional neural networks (CNN) to see if this model can reduce the accuracy gap between different speaking rates. Filter bank energies (FBE) and Mel frequency cepstral coefficients are evaluated on multiple configurations of the CNN where the networks are trained on normal speaking rate and evaluated on slow and fast speaking rates. The results are compared to those obtained by a deep neural network. A breakdown of phoneme-level classification results and the confusion between vowels and consonants is also presented. The experiments show that the CNN architecture when used with FBE features performs better on both slow and fast speaking rates. An improvement of nearly 2% in case of fast and 3% in case of slow speaking rates is observed. [ABSTRACT FROM AUTHOR]

This paper investigates the performance of ultrasonic-assisted drilling (UAD) in machining of Ti-6Al-4V/Al2024-T351 laminated material by using DEFORM-3D finite element method. The effectiveness of two key parameters, frequency and spindle speed, is discussed. The purpose is to explore the effect of UAD on machining performance, to compare it with conventional drilling (CD) and to prove that the UAD technique could achieve better hole quality. To be more specific, the following aspects are taken into account: chip morphology, layer delamination, thrust force, temperature change, and effective stress. The result shows that UAD can produce fragile chips, smaller layer delamination, lower thrust force, larger maximum temperature, and lower effective stress. Both frequency and spindle speed have influence in their own way on machining process. [ABSTRACT FROM AUTHOR]

Manufacturing industry plays a very significant role in the economic functioning of any country. In recent times, reverse engineering (RE) has become an integral part of manufacturing set-up owing to its numerous applications. The quality of RE product primarily depends on the quality of digitization i.e., part measurement. There is a diverse range of digitization devices which can be employed in RE. These machines have variability in terms of cost, accuracy, ease of use, accessibility, scanning time, etc. Therefore, the decision regarding the selection of a suitable device becomes important in a particular RE application. The decisions taken in the planning stage for RE can have a long lasting impact on the functionality, quality and the economics of components to be used by manufacturing industries. To accomplish the selection procedure, a comparative study of three digitization techniques has been carried out. The determination of an appropriate digitization system is basically a multi-criteria decision making (MCDM) problem. MCDM techniques are yet to be applied in the selection of digitization systems for RE. MCDM is one of the most widely used decision methodologies in business and engineering spheres. The aim of this work is to describe various MCDM methods in the selection of digitization systems for RE. This paper intends to employ combinations between different MCDM methods such as group eigenvalue method (GEM), analytic hierarchy process (AHP), entropy method, elimination and choice expressing reality (ELECTRE), technique for order of preference by similarity to ideal solution (TOPSIS) and simple additive weighing (SAW) method. In this work, GEM, AHP, Entropy methods has been used to elicit weights of various selection criteria, while TOPSIS, ELECTRE and SAW have been applied to rank the alternatives. A comparative analysis has also been performed to determine the efficacies of different approaches. The conclusion of the paper reveals the best digitization system as well as the characteristics of different MCDM methods and their suitability in RE application. [ABSTRACT FROM AUTHOR]

Mechanistic force models allow an estimation of the force components in cutting technology. This is essential for an accurate simulation of the force, an analysis of the tool load, or a model-based predictive force control. The model coefficients do not only depend on the material and the tool but also on the engagement condition. This requires an online identification of those coefficients. To determine those coefficients, this paper uses curve fitting based on the instantaneous uncut chip thickness, a method that has only recently gained momentum in milling. This work applies this technique to the well-established, nonlinear Kienzle force model. The paper reviews a broad range of nonlinear, derivative-free optimization algorithms for this least-squares curve-fitting problem evaluating accuracy and runtime. The evaluation is conducted on 121experiments with distinct process conditions resulting in a statistically verified conclusion. The results indicate that in spite of a heterogeneous optimization space, local constrained algorithms are most suited for model identification. [ABSTRACT FROM AUTHOR]

A closed-loop supply chain (CLSC) network is composed of both forward and reverse flows. An essential issue to be considered in designing any supply chain network is determination of number and locations of facilities in each layer of the network. Such a problem is a challenging job, since it contains sub-problems which are proven to be nondeterministic polynomial time complete. This paper proposes a CLSC distribution network design problem in which reverse flows are imported into forward model proposed by Selim and Ozkarahan (Int J Adv Manuf Technol 36:401-418, ). Such a model is considered assuming forward covering (model I) and backward covering (model II) objectives, and then results are compared against the model incorporating covering of both forward and backward networks (model III). Our aim is to accentuate on the role of considering backward parameters in design of a CLSC network and to show how results differ from considering sub-problems separately. To model and solve the problem, a fuzzy goal programming approach is developed for network design in an interactive manner between decision maker and the model. To validate the presented model and the proposed solution approach, a test problem is presented and comparison of results is made using this problem. The results show that the proposed model can solve the CLSC problems in a manageable time. Moreover, outputs of the three models differ significantly. Therefore, the role of incorporating backward flows into the network design problem has been shown using our experiments. [ABSTRACT FROM AUTHOR]

Introduction: Pulmonary metastasectomy for colorectal cancer is a commonly performed and well-established practice of ∼50 years standing. However, there have been no controlled studies, randomised or otherwise. We sought to investigate the evidence base that has been used in establishing its status as a standard of care.Methods: Among 51 papers used in a recent systematic review and quantitative synthesis, a citation network analysis was performed. A total of 344 publications (the 51 index papers and a further 293 cited in them) constitute the citation network.Results: The pattern of citation is that of a citation cascade. Specific analyses show the frequent use of historical or landmark papers, which add authority. Papers expressing an opposing viewpoint are rarely cited.Conclusions: The citation network for this common and well-established practice provides an example of selective citation. This pattern of citation tends to escalate belief in a clinical practice even when it lacks a high-quality evidence base and may create an impression of more authority than is warranted. [ABSTRACT FROM AUTHOR]

Background: Although electronic prescribing (e-prescribing) holds promise for preventing prescription errors in the ambulatory setting, research on its effectiveness is inconclusive.Objective: To assess the impact of a stand-alone e-prescribing system on the rates and types of ambulatory prescribing errors.Design, Participants: Prospective, non-randomized study using pre-post design of 15 providers who adopted e-prescribing with concurrent controls of 15 paper-based providers from September 2005 through June 2007.Intervention: Use of a commercial, stand-alone e-prescribing system with clinical decision support including dosing recommendations and checks for drug-allergy interactions, drug-drug interactions, and duplicate therapies.Main Measures: Prescribing errors were identified by a standardized prescription and chart review.Key Results: We analyzed 3684 paper-based prescriptions at baseline and 3848 paper-based and electronic prescriptions at one year of follow-up. For e-prescribing adopters, error rates decreased nearly sevenfold, from 42.5 per 100 prescriptions (95% confidence interval (CI), 36.7-49.3) at baseline to 6.6 per 100 prescriptions (95% CI, 5.1-8.3) one year after adoption (p < 0.001). For non-adopters, error rates remained high at 37.3 per 100 prescriptions (95% CI, 27.6-50.2) at baseline and 38.4 per 100 prescriptions (95% CI, 27.4-53.9) at one year (p = 0.54). At one year, the error rate for e-prescribing adopters was significantly lower than for non-adopters (p < 0.001). Illegibility errors were very high at baseline and were completely eliminated by e-prescribing (87.6 per 100 prescriptions at baseline for e-prescribing adopters, 0 at one year).Conclusions: Prescribing errors may occur much more frequently in community-based practices than previously reported. Our preliminary findings suggest that stand-alone e-prescribing with clinical decision support may significantly improve ambulatory medication safety.Trial Registration: ClinicalTrials.gov, Taconic Health Information Network and Community (THINC), NCT00225563, http://clinicaltrials.gov/ct2/show/NCT00225563?term=Kaushal&rank=6 . [ABSTRACT FROM AUTHOR]

This paper examines the extent of and the mechanisms behind the penalty to motherhood in six European countries. Each country provides different levels of support for maternal employment allowing us to determine institutional effects on labour market outcome. While mothers tend to earn less than non-mothers, the penalty to motherhood is considerably lower in countries with policy support for working mothers. The paper establishes the United Kingdom and West Germany to have the least policy support for working mothers as well as the largest penalties to motherhood. [ABSTRACT FROM AUTHOR]

Nanotechnology has been proposed as the next general purpose technology and engine for growth for the 21th century. Increasing public R&D investments are foremost reflected in the growth of scientific publications, while nanotechnology still is in an uncertain phase of development with various directions of commercialization pending. This paper focuses on the challenges, modes and outcomes of nanotechnology as an emerging science-based field in Finland. The paper contributes by interrogating how challenges and modes of nanotechnology transfer differ across universities and companies and determine outcomes broadly defined. It uses survey data covering university and company researchers in the Finnish nanotechnology community. The results show significant differences in the perceptions of researchers across these organisations, and highlight specific challenges and modes as determinants of outcomes. The specificities of nanotechnology are also assessed. [ABSTRACT FROM AUTHOR]

As ongoing research efforts contribute to elucidating the consequences of climate change as well as adaptation and mitigation options, aligning the current research knowledge with stakeholder opinions and perceptions remains critical for adopting effective climate change policies. This paper utilizes an interactive survey to (1) address the aforementioned gap in studies involving three groups of stakeholders and opinion makers and (2) perform a comparative primary study of the climate change assumptions, risk perceptions, policy preferences, observations, and knowledge of Czech farmers, governmental policy-makers and researchers. This study shows that the stakeholder groups agree that the climate is clearly changing, attribute this change mostly to man-made causes and expect the negative effects to either prevail or be unevenly geographically distributed. The large majority of all three groups consider unmitigated climate change a major threat even by 2050 and agree that preparing in advance is the best sectoral strategy. Importantly, while investment in adaptation measures is considered the most efficient tool for accelerating the implementation of adaptation measures, the CAP and EU rules (as valid in 2016) are believed to hinder such measures. The results of this study have ramifications for the wider region of Central Europe. [ABSTRACT FROM AUTHOR]

VET (vocational education and training) is a highly complex, multidimensional worldwide phenomenon with diverse structures. Additionally, very different actors define the functions of a national (or even a regional) VET system. The paper contributes to a better understanding of the policy frameworks and current states of such systems. Therefore, we focus on selected VET systems in order to understand their specifics and thus, their market conditions. A qualitative approach is used to answer the research question regarding which conditions create or support market-based opportunities for the provision of commercial vocational training services. We find that the liberalism and deregulation of the VET sectors, as well as the marketisation of VET practices, lead to incentives to internationalise VET offers. Thinking in terms of skills, the kind of education system does not play a role. This is the case in liberal market-driven VET approaches (here, the UK, the USA and Australia) and is mirrored in the micro-analysis categories of curricula, learning location, content, and learning process. [ABSTRACT FROM AUTHOR]

In this paper, a junction-less charge plasma (CP) double-drift region (DDR) impact avalanche transit time (IMPATT) diode structure has been proposed for realizing a high-power and efficient terahertz (THz) source. A comprehensive two-dimensional (2-D) self-consistent quantum drift-diffusion (SCQDD) model has been developed by the author to study the static and THz performance of 4H-SiC based CP-DDR source designed to operate at 1.0 THz. Comparative studies on the DC and THz performance of the proposed device and conventionally doped vertical DDR IMPATT device reveal that the proposed CP-DDR can be the potential alternative of the conventional DDRs (C-DDRs), especially at the THz regime. The proposed THz CP-DDR source can be exclusively preferable over its conventional counterparts due to its easier and less complicated fabrication steps as well as equivalent performance capability with respect to the THz C-DDR sources. [ABSTRACT FROM AUTHOR]

Toe cutting of hillslopes that are intended for the expansion of the transportation networks across the hilly regions need to follow an engineered basis to avert catastrophic failures. The commonly utilized deterministic Limit Equilibrium Method (LEM) does not incorporate the uncertainties in geotechnical properties and might exhibit inappropriate or erroneous consequences of toe excavation. In order to highlight the chances of toe-excavation induced slope failures, this paper reports the outcomes of the probabilistic stability analysis while considering one-dimensional spatial variability of soil shear strength parameters. The importance of such probabilistic analyses is established by finding that 79% of the toe-excavated slopes, which are judged safe from deterministic analysis, actually exhibit high probabilities of failure. Further, the influences of coefficient of variation (CoV) and the correlation between the shear strength parameters are also highlighted. The probability of failure of the cut slopes is found to be decreased by around 70% when the correlation coefficient of the shear strength parameters decreased from +0.5 to −0.5. The permissible width of toe excavation is found to be governed by the indicators of spatial variability. It is revealed that for a CoV value of 0.2 and 0.3, a maximum horizontal extent of 7 m and 5 m can be excavated without leading to slope failure for a dimensionless correlation length up to 0.2 and 0.1, respectively. [ABSTRACT FROM AUTHOR]

Background: Health care costs of migraine constitute a major issue in health economics. Several publications analyzed health care costs for adult migraine patients, based on questionnaires or secondary (health insurance) data. Although migraine often starts already in primary school age, data on migraine related costs in children is scarce. In this paper we aimed to assess the migraine-related health care costs in 6 to 11 year old children in Germany. Methods: Using claims data of a large German health insurer (BARMER), overall annual health care costs of 6 to 11 year old children with a diagnosis of migraine in 2017 (n = 2597) were compared to a control group of 6 to 11 year old children without a headache diagnosis between 2013 and 2017 (n = 306,926). The association of migraine and costs was modeled by generalized linear regression (Gamma regression) with adjustment for sex, age and comorbidities. Results: Children with migraine caused considerably higher annual per capita health care costs than children without a headache diagnosis (migraine group: € 1018, control group: € 618). Excess costs directly related to migraine amounted to € 115. The remaining excess costs were related to comorbidities, which were more frequent in the migraine group. Mental and behavioural disorders constituted the most expensive comorbidity, accounting for € 105 of the € 400 annual excess costs in the migraine group. Conclusion: 6 to 11 year old children with a migraine diagnosis cause significant direct and comorbidity related excess costs in the German health care system. [ABSTRACT FROM AUTHOR]

The present paper focuses on the suppression of background noise in speech signal by utilizing a powerful heuristic optimization algorithm called Bat algorithm (BA) for adaptive filtering in dual channel enhancement systems. Bat algorithm is a recently developed population based meta heuristic approach which is inspired by the hunting behavior of the bats. It is developed by Yang (). As a novel feature Bat algorithm is based on the echo location behavior of micro bats. BA uses the frequency tuning technique to increase the diversity of the solutions in the population, while at the same time it uses the automatic zooming and tries to balance the exploration and exploitation. A few studies have been carried out on the use of heuristics for ANC in speech enhancement by using standard particle swarm optimization (SPSO) and some of its variants till 2010. In order to extend these heuristic approaches to speech, accelerated particle swarm optimization (APSO) based enhancement approach has been proposed (Prajna et al. in Int J Speech Technol 17(4):341-351, ; Prajna et al. in IJISA 6(4):1-10, , doi:; Prajna et al. in IEEE international conference on communications and signal processing (ICCSP), April 2014, pp 1457-1461, , doi:). To overcome the problem of poor exploitation ability of APSO, another approach is proposed based on gravitational search algorithm (GSA) (Prajna et al. , , ). To combine both the abilities of PSO and GSA algorithms, Hybrid PSOGSA algorithm is also proposed to ANC (Prajna et al. , , ). To further improve the efficiency of adaptive filtering in ANC, by providing a dynamic balance between exploration and exploitation, BA is proposed to speech enhancement. This paper intends to present the Bat algorithm as an improved approach to ANC in speech enhancement when compared with that of SPSO, APSO, GSA and Hybrid PSOGSA based speech enhancement algorithms. The performance of all the algorithms is evaluated by computing four objective measures SNRI, PESQ, FAI and WSS, in two real world noise conditions Babble and Factory, at three different input SNR levels set at −10, 0 and 5 dB. Simulation results prove that BA is the most successful algorithm of all the algorithms studied in this work, to suppress the background noise more effectively. [ABSTRACT FROM AUTHOR]

This paper offers a cross-country and cross-disciplinary analysis of the development of open access publishing from 2000 to 2019. Through an analysis of seven world regions and nine scholarly fields, we found that, while the overall share of open access journals has increased significantly over the last two decades, there are important differences across both the analyzed world regions and disciplines. We also found that, with the exception of neuroscience, the proportion of open access journals is considerably lower among the journals ranked in the Q1 quartile of Scopus than in the general field. We also offer a model that explains the development of open access publishing trends on different disciplinary and geographical levels. [ABSTRACT FROM AUTHOR]

Multiple cracks would damage the strength and decrease the service life of structural components due to crack interaction compared with a single crack. This paper focused on the interaction of double cracks under cyclic fatigue loads. A combined investigation method involving tensile experiments, fatigue tests and numerical simulation was presented for exploring the crack interaction mechanism. The results indicated that the larger the aspect ratio was, the faster the crack growth rate became. Then, the interaction could increase the driving force of crack growth further to repress crack growth rate. It was also shown that the crack interaction effect could accelerate the growth rate along the depth direction as the fatigue process continued, leading to the transformation of maximum SIF value position, especially for the cracks with a large aspect ratio (c/a > 1). This suggested that the crack shape would experience a gradual transition from semi-elliptic to semi-circular. [ABSTRACT FROM AUTHOR]

This paper presents a comparative computational analysis of the penetration of shaped charges with copper liners in the form of a cone of progressive thickness with a cone angle of 60°, a hemisphere of constant thickness, and a hemisphere and a semi-ellipsoid of degressive (decreasing from apex to base) thickness. The polar semi-axis of the semi-ellipsoidal liner slightly exceeded the equatorial semi-axis. The parameters of the generated shaped-charge jets were determined by numerical simulation within the framework of a two-dimensional axisymmetric problem of continuum mechanics, and the depth of their penetration into a steel target was determined using an engineering technique that takes into account the influence of the manufacturing precision of the charges. The parameters of the liners of degressive thickness were selected so that the tip velocity of the jets formed from them was close to the velocity provided by the conical liner. In this case, the penetration of the shaped charge with a hemispherical liner of degressive thickness was significantly lower than that of the charge with a conical liner, and the latter, in turn, was slightly inferior in the maximum depth of penetration to the charge with a semi-ellipsoidal liner. The physical reasons of the results are discussed. [ABSTRACT FROM AUTHOR]

Background: Cluster headache is an excruciating disorder with no cure. Greater occipital nerve blockades can transiently suppress attacks in approximately 50% of patients, however, its mechanism of action remains uncertain, and there are no reliable predictors of treatment response. To address this, we investigated the effect of occipital nerve blockade on regional cerebral blood flow (rCBF), an index of brain activity, and differences between treatment responders and non-responders. Finally, we compared baseline perfusion maps from patients to a matched group of healthy controls. Methods: 21 male, treatment-naive patients were recruited while in a cluster headache bout. During a pain-free phase between headaches, patients underwent pseudo-continuous arterial spin labelled MRI assessments to provide quantitative indices of rCBF. MRIs were performed prior to and 7-to-21 days following treatment. Patients also recorded the frequency of their headache attacks in a daily paper diary. Neuropsychological assessment including anxiety, depression and quality of life measures was performed in a first, scanning free session for each patient. Results: Following treatment, patients demonstrated relative rCBF reductions in posterior temporal gyrus, cerebellum and caudate, and rCBF increases in occipital cortex. Responders demonstrated relative rCBF increases, compared to non-responders, in medial prefrontal cortex and lateral occipital cortex at baseline, but relative reductions in cingulate and middle temporal cortices. rCBF was increased in patients compared to healthy controls in cerebellum and hippocampus, but reduced in orbitofrontal cortex, insula and middle temporal gyrus. Conclusions: We provide new mechanistic insights regarding the aetiology of cluster headache, the mechanisms of action of occipital nerve blockades and potential predictors of treatment response. Future investigation should determine whether observed effects are reproducible and extend to other headache disorders. [ABSTRACT FROM AUTHOR]

The generated torque ripples from the BLDC motor is the main issue that affects the drive performance of the BLDC drive system. In this paper, a new switching technique to minimize the torque ripples due to current commutation is proposed. The presented scheme has been implemented using a commercial and low-cost mid-range PIC microcontroller to generate the modified pulse width modulation (PWM) control signals. An analysis of phase current during commutation time is carried out. Experimental results verify the effectiveness of proposed method. Results had shown a smoother output torque and current produced in comparison with that using conventional PWM control technique with an average of 50 % reduction in the generated torque ripples. [ABSTRACT FROM AUTHOR]

This paper presents a solution technique for optimal power flow (OPF) with valve-point effect and prohibited operating zones of power systems using backtracking search algorithm (BSA). BSA is a new population-based evolutionary algorithm. The most important property of the algorithm is not over precision to initial of value, unlike many other heuristic algorithms. The proposed algorithm having four different cases is tested on IEEE-30 bus test system. The results of BSA are compared to those reported in literature. Thus, its validity for so applications in this area is proved. In this paper, OPF problem of power systems is solved by BSA for the first time. [ABSTRACT FROM AUTHOR]

A dimensionless governing equation of clamped square plates was obtained by introducing dimensional analysis method to the basic governing equations of plates. The dimensionless governing equation includes three different influence aspects on structural dynamic response: the geometry of the structure, the dynamic resistance ability of material and the ratio of dynamic loads to the resistance ability of material. The dimensionless governing equation was applied to the dynamic response study of plates under blast loading, and a new dimensionless number was suggested for clamped square plates under explosion loads. The suggested dimensionless number has clear physical meaning, and the parameters included in the dimensionless number are easy to get. The dimensionless number suggested in this paper was applied to analysis the experimental data of clamped square plates under blast loading. Meanwhile, comparative analysis was proceeded which indicated the dimensionless number suggested in this paper can be effectively used to predict the dynamic response. The results showed the deflection-thickness ratio is in direct proportion to the dimensionless damage number. An empirical expression was obtained which can be used to the prediction of dynamic response of similar clamped plate under different blast loading condition. [ABSTRACT FROM AUTHOR]